Science, Faculty of
Chemistry, Department of
DSpace
UBCV
Tsai, Hsin-Yun
Doctor of Philosophy - PhD
University of British Columbia
Förster resonance energy transfer (FRET) is widely used for developing fluorescent probes for bioanalysis and imaging. Typically, multiplexed sensing with FRET involves the deployment of multiple probes. In contrast, concentric FRET (cFRET) is a design motif that enables multiplexed sensing with a single probe. Prior to this thesis, cFRET probes had only been developed around metal chalcogenide quantum dots (QDs), which may limit the scope of biological applications. This thesis focuses on expanding the materials palette of cFRET, with the goal of exploring and evaluating new capabilities and enhancing its suitability for more diverse applications. To avoid metal chalcogenide QDs, an alternative cFRET probe was developed using poly(amidoamine) dendrimers labelled with a luminescent terbium complex (Tb). This material was functionalized with three types of dye-labelled oligonucleotides to establish a network of FRET pathways. The new cFRET probes were characterized, and a time-gated multiplexed assay for DNA targets was demonstrated. The time-gating oﬀered also enabled the rejection of background autoﬂuorescence from serum. A derivative FRET probe was compatible with a smartphone-based time-gated imaging device, suggesting potential applications in point-of-care diagnostics. Silicon QDs, also called silicon nanocrystals (SiNCs), are another potential alternative to metal chalcogenide QDs. The size and PL properties of SiNCs were characterized via spectroelectrophoresis and time-resolved and time-gated spectroscopies. SiNCs were then paired as FRET donors with a series of dark quenchers or a fluorescent dye for systematically studying energy transfer. The polydispersity of the SiNCs and resulting heterogeneity of PL properties made these materials non-ideal for cFRET. Lastly, metal chalcogenide QD-based cFRET probes were structurally integrated with a hydrogel toward sensing cell-secreted protease activity. The hydrogel mimics the extracellular matrix to provide a more physiological-like microenvironment for three-dimensional cell culture. The PL of the QD-based cFRET probes was characterized and compared between bulk solution and hydrogel environments. As an initial proof of concept, QD-based FRET probes were integrated with hydrogel and used to measure the activity of a model protease that diffused into the hydrogel. Overall, this thesis advances the concept of cFRET for bioanalysis and informs future research in this area.
DEVELOPMENT AND CHARACTERIZATION OF PHOTOLUMINESCENT MATERIALS TOWARDS APPLICATIONS OF CONCENTRIC FӦRSTER RESONANCE ENERGY TRANSFER PROBES IN BIOANALYSIS by Hsin-Yun Tsai A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Chemistry) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) June 2023 © Hsin-Yun Tsai, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Development and Characterization of Photoluminescent Materials Towards Applications of Concentric Fӧrster Resonance Energy Transfer Probes in Bioanalysis submitted by Hsin-Yun Tsai in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Chemistry Examining Committee: W. Russ Algar, Associate Professor, Chemistry, UBC Supervisor Jayachandran Kizhakkedathu, Professor, Pathology and Laboratory Medicine, UBC Supervisory Committee Member Michael Wolf, Professor, Chemistry, UBC University Examiner Urs Hafeli, Professor, Pharmaceutical Sciences, UBC University Examiner Additional Supervisory Committee Members: Roman Krems, Professor, Chemistry, UBC Supervisory Committee Member Karen Cheung, Professor, Electrical and Computer Engineering, UBC Supervisory Committee Member iii Abstract Förster resonance energy transfer (FRET) is widely used for developing fluorescent probes for bioanalysis and imaging. Typically, multiplexed sensing with FRET involves the deployment of multiple probes. In contrast, concentric FRET (cFRET) is a design motif that enables multiplexed sensing with a single probe. Prior to this thesis, cFRET probes had only been developed around metal chalcogenide quantum dots (QDs), which may limit the scope of biological applications. This thesis focuses on expanding the materials palette of cFRET, with the goal of exploring and evaluating new capabilities and enhancing its suitability for more diverse applications. To avoid metal chalcogenide QDs, an alternative cFRET probe was developed using poly(amidoamine) dendrimers labelled with a luminescent terbium complex (Tb). This material was functionalized with three types of dye-labelled oligonucleotides to establish a network of FRET pathways. The new cFRET probes were characterized, and a time-gated multiplexed assay for DNA targets was demonstrated. The time-gating offered also enabled the rejection of background autofluorescence from serum. A derivative FRET probe was compatible with a smartphone-based time-gated imaging device, suggesting potential applications in point-of-care diagnostics. Silicon QDs, also called silicon nanocrystals (SiNCs), are another potential alternative to metal chalcogenide QDs. The size and PL properties of SiNCs were characterized via spectroelectrophoresis and time-resolved and time-gated spectroscopies. SiNCs were then paired as FRET donors with a series of dark quenchers or a fluorescent dye for systematically studying iv energy transfer. The polydispersity of the SiNCs and resulting heterogeneity of PL properties made these materials non-ideal for cFRET. Lastly, metal chalcogenide QD-based cFRET probes were structurally integrated with a hydrogel toward sensing cell-secreted protease activity. The hydrogel mimics the extracellular matrix to provide a more physiological-like microenvironment for three-dimensional cell culture. The PL of the QD-based cFRET probes was characterized and compared between bulk solution and hydrogel environments. As an initial proof of concept, QD-based FRET probes were integrated with hydrogel and used to measure the activity of a model protease that diffused into the hydrogel. Overall, this thesis advances the concept of cFRET for bioanalysis and informs future research in this area. v Lay Summary Photoluminescent materials, which give emit light of one colour when illuminated with light of a different colour, are widely used as probes for biological studies. The norm for one probe is to detect only one biomolecular target, such that multiple probes are required to detect multiple targets. A recent development, called “concentric FRET,” is able to detect multiple targets, at the same time, as a single probe design; however, only one type of photoluminescent material has been used for concentric FRET probes to date. In this thesis, different photoluminescent materials and non-photoluminescent materials are explored toward developing new types of concentric FRET probes. The results show that concentric FRET beyond its conventional photoluminescent material is possible, that concentric FRET probes can be integrated with structural materials useful for growing cells, and that different materials have different advantages and disadvantages for concentric FRET. vi Preface All of the studies in this thesis were conducted under the supervision of Prof. W. Russ Algar, who contributed to the project conceptions, experiment designs, data analysis, interpretations and discussion of results, and manuscript writing in a manner consistent with his supervisory role as a principal investigator. Any other contributions and assistance from collaborators and colleagues are mentioned below. Chapter 1 includes adaptions from two published and unpublished works. Sections 1.2.3.2 and 1.4 were reproduced from Algar, W. R.; Massey, M.; Rees, K.; Higgins, R.; Krause, K. D.; Darwish, G. H.; Peveler, W. J.; Xiao, Z.; Tasi, H.-Y.; Gupta, R.; Lix, K.; Tran, M. V.; Kim, H., Photoluminescent Nanoparticles for Chemical and Biological Analysis and Imaging. Chem. Rev. 2021, 121, 9243−9358, with permission from the American Chemical Society. The manuscript was co-written by all the authors with input and final editing from Prof. W. R. Algar. This thesis only includes the sections that I directly contributed to the review article. Sections 1.3.3 to 1.3.6 were adapted from Tsai, H.-Y.; Kim, H.; Massey, M.; Krause, K. D.; Algar, W. R., Concentric FRET: a Review of the Emerging Concept, Theory, and Applications. Methods Appl. Fluoresc. 2019, 7, 042001, with permission from IOPscience. The manuscript was co-written by all the authors with input and final editing from Prof. W. R. Algar. Sections 1.3.3 and 1.3.5 were originally drafted by Prof. W. R. Algar with input and editing by me. Sections 1.3.4 and 1.36 were originally written by me with input and final editing from Prof. W. R. Algar. The rest of sections are unpublished work. vii Chapter 2 is an adaption of published work. The text was reproduced from Tsai, H.-Y.; Algar, W. R., A Dendrimer-Based Time-Gated Concentric FRET Configuration for Multiplexed Sensing. ACS Nano 2022, 16, 8150−8160, with permission from the American Chemical Society. Prof. W. R. Algar proposed the concept. I designed and executed the experiments, analyzed the data, and wrote the manuscript with input and final editing from Prof. W. R. Algar. Chapter 3 includes both published and unpublished work. An adaption of the text was reproduced from Tsai, H.-Y.; Algar, W. R., A Dendrimer-Based Time-Gated Concentric FRET Configuration for Multiplexed Sensing. ACS Nano 2022, 16, 8150−8160, with permission from the American Chemical Society. Prof. W. R. Algar proposed the concept. Sahil S. Kanani and Daina V. Baker tutored and assisted in MATLAB coding. Section 3.2.4 is currently unpublished work that is a manuscript in preparation, where the data was contributed from Sahil S. Kanani, where I provided the dendrimer material for the experiments. The text in this section and corresponding experimental procedures were co-written by Sahil S. Kanani and I, and Prof. W. R. Algar provided input and final editing. Otherwise, I designed and executed the experiments, analyzed the data, and wrote the manuscript with input and final editing from Prof. W. R. Algar. Chapter 4 includes unpublished work that is a manuscript in preparation. Prof. W. R. Algar proposed the concept. Prof. Jonathan G. C. Veinot, Christopher Jay Robidillo, Ziqi Li, Gunwant K. Matharu, Kevin O’Connor, I Teng Cheong, and Chuyi Ni provide silicon nanocrystals and TEM images. Otherwise, I designed and executed the experiments, analyzed the data, and wrote the text with input and final editing from Prof. W. R. Algar. viii Chapter 5 includes unpublished work. Prof. W. R. Algar proposed the concept. Tiffany Jeen assisted with measurement of 1H NMR of 4ARM-PEG-NB. I designed and executed the experiments, analyzed the data, and wrote the text with input and final editing from Prof. W. R. Algar. ix Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ................................................................................................................................ v Preface ........................................................................................................................................... vi Table of Contents ......................................................................................................................... ix List of Tables ............................................................................................................................. xvii List of Figures ........................................................................................................................... xviii List of Abbreviations ................................................................................................................ xxx Acknowledgements ................................................................................................................ xxxiv Chapter 1: Introduction ............................................................................................................... 1 1.1 Fluorescence and phosphorescence .................................................................................. 1 1.1.1 Perrin−Jablonski diagram .......................................................................................... 2 1.1.2 Absorption spectra ..................................................................................................... 4 1.1.3 Emission spectra ........................................................................................................ 6 1.1.4 Quantum yield and lifetime ....................................................................................... 7 1.1.5 Steady-state and time-resolved measurement ............................................................ 9 1.2 Fluorescent and luminescent materials ........................................................................... 12 1.2.1 Conventional fluorescent dyes ................................................................................. 13 1.2.2 Lanthanide complexes ............................................................................................. 14 1.2.3 Quantum dots ........................................................................................................... 17 1.2.3.1 II-VI QDs .......................................................................................................... 18 1.2.3.2 IV QDs .............................................................................................................. 20 1.3 FRET and concentric FRET ........................................................................................... 23 x 1.3.1 FRET theory ............................................................................................................ 23 1.3.2 Measurement of FRET efficiency ........................................................................... 28 1.3.3 Concentric Förster resonance energy transfer ......................................................... 29 1.3.4 Advantages of cFRET ............................................................................................. 33 1.3.5 Requirements for cFRET ......................................................................................... 35 1.3.6 Characterization and analysis of cFRET ................................................................. 39 1.4 Dendrimers ..................................................................................................................... 43 1.5 Hydrogels ........................................................................................................................ 45 1.6 Overview and contributions of this thesis ...................................................................... 47 Chapter 2: Development of Dendrimer-Based Time-Gated cFRET Configuration ............ 50 2.1 Introduction ..................................................................................................................... 50 2.2 Results............................................................................................................................. 52 2.2.1 Labelling and bioconjugation of the dendrimer scaffold ......................................... 52 2.2.1.1 Synthetic strategy .............................................................................................. 52 2.2.1.2 Tb and biotin labelling efficiency ..................................................................... 54 2.2.1.3 NAv loading capacity of dendrimer 3 ............................................................... 56 2.2.1.4 Size characterization of dendrimers .................................................................. 57 2.2.1.5 Loading capacity of dendrimer 4 ...................................................................... 60 2.2.2 FRET pathways ....................................................................................................... 62 2.2.2.1 Tb PL lifetime in cFRET configurations .......................................................... 62 2.2.2.2 Prompt and time-gated excitation spectra ......................................................... 67 2.3 Discussion ....................................................................................................................... 69 2.4 Conclusion ...................................................................................................................... 70 xi 2.5 Experimental methods .................................................................................................... 71 2.5.1 Materials .................................................................................................................. 71 2.5.2 Synthesis of biotin-NHS .......................................................................................... 72 2.5.3 Preparation of the cFRET probe .............................................................................. 73 2.5.4 Absorption and emission measurements ................................................................. 78 2.5.5 Gel electrophoresis .................................................................................................. 79 2.5.6 Lifetime measurements ............................................................................................ 79 2.5.7 Estimating the efficiency of labelling dendrimer 2 with Lumi4-Tb ........................ 81 2.5.8 Labelling efficiency of biotin .................................................................................. 82 2.5.9 Dynamic light scattering measurements .................................................................. 83 2.5.10 Ferguson analysis .................................................................................................... 83 2.5.11 Calculation of FRET parameters ............................................................................. 84 2.5.12 ET efficiency calculations and predictions .............................................................. 84 Chapter 3: Applications of Dendrimer-Based Time-Gated cFRET Probes for Multiplexed Sensing ......................................................................................................................................... 86 3.1 Introduction ..................................................................................................................... 86 3.2 Results............................................................................................................................. 87 3.2.1 PL emission spectra, PL ratios, and mathematical fitting ....................................... 87 3.2.2 DNA displacement assay ......................................................................................... 89 3.2.3 Buffer and serum measurements ............................................................................. 94 3.2.4 DNA displacement assay and smartphone-based time-gated imaging platform ..... 96 3.2.5 Enzyme kinetics ..................................................................................................... 101 3.3 Discussion ..................................................................................................................... 102 xii 3.4 Conclusion .................................................................................................................... 105 3.5 Experimental methods .................................................................................................. 106 3.5.1 Materials ................................................................................................................ 106 3.5.2 Displacement assays .............................................................................................. 108 3.5.3 Buffer and serum experiments ............................................................................... 109 3.5.4 Enzyme kinetics ..................................................................................................... 111 3.5.5 Absorption and emission measurements ............................................................... 111 3.5.6 Lifetime measurements .......................................................................................... 112 3.5.7 ET calculation of PL ratios .................................................................................... 112 3.5.8 Mathematical fitting of PL ratios versus (L, M, N) ............................................... 113 3.5.9 STGIP image measurements and analysis ............................................................. 117 Chapter 4: Characterization of Photoluminescent Silicon Nanocrystals and Energy Transfer to Dyes Using Spectroelectrophoresis and Time-Resolved Spectroscopy............ 120 4.1 Introduction ................................................................................................................... 120 4.2 Results........................................................................................................................... 122 4.2.1 Materials ................................................................................................................ 122 4.2.2 Characterization by spectroelectrophoresis ........................................................... 124 4.2.3 TG spectral characterization .................................................................................. 125 4.2.4 TR spectral characterization .................................................................................. 128 4.2.5 ET with partitioned dark quenchers ....................................................................... 129 4.2.5.1 Prompt ensemble spectra ................................................................................ 130 4.2.5.2 TG spectral snapshots ..................................................................................... 134 4.2.5.3 PL lifetime measurements ............................................................................... 136 xiii 4.2.6 ET with conjugated dark quencher ........................................................................ 139 4.2.7 ET with conjugated fluorescent dye ...................................................................... 145 4.3 Discussion ..................................................................................................................... 148 4.3.1 Polydispersity and photophysical properties ......................................................... 148 4.3.2 Polydispersity and measurements of ET ............................................................... 152 4.3.3 Limitations of this study ........................................................................................ 152 4.3.4 Merits of SiNC as an ET donor ............................................................................. 155 4.4 Conclusion .................................................................................................................... 156 4.5 Experimental Methods .................................................................................................. 157 4.5.1 Materials and instruments ...................................................................................... 157 4.5.2 SiNC(676) 1 partitioned with BHQ dyes .............................................................. 158 4.5.3 Preparation of SiNC(676) 2 ................................................................................... 159 4.5.4 SiNC(676) 2 conjugated with BHQ dyes .............................................................. 160 4.5.5 Label SiNC(676) 2 with sCy5.5 ............................................................................ 162 4.5.6 Capillary gel electrophoresis ................................................................................. 163 4.5.7 Slab gel electrophoresis ......................................................................................... 164 4.5.8 Absorbance measurements. ................................................................................... 164 4.5.9 TG emission/excitation spectra, and EEMs ........................................................... 165 4.5.10 Lifetime measurement using streak camera .......................................................... 168 4.5.11 Estimating extinction coefficient of SiNC(676) 1 ................................................. 169 4.5.12 BHQ dissociation test ............................................................................................ 170 4.5.13 Preparation of serum samples ................................................................................ 170 4.5.14 Quantum yield measurement ................................................................................. 171 xiv 4.5.15 Calculation of FRET parameters ........................................................................... 172 4.5.16 Post-hoc correction of SiNC concentrations ......................................................... 172 Chapter 5: QD-Based cFRET Probes for Extracellular Sensing in Hydrogel .................... 173 5.1 Introduction ................................................................................................................... 173 5.2 Results and discussion .................................................................................................. 175 5.2.1 Strategy .................................................................................................................. 175 5.2.2 Hydrogel casting .................................................................................................... 177 5.2.3 QD-based cFRET probes in hydrogel ................................................................... 178 5.2.4 Proteolysis kinetics in hydrogel ............................................................................. 181 5.3 Conclusions................................................................................................................... 184 5.4 Experimental ................................................................................................................. 185 5.4.1 Materials and instruments ...................................................................................... 185 5.4.2 Synthesis of 4ARM-PEG-NB ................................................................................ 187 5.4.3 Synthesis of linear-PEG-Tz ................................................................................... 188 5.4.4 Peptide labelled with A555/At594/TCO ............................................................... 188 5.4.5 QD-based FRET and cFRET probe preparation .................................................... 189 5.4.6 Enzyme kinetics in solution ................................................................................... 190 5.4.7 Embedding QD-based cFRET probes in hydrogel ................................................ 190 5.4.8 Emission spectra of QD-based cFRET probes in solution and hydrogel .............. 191 5.4.9 Enzyme kinetics in hydrogel ................................................................................. 191 5.4.10 Calculation of PL Ratios ........................................................................................ 192 Chapter 6: Conclusions and Future Work ............................................................................. 194 6.1 Conclusions................................................................................................................... 194 xv 6.2 Unfinished business ...................................................................................................... 195 6.2.1 Optimizing QD PL in hydrogels ............................................................................ 196 6.2.2 Proteolysis and cFRET sensing within a hydrogel ................................................ 197 6.3 Future work ................................................................................................................... 199 6.3.1 Single-particle studies ............................................................................................ 199 6.3.2 Developing additional cFRET probes with alternative materials .......................... 200 6.4 Closing remarks ............................................................................................................ 204 References .................................................................................................................................. 205 Appendices ................................................................................................................................. 230 Appendix A ............................................................................................................................. 230 A.1 Dye quantum yield measurements ......................................................................... 230 Appendix B ............................................................................................................................. 232 B.1 PL emission spectra of calibration data set ........................................................... 232 B.2 Correlation of experimental PL ratios and predictions from mathematical fitting 233 B.3 Detection limits of dendrimer 4, QD520 and QD605 in serum ............................. 237 B.4 Comment on dye photobleaching .......................................................................... 239 Appendix C ............................................................................................................................. 240 C.1 TEM Analysis ........................................................................................................ 240 C.2 Spectroelectrophoresis of SiNC(605) 1 ................................................................. 241 C.3 Absorption, PL emission and excitation, and EEMs of SiNC(717) 1 ................... 242 C.4 Absorption, PL emission and excitation, and EEMs of SiNC(605) 1 ................... 244 C.5 Extinction coefficient of SiNC(676) 1 ................................................................... 246 C.6 Quantum yield of SiNC(676) 1 and 2 .................................................................... 247 xvi C.7 Partitioning and dissociation of BHQs .................................................................. 248 C.8 SiNC(676) 1 partitioned with BHQ2 ..................................................................... 249 C.9 Absorption spectra of SiNC(676) 2 conjugated with BHQ1 and BHQ3 ............... 252 C.10 Absorption spectra of SiNC(676) 2 conjugated with sCy5.5 ................................ 253 C.11 Lifetime data and ET efficiency ............................................................................ 254 xvii List of Tables Table 1.1 Photophysical properties of selected photoluminescent materials.10 ......................................... 12 Table 2.1 Selected photophysical properties of donors and acceptors. ..................................................... 63 Table 2.2 Oligonucleotide sequences and symbols for the number of equivalents per dendrimer. ........... 72 Table 3.1 Oligonucleotide sequences and symbols for the number of equivalents per dendrimer. ......... 107 Table 3.2 Fitting parameters for the calibration data set in Figure 3.2A (64 combinations). ................... 116 Table 3.3 Fitting parameters for the calibration data set in Figure 3.3C (27 combinations). ................... 117 Table 3.4 Double-chopper design and timing parameters and typical values. The parameters and timings are illustrated in Figure 3.7. ...................................................................................................................... 118 Table 5.1 Peptide sequences. .................................................................................................................. 186 Table 6.1 Peptide sequence for MMPs and ADAMs substrates. ............................................................. 198 Table B.1 The actual value of each l, m, and n and PL ratios of the calibration data set (27 combinations) in Figure B.2B and Figure 3.3C (circle points). ....................................................................................... 235 Table B.2 The difference of actual value and calculated value of each l, m, and n and experimental PL ratios. This PL ratio data was plotted in Figure 3.3C as the star points. .................................................. 236 Table C.1 Lifetime of SiNC(676) 1 partitioned with variable equivalent of BHQ1. ................................... 254 Table C.2 Lifetime of SiNC(676) 1 partitioned with variable equivalent of BHQ2. ................................... 256 Table C.3 Lifetime of SiNC(676) 1 partitioned with variable equivalent of BHQ3. ................................... 258 Table C.4 Lifetime of SiNC(676) 2 conjugated with variable equivalent of BHQ1. .................................. 260 Table C.5 Lifetime of SiNC(676) 2 conjugated with variable equivalent of BHQ3. .................................. 261 Table C.6 Lifetime of SiNC(676) 2 conjugated with variable equivalent of sCy5.5. ................................. 262 Table C.7 ET efficiencies for SiNC(676) 1 partitioned with various equivalents of BHQ1 and BHQ3 dyes, estimated from PL intensity data and TR PL data. ................................................................................... 263 xviii List of Figures Figure 1.1 Fundamental fluorescence concepts. (A) Perrin−Jablonski diagram showing how absorption leads to fluorescence and phosphorescence. (i) Absorption: a molecule absorbs light and an electron is promoted to an excited state (S0v0 → S1vn or S2vn). (ii) Kasha’s rule: an excited molecule (Franck–Condon state) rapidly returns to the S1v0 state through vibrational relaxation (VR) and, where applicable, internal conversion (IC). (iii) Fluorescence: an excited molecule returns to the electronic ground state (S0vn) via emission of a photon. (iv) Intersystem crossing (ISC): the spin multiplicity changes from singlet to triplet (S1 → T1). (v) Phosphorescence: an excited molecule returns to the electronic ground state via emission of a photon (T1v0 → S0vn). (B) Generic illustration of absorption, fluorescence, and phosphorescence spectra and the corresponding electronic transitions from the Perrin–Jablonski diagram. Adapted from ref.3 ......... 3 Figure 1.2 Illustration of the Franck–Condon principle and how it contributes to the shape of spectrum. (A) A transition for absorption is most probable when the initial and final wavefunctions have maximum overlap, which is S0v0 → S1v3 in this illustration (and likewise for S1v0 → S0v3 for fluorescence emission). (B) Labelled contributions to an absorption spectrum and fluorescence emission spectrum according to the wavefunctions in panel A. ............................................................................................................................. 5 Figure 1.3 Time-gated measurement. The PL intensity is collected immediately after a short excitation pulse (the pulse ends at time is 0). The emission is only collected after short-lived background (gold curve) has fully decayed, such that the background is rejected. ........................................................................... 10 Figure 1.4 Central core structure for four common families of fluorescent dyes: xanthene, cyanine, coumarin, and boron-dipyrromethene. Adapted from ref.11 Copyright 2021 Wiley-VCH GmbH. ............... 13 Figure 1.5 Photoluminescence mechanism of lanthanide complexes. Multiple steps are involved: (i) ligand excitation by photon absorption; (ii) intersystem crossing from the singlet excited state to the triplet excited state of the ligand; (iii) energy transfer from the ligand to the lanthanide ion; (iv) relaxation of the lanthanide ion by photon emission. .............................................................................................................................. 16 Figure 1.6 Lumi4-Tb. (A) The structure of Lumi4-Tb. (B) The absorption (black data) and emission (green data) spectra of Lumi4-Tb. (C) The multiple narrow and well separated emission peaks from Tb3+ (black data) enable its pairing with multiple fluorophores (coloured data) for multiplexed (bio)sensing with minimum crosstalk (shaded area). Adapted from ref.21 Copyright 2014 Elsevier. ..................................................... 17 xix Figure 1.7 CdSe/ZnS QDs. (A) TEM image of a single CdSe/ZnS QD. (B) Anatomy of core/shell structure of QD with a layer of organic ligand. (C) Cartoon, photograph, and emission spectra of the CdSe/ZnS QDs with different core sizes. Adapted from ref.27 Copyright 2011 American Chemical Society. ...................... 19 Figure 1.8 SiNCs (Si QDs). (A) TEM images of SiNCs with three different sizes (3, 6, and 9 nm). (B) Functionalization of hydride-terminated SiNCs with dodecane via hydrosilylation methods. (C) PL emission spectra of the different-sized SiNCs from panel A. Reproduced from ref.32 Copyright 2017 American Chemical Society. ....................................................................................................................................... 20 Figure 1.9 Jablonski diagram for FRET. Energy transfers from an excited-state donor to a ground-state acceptor via a non-radiative process, which is represented as a green solid arrow. The energy lost by the donor is equal to the energy gained by the acceptor, which is reflected by the dashed arrows of the same length. .......................................................................................................................................................... 24 Figure 1.10 FRET efficiency as a function of the relative distance between the donor and acceptor. The FRET efficiency is highly sensitive to distance in the range of 0.7R0−1.3R0 (steep slope). Reproduced from ref.40 Copyright 2017 American Chemical Society. ..................................................................................... 27 Figure 1.11 Simplified representations of (A) a dye-based molecular beacon, (B) a FRET configuration with a QD donor and multiple copies of a dye acceptor, (C) a dye-based photonic wire, and (D) a cFRET configuration with a central QD and multiple copies of multiple types of dye acceptors. Arrows represent FRET pathways. Acceptor dyes are labelled as A and donor dyes are labelled as D. Relay dyes in the photonic wire act as both acceptor and donor in sequence and are labelled as R. For the QD-FRET and cFRET configurations, the QD is the donor. Although A1 in the cFRET configuration is an acceptor for the QD and a donor for A2, it is not labelled as a relay dye because of the difference in its intended role: the relay dyes in the photonic wire aim to deposit as much energy as possible to the terminal acceptor dye, A, whereas the cFRET configuration aims to deposit energy into both A1 and A2. Reproduced from ref.49 Copyright 2019 IOPscience. ....................................................................................................................... 31 Figure 1.12 A cFRET configuration with a central QD donor and three types of dye acceptor. (A) Simple model of an assembly that uses three different peptide sequences as linkers between the QD and three dyes: Alexa Fluor 555 (A555), either Cyanine 3.5 (Cy3.5) or Atto 594 (At594), and Alexa Fluor 647 (A647). For clarity, the glutathione (GSH) ligand coating on the QD is represented by a mesh and only some of the peptides are shown. (B) Diagram of the energy transfer pathways in the cFRET configuration. Energy transfer pathways (dotted lines) labelled with the same number (e.g. 2a, 2b) compete with one another, whereas pathways labelled with different numbers are sequential. PL and nonradiative (Δ) relaxation pathways are also shown. Reproduced from ref.50. Copyright 2017 American Chemical Society. ............ 32 xx Figure 1.13 Dendrimers. (A) General dendrimer structure and components: core (red), interior branching units (green), and outer functional groups (blue). Adapted from ref.64 Copyright 2015 Elsevier. (B) Chemical structure of a G3 PAMAM dendrimer and (C) TEM image of G7 PAMAM dendrimers stained with sodium phosphotungstate. Chemical structure reproduced from ref.63 Copyright 2016 Wiley Periodicals, Inc. TEM image was adapted from ref.65 Copyright 1998 American Chemical Society. ............................................ 45 Figure 1.14 Hydrogels classification based on their polymeric composition(s): (A) homopolymer; (B) copolymer; and (C) interpenetrating polymer networks. Reproduced from ref.80 Copyright 2012 Elsevier. .................................................................................................................................................................... 46 Figure 2.1 Preparation of the cFRET probe. (A) Summary scheme (not drawn to scale) for labelling and functionalization of the G6 PAMAM dendrimer. The dendrimer illustration is a simplification and does not show its G6 molecular structure. The bolded numbers are used to refer to dendrimer materials throughout the Chapter 2 and 3. (B) Agarose gel (0.5% w/v) electrophoresis shows changes in the mobility of the dendrimer after each modification step. The first lane in the PL image of the gel is the Tb complex, and the remaining lanes are numbered to match the dendrimer materials in panel A. (C) Scheme (not to scale) illustrating the binding of dye-labelled and biotinylated double-stranded oligonucleotides to dendrimer 4. (D) Agarose gel (0.5% w/v) electrophoresis shows changes in mobility after dendrimer 4 binds with different equivalents of biotinylated oligonucleotides. The dye was Alexa Fluor 546 (A546). The first lane is the biotinylated prehybridized A546-labelled DNA; the subsequent lanes are dendrimer 4 with an indicated number of equivalents of the DNA. The orange box outlines the position of 4, which was less bright in the gel PL image. .............................................................................................................................................. 53 Figure 2.2 PL image of an agarose gel (0.5% w/v) with Tb alone and the labelling reaction mixture from labelling dendrimer 1 with Tb. The arrow shows the polarity of the applied electric field (~6.7 V/cm). ...... 54 Figure 2.3 PL decays (and amplitude-weighted average lifetimes) for the Tb alone (2.8 ms), dendrimer 2 (1.2 ms), and dendrimer 3 (1.9 ms). ........................................................................................................... 55 Figure 2.4 Calibration curves with ESI-MS peak area plotted versus concentration for biotin standard solutions (blue dots). The signal measured for the filtrate from purification of the biotin-labelling reaction with dendrimer 2 is shown as a red dot. ..................................................................................................... 56 Figure 2.5 (A) PL image of an agarose gel (0.5%) for estimating the NAv loading capacity of modified dendrimer 3. (B) Absorption spectrum of purified dendrimer 4. Before purification, the NAv was excess. The ratio of NAv:dendrimer = 30:1 prior purification. ......................................................................................... 57 Figure 2.6 Number-weighted size distribution of purified NAv-bound dendrimer 4, measured by DLS. ... 58 xxi Figure 2.7 (A) Images of agarose gels illuminated under UV light and white light. The dendrimers and Au NP standards had different mobilities at various gel densities. (B) Ferguson plots for DHLA-coated Au NP standards. (C) Plots of the square root of retardation factor versus Au NP diameter. The slope and intercept were used to estimate the diameter of dendrimers. (D) Ferguson plots for dendrimer 3 and 4. ................ 60 Figure 2.8 Biotinylated-molecule loading capacities of dendrimer 4. (A) Biotin-FAM: (i) PL image of an agarose gel and (ii) PL ratio (524 nm/490 nm) plot. (B) A546-labelled and biotinylated double-stranded oligonucleotide (Blk2-A546/Prb2 hybrid): (i) PL image of an agarose gel and (ii) PL ratio (572 nm/490 nm) plot. (C) A488-labelled and biotinylated peptide: (i) PL image of an agarose gel and (ii) PL ratio (516 nm/490 nm) plot. All agarose gels were 0.5% w/v. .................................................................................................. 61 Figure 2.9 FRET pairs and pathways. (A) Normalized absorption spectra (dashed lines) and emission spectra (solid lines) for the Tb, A488, A546, and Cy5. (B) Diagram of the six ET pathways in the cFRET configuration. Numbers indicate the sequence of ET pathways and lowercase letters indicate ET pathways that compete with one another. Two Tb are shown engaging in ET to convey that there are multiple possible donors. ........................................................................................................................................................ 63 Figure 2.10 Tb PL decays and quenching efficiencies. (A) Tb PL decays and amplitude-weighted average lifetimes for the (0, 0, 0), (5, 0, 0), (0, 5, 0), and (0, 0, 5) configurations. This data was used to estimate Tb-to-dye ET efficiencies. Tb lifetimes were ± 0.07 ms or less. (B) Tb PL decays and amplitude-weighted average lifetimes for the (5, 5, 0), (5, 0, 5), (0, 5, 5), and (5, 5, 5) configurations. (C) Correlation between the measured and predicted Tb quenching efficiencies (QTb) for two-dye and three-dye configurations. Measured quenching efficiencies were calculated from PL lifetimes in panel B and predictions were derived from the one-dye data in panel A. ............................................................................................................... 65 Figure 2.11 Dyes PL decays. (A) A488 PL decays and lifetimes for the (5, 0, 0), (5, 5, 0), (5, 0, 5), and (5, 5, 5) configurations, indicating ET from the A488 to A546 and Cy5. Dye lifetimes were ± 0.3 ns or less, with the exception of ± 0.6 ns for (5, 0, 0). (B) A546 PL decays and lifetimes for the (0, 5, 0), (0, 5, 5), and (5, 5, 5) configuration, indicating ET from A546 to Cy5. Dye lifetimes were ± 0.2 ns, with the exception of ± 0.4 ns for (5, 5, 5). For the data in panels A and B, the dyes were directly excited. ........................................ 66 Figure 2.12 Prompt and time-gated excitation spectra for various cFRET configurations. (A) Prompt excitation spectra: the black curve is the experimental data; the green, orange, and red curves show the individual contributions of A488, A546, and Cy5; the dashed curves show the excitation spectra for control samples (used to estimated upstream dye contributions from direct excitation and emission crosstalk). (B) Time-gated excitation spectra. .............................................................................................................. 68 xxii Figure 3.1 Time-gated PL emission. (A) Representative examples of PL emission spectra for cFRET configurations (0, 0, N), (0, M, 5), and (L, 3.5, 5). The PL emission spectra for all 64 measured (L, M, N) permutations can be found in the Appendix B.1. L, M, and N are the average numbers of A488, A546, and Cy5, respectively, per dendrimer 5. The colours in the legend match the colour of the corresponding spectrum. (B) Plots of the (i) A488/Tb, (ii) A546/Tb, and (iii) Cy5/Tb PL emission ratios as a function of L, M, and N, respectively (64 points). ............................................................................................................. 88 Figure 3.2 PL ratios and (L, M, N) values. (A) Three-dimensional plot with each dye/Tb PL ratio along an axis. The 64 data points were coloured with RGB values according to the actual values of L (green), M (blue), and N (red). Each (L, M, N) permutation is a unique point in this space. (B) Determination of calculated (L, M, N) from the (ρA488/Tb, ρA546/Tb, ρCy5/Tb) PL ratios. The histogram shows the differences between actual (L, M, N) values and those calculated from (ρA488/Tb, ρA546/Tb, ρCy5/Tb) and mathematical fitting of the PL ratio space. The calculated values were within ± 0.2 of the actual values in ≥60 of the 64 cases for each of L, M, and N. (Note: the histogram bins are centred on the middle bar for M. The bin size is 0.25.) .................................................................................................................................................................... 89 Figure 3.3 Toehold-mediated strand displacement assays with the (5, 5, 5) cFRET probe. (A) Target DNA oligonucleotides, [Tgt1, Tgt2, Tgt3], displaced the dye-labelled oligonucleotides, (Blk1-A488, Blk2-A546, Blk3-Cy5), from dendrimer 5 with loss of FRET. For clarity, only two of each dye are shown. (B) Progress curves for the displacement of (i) Blk1-A488 by Tgt1, (ii) Blk2-A546 by Tgt2, and (iii) Blk3-Cy5 by Tgt3 (5 equiv. of target in all cases). (C) PL ratio calibration data set (27 points) for displacement assays, obtained with different numbers of equivalents [l, m, n] of [Tgt1, Tgt2, Tgt3]. The calibration data points were coloured with RGB values according to the actual values of l (green), m (blue), and n (red). The star points (13 points) represent test samples with random combinations of [l, m, n]. (D) Histograms of the differences between actual and calculated [l, m, n] for the star points in panel C. The calculated values were within ± 0.5 of the actual values in ≥9 of the 13 cases for each of l, m, and n. (Note: the histogram bins are centred on the middle bar for m. The bin size is 0.25.) ....................................................................................................... 91 Figure 3.4 Correlation between the PL ratios measured in borate buffer and in HEPES buffer for five different [l, m, n] amounts of [Tgt1, Tgt2, Tgt3]. .......................................................................................... 94 Figure 3.5 Detection in 50% v/v serum using the (5, 5, 5) cFRET probe. (A) Prompt and time-gated emission spectra for the (5, 5, 5) configuration in 50% serum. The prompt spectrum from serum alone is shown for reference. The autofluorescence background from serum is absent in the time-gated spectrum. (B) Correlation between the PL ratios measured in borate buffer and in 50% serum for five different [l, m, n] amounts of [Tgt1, Tgt2, Tgt3]. ................................................................................................................. 95 xxiii Figure 3.6 Assessment of probe stability in 50% v/v serum. (A) Dye/Tb PL ratios as function of time after diluting with serum. (B) PL spectra at selected time points after diluting with serum. The 24 h-data is shown in the inset. (C) Tb PL lifetime as a function of time after diluting with serum. For panel C, the Tb was excited at 340 nm (13 nm bandwidth) and the emission was measured at 490 nm (3 nm bandwidth). ................. 96 Figure 3.7 STGIP design. (A) Scale renderings of the 3D-printed housing and STGIP components. (B) Illustration of the double-chopper with important design features labelled and highlighted. (C) Model of PL intensity as a function of time as the double-chopper rotates. Only two cycles (corresponding to two gaps and two blades) are shown. The open and closed circles represent gaps and blades, respectively, aligned with the optical axis between the LED and smartphone camera. The tx, td, and tm represent the duration of excitation, delay, and measurement (integration time for imaging), respectively. See Table 3.4 for detail explanation of parameters. The scale bar in panels A and B are 2 cm. STGIP device and illustrations contributed by Sahil S. Kanani. ................................................................................................................... 98 Figure 3.8 Toehold-mediated strand displacement assays with the (0, 5, 0) cFRET probe. (A) Normalized absorption spectra (dashed lines) and emission spectra (solid lines) for the Tb and Tex615. (B) Complementary target DNA oligonucleotides (Tgt2) are designed for displacing the Tex615-labelled oligonucleotides (Blk2-Tex615) from the dendrimer-based probe with loss of FRET. Not to scale. (C) Comparison of the time-gated PL ratios, measured on a plate reader and the STGIP, for the cFRET probe. The samples are (0, 5, 0) probe only, the probe with 1 equivalent of Tgt2, and the probe with 3 equivalents of Tgt1. Time-gated images of the samples from the STGIP are also shown. (D) The PL ratios of the probe with different equivalents of Tgt2, measured on both a plate reader and the STGIP (images also shown). The scale bar in panels C and D are 1.5 mm. Measurement data contributed by Sahil S. Kanani. I prepared dendrimer 4 for these experiments. .......................................................................................................... 100 Figure 3.9 Peptide-conjugated dendrimer-based FRET probe. (A) Trypsin cleaves the A555-labelled peptide substrate from the dendrimer with the loss of FRET. Not to scale. (B) Progress curve for a dendrimer-based probe with 12 equivalents of bound biotinylated-peptide-A555 and various concentrations of trypsin. ................................................................................................................................................... 102 Figure 4.1 SiNCs. (A) Illustration (not to scale) of the SiNC and its surface chemistry, including the initial distal carboxyl(ate) groups (SiNC 1) and partial dihydrazide modification (SiNC 2). (B) PL images of agarose gels showing the electrophoretic mobility of SiNC(676) 1 and 2. The dashed line indicates the position of the sample wells and the polarity of the electric filed is marked. (C) Extinction (blue line) and PL excitation (dashed orange line) and emission (solid orange line) spectra (0 µs delay, 2 ms integration time) for the ensemble of SiNC(676) 1. ............................................................................................................. 124 xxiv Figure 4.2 Capillary gel electrophoresis of SiNC(717) 1. (A) Simplified schematic of the experiment: a polyacrylamide gel (PAG)-filled capillary and electrophoresis setup were mounted on an inverted microscope, where the SiNCs were excited with UV light when passing above an objective lens and the PL emission were recorded via a fibre-coupled CCD spectrometer (not shown). The electropherograms include a peak for a fluorescein as an internal standard. (B) PL electropherograms measured at different emission wavelengths. PL emission measurements were made with continuous (not pulsed) excitation and an 800 ms detector integration time. (C) PL emission spectra as a function of migration time for the same experiment as panel B. The graph on the left shows the measured intensities whereas the graph on the right shows the normalized spectra. (D) Plot of the peak PL emission wavelength versus migration time. .................................................................................................................................................................. 125 Figure 4.3 TG PL measurements and emission spectra. (A) Illustration of the prompt (0 µs delay, 2 ms integration time) and TG (delay ≥ 5 µs) PL measurement concepts with pulsed excitation and different integration times. (B) Prompt PL emission spectrum for SiNC(717) 1 (2 ms integration time; black data) with overlaid TG PL emission spectra with a variable delay and 20 μs integration time (rainbow data). (C) Plot of peak PL emission wavelength (left axis) and FWHM (right axis) versus delay time for the spectra in panel B. (D) EEMs with 0, 10, 40 μs delay and 20 μs integration time. The white area indicates no signal was collected due to off-scale background from excitation light; the black and gray area indicates the values are below and above zero and maximum (6200 in this case), respectively. ............................................ 127 Figure 4.4 PL lifetime of SiNC(676) 1 via TR measurements. (A) Streak camera image that maps PL intensity versus time and wavelength. (B) PL intensity versus decay time for the 540−756 nm (black), 540−600 nm (blue), 600−660 nm (green), and 696−756 nm (red) wavelength ranges, extracted from the data in panel A. The instrument response function (IRF; gray) was collected at 800−810 nm, which is the second-order Raman signal from water. ................................................................................................... 129 Figure 4.5 SiNC(676) 1 paired with BHQ dyes. (A) Absorption spectra of the BHQ dyes overlaid on the prompt PL emission spectrum (0 μs delay, 2 ms integration time) of the SiNC(676) 1. (B) Spectral overlap kernels between the SiNC(676) 1 and BHQ dyes, derived from conventional Förster theory. (C) Illustration (not to scale) of dyes partitioning from solution and into the coating on the SiNCs 1. ............................. 130 Figure 4.6 Spectra and total ET efficiency of SiNC(676) 1 partitioned with BHQ dyes. (A) SiNC(676) 1 partitioned with various equivalents of partitioned BHQ1: (i) emission spectra (0 μs delay, 2 ms integration time) and (ii) absorption spectra. (B) SiNC(676) 1 with various equivalents of partitioned BHQ2: (i) emission spectra (0 μs delay, 2 ms integration time) and (ii) absorption spectra. (C) SiNC(676) 1 with various equivalents of partitioned BHQ3: (i) emission spectra (0 μs delay, 2 ms integration time) and (ii) absorption spectra. (D) ET efficiency of SiNC(676) 1 versus variable equivalents of BHQ1, BHQ2, and BHQ3: full range xxv and zoom for lower equivalents of BHQ. The ET efficiency was calculated from the emission spectra (0 μs delay, 2 ms integration time) in panel A−C. .............................................................................................. 132 Figure 4.7 ET efficiency versus wavelength. SiNC(676) 1 with partitioned (A) BHQ1 and (B) BHQ3. The ET efficiency at different wavelengths were calculated from the prompt ensemble emission spectra (0 μs delay, 2 ms integration time). .................................................................................................................... 134 Figure 4.8 TG spectral snapshots (various delay, 20 µs integration time) of SiNC(676) 1 with partitioned BHQ dyes. (A) SiNCs with various equivalents of partitioned BHQ1: (i) emission peak shift versus delay time and (ii) FWHM versus delay time. (B) SiNCs with various equivalents of partitioned BHQ3: (i) emission peak shift versus delay time, and (ii) FWHM versus delay time. .............................................................. 135 Figure 4.9 Quenching efficiency as a function wavelength and delay time (various delay, 20 μs integration time). (A) SiNC(676) 1 with partitioned BHQ1. (B) SiNC(676) 1 with partitioned BHQ3. SiNCs without added BHQ were used as controls. ..................................................................................................................... 136 Figure 4.10 TR PL measurements of SiNC(676) 1 partitioned with BHQ dyes. (A) PL decays of SiNC(676) 1 with various equivalents of partitioned BHQ1 for the entire emission range (540−756 nm), 540−600 nm, 600−660 nm, and 696−756 nm. (B) PL decay of SiNC(676) 1 with various equivalents of partitioned BHQ3 for the entire emission range (540−756 nm), 540−600 nm, 600−660 nm, and 696−756 nm. .................. 138 Figure 4.11 Box-car measurements of ET with SiNC(676) 1 and partitioned BHQ dyes. (A) Normalized PL intensity decay at various delay for BHQ1 at 540−600 nm, 600−660 nm, and 696−756 nm and ET efficiency at different wavelength windows. (B) Normalized PL intensity decay at various delay for BHQ3 at 540−600 nm, 600−660 nm, and 696−756 nm and ET efficiency at different wavelength windows. ........................ 139 Figure 4.12 ET of SiNC(676) 2 conjugated with BHQs. (A) Illustration of SiNC 2 conjugated with BHQs. (B) Emission spectra (0 μs delay, 2 ms integration time) of SiNC(676) 2 with (i) conjugated BHQ1 and (ii) BHQ3. (C) ET efficiency of SiNC(676) 2 with conjugated BHQ1 and BHQ3. (D) ET efficiency of SiNC(676) 2 with conjugated (i) BHQ1 and (ii) BHQ3 at different wavelength windows (0 µs delay, 2 ms integration time). ......................................................................................................................................................... 140 Figure 4.13 TG spectral snapshots (various delay, 20 µs integration time) of SiNC(676) 2 conjugated with BHQ dyes. (A) SiNC(676) 2 conjugated with various equivalents of BHQ1: (i) emission peak shift versus delay time and (ii) FWHM versus delay time. (B) SiNC(676) 2 conjugated with various equivalents of BHQ3: (i) emission peak shift versus delay time and (ii) FWHM versus delay time. ............................................ 142 Figure 4.14 Quenching efficiency as a function wavelength and delay time (various delay, 20 μs integration time): (A) SiNC(676) 2 conjugated with BHQ1; (B) SiNC(676) 2 conjugated with BHQ3. ....................... 143 xxvi Figure 4.15 Box-car measurements of ET with SiNC(676) 2 with conjugated BHQ dyes. (A) Normalized PL intensity decay at various delay for BHQ1 at 540−600 nm, 600−660 nm, and 696−756 nm and ET efficiency for the different wavelength windows. (B) Normalized PL intensity decay at various delay for BHQ3 at 540−600 nm, 600−660 nm, and 696−756 nm and ET efficiency for the different wavelength windows. . 144 Figure 4.16 ET between SiNC(676) 2 and sCy5.5. (A) Illustration (not to scale) of SiNC 2 conjugated with sCy5.5. (B) Absorption spectra of the sCy5.5 overlaid on the prompt ensemble PL emission spectrum of the SiNC(676) 2. (C) Spectral overlap kernel between the SiNC(676) 2 and sCy5.5 dye, derived from conventional Förster theory. (D) Emission spectra of SiNCs with various equivalents of conjugated sCy5.5 (0 μs delay, 2 ms integration time). (E) Experimental (black data; 0 μs delay, 2 ms integration time) and deconvoluted emission spectrum (orange and dark red data) for SiNC(676) 2 conjugated with 6.0 equivalents of sCy5.5. (F) Wavelength-dependent ET efficiency derived from unmixing of the intensity data in panel D (solid points) and from SiNC PL lifetimes in panel G (box-car method, open points). (G) Box-car measurements of ET with SiNC(676) 2 with conjugated sCy5.5 for different wavelength windows. ....... 146 Figure 4.17 Emission spectra of SiNC(676) 2 and SiNC(676) 2 with conjugated sCy5.5 dispersed in 50% v/v serum (aq). (A) Prompt measurements (0 μs delay, 2 ms integration time) show high background signal and substantial direct excitation of sCy5.5. (B) TG measurement (30 μs delay, 2 ms integration time) suppresses short-lived PL from serum autofluorescence and direct excitation of sCy5.5, leaving only SiNC PL and ET-sensitized sCy5.5 PL. ............................................................................................................. 148 Figure 4.18 Modelling SiNC(676) 1 polydispersity. (A) Ensemble-level emission spectrum (0 μs delay, 2 ms integration time) of SiNCs modelled as emission spectra from 7 discrete sub-populations. (B) Variation in the spectral overlap integral and R0/(R0)max between the hypothetical sub-populations of SiNCs when paired with BHQ dyes or sCy5.5 dye. ....................................................................................................... 150 Figure 5.1 QD-based cFRET probes in the hydrogel for detecting protease activities secreted from cell (not to scale). The illustration is inspired by ref.190 ........................................................................................... 175 Figure 5.2 Hydrogel precursors and hydrogel: (i) 4ARM-PEG-NB, (ii) linear-PEG-Tz, (iii) QD-based cFRET probes, and (iv) hydrogel after casting via cycloaddition click chemistry. Not to scale. ........................... 177 Figure 5.3 Hydrogels functionalized with (0, 0) probes (left) and (0, 10) probes (right). (A) Under white light. (B) Under UV light (356 nm). The scale bars are 0.5 cm. Note: the peptides were a chymotrypsin substrate labelled with a TCO group and the same chymotrypsin substrate labelled with At594. For the final application, it is anticipated that different sequences of peptide would be used for FRET-based sensing of proteolysis and for integration with the hydrogel structure. ...................................................................... 178 xxvii Figure 5.4 The emission spectra of (M, N) cFRET probes. (A) In borate buffer. (B) In hydrogel (immersed in borate buffer). In panels A and B, M and N = 0, 2, 5, and 8. ................................................................ 179 Figure 5.5 The PL ratios of cFRET probes. (A) IA555/IQD in borate buffer (hollow dots and dash line) and hydrogel (solid dots and solid line). (B) IAt594/IQD in borate buffer (hollow dots and dash line) and hydrogel (solid dots and solid line). (C) Plot showing unique PL ratios combinations for each (M, N) permutation in solution. (D) Plot showing unique PL ratio combinations for each (M, N) permutation in hydrogel. ......... 180 Figure 5.6 Enzyme kinetics in solution. (A) Scheme (not to scale) illustrating the QD-based FRET probe for detecting trypsin, where the trypsin cleaves the A555-labelled peptide substrate from the QD with loss of FRET. (B)The trypsin substrate-based (12, 0) probes were dispersed in borate buffer for detecting trypsin. The PL intensities of were measured over time via a plate reader. .......................................................... 181 Figure 5.7 Enzyme kinetics in hydrogel. (A) Images of (6, 0) probes with ~100 nM TRP in hydrogel. Excitation filter: 405±10 nm, QD channel emission filter: 525±20 nm, A555 channel emission filter: 565±15 nm. The scale bars are 0.5 mm. (B) Spectra of (6, 0) probes with ~100 nM TRP in hydrogel. (C) Progress curves of (6, 0) probes with different TRP concentrations. In panels A−C, each (6, 0) probe has 6 copies of TCO-labelled peptide for immobilization in hydrogel. ............................................................................... 183 Figure 6.1 Proposed strategy for developing a UCNP-based cFRET probe (not to scale). PAA-coated NaYF4:Yb3+, Er3+ UCNPs are modified with azide groups through carbodiimide coupling. Then, click chemistry between azide and DBCO groups is used for bioconjugation to introduce dye-labelled pre-hybridized oligonucleotides. Note: the click chemistry is not limited to the azide-DBCO pair (e.g. the Tz-TCO pair is also a potential conjugation method). .................................................................................... 202 Figure 6.2 Proposed strategy for developing Tb-labelled VLP-based cFRET probe (not to scale). The wild type VLPs are modified with Tb complexes and azide groups through NHS ester chemistry. Click chemistry between azide and DBCO groups is used to conjugate dye-labelled pre-hybridized oligonucleotides. Note: the click chemistry is not limited to azide-DBCO pair (e.g. the Tz-TCO pair is also a potential conjugation method). .................................................................................................................................................... 204 Figure A.1 Plots for estimating dye quantum yields: (A) A488 and A546 (with a fluorescein standard) labels on double-stranded oligonucleotides (Blk1-A488/Prb1 and Blk2-A546/Prb2 hybrids); (B) Cy5 (with A546 repurposed as a reference) as a label on a double-stranded oligonucleotide (Blk3-Cy5/Prb3 hybrid). ... 231 Figure B.1 Emission spectra for 64 different (L, M, N) permutations. This figure shows the full data set of spectra for Figure 3.1A in the main text of Chapter 2. ............................................................................. 232 xxviii Figure B.2 Correlations between the PL ratios predicted from mathematical fits of the experimental data and the actual experimentally measured PL ratios. (A) The 64 (L, M, N) permutations for the data in Figure 3.1A. (B) The 27 [l, m, n] permutations for the data in Figure 3.3C (displacement assay). .................... 234 Figure B.3 Detection limits for Tb (dendrimer 4) versus CdSe/CdS/ZnS QD520 and QD605 in 50% v/v serum. (A) Examples of PL emission spectra for (i) dendrimer 4, (ii) QD520, and (iii) QD605. (B) Plots of PL emission intensity versus concentration for (i) dendrimer 4, (ii) QD520, and (iii) QD605. The signal detection limit (defined as three standard deviations of the noise above the average blank spectrum) is shown as a dashed horizontal line. Emission intensities were at 490 nm for Tb, and summed between 518–524 nm for QD520 and 596–608 nm for QD605. ...................................................................................... 238 Figure C.1 TEM of SiNC(676) 1. (A) Bright field TEM image. (B) Dark field TEM image. (C) Size distribution of SiNCs measured from TEM images. The SiNCs and TEM images were provided from Prof. Veinot’s group at the University of Alberta. ............................................................................................................. 240 Figure C.2 Spectroelectrophoresis of SiNC(605) 1. (A) PL electropherograms measured at different emission wavelengths. PL emission measurements were made with continuous (not pulsed) excitation. (B) PL emission spectra as a function of migration time for the same experiment as panel A. (C) Plot of the peak PL emission wavelength versus migration time. .............................................................................. 241 Figure C.3 SiNC(717) 1. (A) Extinction spectrum. (B) Emission spectra with (i) various delay and 2 ms integration time, and (ii) various delay and 20 μs integration time. (C) Excitation spectra with (i) various delay and 2 ms integration time, and (ii) various delay and 20 μs integration time. ................................. 242 Figure C.4 EEMs of SiNC(717) 1: (A) various delay with a fixed integration time (2 ms); (B) various delay with a fixed integration time (20 μs). ......................................................................................................... 243 Figure C.5 SiNC(605) 1. (A) Extinction spectrum. (B) Emission spectra with (i) various delay and 2 ms integration time, and (ii) various delay and 20 μs integration time. (C) Excitation spectra with (i) various delay and 2 ms integration time, and (ii) various delay and 20 μs integration time. ................................. 244 Figure C.6 EEMs of SiNC(605) 1: (A) various delay with a fixed integration time (2 ms); (B) various delay with a fixed integration time (20 μs). ......................................................................................................... 245 Figure C.7 Nominal absorption values (at 350 nm) versus various concentrations of SiNC(676) 1. ....... 246 Figure C.8 Plot for estimating quantum yield of SiNC 1 and 2 using fluorescein as a standard. ............ 247 xxix Figure C.9 BHQs dissociation test. (A) Without added DMSO, BHQs are partitioned on the surface of SiNC. ET occurs between SiNCs and BHQs, SiNCs are quenched. (B) After adding DMSO, BHQs dissociate from the surface of SiNCs. ET efficiency reduced as dissociation taken place. ............................................... 248 Figure C.10 SiNC(676) 1 with various equivalents of partitioned BHQ2: (A) Emission spectra (0μs delay, 2 ms integration time) and (B) ET efficiency versus wavelength. ................................................................ 249 Figure C.11 TG spectral snapshots (variable delay, 20 µs integration) of SiNC(676) 1 with partitioned BHQ2. (A) Emission spectra (only 0 µs delay, 20 µs integration time are shown). (B) Emission peak shift versus delay time. (C) FWHM versus delay time. (D) Quenching efficiency as a function wavelength and delay time. ........................................................................................................................................................... 250 Figure C.12 Lifetime measurements of SiNC(676) 1 partitioned with BHQ2. (A) PL decay of SiNC(676) 1 with various equivalents of partitioned BHQ2 at 540−600 nm, 600−660 nm, and 696−756 nm. (B) Box-car measurements at various delay at 540−600 nm, 600−660 nm, and 696−756 nm. (C) ET efficiency at different wavelength windows. Calculated from panel B. ......................................................................... 251 Figure C.13 Absorption spectra of SiNC(676) 2 with conjugated (A) BHQ1 and (B) BHQ3, after purification. .................................................................................................................................................................. 252 Figure C.14 Absorption spectra of SiNC(676) 2 with conjugated sCy5.5, after purification. ................... 253 xxx List of Abbreviations 2D Two-dimensional 3D Three-dimensional A Acceptor a.u. Arbitrary unit A488 Alexa Fluor 488 A546 Alexa Fluor 546 A555 Alexa Fluor 555 A647 Alexa Fluor 647 Abs. Absorbance ACN Acetonitrile ADAM A disintegrin and metalloproteinase APS Ammonium persulfate At594 Atto 594 Au NP Gold nanoparticle BB Borate buffer BHQ Black hole quencher Biotin-FAM Biotin-fluorescein Blk Block-strand oligonucleotide BMV Brome mosaic virus CCD Charge-coupled device CCMV Cowpea chlorotic mottle virus cFRET Concentric Förster resonance energy transfer CGE Capillary gel electrophoresis ChT Chymotrypsin Cy3.5 Cyanine 3.5 Cy5 Cyanine 5 Cy5.5 Cyanine 5.5 D Donor xxxi DBCO Dibenzocyclooctyne DCC Dicyclohexylcarbodiimide DCM Dichromethane DHLA Dihydrolipoic acid DIC N,N’-Diisopropylcarbodiimide DLS Dynamic light scattering DMAP 4-Dimethylaminopyridine DMF N,N-Dimethylformamide DMSO Dimethyl sulfoxide DNA Deoxyribonucleic acid (oligonucleotide) DPBS Dulbecco’s phosphate buffered saline ECM Extracellular matrix EDC 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide EDTA Ethylenediaminetetraacetic acid EEM Excitation-emission matrix EK Enterokinase Em. Emission ESI Electrospray ionization ET Energy transfer Exc. Excitation Ext. Extinction FRET Förster resonance energy transfer FWHM Full-width-at-half-maximum G channel Green channel G6 Generation 6 GSH L-Glutathione HEPES (4-(2-Hydroxyethyl)piperazine-1-ethanesulfonic acid) HOMO Highest occupied molecular orbital IC Internal conversion Int. Intensity xxxii Intg. Integration ISC Intersystem crossing ISO International standards organization (sensitivity to light) LA Lipoic acid LED Light-emitting diode MES 2-(N-Morpholino)ethanesulfonic acid MMP Matrix metalloproteinases MW Molecular weight MWCO Molecular weight cut-off NAv NeutrAvidin nb Non-bonding orbital NB Norbornene NHS N-Hydroxysuccinimide Ni-NTA Nickel(II) nitrilotriacetic acid NIR Near infrared NMR Nuclear magnetic resonance Norm. Normalized PAA Poly(acrylic acid) PAMAM Poly(amidoamine) PBS Phosphate buffered saline PEG Poly(ethylene glycol) PES Poly(ethersulfone) PL Photoluminescence Prb Probe-strand oligonucleotide Q Quenching efficiency QD Quantum dot QY Quantum yield R channel Red channel RCF Relative centrifugal force RGB Red-green-blue xxxiii RGD Arginylglycylaspartic acid ROI Regions of interest sCMOS Scientific complementary metal-oxide-semiconductor sCy5.5 Sulfo-Cyanine 5.5 SiNC Silicon nanocrystal STGIP Smartphone-based time-gated imaging platform Tb Tb cryptate (Lumi4-Tb) TBE Tris-borate-ethylenediaminetetraacetic acid TCO trans-Cyclooctene TEM Transmission electron microscopy TEMED Tetramethyl ethylenediamine TG Time-gated Tgt Target-strand oligonucleotide TGA Thermogravimetric analysis TMAH Tetramethylammonium hydroxide TMSM 3-(Trimethoxysilyl)propyl methacrylate TR Time-resolved TRP Trypsin Tz Tetrazine UCNP Upconversion nanoparticle UV Ultraviolet vis Visible VLP Virus-like nanoparticle VR Vibrational relaxation xxxiv Acknowledgements I sincerely thank my supervisor, Prof. W. Russ Algar, who gave me a great opportunity to work in his group and to fulfill myself. Research never went smoothly, and writing definitely is not my strength. I sincerely appreciate Prof. Algar continuously helping with my research and providing kind guidance in writing manuscripts and my thesis. I couldn’t imagine reaching this stage of my Ph.D. journey without all of his support over the past years. I would also like to thank Prof. Jayachandran Kizhakkedathu, Prof. Karen Cheung, and Prof. Roman Krems for their helpful feedback as my supervisory committee members. I thank the providers of my graduate scholarships—a Four-Year Fellowship from UBC, the NanoMat training program from NSERC CREATE, and a Taiwanese Government Scholarship to Study Abroad from Taiwan—for relieving my financial burden. I sincerely thank Dr. Saeid Kamal at the Laboratory for Advanced Spectroscopy and Imaging Research, UBC Department of Chemistry, for training and assisting me with various instruments for lifetime measurements. I am also grateful to Prof. Mark MacLachlan for providing access to the DLS instrument and to Prof. Zachary Hudson and his research group for assisting with instrument operation for some experiments. I am also thankful to many technical and support staff within the UBC Department of Chemistry for their help and training me on various instruments. I also thank Prof. Jonathan G. C. Veinot, Christopher Jay Robidillo, Ziqi Li, Gunwant K. Matharu, Kevin O’Connor, I Teng Cheong, and Chuyi Ni from the University of Alberta Department of Chemistry for providing silicon nanocrystals and the TEM images. xxxv I would also thank all of my past and present labmates and friends in the Algar group. Special thanks to Rupsa Gupta, Ghinwa H. Darwish, and Tiffany Jeen for always being there when I needed them, for taking care of me, and for discussing research; Jérémie Asselin for helping my English and bringing hope into my lab life; Zhujun Xiao for being a good listener; Sahil S. Kanani and Daina V. Baker for the helpful MATLAB tutorials; Michael V. Tran and Hyungki Kim for training me on lab instruments; Dr. Melissa Massey for discussing cFRET; Kelly Rees and Katherine D. Krause for being supportive; Cristine Traaseth and Agnes Szwarczewski for bringing fun things to the lab to bring everyone closer together; and Jack Xue for giving me an opportunity to be a mentor. I also thank Kelsi Lix, Dr. William J. Peveler, Rehan Higgins, Jasmine Bernal Escalante, Yihao Wang, Seth Keenan, and Luigi Alde for making my Ph.D. journey more colourful. I would like to thank my Taiwanese friends. Special thanks to Szu-Ping Huang for being a shoulder to cry on; Si-Han Wu for keeping me motivated and being a nice senior to guide me; and all my Taiwanese friends in Canada for accompanying me to explore new cultures and discover new places when I newly arrived in Canada. Home is always my strong and powerful support system. I am sincerely grateful to my parents, brother, sister-in-law, Euka, and all other family members for being super important supports, so I can be fearless to step outside my comfort zone and be in Canada to pursue myself. Pursuing Ph.D. abroad is not an easy thing for me. From applying for graduate school to reaching the current step, countless challenges needed to be overcome. I couldn’t accomplish all of this alone—I am sincerely grateful to everyone who provided any kind of help in the past decade. 1 Chapter 1: Introduction Several subsections in this chapter are adapted from published work. The adaptions are reproduced from: (1) Algar, W. R.; Massey, M.; Rees, K.; Higgins, R.; Krause, K. D.; Darwish, G. H.; Peveler, W. J.; Xiao, Z.; Tasi, H.-Y.; Gupta, R.; Lix, K.; Tran, M. V.; Kim, H., Photoluminescent Nanoparticles for Chemical and Biological Analysis and Imaging. Chem. Rev. 2021, 121, 9243−9358, with permission from the American Chemical Society. (2) Tsai, H.-Y.; Kim, H.; Massey, M.; Krause, K. D.; Algar, W. R., Concentric FRET: a Review of the Emerging Concept, Theory, and Applications. Methods Appl. Fluoresc. 2019, 7, 042001, with permission from IOPscience. The manuscripts were co-written by all the authors with input and final editing from Prof. W. R. Algar. Refer to Preface for detailed author contributions. 1.1 Fluorescence and phosphorescence Luminescence is a phenomenon in which electronically excited species relax back to their ground states by emitting light. The emission wavelengths range from ultraviolet (UV) to infrared (IR) region, depending on the molecule or material. Luminescence can be classified into several different categories according to the excitation method.1 For example, photoluminescence (PL) occurs when the emitters are excited by absorbing light, and chemiluminescence occurs when the emitters are excited by chemical reactions.1 Notably, PL can be divided into fluorescence and phosphorescence, which occur without and with changes in spin multiplicity prior to emitting light, respectively. 2 1.1.1 Perrin−Jablonski diagram A Perrin−Jablonski diagram is widely used for explaining the process of PL (Figure 1.1). In most cases, the multiplicity of electronic ground state is singlet (S), so the ground state is represented as S0. Similarly, S1 and S2 denote the first and second singlet excited states, respectively; and T1 denotes the first triplet excited state. The energy level separation between two electronic states are on the order of 1−10 eV (ca. 8 000−80 000 cm−1).2 Each electronic level contains many vibrational levels, which are denoted v0, v1, v2, etc., having 0.05−0.5 eV (ca. 400−4 000 cm−1) energy separation with its adjacent vibrational levels. Each vibration level can be further divided into multiple rotational levels with about 0.005 eV spacing (not shown in the figure).2 The energy of UV, visible, and NIR light (200−800 nm) is ca. 6.2−1.5 eV, which is suitable for electronically exciting molecules (e.g. S0 → S1 or S0 → S2). When a molecule absorbs a photon of adequate energy, a valence electron (highest occupied molecular orbital, HOMO) is promoted from the ground state to one of its electronic excited states. The excited molecule (Franck–Condon state) returns to S1v0 rapidly via vibrational relaxation (VR) and, if the initial excited state is S2vn or higher, internal conversion (IC). VR is a non-radiative process that dissipates some of excitation energy as heat to the surrounding bath. Fluorescence is observed when the molecule returns to its electronic ground state (S0vn) through emission of a photon. Subsequent VR returns the molecule to S0v0. Instead of relaxing via fluorescence, an excited molecule (S1v0) may also undergo non-radiative IC and VR back to S0v0. A molecule at S1v0 may also undergo intersystem crossing (ISC), where the spin multiplicity changes to triplet (T1vn) and the excited molecule relaxes to T1v0 via VR. Phosphorescence is observed when the molecule in T1v0 returns to the ground state (S0vn) via photon emission concurrent with a change 3 in multiplicity. More detail about absorption, fluorescence, and phosphorescence are discussed in the following sub-sections. Figure 1.1 Fundamental fluorescence concepts. (A) Perrin−Jablonski diagram showing how absorption leads to fluorescence and phosphorescence. (i) Absorption: a molecule absorbs light and an electron is promoted to an excited state (S0v0 → S1vn or S2vn). (ii) Kasha’s rule: an excited molecule (Franck–Condon state) rapidly returns to the S1v0 state through vibrational relaxation (VR) and, where applicable, internal conversion (IC). (iii) Fluorescence: an excited molecule returns to the electronic ground state (S0vn) via emission of a photon. (iv) Intersystem crossing (ISC): the spin multiplicity changes from singlet to triplet (S1 → T1). (v) Phosphorescence: an excited molecule returns to the electronic ground state via emission of a photon (T1v0 → S0vn). (B) Generic illustration of absorption, fluorescence, and phosphorescence spectra and the corresponding electronic transitions from the Perrin–Jablonski diagram. Adapted from ref.3 4 1.1.2 Absorption spectra Absorption only occurs when the energy of excitation light matches the energy gap between the initial and the final states (S0v0 → S1vn or S2vn). The spectral position of an absorption band is mainly determined by the energy differences between two electronic states (e.g. S0→S1 or S0→ S2), whereas the shape of the absorption band is determined by the relative probability of the vibrational transitions between the ground state and the possible vibrational states of the excited electronic state. At room temperature, the thermal energy (𝑘𝐵𝑇) is much lower than ∆𝐸𝑣𝑖𝑏 (0.026 eV versus 0.25 eV), such that a negligible fraction of molecules occupies an excited vibrational state (as per the Boltzmann distribution). Thus, at room temperature, absorption only occurs from the ground electronic and vibrational states (S0v0). The absorption is a very fast process (ca. 10−15 s), whereas the nuclear motion is at least a thousand-fold slower (ca. 10−10−10−12 s).4 During the rapid electronic transition of absorption), the nuclei of the molecule and its surroundings do not move. This phenomenon is Franck–Condon principle, which stipulates a vertical transition on a Perrin–Jablonski diagram, where the final state is called Franck–Condon state (Figure 1.2).4 The intensity or probability of the transition is positively correlated with the overlap of the initial and final wavefunctions, e.g. S0v0 (initial) and S1v2 (final) states. The shape of the absorption peak (and shoulders or other features) is thus determined by the overlap between wavefunctions of different vibrational levels (e.g. overlap of S0v0 with S1v0 versus S1v2, S1v3, and so on). The Perrin–Jablonski diagram suggests that line spectra should be observed; however, in most cases, band-shape spectra are observed. The broadening result from the interactions of the 5 absorbing molecule with surrounding molecules, which distort energy levels and create a distribution of transition energies for each formal transition on a Perrin–Jablonski diagram. Line-shape absorption spectra only can be observed when sample is in vapor form, where the rotational and vibrational sub-transitions of electronic transitions become visible.4 Figure 1.2 Illustration of the Franck–Condon principle and how it contributes to the shape of spectrum. (A) A transition for absorption is most probable when the initial and final wavefunctions have maximum overlap, which is S0v0 → S1v3 in this illustration (and likewise for S1v0 → S0v3 for fluorescence emission). (B) Labelled contributions to an absorption spectrum and fluorescence emission spectrum according to the wavefunctions in panel A. The Beer-Lambert law quantifies a chromophore’s absorption of light at a specific wavelength, as defined by Eqn. 1.1: 𝐴(𝜆) = −log𝑇(𝜆) = log (𝐼0(𝜆)𝐼(𝜆)) = 𝜀(𝜆)𝑏𝑐 (1.1) 6 where 𝐴(𝜆) is the measured absorbance, 𝜆 is the wavelength, 𝑇(𝜆) is the transmittance, 𝐼0(𝜆) is the incident light intensity before entering the sample, 𝐼(𝜆) is the remaining light intensity after passing through the sample, 𝜀(𝜆) is molar absorption coefficient of the chromophore, b is the path length of light passing through the sample, and c is the concentration of the chromophore. In many cases, the values of molar absorption coefficients are known (a larger molar absorption coefficient indicates the more probable electronic transition), such that a chromophore’s concentration is readily determined by the Beer-Lambert Law. Otherwise, a molar absorption coefficient of a chromophore is determinable from a series of known concentrations and measured absorbance values, where the molar absorption coefficient is the slope of a plot of absorbance versus concentration. 1.1.3 Emission spectra A molecule will relax almost immediately after excitation to the Franck–Condon state (S0v0 → S1vn or S2vn). According to the Kasha’s rule, the excited molecule relaxes to the lowest electronic excited state (S1v0) via VR (from S1vn) or via a sequence of VR, IC, and VR (from S2vn). This is a rapid process, since the time scale for VR and IC are 10−12−10−10 and 10−11−10−9 s, respectively.3 Subsequently, the excited molecule returns to ground state through radiative (i.e. fluorescence or phosphorescence) or non-radiative pathways (i.e. IC followed by VR). Fluorescence is the radiative transition from the lowest singlet excited state to the electronic ground state (S1v0 → S0vn). The time scale for photon emission is 10−15 s (as fast as photon absorption);3 however, the excited electron resides in the S1v0 state for 10−10−10−7 s before emitting light. This time is the main contribution to the fluorescence lifetime of a molecule (vide infra). As 7 a result of Kasha’s rule for emission only from the S1v0 state, emission spectra do not depend on the excitation wavelength.5 Another consequence is that fluorescence emission spectra are shifted to longer wavelengths than the absorption spectra, with the difference between absorption and emission peaks known as the Stokes shift.5 The emissive transitions also follow the Franck–Condon principle, such that the fluorescence emission spectrum is approximately a mirror image of the absorption spectrum.5 Phosphorescence is the radiative transition from the lowest triplet excited state to the electronic ground state (T1v0 → S0vn). After being excited and relaxing to the S1v0 state, ISC occurs with a change spin multiplicity for an S1v0 → T1vn transition. The timescale of intersystem crossing is typically 10−10−10−8 s in phosphorescent molecules (and much slower in non-phosphorescent molecules).3 Subsequently, the excited molecule relaxes to T1v0 state through VR, which is followed by emission of a photon as phosphorescence. Before emitting this photon, the excited electron typically resides in the T1v0 state for 10−6−1 s,3 which is the cause of the long-lived characteristic of phosphorescence. Based on Hund’s rule, the energy level of the lowest triplet excited state (T1) is lower than the lowest singlet excited state (S1), which leads to phosphorescence spectra being shifted to longer wavelengths than fluorescence spectra. 1.1.4 Quantum yield and lifetime The fluorescence quantum yield (∅) and lifetime (𝜏) are controlled by the rates of radiative and non-radiative processes. The fluorescence quantum yield is the fraction of excited molecules that relax to the ground state (S0) by emitting a photon from S1v0, which is defined as Eqn. 1.2: 8 ∅ = 𝑘𝑓𝑘𝑓 + ∑𝑘𝑛𝑟 (1.2) ∑𝑘𝑛𝑟 = 𝑘𝐼𝐶 + 𝑘𝐼𝑆𝐶 + 𝑘𝐸𝑇 + 𝑘𝑄 + 𝑘𝑝𝑑 … (1.3) where 𝑘𝑓 is the decay rate constant of fluorescence and 𝑘𝑛𝑟 is the rate constant of non-radiative relaxation. The non-radiative rate constant can be broken down in the sum of 𝑘𝐼𝐶 , 𝑘𝐼𝑆𝐶 , 𝑘𝐸𝑇 , 𝑘𝑄,and 𝑘𝑝𝑑, which are the decay rate constants of IC, ISC, energy transfer, quenching processes, and photodegradation, respectively. The quantum yield scales between 0 to 1. It is often oversimplified that a molecule material is bright when it has a fluorescence quantum yield close to unity. Formally, brightness is a product of molar absorption coefficient and quantum yield.6,7 Thus, a molecule or material with high absorption coefficient and high quantum yield is expected to be bright since its both absorbs and emits photons more efficiently. The PL lifetime is a measure of the average time a molecule stays in its excited state before emitting fluorescence and is defined as Eqn. 1.4: 𝜏 = 1𝑘𝑓 + ∑𝑘𝑛𝑟= ∅𝑘𝑓 (1.4) Typically, fluorescence intensity after pulsed excitation follows first-order kinetics, where the concentration of the excited-state molecule as a function of time is described by Eqn. 1.5: [𝑆1(𝑡)] = [𝑆1]0 ∙ 𝑒−(𝑘𝑓+ ∑𝑘𝑛𝑟)𝑡 = [𝑆1]0 ∙ 𝑒−𝑡 𝜏⁄ (1.5) 9 where t is time, [𝑆1(𝑡)] is the concentration of the excited state molecules at time t, [𝑆1]0 is the initial concentration of the excited state molecules. Since the population of excited state molecules is proportional to the measured fluorescence intensity, Eqn. 1.6 is obtained: 𝐼(𝑡) = 𝐼0𝑒−𝑡 𝜏⁄ (1.6) where 𝐼(𝑡) is PL intensity when time is t, and 𝐼0 is the initial PL intensity. Fluorescence emission is a stochastic process, where each molecule only emits one photon, and the distribution of times across a population of molecules follows first-order kinetics.5 According to Eqn. 1.6, 63% of excited molecules have returned to the ground state before the lifetime (𝜏) has elapsed after excitation. Accordingly, 37% of excited molecule remain at its excited state. Eqn. 1.6 is a mono-exponential decay, which can be used for describing a homogeneous sample with a single emissive pathway (e.g. well-dissolved fluorescein solution). For heterogeneous samples and/or multiple emissive pathways, bi-exponential or tri-exponential decays will often better describe fluorescence decays. In these cases, an amplitude-weighted average lifetime or an intensity-weighted lifetime is used to produce a single value for the fluorescence lifetime. 1.1.5 Steady-state and time-resolved measurement PL measurements can be roughly divided into two categories: steady-state and time-resolved measurements.5 Steady-state PL measurements are the most common approach. Emission intensities (or spectra) are collected while the samples are continuously illuminated, resulting in an equilibrium condition where the ground-state and excited-state population are constant from equal rates of excitation and relaxation. Time-resolved measurements record PL intensities as a function of time, mostly commonly after excitation of a samples with a short excitation pulse.5 The 10 dynamic change of the excited state population is thus measured, corresponding to the fluorescence lifetime with sufficient time points and resolutions. Lifetime-measuring techniques in the time domain include time-correlated single photon counting, multi-channel scaling, and streak imaging. Time-gated PL measurements are made by collecting PL intensities (or spectra) at a defined delay time after the excitation pulse (Figure 1.3). The difference versus time-resolved PL measurements is that PL intensity is not recorded at multiple time points, but rather ignored for a set duration then integrated into a single value for another duration. Time-gated measurement can be used for gating out short-lifetime background (e.g. scattered excitation light, biological autofluorescence with a lifetime on order of nanoseconds) to improve signal-to-background ratio. Since short-lived signals are rejected, this time-gated measurement is only suitable for materials with long PL lifetimes. Figure 1.3 Time-gated measurement. The PL intensity is collected immediately after a short excitation pulse (the pulse ends at time is 0). The emission is only collected after short-lived background (gold curve) has fully decayed, such that the background is rejected. 11 Box-car measurements are a method from which a PL decay is derived from time-gated PL measurements.8,9 The time-gated PL intensities is recorded with a fixed integration time window at various delays following pulsed excitation. The PL decay is generated by plotting the time-gated PL emission intensities against various delay time. A shorter integration and more delay time points will provide a higher resolution PL decay curve. 12 1.2 Fluorescent and luminescent materials The development of photoluminescent probes is motivated by the intrinsic photophysical properties of the materials. A wide range of luminescent materials have been studies and used to develop luminescent probes for biological applications. Table 1.1 summarized the photophysical properties of several different photoluminescent materials. Table 1.1 Photophysical properties of selected photoluminescent materials.10 Material Conventional Dyes Lanthanide complexes II-VI QDsc VI QDs (SiNCsd) Size (nm) <2 <2 1−10 1−10 Excitation Rangea (nm) UV−NIR-II UV UV−vis UV−vis Extinction Coefficientb (M−1 cm−1) 104−105 104 105−107 104−105 Emission Rangea (nm) vis−NIR-II UV−NIR-II vis−NIR-I vis−NIR-I Emission FWHM (nm) 25−50 (vis) 40−150 (NIR) 15−30 (vis) 50−100 (NIR) 25−75 100−200 Quantum Yield 0.1−0.9 0.1−0.6 0.1−0.9 ≤0.7 Lifetime (s) 10−10−10−8 10−6−10−3 10−9−10−8 10−6−10−4 a Wavelength ranges: UV (200−400 nm), vis (visible, 400−650 nm), NIR-I (650−950 nm), and NIR-II (1000−1800 nm). b Extinction is the sum of absorption and scattering. For conventional dyes and lanthanide complexes, the values are equal to their absorption coefficients. c QDs: quantum dots. d SiNCs: silicon nanocrystals. 13 1.2.1 Conventional fluorescent dyes Conventional fluorescent dyes are organic molecules with extended π conjugated systems, so most of their structures have aromatic rings. The molecular weights of the fluorescent dyes are usually less than 2 kDa, and the physical dimensions are smaller than 2 nm.10 Dyes can be categorized into different categories according to the general structure of the fluorescent scaffolds: e.g. xanthenes, cyanines, coumarins, and boron-dipyrromethenes (Figure 1.4).5,10,11 Figure 1.4 Central core structure for four common families of fluorescent dyes: xanthene, cyanine, coumarin, and boron-dipyrromethene. Adapted from ref.11 Copyright 2021 Wiley-VCH GmbH. The molar absorption coefficients of dyes are typically 104−105 M−1 cm−1.10,12 The value increases as their π conjugation systems increase.5 The absorption and emission spectra of each fluorescent dyes are approximately mirror images with 15−30 nm Stokes shifts.10,11 In general, larger Stokes shifts are preferred for biological applications because crosstalk from excitation light is more easily minimized (providing better signal-to-background ratio) and self-quenching resulting from self-absorption also is more easily avoided.13,14 The emission peaks are usually asymmetric, with a 14 shoulder on the long-wavelength side. The full-width-at-half-maximum (FWHM) is 20−50 nm for spectra with modest shoulders and 30−80 nm peak for spectra with pronounced shoulders.10,12 The emission of fluorescent dyes results from π* → π transition (several cases are from π* → nb) from the extended conjugation system. The transition energy decreases as the conjugation increases, such that absorption and emission red-shift.5 Fluorescence properties are also controlled by the rigidity of the structure and the substituents on the molecules. The quantum yield of dyes varies from 0.1 to 0.9, and the PL lifetime is ca. 1−10 ns.10 In general, more rigid molecules have higher quantum yield and shorter lifetime. Fluorescent dyes have the longest development history. The options for the emission colours span a wide spectral range from ultraviolet (UV) to near-infrared (NIR). Versatile functionalities are available for different biological settings and labelling reactions. Also, several modern technologies have been developed based on the properties of fluorescent dyes.15 Flow cytometry is an example where a combination of a multicolour laser array and a multicolour detector array enables double-digit multiplexing, which relies on both excitation and emission wavelength to distinguish signals from different dyes.15 Fluorescent dyes are still one of the most widely used fluorescent materials in biological applications. 1.2.2 Lanthanide complexes Most of the trivalent lanthanide (Ln3+) ions are luminescent. Their emission spectra comprise multiple narrow peaks, which result from shielded 4f−4f transitions. The emission peaks of Ln3+ are across UV to NIR spectral regions (mostly in visible to NIR range).16 The excited state lifetimes are long, being in the microsecond to millisecond range.17–20 Since the 4f−4f transition are Laporte-15 forbidden transition, absorption coefficients are very weak (< 3 M−1 cm−1).19 The luminescence of Ln3+ ion is also quenched by water molecules.21 The resulting low brightness of luminescence is a drawback, so solely using Ln3+ ions for applications is not practical. A lanthanide complex is composed of a Ln3+ ion and organic ligand(s) (e.g. chelates or cryptates). The physical dimension of a lanthanide complex is less than 2 nm.10 The ligands coordinate with a central Ln3+ ion and serves as a “cage” and “antenna” for the ion. The “cage” function is used for protecting from quenching of the ion with the surrounding molecules. The “antenna” function is used for increasing light absorption to overcome the low absorption coefficients of ions. The ligands usually are usually chromophores with molar absorption coefficients ~104 M−1 cm−1 at wavelengths > 100 nm shorter than the emission of the Ln3+.10,20 Multiple steps are involved to have luminescence (Figure 1.5).19,20 First, the excitation light is absorbed by the ligands, and the ligands are excited to their excited singlet sate. Next, an ISC happens so that singlet state passes to a triplet state non-radiatively. Third, the energy transfers from the excited-triplet-state ligands to the Ln3+. Lastly, emission is observed through the radiatively relaxation of the Ln3+ ion. It is possible that the energy transferred directly from excited singlet state ligand to Ln3+, but it’s might not be efficient because of the short-lived singlet state.19 The radiative and non-radiative relaxation processes of the ligands and back-energy transfer from the Ln3+ to the ligands compete with the luminescence process. The ligands thus play an important role in optimizing Ln3+ luminescence. 16 Figure 1.5 Photoluminescence mechanism of lanthanide complexes. Multiple steps are involved: (i) ligand excitation by photon absorption; (ii) intersystem crossing from the singlet excited state to the triplet excited state of the ligand; (iii) energy transfer from the ligand to the lanthanide ion; (iv) relaxation of the lanthanide ion by photon emission. Tb3+ and Eu3+ complexes are the most commonly used luminescent lanthanide complexes for biological studies.21,22 A Tb complex, Lumi4-Tb, is the main focus in this paragraph since it is used in this thesis. Figure 1.6A−B shows the structure of Lumi4-Tb and the absorbance and the emission spectra. The macrocyclic ligand absorbs in the UV range and the emission peaks are in visible range. The large “Stokes shift” helps to minimize unwanted signal from the excitation light. Lumi4-Tb is advantageous as a FRET donor because the emission peaks are narrow and well separated across the visible range, allowing for effective spectral overlap (between donor emission and acceptor absorption) with several different FRET acceptors with minimum crosstalk (between donor and acceptor emission; Figure 1.6C). The lifetime of Lumi4-Tb is around 2.6 ms, which is longer than most conventional dyes and autofluorescence background from biological matrices. This long lifetime enables time-gated measurements (see Section 1.1.5). Since the autofluorescence from biological samples are usually in nanosecond scale,23 the combination of 17 Lumi4-Tb and time-gated measurements are a perfect fit for bioanalysis to reject short-lifetime background signal. Figure 1.6 Lumi4-Tb. (A) The structure of Lumi4-Tb. (B) The absorption (black data) and emission (green data) spectra of Lumi4-Tb. (C) The multiple narrow and well separated emission peaks from Tb3+ (black data) enable its pairing with multiple fluorophores (coloured data) for multiplexed (bio)sensing with minimum crosstalk (shaded area). Adapted from ref.21 Copyright 2014 Elsevier. 1.2.3 Quantum dots Semiconductor quantum dots (QDs) are inorganic nanocrystals having core diameters ca. 1−10 nm.10,24 A QD is approximately an example of “particle in a box.”24 As the bulk material reduces in size to the nanoscale, the energy levels become discrete at the conduction and valence band edges. The band gap will increase as the nanoparticle diameter is reduced through an effect known as quantum confinement, so the absorption and photoluminescence of QDs is size-dependent. Based on the compositions of the core structure, QDs can be categorized into several different groups (e.g. II−VI QDs with a cadmium chalcogenide core, IV QDs with Si or Ge core, and IV-VI QDs with a lead chalcogenide core).10 18 1.2.3.1 II-VI QDs Common cadmium chalcogenide QDs are based on CdS, CdSe, and CdTe cores. According to the quantum confinement effect, the emission wavelength is related to the core size of the QD; however, the core structure does not provide an infinite potential barrier (confinement is not complete). In addition, trap states caused by surface dangling bonds, structural defects, and adsorbates promote non-radiative exciton recombination, which lead to decrease photoluminescent efficiency for the QDs.25 Thus, in most biological applications, a shell structure is introduced for providing better confinement, passivating the surface of the core, and protecting the core from interaction with the environment. A layer of structurally similar semiconductor is preferred. ZnS is the most common shell for II-VI QDs because of its structural similarity and because its higher band gap energy provides better confinement of the exciton.26 Figure 1.7A shows a TEM image of CdSe/ZnS QDs. A 5−10 nm red shift of the emission peak is typically observed after growing a shell around the core.26 For biological applications, a layer of organic hydrophilic ligands is required on top of the core/shell structure. Figure 1.7B shows an anatomy of core/shell QD with various surface modifications. The photoluminescence of QDs is the result of recombination between an excited electron and a hole, where the colour of QD emission depends on the band gap energy. The band gap increases as the nanoparticle diameter is reduced. The band gap energy of II-VI QDs (CdS, CdSe, and CdTe) is ca. 1.5−3.2 eV, which covers the entire visible range.10 Figure 1.7C shows photograph and emission spectra of the CdSe/ZnS QDs with different core sizes. The absorption spectra of QDs are broad, such that QDs can be excited with wide range of excitation wavelengths. The molar absorption coefficients of II-VI QDs are typically 105−107 M−1 cm−1 and the quantum yields are 19 in the range of ca. 0.1−0.9.10 The combination of large molar absorption coefficient and good quantum yield leads to high brightness. In addition, the narrow emission peak makes QDs an outstanding material for multiplexed detection with minimal crosstalk. Usually, high quality of II-VI QDs can be obtained through well-established synthetic methods. For example, solvothermal methods produce highly monodisperse QDs where the FWHM of the photoluminescent peaks are ca. 25−40 nm.10,27 In general, the photoluminescent decay of II-VI QD is multiexponential decay, and the average lifetime is ca. 10−50 ns.10 Among different categories of QDs, the II-VI QDs are the most widely used materials, due to the outstanding PL properties.10 Particularly, the core/shell CdSe/ZnS QDs are so-called the “flagship” materials that widely used for biological applications.26 Figure 1.7 CdSe/ZnS QDs. (A) TEM image of a single CdSe/ZnS QD. (B) Anatomy of core/shell structure of QD with a layer of organic ligand. (C) Cartoon, photograph, and emission spectra of the CdSe/ZnS QDs with different core sizes. Adapted from ref.27 Copyright 2011 American Chemical Society. 20 1.2.3.2 IV QDs Silicon QDs are more often called silicon nanocrystals (SiNCs). These materials comprise a crystalline silicon core with a layer of functionalization on its surface and have typical dimensions of 1.5−10 nm.28–31 Figure 1.8A shows TEM images of SiNCs with three different sizes.32 Germanium nanocrystals are in many ways analogous materials to SiNCs31,33 but are less developed and applied. Figure 1.8 SiNCs (Si QDs). (A) TEM images of SiNCs with three different sizes (3, 6, and 9 nm). (B) Functionalization of hydride-terminated SiNCs with dodecane via hydrosilylation methods. (C) PL emission spectra of the different-sized SiNCs from panel A. Reproduced from ref.32 Copyright 2017 American Chemical Society. Common methods for the synthesis of SiNCs include reduction of silicon halides (e.g. SiCl4), reaction of metal silicides (e.g. MgSi), and thermal decomposition of organosilanes and silicon oxides (e.g. silsesquioxane).28–32 The resulting SiNCs are typically hydride-, halide-, or oxide-terminated, with the latter tending to be further etched to give hydride-terminated SiNCs. Hydride- and halide-terminated NCs are sensitive to oxygen and moisture, such that surface passivation and stabilization are required to preserve the structure and properties of the materials.29–31 In contrast 21 to the aforementioned II-VI QDs, the growth of a shell of an inorganic semiconductor around SiNCs has, to date, been largely ineffective, impractical, and uncommon. Instead, the surface is covalently modified with organic molecules. For hydride-terminated SiNCs, the preferred surface passivation reactions are hydrosilylation, as illustrated in Figure 1.8B, whereas for halide-terminated SiNCs, the preferred reactions are those with Grignard and alkyllithium reagents, yielding Si−C bonds in all cases.29,30,32,34 Other reactions that introduce Si−O and Si−N bonds (e.g. reaction of amines with halide-terminated SiNCs) are also possible; however, these reactions often modify the PL properties. Some SiNCs are aptly described as “Si QDs” because PL emission arises from quantum confinement. These materials tend to be ∼5 nm or less in diameter, as the exciton Bohr radius for Si is ca. 4.5 nm.28,29,31 Analogous to that from other materials, PL from quantum confinement shifts to shorter wavelengths as the nanocrystal size decreases. For SiNCs, the practical size-tuning range has, to date, been from green/yellow to NIR PL emission (ca. 500−1000 nm). The FWHM values for ensemble PL spectra are 100−200 nm, and the QYs are as high as 0.7.28–30 Figure 1.8C shows PL emission spectra for SiNCs with three different sizes.32 As silicon is an indirect-band-gap material (electronic transitions must be phonon-assisted), excitons recombine more slowly than in direct-band-gap materials (e.g. CdSe), and the PL lifetimes are on the order of microseconds. These quantum-confined PL properties are most frequently obtained with SiNCs synthesized at higher temperatures (>160 °C).29 Another consequence of the indirect band gap is weaker light absorption by SiNCs compared with direct-band-gap QD materials, for which the molar extinction coefficients are estimated as 104−105 M−1 cm−1.35,36 The absorption spectra are relatively featureless but likewise increase in intensity from the band gap energy toward the UV. 22 In other cases, SiNCs exhibit PL emission from surface or other defect states. This PL generally ranges from the UV through blue/green and has lifetimes on the order of 1−10 ns and QYs of 0.1−0.3.29 Lower-temperature syntheses (<160 °C) more frequently produce SiNCs with such PL characteristics, as do certain surface modifications, particularly those that yield Si−N and Si−O bonds.29 The PL mechanism and properties (e.g. QYs, lifetimes) of SiNCs can have a nonmonotonic relationship with the surface area-to-volume ratio (and thus the SiNC size) because of the competing effects of quantum confinement and the magnitude of the influence of surface states.34 The latter includes both radiative and nonradiative relaxation pathways associated with surface states. The selection of surface chemistry for SiNCs is, on one hand, driven by the need to passivate the nanocrystal surface and retain the desired PL properties. On the other hand, it is driven by requirements for colloidal stability and downstream (bio)conjugation reactions. The most common functionalization strategies use bifunctional reagents or mixtures of bifunctional reagents with hydride-terminated SiNCs.37–39 One functionality is an alkene or alkyne group for hydrosilylation, and the other (usually distal) functionality is either polar (e.g. PEG) or suitable for further functionalization or conjugation reactions (e.g. alkene, carboxyl, amine). There are indications that the characteristics of the distal functional group and the bonding to the SiNC can affect PL properties. 23 1.3 FRET and concentric FRET Bioconjugation enables luminescent materials to selectively target and interact with other biological molecules. Having a mechanism of turning luminescence “on” and “off” in response to these interactions with biomolecules enables biosensing.40,41 Förster resonance energy transfer (FRET) is a powerful mechanism for this luminescence modulation. 1.3.1 FRET theory FRET is an energy transfer process between a fluorophore (or luminescent nanoparticle) and a chromophore, in the roles of energy donor (D) and acceptor (A), respectively.40–42 In many cases, the acceptors are a different type of luminescent materials versus the donor, although acceptors can also be dark quenchers (i.e. negligible emission quantum yield) or the same material as the donor (a.k.a homo-FRET). The FRET process is summarized with a Jablonski diagram in Figure 1.9. First, a donor is excited by incident light. The energy transfers from excited donor to a ground-state acceptor through a dipole-dipole interaction. This energy transfer is a non-radiative process, so no photon is emitted during the transfer process (i.e. the donor does not emit light). Then, the sensitized acceptor releases the transferred energy via emitting light or via non-radiative mechanisms. Since FRET is a resonance propagation, the energy transferred from a donor needs to be equal to the energy received by acceptor; that is, spectral overlap between the emission of the donor and the absorption of the acceptor is required for FRET to take place. FRET efficiency is highly dependent on the distance between the donor and acceptor, with the efficiency increasing (FRET is turned “on”) as a power function as the distance decreases. The changing of FRET efficiency can be used for measuring the donor-acceptor distance, so FRET is also known as “spectroscopic ruler.”40,42 The typical distance range for FRET is ca. 1−10 nm (although it can be 24 up to 20 nm for certain FRET pairs),40,41 which is similar to the size of biomolecules. Therefore, FRET is a tool that is widely used in biological and biochemistry fields. Figure 1.9 Jablonski diagram for FRET. Energy transfers from an excited-state donor to a ground-state acceptor via a non-radiative process, which is represented as a green solid arrow. The energy lost by the donor is equal to the energy gained by the acceptor, which is reflected by the dashed arrows of the same length. FRET equations have been successfully derived from classical and quantum mechanical theories.43,44 The FRET donor and acceptor are approximated as point-diploes. The energy transfer is described as a dipole-dipole coupling, which is a Coulombic interaction. From the perspective of a quantum mechanical transition dipole interaction, the FRET rate constant (donor-to-acceptor transition probability per unit of time) can be expressed as using Fermi’s golden rule: 𝑘𝐹𝑅𝐸𝑇 = 2𝜋ℏ|𝑉𝐶𝑜𝑢𝑙|2𝜌 (1.7) where 𝑘𝐹𝑅𝐸𝑇 is the FRET rate constant, ℏ is the reduced Planck constant, 𝑉𝐶𝑜𝑢𝑙 is a Coulombic interaction term that describes the transition dipole-dipole interaction, and 𝜌 is the density of 25 isoenergetic states between donor and acceptor, which is related to spectral overlap between donor emission and acceptor absorption. The Coulombic interaction term can be expressed as 𝑉𝐶𝑜𝑢𝑙 = 𝜅|𝜇𝐷⃗⃗ ⃗⃗ ||𝜇𝐴⃗⃗⃗⃗ |4𝜋𝜀0𝑛2𝑟3 (1.8) where 𝜇𝐷⃗⃗ ⃗⃗ is the transition dipole moment corresponding to donor emission, 𝜇𝐴⃗⃗⃗⃗ is the transition dipole moment corresponding to acceptor absorption, 𝜅 is the orientation factor between donor and acceptor dipole moments, 𝜀0 is the vacuum permittivity, 𝑛 is refractive index, and 𝑟 is the distance between donor and acceptor. The squared of the transition dipole moments are related to oscillator strength which is related to natural emission lifetime of the donor (𝜏𝐷𝑛𝑎𝑡 = 𝜏𝐷 𝜙𝐷⁄ ) and the molar absorption coefficient of the acceptor (𝜀𝐴).40,44 Eqn. 1.9 is obtained by substituting Eqn. 1.8 into Eqn. 1.7 with transformation of the transition dipole moment terms to lifetime- and absorption coefficient-related terms, and then part of the transformed dipole moment terms are combined with 𝜌 to form spectral integral term (𝐽). 𝑘𝐹𝑅𝐸𝑇 =9(𝑙𝑛10)𝜅2𝜙𝐷128𝜋5𝑁𝐴𝑛4𝜏𝐷𝑟6𝐽 (1.9) where 𝜙𝐷 is quantum yield of the donor, 𝑁𝐴 is the Avogadro’s number, 𝜏𝐷 is measured lifetime of donor without acceptor. The natural lifetime of donor (𝜏𝐷𝑛𝑎𝑡) can be calculated from measured lifetime and quantum yield, or it can be theoretically calculated from the molar absorption coefficients, absorption spectrum, and emission spectrum.5 26 The spectral overlap between donor emission and acceptor absorption is essential for FRET occurring, and the spectral overlap integral is expressed as: 𝐽 =∫ 𝐼𝐷(𝜆)𝜀𝐴(𝜆)𝜆4𝑑𝜆∞0∫ 𝐼𝐷(𝜆)𝑑𝜆∞0 (1.10) where 𝜆 is the wavelength, 𝐼𝐷(𝜆) is the photoluminescence intensity of donor, 𝜀𝐴(𝜆) is the molar absorption coefficient of acceptor. The denominator is the integration of donor emission spectrum, which is used for normalization. To a certain extent, greater spectra overlap results in a larger spectral overlap integral; however, the wavelength to the fourth power term (𝜆4) in Eqn. 1.10 also contributes to the spectral integral, so longer wavelength (“redder”) FRET pairs tend to have larger spectral overlap integral.41,44 When the FRET rate constant and all other radiative and nonradiative decay rate constants reach equilibrium (𝑘𝐹𝑅𝐸𝑇 = 𝑘𝑅 + 𝑘𝑁𝑅 = 𝜏𝐷−1, where 𝑘𝑅 and 𝑘𝑁𝑅 are radiative and nonradiative decay rate constants), the FRET efficiency (𝐸𝐹𝑅𝐸𝑇) equals to 50%,40 and the distance between donor and acceptor (𝑟) is defined as Förster distance (𝑅0). Deriving from Eqn. 1.9, the 𝑅0 can be expressed as: 𝑅0 = [9(𝑙𝑛10)𝜅2𝜙𝐷128𝜋5𝑁𝐴𝑛4𝐽]1 6⁄ (1.11) Transforming from Eqns. 1.9 and 1.11, the 𝑘𝐹𝑅𝐸𝑇 can be described as Eqn. 1.12. Then, 𝐸𝐹𝑅𝐸𝑇 can be expressed as Eqn. 1.13, which shows the energy transfer efficiency is inverse six power distance (𝑟−6) dependent. 27 𝑘𝐹𝑅𝐸𝑇 = 𝜏𝐷−1 (𝑅0𝑟)6 (1.12) 𝐸𝐹𝑅𝐸𝑇 =𝑘𝐹𝑅𝐸𝑇𝑘𝐹𝑅𝐸𝑇 + 𝑘𝑅 + ∑𝑘𝑁𝑅=𝑅06𝑟6 + 𝑅06 (1.13) Figure 1.10 shows the FRET efficiency as a function of the distance of donor and acceptor (Eqn. 1.14). The FRET efficiency is highly sensitive to the FRET pair distance in the range of 0.7𝑅0 to 1.3𝑅0 (steep slope).40 Beyond this range, the changing of FRET efficiency will be small (flat curve), so it is impractical to use FRET as a “spectroscopic ruler” at this point. The 𝑅0 is determined by each FRET pair, so having appropriate FRET pair is important for measuring distances and other applications. Figure 1.10 FRET efficiency as a function of the relative distance between the donor and acceptor. The FRET efficiency is highly sensitive to distance in the range of 0.7R0−1.3R0 (steep slope). Reproduced from ref.40 Copyright 2017 American Chemical Society. It is worth mentioning that having correct unit for each term is critical for calculate Förster distance. The Eqn. 1.14. is obtained from Eqn. 1.11 and it is only valid when the correct units are used: nm 28 for wavelength and M−1 cm−1 for the absorption coefficient. In this case, 𝑅0 is calculated in Eqn. 1.14 in units of nm. 𝑅0 = 0.02108(𝜅2𝜙𝐷𝑛−4𝐽)1 6⁄ (in nm) (1.14) Last but not least, depending on the orientation of the two dipoles, the value of the dipole orientation factor (𝜅2) ranges from 0 to 4. Given the sixth root relation between 𝜅2 and distance, the error caused by uncertainty in the 𝜅2 term is limited. In many cases, donor and acceptor are assumed to have dynamically random dipole orientations, so 𝜅2 = 2/3 is used in most of the calculations. Otherwise, measuring the fluorescence anisotropy of donor and acceptor is a way to estimate an appropriate range of 𝜅2 value.42 1.3.2 Measurement of FRET efficiency Experimentally, FRET efficiency can be quantified and calculated by measuring the photoluminescence intensity (𝐼), lifetime (𝜏), or quantum yield (𝜙) of the donor, with and without acceptor: 𝐸𝐹𝑅𝐸𝑇 = 1 −𝐼𝐷𝐴𝐼𝐷= 1 −𝜏𝐷𝐴𝜏𝐷= 1 −𝜙𝐷𝐴𝜙𝐷 (1.15) where 𝐼𝐷𝐴 is the photoluminescence intensity of donor with acceptor present, and 𝐼𝐷 is the photoluminescence intensity of donor in absence of acceptor (donor only). Similarly, 𝜏𝐷𝐴 and 𝜏𝐷 are the lifetime of donor in presence and absence of acceptor, and 𝜙𝐷𝐴 and 𝜙𝐷 are the quantum yield of donor in presence and absence of acceptor. To calculate FRET efficiency from Eqn. 1.15, a control experiment (donor only) is required. 29 For biosensing application, FRET probes are designed with a known D-A distance or the distance is not the interest. Instead, the main focus is measuring the concentration or activity of an analyte. Compared to calculating FRET efficiency, PL ratio is an easy and robust approach to quantifying FRET (Eqn. 1.16) and correlating to the analyte concentration of interest: PL ratio =𝐼𝐴(𝐹𝑅𝐸𝑇)𝐼𝐷𝐴 (1.16) where 𝐼𝐴(𝐹𝑅𝐸𝑇) is the FRET-sensitized PL intensity of the acceptor and 𝐼𝐷𝐴 is the PL intensity of the donor with the acceptor present. Both of PL intensities can be measured at specific wavelengths or integrated over certain wavelength range for each fluorophore. Since this approach is ratiometric, the signal is approximately insensitive to dilution and fluctuation of the excitation source. In addition, changes in the PL ratio are amplified versus the FRET efficiency because the 𝐼𝐴(𝐹𝑅𝐸𝑇) and 𝐼𝐷𝐴 change in opposite directions (e.g. when FRET increases, 𝐼𝐴(𝐹𝑅𝐸𝑇) increases and 𝐼𝐷𝐴 decreases).41 1.3.3 Concentric Förster resonance energy transfer Concentric Förster resonance energy transfer (cFRET) is a method of leveraging the nanoscale size and optical properties of QDs for single-vector multiplexed bioanalysis and imaging. More generally, cFRET is a design motif for achieving these single-vector capabilities—it is facilitated by the use of QDs but is not necessarily limited to these materials. 30 FRET-based sensing with QDs was first reported in 200345 and represented the first lab-made FRET configuration with a well-defined 1:N stoichiometry (N > 1) between donor QD and acceptor dye. As Figure 1.11B illustrates, there are N approximately equivalent FRET pathways from a central QD donor to N copies of an acceptor dye arranged around it. Consequently, Eqn. 1.13 for the FRET efficiency becomes Eqn. 1.17: 𝐸𝐹𝑅𝐸𝑇 = 𝑁𝑅06𝑟6 + 𝑁𝑅06 (1.17) Another relevant development is the photonic wire concept, depicted in Figure 1.11C. The aim of these (bio)macromolecular assemblies is the directed transport of energy from one end of the assembly to the other, often through a multi-step “FRET relay.”46–48 In a FRET relay, energy is transferred from an initial donor fluorophore to a final acceptor fluorophore through one or more intermediate fluorophores. In principle, each intermediate fluorophore acts, in succession, as an acceptor for the upstream fluorophore and a donor for the downstream fluorophore. The primary metric for the success of a photonic wire design is the end-to-end transfer efficiency vis-à-vis the end-to-end distance. 31 Figure 1.11 Simplified representations of (A) a dye-based molecular beacon, (B) a FRET configuration with a QD donor and multiple copies of a dye acceptor, (C) a dye-based photonic wire, and (D) a cFRET configuration with a central QD and multiple copies of multiple types of dye acceptors. Arrows represent FRET pathways. Acceptor dyes are labelled as A and donor dyes are labelled as D. Relay dyes in the photonic wire act as both acceptor and donor in sequence and are labelled as R. For the QD-FRET and cFRET configurations, the QD is the donor. Although A1 in the cFRET configuration is an acceptor for the QD and a donor for A2, it is not labelled as a relay dye because of the difference in its intended role: the relay dyes in the photonic wire aim to deposit as much energy as possible to the terminal acceptor dye, A, whereas the cFRET configuration aims to deposit energy into both A1 and A2. Reproduced from ref.49 Copyright 2019 IOPscience. In essence, cFRET merges the two ideas of a FRET relay and 1:N stoichiometry between an initial donor and dye acceptor. The simplest cFRET configuration, illustrated generically in Figure 1.11D, comprises a QD donor surrounded by multiple copies of two acceptors, A1 and A2, with 1:M:N stoichiometry. Energy is transferred from the QD donor to either A1 or A2, and, if the energy is transferred to A1, a relay step subsequently transfers the energy from A1 to A2. Prior to the studies in this thesis, cFRET configurations have used only QDs as the initial donor and principally used fluorescent dyes as the nominal acceptors. (The potential for dyes in a cFRET configuration to act as a donor for other dyes, so the “nominal” term was used.) Figure 1.12 depicts an example of a cFRET configuration that features a QD and three fluorescent dyes at a 1:L:M:N ratio with the QD.50 Some of the FRET pathways compete with one another whereas others occur sequentially. 32 The dyes are linked to the QD via peptides, which confer biochemical utility to the configuration. Each of the three types of peptides is a substrate for a protease, and hydrolysis of the peptides by proteases is tracked via changes in fluorescence. The “concentric FRET” nomenclature comes from two aspects of the configuration: (i) geometry with a central and approximately spherical donor (e.g. QD); and (ii) a FRET relay that aims to distribute energy across the network of nominal acceptors within a sphere concentric with a donor rather than directionally over a distance (cf. a photonic wire).51 Figure 1.12 A cFRET configuration with a central QD donor and three types of dye acceptor. (A) Simple model of an assembly that uses three different peptide sequences as linkers between the QD and three dyes: Alexa Fluor 555 (A555), either Cyanine 3.5 (Cy3.5) or Atto 594 (At594), and Alexa Fluor 647 (A647). For clarity, the glutathione (GSH) ligand coating on the QD is represented by a mesh and only some of the peptides are shown. (B) Diagram of the energy transfer pathways in the cFRET configuration. Energy transfer pathways (dotted lines) labelled with the same number (e.g. 2a, 2b) compete with one another, whereas pathways labelled with different numbers are sequential. PL and nonradiative (Δ) relaxation pathways are also shown. Reproduced from ref.50. Copyright 2017 American Chemical Society. Importantly, the emission signatures of the cFRET configuration (i.e. overall spectral profile or combination of PL ratios) should be unique to each combination of the numbers of each fluorescent 33 dye per donor (e.g. 1:M:N or 1:L:M:N), which enables cFRET probes to be used for quantitative bioanalysis. 1.3.4 Advantages of cFRET Why is cFRET of interest? The answer is its capability for single-vector multiplexed bioanalysis and imaging, which offers several demonstrated and prospective advantages over the use of multiple probe or sensor vectors, as discussed in the paragraphs below. More efficient use of the spectrum A cFRET configuration requires only n + 1 emitters (an initial donor plus n nominal acceptors) for n-plexed detection, whereas n distinct probes with different D-A pairs require 2n emitters. The smaller number of emitters in cFRET thus offers better resolution of emission signals within a given spectral range. For example, archetypical two-plex and three-plex cFRET configurations use three and four emitters,50–52 respectively, within the spectral range from ca. 500 nm to 750 nm, whereas a duo and trio of conventional FRET probes with different D-A pairs would use four and six emitters, respectively. Less emission crosstalk and the ability to use emission filters with broader bandpass are two of the advantages of fewer emitters. Alternatively, more versatile use of a total of 2n emitters would allocate n + 1 emitters for multiplexed detection via cFRET and allocate the remaining emitters for other purposes, such as staining structural features of a biological sample. 34 Although n conventional FRET probes with a common donor emitter would likewise require only n + 1 emitters and, in principle, support quantitative multiplexed measurements through a unique set of emission ratios, there are drawbacks for such a strategy versus cFRET. The advantages of a single vector (vide infra) would be lost, and emission ratio measurements would only be reliable in a closed system with no flux or uncertainty in the numbers of each probe in the measurement volume. As mentioned earlier, detection via an emission ratio tends to be more robust, more reproducible, and more quantitative because the ratio is approximately independent of excitation intensity, dilution, and detection efficiency. A cFRET configuration retains its capacity for multiplexed quantitative analysis via emission ratios, even in an open system with flux, because all of the emitters are combined in a single assembly. One-shot excitation A challenge with the use of n different D-A FRET pairs is that a single excitation wavelength, particularly outside the UV region, is unlikely to excite all n probes with similar efficiencies. The outcome of this deficiency tends to be significantly different brightness between different probes or the parallel or sequential use of multiple excitation wavelengths. This challenge is especially applicable to n different dye- or fluorescent protein-based FRET pairs, but also applies to an extent with FRET pairs with QD donors. Although a single excitation wavelength is suitable for many colours of QD, larger QDs tend to be much brighter than smaller QDs of the same composition (e.g. red-emitting QDs are much brighter than green-emitting QDs).53 A cFRET configuration requires only one excitation wavelength and the brightness of all emitters is largely set by the initial donor. 35 Single vector The number of assemblies required for n-plex detection is just one for cFRET and n for conventional FRET probes. cFRET therefore requires the introduction of n-fold fewer probes to a biological system and avoids challenges from differences in cellular uptake, distribution, stability, brightness, or other properties that may occur between n separate probes. In parallel, multiple emission signals from a single assembly affords the expected compatibility with samples that have flux in or no control over the number of probes interrogated. It is anticipated that this property of cFRET probes will also enable n-plex detection with unprecedented resolution through pairing with single-molecule (or particle) fluorescence measurements and super-resolution imaging methods. Conventional FRET probes only multiplex at the ensemble-level because the n probes are not physically coupled to one another and therefore not spatially correlated. While the foregoing are compelling reasons to develop cFRET, the method is not without its limitations and challenges (e.g. unanswered fundamental questions, overall multiplexing capacity, robust and streamlined calibration, materials beyond QDs). 1.3.5 Requirements for cFRET As noted earlier, experimental realization of the cFRET concept has mainly utilized QDs. (This thesis is the first research to develop cFRET probe without using QDs.) There are good reasons for the use of QDs but it is worthwhile to first consider the three components of a generic cFRET configuration: (i) a central scaffold around which the FRET network is assembled; (ii) an initial donor emitter; (iii) and two or more nominal acceptor emitters. 36 The central scaffold should be of a size small enough for the distances between donor and acceptors to be amenable to FRET. The scaffold must have surface area that is sufficient for multivalent conjugation of the various emitters, and must have functional groups or other chemistry that supports its conjugation, generally through biomolecular linkers. The initial donor emitter should be bright and characterized by a broad or spectrally distinct absorption spectrum, large molar absorption coefficient, and favourable quantum yield. The nominal acceptor fluorophores are, in large part, determined by FRET requirements, such as the spectral overlap between acceptor absorption and donor emission. Acceptor brightness is also important because a large molar absorption coefficient favours larger Förster distances and a high quantum yield increases FRET-sensitized emission.40 Ideal acceptors are not directly excited in parallel with the initial donor, and their emission is at least partially resolved from the emission of the donor and other acceptors. Selection of a nominal acceptor dye for a cFRET configuration is not trivial. Multiple criteria need to be satisfied, as discussed in the paragraphs below. Brightness Brightness is the mathematical product of absorption coefficient and quantum yield. In general, brighter dyes are better for cFRET. A larger quantum yield favours larger Förster distances when a dye acts as an energy donor and increases PL ratios (i.e. more intense FRET-sensitized acceptor emission) when the dye acts as an acceptor. A larger molar absorption coefficient favours larger Förster distances when a dye acts as an acceptor, which also increases its observed FRET-sensitized emission. The caveat for a bright dye is that significant direct excitation must still be avoided (vide infra). 37 Spectral overlap Spectral overlap between donor emission and acceptor absorption is essential for FRET.40 The challenge with a cFRET configuration is that all nominal acceptors must have some spectral overlap with the initial donor and still have emission that is adequately spectrally resolved from other emitters. This criterion is notably different from a photonic wire, where the typical goal is to optimize spectral overlap and energy transfer between neighboring pairs of dyes, and direct energy transfer between the initial donor and final acceptor is neither expected nor required as it is in cFRET. Important parameters for cFRET acceptors are therefore the spectral position of their absorption maximum and the width of their absorption spectrum relative to the spectral position of donor emission, as well as the magnitude of their molar absorption coefficient and the Stokes shift. These parameters will set the rates of D-A FRET pathways such as 1a-c in Figure 1.12B. Emission spectra The practical application of a cFRET configuration relies on the detection of emission from the donor and each of the nominal dye acceptors. The broad, red-tailed emission spectra of dyes are such that some emission crosstalk between the nominal acceptors is unavoidable; however, corrections for crosstalk are most robust when crosstalk is minimized. To date, cFRET configurations have had dye emission peaks at least 40 nm apart, with contrast of at least 2:1 between the peak emission of one dye and the red-tail of another dye. 38 Excitation spectra Minimization of the direct excitation of acceptors is one of the general benefits of QDs as FRET donors and is straightforward to achieve because the width of the QD absorption spectrum assures that it will be excited at the wavelength of minimum excitation for the dye. The task is not as straightforward with cFRET because the excitation minima for two or three nominal acceptor dyes must approximately coincide. The optimal wavelengths were estimated from excitation spectra, and control experiments were run to confirm that directly-excited dye emission was negligible versus cFRET-sensitized emission. Photostability The effect of photobleaching on a cFRET configuration is analogous to the effect on any other FRET probe: loss of function and/or false signals because bleaching of even one emitter type affects the network of energy transfer pathways. For example, QDs are generally more photostable than dyes in a QD-based cFRET configuration, so the nominal acceptors tend to be the weak link. There is a need to find combinations of dyes that satisfy the spectral requirements for cFRET and also show resistance to photobleaching. Self-quenching The term “self-quenching” commonly refers to phenomena where the per-dye brightness decreases as more dye labels are attached to a protein or as multiple labelled biomolecules aggregate,54–57 but does not imply a specific mechanism for this behaviour. cFRET configurations are at risk of detrimental self-quenching because of their dependence on the multivalent assembly of multiple 39 dyes. Any strong inter-dye interactions that form complexes would add a new species and thus new FRET pathways, both competitive and (if the complex is emissive) sequential. Non-specific interactions In practical application, a biorecognition event will directly or indirectly actuate dyes to associate with or dissociate from a donor in a cFRET configuration. Spontaneous association of a dye with the donor conjugate is therefore problematic. In the absence of the designed biomolecular linker, an ideal dye should have little or no affinity for any component of a cFRET conjugate. Dyes with greater hydrophilicity and a larger net negative charge show less indications of non-specific interactions are preferred. 1.3.6 Characterization and analysis of cFRET Physical characterization of cFRET configurations use the same methods that are used for nanoparticle bioconjugates in general. Spectroscopic characterization is analogous to other FRET systems and is based on intensity measurements (in the form of both quenching efficiencies and intensity ratios), lifetime measurements, and rates of photobleaching. Note that all of the discussion is in the context of ensemble-level measurements. Intensity There are n + 1 intensities to measure in an n-acceptor cFRET configuration: the donor and each of the n nominal acceptors. Energy transfer efficiencies, 𝐸, can be calculated from quenching of PL intensities as the number of nominal acceptors increases. However, it must be recognized that the efficiency reflects energy transfer to all assembled acceptors if more than one nominal acceptor 40 is assembled to the donor (for example, two or more of the pathways 1a-c in Fgure 1.12B). A quenching efficiency, 𝑄, is therefore the more general representation. Eqn. 1.18 is the efficiency with which the donor is quenched, where 𝐼𝐷(𝐿,𝑀,𝑁) is the measured donor PL emission intensity when assembled with an average of (L, M, N) copies of nominal acceptors (A1, A2, A3). 𝑄𝐷 = 1 − 𝐼𝐷(𝐿,𝑀,𝑁)𝐼𝐷(0, 0, 0) (1.18) The energy transfer efficiency from a donor to a specific type of acceptor can only be determined when the other acceptors are omitted from the configuration. As an example, Eqn. 1.19 is the efficiency of energy transfer from a donor to the first of three possible acceptor dyes (pathway 1a in Figure 1.12B). 𝐸𝐷→𝐴1 = 1 − 𝐼𝐷(𝐿, 0, 0)𝐼𝐷(0, 0, 0) (1.19) The efficiency of a sequential energy transfer step between dyes, such as pathways 2a-b and 3 in Figure 1.12B, can likewise be measured from quenching of the appropriate donor dye, but must be referenced to the configuration with the same number of donor dyes. For example, Eqn. 1.20 reflects the efficiency from the nominal first acceptor dye to the nominal second acceptor dye (pathway 2a in Figure 1.12B), but only in the special case that A1 is directly excited, bypassing excitation of the donor. (The prime notation indicates direct excitation of A1.) The equation also assumes negligible direct excitation of A2 within the same single-particle assembly. (Directly-excited A2 on an assembly without excited A1 will not affect the measurement.) Analogous equations can be written for energy transfer from the first to third and second to third nominal acceptor dyes (pathways 2b and 3 in Figure 1.12B). 41 𝐸𝐴1→𝐴2′ = 1 − 𝐼𝐴1′ (𝐿,𝑀, 0)𝐼𝐴1′ (𝐿, 0, 0) (1.20) In contrast, Eqn. 1.21 reflects the efficiency of energy transfer from the directly-excited first nominal acceptor dye to all other nominal acceptor dyes and is therefore better represented as a quenching efficiency. 𝑄𝐴1′ = 1 − 𝐼𝐴1′ (𝐿,𝑀,𝑁)𝐼𝐴1′ (𝐿, 0, 0) (1.21) If, instead of direct excitation of A1, the donor is initially excited without significant direct excitation of the nominal acceptors (i.e. the usual condition for cFRET), then Eqn. 1.20 and 1.21 become Eqn. 1.22, which is also a quenching efficiency. (Note that the prime notation is dropped in Eqn. 1.22.) 𝑄𝐴1 = 1 − 𝐼𝐴1(𝐿,𝑀,𝑁)𝐼𝐴1(𝐿, 0, 0) (1.22) The reason for distinguishing between FRET efficiencies and quenching efficiencies, and between direct and FRET-sensitized excitation of dye, is the combined effects of competitive and sequential energy transfer. For example, consider a (L, 0, 0) versus a (L, M, 0) configuration. The emission intensity of A1 will be lower for (L, M, 0) than (L, 0, 0), even in the absence of A1-to-A2 FRET, because some of the energy that was originally transferred from the donor to A1 goes to A2 instead. A1 and A2 compete for energy from the donor. Any sequential FRET from A1 to A2 will then further reduce the emission intensity of A1. It is for this reason that the quenching efficiencies from Eqn. 1.21 and 1.22 are not expected to be equal (𝑄𝐴1′ ≠ 𝑄𝐴1). 42 PL ratios Another metric that can be derived from PL intensity measurements are A/D emission ratios. These are the ratios A1/D, A2/D, and A3/D for a cFRET configuration with three nominal acceptor dyes, generally defined by Eqn. 1.23, where 𝐴𝑛 is an arbitrary nominal acceptor. 𝜌𝐴𝑛 𝐷⁄ =𝐼𝐴𝑛(𝐿,𝑀, 𝑁)𝐼𝐷 (𝐿,𝑀,𝑁) (1.23) The PL intensities in Eqn. 1.23 are measured at a particular wavelength setting of a monochromator or with a particular bandpass filter. The resulting PL ratios are therefore empirical as measured, semiempirical if corrected only for crosstalk, and “true” if also corrected for the fraction of the total emission collected for each emitter. Examples of the latter are a correction for the fraction of the area under the emission spectra passed by microscopy bandpass filters, or a correction for the ratio of the area of an emission spectrum versus its peak height.51 (If direct excitation of the nominal acceptor dyes is not negligible, a “true” ratio also requires a correction for directly excited acceptor emission.) In principle, true PL ratios are linked to energy transfer efficiencies,58 but such analyses have not proven very robust in practice, as even non-cFRET configurations with donors and dye acceptors have shown deviations from the expected first-principles behaviour.59,60 Notably, PL ratios have become a de facto characteristic of a cFRET configuration in that the combination of PL ratios, denoted as (A1/D, A2/D, A3/D), is unique to a particular set of numbers of each acceptor per donor, (L, M, N). 43 Emission lifetimes As with other FRET systems, measurement of emission lifetimes is useful for characterization of cFRET. This data is, in principle, useful for determination of FRET efficiencies or quenching efficiencies (as appropriate). A PL emission decay trace for the donor is usually straightforward to obtain, and the analysis via Eqn. 1.24 and 1.25 is analogous to the analysis of donor PL intensities (Eqn. 1.18 and 1.19), where 𝜏𝐷 is the amplitude-weighted average lifetime of the donor. 𝑄𝐷 = 1 − 𝜏𝐷(𝐿,𝑀,𝑁)𝜏𝐷(0, 0, 0) (1.24) 𝐸𝐷→𝐴1 = 1 − 𝜏𝐷(𝐿, 0, 0)𝜏𝐷(0, 0, 0) (1.25) For the PL emission decays of the nominal acceptor dyes, FRET sensitization means that the dyes take on some of the multi-exponential decay character of the donor. Quantitative analysis is therefore more challenging, and becomes even more challenging if emission crosstalk cannot be ignored. Thus, characterization of cFRET based on PL lifetimes has been quite limited. 1.4 Dendrimers Dendrimers are hyperbranched polymer nanoparticles with a recurring pattern of branching.61–63 The numbers of branches and (nominal) surface functional groups increase exponentially with each generation of synthesis, while the particle diameter increases linearly.62 Dendrimers are highly monodisperse (although not necessarily perfectly monodisperse in practice) and multivalent with respect to functional groups.62,63 44 As shown in Figure 1.13A,64 the structure of a dendrimer can be divided into three parts: the core, the interior branching shell, and the outer shell (i.e. nominal surface groups).61–63 The core of the dendrimer is the scaffold for growing the dendritic arms. A core grows with one layer of shell is called the first-generation dendrimer and is denoted as G1. The dendrimer generation increases as more layers of shells are added, denoted as GN where N is an integer equal to the rounds of growth. As the dendrimer generation increases, the dendrimer transitions from flexible to more rigid, adopting an approximately spherical shape.61 As an example, PAMAM dendrimers, shown in Figure 1.13B, are widely used and commercially available dendrimers. Figure 1.13C shows a TEM image of PAMAM G7 dendrimers.65 The dimension of a PAMAM dendrimer grows from ∼2 nm for the first generation to ∼13 nm for the 10th generation, with a concomitant increase in the number of primary amine groups from eight to 4096.66 These groups are nominally at the surface of the dendrimer; however, experiments suggest that PAMAM, like some other dendrimers, undergoes a degree of backfolding (i.e. a denser core and less dense shell).67 Dendrimers are commonly used as nanocarriers for drug delivery studies or as nanoplatforms for scaffolding photoluminescent molecules.68–70 In general, photoluminescent molecules are either covalently conjugated to the surface functional groups of a dendrimer,71 or non-covalently associated with the interior of the dendrimer on the basis of electrostatic or hydrophobic interactions.72,73 45 Figure 1.13 Dendrimers. (A) General dendrimer structure and components: core (red), interior branching units (green), and outer functional groups (blue). Adapted from ref.64 Copyright 2015 Elsevier. (B) Chemical structure of a G3 PAMAM dendrimer and (C) TEM image of G7 PAMAM dendrimers stained with sodium phosphotungstate. Chemical structure reproduced from ref.63 Copyright 2016 Wiley Periodicals, Inc. TEM image was adapted from ref.65 Copyright 1998 American Chemical Society. 1.5 Hydrogels Hydrogels are three-dimensional (3D) hydrophilic polymer networks that are able to hold a large quantity of water.74,75 Hydrogels can be categorized in several different ways. Based on the sources of the polymers, hydrogels can be categorized into to three types: natural hydrogels (e.g. using collagen, fibrin, or alginate to form networks), synthetic hydrogels (e.g. using poly(ethylene glycol), or poly(acrylamide) to form networks), and hybrid hydrogels (i.e. using both natural and synthetic polymers to form 3D networks).74–76 In biological fields, the advantages of using natural hydrogels include being more biocompatible, bioactive, and biodegradable.75,77 Synthetic hydrogel scaffolds tend to offer better control between batches and tunable mechanical and chemical microenvironments since the molecular weight and the length of the polymers are tailorable.78 Although synthetic hydrogels are not naturally bioactive, versatile functionalization and bioconjugation techniques mitigate this weakness.75,78 Hydrogels may be categorized based on the 46 cross-linking strategy, whether chemical bond formation or non-covalent physical interactions (e.g. electrostatic interaction). Hydrogels may also be divided into three groups based on their polymeric compositions: homopolymer, copolymer, and interpenetrating polymer network (Figure 1.14).75 Homopolymers contain one type of repeating unit, copolymers contain two or more types of repeating units, and interpenetrating polymer networks are two different network systems penetrating each other to form a hydrogel. Both homopolymers and copolymers have only one type of polymer network, whereas two or more types of polymers can be found in an interpenetrating network. Generally, hydrogels based on interpenetrating polymer networks have better mechanical strength than homopolymer and copolymer hydrogels.75,79 Figure 1.14 Hydrogels classification based on their polymeric composition(s): (A) homopolymer; (B) copolymer; and (C) interpenetrating polymer networks. Reproduced from ref.80 Copyright 2012 Elsevier. Hydrogels have wide range of applications, including wearable electronics, tissue engineering, drug delivery, sensing applications, and more.75 One important application of hydrogels is 47 mimicking the extracellular matrix (ECM) microenvironment for cell culture.74,77 Conventionally, cells are grown in two-dimensional (2D) environment; however, the substrates (e.g. plastic or glass) have non-physiological stiffness and limit cell growth and migration in 2D.74,77 This non-natural microenvironment can induce aberrant cell behaviours, which yields misleading results prior in vivo studies.74,81 Compared to conventional cell culture, the use of a hydrogel provides more reliable predictions for downstream in vivo experiments and helps reduce the expense of animal studies by bridging the gap between 2D cell cultures and animal models.74 1.6 Overview and contributions of this thesis This thesis contains six chapters plus appendices with supporting details and data for the chapters. In aggregate, the thesis focuses on expanding the materials palette for cFRET-based bioanalysis. As noted earlier, cFRET is a highly promising strategy for multiplexed sensing, but has been limited in scope to freely-diffusing probes based on metal chalcogenide semiconductor QDs. Concerns about the potential toxicity of these QDs (whether founded or unfounded) warrant the evaluation of alternative materials for cFRET. The integration of cFRET probes with interfaces and structured materials is also expected to provide new opportunities and benefits, as such integration has done for many biomolecular assays and sensors. Given these contexts, the overall goal of this thesis was to advance the scope of applications for cFRET and enhance it suitability for those applications by exploring and evaluating new materials. Chapter 1 has laid the conceptual foundations for understanding the physical and fluorescence properties of materials relevant to this thesis, and for understanding cFRET and its current state of the art. 48 Chapter 2 describes the development of a dendrimer-based time-gated cFRET configuration—the first cFRET configuration that does not use a QD as a FRET donor and central scaffold. A luminescent terbium complex replaces the QDs as a donor and the dendrimer replaces the QD as a scaffold. The focus of the chapter is the preparation and physical and spectroscopic characterization of the probe and its energy transfer network. Chapter 3 continues to describe the dendrimer-based time-gated cFRET probe, focusing on its sensing application. Proof-of-concept is demonstrated for triply multiplexing sensing as a single vector, matching the capability of prior QD-based cFRET probes and showing that similar methods of quantification are applicable. Nucleic acid detection is the principle example for cFRET, but potential for FRET-based protease sensing and for measurements on a smartphone-based platform is also shown. Advantages and disadvantages versus QD-based cFRET are discussed. Overall, the dendrimer-based time-gated cFRET probe is a new and promising platform for multiplexed bioanalysis. Chapter 4 investigates energy transfer between SiNCs and dark quenchers or a fluorescent dye. Spectroelectrophoresis, time-resolved spectroscopy, and time-gated spectroscopy are used to characterize the size and PL properties of the SiNC and systematically study energy transfer. Although this chapter does not go as far as developing SiNC-based cFRET probes, the research was an important step toward this goal. The results revealed challenges and complications from the polydispersity of SiNCs that would hinder practical cFRET with these materials. Chapter 5 begins the development of hydrogels for 3D cell culture with embedded QD-based cFRET probes for cell-secreted protease activity. The first examples of hydrogels with structurally 49 integrated cFRET probes were prepared. PL emission was evaluated and the FRET network and multiplexing capability of solution-phase cFRET probes was qualitatively retained by probes within the gel. Proof-of-concept for non-concentric FRET-based detection of protease activity was demonstrated, suggesting strong potential for future application with 3D cultured cells. Chapter 6 summarizes the main results contributions from the previous chapters and discusses potential directions for further research and development of next-generation of cFRET probes and their applications. Overall, this thesis presents novel and impactful research at the interface between materials science, nanotechnology, spectroscopy, and bioanalytical chemistry. The work helps move cFRET towards its full potential and eventual applications in biomedical research. 50 Chapter 2: Development of Dendrimer-Based Time-Gated cFRET Configuration This chapter is an adaption of published work. The text was reproduced from Tsai, H.-Y.; Algar, W. R., A Dendrimer-Based Time-Gated Concentric FRET Configuration for Multiplexed Sensing. ACS Nano 2022, 16, 8150−8160, with permission from the American Chemical Society. 2.1 Introduction Förster resonance energy transfer (FRET) is utilized in a wide range of applications in bioanalysis and imaging. Fluorescent probes based on simple donor-acceptor FRET pairs offer benefits such as real-time, ratiometric and wash-free detection,41 and have been designed for a wide array of biomolecular targets (e.g. nucleic acids,82,83 proteins/enzymes,82 metabolites,82–84 inorganic ions82,83). Conventionally, the multiplexed detection of multiple targets—a critical need of growing importance in bioanalysis—has been demonstrated through the use of multiple, spectrally-resolved FRET pairs. Colloidal semiconductor quantum dots (QDs) bring several advantages to the design of FRET probes, including high brightness, advantageous spectral properties, and straightforward access to single donor-multiple acceptor and multiple donor-single acceptor configurations, but still generally relied on multiple FRET probes for multiplexed detection.40,49 A subsequent innovation was concentric FRET (cFRET), which features a FRET network assembled around a QD. Most commonly, the QD serves as an initial donor for multiple assembled acceptor dyes with one or more downstream dye-to-dye FRET pathways.52,85–87 As reviewed elsewhere, cFRET 51 probes are potentially powerful because of their capability for multiplexed detection as a single probe and vector.49 Although cFRET configurations have, to date, always had a central QD scaffold, the concept is not necessarily limited to QDs. Practically, a QD is well-suited to cFRET because it is able to simultaneously function as both a scaffold and an initial donor. However, a persistent concern around many QD materials is the risk of toxicity in a biological system, despite known mitigation strategies.88–90 Non-QD scaffolds and initial donors are therefore of interest and may also offer their own unique advantages in cFRET. Important criteria for a new scaffold material for cFRET are sufficiently small size and capacity for attachment of multiple copies of multiple types of biomolecular probes and dyes. Given the foregoing, dendrimers are a promising alternative scaffold because of their small and well-defined size and their multitude of surface functional groups.72,91 For a new initial donor, important criteria are selective excitation, adequate brightness, and spectral overlap with a range of downstream dyes. Among initial donor candidates, luminescent terbium(III) complexes are promising. These complexes offer narrow emission lines across the visible spectrum for spectral overlap and resolution of emission when paired with a wide range of dyes, and offer selective excitation through their long-lifetime and compatibility with time-gated luminescence measurements.21 The modest brightness of most terbium complexes is potentially compensated by the high signal-to-background ratios possible with time gating, and by utilizing multiple copies of a complex. In this chapter, a novel cFRET configuration was developed where the central QD was replaced with a dendrimer scaffold and luminescent terbium complex as the initial donor. For proof-of-52 concept, the dendrimer material selected was a sixth-generation (G6) poly(amidoamine) (PAMAM) dendrimer. PAMAM dendrimers are one of the most extensively studied varieties of dendrimer and provide a multitude of bioconjugation-friendly amine groups near their surface. The size of the G6 PAMAM dendrimer was also similar to the size scale of the core/shell QDs used for previous cFRET configurations. The luminescent terbium was an octadentate caged Tb(III) 2-hydroxyisophthalamide complex (Lumi4-Tb)92 with brightness on the order of 104 M–1 cm–1 and an excited state lifetime on the order of milliseconds. The G6 PAMAM dendrimer was labelled with multiple copies of Lumi4-Tb and biotin for subsequent bioconjugation. Concentric FRET pathways were evaluated in conjugates with dye-labelled oligonucleotides. The energy transfer between the Lumi4-Tb and the dyes, and between the different dyes, created the FRET network characteristic of cFRET. This work clearly shows the potential for using materials other than QDs as scaffolds and initial donors for cFRET. 2.2 Results 2.2.1 Labelling and bioconjugation of the dendrimer scaffold 2.2.1.1 Synthetic strategy Figure 2.1A illustrates the construction of the cFRET system. The G6 PAMAM dendrimer (1) nominally had 256 primary amine groups near its surface. Multiple copies of Lumi4-Tb (Tb) and biotin were conjugated per 1 using N-hydroxysuccinimide (NHS) ester chemistry to yield 2. To increase colloidal stability, the dendrimers were electrostatically assembled with poly(acrylic acid) (PAA), yielding a net negative charge for 3. The stepwise functionalization was evaluated by agarose gel electrophoresis, as shown in Figure 2.1B. 53 To enable conjugation with biotinylated oligonucleotides, dendrimer 3 was modified with NeutrAvidin (NAv) to yield 4 (Figure 2.1A). Figure 2.1C−D illustrates the binding of biotinylated oligonucleotides and confirmation by gel electrophoresis. Although we focus on oligonucleotides in this study, the binding of peptides and small molecules may prove useful in future permutations of the system. Figure 2.1 Preparation of the cFRET probe. (A) Summary scheme (not drawn to scale) for labelling and functionalization of the G6 PAMAM dendrimer. The dendrimer illustration is a simplification and does not show its G6 molecular structure. The bolded numbers are used to refer to dendrimer materials throughout the Chapter 2 and 3. (B) Agarose gel (0.5% w/v) electrophoresis shows changes in the mobility of the dendrimer after each modification step. The first lane in the PL image of the gel is the Tb complex, and the remaining lanes are numbered to match the dendrimer materials in panel A. (C) Scheme (not to scale) illustrating the binding of dye-labelled and biotinylated double-stranded oligonucleotides to dendrimer 4. (D) Agarose gel (0.5% w/v) electrophoresis shows changes in mobility after dendrimer 4 binds with different equivalents of biotinylated oligonucleotides. The dye was Alexa Fluor 546 (A546). The first lane is the biotinylated prehybridized A546-labelled DNA; the subsequent lanes are dendrimer 4 with an indicated number of equivalents of the DNA. The orange box outlines the position of 4, which was less bright in the gel PL image. 54 2.2.1.2 Tb and biotin labelling efficiency For labelling the G6 PAMAM dendrimer with Tb, Figure 2.2 shows a PL image of an agarose gel of the labelling reaction mixture. The mixture separated into two different bands: one band was free Tb and one band was the labelled dendrimer. To estimate the labelling efficiency, the ratio of free and dendrimer-conjugated Tb was estimated using band PL intensities, with a correction for relative quantum yield (vide infra). The labelling efficiency was approximately 64 ± 2%. Since ~12.7 equivalents of Tb complex were mixed with PAMAM dendrimer, the average number of Tb labels per dendrimer was 8.1 ± 0.2 equivalents. The lane with free Tb had a minor band, which was ignored in the labelling efficiency calculation. Figure 2.2 PL image of an agarose gel (0.5% w/v) with Tb alone and the labelling reaction mixture from labelling dendrimer 1 with Tb. The arrow shows the polarity of the applied electric field (~6.7 V/cm). Lifetime measurements were used to estimate the change in quantum yield between free Tb and Tb-labelled dendrimer. Figure 2.3 shows the PL decays for both forms in borate buffer. The amplitude-weighted average PL lifetime for the free Tb complex was 2.8 ms, whereas the Tb 55 lifetime associated with dendrimer 3 was 1.9 ms. The corresponding lifetimes were used for assessing the quantum yield of dendrimer 3. With the assumption that the change in lifetime was from an increase in the non-radiative relaxation rate of the Tb, the quantum yield of the dendrimer-conjugated Tb was taken to be ~70% of that of the free Tb. Figure 2.3 PL decays (and amplitude-weighted average lifetimes) for the Tb alone (2.8 ms), dendrimer 2 (1.2 ms), and dendrimer 3 (1.9 ms). Considering biotin labelling, Figure 2.4 shows the calibration data set for biotin standards that were measured via ESI mass spectrometry. Using this calibration, the concentration of biotin in the filtrate (the unconjugated biotin, separated from the reaction mixture via centrifugal filtration) was compared to the amount added to the biotin conjugation reaction with dendrimer 2. The filtrate contained ~40% of the initially added biotin, suggesting a labelling efficiency of ~60%, corresponding to an average ~29 biotin per dendrimer. 56 Figure 2.4 Calibration curves with ESI-MS peak area plotted versus concentration for biotin standard solutions (blue dots). The signal measured for the filtrate from purification of the biotin-labelling reaction with dendrimer 2 is shown as a red dot. 2.2.1.3 NAv loading capacity of dendrimer 3 Aliquots of dendrimer 3 were mixed with an increasing number of equivalents of NAv. Figure 2.5A shows the PL image of an agarose gel for estimating the NAv loading capacity of the dendrimer as 10−20 NAv per dendrimer, corresponding to diminishing shifts in electrophoretic mobility with increasing equivalents of NAv. Thirty equivalents of NAv were mixed with one equivalent of the dendrimer 3, and the excess NAv was removed via size exclusion chromatography. Figure 2.5B shows the absorption spectrum of the purified NAv-conjugated dendrimer 4. The average number of NAv per dendrimer was assessed from the absorbance of NAv at 280 nm, including a correction for the absorbance contribution of the Tb complex at 280 nm. The absorption coefficients for NAv at 280 nm and 340 nm are 99 600 M–1 cm–1 and 7481 M–1 cm–1, respectively. The absorption coefficients for dendrimer 4 at 280 nm and 340 nm were estimated as 57 908 M–1 cm–1 and 210 297 (= 26 000 × 57 number of Tb per dendrimer) M–1 cm–1, respectively. The final purified dendrimer 4 had 11−13 NAv per dendrimer, and the NAv-to-Tb ratio per dendrimer was ~1.5. Figure 2.5 (A) PL image of an agarose gel (0.5%) for estimating the NAv loading capacity of modified dendrimer 3. (B) Absorption spectrum of purified dendrimer 4. Before purification, the NAv was excess. The ratio of NAv:dendrimer = 30:1 prior purification. Note: The purified dendrimer 4 had an average of 11−13 NAv per dendrimer when prepared as four different batches. Another batch of dendrimer 4 had ~16 NAv per dendrimer, and this batch was only used for the Ferguson analysis. All other experiments used batches with 11–13 NAv per dendrimer. 2.2.1.4 Size characterization of dendrimers The hydrodynamic size of purified NAv-conjugated dendrimer 4 was measured by dynamic light scattering (DLS). Figure 2.6 shows that the number-weighted size was ~18 nm. 58 Figure 2.6 Number-weighted size distribution of purified NAv-bound dendrimer 4, measured by DLS. A Ferguson analysis was used for estimating the size of dendrimer 3 and 4. Figure 2.7 summarizes the results of this analysis. DHLA-coated gold nanoparticles (Au NPs; used as size standards) and modified dendrimers were run on a series of agarose gels with agarose concentrations between 0.3−1.5% w/v. The PL from the Tb-labelled dendrimers was observed under UV light, whereas shadowing from the Au NPs standards was observed under white light. Image J software was used to measure the mobilities of the Au NPs and modified dendrimers: velocities were measured (pixels s–1), converted to the SI unit (m s–1), then divided by the field strength (V m–1) to obtain mobilities (m2 V–1 s–1). The relationship between mobility, M, and the gel concentration, T, is shown in Eqn. 2.1: logM = logM0 − 𝐾𝑅𝑇 (2.1) where M0 is the mobility of particles in the solution, and 𝐾𝑅 is a retardation coefficient that is obtained from the plot of logM versus T. The 𝐾𝑅 values for the Au NPs at various gel densities 59 were used for plotting a calibration curve and determining the constants, a and b, according to Eqn. 2.2: √𝐾𝑅 = 𝑎𝑅 + 𝑏 (2.2) where R is the diameter of the Au NPs (and subsequently the dendrimer). In Figure 2.7 C, the slope and intercept (a = 0.012 and b = 0.20 in Eqn. 2.2) from plots of the square root of the retardation factor (√𝐾𝑅) versus Au NP diameter were used to estimate the hydrodynamic size (𝑅) of the dendrimers with their √𝐾𝑅 values. The √𝐾𝑅 for dendrimers 3 and 4 were 0.28 and 0.54, respectively. The diameters of dendrimers 3 and 4 were estimated to be ~6 nm and ~29 nm, respectively. 60 Figure 2.7 (A) Images of agarose gels illuminated under UV light and white light. The dendrimers and Au NP standards had different mobilities at various gel densities. (B) Ferguson plots for DHLA-coated Au NP standards. (C) Plots of the square root of retardation factor versus Au NP diameter. The slope and intercept were used to estimate the diameter of dendrimers. (D) Ferguson plots for dendrimer 3 and 4. 2.2.1.5 Loading capacity of dendrimer 4 To estimate the loading capacity of dendrimer 4, various equivalents of dye-labelled biotinylated molecules were added and the samples subsequently analyzed by agarose gel electrophoresis and 61 their time-gated PL emission spectra. For the gel method, loading capacities were estimated from shifts in electrophoretic mobilities for the dendrimer and from the appearance of a band of non-conjugated biotinylated molecule. For the spectra, the loading capacity was estimated from reaching an approximate plateau in the dye/Tb PL ratio. The loading capacity of dendrimer 4 was 15−25 equivalents with biotin-FAM, 10−20 equivalents with biotin-oligonucleotide, and 10−15 equivalents with biotin-peptide (Figure 2.8). Figure 2.8 Biotinylated-molecule loading capacities of dendrimer 4. (A) Biotin-FAM: (i) PL image of an agarose gel and (ii) PL ratio (524 nm/490 nm) plot. (B) A546-labelled and biotinylated double-stranded oligonucleotide (Blk2-A546/Prb2 hybrid): (i) PL image of an agarose gel and (ii) PL ratio (572 nm/490 nm) plot. (C) A488-labelled and biotinylated peptide: (i) PL image of an agarose gel and (ii) PL ratio (516 nm/490 nm) plot. All agarose gels were 0.5% w/v. 62 Although the focus is on oligonucleotides in this chapter and the next, the binding of peptides and small molecules may prove useful in future permutations of the system. The somewhat similar binding capacities between the FAM, peptides, and oligonucleotides also suggested that loading was, at least in part, limited by available biotin binding sites and not just by steric considerations. 2.2.2 FRET pathways 2.2.2.1 Tb PL lifetime in cFRET configurations Dendrimer 5 with dye-labelled oligonucleotides was used to establish the competitive and sequential energy transfer (ET) pathways characteristic of cFRET. As listed in Table 2.2 (see Section 2.5.1), three different biotinylated oligonucleotide sequences (19 or 20 nucleotides (nt) in length) were hybridized with dye-labelled complementary oligonucleotides (14 or 15 nt) and multiple copies of each were subsequently bound to 4 (Figure 2.1C). The dye labels were Alexa Fluor 488 (A488), Alexa Fluor 546 (A546), and Cyanine 5 (Cy5). The absorption and emission spectra of each dye are shown in Figure 2.9A and selected photophysical properties and FRET parameters are listed in Table 2.1. These dyes were chosen because they had FRET-relevant spectral overlap with the Tb and one another, while also having emission peaks that were resolved from one another and the two most intense emission lines of the Tb. The anticipated ET pathways in the configuration are shown in Figure 2.9B. The Tb-to-A488, Tb-to-A546, and Tb-to-Cy5 pathways compete with one another as the first ET step. In turn, excitation of the A488 may be followed by the A488-to-A546 and A488-to-Cy5 pathways, which compete with one another. Likewise, excitation of A546 may be followed by the A546-to-Cy5 pathway. 63 Figure 2.9 FRET pairs and pathways. (A) Normalized absorption spectra (dashed lines) and emission spectra (solid lines) for the Tb, A488, A546, and Cy5. (B) Diagram of the six ET pathways in the cFRET configuration. Numbers indicate the sequence of ET pathways and lowercase letters indicate ET pathways that compete with one another. Two Tb are shown engaging in ET to convey that there are multiple possible donors. Table 2.1 Selected photophysical properties of donors and acceptors. Donor εa (M–1 cm–1) Φb τc (ns) FRET parametersd,e Acceptor A488 A546 Cy5 Tb 26 000 0.63 2.1 × 106 R0 (J) 4.8 (1.1) 6.4 (5.9) 6.2 (4.7) A488 73 000 0.54 3.7 R0 (J) 4.6 (0.90) 6.0 (4.9) 5.0 (1.6) A546 112 000 0.46 2.9 R0 (J) -- 5.8 (4.3) 6.4 (8.4) Cy5 250 000 0.19 1.2 R0 (J) -- -- 6.0 (13) a Peak molar absorption coefficient. The Tb value is for the complex. b Emission quantum yield. The Tb value is extrapolated from the lifetime of dendrimer 4 and the quantum yield (0.77) and lifetime (2.6 ms) for the Tb(III) ion in ref.93 . The values for the dyes are experimentally measured (see Appendix A.1 for detail). c Emission lifetime. The Tb value is for dendrimer 4. d Förster distance (R0 = nm). e Spectral overlap integral (J = 1015 M–1 cm–1 nm4). 64 The ET was characterized with different combinations of dyes. The shorthand notation used for permutations of the cFRET configuration is (L, M, N), where L, M, and N are numbers that represent the average equivalents of A488, A546, and Cy5 labels per dendrimer, respectively. ET efficiencies for Tb (donor)-to-dye (acceptor) pathways were assessed using PL lifetime measurements. Intensity measurements were unreliable because of the progressive change in Tb lifetime (with increasing ET efficiency) and corresponding change in the fraction of total emission within the signal integration time. Consistent with expectations for FRET, larger decreases in the Tb donor lifetime were observed with larger Förster distances for the Tb-dye pairs in the (5, 0, 0), (0, 5, 0), and (0, 0, 5) configurations (Figure 2.10A). Efficiencies were 30%, 55%, and 47%, respectively. This general trend also held with the (5, 5, 0), (5, 0, 5) and (0, 5, 5) configurations, and the (5, 5, 5) configuration had the largest overall decrease in Tb lifetime (Figure 2.10B). Moreover, the ET efficiencies measured for the (5, 0, 0), (0, 5, 0), and (0, 0, 5) configurations reasonably predicted (via the combination of Eqns. 2.9 and 2.10; see Section 2.5.12) the ET efficiencies observed for the (5, 5, 0), (5, 0, 5), (0, 5, 5), and (5, 5, 5) configurations (Figure 2.10C). 65 Figure 2.10 Tb PL decays and quenching efficiencies. (A) Tb PL decays and amplitude-weighted average lifetimes for the (0, 0, 0), (5, 0, 0), (0, 5, 0), and (0, 0, 5) configurations. This data was used to estimate Tb-to-dye ET efficiencies. Tb lifetimes were ± 0.07 ms or less. (B) Tb PL decays and amplitude-weighted average lifetimes for the (5, 5, 0), (5, 0, 5), (0, 5, 5), and (5, 5, 5) configurations. (C) Correlation between the measured and predicted Tb quenching efficiencies (QTb) for two-dye and three-dye configurations. Measured quenching efficiencies were calculated from PL lifetimes in panel B and predictions were derived from the one-dye data in panel A. 66 Dye (donor)-to-dye (acceptor) ET pathways were also assessed via PL lifetime measurements. The donor dye was directly excited for these measurements, bypassing the Tb (Figure 2.11). Decreases in A488 lifetime were observed for the (5, 5, 0) and (5, 0, 5) configurations versus (5, 0, 0). These results suggested FRET pathways from A488 to A546 and Cy5, with efficiencies of ~17% and ~10%, respectively. The largest decrease in A488 lifetime was observed for (5, 5, 5) versus (5, 0, 0), with a net ET efficiency of ~23%, consistent with competitive FRET from A488 to both A546 and Cy5. Decreases in A546 lifetime were observed for the (0, 5, 5) and (5, 5, 5) configurations versus (0, 5, 0), corresponding to an A546-to-Cy5 ET efficiency between ~5% and ~11%. Figure 2.11 Dyes PL decays. (A) A488 PL decays and lifetimes for the (5, 0, 0), (5, 5, 0), (5, 0, 5), and (5, 5, 5) configurations, indicating ET from the A488 to A546 and Cy5. Dye lifetimes were ± 0.3 ns or less, with the exception of ± 0.6 ns for (5, 0, 0). (B) A546 PL decays and lifetimes for the (0, 5, 0), (0, 5, 5), and (5, 5, 5) configuration, indicating ET from A546 to Cy5. Dye lifetimes were ± 0.2 ns, with the exception of ± 0.4 ns for (5, 5, 5). For the data in panels A and B, the dyes were directly excited. 67 2.2.2.2 Prompt and time-gated excitation spectra Given the small changes in dye lifetimes with FRET, both prompt and time-gated excitation spectra were measured for each dye to gain further insight into dye-to-dye ET pathways. Although the prompt excitation spectrum for each dye was dominated by the absorption feature for that dye (i.e. direct excitation), additional features were also observed. In the (5, 5, 0) configuration, the prompt excitation spectrum for A546 had a small feature that corresponded to A488 absorption, consistent with ET from A488 to A546 (Figure 2.12A). The A488-to-Cy5 and A546-to-Cy5 ET pathways were similarly indicated by small features for the absorption of A488 and A546 in the prompt Cy5 excitation spectra for the (5, 0, 5) and (0, 5, 5) configurations, respectively. For the (5, 5, 5) configuration, an absorption feature for A488 was again observed in the prompt A546 excitation spectrum, and absorption features for both A488 and A546 excitation peaks were observed in the prompt Cy5 excitation spectrum. In all cases, control experiments confirmed that emission crosstalk did not account for the absorption peaks for nominal donor dyes in the prompt excitation spectra of the nominal acceptors. As expected, the time-gated excitation spectra for all dyes showed only the Tb absorption feature, indicating that all time-gated signals originated from the initial Tb donor (Figure 2.12B). 68 Figure 2.12 Prompt and time-gated excitation spectra for various cFRET configurations. (A) Prompt excitation spectra: the black curve is the experimental data; the green, orange, and red curves show the individual contributions of A488, A546, and Cy5; the dashed curves show the excitation spectra for control samples (used to estimated upstream dye contributions from direct excitation and emission crosstalk). (B) Time-gated excitation spectra. 69 2.3 Discussion To date, cFRET probes have been exclusively based on QDs, with the QD serving as both a scaffold and an initial donor. In the new cFRET configuration design presented here, the scaffold and initial donor roles were split between two materials: the G6 PAMAM dendrimer was the scaffold and Tb was the initial donor. The advantages and disadvantages of the Tb is discussed in the next chapter, and the advantages and disadvantages of the G6 PAMAM dendrimer are discussed below. The three-dimensional size and multiple surface-accessible amine groups of G6 PAMAM dendrimer made it a useful scaffold material, supporting multiple copies of Tb and biotin. In turn, the biotin enabled further conjugation with multiple copies of NAv and biotinylated oligonucleotides and peptides. The high affinity of the biotin-NAv interaction94,95 was useful in that it provided good control over the stoichiometry of dyes per Tb-labelled G6. The NAv also makes the system compatible with a wide array of biomolecular probes—likely any biomolecule that has a size amenable to FRET and that can be biotinylated and directly or indirectly labelled with a fluorescent dye. Although convenient for proof-of-concept because of its ready availability and reactivity with succinimidyl esters, PAMAM is not necessarily the optimum dendrimer material for future cFRET configurations. It has potential limitations with susceptibility to non-specific binding interactions, potential (cyto)toxicity,96–98 and other aspects of biocompatibility. Indeed, functionalization with PAA and NAv may have masked some of the less optimal properties of PAMAM dendrimer in 70 this study. Hydrophilic polyester dendrimers,99–102 hydrophilic polyamide dendrimers,99,100 or materials such as hyperbranched polyglycerol103 and dendritic and star-like DNA structures104,105 are potentially useful alternatives to PAMAM dendrimers to consider in future work. Custom synthesis of a dendrimer would also allow tailoring of the core material and outermost functional group(s) to achieve an optimal combination of properties. Beyond the donor and scaffold, another difference between this new cFRET probe and prior QD-based cFRET probes was that the dye-to-dye ET was less efficient. This result was despite the inter-dye Förster distances being larger than those for prior QD-based probes. The difference likely arose from a combination of factors: lower numbers of equivalents of each dye per dendrimer, greater repulsion between dendrimer-bound oligonucleotides than between QD-bound peptides, and the added layer of NAv protein (~5.6 nm × 5 nm × 4 nm).106 The NAv increases the overall radius of the cFRET probe and thus the average linear distance between dyes. 2.4 Conclusion The first of a new generation of QD-free cFRET probes was developed by leveraging the size and multivalency of a G6 PAMAM dendrimer and the unique PL emission properties of a luminescent Tb complex. The Tb-labelled G6 PAMAM dendrimer had a role analogous to the QD in an archetypical cFRET configuration. Co-labelling of the G6 PAMAM dendrimer with biotin enabled conjugation with NAv and, subsequently, biotinylated oligonucleotides and peptides. The oligonucleotides were hybridized with complementary sequences labelled with A488, A546, and Cy5 to establish the competitive and sequential ET pathways characteristic of cFRET. More generally, this work has shown that QDs are not the only viable material for assembling cFRET 71 probes and that a combination of a molecular luminophore and non-luminescent nanomaterial can fulfill the initial donor and scaffold roles. This finding opens the door to a wide array of materials for developing cFRET probes. 2.5 Experimental methods 2.5.1 Materials Lumi4-Tb-NHS was from Lumiphore (Berkeley, CA, USA). Generation 6 PAMAM dendrimer, PAA (MW ~1800), biotin, biotin-FAM, dicyclohexylcarbodiimide (DCC), tetramethylammonium hydroxide (TMAH) solution (25% w/w in H2O), N,N-dimethylformamide (DMF), diethyl ether, dimethyl sulfoxide (DMSO), Sephacryl 200-HR, Amicon centrifugal filters (MWCO 30 kDa and 100 kDa, Ultracel membrane, 0.5 mL capacity), and bovine serum (B9433), trypsin (T1426) were from Sigma-Aldrich (Oakville, ON, Canada). NHS was from Merck Group (Darmstadt, Germany). NAv, NaCl, and 10× Tris-borate-ethylenediaminetetraacetic acid (TBE) buffer were from Thermo-Fisher Scientific (Burlington, ON, Canada). Oligonucleotides were from Integrated DNA Technologies (Coralville, IA, USA) and the sequences are listed in Table 2.2. Centrifugal devices (MWCO 100 kDa, Omega membrane, 5 mL capacity) were from Pall (Port Washington, NY, USA). Au NPs were from Cytodiagnostics (Burlington, ON, Canada). Lipoic acid (LA) was from Oakwood Chemical (Estill, SC, USA). Peptides were from BioSynthesis Inc. (Lewisville, TX, USA). Alexa Fluor 488 C5 maleimide and Alexa Fluor 555 C2 Maleimide were from Life Technologies (Carlsbad, CA, USA). Acetonitrile (ACN) was from VWR Chemicals BDH (Radnor, PA, USA). DMSO-d6 was from Cambridge Isotope Laboratories, Inc. (Tewksbury, MA, USA). Bio-Gel P-4 gel was from Bio-Rad (Hercules, CA, USA). Borate buffer and 4-(2-72 hydroxyethyl)piperazine-1-ethanesulfonic acid (HEPES) buffer were prepared and sterilized by filtration (0.22 μm pore-size filter). Table 2.2 Oligonucleotide sequences and symbols for the number of equivalents per dendrimer. Name Sequencec Number of Equiv. Prb1a 3’-GGATA CATGGCGAAGTGAC -5’-Biotin L Blk1-A488b 5’-GTACCGCTTCACTG T-3’-A488 L Prb2 3’-AAAGG GCAGAGAGTGTGTCG -5’-Biotin M Blk2-A546 5’-CGTCTCTCACACAGC -3’-A546 M Prb3 3’-TAGGT GTGCCGGTTCTCTA -5’-Biotin N Blk3-Cy5 5’-CACGGCCAAGAGAT -3’-Cy5 N a Prb: probe-strand oligonucleotide. b Blk: block-strand oligonucleotide. c The underlined portions of the probe strands do not hybridize with the block strands. 2.5.2 Synthesis of biotin-NHS Biotin (0.493 g, 2.02 mmol, 1.00 equiv.) and NHS (0.237 g, 2.06 mmol, 1.02 equiv.) were partially dissolved in anhydrous DMF (16 mL) and heated to 60 ○C until fully dissolved. DCC (0.557 g, 2.70 mmol, 1.34 equiv.) was added and the reaction was stirred overnight at room temperature. The white precipitate (dicyclohexylurea) was removed by filtration. The biotin-NHS product was then precipitated from the filtrate by adding diethyl ether (~125 mL). The white product was washed with diethyl ether. The isolated biotin-NHS was dried in vacuo and stored at –20 ○C until needed. ESI+ MS (MeOH): calcd. for C14H19N3O5SNa [M+Na]+ m/z = 364.37, found m/z = 364.0. NMR 1H (400 MHz, DMSO-d6): 6.40 ppm (d, 2H, J = 23.6 Hz), 4.30 ppm (t, 1H, J = 6.1 Hz), 4.15 ppm (t, 1H, J = 5.7 Hz), 3.10 ppm (dd, 1H, J = 11.4, 6.6 Hz), 2.85−2.81 ppm (m, 5H), 2.67 ppm (t, 2H, J = 7.3 Hz), 2.58 ppm (d, 1H, J = 12.4 Hz), 1.68−1.37 ppm (m, 6H). 73 2.5.3 Preparation of the cFRET probe Lumi4-Tb and biotin-labelled dendrimer 2 The PAMAM dendrimers (1) were received as a dispersion in MeOH. The dendrimers were aliquoted into 1.7 mL-microcentrifuge tubes (~39 nmol per tube), dried in vacuo, and stored at 4 ○C until needed. Lumi4-Tb-NHS and biotin-NHS were dissolved in anhydrous DMSO to final stock concentrations of 5.7 mM and 50 mM, respectively. The stocks were stored at –20 ○C until needed. Dried PAMAM dendrimer 1 (~39 nmol, 1.0 equiv.) was dispersed in 533 μL of borate buffer (125 mM, pH 8.6), and then diluted with 533 μL of water. In another tube, Lumi4-Tb-NHS (~500 nmol, 12.7 equiv.) and biotin-NHS (~1.9 μmol, 48 equiv.) were diluted in anhydrous DMSO to a final volume of 533 μL. The solution of Lumi4-Tb-NHS and biotin-NHS was added to the dendrimer solution. The mixture was protected from light and reacted overnight at room temperature. Four aliquots of the reaction mixture (5 μL × 4, 0.12 nmol × 4 of dendrimer) were used for agarose gel electrophoresis to characterize the labelling efficiency. The remainder of the reaction mixture (~1.58 mL, ~39 nmol of dendrimer) was used for further preparation. Note: A high percentage of DMSO in solution appeared to cause leakage of Tb3+ ions from the complex. To avoid the leakage of Tb3+, solutions with a high percentage of aqueous buffer were preferred. 74 For agarose gel electrophoresis, water (11.7 μL) was added to the aliquots of reaction mixture to reduce the percentage of organic solvent. After 1 h, borate buffer (33 μL, 100 mM, pH 8.6) was added along with an aqueous solution of PAA (~49 nmol, 10 mM, 400 equiv.), and this mixture was sonicated for ~15 s and then agitated on a rotary mixer for another 1 h. (The PAA imparted a net negative charge to the dendrimers and helped in obtaining a band that was separate from the free Lumi4-Tb band in the gel electrophoresis analysis.) An aliquot of the new mixture (1.3 μL, ~3.3 pmol of dendrimer) was diluted with 50 mM borate buffer (16 μL) and used for agarose (0.5% w/v) gel electrophoresis analysis (vide infra) without further purification. For further preparation, the original reaction mixture was divided into 11 tubes (10 × 145 μL aliquots tubes and 1 × ~100 μL aliquot). Water (338 μL and 223 μL) was added to the tubes to lower the concentration of DMSO. After 1 h, additional water (994 μL and 667 μL) was added to further lower the concentration of DMSO (for better compatibility with 30 kDa Ultracel membrane centrifugal filters). The reaction mixtures were concentrated and purified with 30 kDa centrifugal filters. Each centrifugal device held the first aliquot of 500 μL reaction mixture and was spun at 14 000 RCF for 10 min. Another aliquot 500 μL of the reaction mixture was added into the centrifugal device and was spun again. This step was repeated two or three times to obtain a final volume ~23 μL in individual tubes. The residue was further washed three times with three portions of 500 μL of borate buffer (50 mM, pH 8.6) with centrifugation at 14 000 RCF for 10 min. The purified residue was then diluted with borate buffer to a final concentration of ~36 μM dendrimer and stored at 4 ○C until needed. The dendrimer 2 concentration was determined from the absorption peak of the Lumi4-Tb (molar absorption coefficient 26 000 M–1 cm–1 at 340 nm). The labelling 75 efficiency was estimated by combining results of gel electrophoresis analysis and lifetime analysis. Further details can be found in Section 2.5.4. Note: A smaller scale of the reaction (~3.5 nmol of dendrimer 1) was successful using the same procedures with scaled down reagent quantities. Dendrimer 2 coated with PAA to form dendrimer 3 PAA was dissolved in water to a final concentration of 10 mM and this stock solution was stored at 4 ○C until needed. Borate buffer (50 mM, pH 8.6, 1.44 mL) was added to an aliquot of PAA (96 µL, ~960 nmol, 400 equiv.) stock solution to maintain the pH, and then dendrimer 2 (66 µL, ~2.4 nmol, 1 equiv.) was added. The mixture was then sonicated for ~40 s. The final volume was 1.6 mL, the final concentration of dendrimer was 1.5 μM, and the concentration of borate buffer was 47 mM. The mixture was agitated on a rotary mixer for ≥ 1 h at room temperature. The excess PAA was removed via spin filtration with 30 kDa centrifugal filter. First, the volume of the reaction mixture (1.6 mL) was reduced via spin filtration with a 30 kDa centrifugal filter (14 000 RCF, 10 min). Another aliquot of 500 μL of the reaction mixture was added into the centrifugal device and was spun again. This step was repeated three times to reduce the volume to ~125 μL. Second, the excess PAA was removed using the same 30 kDa centrifugal filter. The collected residue was washed with three 500 μL portions of 50 mM borate buffer (14 000 RCF, 10 min), then dispersed in borate buffer to a final concentration of ~20 μM and stored at 4 ○C until needed. Note: A smaller scale of the reaction (~0.7 nmol of dendrimer 2) was successful using the same procedures with scaled down reagent quantities. 76 Dendrimer 3 conjugated with NAv to form dendrimer 4 Lyophilized NAv protein from the supplier (1.5−3.8 mg) was dissolved in 45−120 μL water and further diluted with an equal volume of borate buffer (20 mM, pH 8.6) to a final concentration of 180−230 μM. The concentrations of NAv solutions were determined by absorption (molar absorption coefficient of 99 600 M–1 cm–1 at 280 nm). Borate buffer (50 mM, pH 8.6, 970−990 μL) was added to an aliquot of 50−65 μL NAv solution (~12 nmol, 30 equiv.) and an aliquot of 100 uL of 4 μM dendrimer 3 (~0.4 nmol, 1 equiv.) was added. The final volume was 1.14 mL, the concentration of dendrimer was 0.35 μM and the concentration of borate buffer was ~48 mM. One to three reactions at this scale were usually run simultaneously. The mixture was agitated on a rotary mixer for ≥ 2 h at room temperature and stored at 4 ○C until ready for further purification. All of the parallel reaction mixtures were combined together and concentrated using a Pall 100 kDa centrifugal filter (1000 RCF, 5−15 min). The residue was purified on a Sephacryl 200-HR size exclusion column, where the media was packed in a column with a 1 cm diameter and had a bed volume of ~21 mL. The eluate was collected and the fractions with only NAv-conjugated dendrimers were combined. Absorption measured at 280 nm and 340 nm, and PL emission measured at 548 nm (excited at 340 nm), were used to determine the fractions with NAv-conjugated dendrimer 4. If needed, the purified NAv-conjugated dendrimer was further concentrated using a 100 kDa centrifugal filter (1000 RCF, 5 min). The final concentrations of dendrimer 4 were 0.8−3.4 μM. Dendrimer 4 was stored at 4 ○C until needed. 77 Note: To avoid adverse effects on the NAv protein, a low speed of centrifugation is recommended. Dendrimer 4 was successfully obtained using combination of Sephacryl 200-HR size exclusion column and 3000 RCF for 10 min (Amicon centrigugal filters MWCO 100 kDa). Dendrimer conjugated with (pre-hybridized) oligonucleotides (dendrimer 5) and PL measurements for (L M, N) combinations Oligonucleotides (12−155 nmol) were dissolved in nuclease-free water to a final concentration of 25−190 mM, then stored at –20 ○C until needed. Biotinylated probe oligonucleotides were hybridized with dye-labelled blocking oligonucleotides strands at a 1:1 ratio in borate buffer (50 mM with 400 mM NaCl, pH 8.6) for 6 h at room temperature. The final concentration of hybridized DNA was 10 μM, and the solutions were stored at 4 ○C until needed. To collect the cFRET calibration data set for different (L, M, N) combinations, samples of the DNA-conjugated dendrimers were prepared in several steps. First, the pre-hybridized DNA solutions were further diluted with borate buffer (50 mM with 400 mM NaCl, pH 8.6) to final concentrations of 1.1 μM. Second, 2.2 pmol × L of pre-hybridized Biotin-DNA-A488, 2.2 pmol × M of pre-hybridized Biotin-DNA-A546, and 2.2 pmol × N of pre-hybridized Biotin-DNA-Cy5 were mixed and diluted with borate buffer (50 mM with 400 mM NaCl, pH 8.6) to a final volume of 34 μL. All combinations of L, M, and N values of 0, 2, 3.5, 5 were prepared, amounting to 64 samples. Third, 53.4 μL of 2.88 μM dendrimer 4 (154 pmol of dendrimer) was diluted with 125 mM borate buffer and water, then mixed with 140 μL of 2 M NaCl to obtain a dendrimer concentration of 0.22 μM in borate buffer (54 mM with 400 mM NaCl). Lastly, a 10 μL aliquot of the dendrimer solution (2.2 pmol, 1 equiv.) was added to each DNA permutation, where the final 78 dendrimer concentrations were 0.05 μM (total volume of 44 μL). The samples were mixed thoroughly, then protected from light and left to stand for 2 h at room temperature. An aliquot (40 μL) of the samples were transferred into a well of a 384-well black plate for PL measurements. Note: A high ionic strength had the potential to reduce the colloidal stability of dendrimer 4. The 0.22 μM dendrimer 4 solution with 400 mM NaCl was therefore freshly prepared. 2.5.4 Absorption and emission measurements The absorption and PL excitation and emission spectra were measured using an Infinite M1000 Pro plate reader (Tecan Ltd., Morrisville, NC) equipped with a xenon flash lamp, excitation and emission monochromators, and a photomultiplier tube detector. For absorption measurements, sample volumes of 80 or 170 μL were aliquoted into a clear-bottom half-area 96-well plates (#675801; Greiner, Monroe, NC) having a 0.5 or 1.0 cm pathlength for absorption measurements. The concentrations of Lumi4-Tb were measured using its UV absorption peak at 340 nm (molar absorption coefficient 26 000 M–1 cm–1). For PL emission measurements, sample volumes of 40 μL at 0.05 μM concentration were dispensed into a 384-well black plate (#3575; Corning, Corning, NY) and excited at 340 nm (excitation bandwidth was varied between 5−20 nm; emission bandwidth was 5 nm). Prompt measurements corresponded to acquisition of an emission signal with a 0 μs delay after a flash of excitation light. Time-gated measurements corresponded to acquisition of an emission signal with a 60 µs delay after a flash of excitation light. The integration time was 2000 μs for prompt and 79 time-gated emission measurements. For measurement of prompt excitation spectra, the excitation wavelength (5 nm bandwidth) was scanned and emission was collected at 530, 630, and 700 nm (20 nm bandwidth). For measurement of time-gated excitation spectra, the excitation wavelength (7 nm bandwidth) was scanned and emission was collected at 520, 548, 608, and 675 nm (20 nm bandwidth). 2.5.5 Gel electrophoresis Samples were diluted with buffers as described earlier. Glycerol/H2O (4.2 μL, 50% v/v) was mixed with a 16.8 μL aliquot of sample (final glycerol concentration of 10% v/v). Aliquots (20 µL) of sample with glycerol (3−5 pmol of dendrimers) were loaded into the wells of a 0.3−1.5% w/v agarose gel. Tris-borate-EDTA buffer (89 mM Tris, 89 mM boric acid, 2 mM EDTA, pH 8.3) was the running buffer. The field strength was ~6.7 V/cm with a run time of 30 min. The gel was imaged with a Gel Doc XR+ Imager (Bio-Rad, Mississauga, ON, Canada) equipped with a UV excitation source. The images were analyzed using the integrated density function in Image J software (National Institutes of Health, Bethesda, MD). 2.5.6 Lifetime measurements Tb PL Lifetime Measurements Some of the time-resolved PL measurements for the Tb (Figure 2.3) were made using a FluoroCube (Horiba Jobin Yvon) in multichannel scaling mode. The Fluorocube was equipped with a 355 nm LED light source. Samples (dendrimer 2, Lumi4-Tb) were dispersed or dissolved in borate buffer (pH 8.6) to final concentrations corresponding to 1−5 μM of Lumi4-Tb. Samples 80 (400 µL) were measured in a quartz micro cuvette (#18F-Q-10; Starna Cells, Inc., Atascadero, CA). Time bins were 100 μs with 500 channels per sweep. Other time-resolved PL measurements for the Tb (Figure 2.10A−B) were made using an FLS1000 photoluminescence spectrometer (Edinburgh Instruments Ltd., Livingston, United Kingdom) equipped with a xenon microsecond flash lamp. Samples (100 µL) were dispersed in borate buffer (50 mM with 400 mM NaCl, pH 8.6) to a final concentration of 0.05 μM and transferred to a sub-micro quartz cuvette (#16.100F-Q-10/Z15; Starna Cells, Inc., Atascadero, CA). The samples were excited at 340 nm (10 nm bandwidth). The source trigger delay was 0.500 ms, the time range was 20 ms, and the delay time was 0.700 ms. A longpass filter (400 nm cut-off) was insert into the optical axis for collection emission. Emission was measured at 490 nm (2 nm monochromator bandwidth). This emission wavelength and bandwidth minimized collection of any dye emission during the measurements. The lifetime decay curves were fit with an exponential decay function, and the lifetime (single exponential function; e.g. Tb alone and directly excited dye fluorescence) or amplitude-weighted average lifetimes (biexponential function; e.g. Tb in dendrimer configurations) were reported. Dye PL lifetime measurements Samples (100 µL) were dispersed in borate buffer (50 mM with 400 mM NaCl, pH 8.6) to a final concentration of 0.05 μM and transferred to a sub-micro quartz cuvette. The excitation pluses were generated with a Nd:YAG laser (PL2241; EKSPLA, Vilnius, Lithuania) at 355 nm with 35 ps pulse duration and 10 Hz repetition. The laser output was wavelength-tuned with a picosecond 81 optical parametric generator (PG401; EKSPLA, Vilnius, Lithuania). Wavelength-resolved lifetime data were obtained with an Acton spectrometer (Princeton Instruments, Trenton, NJ) and a streak camera (C7700; Hamamatsu Photonics, Hamamatsu, SZK, Japan). The samples were excited with laser pulses at 430 nm (or 440 nm) for A488, 530 nm for A546, and 615 nm for Cy5. The time-resolved spectra were collected between 396−758 nm (A488 and A546) or 466−828 nm (Cy5) with a 50 ns time window. A longpass filter (450 nm cut-off) was insert into the optical axis for collection of emission when samples were excited at 430 nm (or 440 nm). For analysis of the lifetime of each dye, a range of wavelengths around the dye peak was selected and avoided overlap with emission from any other dyes present. Emission from the Tb was negligible on the 50 ns time scale because of its much slower rate of emission. 2.5.7 Estimating the efficiency of labelling dendrimer 2 with Lumi4-Tb The method was analyzing the PL intensity of the unconjugated and dendrimer-conjugated bands for Lumi4-Tb on an agarose gel after electrophoretic separation. The labelling efficiency was estimated from a PL image of the gel using the integrated intensities, B, of each band, as per Eqn. 2.3: 𝐿𝑎𝑏𝑒𝑙𝑙𝑖𝑛𝑔 𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 = 𝐵𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑𝐵𝑢𝑛𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑 + 𝐵𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑 × 100% (2.3) To help improve the accuracy of this calculation, a correction was made for a potential difference in quantum yield between unconjugated and dendrimer 3-conjugated Lumi4-Tb. This difference in quantum yield, 𝛷, was estimated from the change in PL lifetime, τ, assuming that any change in lifetime was from a change in the rate of non-luminescent pathways, as per Eqn. 2.4: 82 𝛷𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑 = 𝜏𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑𝜏𝑢𝑛𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑× 𝛷𝑢𝑛𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑 (2.4) The labelling efficiency was then estimated from band PL intensities using Eqn. 2.5. The measured lifetime of unconjugated Lumi4-Tb in borate buffer (50 mM, pH 8.6) was 2.8 ms, versus 1.9 ms for dendrimer-conjugated Lumi4-Tb. A quantum yield value of 𝛷𝑢𝑛𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑 = 0.60 was taken as the net emission quantum yield of the unconjugated Lumi4-Tb complex.9,93 With this method, a labelling efficiency of ~64% was calculated, corresponding to ~8.1 Lumi4-Tb per dendrimer. 𝐿𝑎𝑏𝑒𝑙𝑙𝑖𝑛𝑔 𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 ≡ 𝐵𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑𝛷𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑𝐵𝑓𝑟𝑒𝑒𝛷𝑓𝑟𝑒𝑒+ 𝐵𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑𝛷𝑐𝑜𝑛𝑗𝑢𝑔𝑎𝑡𝑒𝑑 (2.5) 2.5.8 Labelling efficiency of biotin The efficiency of labelling dendrimer 2 with biotin was evaluated by analyzing the concentration of unlabelled biotin in the filtrate using a mass spectrometer (Waters ZQ) equipped with an ESI ionization source. Biotin-NHS was dissolved in DMSO to a final concentration of 16 mM as a stock solution. To take possible matrix effects into account, standard solutions of biotin were prepared using a mixture of DMSO, borate buffer, and water (to match the matrix of the filtrate) to final concentrations of 0, 20, 40, 60, 80, and 100 μM biotin. The final composition of the solvent was 3.3% v/v DMSO and 4.2 mM borate salts in water. An aliquot of sample (5 μL) was injected with a 1:1 solvent mixture of MeOH and H2O with 0.1% formic acid as the mobile phase. The concentration of biotin was analyzed by integrating and summing the peak areas having [M+H]+ m/z = 245.3 and [M+Na]+ m/z = 267.3. 83 2.5.9 Dynamic light scattering measurements Samples were dispersed in borate buffer (50 mM, pH 8.6) to final concentration of ~0.4 μM. Measurements were made using a NanoBrook Omni particle size analyzer (Brookhaven Instruments Corporation, Holtsville, NY) equipped with a 640 nm laser. 2.5.10 Ferguson analysis A Ferguson analysis was used for estimating the sizes of modified dendrimers, as described previously for other nanomaterials.107,108 A series of DHLA-coated Au NPs were used as nanoparticle size standards. The diameters of the Au NPs were 5, 10, 15, and 20 nm (Cytodiagnostics, Burlington, ON, Canada). These Au NPs were stabilized with citrate ligands and dispersed in 0.1 mM PBS with concentration between 90 nM−1 nM (larger particles had lower concentrations) as received. The Au NPs were re-coated with more stable DHLA ligands via ligand exchange. Briefly, 1 mL of Au NP stock was mixed with 11−14 mg of lipoic acid (LA) and vortexed vigorously until the LA was fully dissolved. The solutions changed colour from red to purple. Subsequently, 200 μL of TMAH solution (25% w/w in H2O) was added, turning the colour back to red. The mixtures were agitated overnight at room temperature. The excess ligands were removed by centrifugation of the Au NPs to a pellet (21 300−6500 RCF, 45−30 min) and discarding the supernatant. The pellets were re-dispersed in water (500 μL). The DHLA-coated Au NPs were washed with water in this manner two times, then re-dispersed in ~50 μL of water. 84 DHLA-coated Au NPs and modified dendrimers were run on a series of agarose gels with agarose concentrations between 0.3−1.5% w/v. The sample preparation for Ferguson analysis was the same as for other gel electrophoresis analyses (vide supra). 2.5.11 Calculation of FRET parameters The Förster distance, 𝑅0 (in nm), for each FRET pair was calculated using Eqn. 2.7, where the 𝜅2 = 2/3 was the assumed orientation factor, 𝛷𝐷was the quantum yield of the donor, 𝑛 (=1.334) was the refractive index of the solvent, and 𝐽 was the spectral overlap integral of a FRET pair. The 𝐽 (in mol–1 cm–1 nm4) was calculated using Eqn. 2.8, where the λ was wavelength in nm, and 𝐼𝐷(𝜆) was the PL intensity of the donor as a function of wavelength, and 𝜀𝐴 (in M–1 cm–1) was the molar absorption coefficient of the acceptor as a function of wavelength. 𝑅0 = 0.02108(𝜅2𝛷𝐷𝑛−4𝐽)1 6⁄ (2.7) 𝐽 =∫ 𝐼𝐷(𝜆)𝜀𝐴(𝜆)𝜆4𝑑𝜆∫ 𝐼𝐷(𝜆)𝑑𝜆 (2.8) 2.5.12 ET efficiency calculations and predictions The ET efficiency, E, from Tb to all possible dye acceptors in a configuration was calculated from the change in measured Tb PL lifetime as per Eqn. 2.9. 𝐸𝑇𝑏,𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑑(𝐿,𝑀, 𝑁) = 1 − [𝜏𝑇𝑏(𝐿,𝑀,𝑁)𝜏𝑇𝑏(0, 0, 0)] (2.9) Experimental measurement of the Tb ET efficiency for separate series of (L, 0, 0), (0, M, 0), and (0, 0, N) configuration samples permitted calculation of the corresponding relative rate of Tb-to-85 dye energy transfer, ΓTb-dye. The values were then used to predict the total ET efficiency for (L, M, N) configurations using Eqn. 2.10. 𝐸𝑇𝑏,𝑝𝑟𝑒𝑑(𝐿,𝑀, 𝑁) =Γ𝑇𝑏−𝐴488(𝐿, 0, 0) + Γ𝑇𝑏−𝐴546(0,𝑀, 0) + Γ𝑇𝑏−𝐶𝑦5(0, 0, 𝑁)1 + Γ𝑇𝑏−𝐴488(𝐿, 0, 0) + Γ𝑇𝑏−𝐴546(0,𝑀, 0) + Γ𝑇𝑏−𝐶𝑦5(0, 0, 𝑁) (2.10) Experimental dye-to-dye ET efficiencies were calculated using the measured lifetime of the donor dye. The efficiencies of the A488-to-A546, A488-to-Cy5, and A546-to-Cy5 ET pathways in two-dye configurations were calculated using Eqns. 2.11−2.13. The net ET efficiency or quenching efficiency, Q, for A488 in the (5, 5, 5) configuration was calculated using Eqn. 2.14. Likewise, the quenching efficiency for A546 in the (5, 5, 5) configuration was calculated using Eqn. 2.15. 𝐸𝐴488−𝐴546,𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑑(𝐿,𝑀, 0) = 1 − [𝜏𝐴488(𝐿,𝑀, 0)𝜏𝐴488(𝐿, 0, 0)] (2.11) 𝐸𝐴488−𝐶𝑦5,𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑑(𝐿, 0, 𝑁) = 1 − [𝜏𝐴488(𝐿, 0, 𝑁)𝜏𝐴488(𝐿, 0, 0)] (2.12) 𝐸𝐴546−𝐶𝑦5,𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑑(0,𝑀,𝑁) = 1 − [𝜏𝐴546(0,𝑀,𝑁)𝜏𝐴546(0,𝑀, 0)] (2.13) 𝑄𝐴488,𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑑(𝐿,𝑀,𝑁) = 1 − [𝜏𝐴488(𝐿,𝑀,𝑁)𝜏𝐴488(𝐿, 0, 0)] (2.14) 𝑄𝐴546,𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑑(𝐿,𝑀,𝑁) = 1 − [𝜏𝐴546(𝐿,𝑀,𝑁)𝜏𝐴546(0,𝑀, 0)] (2.15) 86 Chapter 3: Applications of Dendrimer-Based Time-Gated cFRET Probes for Multiplexed Sensing This chapter includes both published and unpublished work. An adaption of the text was reproduced from Tsai, H.-Y.; Algar, W. R., A Dendrimer-Based Time-Gated Concentric FRET Configuration for Multiplexed Sensing. ACS Nano 2022, 16, 8150−8160, with permission from the American Chemical Society. The smartphone section was unpublished work that is a manuscript in preparation, where the data was contributed from Kanani, S. S., and I provided the dendrimer material for the experiments. 3.1 Introduction Chapter 2 presented a novel dendrimer-based cFRET configuration that used luminescent terbium(III) complexes (Tb) as donors and different combinations of three different dye-labelled oligonucleotides (i.e. A488, A546, and Cy5-labelled) as acceptors. The physical properties and ET within these configurations were also characterized in Chapter 2. Here, the current chapter evaluates the potential analytical utility of the dendrimer-based cFRET configuration and a simpler FRET configuration. Multiple approaches to analysis were explored. First, proof-of-concept for time-gated, triply-multiplexed DNA sensing with the dendrimer-based cFRET probes was demonstrated. A calibration data based on PL emission ratios for different numbers of each dye-labelled oligonucleotide per QD was mathematical fit to an empirical model, and this model enabled 87 quantitative analysis. Second, to demonstrate robust compatibility for the probes under various conditions, experiments were done in different buffer systems and in serum. The buffer change was well tolerated and time-gating successfully rejected the background autofluorescence from the serum while also retaining the PL ratio calibration and selective recognition of target DNA. Third, to demonstrate potential application in point-of-care diagnostics, a FRET probe based on the dendrimer system was tested for target DNA detection with measurement via a smartphone-based time-gated imaging platform (STGIP). Lastly, to show the possibility of a broader scope of biomolecular targets for the dendrimer-based system, a peptide-conjugated probe was developed and sensing of proteolytic activity was demonstrated. Overall, this chapter shows that Tb-labelled dendrimer-based probes are a promising platform for bioanalysis. 3.2 Results 3.2.1 PL emission spectra, PL ratios, and mathematical fitting The ET network between Tb (dendrimer 5) and A488, A546, and Cy5 cFRET system was characterized in Chapter 2 on the basis of changes in Tb donor lifetime (for Tb-to-dye ET) and dye donor lifetime (for dye-to-dye ET). Here, mathematical correlations between numbers of each type of dye per dendrimer 5 (see Figure 2.1) and the PL ratios were developed. Analogous to Chapter 2, the (L, M, N) shorthand notation is used in this chapter for different permutations of the cFRET configuration, where L, M, and N are numbers that represent the average equivalents of A488, A546, and Cy5 labels per dendrimer, respectively. Figure 3.1A shows PL emission spectra for 12 selected (L, M, N) configurations for dendrimer 5. The PL emission spectra for all 64 permutations of L (= 0, 2, 3.5, 5), M (= 0, 2, 3.5, 5), and N (= 0, 2, 3.5, 5) can be found in the Appendix B.1. For permutations with just one dye, the dye/Tb PL ratios (ρdye/Tb) increased as the value of L, M, or N 88 increased. With two or three dyes, each dye/Tb PL ratio trended higher with an increasing number of upstream dyes (i.e. A488 for A546, both A488 and A546 for Cy5) and trended lower with an increasing number of downstream dyes (i.e. both A546 and Cy5 for A488, Cy5 for A546). These trends, summarized in Figure 3.1B, were consistent with the ET pathways in Figure 2.9B. Figure 3.1 Time-gated PL emission. (A) Representative examples of PL emission spectra for cFRET configurations (0, 0, N), (0, M, 5), and (L, 3.5, 5). The PL emission spectra for all 64 measured (L, M, N) permutations can be found in the Appendix B.1. L, M, and N are the average numbers of A488, A546, and Cy5, respectively, per dendrimer 5. The colours in the legend match the colour of the corresponding spectrum. (B) Plots of the (i) A488/Tb, (ii) A546/Tb, and (iii) Cy5/Tb PL emission ratios as a function of L, M, and N, respectively (64 points). Analytically, Figure 3.2A shows that each (L, M, N) permutation had a unique coordinate in a three-dimensional plot with each PL ratio representing an axis. This result is similar to prior QD-89 based cFRET configurations.50–52,86,87 The 64 data points were fitted with empirical functions that related the PL ratio space to the values of L, M, and N (see Section 3.5.8 and Appendix B.2 for detail). Importantly, for a given set of experimental PL ratios, (ρA488/Tb, ρA546/Tb, ρCy5/Tb), these functions were solvable for the values of L, M, and N. The histogram in Figure 3.2B shows that the solved values (i.e. calculated) were very close to the actual values, within ± 0.2 for the majority of the permutations. With this capability, the cFRET configuration was determined to be potentially useful for quantitative triply multiplexed sensing. Figure 3.2 PL ratios and (L, M, N) values. (A) Three-dimensional plot with each dye/Tb PL ratio along an axis. The 64 data points were coloured with RGB values according to the actual values of L (green), M (blue), and N (red). Each (L, M, N) permutation is a unique point in this space. (B) Determination of calculated (L, M, N) from the (ρA488/Tb, ρA546/Tb, ρCy5/Tb) PL ratios. The histogram shows the differences between actual (L, M, N) values and those calculated from (ρA488/Tb, ρA546/Tb, ρCy5/Tb) and mathematical fitting of the PL ratio space. The calculated values were within ± 0.2 of the actual values in ≥60 of the 64 cases for each of L, M, and N. (Note: the histogram bins are centred on the middle bar for M. The bin size is 0.25.) 3.2.2 DNA displacement assay To demonstrate quantitative triply multiplexed sensing with the dendrimer-based cFRET configuration, a toehold-mediated strand displacement assay was used as a model system. The 90 sequences of the three different oligonucleotides are listed in Table 3.1. As illustrated in Figure 3.3A, biotinylated probe strands (19 or 20 nt) and dye-labelled block strands (14 or 15 nt) were pre-hybridized, leaving a 5 base-pair toehold at the distal terminus, then bound to NAv-coated dendrimer 4 to form dendrimer 5 as the cFRET probe. Five equivalents of all three dye-labelled duplexes were added to yield an (L, M, N) = (5, 5, 5) configuration suitable for the detection of three corresponding oligonucleotide targets [Tgt1, Tgt2, Tgt3]. The targets (19 or 20 nt) displaced the block stands and their associated dye labels, effectively changing the value(s) of L, M, and/or N. 91 Figure 3.3 Toehold-mediated strand displacement assays with the (5, 5, 5) cFRET probe. (A) Target DNA oligonucleotides, [Tgt1, Tgt2, Tgt3], displaced the dye-labelled oligonucleotides, (Blk1-A488, Blk2-A546, Blk3-Cy5), from dendrimer 5 with loss of FRET. For clarity, only two of each dye are shown. (B) Progress curves for the displacement of (i) Blk1-A488 by Tgt1, (ii) Blk2-A546 by Tgt2, and (iii) Blk3-Cy5 by Tgt3 (5 equiv. of target in all cases). (C) PL ratio calibration data set (27 points) for displacement assays, obtained with different numbers of equivalents [l, m, n] of [Tgt1, Tgt2, Tgt3]. The calibration data points were coloured with RGB values according to the actual values of l (green), m (blue), and n (red). The star points (13 points) represent test samples with random combinations of [l, m, n]. (D) Histograms of the differences between actual and calculated [l, m, n] for the star points in panel C. The calculated values were within ± 0.5 of the actual values in ≥9 of the 13 cases for each of l, m, and n. (Note: the histogram bins are centred on the middle bar for m. The bin size is 0.25.) 92 As an initial experiment, the probes were mixed with 5 equivalents (250 nM) of Tgt1, Tgt2, and Tgt3 individually, and the corresponding PL ratios were measured as a function of time after mixing. As shown in Figure 3.3B, maximum displacement of Blk1 by Tgt1 required ~60 min, whereas the maximum displacement of Blk2 and Blk3 (by Tgt2 and Tgt3, respectively) required ~30 min. The changes in all three dye/Tb PL ratios over time were generally consistent with the ET pathways described earlier. For example, displacement of Blk2 and the decrease in the A546/Tb PL ratio was accompanied by a parallel increase in the A488/Tb PL ratio and a parallel decrease in the Cy5/Tb PL ratio. These trends were consistent with the acceptor role of A546 with A488 and the donor role of A546 with Cy5. The ET pathways from A488 to Cy5 and from A546 to Cy5 were also apparent in the increases in the A488/Tb and A546/Tb PL ratios with displacement of Blk3 and the main decrease in Cy5/Tb PL ratio. The possible exception was that there was little change in the A546/Tb and Cy5/Tb PL ratio in response to Tgt1. This result may have been from a combination of two effects: loss of A488-to-A546 ET being offset by increased Tb-to-A546 ET; and incomplete displacement of Blk1 (as suggested by the residual A488/Tb PL ratio in Figure 3.3Bi). To demonstrate a quantitative assay, the cFRET probe was calibrated by mixing the (5, 5, 5) probe with known equivalents of Tgt1, Tgt2, and Tgt3. To describe the number of equivalents of each target added, the shorthand notation [l, m, n] is used, where l, m, and n are the equivalents of Tgt1, Tgt2, and Tgt3, respectively, and had possible values of 0, 2.5, or 5 equivalents. Figure 3.3C shows the PL ratio values for the calibration data set. As anticipated from the binding of pre-hybridized dye-labelled DNA, the 27 permutations measured for dye displacement had unique 93 (A488/Tb, A546/Tb, Cy5/Tb) PL ratio combinations. The data was fit to the same form of mathematical model as the data in Figure 3.2, once again with good success in reproducing the PL ratio values and solving for values of l, m, and n. The displacement assay was next tested with 13 samples that had random combinations [l, m, n] for the three targets. Figure 3.3D shows histograms for [Δl, Δm, Δn], which are the differences between the actual number of target equivalents and the value calculated from the calibration data set with the 27 samples in Figure 3.3C. The means and standard deviation for [Δl, Δm, Δn] were [−0.1 ± 0.5, 0.0 ± 0.4, 0.0 ± 0.2]. The values of [Δl, Δm, Δn] for each sample are listed in Table B.2 (Appendix B.2). For probe concentrations of 50 nM, the limit of detection was one equivalent of target. This limit of detection would decrease with the use of lower probe concentrations (down to ≤ 10 nM of probe 5 was possible on our instrument). For different preparations of 5, made from the same stocks of 4 and blocked oligonucleotide probes, the calibration data for one preparation was applicable to another preparation with Δl, Δm, and Δn within ± 0.5 for 92% of the values for 13 random [l, m, n] combinations. For retaining the same calibration with a batch of 5 made from different stock materials, Δl, Δm, and Δn were within ± 0.5 for only 49% of the values for 13 random [l, m, n] combinations, but this improved to 95% for Δl, Δm, and Δn within ± 1.5. Overall, these results further demonstrated the capacity for quantitative triply multiplexed sensing with the dendrimer-based cFRET probes. 94 3.2.3 Buffer and serum measurements The DNA displacement assay was also tested in HEPES buffer (25 mM with 400 mM NaCl, pH 7.4), which is a more common buffer for biological samples than borate buffer, to show its compatibility with different experimental conditions. Figure 3.4 shows that the PL ratios measured for (5, 5, 5) configurations of dendrimer 5 with different [l, m, n] amounts of target had a good correlation between borate buffer and HEPES buffer. This result indicates that the probe will function in HEPES. Phosphate buffered saline (PBS) was not tested because of the potential for precipitation or complexation reactions with the terbium(III) ion, albeit that the cryptate structure might provide protection against such reactions. Figure 3.4 Correlation between the PL ratios measured in borate buffer and in HEPES buffer for five different [l, m, n] amounts of [Tgt1, Tgt2, Tgt3]. To show the benefit of time-gated measurements, the cFRET probes were dispersed in borate buffer and 50% v/v serum. Figure 3.5A shows the prompt (0 µs time delay) and time-gated (60 µs time delay) PL emission spectra. The prompt PL emission spectrum shows high 95 autofluorescence from serum, which was not observed in the time-gated spectrum. The displacement assay was also tested in 50% serum. The [0, 0, 0], [5, 0, 0], [0, 5, 0], [0, 0, 5], and [5, 5, 5] permutations of target equivalents were mixed with (5, 5, 5) cFRET probes in 50% serum and the time-gated PL spectra were measured (Figure 3.5B). The PL ratios measured in serum correlated well with analogous measurements in buffer. These results show that the probes are able to detect oligonucleotide targets without significant interference from the autofluorescence or complex sample matrix of serum. Figure 3.5 Detection in 50% v/v serum using the (5, 5, 5) cFRET probe. (A) Prompt and time-gated emission spectra for the (5, 5, 5) configuration in 50% serum. The prompt spectrum from serum alone is shown for reference. The autofluorescence background from serum is absent in the time-gated spectrum. (B) Correlation between the PL ratios measured in borate buffer and in 50% serum for five different [l, m, n] amounts of [Tgt1, Tgt2, Tgt3]. To assess for possible aggregation of the cFRET probe in serum, PL emission from the (5, 5, 5) configuration for dendrimer 5 was monitored at regular intervals over 3 h and then measured again at 24 h. Probe in borate buffer was also measured in parallel. There were no differences between 96 the data from buffer and from serum that suggested aggregation in the latter. Most importantly, the dye/Tb PL ratios in serum were approximately constant over 3 h and still unchanged after 24 h (Figure 3.6). The Tb PL lifetime also did not change over the 3 h period. Changes in FRET, and thus changes in dye/Tb PL ratios and Tb PL lifetime, would be expected upon aggregation. The absence of changes in these quantities suggested good stability in serum over a timescale relevant to measurements. Figure 3.6 Assessment of probe stability in 50% v/v serum. (A) Dye/Tb PL ratios as function of time after diluting with serum. (B) PL spectra at selected time points after diluting with serum. The 24 h-data is shown in the inset. (C) Tb PL lifetime as a function of time after diluting with serum. For panel C, the Tb was excited at 340 nm (13 nm bandwidth) and the emission was measured at 490 nm (3 nm bandwidth). 3.2.4 DNA displacement assay and smartphone-based time-gated imaging platform To this point, the time-gated measurements were acquired via a plate reader. To demonstrate the potential applications of the dendrimer-based time-gated probe for point-of-care diagnostics, its utility was tested with a portable and easy-access STGIP. The STGIP device was developed by a colleague in the research group (Sahil S. Kanani). Its basic operating principles are described so that the reader fully understands its application with the dendrimer-based time-gated FRET probes. 97 Figure 3.7A shows the design and the construction of the smartphone-based time-gated imaging platform. The choppers and housing were 3D printed. The light source was LED (340 nm peak wavelength), and the chopper was rotated by a micro-gear motor (rated for a maximum speed of 6500 rpm). The LED and motor were connected to the same circuit board within the housing, and both were powered by a 5000 mAh portable power bank via a USB connection. A sample holder was designed to fit the dimensions of a standard microscope slide (25 mm × 75 mm) and slid between the excitation and emission choppers, positioning the sample on the optical axis between the LED and camera. The sample holder was generally a 3 × 3 array of wells, each holding 15 µL of solution. A lens for magnifying the image was positioned on the optical axis, above an emission filter. Although the chopper design blocked excitation light from reaching the camera (i.e. time-gating feature; vide infra), an emission filter was still used as a precaution against stray reflections of excitation light. Figure 3.7B−C shows a double-chopper system was designed to create the pulsed excitation, delay, and integration time required for time-gated imaging. Each chopper had a circular sector design with blades (closed sectors that block light) and gaps (open sectors that transmit light). The two choppers were attached to a common axle and mounted onto the shaft of a micro-gear motor. Samples were inserted in the gap between the choppers. The excitation chopper converted continuous output from a light source into a series of pulses. The emission chopper defined the integration time (i.e. period during which sample emission was transmitted to a camera). The two choppers were aligned out-of-phase, with the blades of one chopper aligned with the gaps of the other, and the blades of the emission chopper slightly wider than the gaps of the excitation chopper. This alignment created the time gate between each excitation pulse and each integration time and 98 ensured that the camera never had a direct line of sight to the light source. The time-gating cycle was repeated many times per camera image. Table 3.4 summarizes the design parameters for timing values suitable for imaging of dendrimer-based time-gated probes (Section 3.5.9). Figure 3.7 STGIP design. (A) Scale renderings of the 3D-printed housing and STGIP components. (B) Illustration of the double-chopper with important design features labelled and highlighted. (C) Model of PL intensity as a function of time as the double-chopper rotates. Only two cycles (corresponding to two gaps and two blades) are shown. The open and closed circles represent gaps and blades, respectively, aligned with the optical axis between the LED and smartphone camera. The tx, td, and tm represent the duration of excitation, delay, and measurement (integration time for imaging), respectively. See Table 3.4 for detail explanation of parameters. The scale bar in panels A and B are 2 cm. STGIP device and illustrations contributed by Sahil S. Kanani. 99 The STGIP was used to measure the PL response of a dendrimer-based, time-gated FRET probe. Instead of using three dyes (e.g. A488, A546, and Cy5) for triply multiplexed sensing, only Tex615 dye was used in probe, thus making a FRET system rather than a cFRET system. The TEx615 dye was selected over the previous dyes because it better aligned with red (R) channel of the red-green-blue (RGB) colour channels of the smartphone camera. This better spectral alignment reduced (but did not eliminate) crosstalk between PL signals from the Tb and dye when using an RGB image analysis and thus facilitated continued use of ratiometric detection. Figure 3.8A shows the normalized absorption and the emission spectra of the Tb and Tex615. As illustrated in Figure 3.8B, biotinylated Prb2 and Blk2-Tex615 were pre-hybridized, leaving a 5 base-pair toehold at the distal terminus, then bound to NAv-coated dendrimer 4 to form the cFRET probe. The sequences of oligonucleotides are listed in Table 3.1. Five equivalents of Tex615-labelled duplexes were added to yield an (0, 5, 0) configuration suitable for the detection of Tgt2. Tgt2 was designed for displacing Blk2-Tex615, effectively changing the number of equivalents of Tex615 (value of M) per dendrimer. Displacement was not expected to take place with the non-complimentary target sequences (e.g. Tgt1 and Tgt3). 100 Figure 3.8 Toehold-mediated strand displacement assays with the (0, 5, 0) cFRET probe. (A) Normalized absorption spectra (dashed lines) and emission spectra (solid lines) for the Tb and Tex615. (B) Complementary target DNA oligonucleotides (Tgt2) are designed for displacing the Tex615-labelled oligonucleotides (Blk2-Tex615) from the dendrimer-based probe with loss of FRET. Not to scale. (C) Comparison of the time-gated PL ratios, measured on a plate reader and the STGIP, for the cFRET probe. The samples are (0, 5, 0) probe only, the probe with 1 equivalent of Tgt2, and the probe with 3 equivalents of Tgt1. Time-gated images of the samples from the STGIP are also shown. (D) The PL ratios of the probe with different equivalents of Tgt2, measured on both a plate reader and the STGIP (images also shown). The scale bar in panels C and D are 1.5 mm. Measurement data contributed by Sahil S. Kanani. I prepared dendrimer 4 for these experiments. On the STGIP, the Tb PL emission was most intense in the green channel (ca. 460−620 with peak at ~520 nm) of images, and the Tex615 PL emission was only detected in the red channel (ca. 101 570−650 nm with peak at ~620 nm). There was also some Tb PL detected in the red channel. A crosstalk correction factor, based on the know emission peak ratios for the Tb, was applied for calculating Tex615/Tb PL ratios from the R and G channel intensities in images. When the (0, 5, 0) probes were mixed with non-complementary Tgt1 (3 equiv.), the PL ratio of the sample was nearly identical to the sample of the (0, 5, 0) probe, indicating no displacement of the Blk2-Tex615 strand (Figure 3.8C). In contrast, a decreasing PL ratio was observed as increasing equivalents of complementary Tgt2 were added. When the Tgt2 was in excess (i.e. more than 1 equiv. was added per oligonucleotide probe), the PL ratio remained constant. Figure 3.8D shows that qualitatively similar trends of PL ratios were obtained with added Tgt2 on both a plate reader and the STGIP. The quantitative values of PL ratios are different because the ratios are calculated from different metrics (RGB channel intensities versus specific wavelengths), and because the plate reader and smartphone camera have different spectral sensitivities. Each readout instrument thus requires its own calibration data set for quantitative analysis. These cumulative results of this section demonstrate that the dendrimer-based time-gated FRET probe is a useful material for designing STGIP-based point-of-care diagnostics. 3.2.5 Enzyme kinetics To demonstrate the potential future application of a dendrimer-based cFRET probe for detecting protease activity, dendrimer 4 was bound with ~12 equiv. of biotinylated peptide (Figure 3.9A). The peptide was a trypsin substrate (i.e. contained an arginine residue) and was labelled with Alexa Fluor 555 (A555) dye at its distal end, which is a good acceptor for the Tb donor. The probe was used for detecting the activity of trypsin, which cleaves the A555-labelled peptide substrate from 102 the dendrimer with the loss of FRET. Figure 3.9B shows progress curves after mixing, where the A555/Tb time-gated PL intensity ratio was calculated from measurements at wavelengths of 568 nm and 490 nm. As expected, the PL ratio decreased over time because of the trypsin-catalyzed hydrolysis of the peptide and the resulting separation of the Tb-A555 FRET pair. Although there was only one dye in this configuration, this simple experiment suggests the possibility of using a dendrimer-based cFRET probe for detecting protease activity. Figure 3.9 Peptide-conjugated dendrimer-based FRET probe. (A) Trypsin cleaves the A555-labelled peptide substrate from the dendrimer with the loss of FRET. Not to scale. (B) Progress curve for a dendrimer-based probe with 12 equivalents of bound biotinylated-peptide-A555 and various concentrations of trypsin. 3.3 Discussion As mentioned in Chapter 2, previous cFRET probes have been exclusively based on QDs, with the QD serving as both a scaffold and an initial donor. The new time-gated, dendrimer-based cFRET probe configuration, as designed and characterized in Chapter 2, has now been seen in this chapter to be capable of multiplexed sensing using methods analogous to those of prior QD-based cFRET probes. 103 Like the dye/QD PL ratios for prior QD-based cFRET probes, each unique (L, M, N) combination for the Tb-dendrimer cFRET probe had a unique combination of dye/Tb PL ratios, permitting multiplexed sensing as a single vector. For the mathematical fitting of the dye/Tb PL ratios, different initial parameter values led to different coefficients in the empirical model; however, the calculated l, m, and n obtained from solving the equations were nearly the same. This result suggested that there were multiple viable but functionally equivalent empirical solutions when fitting the PL ratio space. Although this chapter only demonstrated triply multiplexed DNA sensing, similar triply multiplexed sensing of, for example, proteases activity should also be possible. The results of this chapter showed that protease detection is possible; the next step would be to substitute the biotinylated A555-labelled peptide with three different biotinylated peptide sequences, each labelled with one of A488, A546, and Cy5. Besides peptides, other possible biorecognition agents for sensing with this new cFRET configuration include biotinylated aptamers,86,109–112 small antibody derivatives,113–117 and affinity proteins,118,119 among others. As an initial donor, the Tb is not as bright as a QD. The multiple copies of Tb complexes per dendrimer help to reduce this shortcoming: for 8.1 copies per dendrimer, the per-probe absorption coefficient is ~218 000 M–1 cm–1. This value compares to ~116 000, ~568 000, and ~2 600 000 M–1 cm–1 for CdSe/CdS/ZnS QD520, CdSeS/ZnS QD525, and CdSe/CdS/ZnS QD605 at their cFRET-optimal excitation wavelength.50,52,120 Any limitation with brightness is from a detection standpoint, as the Tb still serves as an exclusive initial donor because its long-lifetime and time-gated measurement capability eliminated any effects from direct excitation of dyes. Time-gated measurement capability also enables rejection of short-lived background fluorescence or excitation 104 scattering, potentially improving signal-to-background to a degree that should, in many situations, offset the still superior brightness of QDs. Further to this point, we compared the detection limits for dendrimer 4, CdSe/CdS/ZnS QD520, and CdSe/CdS/ZnS QD605 in 50% v/v serum. The QDs were excited at their cFRET-optimum wavelengths and the prompt emission measured.50,52,86,87,120 Dendrimer 4 was excited at its optimum wavelength and the time-gated emission was measured. The detection limits were ~0.05 nM for QD605, ~0.2 nM for dendrimer 4, and ~5 nM for QD520 (see Appendix B.3 for detail). Although the Tb was not able to outperform the higher brightness and longer-wavelength emission of the QD605, the time-gated emission from the Tb was able to significantly outperform the prompt emission from the spectrally similar QD520. Similar to its QD-based predecessors, any limitations with respect to photobleaching arise from the dye acceptors, rather than from the more bleaching-resistant Tb. Although significant photobleaching of the dyes was not observed in this study (see Appendix B.4 for detail), it might be observed in future imaging applications where excitation is more intense. Another potential drawback of the Tb is that it requires shorter wavelength excitation (330–360 nm) than the QDs (400–460 nm); however, a further advantage is that the multiple narrow emission peaks of the Tb make it a viable donor for a wide range of colours of acceptor while minimizing emission crosstalk with those acceptors.121 Indeed, since the first demonstration of energy transfer from a luminescent terbium(III) complex to a dye,122 the narrow emission lines and long lifetimes have been leveraged for more conventional FRET-based assays with spectral multiplexing, temporal multiplexing, and a combination of spectral and temporal multiplexing.123–125 These advantages also make the dendrimer-Tb combination a more attractive replacement for a semiconductor QD than a carbon dot or graphene quantum dot, which have spectrally broad 105 emission, nanosecond-scale lifetimes, and surface chemistry and origins of PL that are sometimes poorly defined.10 Although far from practice at this point, time-gated imaging capability and the absence of a QD may enable future application of cFRET beyond in vitro sensing; for example, in vivo sensing applications that do not require deep penetration of light into tissue (e.g. skin, open wounds, colon or other endoscopic measurements). Short-term studies (over several days) show an encouraging absence of toxicity for the Tb in an animal model.126 Clinical approval for (hypothetical) in vivo applications may be more likely with a cFRET probe that does not include a semiconductor QD. 3.4 Conclusion Tb-dendrimer-based cFRET probes are capable of single-vector multiplexed detection using dye/Tb PL ratios as analytical signals. As a specific example, toehold-mediated strand displacement of the dye-labelled complements enabled quantitative detection of three target DNA sequences. Moreover, the long-lifetime of the Tb enabled time-gated measurements for rejection of background autofluorescence from serum, there is potential for application of the probe in point-of-care diagnostics. More generally, this work has shown that QDs are not the only viable material for assembling cFRET probes and that a combination of a molecular luminophore and non-luminescent nanomaterial can fulfill the initial donor and scaffold roles. These findings open doors to a wide array of materials for developing cFRET probes, and to applications where the benefits of cFRET are advantageous but the properties or risks of QDs are not. 106 3.5 Experimental methods 3.5.1 Materials The materials used in this chapter are largely the same as those listed in Chapter 2. Only the key materials and any additional materials that were first mentioned in this chapter are listed below. Bovine serum (B9433) and trypsin (T1426) were from Sigma-Aldrich (Oakville, ON, Canada). Oligonucleotides were from Integrated DNA Technologies (Coralville, IA, USA). Peptides were from BioSynthesis Inc. (Lewisville, TX, USA). Alexa Fluor 555 C2 Maleimide were from Life Technologies (Carlsbad, CA, USA). Borate buffer and HEPES buffer were prepared and sterilized by filtration (0.22 µm pore-size filter). Components of the STGIP were designed and 3D-rendered using Autodesk AutoCAD 2021 software (AutoDesk, San Rafael, CA, USA). All 3D-printed components were printed using black, 1.75 mm-diameter polylactic acid filament on an Ender-3 Pro 3D Printer (Creality 3D Technology Co., Shenzhen, China). The two 3D-printed choppers were attached to the shaft of a 6500 rpm, 6 V brushed DC motor with a 4.995:1 metal gearbox (#3082, Pololu Robotics and Electronics, Las Vegas, NV, USA). A quadrature encoder (12 counts per revolution of the motor shaft, when counting both edges from both output channels; #4761; Pololu Robotics and Electronics, Las Vegas, NV, USA) was attached to the back shaft to monitor the speed of rotation. The encoder was connected across a 3.5 V potential difference from an external power supply. A threaded spigot attachment was used as a sleeve over the motor shaft to hold the two choppers in place. A 3D-printed block spacer vertically separated the choppers. The LED (340 nm peak wavelength) was from Marktech Optoelectronics (#MTSM340UV-F5120; 55mW; Latham, NY, USA). The 107 smartphone was a Samsung Galaxy S7 (#SM-G930W8; Samsung Electronics, Suwong, South Korea). The power bank was from Miniso (#JP-85; Guangzhou, Guangdong, China) and had a cell capacity of 5000 mAh and an output direct current voltage and max current of 5 V and 2 A respectively. Table 3.1 Oligonucleotide sequences and symbols for the number of equivalents per dendrimer. Name Sequenced,e Number of Equiv. Prb1a 3’-GGATA CATGGCGAAGTGAC -5’-Biotin L Blk1-A488b 5’-GTACCGCTTCACTG T-3’-A488 L Tgt1c 5’-CCTAT GTACCGCTTCACTG -3’ l Prb2 3’-AAAGG GCAGAGAGTGTGTCG -5’-Biotin M Blk2-A546 5’-CGTCTCTCACACAGC -3’-A546 M Tgt2 5’-TTTCC CGTCTCTCACACAGC -3’ m Prb3 3’-TAGGT GTGCCGGTTCTCTA -5’-Biotin N Blk3-Cy5 5’-CACGGCCAAGAGAT -3’-Cy5 N Tgt3 5’-ATCCA CACGGCCAAGAGAT -3’ n Blk2-Tex615 5’-CGTCTCTCACACAGC -3’-Tex615 M a Prb: probe-strand oligonucleotide. b Blk: block-strand oligonucleotide. c Tgt: target-strand oligonucleotide. d The underlined portions are the toehold used by the target sequence to displace the block oligonucleotide from the probe oligonucleotide. e The calculated melting temperatures of hybridized oligonucleotides (probe and target strands) 1, 2, and 3 are 63.8, 68.5, and 67.9 ºC, respectively, under the experimental condition (250 nM probe strand, 250 nM target strand, 400 mM NaCl). 108 3.5.2 Displacement assays Target oligonucleotides (180−210 nmol) were dissolved in nuclease-free water to a final concentration of 320−360 µM, then stored at –20 ○C until needed. For displacement assays, the mixtures of DNA targets and DNA-conjugated dendrimers were prepared separately. Individual target DNA solutions were diluted with borate buffer (50 mM with 400 mM NaCl, pH 8.6) to final concentrations of 4 µM. Next, 4.0 pmol × l of Tgt 1, 4.0 pmol × m of Tgt 2, and 4.0 pmol × n of Tgt 3 were mixed and diluted with borate buffer (50 mM with 400 mM NaCl, pH 8.6) to a final volume of 20 µL. All combinations of l, m, and n values of 0, 2.5, and 5 were prepared, amounting to 27 samples. DNA-conjugated dendrimers (5) were prepared using the same method described in Chapter 2, excepting that only the (L, M, N) = (5, 5, 5) configuration was used for displacement assay experiments. The final concentration of the probe was 0.067 µM in borate buffer (50 mM with 400 mM NaCl, pH 8.6). Mixtures of target (11 µL) were mixed with 33 µL of 0.067 µM of dendrimer 5. The final concentration of the dendrimer was 0.05 µM in borate buffer (50 mM with 400 mM NaCl, pH 8.6). The solutions were mixed thoroughly, then protected from light and left to stand for 2 h at room temperature. Aliquots (40 µL) of the samples were transferred into a 384-well black plate for PL measurements. For the experiments in 50% serum, the individual target DNA solutions were diluted with borate buffer (50 mM with 400 mM NaCl, pH 8.6) to final concentrations of 5.0 µM. Second, 12.5 pmol of Tgt 1, Tgt 2, and Tgt 3 were diluted with either borate buffer (50 mM with 400 mM NaCl, pH 8.6) or borate buffer with 67% serum, both to a final volume of 37.5 µL. The (5, 5, 5) probe was prepared and dispersed (0.2 µM dendrimer 5) in borate buffer (50 mM with 400 mM NaCl, pH 109 8.6). The target DNA solutions (37.5 µL) were mixed with the (5, 5, 5) probe (12.5 µL). The final concentration of the dendrimer was 0.05 µM in either borate buffer or borate buffer with 50% v/v serum. The solutions were mixed thoroughly, protected from light, and left to stand for 2 h at room temperature. Aliquots (40 µL) of the samples were transferred into a 384-well black plate for PL measurements. For the DNA displacement assay with the STGIP, DNA-conjugated dendrimers (5) were prepared using the same method described earlier, excepting that only the (L, M, N) = (0, 5, 0) configuration was used. It is worth noting that the acceptor was Tex615 (instead of A546). Diluted Tgt1or Tgt2 (0−3 equivalents) were mixed with the (0, 5, 0) probes. The final concentration of the dendrimer was 0.05 µM in borate buffer (50 mM with 400 mM NaCl, pH 8.6). The solutions were mixed thoroughly, then protected from light and left to stand for 2 h at room temperature. Aliquots (15 µL) of the samples were transferred into sample wells for STGIP imaging measurements, and aliquots (40 µL) of the samples were transferred into a 384-well black plate for PL measurements on a plate reader. 3.5.3 Buffer and serum experiments Buffer compatibility The procedures are adapted from Chapter 2 with minor modifications. Briefly, the DNA displacement assays in borate (50 mM with 400 mM NaCl, pH 8.6) and HEPES buffer (25 mM with 400 mM NaCl, pH 7.4) were prepared in several steps. First, the pre-hybridized DNA solutions were prepared in water (with 400 mM NaCl) to final concentration of 10 µM. Second, 105 pmol × 5 of pre-hybridized Biotin-DNA-A488, 105 pmol × 5 of pre-hybridized Biotin-DNA-110 A546, and 105 pmol × 5 of pre-hybridized were mixed with dendrimer 4 for 2 h to form (5, 5, 5) probes, where the final concentration of the probe was 0.3 μM in water (with 400 mM NaCl). Third, the probes were further diluted with borate buffer or HEPES buffer to the final concentration of 0.1 μM. Next, 4.4 pmol × l of Tgt 1, 4.4 pmol × m of Tgt 2, and 4.4 pmol × n of Tgt 3 were mixed and diluted with borate buffer (with 400 mM NaCl) or HEPES buffer (with 400 mM NaCl) to final volume of 44 μL. All possible combinations of l, m, and n values of 0 or 5 were prepared. Then, 4.4 pmol (44 μL) of the (5, 5, 5) probes were mixed with the target mixtures, where the final concentration of the probes was 0.05 μM in borate buffer (50 mM with 400 mM NaCl, pH 8.6) or HEPES buffer (25 mM with 400 mM NaCl, pH 7.4). The samples were mixed thoroughly, then protected from light and left to stand for 2 h at room temperature. An aliquot (40 μL) from each sample was transferred into a well of a 384-well black plate for PL measurements. Stability of dendrimer 5 in 50% serum The procedure for preparing (5, 5, 5) probe was the same as described above. Briefly, the (5, 5, 5) cFRET probes were prepared and diluted in borate buffer (50 mM with 400 mM NaCl, pH 8.6) to the final concentration of 0.1 μM. Then, 4.5 pmol (45 μL) of (5, 5, 5) probe was diluted with 45 μL of borate buffer or Serum the final concentration of 0.5 μM. The samples were mixed thoroughly. An aliquot (40 μL) of the samples were transferred into a well of a 384-well black plate for PL measurements. For PL lifetime time measurements, 6.0 pmol (60 μL) of (5, 5, 5) probe was diluted with 60 μL of Serum. An aliquot (100 μL) of each sample was transferred into a well of a 384-well black plate for PL measurements. 111 3.5.4 Enzyme kinetics Peptide-conjugated dendrimer probes were prepared by simply mixing dendrimer 4 and ~12 equivalent of biotinylated peptide in borate buffer (50 mM, pH 8.5) at room temperature. The peptide was a trypsin substrate (Biotin-GGPPPPPGLVPRGSGC-A555) and was labelled with an A555 dye at its distal end (C-terminus). Next, 0, 25, 50, and 100 nM of trypsin solutions were prepared. An aliquot (35 µL) of the probe was directly mixed with trypsin solutions (35 µL) in the wells of a 96-well half-area plate. The final concentration of the dendrimer-based probe was ~0.04 µM, and the final concentrations of trypsin were 0, 13, 25, and 50 nM. The PL measurement of the mixtures were collected every one minute for 1.5 h. 3.5.5 Absorption and emission measurements The absorption and PL excitation and emission spectra were measured using an Infinite M1000 Pro plate reader (Tecan Ltd., Morrisville, NC, USA) equipped with a xenon flash lamp, excitation and emission monochromators, and a photomultiplier tube detector. For absorption measurements, sample volumes of 80 or 170 µL were aliquoted into a clear-bottom half-area 96-well plates (#675801; Greiner, Monroe, NC) having a 0.5 or 1.0 cm pathlength for absorption measurements. For PL emission measurements, sample volumes of 40 µL at 0.05 µM concentration were dispensed into a 384-well black plate (#3575; Corning, Corning, NY) and excited at 340 nm (excitation bandwidth was varied between 20 nm; emission bandwidth was 5 nm). Prompt measurements corresponded to acquisition of an emission signal with a 0 µs delay after a flash of 112 excitation light. Time-gated measurements corresponded to acquisition of an emission signal with a 60 µs delay after a flash of excitation light. The integration time was 2000 µs for prompt and time-gated emission measurements. 3.5.6 Lifetime measurements The time-resolved PL measurements for the Tb (Figure 3.6C) were made using an FLS1000 photoluminescence spectrometer (Edinburgh Instruments Ltd., Livingston, United Kingdom) equipped with a xenon microsecond flash lamp. Samples (100 µL) were dispersed in 50% serum to a final concentration of 0.05 μM and transferred to a sub-micro quartz cuvette (#16.100F-Q-10/Z15; Starna Cells, Inc., Atascadero, CA). The samples were excited at 340 nm (10 nm bandwidth). The source trigger delay was 0.500 ms, the time range was 20 ms, and the delay time was 0.700 ms. A longpass filter (400 nm cut-off) was insert into the optical axis for collection emission. Emission was measured at 490 nm (2 nm monochromator bandwidth). This emission wavelength and bandwidth minimized collection of any dye emission during the measurements. The lifetime decay curves were fit with an exponential decay function, and the amplitude-weighted average lifetimes (biexponential function) were reported. 3.5.7 ET calculation of PL ratios PL ratios were calculated according to Eqns. 3.1–3.7, where 𝐼𝜆 is the PL intensity measured from an emission spectrum at wavelength λ nm. 𝐼𝑋 is the PL intensity of each emitter, where X is Tb, A488, A546, or Cy5. The emitters are the primary contributors to emission measured at 490, 518, 572, and 664 nm, respectively. Crosstalk coefficients, which account for minor contributions from other emitters at these wavelengths, were defined from PL emission spectra. They are formulated 113 as percentage of the peak emission intensity for an emitter and denoted as 𝜎𝑋−𝜆, indicating the contribution of emitter X at λ nm. Specific correction coefficients were 𝜎𝐴488−490 = 0.063 , 𝜎𝐴488−572 = 0.167, and 𝜎𝐴546−664 = 0.042. Other potential crosstalk coefficients were negligible. 𝐼𝑇𝑏 = 𝐼490 − 𝜎𝐴488−490𝐼𝐴488 (3.1) 𝐼𝐴488 = 𝐼518 (3.2) 𝐼𝐴546 = 𝐼572 − 𝜎𝐴488−572𝐼𝐴488 (3.3) 𝐼𝐶𝑦5 = 𝐼664 − 𝜎𝐴546−664𝐼𝐴546 (3.4) 𝜌𝐴488 𝑇𝑏⁄ = 𝐼𝐴488 𝐼𝑇𝑏⁄ (3.5) 𝜌𝐴546 𝑇𝑏⁄ = 𝐼𝐴546 𝐼𝑇𝑏⁄ (3.6) 𝜌𝐶𝑦5 𝑇𝑏⁄ = 𝐼𝐶𝑦5 𝐼𝑇𝑏⁄ (3.7) Note: In the progress curves for the displacement assays (Figure 3.3B), the PL intensities of Tb, A488, A546, and Cy5 were measured at 488, 518, 572, and 662 nm, respectively. The specific crosstalk correction coefficients were 𝜎𝐴488−488 = 0.045, 𝜎𝐴488−572 = 0.167, and 𝜎𝐴546−662 =0.045. The 𝜎𝐴488−488 and 𝜎𝐴546−662 were substituted for 𝜎𝐴488−490 and 𝜎𝐴546−664 in Eqns. 3.1 and 3.4, and the PL ratios were calculated using Eqns. 3.5−3.7. 3.5.8 Mathematical fitting of PL ratios versus (L, M, N) The A488/Tb PL ratio, denoted as 𝜌A488/Tb, was a function of L, M, and N (Eqn. A1), where L, M, and N were the average number of A488, A546, and Cy5 per dendrimer 5, respectively. 𝜌𝐴488/𝑇𝑏 = 𝑓[𝐿,𝑀,𝑁] (3.8) 114 The A488/Tb PL ratio had a linear trend with L, but the slope and intercept for this line varied with M and N. To derive an equation of fit, the A488/Tb PL ratios were plotted as a function of L for all values of M and N and fit with Eqn. 3.9, where 𝑙1 was a local variable that was a function of M and N, and 𝑙2 and 𝑙3 were global variables. 𝜌𝐴488/𝑇𝑏 = 𝑙1[𝑀, 𝑁](𝑙2𝐿 + 𝑙3) (3.9) The value of 𝑙1 was then plotted as function of M with different values of N, then fit with Eqn. 3.10 with 𝑙4 and 𝑙5 as local variables. In turn, the values of 𝑙4 and 𝑙5 were plotted as a linear function of N, according to Eqn. 3.11 and Eqn. 3.12. 𝑙1[𝑀,𝑁] = 𝑙4[𝑁]𝑀 + 𝑙5[𝑁] (3.10) 𝑙4[𝑁] = 𝑙6𝑁 + 𝑙7 (3.11) 𝑙5[𝑁] = 𝑙8𝑁 + 𝑙9 (3.12) The full equation for 𝜌𝐴488/𝑇𝑏 was Eqn. 3.13 and obtained by substitution of Eqns. 3.10–3.12 into Eqn. 3.9. The fitted values for the 𝑙𝑥 parameters are listed in Table 3.2. The initial guess (when fitting) for all the 𝑙𝑥 was 0.05. 𝜌𝐴488/𝑇𝑏 = 𝑓[𝐿,𝑀, 𝑁] = [(𝑙6𝑁 + 𝑙7)𝑀 + (𝑙8𝑁 + 𝑙9)](𝑙2𝐿 + 𝑙3) (3.13) The general procedure described above was repeated with the A546/Tb PL ratio, 𝜌A546/Tb, which was also a function of L, M, and N (Eqn. 3.14). Stepwise fitting (Eqns. 3.15–3.18) yielded the final equation for 𝜌𝐴546/𝑇𝑏 (Eqn. 3.19). The fitted values for the 𝑚𝑥 parameters are listed in Table 3.2. The initial guess (when fitting) for all the 𝑚𝑥 was 0.05. 115 𝜌𝐴546/𝑇𝑏 = 𝑔[𝐿,𝑀,𝑁] (3.14) 𝜌𝐴546/𝑇𝑏 = 𝑚1[𝐿, 𝑁](𝑚2𝑀 + 𝑚3) (3.15) 𝑚1[𝐿, 𝑁] = 𝑚4[𝐿]𝑁 + 𝑚5[𝐿] (3.16) 𝑚4[𝐿] = 𝑚6𝐿 + 𝑚7 (3.17) 𝑚5[𝐿] = 𝑚8𝐿 + 𝑚9 (3.18) 𝜌𝐴546/𝑇𝑏 = 𝑔[𝐿,𝑀, 𝑁] = [(𝑚6𝐿 + 𝑚7)𝑁 + (𝑚8𝐿 + 𝑚9)](𝑚2𝑀 + 𝑚3) (3.19) The fitting procedure was again repeated with the Cy5/Tb PL ratio, 𝜌Cy5/Tb, which was also a function of L, M, and N (Eqn. 3.20). Stepwise fitting (Eqns. 3.21–3.24) yielded the final equation for 𝜌𝐶𝑦5/𝑇𝑏 (Eqn. 3.25). The fitted values for the 𝑛𝑥 parameters are listed in Table 3.2. The initial guess (when fitting) for all the 𝑛𝑥 was 0.05. 𝜌𝐶𝑦5/𝑇𝑏 = ℎ[𝐿,𝑀,𝑁] (3.20) 𝜌𝐶𝑦5/𝑇𝑏 = 𝑛1[𝐿,𝑀](𝑛2𝑁 + 𝑛3) (3.21) 𝑛1[𝐿,𝑀] = 𝑛4[𝑀]𝐿 + 𝑛5[𝑀] (3.22) 𝑛4[𝑀] = 𝑛6𝑀 + 𝑛7 (3.23) 𝑛5[𝑀] = 𝑛8𝑀 + 𝑛9 (3.24) 𝜌𝐶𝑦5/𝑇𝑏 = ℎ[𝐿,𝑀,𝑁] = [(𝑛6𝑀 + 𝑛7)𝐿 + (𝑛8𝑀 + 𝑛9)](𝑛2𝑁 + 𝑛3) (3.25) The calibration data sets were mathematically fitted using MATLAB. 116 Eqns. 3.8−3.25 were also used for fitting in the displacement assay experiments, where the notation of L, M, and N in the equations indicated the average number of Tgt1, Tgt2, and Tgt3, respectively. The fitted values for the parameters 𝑙𝑥, 𝑚𝑥, and 𝑛𝑥 are listed in Table 3.3. The initial guess (when fitting) for all the 𝑙𝑥, 𝑚𝑥, and 𝑛𝑥 was 0.05. Note: Eqns. 3.8−3.25 and Table 3.3 are the only places where L, M, and N were used for representing the average number of Tgt1, Tgt2, and Tgt3 (instead of l, m, and n, as in the main text). Table 3.2 Fitting parameters for the calibration data set in Figure 3.2A (64 combinations). 𝜌𝐴488/𝑇𝑏 = 𝑓[𝐿,𝑀,𝑁] 𝜌𝐴546/𝑇𝑏 = 𝑔[𝐿,𝑀,𝑁] 𝜌𝐶𝑦5/𝑇𝑏 = ℎ[𝐿,𝑀,𝑁] Parameter Value Parameter Value Parameter Value 𝑙1[𝑀,𝑁] -- 𝑚1[𝐿, 𝑁] -- 𝑛1[𝐿,𝑀] -- 𝑙2 0.045 𝑚2 0.064 𝑛2 0.069 𝑙3 0.0073 𝑚3 0.0045 𝑛3 0.0066 𝑙4[𝑁] -- 𝑚4[𝐿] -- 𝑛4[𝑀] -- 𝑙5[𝑁] -- 𝑚5[𝐿] -- 𝑛5[𝑀] -- 𝑙6 –0.0028 𝑚6 –0.014 𝑛6 –5.5E–05 𝑙7 –0.086 𝑚7 –0.14 𝑛7 0.046 𝑙8 –0.032 𝑚8 0.14 𝑛8 0.20 𝑙9 1.8 𝑚9 3.0 𝑛9 1.6 117 Table 3.3 Fitting parameters for the calibration data set in Figure 3.3C (27 combinations). 𝜌𝐴488/𝑇𝑏 = 𝑓[𝐿,𝑀,𝑁] 𝜌𝐴546/𝑇𝑏 = 𝑔[𝐿,𝑀,𝑁] 𝜌𝐶𝑦5/𝑇𝑏 = ℎ[𝐿,𝑀,𝑁] Parameter Value Parameter Value Parameter Value 𝑙1[𝑀,𝑁] -- 𝑚1[𝐿, 𝑁] -- 𝑛1[𝐿,𝑀] -- 𝑙2 –0.057 𝑚2 –0.12 𝑛2 –0.13 𝑙3 0.42 𝑚3 0.75 𝑛3 0.70 𝑙4[𝑁] -- 𝑚4[𝐿] -- 𝑛4[𝑀] -- 𝑙5[𝑁] -- 𝑚5[𝐿] -- 𝑛5[𝑀] -- 𝑙6 0.00035 𝑚6 –0.0011 𝑛6 0.0078 𝑙7 0.051 𝑚7 0.15 𝑛7 –0.051 𝑙8 0.036 𝑚8 –0.023 𝑛8 –0.14 𝑙9 0.59 𝑚9 1.2 𝑛9 1.7 3.5.9 STGIP image measurements and analysis The double-chopper design and parameters are listed in Table 3.4. The samples were loading into a microwell chip that contained 9 microwells. The samples were excited with an LED (340 nm peak wavelength). All the PL images were acquired using a Samsung Galaxy S7 smartphone camera (#SM-G930W8; Samsung Electronics, South Korea). All images were acquired in RAW mode to prevent automatic processing and adjustment of imaging parameters. The white balance was set to 5000 K, the f-number was maintained at 1.7 and all images were acquired at a resolution of 3024 × 4032 pixels with an 8-bit depth. The exposure time and ISO were set to their maximum values (exposure time = 10 s, ISO = 800). 118 Table 3.4 Double-chopper design and timing parameters and typical values. The parameters and timings are illustrated in Figure 3.7. Chopper Parameter Typical Value Timing Parametera Typical Timingb Role(s) ω 2000 rpm (209 rad/s) tx, td, tm -- Global scaling of all timing parameters αx 10º (0.17 rad) tx 0.8 ms Sets relative duration of excitation pulse βx 35º (0.61 rad) td, tm -- Blocks excitation light from reaching sample αm 20º (0.35 rad) tx 1.6 ms Sets relative length of integration time βm 25º (0.44 rad) tx, td -- Blocks excitation light from reaching camera γ (β2 – α1) / 2 (minimum 7.5º) td 0.6 ms Sets relative length of delay time n 8 -- -- Number of cycles per revolution -- -- T 10 s Camera exposure time, number of cycles per image a Timing parameter values are aligned with the design parameter that is their main determinant. b Values for timing parameters are only listed once. PL intensities were measured by exporting the RAW image files into ImageJ software.127 The DCRAW Import function from the Multispectral Image Calibration and Analysis (mica) Toolbox plug-in was used to import DNG images from the smartphone. The red, green, and blue (RGB) colour channels were split into separate images and regions of interest (ROIs) were defined. Colour-specific PL intensities were recorded as the mean intensity value within a defined ROI. All intensities were measured on an 16-bit scale, with 0 representing the lowest measured intensity, 119 and 65 535 representing the highest measured intensity. The as-measured intensity values were then corrected with the following order: (i) blank correction and (ii) excitation correction. The blank correction is that the mean intensity of a blank solution was subtracted from all other measured intensity values. The excitation correction is a correction factor was applied to each well to account for the spatial heterogeneity in the LED illumination intensity. A well-based correction matrix was constructed by imaging the same standard solution of fluorescein in 8 wells of the microwell chip and a blank solution in the ninth well. All intensity values were blank-corrected and then normalized with respect to the particular well that had the least intensity variation across replicate measurements. For experimental samples, the mean intensity values from each well were divided by the respective normalization factor. 120 Chapter 4: Characterization of Photoluminescent Silicon Nanocrystals and Energy Transfer to Dyes Using Spectroelectrophoresis and Time-Resolved Spectroscopy This chapter includes unpublished work that is a manuscript in preparation. Prof. W. R. Algar proposed the concept. Prof. Jonathan G. C. Veinot, Christopher Jay Robidillo, Ziqi Li, Gunwant K. Matharu, Kevin O’Connor, I Teng Cheong, and Chuyi Ni provided silicon nanocrystals and TEM images. I designed and performed the experiments, analyzed the data, and wrote the text with input and final editing from Prof. W. R. Algar. 4.1 Introduction QDs are attractive luminescent nanomaterials for biological applications because of their advantageous physical properties and optical properties derived from quantum confinement.26,27,40 These properties potentially include size-dependent PL wavelengths, narrow and/or symmetric emission spectra, high brightness, resistance to photobleaching, small size, capacity for surface functionalization, and multivalent bioconjugation.26,27,40 Many of the best developed and widely utilized QD materials for bioanalysis and imaging have nominally toxic heavy metals (e.g. Cd, Pb) in their composition.128,129 Other metal-based QD compositions (e.g. In-based) have also been found to be potentially cytotoxic.130–133 Several strategies are available for mitigating the potential cytotoxicity associated with these materials, and studies have found greater tolerance of QDs by 121 animal models, including the absence of acute toxicity.88–90,134 Nevertheless, concerns persist for the use of metal-containing QDs for biological research and are a barrier to prospective clinical applications. SiNCs—which behave as QDs when prepared with high quality—are a possible alternative material. Silicon is more abundant than other QD materials and is generally accepted to be much more benign toward biological systems.29,135–138 Like other QD materials, the size-dependent PL of SiNCs arises from quantum confinement effects when the nanocrystal is smaller than its Bohr exciton radius (~4.5 nm for Si).10,29,139 SiNCs differ from most other semiconductor QD materials in that silicon has an indirect band gap rather than a direct band gap, such that electronic transitions in SiNCs are phonon-assisted.10,38,140 As a result, light absorption is weaker and the exciton recombination rate is slower when compared to direct-band-gap QDs. The reduced brightness is at least partially offset by the long PL lifetime of SiNCs, which enables time-gating for low/no-background measurements. Benchmarking against high-quality cadmium chalcogenide QDs, SiNC PL is spectrally broader (FWHM of 100−200 nm versus 20–40 nm),10,139,141 more prone to unwanted effects from defect states,139,142–145 more sensitive to surface chemistry,146 and generally more polydisperse.141,144 Given this mix of potential advantages and disadvantages, identifying the most strategic biological applications for SiNCs remains an important area of research.38,39,147–149 FRET is a popular and powerful method for bioanalysis and imaging. One of its many capabilities is sensitive and real-time detection of biomolecular targets, including in multiplexed formats. Direct band gap QD materials such as CdSe/ZnS core/shell QDs have been prolific in their utilization in FRET-based sensors.40 These materials offer numerous advantages as FRET donors 122 and, in select cases, as FRET acceptors.40 Single-vector multiplexed sensing in the form of cFRET was first enabled by the properties of QDs. In contrast, the suitability, strengths, and limitations of SiNCs as FRET donors is largely unexplored. There has only been one proof-of-concept studies on FRET-based sensing150 and few, if any, in-depth photophysical studies.151–153 Here, a detailed and multifaceted study of ET between aqueous SiNC donors and dye acceptors is reported. The PL of SiNCs is first characterized using spectroelectrophoresis and time-gated (TG) spectroscopy to resolve heterogeneity in the nanocrystal size. ET from the SiNCs to a series of dark quencher dyes with different degrees of spectral overlap is then evaluated. Insights into ET at the level of the ensemble of SiNCs and for different sub-populations were obtained by varying the parameters for TG and time-resolved (TR) spectroscopies. Comparisons between ET with spontaneously-partitioned hydrophobic quencher dyes and covalently-conjugated quencher dyes provided further insight into important considerations for ET, as did measurements with conjugated fluorescent dye as an acceptor. TG ET with rejection of autofluorescence background from serum was possible. Overall, this study is an important step toward developing and optimizing SiNC-based ET configurations, whether for bioanalysis and imaging or for other applications. 4.2 Results 4.2.1 Materials Hydride-terminated SiNCs were prepared from commercial hydrogen silsesquioxane and their surface was functionalized for aqueous dispersion by hydrosilylation, as described previously.38 Several batches of SiNC were used in this study. A shorthand notation is used to distinguish 123 different batches of SiNCs with different surface modifications: (i) a bold number specifies the surface chemistry of the SiNCs; (ii) a numeral in parentheses denotes the peak emission wavelength of SiNCs (in nm). Different surface modifications might cause small shift in the emission peak. The peak wavelengths noted are for SiNC 1 and this notation was retained even if the surface chemistry changed. The hydrosilylated SiNCs 1 were functionalized with a mixture of PEG moieties and carboxylate-terminated alkyl chains. The PEG moieties imparted colloidal stability whereas the surface carboxylate groups facilitated conjugation reactions (Figure 4.1A). Agarose gel electrophoresis (Figure 4.1B) confirmed that the SiNCs 1 had a net negative charge from the surface carboxylate groups. For some experiments, a fraction of the carboxylate groups were converted into hydrazide groups (SiNC 2) through carbodiimide coupling with adipic acid dihydrazide. This modification was confirmed by a decrease in electrophoretic mobility on an agarose gel (Figure 4.1B). The hydrazide groups were used for covalent conjugation of the SiNCs with succinimidyl esters of dyes (vide infra). Figure 4.1C shows the ensemble absorbance and PL excitation and emission spectra of the SiNC(676) 1, which was the most extensively used SiNCs in this study. The TEM images are included in Appendix C.1. 124 Figure 4.1 SiNCs. (A) Illustration (not to scale) of the SiNC and its surface chemistry, including the initial distal carboxyl(ate) groups (SiNC 1) and partial dihydrazide modification (SiNC 2). (B) PL images of agarose gels showing the electrophoretic mobility of SiNC(676) 1 and 2. The dashed line indicates the position of the sample wells and the polarity of the electric filed is marked. (C) Extinction (blue line) and PL excitation (dashed orange line) and emission (solid orange line) spectra (0 µs delay, 2 ms integration time) for the ensemble of SiNC(676) 1. 4.2.2 Characterization by spectroelectrophoresis SiNC(717) 1 were characterized using a previously described “stubby” format of poly(acrylamide)-based capillary gel electrophoresis (CGE) with real-time spectrofluorimetric detection (Figure 4.2A).154,155 PL electropherograms of SiNC(717) 1 were collected at multiple wavelengths between 530 and 780 nm. The migration time increased as the wavelength increased (Figure 4.2B). In turn, the emission spectrum gradually red-shifted by more than 100 nm as the migration time increased (Figure 4.2C−D). These data revealed non-trivial size polydispersity in the population of SiNC(717) 1, where larger SiNCs had longer emission wavelengths on average, consistent with expectations from quantum confinement. Similar results were observed with SiNC(605) 1 (Appendix C.2). 125 Figure 4.2 Capillary gel electrophoresis of SiNC(717) 1. (A) Simplified schematic of the experiment: a polyacrylamide gel (PAG)-filled capillary and electrophoresis setup were mounted on an inverted microscope, where the SiNCs were excited with UV light when passing above an objective lens and the PL emission were recorded via a fibre-coupled CCD spectrometer (not shown). The electropherograms include a peak for a fluorescein as an internal standard. (B) PL electropherograms measured at different emission wavelengths. PL emission measurements were made with continuous (not pulsed) excitation and an 800 ms detector integration time. (C) PL emission spectra as a function of migration time for the same experiment as panel B. The graph on the left shows the measured intensities whereas the graph on the right shows the normalized spectra. (D) Plot of the peak PL emission wavelength versus migration time. 4.2.3 TG spectral characterization TG PL emission measurements are made by detecting emission after a defined delay time following pulsed excitation of a sample. In contrast, conventional or “prompt” PL emission measurements are made with no temporal separation between excitation and detection of emission 126 (Figure 4.3A). TG measurements also utilized an integration time, which was the duration over which emission was detected following the delay. For experiments in this study, an integration time of either 2 ms or 20 µs was used. The integration time of 2 ms, which was generally used with a 0 µs delay time, was much longer than the ensemble PL lifetime of the SiNCs and thus sufficient to collect virtually all of the PL emitted. The integration time of 20 µs was the shortest possible on the instrument, acquired a relatively small fraction of the total PL emission, and was used with a variable delay time. Each delay period had different relative contributions from small and large SiNCs in the ensemble, with shorter delays more biased toward PL from smaller SiNCs (vice versa). The prompt PL emission spectrum (0 µs delay, 2 ms integration time) of SiNC(717) 1 was compared with TG PL emission spectra acquired with various delay and a fixed 20 µs integration time (Figure 4.3B). The prompt spectrum had a peak at 717 nm and a FWHM of 168 nm. In contrast, the TG spectrum (0 µs delay, 20 µs integration time) had a peak at 663 nm and a FWHM of 180 nm. These values gradually shifted to 760 nm and 117 nm, respectively, as the delay time was increased up to 300 µs (Figure 4.3B−C). Similar results were obtained with a variable delay and a fixed integration time of 2 ms, but shifted to longer peak PL emission wavelengths and narrower FWHMs. 127 Figure 4.3 TG PL measurements and emission spectra. (A) Illustration of the prompt (0 µs delay, 2 ms integration time) and TG (delay ≥ 5 µs) PL measurement concepts with pulsed excitation and different integration times. (B) Prompt PL emission spectrum for SiNC(717) 1 (2 ms integration time; black data) with overlaid TG PL emission spectra with a variable delay and 20 μs integration time (rainbow data). (C) Plot of peak PL emission wavelength (left axis) and FWHM (right axis) versus delay time for the spectra in panel B. (D) EEMs with 0, 10, 40 μs delay and 20 μs integration time. The white area indicates no signal was collected due to off-scale background from excitation light; the black and gray area indicates the values are below and above zero and maximum (6200 in this case), respectively. In contrast to the emission spectra, TG excitation spectra of SiNC(717) 1, acquired with variable delay and fixed integration times (20 µs or 2 ms), showed no obvious spectral shifts (Figure C.3C). This result was confirmed by measurement of TG excitation-emission matrices (EEMs), which revealed a temporal shift of the PL intensity along the emission axis without any shift along the excitation axis (Figure 4.3D and Appendix C.3). Similar overall results for the TG PL excitation 128 and emission spectra were obtained with SiNC(605) 1 (Appendix C.4). The results suggested that changing the excitation wavelength was an impractical means of selectively probing different sub-populations of the SiNCs. 4.2.4 TR spectral characterization SiNCs were further characterized by TR PL measurements, which also recorded PL intensity following an excitation pulse, but without the delay of TG measurements and with higher temporal resolution (2.0 µs versus 20 µs). These data provide an important baseline for TR measurements on ET (vide infra). Wavelength-resolved PL decays of SiNC(676) 1 (Figure 4.4A) and average PL decay profiles for the different wavelength windows (Figure 4.4B) clearly showed an increase in PL lifetime as the emission wavelength increased. The average lifetime across whole wavelength range (540−756 nm) was 53 μs, whereas the average lifetime changed from 34 μs for emission between 540−600 nm) to 82 µs for emission between 696−756 nm. All PL decays were poorly fit by monoexponential models. It is likely that at least some of this multiexponential character within each wavelength window arose from size polydispersity. 129 Figure 4.4 PL lifetime of SiNC(676) 1 via TR measurements. (A) Streak camera image that maps PL intensity versus time and wavelength. (B) PL intensity versus decay time for the 540−756 nm (black), 540−600 nm (blue), 600−660 nm (green), and 696−756 nm (red) wavelength ranges, extracted from the data in panel A. The instrument response function (IRF; gray) was collected at 800−810 nm, which is the second-order Raman signal from water. 4.2.5 ET with partitioned dark quenchers Collectively, the CGE results, TG PL spectra, and TR PL measurements show that the ensemble of SiNCs has sub-populations of smaller SiNCs with shorter PL emission wavelengths and shorter PL lifetimes than sub-populations of larger SiNCs. These differences are expected to lead to heterogeneity in the efficiency of ET. To study ET, SiNC(676) 1 were paired with a series of non-emissive Black Hole Quencher (BHQ) dyes: BHQ1, BHQ2, and BHQ3. These dyes had different degrees of overlap between their absorption spectra and the SiNC PL emission (0 μs delay, 2 ms integration time; Figure 4.5A), resulting in different spectral overlap integral (J) kernels derived from conventional FRET theory (Figure 4.5B). The estimated Förster distances (R0) for the ensemble of SiNC(676) 1 were 3.3 nm, 3.7 nm, and 4.5 nm with BHQ1, BHQ2, and BHQ3 acceptors, respectively. (As discussed later, 130 these initial values for J and R0 were naive.) Non-emissive dyes were useful for studying ET because they permitted unobstructed resolution of ET-induced changes in the PL emission spectrum of the SiNC samples. A further advantage of BHQ dyes was their very hydrophobic character, which drove the dyes to associate with the SiNCs by partitioning into the alkyl/PEG layer of their coating (see Appendix C.7 for confirmatory experiments). Figure 4.5 SiNC(676) 1 paired with BHQ dyes. (A) Absorption spectra of the BHQ dyes overlaid on the prompt PL emission spectrum (0 μs delay, 2 ms integration time) of the SiNC(676) 1. (B) Spectral overlap kernels between the SiNC(676) 1 and BHQ dyes, derived from conventional Förster theory. (C) Illustration (not to scale) of dyes partitioning from solution and into the coating on the SiNCs 1. 4.2.5.1 Prompt ensemble spectra An increasing number of equivalents of added BHQ dyes per SiNC(676) 1 resulted in a progressive decrease in SiNC PL intensity. Control experiments used the addition of DMSO to better solubilize the BHQs and confirm that inner filter effects were not the primary cause of quenching in PL intensity measurements, and size-selective filtration confirmed that the dyes were associated with the SiNCs (Appendix C.7). A superficial analysis of the total quenching efficiency (0 µs delay, 2 ms integration time) versus equivalents of BHQ revealed that, at lower numbers of equivalents, 131 the trend in efficiency was BHQ1 < BHQ2 < BHQ3 (Figure 4.6D), consistent with the trend in the naive ensemble values of J and R0. Although the trend persisted at higher equivalents for BHQ1 and BHQ3, the data for BHQ2 deviated, approaching a maximum quenching efficiency of 70% (cf. ≥ 90% for BHQ1 and BHQ3). Absorption spectra (Figure 4.6Bii) suggested that the BHQ2 began to form H-aggregates as more dye was added, shifting out of resonance with the SiNC(676) 1 emission with loss of ET. Further analysis of quenching from BHQ2 was limited due to this aggregation confounding observation of ET. Given its slow increase in quenching efficiency beyond 90%, BHQ1 may have also had some tendency to aggregate, but not to a degree that was evident in the absorption spectra (Figure 4.6Aii) or cautioned against further analysis. 132 Figure 4.6 Spectra and total ET efficiency of SiNC(676) 1 partitioned with BHQ dyes. (A) SiNC(676) 1 partitioned with various equivalents of partitioned BHQ1: (i) emission spectra (0 μs delay, 2 ms integration time) and (ii) absorption spectra. (B) SiNC(676) 1 with various equivalents of partitioned BHQ2: (i) emission spectra (0 μs delay, 2 ms integration time) and (ii) absorption spectra. (C) SiNC(676) 1 with various equivalents of partitioned BHQ3: (i) emission spectra (0 μs delay, 2 ms integration time) and (ii) absorption spectra. (D) ET efficiency of SiNC(676) 1 versus variable equivalents of BHQ1, BHQ2, and BHQ3: full range and zoom for lower equivalents of BHQ. The ET efficiency was calculated from the emission spectra (0 μs delay, 2 ms integration time) in panel A−C. 133 Changes in the SiNC PL emission spectra with increasing equivalents of each BHQ dye were also assessed in detail. One set of measurements sampled the full ensemble of SiNCs concurrently (0 µs delay, 2 ms integration time). Spectral shifts were monotonically bathochromic (up to 16 nm) with increasing equivalents of BHQ1 (Figure 4.6Ai), and were monotonically hypsochromic (up to 13 nm) with BHQ3 (Figure 4.6Ci). The shifts were consistent with more efficient quenching of smaller and larger SiNCs by BHQ1 and BHQ3, respectively, consistent with their qualitative spectral overlap with the ensemble of SiNC(676) 1 (Figure 4.5B). Changes in FWHM were also observed (+17 nm for BHQ1 and –13 nm for BHQ3). The spectral shifts suggested more efficient quenching of smaller and larger SiNCs by BHQ1 and BHQ3, respectively, and were consistent with the quantitative spectral overlaps between these dyes and the ensemble of SiNCs (Figure 4.5A). Differences in wavelength-dependent quenching efficiency were also observed between BHQ1 and BHQ3 (spectra for 0 µs delay, 2 ms integration time; Figure 4.7). These differences and were thought to arise from three factors: different spectral overlap integrals between the dyes, smaller donor-acceptor distances for smaller SiNCs, and a preference for dye to partition onto larger SiNCs with larger surfaces and a larger fraction of the total volume of alkyl/PEG phase. Unambiguous interpretation of the trends was thus challenging. For BHQ3, which had much more aligned spectral overlap with SiNC(676) 1, the trend at low equivalents of dye appeared to favour the shorter donor-acceptor distance of smaller SiNCs, then transitioned to a trend at higher equivalents of dye that appeared to reflect the better quantitative spectral overlap and greater partitioning with larger SiNC(676) 1. For BHQ1, the quenching at lower equivalents of dye appeared to favour the 134 greater surface area of larger SiNC(676) 1, then transitioned to favouring the shorter donor-acceptor distance and greater spectral overlap integral for the smaller SiNC(676) 1. Figure 4.7 ET efficiency versus wavelength. SiNC(676) 1 with partitioned (A) BHQ1 and (B) BHQ3. The ET efficiency at different wavelengths were calculated from the prompt ensemble emission spectra (0 μs delay, 2 ms integration time). 4.2.5.2 TG spectral snapshots Another set of SiNC PL emission spectrum measurements were done with a variable delay and fixed 20 µs integration time to obtain “spectral snapshots” biased toward different sizes of SiNC. As already established, the peak PL wavelength bathochromically-shifted with increasing delay time for the SiNC alone (Figure 4.8A). With BHQ1, the temporal trajectory for the peak SiNC(676) 1 PL wavelength had a gradual bathochromic shift (up to 45 nm) with increasing equivalents of dye. The FWHM changed from a trajectory that narrowed by 7 nm to one that widened up to 30 nm. In contrast, with BHQ3, the gradual temporal shift in the trajectory for the peak PL wavelength was smaller and hypsochromic (Figure 4.8B), and the FWHMs narrowed with a slightly faster rate of narrowing with more equivalents of dye. These shifts in the spectral trajectories were 135 consistent with the shifts observed in the prompt spectra and more efficient ET between smaller SiNCs and BHQ1 and between larger SiNCs and BHQ3. Figure 4.8 TG spectral snapshots (various delay, 20 µs integration time) of SiNC(676) 1 with partitioned BHQ dyes. (A) SiNCs with various equivalents of partitioned BHQ1: (i) emission peak shift versus delay time and (ii) FWHM versus delay time. (B) SiNCs with various equivalents of partitioned BHQ3: (i) emission peak shift versus delay time, and (ii) FWHM versus delay time. Lastly, the quenching efficiency as a function of wavelength and delay time was evaluated. For BHQ1, the quenching efficiency skewed toward higher values at longer wavelengths for lower equivalents of dyes, and toward shorter wavelengths for higher equivalents of dye (Figure 4.9A). For BHQ3, the quenching efficiency was consistently skewed toward higher values at longer 136 wavelengths (Figure 4.9B). These overall trends were similar to those observed with prompt ensemble spectra (0 µs delay, 2 ms integration time, Figure 4.7). For both BHQ1 and BHQ3, the apparent quenching efficiency increased as the delay time increased. This trend likely resulted from ET-induced shortening of the PL lifetime: a sub-population of SiNCs that previously contributed non-zero emission to given “snapshot” time window instead contributed negligible emission. Figure 4.9 Quenching efficiency as a function wavelength and delay time (various delay, 20 μs integration time). (A) SiNC(676) 1 with partitioned BHQ1. (B) SiNC(676) 1 with partitioned BHQ3. SiNCs without added BHQ were used as controls. 4.2.5.3 PL lifetime measurements ET between the SiNC(676) 1 and BHQ dyes was also investigated using wavelength-resolved and TR PL measurements (analogous to Figure 4.4). In all cases, the PL lifetime decreased as the number of equivalents of BHQ dyes increased (Figure 4.10), which was qualitatively consistent 137 with ET rather than an inner filter effect. Quantitatively, ET efficiencies estimated from amplitude-weighted PL lifetimes for the SiNC ensemble were compared to those measured from intensity measurements (0 μs delay, 2 ms integration time; Figure 4.6D). The trends of ET efficiencies measured from PL lifetimes were qualitatively consistent with the ET efficiencies from PL intensity data (Figure 4.10); however, the ET efficiencies obtained from PL lifetime measurements were lower than those from PL intensity measurements, by as much as a factor of two (Appendix C.11, Table C.7). PL lifetimes were also analyzed for three separate wavelength windows across the ensemble SiNC PL emission spectrum. For BHQ1, the lifetime-derived ET efficiency increased as the wavelength window increased from 540–600 nm to 600–660 nm to 696–756 nm (Figure 4.10A). The centre of the three wavelength windows (i.e. 570, 630, and 726 nm) are the wavelengths have ~50%, ~100%, and ~50% of the peak PL emission intensity, respectively (0 μs delay, 20 μs integration time). For BHQ3, the apparent ET efficiency was similar between the intermediate and long wavelength windows, but tended to be higher for the short wavelength window (Figure 4.10B). 138 Figure 4.10 TR PL measurements of SiNC(676) 1 partitioned with BHQ dyes. (A) PL decays of SiNC(676) 1 with various equivalents of partitioned BHQ1 for the entire emission range (540−756 nm), 540−600 nm, 600−660 nm, and 696−756 nm. (B) PL decay of SiNC(676) 1 with various equivalents of partitioned BHQ3 for the entire emission range (540−756 nm), 540−600 nm, 600−660 nm, and 696−756 nm. The TR PL measurements were compared the TG PL measurements with variable delay and 20 µs integration time. Scanning the delay time for the latter was equivalent to a box-car measurement of PL lifetime. Figure 4.11 shows these PL decays curves for the same wavelength windows as Figure 4.10. The data from the box-car method was reasonably consistent with the data from the TR instrument, with a bias of –12 ± 4 µs in the average lifetime and a bias in ET efficiency of 3 ± 8% (absolute value). These differences were considered to be sufficiently small for using the box-car method to assess trends in PL lifetime in some subsequent ET experiments. This approach avoided the need for TR PL measurements that had higher excitation intensities, longer times per sample, and serial rather than parallel throughput versus the box-car method on the plate reader, 139 and thus enabled the analysis of more samples. The box-car method (applied to the same sample set as Figures 4.10) suggested the lifetime-derived ET efficiency increased across the wavelength windows 540–600 nm, 600–660 nm, and 696–756 nm for both BHQ1 and BHQ3 (Figure 4.11). This trend was generally expected for BHQ3, but was opposite the expectation for BHQ1 based on spectral overlap. Figure 4.11 Box-car measurements of ET with SiNC(676) 1 and partitioned BHQ dyes. (A) Normalized PL intensity decay at various delay for BHQ1 at 540−600 nm, 600−660 nm, and 696−756 nm and ET efficiency at different wavelength windows. (B) Normalized PL intensity decay at various delay for BHQ3 at 540−600 nm, 600−660 nm, and 696−756 nm and ET efficiency at different wavelength windows. 4.2.6 ET with conjugated dark quencher In addition to partitioning, BHQ1 and BHQ3 were covalently coupled to SiNC(676) 2 (Figure 4.12A). SiNC(676) 1 was modified with adipic acid dihydrazide using carbodiimide coupling to 140 obtain hydrizide-modified SiNC(676) 2. Successful adipic acid dihydrazide modifications were confirmed by gel electrophoresis (Figure 4.1B). The dihydrazide groups were then conjugated with succinimidyl esters of BHQ1 and BHQ3 for comparison with adsorption of these dyes. Successful conjugation was confirmed from a post-purification absorption feature (see Appendix C.9) and from the quenched PL emission intensity for SiNC(676) 2 (Figure 4.12B). Figure 4.12 ET of SiNC(676) 2 conjugated with BHQs. (A) Illustration of SiNC 2 conjugated with BHQs. (B) Emission spectra (0 μs delay, 2 ms integration time) of SiNC(676) 2 with (i) conjugated BHQ1 and (ii) BHQ3. (C) ET efficiency of SiNC(676) 2 with conjugated BHQ1 and BHQ3. (D) ET efficiency of SiNC(676) 2 with conjugated (i) BHQ1 and (ii) BHQ3 at different wavelength windows (0 µs delay, 2 ms integration time). Progressive bathochromic and hypsochromic shifts were again observed with BHQ1and BHQ3 (Figure 4.12B), with a large magnitude for BHQ1. Figure 4.12C shows the quenching efficiencies 141 of SiNC(676) 2 with various equivalents of conjugated BHQ1 and BHQ3 (0 μs delay, 2 ms integration time). Compared to partitioned samples (dashed lines), the naive quenching efficiencies of conjugated samples were lower in both cases, suggesting that the conjugated dyes were, on average, further away from the SiNC than the partitioned dyes. Figure 4.12D shows that conjugated BHQ1 and BHQ3 both had higher quenching efficiencies at shorter wavelengths, regardless of the number of equivalents of BHQs. This trend was expected for BHQ1, and generally agreed with the expectation for BHQ3 based on spectral overlap. 142 Figure 4.13 TG spectral snapshots (various delay, 20 µs integration time) of SiNC(676) 2 conjugated with BHQ dyes. (A) SiNC(676) 2 conjugated with various equivalents of BHQ1: (i) emission peak shift versus delay time and (ii) FWHM versus delay time. (B) SiNC(676) 2 conjugated with various equivalents of BHQ3: (i) emission peak shift versus delay time and (ii) FWHM versus delay time. TG “spectral snapshots” (variable delay, 20 µs integration time) showed temporal trajectories for the peak PL wavelength for SiNC that shifted bathochromically for BHQ1 with larger magnitude (Figure 4.13A), and hypsochromically for BHQ3 with smaller magnitude (Figure 4.13B). These trends were consistent with the prompt ensemble spectral data for conjugated dyes (Figure 4.12B), and also with prompt ensemble data and TG snapshot data for partitioned BHQ dyes (Figure 4.8). For both BHQ dyes, the temporal change in FWHM was much reduced versus the analogous data 143 for partitioned samples (Figure 4.8). The quenching efficiency as a function of wavelength and delay time was evaluated. Both conjugated BHQ1 and BHQ3 samples show higher quenching efficiency at lower wavelength range (Figure 4.14). As with partitioned dye, the quenching efficiencies generally increased as the delay time increased (Figure 4.9). Figure 4.14 Quenching efficiency as a function wavelength and delay time (various delay, 20 μs integration time): (A) SiNC(676) 2 conjugated with BHQ1; (B) SiNC(676) 2 conjugated with BHQ3. 144 Based on box-car PL lifetime measurements in the wavelength windows 540–600 nm, 600–660 nm, and 696–756 nm (Figure 4.15), the apparent ET efficiency increased at longer wavelengths for BHQ3 and decreased at longer wavelengths for BHQ1, consistent with expectations based on spectral overlap. Figure 4.15 Box-car measurements of ET with SiNC(676) 2 with conjugated BHQ dyes. (A) Normalized PL intensity decay at various delay for BHQ1 at 540−600 nm, 600−660 nm, and 696−756 nm and ET efficiency for the different wavelength windows. (B) Normalized PL intensity decay at various delay for BHQ3 at 540−600 nm, 600−660 nm, and 696−756 nm and ET efficiency for the different wavelength windows. 145 4.2.7 ET with conjugated fluorescent dye Various equivalents of sulfonated Cyanine 5.5 (sCy5.5) dye were conjugated to SiNC(676) 2 to obtain sCy5.5 conjugated samples for further investigation of ET. The emission spectrum of SiNC(676) 2 and absorbance and emission spectra of sCy5.5 are overlaid in Figure 4.16B, which also shows the FRET spectral overlap kernel (Figure 4.16C). With the requirement for spectral overlap, the emission spectrum for sCy5.5 was poorly resolved from the broad SiNC(676) 2 emission spectrum. Covalent conjugation was necessary because the sCy5.5 was hydrophilic and did not spontaneously associate with SiNCs in buffer. Successful conjugation was confirmed by a sCy5.5 feature in absorption spectra following purification of the SiNCs by size-selective centrifugal filtration (Appendix C.10). 146 Figure 4.16 ET between SiNC(676) 2 and sCy5.5. (A) Illustration (not to scale) of SiNC 2 conjugated with sCy5.5. (B) Absorption spectra of the sCy5.5 overlaid on the prompt ensemble PL emission spectrum of the SiNC(676) 2. (C) Spectral overlap kernel between the SiNC(676) 2 and sCy5.5 dye, derived from conventional Förster theory. (D) Emission spectra of SiNCs with various equivalents of conjugated sCy5.5 (0 μs delay, 2 ms integration time). (E) Experimental (black data; 0 μs delay, 2 ms integration time) and deconvoluted emission spectrum (orange and dark red data) for SiNC(676) 2 conjugated with 6.0 equivalents of sCy5.5. (F) Wavelength-dependent ET efficiency derived from unmixing of the intensity data in panel D (solid points) and from SiNC PL lifetimes in panel G (box-car method, open points). (G) Box-car measurements of ET with SiNC(676) 2 with conjugated sCy5.5 for different wavelength windows. 147 Ensemble PL emission spectra (0 µs delay, 2 ms integration time; Figure 4.16D) were measured as the number of equivalents of sCy5.5 conjugated per SiNC increased. Two trends were observed: the SiNC PL emission intensity decreased and a sharper feature progressively emerged at ~696 nm, corresponding to the sCy5.5 emission peak. Wavelength-dependent quenching of the SiNC was more difficult to assess with the overlapping emission from the sCy5.5; however, unmixing of the spectra suggested the quenching of the SiNC increased from ~550 nm to ~680 nm, the latter wavelength corresponding to the absorbance peak of the sCy5.5, then decreased more steeply at longer wavelengths (Figure 4.16F). Box-car-type PL decay measurements (Figure 4.16F−G) showed that the ET efficiency was modest near 600 nm but increased significantly toward ~725 nm. Next, to demonstrate a potential advantage of using SiNC-based FRET probes and TG measurements for bioanalysis (Figure 4.17), SiNC(676) 2 conjugated with sCy5.5 were dispersed in 50% v/v serum. The prompt PL emission spectrum shows very strong background from the serum autofluorescence, as well as intense PL emission from direct excitation of sCy5.5 (i.e. not from ET). The TG PL emission spectrum (30 µs delay, 2 ms integration time) eliminates both of these contributions, leaving on the SiNC emission and ET-sensitized sCy5.5 emission. 148 Figure 4.17 Emission spectra of SiNC(676) 2 and SiNC(676) 2 with conjugated sCy5.5 dispersed in 50% v/v serum (aq). (A) Prompt measurements (0 μs delay, 2 ms integration time) show high background signal and substantial direct excitation of sCy5.5. (B) TG measurement (30 μs delay, 2 ms integration time) suppresses short-lived PL from serum autofluorescence and direct excitation of sCy5.5, leaving only SiNC PL and ET-sensitized sCy5.5 PL. 4.3 Discussion 4.3.1 Polydispersity and photophysical properties Theory and many prior studies have correlated the size of SiNCs with their optical properties. Quantum confinement leads to an increase in band-gap energy and decrease in PL emission wavelength as the nanocrystal size decreases.156,157 Being derived from an indirect-band-gap material, a substantial increase in radiative rate and a concomitant decrease in PL lifetime is also expected as size decreases.156,157 Although the oscillator strength of electronic transitions is expected to increase as size decreases, the molar absorption coefficient increases as size increases158 due to the increased density of states.159 This study has made the first use of spectroelectrophoresis and variable-delay TG PL to reveal correlations between SiNC size and PL properties. 149 Given Förster theory, polydispersity in size and PL properties is expected to impact ET with SiNC donors and also its experimental measurement: PL intensity and lifetime are common metrics for measuring ET efficiency; and the radius, PL emission quantum yield and homogeneous line width of an individual nanocrystal will partly determine the ET efficiency with proximal acceptors. These aspects of polydispersity have generally been unnecessary to consider when FRET donors are fluorescent dyes or QDs derived from direct band-gap semiconductors. Although high-quality cadmium chalcogenide QDs have heterogeneous broadening from size polydispersity—observable as small spectral shifts (≤ 10 nm) from wavelength-dependent FRET efficiencies—the magnitude of these effects is generally small enough to ignore when designing and utilizing FRET systems for practical applications (e.g. biological sensing and imaging, light harvesting). Here, the experimental data show that effects from the polydispersity of SiNCs is not necessarily negligible. The homogeneous PL emission wavelength of SiNCs has been estimated to be ~220 meV (FWHM), at 300 K, for alkyl-capped nanocrystals.160 (This energy FWHM corresponds to wavelength FWHMs of approximately 50–120 nm depending on peak PL wavelength.) As shown in Figure 4.18A, it was possible to fit the prompt ensemble PL emission spectrum with 7 peaks (Gaussian) of the specified FWHM. Of course, the real ensemble has a continuous distribution of nanocrystal sizes rather than discrete sub-populations; however, this exercise is useful for estimating the impact of polydispersity on FRET. The spectral overlap integral, J, with the BHQ and sCy5.5 dyes was recalculated for each of the SiNC sub-populations and shows substantial variation for each acceptor dye (Figure 4.18B). These spectral overlap integrals were then converted into R0/(R0)max—effectively a relative Förster distance—to show the corresponding 150 variation in this FRET parameter. The trends in R0/(R0)max are a qualitative match to the wavelength-dependent quenching trends for conjugated BHQ1, BHQ3, and sCy5.5. The match to the trends for partitioned BHQ1 and BHQ2 is poorer, suggesting that conjugation of dye may have provided a narrower distribution of donor-acceptor distances than partitioning of dye and/or other more ideal characteristics. Figure 4.18 Modelling SiNC(676) 1 polydispersity. (A) Ensemble-level emission spectrum (0 μs delay, 2 ms integration time) of SiNCs modelled as emission spectra from 7 discrete sub-populations. (B) Variation in the spectral overlap integral and R0/(R0)max between the hypothetical sub-populations of SiNCs when paired with BHQ dyes or sCy5.5 dye. 151 Specific values for Förster distances, R0, were estimated assuming a negligible change in quantum yield between sub-populations. Values ranged between 2.4−4.0 nm for BHQ1, 2.1−4.3 nm for BHQ2, and 3.0–4.7 nm for BHQ3, depending on the sub-population and quantum yield of the SiNC (~8% for partitioned dye with the original SiNC functionalization, ~3% for conjugated dye with the hydrazide modification; see Appendix C.6). These values compare to naive R0 values of 3.3/2.9 nm, 3.7/3.2 nm, 4.5/3.8 nm, and 5.1/4.3 nm (8%/3% quantum yield) for BHQ1, BHQ2, BHQ3, and sCy5.5, respectively, calculated from the prompt ensemble PL emission spectrum of the SiNC(676) 1 and 2. A previous study reported that the quantum yields of SiNCs prepared using the same type of synthetic methods were 23−30%. Our estimated quantum yields may be biased low by relative measurement versus a standard if there was a non-negligible contribution of light scattering to absorbance measured for SiNCs. Lager quantum yields would lead to larger R0 values (maximum ~1.1 nm larger in this case), but similar trends would be expected. The effective mass approximation suggests that the emissive SiNC diameters range from 2.0–3.3 nm for the hypothetical sub-populations. The R0 values thus range from 1–3 nm longer than the nanocrystal radii, where the donor-acceptor distances are assumed to be the best measured from the centre of the SiNC (by analogy with CdSe QDs). Given the thickness of the SiNC surface chemistry and length scale of common biomolecular probes (e.g. oligopeptides, proteins, oligonucleotides), the donor-acceptor distance will typically be >0.5R0, falling within the “molecular ruler” range where FRET is most sensitive to changes in distance. In turn, polydispersity in nanocrystal size will lead to maximum variation in FRET efficiency between individual nanocrystals. Even with ~10 equidistant acceptors per donor, which is readily achieved 152 with nanoparticle donors and dye acceptors, the onset of the molecular ruler regime is only delayed to ~0.8R0, or another 0.6–1.4 nm. Most SiNC conjugates with a molecular spacer between nanocrystal and dye should therefore expect substantial effects on FRET from size polydispersity. 4.3.2 Polydispersity and measurements of ET The polydispersity of the SiNCs also has consequences for measurements of ET. For example, different ET efficiencies will be obtained for different wavelength ranges, such that selection of spectral ranges or filter bandpasses has the potential to affect quantitative results. For instruments with pulsed excitation and finite times for PL measurement, the selected temporal parameters may also affect quantitative results. The most rigorous interpretation of data will require explicit consideration of a heterogeneous population of SiNC. When paired with fluorescent dyes, the spectrally broad emission of the SiNC and small Stokes shift of many dyes will make it difficult to obtain good FRET spectral overlap and good resolution of SiNC and dye emission in parallel. Deconvolution is challenging because the shape of the SiNC emission spectrum varies with the FRET efficiency. It is not a simple case of unmixing two invariant shapes of emission spectra with different scaling coefficients, as would be the case with dye-only FRET systems and more monodisperse QDs. Consequently, there is greater opportunity for error or bias. 4.3.3 Limitations of this study The data does not unequivocally confirm that the mechanism of ET between SiNC donors and dye acceptors is specifically the Förster mechanism (FRET); however, the observed dependence of ET 153 on the spectral overlap is strongly suggestive of FRET. Drawing an unequivocal conclusion would require measurement of the ET efficiency in parallel with precise and systematic variation of the distance between SiNC and acceptor dye, as well as reasonably accurate knowledge of the number of dyes per SiNC, to establish the inverse-sixth-power distance dependence of ET efficiency. Experiments to systematically control the donor-acceptor distance, while also accounting for size polydispersity, are beyond the scope of this initial study. There are also challenges to resolve for accurate determination of dye:SiNC ratios. Dye concentrations are straightforward to determine with their well-defined absorption peaks, their well-known molar absorption coefficients, and the expectation of a Poisson-like distribution of dyes per SiNC.161 The challenge is obtaining an accurate concentration of SiNC-dye conjugates. Although non-optical methods (e.g. combination of TEM and TGA) may be used to estimate concentration for a large batch of material, the methods tend to be impractical for the scale of individual samples. Optical absorbance methods are far more suitable, but are limited by the relatively weak absorption of the SiNC and lack of defined peak—especially in comparison to dyes within the same sample. An advantage of this partitioning approach was that it did not require purification after adding dye, thereby avoiding potential loss of SiNCs during purification and enabling more reliable measurements of ET efficiency from quenching of the SiNC PL and more precise variation of the relative amount of dye per SiNC. To assess the plausibility of the original SiNC concentration estimate, the extreme hypothesis that one BHQ3 is able to quench one SiNC with 100% ET efficiency was considered. With a Poisson distribution of one dye per SiNC, ~63% of the SiNC population would have ≥ 1 BHQ3 molecule. 154 In the prompt ensemble measurements, 0.15 equivalents of BHQ3 FRET yielded ~63% quenching, which suggests that the actual SiNC concentration might be around 6.7-fold more diluted than the current estimate. Of course, it is also possible that one SiNC requires more than one BHQ3 for complete quenching; however, one of the few prior reports of ET with SiNCs noted ~80% quenching at one equivalent of dye, consistent with the idea of complete quenching from a single dye per SiNC. The concentrations revised by 6.7-fold also yield calculated donor-acceptor distances that are shorter and more consistent nanocrystal radii plus coating thickness. (The equivalents indicated in the figures are the revised values.) Another limitation is the assumption that the orientation factor is κ2 = 2/3, corresponding to dynamically random orientations of the SiNC and dye transition dipoles. This assumption has generally proven adequate with CdSe QDs and is plausible for conjugated hydrophilic sCy5.5. However, for all of the hydrophobic BHQ dyes, which have preference to partition into the SiNC surface coating, the assumption of dynamic rotation is questionable. Nevertheless, any error in the κ2 should apply across the ensemble of SiNCs, affecting the R0 for different sub-populations by the same relative degree. The observed qualitative trends should not be significantly affected by the assumption of κ2 = 2/3. Another limitation to consider is inner filter effects. Intensity measurements yielded higher ET efficiencies than lifetime measurements and inner filter effects are a possible explanation for this difference. The absorption spectra check suggested an absence of significant reabsorption of SiNC emission by BHQ; however, competitive absorption of excitation light by BHQ may still have caused some reduction of SiNC PL intensity. Even with non-zero inner filter effects, the 155 occurrence of ET remains clear from the dye-induced decrease in SiNC PL lifetime, and from the observation sCy5.5 that, due to time-gating, must arise from ET rather than direct excitation. 4.3.4 Merits of SiNC as an ET donor In addition to biocompatibility, SiNCs are attractive materials for biological applications because of their long-lived PL property. Excitation of SiNC PL is most efficient in the UV, which will often yield unwanted and non-negligible direct excitation of a fluorescent dye acceptor, as well as autofluorescence background from many biological samples. The time-gating afforded by the long SiNC PL lifetime negates these challenges, and the improvement in signal-to-background ratio helps mitigate the lower brightness of SiNCs versus direct-band-gap QDs. A shortcoming of SiNCs that time-gating does not mitigate is their spectrally broad PL emission. As note earlier, the broad emission makes it difficult to resolve emission from a fluorescent acceptor, and spectral deconvolution is possible but more difficult and less reliable than for other systems. Conventional ratiometric measurements (e.g. via bandpass filters or selected wavelengths) may be ineffective in some cases because loss of SiNC PL intensity from FRET is offset by the increase of FRET-sensitized dye emission at the same wavelength(s). Larger shifts of the SiNC peak may also complicate quantitative analysis. The broad emission and overlap with emission from other emitters are also a barrier to multiplexed FRET, whether via different colours of SiNC donor paired with different acceptor dyes or one colour of SiNC donor paired with multiple acceptor dyes (e.g. cFRET). 156 To maximize the potential of SiNC as ET donors, particularly for assay and sensor development, it will be necessary to continue to optimize their synthesis and functionalization to obtain size monodispersity, high quantum yield, and reduced surface sensitivity. If these three advancements can be made, then the smaller size and putatively more benign composition if SiNCs may become substantial advantages of SiNCs versus direct-band-gap QDs and other luminescent nanoparticles. Benefits of smaller size include a shorter minimum donor-acceptor distance for ET, and reduced risk of adverse steric effects (e.g. on the structure and activity of conjugated biomolecules or their binding partners, hindered access to cellular and tissue environments). Optimizing synthesis processes and post-synthesis purification (e.g. density gradient ultracentrifugation) have been reported as approaches to obtain monodispersed SiNCs.141,162–164 There are also efforts to improve quantum yields in water. Overcoming PL sensitivity to nitrogen-containing molecules is also something that will be important for various bioconjugation strategies.145 4.4 Conclusion SiNCs and ET systems with SiNC donors paired with a series of quencher dyes or fluorescent dye were characterized using a combination of spectroelectrophoresis, TG PL measurements, and TR PL measurements. The collective data shows that the size polydispersity of the SiNCs and resulting distribution of PL properties has a substantial impact on ET, both in terms of its efficiency and its measurement. Although further investigation is warranted, the results of this study are consistent with a Förster type mechanism. As donors, the SiNCs are potentially disadvantageous in their relatively low brightness and heterogeneity, but potentially advantageous in their small size, composition, and long PL lifetime that supports TG measurements. Overall, SiNCs are unlikely to become the preferred ET donor material for most applications in bioanalysis and imaging, 157 Nevertheless, with continued optimization and suitable approaches for analysis, SiNC-based FRET probes are likely to become useful for select applications. This study has provided an important foundation for moving toward this objective. 4.5 Experimental Methods 4.5.1 Materials and instruments BHQ1 NHS ester, BHQ2 NHS ester, and BHQ3 NHS ester were from Biosearch (Teddington, UK; distributed by Cedarlane, Burlington, ON, Canada). Sulfo-Cyaninie5.5 NHS ester was from Lumiprobe (Hunt Valley, MD, USA). NHS was from Merck (Darmstadt, Germany). Sodium tetraborate decahydrate, tetramethylethylenediamine (TEMED), ammonium persulfate (APS) were from Amresco (Boise, ID, USA). 2-(N-Morpholino)ethanesulfonic acid (MES), NaCl, acetic acid, NaOH, and 10× TBE buffer were from Thermo-Fisher Scientific (Burlington, ON, Canada). Acrylamide:bis-acrylamide (37.5:1, 40% w/w in water) solution, 3-(trimethoxysilyl)propyl methacrylate (TMSM), Sigmacote, boric acid, Dulbecco’s phosphate buffered saline (DPBS; D5652), adipic acid dihydrazide, 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC), agarose, DMSO, Amicon centrifugal filters (MWCO 30 kDa, Ultracel membrane, 0.5 mL capacity), and bovine serum (B9433) were from Sigma-Aldrich (Oakville, ON, Canada). SiNCs 1 were synthesized using a previously published method39 by Christopher Jay Robidillo, Ziqi Li, Gunwant K. Matharu, Kevin O’Connor, or I Teng Cheong from Prof. Jonathan Veinot’s group (University of Alberta). UV-visible absorption spectra and PL spectra (including solution-phase protease assays) were measured with an Infinite M1000 Pro multifunction plate reader (Tecan Ltd., Morrisville, NC, 158 USA) using a transparent half-area 96-well plate (#3679 or #3695; Corning, Corning, NY, USA; or #675801; Greiner, Monroe, NC, USA) or a black 384-well plate (#3575; Corning, NY, USA). CGE experiments were performed on an IX83 inverted epifluorescence microscope (Olympus, Richmond Hill, ON, Canada) equipped with an X-Cite 120XL metal-halide light source (Excelitas Technologies, Mississauga, ON, Canada), a high-voltage power supply (ER230 HV; eDAQ, Colorado Springs, CO, USA), a GreenWave 16 VIS-50 portable CCD spectrometer (StellarNet, Tampa, FL, USA), and LabVIEW software (National Instruments, Austin, TX, USA). Borosilicate glass capillaries were from Drummond Scientific (75 mm length, 0.4 mm inner diameter; Drummond Scientific Co., Broomall, PA, USA). Plasma cleaner was from Harrick Plasma (PDC-32G; Ithaca, NY, USA). Microscope glass slide (75 mm × 26 mm) drilled with a 1.3-cm diameter hole and coated with hydrophobic Sigmacote. TR PL measurements were made using a sub-micro quartz cuvette (#16.100F-Q-10/Z15; Starna Cells, Inc., Atascadero, CA, USA). The excitation pluses were generated with a Nd:YAG laser (PL2241; EKSPLA, Vilnius, Lithuania). The laser output was wavelength-tuned with a picosecond optical parametric generator (PG401; EKSPLA, Vilnius, Lithuania). Wavelength-resolved lifetime data were obtained with an Acton spectrometer (Princeton Instruments, Trenton, NJ, USA) and a streak camera (C7700; Hamamatsu Photonics, Hamamatsu, SZK, Japan). 4.5.2 SiNC(676) 1 partitioned with BHQ dyes NHS ester functionalized BHQ1, BHQ2, and BHQ3 were dissolved in DMSO, and the concentrations were determined using the reported absorbance coefficients at the maximum 159 absorbance wavelengths (see “Absorbance Measurement” section). The quenchers were diluted with DMSO to final concentrations of 0.012−0.50 mM, and then 0.60 nmol × n of BHQ1, BHQ2, and BHQ3 were further mixed with DMSO to final volume of 10 μL, where the n were the equivalents of each quencher per SiNC(676) 1 (n = 0, 0.05, 0.1, 0.3, 0.5, 0.7, 1, 2, 4, and 7 equivalents for BHQ1; 0, 0.05, 0.1, 0.2, 0.4, 0.7, 1, 3, and 6 equivalents for BHQ2; 0, 0.02, 0.03, 0.05, 0.06, 0.07, 0.1, 0.15, 0.2, 0.5, 1, and 2 equivalents for BHQ3; the n values were without applying 6.7-fold correction). A 60 μL aliquot of 10 μM carboxylic acid modified SiNC(676) 1 (0.60 nmol, 1.0 equiv.) was added into the BHQ/DMSO solution, and then 330 μL of 1× DPBS (pH 7.5) was added to induce adsorption of quenchers to the SiNCs. For preparing smaller scale of samples, 0.11 or 0.22 nmol of SiNC(676) 1 and scaled-down reagents were used with the same procedures. The final concentration of SiNCs was 1.5 μM, and the final composition of the solvent was 1× DPBS with 2.5% v/v DMSO. The BHQs partitioned SiNCs were leave at room temperature overnight for hydrolysis of the NHS ester, and then store at 4 ○C until needed. 4.5.3 Preparation of SiNC(676) 2 SiNC(676) 1 (45 nmol, 1.0 equiv.) was diluted and dispersed with MES buffer (0.1 M, pH 6.0, with 0.5 M NaCl) to a final volume of 510 μL. An aliquot of 45 μL of 200 mM of NHS/MES solution (9.0 mmol, 200 equiv.) and 45 μL of 200 mM of EDC/MES solution (9.0 mmol, 200 equiv.) were added into the SiNC solution, and then the mixture was reacted for 15 min at room temperature. Next, an aliquot (45 μL) of adipic acid dihydrazide (200 mM, 9.0 mmol, 200 equiv.) dissolved in 2× DPBS and an additional 2× DPBS (3.72 mL) were added, followed by mixing for 1 h at room temperature. The reaction was recharged with three additional aliquots of EDC (45 μL, 9.0 mmol, 200 equiv.) in 2× DPBS at 1 h intervals. The final concentration of SiNC was 10 μM. 160 The reaction was prevented from light, agitated on a mixer, and reacted overnight at room temperature. The reaction mixture was concentrated/purified using 30 kDa centrifugal filters (0.5 mL capacity) and span at 14 000 RCF for 10 min. Four centrifugal filters were used parallelly, and two centrifugation cycles were used for reducing the volume of the solution. The concentrated reaction mixture was further washed with 450 μL of 2× DPBS (pH 7.3) and span at 14 000 RCF for 10 min. In total, the mixture was washed with 450 μL of 2× DPBS four times using the same centrifugal filters. The purified hydrazide modified SiNC(676) 2 were further diluted with 2× DPBS buffer. The concentration was determined by the absorption at 350 nm (extinction coefficient: 12 160 M−1 cm−1 at 350 nm). The sample was stored at 4 ○C until needed. Note: A smaller scale of SiNC 2 was successfully prepared using the same procedures starting with 20 nmol of the SiNC 1 and scaled down reagent quantities. 4.5.4 SiNC(676) 2 conjugated with BHQ dyes Succinimidyl ester functionalized BHQ1 were dissolved in DMSO to final concentrations of 0.50 mM, and then 1.8 nmol × n of the BHQ1 was further mixed with DMSO to final volume of 20 μL. The n was the average equivalent of the BHQ1 per SiNC, and the values of n were 0, 1, 2, 5, 10, and 20 (the n values were without applying 6.7-fold correction). The zero-equivalent BHQ1 reaction was used as a control reaction. Hydrazide modified SiNC(676) 2 (1.8 nmol, 1.0 equiv.) was mixed with the BHQ1/DMSO, and then 2× DPBS was added into the reaction mixture to final 161 volume of 180 μL. The final concentration of SiNC was 10 μM. The reaction was agitated and reacted overnight at room temperature. Next, the reactions were further diluted with 600 μL of 65% v/v EtOH (aq) to lower the concentration of DMSO, and then the reaction mixture was concentrated using 30 kDa centrifugal filters (0.5 mL loading capacity) and span at 14 000 RCF for 5 min for two cycles. Purification was done using the same filters by washing seven times with 400 μL of 65% v/v EtOH (aq), spinning at 14 000 RCF for 5 min Then, the sample were switched to 1×DPBS using the same filters by washing four times with 450 μL 1× DPBS, spinning at 14 000 RCF for 10 min. The volume of purified SiNC was ~23 μL, and then 92 μL of 1× DPBS was added to further dilute the SiNC to final volume of ~115 μL. The concentrations of SiNCs were estimated from the control reaction (n = 0) by measuring the extinction at 350 nm (extinction coefficient: 12 160 M−1 cm−1). The labelling efficiencies of BHQ1 were estimated from the absorption of BHQ1 at 534 nm (molar absorption coefficient: 34 000 M−1 cm−1). The sample were further diluted with 1× DPBS to the final concentrations of SiNC were 1.5 μM. All the samples were store at 4 ○C until needed. The yield of the SiNC were ~58%. The labelling efficiencies of BHQ1 were 19.3−5.8%. The lower equivalent of BHQ1 in reaction had higher labelling efficiency. Procedures analogous to those described above were used for labelling SiNC(676) 2 with BHQ3. The average equivalent of the BHQ3 per SiNC were 0, 0.06, 0.15, 0.4, 1, and 5 (the equivalents were without applying 6.7-fold correction) for labelling reactions. The labelling efficiencies of BHQ3 were estimated from the absorption of BHQ3 at 654 nm (molar absorption coefficient: 42 162 700 M−1 cm−1). The yield of the SiNC were ~65%. The labelling efficiencies of BHQ3 were 26−9.2%. The lower equivalent of BHQ3 in reaction had higher labelling efficiency. 4.5.5 Label SiNC(676) 2 with sCy5.5 The procedures were modified from the experimental section of labelling SiNC(676) 2 with BHQ1 or BHQ3. Briefly, succinimidyl ester functionalized sCy5.5 were dissolved in DMSO, and the concentration was determine using the reported absorbance coefficients at maximum absorbance wavelengths. The concentrations of the sCy5.5 stock was 12.4 mM, and then 1.8 nmol × n of the sCy5.5 was mixed with DMSO to final volume of 20 μL. The n was the average equivalent of the sCy5.5 per SiNC, and the values of n were 0, 10, 20, and 50. Hydrazide modified SiNC(676) 2 (1.8 nmol, 1.0 equiv.) was mixed with the sCy5.5/DMSO, and then 2× DPBS was added into the reaction mixture to final volume of 200 μL. The final concentration of SiNC was 9.0 μM, and the reaction was agitated and reacted overnight at room temperature. The reactions were further diluted with 600 μL 1× DPBS, and then the reaction mixture was concentrated and purified using 30 kDa centrifugal filters (0.5 mL loading capacity) and span at 14 000 RCF for 10 min. Two centrifugation cycle were used for reducing the volume, and then the concentrated reaction mixtures were purified with 450 μL 1× DPBS. In total, the concentrated reaction mixture was washed with 450 μL 1× DPBS five times. The volume of purified SiNC was ~23 μL, and then 92 μL of 1× DPBS was added to further dilute the SiNC to final volume of ~115 μL. The concentrations of SiNC were estimated from the control reaction (n = 0) by measuring the extinction at 350 nm (molar extinction coefficient: 12 160 M−1 cm−1). The labelling efficiencies of sCy5.5 were estimated from the absorption of sCy5.5 at 676 163 nm (molar absorption coefficient: 211 000 M−1 cm−1). The sample were further diluted with 1× DPBS the final concentrations of SiNC were 1.5 μM. All the samples were store at 4 ○C until needed. The yield of the SiNC were ~57%. The labelling efficiencies of sCy5.5 were 3.1−1.0%. The lower equivalent of sCy5.5 in reaction had higher labelling efficiency. 4.5.6 Capillary gel electrophoresis The CGE experiments were slightly modified from reported protocols.154,155 Briefly, capillaries were modified with TMSM and filled with poly(acrylamide) gel. Cleaned borosilicate glass capillaries (75 mm length, 0.4 mm inner diameter) were immersed in TMSM/acetic acid/ethanol solution (3% v/v of TMSM and 1% v/v of acetic acid in ethanol) for 4 h. The TMSM modified capillaries were dried with air and placed in a ~70 ○C oven at least overnight. To form a 3.0% w/w gel, 113 μL of acrylamide:bis-acrylamide (37.5:1, 40% w/w in water) solution was diluted with 1381 μL of borate buffer (50 mM, pH 8.6), and then 1.5 μL of TEMED and 4.5 μL of APS solution (25% w/v in water) were added to the solution. The TMSM modified capillaries were filled with the solution by capillary action and left at room temperature for 2−3 h to allow the gel to solidify. The gel-filled capillaries were soaked and stored in borate buffer until needed. The gel-filled capillaries were truncated to ~5.5 cm to fit in the customized gel electrophoresis setup. The concentration of SiNC(717) 1 were ~6.4 μM or ~210 μM, and fluorescein (~30 nM or 1.5 μM) was added as an internal standard. The SiNC samples were electrokinetically injected into capillaries by applying 300 V for 5 s. The borate buffer (50 mM, pH 9.2) was used as running buffer, and the field strength was ~55 V/cm (300 V was applied across two electrodes). A metal-halide light source built in an inverted fluorescence microscope was used as an excitation source. 164 The excitation filter (405/20 nm or 380/15 nm; centre wavelength/bandwidth), dichromic mirror (510 nm or 425 nm cutoff), and emission filter (530 nm or 435 nm longpass). A CCD spectrometer was connected to the microscope with an optical fibre to collect the electropherograms and the real-time spectra. The data were recorded in LabVIEW. Data points were collected every 2 s, and the integration time of each data point was 0.8 s. 4.5.7 Slab gel electrophoresis A 0.5% w/v agarose gel was prepared. The SiNC(676) 1 and SiNC(676) 2 were individually dispersed in DPBS to the final volume of 16.8 μL, and then a 4.2 μL aliquot of 50% v/v glycerol/H2O were added to the final concentration of glycerol was 10% v/v. Sample volumes of 20 μL of SiNC were loaded into wells that each well contains ~30 pmol of SiNCs. TBE buffer (89 mM Tris base, 89 mM boric acid, 2 mM EDTA, pH 8.3) was used as running buffer. The gel was run with ~6.7 V/cm field strength for 30 min. The gel was imaged with a Gel Doc XR+ Imager (Bio-Rad, Mississauga, ON, Canada) equipped with a UV excitation source. 4.5.8 Absorbance measurements. The absorbance spectra were measured using an Infinite M1000 Pro plate reader (Tecan Ltd., Morrisville, NC, USA) equipped with a xenon flash lamp, excitation and emission monochromators, and a photomultiplier tube detector. Sample volumes of 100 μL were transferred into a clear-bottom half-area 96-well plate (Corning #3695 or Corning#3679) for absorbance and concentration measurements, and the path lengths of the samples were 0.6 cm. Alternatively, 80 μL aliquot of samples were transferred into a clear-bottom half-area 96-well plate (Greiner 165 #675801) for absorbance and concentration measurements, and the path lengths of the samples were 0.5 cm. The concentration of BHQ1 was determined at the absorbance peak (520 or 534 nm) with absorbance coefficient 34 000 M−1 cm−1. The concentration of BHQ2 was determined at the absorbance peak (570 nm) with absorbance coefficient 38 000 M−1 cm−1. The concentration of BHQ3 was determined at the absorbance peak (654 nm) with absorbance coefficient 42 700 M−1 cm−1. The concentration of sCy5.5 was determined at the peak (675 or 676 nm) with absorbance coefficient 211 000 M−1 cm−1. The concentration of SiNC was determined at 350 nm with extinction coefficient 12 160 M−1 cm−1. 4.5.9 TG emission/excitation spectra, and EEMs The emission and excitation spectra were measured using an Infinite M1000 Pro plate reader (Tecan Ltd., Morrisville, NC, USA) equipped with a xenon flash lamp, excitation and emission monochromators, and a photomultiplier tube detector. Sample volumes of 100 μL or 40 μL were transferred into a clear-bottom half-area 96-well plate (Corning #3695 or Corning #3679) or a black 384-well plate (Corning #3575) for PL measurement. TG emission and excitation spectra of SiNC(717) 1 A 100 μL aliquot of ~6.4 μM SiNC(717) 1 (in 50 mM borate buffer, pH 8.6) was transferred into a clear-bottom half-area 96-well plate. The sample was excited at 280 nm with 2.5 nm bandwidth for collection of emission spectra. The emission wavelengths were between 400−850 nm, and bandwidth was 5 nm. The delay time was 0−400 μs, and the integration time were 20 and 2 ms. 166 Next, the sample was excited between 230−702 nm for collection of excited spectra. The bandwidth was 2.5 nm when excited at 230−300 nm, the bandwidth was 5 nm when excited 300−702 nm. The emission wavelength was 712 nm, and bandwidth was 5 nm. The delay time was 0−200 μs, and the integration time were 20 or 2 ms. For measuring a smaller diameter of SiNC(605) 1, which has emission around 550−630 nm, the concentration of the SiNC was ~12.6 μM dispersed in borate buffer. The sample was excited at 280 nm with 2.5 nm bandwidth for collection of emission spectra. The emission wavelengths were between 400−850 nm, and bandwidth was 5 nm. The delay time was 0−150 μs, and the integration time were 20 and 2 ms. Next, the sample was excited between 230−500 nm for collection of excitation spectra. The bandwidth was 2.5 nm when excited at 230−300 nm, the bandwidth was 5 nm when excited 300−500 nm. The emission wavelength was 582 nm, and bandwidth was 5 nm. The delay time was 0−150 μs, and the integration time were 20 or 2 ms. (This set of data is shown in Appendix C.4.) Excitation-emission matrix A 100 μL aliquot of ~6.4 μM SiNC(717) 1 (in 50 mM borate buffer, pH 8.6) was transferred into a clear-bottom half-area 96-well plate. The excitation wavelengths were between 252−600 nm. The bandwidth was 2.5 nm when excited at 252−300 nm, the bandwidth was 5 nm when excited 300−600 nm. The increment of excitation wavelength was 12 nm. The emission spectra were collected between 450−846 nm with 5 nm bandwidth in 12 nm steps. The delay time was 0−300 μs, and the integration time were 20 or 2 ms. 167 For measuring a smaller diameter of SiNC(605) 1, which has emission around 550−630 nm, a 100 μL aliquot of ~12.6 μM SiNC(605) 1 (in 50 mM borate buffer, pH 8.6) was transferred into a clear-bottom half-area 96-well plate. The excitation wavelengths were between 230−636 nm. The bandwidth was 2.5 nm when excited at 230−300 nm, the bandwidth was 5 nm when excited 300−636 nm. The increment of excitation wavelength was 14 nm. The emission spectra were collected between 349−839 nm with 5 nm bandwidth in14 nm steps. The delay time was 0−150 μs, and the integration time were 20 or 2 ms. (This set of data is shown in Appendix C.4.) TG emission spectra of partitioned SiNC(676) 1 and conjugated SiNC(676) 2 Sample volumes of 100 μL aliquot of 1.5 μM SiNC(676) 1 partitioned with BHQ dyes (in 1× DPBS with 2.5% v/v DMSO) or BHQs or sCy5.5 conjugated SiNC(676) 2 (in 1× DPBS) were transferred into a clear-bottom half-area 96-well plate. The excitation wavelengths were at 240 nm with 2.5 nm bandwidth. The emission spectra were collected between 400−850 nm with 5 nm bandwidth. The delay time was 0−400 μs, and the integration time were 20 and 2 ms. The emission spectra of partitioned SiNC(676) 1 and BHQs conjugated SiNC(676) 2 were fitted with GCAS function (Gram-Charlier peak function) built in Origin to determine the wavelength at the maximum PL intensities and the FWHM of the emission peaks. The emission spectra with 2 ms integration time were used for calculating the quenching efficiencies. Since the emission of SiNC and sCy5.5 are overlapping, subtracting the FRET-sensitised sCy5.5 PL signals are required for estimating the quenching efficiencies of the SiNC(676) 2 in the sCy5.5 conjugated samples. First, a sCy5.5 emission spectrum were fitted with two bigaussian functions. 168 These two bigaussian with finding central wavelengths, widths of these peaks, and ratio of the peak heights were used for describing the sCy5.5 emission signal. Next, the SiNC(676) 2 emission spectra (integration time = 2 ms) were fitted with three bigaussian functions. Two of the functions were used for describing FRET-sensitized sCy5.5 signal by fixing the central wavelengths (peak 1: 692.3 nm, peak 2: 720.8 nm), the widths (peak 1: 14.3 and 14.1 nm, peak 2: 10.1 and 47.8 nm), and the ratio of the peak heights (peak 1 = 3.99 peak 2). The third bigaussian function was used for describing the emission of SiNC, and the fitted functions was used for calculating the quenching efficiency of the SiNC. 4.5.10 Lifetime measurement using streak camera A 120 μL aliquot of 1.5 μM of BHQ portioned SiNC(676) 1 (dispersed in 1× DPBS with 2.5% v/v DMSO) was transferred into a sub-micro quartz cuvette (#16.100F-Q-10/Z15; Starna Cells, Inc., Atascadero, CA, USA). The excitation pluses were 355 nm with 35 ps pulse duration and 10 Hz repetition generated with a Nd:YAG laser (PL2241; EKSPLA, Vilnius, Lithuania). Wavelength-resolved lifetime data were obtained with a combination of an Acton spectrometer (Princeton Instruments, Trenton, NJ) and a streak camera (C7700; Hamamatsu Photonics, Hamamatsu, SZK, Japan). The excitation pulses were 355 nm, and the power of excitation pulses was between 200−250 μJ. The TR spectra were collected between 476−838 nm, and the time ranges were 1 ms. The PL intensities were adjusted using neutral density filters with optical density filters (ND = 0.2−1) to avoid pile-up effect. The lifetime signals were accumulated with 100 000 excitation pulses. 169 4.5.11 Estimating extinction coefficient of SiNC(676) 1 The concentration of SiNC(676) 1 was estimated by combining the results of transmission electron microscopy (TEM) images and thermogravimetric analysis (TGA). First, the average diameter of the SiNC was determined by measuring the nanocrystal size from the TEM images. The average mass per nanocrystal was calculated from the diameter and the density of Si crystal (2.33 g/cm3). Second, the quantity of Si element in a SiNC(676) 1 stock solution (dispersed in water) was determined from the TGA results, which provides the mass of Si element per unit volume (mg/mL). The concentration of SiNC were obtained from dividing the TGA results by the mass of SiNC. To estimate the extinction coefficient of the SiNC(676) 1, the SiNCs was dispersed in 1× DPBS to final concentrations of 0−14.6 μM. In total, 6 concentrations were prepared (blank was included). Sample volumes of 100 μL of the SiNC samples were transferred into a clear-bottom half-area 96-well plate for absorbance measurement, and the path lengths were 0.6 cm. The absorbance values (including extinction) at 350 nm were measured. A plot of the absorbance (and extinction) versus the concentration was plotted, and then a linear fit was applied with a constraint that the intercept at y = 0. The slope of the linear fit was used as the extinction coefficient of the SiNC(676) 1 at 350 nm. (This set of data is shown in Appendix C.5.) Note: A post-hoc revision of the nominal concentrations was later motivated by the results of ET experiments with portioned BHQ dye and modelling of a Poisson distribution with the assumption of 100% ET efficiency for one dye per SiNC (vide infra). The experimental methods are written for the nominal concentration of SiNCs; however, the data in the Results sections report the revised 170 concentrations and dye/SiNC ratios, which are 6.7-fold more dilute and larger, respectively, than the nominal values. There was no adjustment of the dye concentrations. 4.5.12 BHQ dissociation test The 1.5 μM of BHQ partitioned SiNC(676) 1 were prepared as described earlier. Briefly, the SiNC(676) 1 (0.11 nmol, 1.0 equiv.) were mixed with 1.0 equivalents of BHQ1, BHQ2, and BHQ3 individually. SiNCs without quenchers were prepared and used as reference samples. Sample volumes of 100 μL of the SiNC samples (in 1× DPBS with 2.5% v/v DMSO) were transferred into a 96-well plate for PL measurement, and the integrated PL intensities were used for calculating the quenching efficiencies caused by adsorption of the quenchers. Another 42 μL aliquot of the SiNC from each sample was mixed with 63 μL of DMSO individually to allow the quenchers to dissociate from the SiNCs. The final concentration of SiNC was 0.75 μM, and the final composition of the solvent was 1× DPBS with 41.5 % v/v DMSO. Sample volumes of 100 μL of these SiNC samples were transferred into a 96-well plate for PL measurement, and the integrated PL intensities were used to calculate the quenching efficiencies caused by (partly) dissociation of the quenchers. All the emission spectra were excited at 240 nm with 2.5 nm bandwidth. The emission spectra were collected from 400−850 nm, and bandwidths were 5 nm. The delay time was 0 μs, and the integration time was 2 ms. (This set of data is shown in Appendix C.9.) 4.5.13 Preparation of serum samples The 1.5 μM of SiNC(676) 2 and SiNC(676) 2-sCy5.5 were dispersed in 1× DPBS. A 25 μL aliquot of the SiNCs was mixed with 25 μL of serum to the final concentration of SiNC was 0.75 μM, and the final composition of the solvent was 1× DPBS with 50% v/v serum. Sample volumes of 40 μL 171 of the SiNC samples were transferred into a 384-well black plate. The samples were excited at 240 nm with 4 nm bandwidth. The emission wavelengths were 400−850 nm, and the bandwidth was 5 nm. The delay time were 0 and 30 μs, and the integration time was 2 ms. The flash frequency was 100 Hz, and the number of flashes was set at 100. 4.5.14 Quantum yield measurement The quantum yields of SiNC(676) 1 and SiNC (676) 2 were estimated by comparison to fluorescein, the procedures were adopted from previous reports with minor modifications. The fluorescein was dissolved in 0.1 N NaOH (aq), and the quantum yield of fluorescein (𝛷𝐹𝐿) was 0.91.165,166 The SiNC samples were dispersed in 1× DPBS. A series of dilutions of fluorescein, SiNC(676) 1, and SiNC(676) 2 were prepared. The integrated PL intensities were plotted as functions of their absorbance values, and linear fits were applied with a constraint that intercept at y = 0. To have reliable fluorescein absorbance values without saturated PL signals, the absorbance values of fluorescein samples were obtained from their 10-times concentrated samples, so that the absorbance value for the plot can be simply divided by the dilution factor (10 in this experiment). The absorbance values of SiNCs were corrected by subtracting the contribution from scattering. The quantum yields of SiNCs were obtained by comparing the slopes of the plots (𝐼𝐹𝐿 𝐴𝐹𝐿⁄ versus 𝐼𝑆𝑖𝑁𝐶 𝐴𝑆𝑖𝑁𝐶⁄ ), where 𝐼 is the integrated PL intensity (500−850 nm), 𝐴 is absorbance at the excitation wavelength, and 𝑛 is the refractive index of the solvent (1.334). (This set of data is shown in Appendix C.6.) 𝛷𝑆𝑖𝑁𝐶 = 𝛷𝐹𝐿𝐼𝑆𝑖𝑁𝐶𝐴𝑆𝑖𝑁𝐶𝐴𝐹𝐿𝐼𝐹𝐿𝑛𝑆𝑖𝑁𝐶2𝑛𝐹𝐿2 (4.1) 172 4.5.15 Calculation of FRET parameters The Förster distances, 𝑅0 (in nm), for each FRET pair was calculated using Eqn. 4.2, where the 𝜅2 = 2/3 was the assumed orientation factor, 𝛷𝐷 was the quantum yield of the donor, 𝑛 (=1.334) was the refractive index of the solvent, and 𝐽 was the spectral overlap integral of a FRET pair. The 𝐽 (in mol–1 cm–1 nm4) was calculated using Eqn. S3, where λ was the wavelength in nm, and 𝐼𝐷(𝜆) was the PL intensity of the donor as a function of wavelength, and 𝜀𝐴 (in M–1 cm–1) was the molar absorbance coefficient of the FRET acceptor as a function of wavelength. The 𝐽(𝜆) (in mol–1 cm–1 nm4) was the spectral overlap function (Eqn. 4.4). 𝑅0 = 0.02108(𝜅2𝛷𝐷𝑛−4𝐽)1 6⁄ (4.2) 𝐽 =∫ 𝐼𝐷(𝜆)𝜀𝐴(𝜆)𝜆4𝑑𝜆∫ 𝐼𝐷(𝜆)𝑑𝜆 (4.3) 𝐽(𝜆) =𝐼𝐷(𝜆)𝜀𝐴(𝜆)𝜆4∫ 𝐼𝐷(𝜆)𝑑𝜆 (4.4) 4.5.16 Post-hoc correction of SiNC concentrations The number of equivalents added to an ensemble that results in ≥ 1 BHQ per SiNC can be modeled using Poisson statistics. From first principles, the most efficient ET possible is full quenching of the PL of a single SiNC with one proximal BHQ dye molecule. With this assumption, the minimum number of equivalents of dye per SiNC that would yield the measured ET efficiency in each sample was modeled, then average to a single correction factor (6.7-fold) that was applied to the nominal number of equivalents of dye. 173 Chapter 5: QD-Based cFRET Probes for Extracellular Sensing in Hydrogel This chapter includes unpublished work. Prof. W. R. Algar proposed the concept. I designed and performed the experiments, analyzed the data, and wrote the chapter with input and final editing from Prof. W. R. Algar. 5.1 Introduction In vitro cell culture is an important technique for biological studies that provides well-controlled environments for investigating basic cell biology, for the production of vaccines and proteins, and for drug discovery and development.167,168 Conventional 2D cell culture provides a non-physiological environment that could cause aberrant cellular behaviours.77,169,170 The limitations of 2D cell culture include, but are not limited to, cells being grown on a high-stiffness surfaces (e.g. plastic or glass) instead of soft environments like extracellular matrices (ECMs), cell adhesion and migration being restricted in x-y plane without cell-ECM and cell-cell interactions in the z dimension, and cell microenvironments lacking the gradients in nutrients or oxygen that occur in the tissue.77,169,170 As an alternative to 2D cell culture, hydrogels are used to mimic ECMs for 3D cell culture.77 Performing cell studies in a more physiological-like environment is expected to provide better predictions for in vivo experiments. Since the ECM is a network that gives structure and biochemical support to cells, 3D cell culture in hydrogel is especially useful for studying cellular processes that are related to or influenced by their ECM. Matrix metalloproteinases (MMPs) and a disintegrin and metalloproteinases (ADAMs) are two families of enzymes that are essential in remodelling the 3D structure of the in vivo ECM.171–173 It 174 is known that invasive cancer cells overexpress MMPs174–178 and/or ADAMs,173,175,179,180 which are associated with ECM degradation, promotion of tumour growth, and metastasis. The investigation of MMPs and ADAMs expressions/activities secreted from cells in a 3D cell culture system has the potential to provide more representative and predictive results for in vivo experiments, especially for certain classes of invasive cancer cells. Many techniques have been developed for the detection of enzyme expression and activity (e.g. gene expression analysis, zymography, and immunochemical assays).181 However, these techniques require extensive processing steps before results are obtained and do not provide insight into the real-time spatial and temporal localization of proteases and their activities. The introduction of sensors inside a hydrogel for 3D cell culture would provide this capability and avoid complicated sample processing. cFRET probes are a promising candidate for this task because of their multiplexed sensing advantages. Their surface area and capacity for bioconjugation should also allow them to be integrated as a structural component of the hydrogel. PEGs are synthetic, hydrophilic, and biocompatible polymers that have been widely used in biological and biomaterial applications such as nanoparticle functionalization,182–184 drug delivery,184–186 implantable medical devices,187,188 and tissue engineering.186,189 The hydrophilicity of PEGs enables to hold water within PEG-based hydrogels and the wide range of molecular weights and possible terminal functional groups allow these polymers to form versatile hydrogels with various bioconjugation and crosslinking methods to mimic the tissue microenvironments. In this chapter, PEG-based hydrogel was prepared, QD-based cFRET probes were incorporated, and the PL emission of those cFRET probes was investigated. To show the potential for QD-based 175 cFRET probes to detect enzyme activity in a hydrogel, trypsin-sensitive, QD-based FRET probes were tested and found to be responsive. Future work will focus on detection of MMP and ADAM activity in hydrogels using QD-based cFRET probes, building up to sensing of extracellular protease activity associated with 3D cell culture models. 5.2 Results and discussion 5.2.1 Strategy Figure 5.1 illustrates the proposed cFRET hydrogel design for the detection of protease activity. The PEG-based hydrogel is used as a mimic ECM for 3D cell culture. The embedded QD-based cFRET probes help crosslink the gel and are also used for detecting MMPs, ADAMs, or other types of protease secreted from cells growing within the hydrogel. Figure 5.1 QD-based cFRET probes in the hydrogel for detecting protease activities secreted from cell (not to scale). The illustration is inspired by ref.190 For experiments, the emitters in the QD-based cFRET probe were green-emitting QDs (CdSeS/ZnS), Alexa Fluor 555 (A555) dye, and Atto594 (At594) dye. In this cFRET configuration, 176 the QD had two functions: a central scaffold and the initial point of excitation and FRET donor. The A555 and At594—which were obtained with a maleimide group for labelling peptide substrates via thioether bond formation at C-terminal cysteine residues—were used as nominal acceptors in the cFRET configuration. The dye-labelled peptide substrates had an N-terminal polyhistidine sequence to enable spontaneous binding to the central QD via metal-affinity coordination. For understanding the energy transfer network between donor and acceptors, the QDs were assembled with different equivalents of dye-labelled peptide substrates. As in previous chapters, the shorthand notation used for permutations of the cFRET configurations is (M, N), where M and N represent the average number of equivalents of A555 and At594 dyes per QD. The PEG-based hydrogel consisted of 4-arm-PEG (MW ~20 000) and linear-PEG (MW ~3500).181,191,192 Cycloaddition click chemistry between norbornene (NB) and tetrazine (Tz), or between trans-cyclooctene (TCO) and Tz, are used for cross-linking. More specifically, 4-arm-PEG with terminal norbornene group on each arm (4ARM-PEG-NB) was crosslinked into a 3D network by using linear-PEG that had Tz groups at both ends (linear-PEG-Tz). This coupling chemistry has fast kinetics and uses bioorthogonal reactive groups, which would not influence cell metabolism during cell culture.193 In order to integrate and immobilize the cFRET probes into the hydrogel scaffold, the QD was functionalized with non-substrate peptides that were distally labelled with a TCO group. Multiple TCO-labelled peptides were assembled on each QD, enabling the QDs to play a similar role to 4ARM-PEG-NB. The overall construction is shown in Figure 5.2. 177 Figure 5.2 Hydrogel precursors and hydrogel: (i) 4ARM-PEG-NB, (ii) linear-PEG-Tz, (iii) QD-based cFRET probes, and (iv) hydrogel after casting via cycloaddition click chemistry. Not to scale. 5.2.2 Hydrogel casting 4ARM-PEG-NB and linear-PEG-Tz were used for casting hydrogels in poly(propylene) microcentrifuge tubes. Figure 5.3 shows two hydrogels embedding (0, 0) and (0, 10) probes under white light and UV light. Each QD was assembled with an average of 4 copies of TCO-labelled peptides (sequence in Table 5.1). The green emission from the hydrogel with the (0, 0) probe is due to the green-emitting QDs, and the red emission from the hydrogel with (0, 10) probes arises from energy transfer from the QD to At594 (and possibly some direct excitation of At594 under UV light). The homogeneous PL revealed that QDs were uniformly distributed throughout the entire hydrogel without any macroscopic aggregation. Subsequent microscopic imaging (vide infra) also did not show any aggregates. Nevertheless, to gain more information related to the distribution of the QD-based cFRET probes in a hydrogel, higher resolution techniques should be utilized in 178 future work (e.g. z-stack fluorescent imaging by confocal microscopy, cryogenic scanning electron microscopy). Figure 5.3 Hydrogels functionalized with (0, 0) probes (left) and (0, 10) probes (right). (A) Under white light. (B) Under UV light (356 nm). The scale bars are 0.5 cm. Note: the peptides were a chymotrypsin substrate labelled with a TCO group and the same chymotrypsin substrate labelled with At594. For the final application, it is anticipated that different sequences of peptide would be used for FRET-based sensing of proteolysis and for integration with the hydrogel structure. 5.2.3 QD-based cFRET probes in hydrogel To characterize the energy transfer of the cFRET probes in hydrogels, PL emission spectra were measured for each (M, N) cFRET probe and compared between bulk solution and hydrogel environments. The configuration permutations had M and N = 0, 2, 5, or 8. The probes in solution and hydrogel were each assembled with 6 copies of TCO-labelled peptide (Table 5.1). Figure 5.4A shows the PL emission spectra of the cFRET probes in solution. In general, the FRET-sensitized A555 PL intensity increased as M increased and decreased as N increased. The intensity of the FRET-sensitized At594 PL signal increased with increases in the value of both M and N. The qualitative trends agreed with the expectations for the three energy transfer pathways: QD-to-A555, QD-to-At594, and A555-to-At594. Notably, the PL intensity of cFRET probes in hydrogel 179 was much lower than the probe in solution, which suggested that the hydrogel caused some quenching of the QD PL and/or an inner-filter effect from light scattering. Figure 5.4 The emission spectra of (M, N) cFRET probes. (A) In borate buffer. (B) In hydrogel (immersed in borate buffer). In panels A and B, M and N = 0, 2, 5, and 8. PL ratios were used for analyses to eliminate artefacts and systemic biases that might affect the measurement of absolute PL intensity values. The trends in PL ratio (crosstalk corrected) between solution and hydrogels are qualitatively correlated but are not equivalent (Figure 5.5 A−B). Differences might have arisen from differential quenching of the QD or dyes within the hydrogel matrix. The hydrogel environment has the potential to increase or decrease the probability of different non-radiative relaxation pathways. It is also worth noting that the PL intensity of the QD-based probes in the hydrogel were “photoactivated,” with the PL intensity increasing as the time 180 of exposure time to the excitation increased. Such photobrightening of QDs is known in the literature,194,195 but it is not clear why photobrightening behaviour would be so much more pronounced in the hydrogel versus bulk solution. The underlying causes of these observations are likely complex, and a detailed photophysical characterization (e.g. PL lifetime, quantum yield, anisotropy) will be required in future work to full understand the behaviour. Figure 5.5C−D shows that the combination of the two PL ratios is unique for each (M, N) permutation (16 resolved data points) in solution and hydrogel, which confirms the excepted cFRET utility for independent and quantitative analysis of hydrolysis of both substrates and thus two proteases. Figure 5.5 The PL ratios of cFRET probes. (A) IA555/IQD in borate buffer (hollow dots and dash line) and hydrogel (solid dots and solid line). (B) IAt594/IQD in borate buffer (hollow dots and dash line) and hydrogel (solid dots and solid line). (C) Plot showing unique PL ratios combinations for each (M, N) permutation in solution. (D) Plot showing unique PL ratio combinations for each (M, N) permutation in hydrogel. 181 5.2.4 Proteolysis kinetics in hydrogel Proteolysis kinetics in bulk solution are a useful baseline for comparison to kinetics in a hydrogel. To this end, an average of 12 copies of A555-labelled trypsin substrates were assembled on each QD, represented as (12, 0). The protease-catalyzed substrate hydrolysis reaction was tracked in real-time by measuring changes in FRET, quantified as a A555/QD PL ratio measured at the peak emission wavelength of each emitter. The A555-labelled trypsin substrates were hydrolyzed by the trypsin to produce two peptide fragments. The non-labelled peptide fragments remained bound to the QDs, while the A555-labelled fragments diffused away from the QDs, leading to a decrease in PL ratios with loss of FRET over time (Figure 5.6A). Single-phase progress curves were obtained, and the curves were convergent (Figure 5.6B). This form of progress curve was expected for a glutathione (GSH) surface chemistry on the QDs because it is a pseudo-zwitterionic ligand that tempers protein non-specific adsorption.108,196 Figure 5.6 Enzyme kinetics in solution. (A) Scheme (not to scale) illustrating the QD-based FRET probe for detecting trypsin, where the trypsin cleaves the A555-labelled peptide substrate from the QD with loss of FRET. (B)The trypsin substrate-based (12, 0) probes were dispersed in borate buffer for detecting trypsin. The PL intensities of were measured over time via a plate reader. 182 To investigate proteolysis kinetics in hydrogels, the hydrogels with (6, 0) probes were cast in a 96-well plate. After casting the gels, borate buffer was added into the wells to wash and swell the hydrogel, and then trypsin was directly spiked into the wells as a supernatant on top of the gels. Changes in PL ratio in the hydrogel were measured through multicolour fluorescence microscopy. QD and A555 PL intensities were measured at different regions of interest. Figure 5.7A (time = 0 min) shows higher PL intensity in the peripheral area because of capillarity effects (i.e. meniscus) leading to a higher amount of gel precursors near the edges of the wells during gel casting. The PL intensity in the A555 filter channel decreased while the intensity in the QD filter channel increased as time progressed—as expected for tryptic hydrolysis of the A555-labelled peptide with loss of FRET. Meanwhile, the spectra were measured via a CCD spectrometer connected to the microscope by an optical fibre. Figure 5.7B shows the spectra changing over time after the addition of trypsin. The intensities of QD and A555 peaks progressively increase and decrease, respectively, as expected and consistent with the images. 183 Figure 5.7 Enzyme kinetics in hydrogel. (A) Images of (6, 0) probes with ~100 nM TRP in hydrogel. Excitation filter: 405±10 nm, QD channel emission filter: 525±20 nm, A555 channel emission filter: 565±15 nm. The scale bars are 0.5 mm. (B) Spectra of (6, 0) probes with ~100 nM TRP in hydrogel. (C) Progress curves of (6, 0) probes with different TRP concentrations. In panels A−C, each (6, 0) probe has 6 copies of TCO-labelled peptide for immobilization in hydrogel. The progress curves show that the proteolytic rate in the hydrogel was slower than in solution. Trypsin (60 nM) took less than 5 min completely hydrolyze the cFRET probes (~20 substrates per trypsin) in bulk solution, but 75 nM trypsin in the hydrogel did not finish hydrolysis (~10 substrates 184 per trypsin) even after 1 h. The hydrogel scaffold possibly induces steric hindrance to accessing the peptide substrates on each QD, and steric hindrance for protease diffusion between QDs. Moreover, in bulk solution, both the QD and protease are able to diffuse, whereas only the latter can diffuse in the hydrogel. This latter point was especially relevant to the design of this experiment, as protease had to diffuse from bulk solution into the hydrogel. These limitations are likely an intrinsic property of hydrogel systems and not dissimilar to the real ECM microenvironment. Some optimizations of the design of the hydrogel and QD conjugate may improve kinetics, but proteolysis rates are unlikely to ever match those observed in bulk solution. In the present case, enzyme introduction into the hydrogel is diffusion-limited, which is difficult to compare with enzyme secretion from encapsulated in vitro cells. Diffusion limitations could be partially addressed in ongoing proof of concept experiments by directly injecting enzymes into the 3D matrix. 5.3 Conclusions The PEG-based hydrogel was successfully cast using bioorthogonal click chemistry (NB and Tz), and QD-based FRET or cFRET probes were integrated into the hydrogel via the same type of click chemistry (TCO and Tz). The FRET probes were able to track the proteolytic activity of trypsin within these hydrogels in real time. Investigation and optimization of in-gel photophysics and proteolysis rates are directions for further study, as in in-gel demonstration of multiplexed protease activity sensing via cFRET. In the long term, the optimized cFRET hydrogel are anticipated to be useful for measuring the activity of MMP and ADAM proteases secreted from breast cancer cells grown in 3D culture within the hydrogels. 185 5.4 Experimental 5.4.1 Materials and instruments Alkyl-coated CdSeS/ZnS QDs were from Cytodiagnostics (Burlington, ON, Canada). Alexa Fluor 555 C2 maleimide, ethylenediaminetetraacetic acid (EDTA), sodium phosphate monobasic anhydrous (NaH2PO4), sodium phosphate dibasic heptahydrate (Na2HPO4·7H2O) and sodium chloride (NaCl) were from Thermo-Fisher Scientific (Burlington, ON, Canada). Atto 594 maleimide was from Sigma-Aldrich (Oakville, ON, Canada). Peptides (Table 5.1) were from Bio-Synthesis, Inc. (Lewisville, TX, USA). PEGs were from JenKem Technology (Plano, TX, USA). Sodium tetraborate decahydrate was from Amresco (Boise, ID, USA). Nickel(II) nitrilotriacetic acid agarose was from Qiagen (Toronto, ON, Canada). Amberchrom CG-300 resin was from Dow Chemical (Midland, MI, USA). Trypsin (TRP; ≥ 10000 BAEE units/mg protein; EC number: 3.4.21.4) and other chemicals were from Sigma-Aldrich (Oakville, ON, Canada). Borate buffers (BBs) and phosphate buffer saline (PBS) were prepared and sterilized by filtration (0.22 μm pore-size filter). UV-visible absorption spectra and solution-phase PL spectra (including solution-phase protease assays) were measured with an Infinite M1000 Pro multifunction plate reader (Tecan Ltd., Morrisville, NC, USA) using a transparent half-area 96-well plate (# 3679; Corning, Corning, NY, USA). PL emission from hydrogels was imaged on an IX83 inverted epifluorescence microscope (Olympus, Richmond Hill, ON, Canada) equipped with an X-Cite 120XL metal-halide light source (Excelitas Technologies, Mississauga, ON, Canada), an Orca-Flash 4.0 V2 scientific complementary metal-oxide-semiconductor (sCMOS) camera (C11440; Hamamatsu Photonics, Hamamatsu, SZK, Japan), and MetaMorph/MetaFluor software (Molecular Devices, Sunnyvale, 186 CA, USA). Emission spectra from hydrogels (including gel-phase protease assays) were measured with a GreenWave 16 VIS-50 portable CCD spectrometer (StellarNet, Tampa, FL, USA). Table 5.1 Peptide sequences. Name Sequence (N-terminal to C-terminal)d,e PepTRP-A555a HHHHHHSPPPPPPSGQGEGEGNSGR↓GGSGNGC-A555 PepEK-At594b HHHHHHSPPPPPPSGQGEGGNSDDDDK↓SGNGC-At594 PepChT-TCOc HHHHHHSPPPPPPSGQGEGEGNSAAYASGNGC-TCO a PepTRP indicates the peptide can be digested by trypsin. b PepEK indicates the peptide can be digested by enterokinase. c PepChT indicates the peptide can be digested by chymotrypsin. d The down arrow indicates the hydrolysis site of the peptide. e The residues in bold indicates the recognition sequence for enterokinase. 187 5.4.2 Synthesis of 4ARM-PEG-NB Scheme 5.1 The method for the synthesis of 4ARM-PEG-NB. (A) Synthesis of dinorbornene anhydride. (B) Modify 4ARM-PEG-OH with NB group on each arm. 4ARM-PEG-NB was synthesized from 4ARM-PEG-OH (MW ~20 000 g/mol) as described previously.181,192 Briefly, 5-norbornene-2-carboxylic acid (0.3316 g, 2.4 mmol) was first converted to dinorbornene anhydride using N,N’-diisopropylcarbodiimide (DIC, 185.8 μL, 1.2 mmol) in 5 mL dichloromethane (DCM) at room temperature for 1 h. 4ARM-PEG-OH (2.0 g, ~0.1 mmol) was dried under vacuum at 50 °C overnight. The dried 4ARM-PEG-OH was mixed with pyridine (2 mmol, 161.8 μL), 4-dimethylamino pyridine (DMAP, 0.2 mol, 24.4 mg), and DCM (10 mL), Then transferred into 4ARM-PEG-OH, and the reaction was reacted overnight at room temperature under nitrogen. The product was filtered, collected, and dried under vacuum. The product was then washed with ether and again dried under vacuum. 4ARM-PEG-NB was dissolved in deionized water and further purified using a dialysis membrane (3.5 kDa molecular weight cut-off) against deionized water. The dialyzed solution was dried under vacuum and characterized by thin layer chromatography: 10:1 (v/v) CHCl3:MeOH, Rf (4ARM-PEG-OH)=0.2−0.3, Rf (4ARM-PEG-NB)=0.2−0.4 on TLC plates stained with iodine. 1H NMR (400 MHz, CDCl3) δ 6.18−5.93 (m, 2H 188 per arm), 4.24−4.16 (m, 2H per arm), 3.81−3.40 (m, ~452H per arm). Using the integration of ethylene glycol protons as a reference, roughly 80% of hydroxyl groups were converted to norbornene. 5.4.3 Synthesis of linear-PEG-Tz Linear-PEG-NH2 (MW ~3500 g/mol, ~17.1 mg, 1 equiv.) was dissolved in DCM (1.8 mL). Tz-NHS/DMSO (200 uL, 2.5 equiv.) and N,N-diisopropylethylamine (20 μL) were added and the reaction was left overnight at room temperature. The reaction mixture was dried under vacuum. Crude product was dissolved in deionized water and filtered through a 0.22 μm syringe filter (PES membrane), and dialyzed (2 kDa molecular weight cut-off) against 10% v/v DMSO and deionized water to purify. The internal solution was dried under vacuum. 5.4.4 Peptide labelled with A555/At594/TCO The peptides with terminal cysteine residues were labelled with maleimide functionalized A555, At594, or TCO as described previously.197 The trypsin (TRP) peptide substate is labelled with A555 for trypsin sensing. The enterokinase (EK) peptide substrate is labelled with At594 for enterokinase sensing. The chymotrypsin (ChT) peptide substrate is labelled with TCO for crosslink with hydrogel and the peptide is resistant to digestion with the existence of trypsin or enterokinase. For preparing PepTRP-A555, ~0.33 mg (~104 nmol, 1 equiv.) of peptide was dissolved in 25 μL of 50% v/v acetonitrile (aq) and diluted with 250 μL phosphate buffer saline (PBS; 2 mM NaH2PO4, 8 mM Na2HPO4, 154 mM NaCl, pH 7.4). The peptide was then mixed with reactive A555 (2 equiv.), dissolved in 25 μL DMSO, and left in the dark at room temperature overnight. The 189 peptides were purified with a nickel (II) nitrilotriacetic acid (Ni-NTA) agarose gel and desalted with an Amberchrom CG-300 resin as described previously.197 The purified peptides were quantified spectrophotometrically (molar absorption coefficient is 158 000 M−1 cm−1 at 556 nm), dried in vacuo, and stored at −20 ○C. Similar synthetic procedures were used for labelling of PepEK-At594 and PepChT-TCO, where the scales of the reactions were 40−250 nmol of peptide. The same purification procedure was used for purifying all the labelled peptides. The molar absorption coefficient of PepEK-At594 is 120 000 M−1 cm−1 at 603 nm. The molar absorption coefficient of PepChT-TCO is 1420 M−1 cm−1 at 280 nm, where 1280 and 140 M−1 cm−1 are contributed from the peptide and TCO group, respectively. 5.4.5 QD-based FRET and cFRET probe preparation GSH-coated QDs were prepared as described previously.60 Briefly, alkyl-coated QDs (10 μL, ~10 μM) were diluted with 990 μL chloroform to a final concentration of 0.1 μM. In another microcentrifuge tube, 80 mg GSH were dissolved in 300 μL of 25 wt% tetramethylammonium hydroxide (TMAH) in methanol. The GSH/TMAH solution was mixed with the QDs solution and stored in the dark at room temperature overnight. 200 μL of borate buffer with salt (BB1; 50 mM borate, 250 mM NaCl, pH 9.2) was added to the QD solution. The organic layer was discarded and 750 μL ethanol was added. The solution was centrifuged at 4800 RCF for 1−3 min and the supernatant was discarded. The purification step was repeated three times and the QDs was then re-dispersed QDs in borate buffer (BB2; 50 mM borate, pH 9.2), and quantified spectrophotometrically. 190 Dye labelled peptides (20 nmol) were first dissolved in 20 μL of 50% v/v acetonitrile (aq), diluted with 180 μL borate buffer (BB3; 50 mM borate, pH 8.5), and then quantified spectrophotometrically. GSH-coated QDs were mixed with peptides and diluted with borate buffer with QDs to final concentrations were 1.13−2.25 μM. If more than one kind of peptides was needed to assemble on QDs, all the peptides were mixed together first, then assembled on QDs. Samples were ready to use after a 2−5 h peptide assembly period. 5.4.6 Enzyme kinetics in solution TRP was dissolved in 1.0 mM HCl at final concentrations of ~84 μM. The approximate concentration of enzyme was determined spectrophotometrically (molar absorption coefficient 35 000 M−1 cm−1 at 280 nm), and BB3 was used to dilute enzyme to the desired concentrations (120, 60, 20, and 10 nM). The QDs-based FRET probes were diluted with BB3 to a final concentration of 0.2 μM. The QD solution was aliquoted (35 μL) into each microplate well. Different concentrations of enzyme solutions (35 µL) were added into each well containing QDs and the samples were measured immediately. The samples were excited at 405 nm, and emission was detected at 525 and 565 nm over time. The spectral bandwidth was 5 nm in all cases. 5.4.7 Embedding QD-based cFRET probes in hydrogel In a microcentrifuge tube, the following were added and mixed: 9 mM EDTA (1.5 μL in BB3), 4ARM-PEG-NB (~9.3 mM in H2O, ~19 wt% , 3 μL), and linear-PEG-Tz (~13.5 mM in H2O, ~5% w/w, 3 μL). After mixing, QD-based FRET or cFRET probes were added (6 μL, 1.13 μM) and immediately mixed again. This hydrogel precursor mixture (11 µL) was transferred into a well of 191 a half-area 96-well plate as soon as possible. The hydrogel was cast overnight at room temperature and protected from light. Before using the hydrogel, BB3 (100 µL) was added to swell the hydrogel for 15 min, and the hydrogel was washed with 3×100 μL of BB3. Hydrogels were then immersed in 50−100 μL of BB3. 5.4.8 Emission spectra of QD-based cFRET probes in solution and hydrogel The prepared cFRET probes were diluted with BB3 to a final concentration of 0.5 µM and 11 µL of the diluted solution was transferred into a half-area 96-well plate. The casted hydrogel samples were swelled and washed with BB3, and then immersed in 50 μL of BB3. The hydrogel samples were photoactivated by continuously illuminating them with the excitation light (vide infra) for 2−3 min immediately prior to measuring emission spectra. The spectra of the QD-based cFRET probes were measured via a CCD spectrometer connected to the microscope with an optical fibre. The excitation filter was 440 ± 10 nm (centre ± half-width of transmission) and the emission filter was 470 nm long pass. The CCD spectrometer integration times were 250 and 2000 ms for solution and hydrogel samples, respectively. 5.4.9 Enzyme kinetics in hydrogel The hydrogels were prepared using the same method as Section 5.4.7, except that the concentration of the (6, 0) probes was 2.25 μM. Trypsin was dissolved in 1.0 mM HCl at final concentrations of ~84 μM. The approximate concentration of enzyme was determined spectrophotometrically and BB3 was used to dilute the enzyme to the desired concentration (200, 150, and 60 nM). The hydrogel was immersed in 50 μL of BB3, and trypsin (50 µL) was added to the well and mixed. 192 Images were collected over time (Excitation filter: 405 ± 10 nm, QD channel emission filter: 525 ± 20 nm, A555 channel emission filter: 565 ± 15 nm). 5.4.10 Calculation of PL Ratios PL ratios were calculated according to Eqns. 5.1–5.5, where 𝐼𝜆 is the PL intensity measured from an emission spectrum at wavelength λ nm. 𝐼𝑋 is the PL intensity of each emitter, where X is QD, A555, or At594. These emitters were the primary contributors to emission measured at 525, 564, and 628 nm, respectively. Crosstalk coefficients, which account for minor contributions from other emitters at these wavelengths, were defined from PL emission spectra. They were formulated as percentage of the peak emission intensity for an emitter and denoted as 𝜎𝑋−𝜆 , indicating the contribution of emitter X at λ nm. Specific correction coefficients were 𝜎𝑄𝐷−564 = 0.053 and 𝜎𝐴555−628 = 0.127 for cFRET probes in solution, and 𝜎𝑄𝐷−564 = 0.151 and 𝜎𝐴555−628 = 0.216 for cFRET probes in hydrogel. The collected emission spectra or signals were blank subtracted (or baseline corrected) prior to calculate PL ratios. 𝐼𝑄𝐷 = 𝐼525 (5.1) 𝐼𝐴555 = 𝐼564 − 𝜎𝑄𝐷−564𝐼𝑄𝐷 (5.2) 𝐼𝐴𝑡594 = 𝐼628 − 𝜎𝐴555−628𝐼𝐴555 (5.3) 𝜌𝐴555 𝑄𝐷⁄ = 𝐼𝐴555 𝐼𝑄𝐷⁄ (5.4) 𝜌𝐴𝑡594 𝑄𝐷⁄ = 𝐼𝐴𝑡594 𝐼𝑄𝐷⁄ (5.5) Note: In the progress curves for the enzyme kinetics in solution (Figure 5.6), the PL intensities of the QD and A555 were measured at 525 and 565 nm, respectively. The specific crosstalk correction 193 coefficients were 𝜎𝑄𝐷−565 = 0.051. In the progress curves for the enzyme kinetics in hydrogel (Figure 5.7C), the PL intensities of QD, and A555 were measured at 525 ± 20 and 565 ± 15 nm, respectively. The crosstalk correction coefficient was 𝜎𝑄𝐷−565 = 0.090. 194 Chapter 6: Conclusions and Future Work 6.1 Conclusions Although different photoluminescent materials were used in each chapter of this thesis, and each chapter had a different focus, the goal of all the research was to broaden the scope of cFRET probes toward biological applications. Chapter 2 developed the first QD-free cFRET configuration. A Tb-labelled dendrimer was used as a donor and scaffold to replace the role of metal chalcogenide QD in the archetypical cFRET configuration, and oligonucleotides were hybridized with complementary sequences labelled with three different fluorescent dyes to establish an ET network characteristic of cFRET. The Tb-dendrimer probes and the ET network, were characterized physically and photophysically. Chapter 3 demonstrated the capability of the Tb-labelled dendrimer-based cFRET probes for quantitative, triply multiplexed detection of target DNA. The long-lived Tb signals enabled time-gated PL measurements to reject background signals in serum. Time-gated measurements of a Tb- dendrimer FRET probe signals were also possible using a smartphone-based device. These chapters expand the toolbox of cFRET probes for biological applications, offering the benefits of the PL properties of Tb and avoid the potential compositional concern of cadmium chalcogenide QD-based cFRET probes. Chapter 4 explored the possibility of a FRET configuration based on SiNCs. These materials were characterized via spectroelectrophoresis and both time-resolved and time-gated spectroscopies. ET was investigated between the SiNCs (as donors) and series of dyes (as acceptors) with different 195 degree of FRET-relevant spectral overlap. ET was observed, and consistent with a Förster mechanism within the limitations of the study; however, the polydispersity of the SiNCs presented challenges for quantitative analysis of the ET and for downstream applications. cFRET with SiNCs is unlikely to be viable until synthetic methodology can produce more monodisperse materials. Nevertheless, the research built up important foundational knowledge toward developing SiNC-based FRET probes for biological applications, where the PL properties of SiNCs may yet prove advantageous for select applications. Chapter 5 developed chemistry for integrating metal chalcogenide QD based cFRET probes within hydrogels as a structural component. The PL properties and ET network of the cFRET probes was compared between bulk solution and the hydrogel environment. Although the measured PL ratios changed between environments, the critical ability to correlate a set of two PL ratios with a specific combination of numbers of the two acceptor dye types per QD was retained. A simple proof-of-concept for sensing of protease activity within the hydrogel was also achieved. These preliminary results suggest that multiplexed sensing using QD-based cFRET probes structurally integrated with hydrogels should be possible. 6.2 Unfinished business In Chapter 5, the preliminary results were a step toward the application of cFRET probes for multiplexed sensing of protease activity associated with 3D cultured cells. However, the system still needs to be optimized to improve the brightness of the QDs in the hydrogel matrix and for cFRET sensing within a hydrogel. Potential optimization methods and next steps are discussed in the sub-sections below. 196 6.2.1 Optimizing QD PL in hydrogels A significant challenge was apparent quenching of QD PL within the hydrogel environment. Since the QD is the initial donor, quenching affects the downstream ET and acceptor dye PL emission, with potential loss of sensitivity or even function. The precise reason for quenching of QD PL within the hydrogel is unclear and experiments (e.g. PL lifetime measurements) should be done to unambiguously distinguish between true quenching and inner filter effects (e.g. attenuation of incident excitation light and emitted PL). Nevertheless, two potential approaches to addressing the PL quenching are described below. First, the QD could be coated with PEG-based ligands rather than GSH ligands. PEG-DHLA-coated QDs were used in a previous study, and such an obvious decrease in PL intensity was not observed.86,108 Perhaps the PEG-based ligands will function as a mediator between solution and hydrogel, such that QDs will experience less dramatic environmental change when incorporated into a hydrogel, which might help to maintain the PL intensity. More drastically, replacement of hydrophilic ligand surface chemistry on the QDs with encapsulation of as-synthesized hydrophobic QDs within an amphiphilic polymer may also avoid quenching.198,199 This approach better isolates the QDs from the surrounding environment and is well known to produce brighter QDs, but would require redesign of the peptide conjugation strategy for downstream sensing of protease activity. A second approach that may reduce quenching of QD PL is increasing the relative amount of 4-ARM-PEG-NB (decreasing the relative amount of linear-Tz) or otherwise changing the gel 197 crosslinking chemistry. Any unreacted Tz groups might cause quenching of QDs since the Tz has an absorption bad around 520 nm that overlaps with the emission of green-emitting QDs. Different ratios of 4ARM-PEG-NB and linear-PEG-Tz ratio may minimize inner filter effects or energy transfer associated with the Tz absorption. If the ratio of 4ARM-PEG-NB and linear-PEG-Tz needs to be kept constant, any excess Tz might be made non-absorbing by treating the gel with free NB or TCO groups after casting. Another potential solution is using different crosslinking chemistry, such as dibenzocyclooctyne (DBCO) and azide click chemistry,200–202 which does not absorb light in the visible range. 6.2.2 Proteolysis and cFRET sensing within a hydrogel Trypsin was used as a model protease to demonstrate detection with a QD-based FRET probe integrated within a hydrogel. Although useful for proof of concept, trypsin is not a protease that will generally be of interest for secretion from cells. MMPs and ADAMs are of much greater relevance. To detect MMPs and ADAMs secreted from cells in a hydrogel system, the next steps are (i) finding optimal peptide substrates, (ii) characterizing the responses of a QD-based cFRET probe to MMPs and ADAMs in a hydrogel, (iii) optimizing assay conditions, (iv) growing cells in the hydrogel system, and (v) measuring the activity of MMP and ADAM proteases secreted (or not) from different cells, both in the presence and in the absence of inhibitors. For step (i), MDA-MB-231 breast cancer cell is an invasive cell line, which has been reported to overexpress MMPs 1, 2, 3, 7, 9, and 13176,178 and ADAMs 8, 10, and 17203–205 for metastasis. SK-198 BR-3 is a non-invasive cell line that does not overexpress MMPs and ADAMs and would be useful as a control cell line. Table 6.1 lists potential peptide sequences for different MMPs and ADAMs. The peptide substrate sequences should be carefully designed for high specific activities with the target proteases. In addition to the protease recognition sequences within the peptides, the polyhistidine tails of peptide sequences are useful for assembly to QDs through metal-affinity coordination; the polyproline segments are putative helical spacers for separating the recognition site from QD surface; the remaining glutamine, glycine, and serine residues will confer aqueous solubility and limit the formation of secondary structure; and the C-terminal cysteine is useful as labelling site for fluorescent acceptor dyes. Table 6.1 Peptide sequence for MMPs and ADAMs substrates. Name Sequence (N- to C-terminal)a MMP 3 subtrate206 HHHHHHSPPPPPSQGSQGRPKPVE↓(Nva)WRGCb MMP 13 subtrate207 HHHHHHSPPPPPSQGSQGSQGPLG↓MRGLGC ADAM 8 subtrate208 HHHHHHSPPPPPSNGSNGGHGDQMA↓QKSGC ADAM 17 subtrate209,210 HHHHHHSPPPPPSQGSQGEHADLLA↓VVAAGC a The down arrow indicates the hydrolysis site of the peptide. The residues in bold indicates the recognitions for the corresponding proteases. b Nva: Norvaline residue. For step (iii), performing cell culture in the hydrogel system may require additional modifications. Synthetic hydrogels lack many of the molecular cues of a genuine biological environment, so certain functionalization might be required for promoting cell growth. For example, the arginylglycylaspartic acid (RGD) peptide sequence,181,192,211 which is widely present within ECM proteins, is a binding site for interacting with cell membrane proteins (integrins) and is responsible for cell adhesion. To introduce the RGD peptide sequence into the synthetic hydrogel system, 199 polyhistidine-tagged RGD peptides can be introduced to QD surface via the same method as other dye-labelled peptide substrates, and RGD peptides can be modified with Tz for linking to the gel itself. After the testing and optimization, MBA-MD-231 and SKBR3 cell lines are expected to be cultured in the optimized hydrogel systems separately, and the PL ratios of the cFRET probes within the gel will be monitored over time by collecting fluorescence microscope images and/or emission spectra. 6.3 Future work Compared to conventional FRET probes in the form of a discrete donor-acceptor pair, cFRET configurations are more complex. Although there have been fundamental studies alongside proofs of concept for sensing,50,120 more research is needed to fully understand cFRET systems, their optimization, and their limitations. Also, as a more novel format, cFRET probes have yet to be developed for the scope for biological applications as conventional FRET probes. Future work should focus on addressing these deficiencies. Some ideas, both general and as next steps to the chapters in this thesis, are described in the sub-sections below. 6.3.1 Single-particle studies All of the cFRET configurations in this thesis and in previous studies were characterized and applied at ensemble-level.50–52,86,87 Such measurements reveal average behaviour without considering heterogeneity between individual cFRET probes. Single-particle PL imaging and measurements will be able to reveal this heterogeneity, as well as the temporal dynamics of ET. 200 The best initial systems for these studies will be archetypical CdSe/ZnS QD-based cFRET configurations because of their higher brightness and faster radiative rate versus Tb, the good resistance of the QD to photobleaching, and the non-zero polydispersity of the QDs. In addition to gaining better fundamental understanding of cFRET, these studies will be an important first step toward realizing the untapped potential of cFRET probes for single-vector multiplexed sensing at the single-particle level, with super-resolution capability. 6.3.2 Developing additional cFRET probes with alternative materials As mentioned earlier, cFRET is a design motif and the initial donor is not necessarily limited to QD or Tb-labelled dendrimer. Evaluating more materials in the initial donor and/or scaffold role(s) will help the scope of cFRET probes grow to accommodate a wider range of experimental and measurement conditions, and biological applications. Although a variety of molecular and nanoparticulate photoluminescent materials are available, finding the right combination of properties for the initial donor and scaffold for cFRET is not a trivial thing. For example, compared to QDs or lanthanide complexes, most of the photoluminescent materials have spectrally broader emission bands, which could cause problematic crosstalk that requires complicated data analysis or even loss of the correlation between PL ratios and numbers of each type of acceptor. In addition, having compatible surface chemistry and conjugation chemistries is also important since the reactants used for synthesis might cause changes in photophysical properties of PL emitters, and because control over the number and linkage of each type of acceptor is essential for the sensing function of cFRET. 201 One strategy for exploring new materials for cFRET is to replace the dual donor-scaffold role of cadmium chalcogenide QDs in the archetypical configuration with another photoluminescent nanoparticle. From Chapter 4, it is evident that the heterogeneously broadened emission of SiNCs is not suitable for developing cFRET configurations; however, the small size, anticipated biocompatibility, and long-lived PL decay (similar to Tb) are attractive properties of SiNCs. It will be worth revisiting the idea SiNC-based cFRET configuration when SiNCs with more spectrally narrow PL emission are available. In terms of bioconjugation, it will be good to continue with the SiNCs utilized in Chapter 4 (i.e. SiNC 1) or SiNCs with a similar surface chemistry. The surface carboxylate groups can potentially useful for conjugating with amine-terminated oligonucleotides or peptides through carbodiimide activation. However, the steric hindrance from the alkyl and PEG chains might significantly lower the bioconjugation efficiency, such that shorter PEG chains or carboxyl-terminated PEG chains (instead of alkyl chains) may be preferred. Alternatively, upconversion nanoparticles (UCNPs) are another potential candidate. UCNPs are excited with near-infrared light and have long-lived PL decay properties are favourable for minimizing background fluorescence and increasing signal-to-background ratio.10,212 The multiple narrow emission peaks are good for multiplexed sensing paired with multiple acceptors without crosstalk problem. Moreover, UCNPs have been utilized as FRET donors for biosensing,212–214 The potential challenge with UCNPs is that only the lanthanide ions nearest to the particle surface are within range of conjugated acceptors to engage in FRET, such that there may be a substantial amount of unquenched lanthanide emission. It is unclear whether the foregoing will hinder quantitative analysis via unique PL ratios, but otherwise UCNPs are a promising candidate for cFRET configurations. Figure 6.1 shows a potential approach for constructing a UCNP-based 202 cFRET probe. Relatively small NaYF4:Yb3+, Er3+ UCNPs (~24 nm in diameter) coated with PAA are used as the starting material. A PAA coating is preferred to silica shell, since PAA-coated UCNPs have better performance in biosensing, as investigated previously.215 The surface carboxylate groups will be converted into azide groups through carbodiimide coupling with N3-PEG3-amine. Cycloaddition click chemistry between azide and DBCO groups will then be used for bioconjugation. Similar to Chapter 2 and 3, DBCO modified probe-strand oligonucleotides will be pre-hybridized with dye-labelled block-strand oligonucleotides. (The azide and DBCO modifications of UCNPs and oligonucleotides, respectively, are interchangeable in principle; however, DBCO is hydrophobic, which might reduce the colloidal stability of UCNPs when multiple copies are attached.) A555, Cyanine 3.5 (Cy3.5), and Cy5.5 (or A647) are the potential cFRET acceptor combination for NaYF4:Yb3+, Er3+ UCNPs. Figure 6.1 Proposed strategy for developing a UCNP-based cFRET probe (not to scale). PAA-coated NaYF4:Yb3+, Er3+ UCNPs are modified with azide groups through carbodiimide coupling. Then, click chemistry between azide and DBCO groups is used for bioconjugation to introduce dye-labelled pre-hybridized oligonucleotides. Note: the click chemistry is not limited to the azide-DBCO pair (e.g. the Tz-TCO pair is also a potential conjugation method). A second strategy for exploring new materials for cFRET, similar to the Tb-labelled dendrimers in Chapters 2 and 3, is having the central scaffolds and initial donor as two different materials. 203 This strategy provides more flexibility for choosing both scaffolds and emitters, which opens the door to a wide array of materials for developing cFRET probes. For example, other types of hydrophilic dendrimers, hyperbranched polyglycerol, and star-like DNA structures are potential scaffolds for replacing PAMAM dendrimers in a configuration with Tb donors. Virus-like nanoparticles (VLPs) are another possibility for an alternative scaffold. VLPs are assembled from protein units without genetic materials. The structures are well-defined and have perfect monodispersity.216 The surface chemistry is defined by the exposed amino acid residues and their positions on the surface, and these residues can be controlled via genetic engineering. Common conjugation chemistries have been used for modifying VLPs,217 suggesting that VLPs are a promising scaffold material. Figure 6.2 shows a potential approach for constructing a Tb-labelled VLP-based cFRET probe. Small and wild-type icosahedral VLPs (25−35 nm in diameter, e.g. brome mosaic virus (BMV), cowpea chlorotic mottle virus (CCMV), MS2, or Qβ capsids) are potential starting materials. The surface lysine resides will be used for introducing Tb complexes and azide groups through NHS ester chemistry. Similar to what was described for the prospective UCNP cFRET probe, cycloaddition click chemistry will be used for conjugation of pre-hybridized oligonucleotides (DBCO-modified probe strand and dye-labelled block strand). A555, A546, and Cy5 are the potential cFRET acceptors for Tb-labelled VLPs. For improving the colloidal stability of VLPs and reducing non-specific adsorption, PEG chains could be grafted onto lysine side chains or N-termini via NHS ester chemistry, or onto cysteine side chains via maleimide chemistry. Instead of modifying azide groups on VLPs, amber codon suppression has been used in protein expression to directly express protein with non-natural azide residues.218 204 Figure 6.2 Proposed strategy for developing Tb-labelled VLP-based cFRET probe (not to scale). The wild type VLPs are modified with Tb complexes and azide groups through NHS ester chemistry. Click chemistry between azide and DBCO groups is used to conjugate dye-labelled pre-hybridized oligonucleotides. Note: the click chemistry is not limited to azide-DBCO pair (e.g. the Tz-TCO pair is also a potential conjugation method). 6.4 Closing remarks This thesis has presented a range of research that contribute to broadening the scope of cFRET as a tool for bioanalysis and imaging. The chapters include materials characterization, spectroscopic studies, and applications in this context. The results have shown new approaches to be possible, revealed important considerations for materials selection, and informed directions for future research. It thus advances the development of cFRET as new and more powerful tool for bioanalysis and imaging, and is thus an important contribution to science at the nexus between materials, physical, biological, and analytical chemistry. 205 References (1) Valeur, B.; Berberan‐Santos, M. N. Introduction. In Molecular Fluorescence: Principles and Applications; Wiley-VCH Verlag GmbH & Co. KGaA, 2012; pp 1–30. (2) Gauglitz, G.; Moore, D. S. Inductively Coupled Plasma Spectrometry. In Handbook of Spectroscopy: Second, Enlarged Edition; Wiley‐VCH Verlag GmbH & Co. KGaA, 2014; pp 583–645. (3) Valeur, B.; Berberan‐Santos, M. N. Characteristics of Fluorescence Emission. In Molecular Fluorescence: Principles and Applications; Wiley-VCH Verlag GmbH & Co. KGaA, 2012; pp 53–74. (4) Valeur, B.; Berberan‐Santos, M. N. Absorption of Ultraviolet, Visible, and Near‐Infrared Radiation. In Molecular Fluorescence: Principles and Applications; Wiley-VCH Verlag GmbH & Co. KGaA, 2012; pp 31–51. (5) Lakowicz, J. R. Introduction to Fluorescence. In Principles of Fluorescence Spectroscopy; Springer New York, NY, 2006; pp 1–25. (6) Brightness of A Laser Dye. IUPAC Gold Book, 2014. https://goldbook.iupac.org/terms/ view/BT07338 (accessed 2023-01). (7) Wong, K.-L.; Bünzli, J.-C. G.; Tanner, P. A. Quantum Yield and Brightness. J. Lumin. 2020, 224, 117256. (8) James, D. R.; Siemiarczuk, A.; Ware, W. R. Stroboscopic Optical Boxcar Technique for the Determination of Fluorescence Lifetimes. Rev. Sci. Instrum. 1992, 63, 1710. (9) Massey, M.; Ancona, M. G.; Medintz, I. L.; Algar, W. R. Time-Gated DNA Photonic Wires with Förster Resonance Energy Transfer Cascades Initiated by a Luminescent Terbium Donor. ACS Photonics 2015, 2, 639–652. 206 (10) Algar, W. R.; Massey, M.; Rees, K.; Higgins, R.; Krause, K. D.; Darwish, G. H.; Peveler, W. J.; Xiao, Z.; Tsai, H.-Y.; Gupta, R.; et al. Photoluminescent Nanoparticles for Chemical and Biological Analysis and Imaging. Chem. Rev. 2021, 121, 9243–9358. (11) Colas, K.; Doloczki, S.; Posada Urrutia, M.; Dyrager, C. Prevalent Bioimaging Scaffolds: Synthesis, Photophysical Properties and Applications. Eur. J. Org. Chem. 2021, 2021, 2133–2144. (12) Massey, M.; Wu, M.; Conroy, E. M.; Algar, W. R. Mind Your P’s and Q’s: The Coming of Age of Semiconducting Polymer Dots and Semiconductor Quantum Dots in Biological Applications. Curr. Opin. Biotechnol. 2015, 34, 30–40. (13) Gao, Z.; Hao, Y.; Zheng, M.; Chen, Y. A Fluorescent Dye with Large Stokes Shift and High Stability: Synthesis and Application to Live Cell Imaging. RSC Adv. 2017, 7, 7604–7609. (14) Ren, T.-B.; Xu, W.; Zhang, W.; Zhang, X.-X.; Wang, Z.-Y.; Xiang, Z.; Yuan, L.; Zhang, X.-B. A General Method To Increase Stokes Shift by Introducing Alternating Vibronic Structures. J. Am. Chem. Soc. 2018, 140, 7716–7722. (15) Algar, W. R. Heroes or Villains? How Nontraditional Luminescent Materials Do and Do Not Enhance Bioanalysis and Imaging. Chem. Mater. 2020, 32, 4863–4883. (16) Debnath, G. H.; Mukherjee, P.; Waldeck, D. H. Optimizing the Key Variables to Generate Host Sensitized Lanthanide Doped Semiconductor Nanoparticle Luminophores. J. Phys. Chem. C 2020, 124, 26495–26517. (17) Sabbatini, N.; Guardigli, M.; Lehn, J.-M. Luminescent Lanthanide Complexes as Photochemical Supramolecular Devices. Coord. Chem. Rev. 1993, 123, 201–228. (18) Lis, S.; Kimura, T.; Yoshida, Z. Luminescence Lifetime of Lanthanide(III) Ions in Aqueous Solution Containing Azide Ion. J. Alloys Compd. 2001, 323–324, 125–127. (19) Bünzli, J.-C. G.; Piguet, C. Taking Advantage of Luminescent Lanthanide Ions. Chem. Soc. Rev. 2005, 34, 1048–1077. 207 (20) Algar, W. R.; Kim, H.; Medintz, I. L.; Hildebrandt, N. Emerging Non-Traditional Förster Resonance Energy Transfer Configurations with Semiconductor Quantum Dots: Investigations and Applications. Coord. Chem. Rev. 2014, 263–264, 65–85. (21) Hildebrandt, N.; Wegner, K. D.; Algar, W. R. Luminescent Terbium Complexes: Superior Förster Resonance Energy Transfer Donors for Flexible and Sensitive Multiplexed Biosensing. Coord. Chem. Rev. 2014, 273–274, 125–138. (22) Vuojola, J.; Soukka, T. Luminescent Lanthanide Reporters: New Concepts for Use in Bioanalytical Applications. Methods Appl. Fluoresc. 2014, 2, 012001. (23) Lakowicz, J. R. Fluorophores. In Principles of Fluorescence Spectroscopy; Springer New York, NY, 2006; pp 63–95. (24) Murphy, C. J. Optical Sensing with Quantum Dots. Anal. Chem. 2002, 74, 520 A–526 A. (25) Zillner, E.; Fengler, S.; Niyamakom, P.; Rauscher, F.; Köhler, K.; Dittrich, T. Role of Ligand Exchange at CdSe Quantum Dot Layers for Charge Separation. J. Phys. Chem. C 2012, 116, 16747–16754. (26) Petryayeva, E.; Algar, W. R.; Medintz, I. L. Quantum Dots in Bioanalysis: A Review of Applications across Various Platforms for Fluorescence Spectroscopy and Imaging. Appl. Spectrosc. 2013, 67, 215–252. (27) Algar, W. R.; Susumu, K.; Delehanty, J. B.; Medintz, I. L. Semiconductor Quantum Dots in Bioanalysis: Crossing the Valley of Death. Anal. Chem. 2011, 83, 8826–8837. (28) Cheng, X.; Lowe, S. B.; Reece, P. J.; Gooding, J. J. Colloidal Silicon Quantum Dots: From Preparation to the Modification of Self-Assembled Monolayers (SAMs) for Bio-Applications. Chem. Soc. Rev. 2014, 43, 2680–2700. (29) McVey, B. F. P.; Tilley, R. D. Solution Synthesis, Optical Properties, and Bioimaging Applications of Silicon Nanocrystals. Acc. Chem. Res. 2014, 47, 3045–3051. 208 (30) Dasog, M.; Kehrle, J.; Rieger, B.; Veinot, J. G. C. Silicon Nanocrystals and Silicon-Polymer Hybrids: Synthesis, Surface Engineering, and Applications. Angew. Chem., Int. Ed. 2016, 55, 2322–2339. (31) McVey, B. F. P.; Prabakar, S.; Gooding, J. J.; Tilley, R. D. Solution Synthesis, Surface Passivation, Optical Properties, Biomedical Applications, and Cytotoxicity of Silicon and Germanium Nanocrystals. ChemPlusChem 2017, 82, 60–73. (32) Clark, R. J.; Aghajamali, M.; Gonzalez, C. M.; Hadidi, L.; Islam, M. A.; Javadi, M.; Mobarok, M. H.; Purkait, T. K.; Robidillo, C. J. T.; Sinelnikov, R.; et al. From Hydrogen Silsesquioxane to Functionalized Silicon Nanocrystals. Chem. Mater. 2017, 29, 80–89. (33) Fan, J.; Chu, P. K. Group IV Nanoparticles: Synthesis, Properties, and Biological Applications. Small 2010, 6, 2080–2098. (34) Sun, W.; Qian, C.; Chen, K. K.; Ozin, G. A. Silicon Nanocrystals: It’s Simply a Matter of Size. ChemNanoMat 2016, 2, 847–855. (35) Rosso-Vasic, M.; Spruijt, E.; van Lagen, B.; De Cola, L.; Zuilhof, H. Alkyl-Functionalized Oxide-Free Silicon Nanoparticles: Synthesis and Optical Properties. Small 2008, 4, 1835–1841. (36) Kitasako, T.; Saitow, K. Si Quantum Dots with a High Absorption Coefficient: Analysis Based on Both Intensive and Extensive Variables. Appl. Phys. Lett. 2013, 103, 151912. (37) Yu, Y.; Hessel, C. M.; Bogart, T. D.; Panthani, M. G.; Rasch, M. R.; Korgel, B. A. Room Temperature Hydrosilylation of Silicon Nanocrystals with Bifunctional Terminal Alkenes. Langmuir 2013, 29, 1533–1540. (38) Robidillo, C. J. T.; Islam, M. A.; Aghajamali, M.; Faramus, A.; Sinelnikov, R.; Zhang, X.; Boekhoven, J.; Veinot, J. G. C. Functional Bioinorganic Hybrids from Enzymes and Luminescent Silicon-Based Nanoparticles. Langmuir 2018, 34, 6556–6569. 209 (39) Robidillo, C. J. T.; Aghajamali, M.; Faramus, A.; Sinelnikov, R.; Veinot, J. G. C. Interfacing Enzymes with Silicon Nanocrystals through the Thiol–Ene Reaction. Nanoscale 2018, 10, 18706–18719. (40) Hildebrandt, N.; Spillmann, C. M.; Algar, W. R.; Pons, T.; Stewart, M. H.; Oh, E.; Susumu, K.; Díaz, S. A.; Delehanty, J. B.; Medintz, I. L. Energy Transfer with Semiconductor Quantum Dot Bioconjugates: A Versatile Platform for Biosensing, Energy Harvesting, and Other Developing Applications. Chem. Rev. 2017, 117, 536–711. (41) Algar, W. R.; Hildebrandt, N.; Vogel, S. S.; Medintz, I. L. FRET as a Biomolecular Research Tool — Understanding Its Potential While Avoiding Pitfalls. Nat. Methods 2019, 16, 815–829. (42) Lakowicz, J. R. Energy Transfer. In Principles of Fluorescence Spectroscopy; Springer New York, NY, 2006; pp 443–476. (43) Clegg, R. M. The History of FRET. In Reviews in Fluorescence 2006; Springer New York, NY: Boston, MA, 2006; Vol. 2006, pp 1–45. (44) van der Meer, B. W. Fӧrster Theory. In FRET - Förster Resonance Energy Transfer: From Theory to Applications; Wiley-VCH Verlag GmbH & Co. KGaA, 2013; pp 23–62. (45) Medintz, I. L.; Clapp, A. R.; Mattoussi, H.; Goldman, E. R.; Fisher, B.; Mauro, J. M. Self-Assembled Nanoscale Biosensors Based on Quantum Dot FRET Donors. Nat. Mater. 2003, 2, 630–638. (46) Kawahara, S.; Uchimaru, T.; Murata, S. Sequential Multistep Energy Transfer: Enhancement of Efficiency of Long-Range Fluorescence Resonance Energy Transfer. Chem. Commun. 1999, No. 6, 563–564. (47) Ohya, Y.; Yabuki, K.; Hashimoto, M.; Nakajima, A.; Ouchi, T. Multistep Fluorescence Resonance Energy Transfer in Sequential Chromophore Array Constructed on Oligo-DNA Assemblies. Bioconjugate Chem. 2003, 14, 1057–1066. 210 (48) Heilemann, M.; Tinnefeld, P.; Mosteiro, G. S.; Parajo, M. G.; Van Hulst, N. F.; Sauer, M. Multistep Energy Transfer in Single Molecular Photonic Wires. J. Am. Chem. Soc. 2004, 126, 6514–6515. (49) Tsai, H.-Y.; Kim, H.; Massey, M.; Krause, K. D.; Algar, W. R. Concentric FRET: A Review of the Emerging Concept, Theory, and Applications. Methods Appl. Fluoresc. 2019, 7, 42001. (50) Massey, M.; Kim, H.; Conroy, E. M.; Algar, W. R. Expanded Quantum Dot-Based Concentric Förster Resonance Energy Transfer: Adding and Characterizing Energy-Transfer Pathways for Triply Multiplexed Biosensing. J. Phys. Chem. C 2017, 121, 13345–13356. (51) Algar, W. R.; Ancona, M. G.; Malanoski, A. P.; Susumu, K.; Medintz, I. L. Assembly of a Concentric Förster Resonance Energy Transfer Relay on a Quantum Dot Scaffold: Characterization and Application to Multiplexed Protease Sensing. ACS Nano 2012, 6, 11044–11058. (52) Li, J. J.; Algar, W. R. A Long-Wavelength Quantum Dot-Concentric FRET Configuration: Characterization and Application in a Multiplexed Hybridization Assay. Analyst 2016, 141, 3636–3647. (53) Lim, S. J.; Zahid, M. U.; Le, P.; Ma, L.; Entenberg, D.; Harney, A. S.; Condeelis, J.; Smith, A. M. Brightness-Equalized Quantum Dots. Nat. Commun. 2015, 6, 8210. (54) Panchuk-Voloshina, N.; Haugland, R. P.; Bishop-Stewart, J.; Bhalgat, M. K.; Millard, P. J.; Mao, F.; Leung, W.-Y.; Haugland, R. P. Alexa Dyes, a Series of New Fluorescent Dyes That Yield Exceptionally Bright, Photostable Conjugates. J. Histochem. Cytochem. 1999, 47, 1179–1188. (55) Swiecicki, J.-M.; Thiebaut, F.; Di Pisa, M.; Gourdin-Bertin, S.; Tailhades, J.; Mansuy, C.; Burlina, F.; Chwetzoff, S.; Trugnan, G.; Chassaing, G.; et al. How to Unveil Self-Quenched 211 Fluorophores and Subsequently Map the Subcellular Distribution of Exogenous Peptides. Sci. Rep. 2016, 6, 20237. (56) Chen, W.; Young, L. J.; Lu, M.; Zaccone, A.; Strohl, F.; Yu, N.; Schierle, G. S. K.; Kaminski, C. F. Fluorescence Self-Quenching from Reporter Dyes Informs on the Structural Properties of Amyloid Clusters Formed in Vitro and in Cells. Nano Lett. 2017, 17, 143–149. (57) Szabó, Á .; Szendi-Szatmári, T.; Ujlaky-Nagy, L.; Rádi, I.; Vereb, G.; Szöllősi, J.; Nagy, P. The Effect of Fluorophore Conjugation on Antibody Affinity and the Photophysical Properties of Dyes. Biophys. J. 2018, 114, 688–700. (58) Algar, W. R.; Massey, M.; Krull, U. J. Semiconductor Quantum Dots and FRET. In FRET - Förster Resonance Energy Transfer: From Theory to Applications; Wiley-VCH Verlag GmbH & Co. KGaA, 2013; pp 475–605. (59) Algar, W. R.; Malonoski, A.; Deschamps, J. R.; Blanco-Canosa, J. B.; Susumu, K.; Stewart, M. H.; Johnson, B. J.; Dawson, P. E.; Medintz, I. L. Proteolytic Activity at Quantum Dot-Conjugates: Kinetic Analysis Reveals Enhanced Enzyme Activity and Localized Interfacial “Hopping.” Nano Lett. 2012, 12, 3793–3802. (60) Wu, M.; Petryayeva, E.; Medintz, I. L.; Algar, W. R. Quantitative Measurement of Proteolytic Rates and Förster Resonance Energy Transfer. In Quantum Dots: Applications in Biology; Humana Press, New York, NY, 2014; Vol. 1199, pp 215–239. (61) Menjoge, A. R.; Kannan, R. M.; Tomalia, D. A. Dendrimer-Based Drug and Imaging Conjugates: Design Considerations for Nanomedical Applications. Drug Discovery Today 2010, 15, 171–185. (62) Mintzer, M. A.; Grinstaff, M. W. Biomedical Applications of Dendrimers: A Tutorial. Chem. Soc. Rev. 2011, 40, 173–190. 212 (63) Hsu, H.-J.; Bugno, J.; Lee, S.-R.; Hong, S. Dendrimer-Based Nanocarriers: A Versatile Platform for Drug Delivery. Wiley Interdiscip. Rev.: Nanomed. Nanobiotechnol. 2017, 9, e1409. (64) Sepúlveda-Crespo, D.; Gómez, R.; DeLa Mata, F. J.; Jiménez, J. L.; Muñoz-Fernández, M. Á . Polyanionic Carbosilane Dendrimer-Conjugated Antiviral Drugs as Efficient Microbicides: Recent Trends and Developments in HIV Treatment/Therapy. Nanomed.: Nanotechnol. Biol. Med. 2015, 11, 1481–1498. (65) Jackson, C. L.; Chanzy, H. D.; Booy, F. P.; Drake, B. J.; Tomalia, D. A.; Bauer, B. J.; Amis, E. J. Visualization of Dendrimer Molecules by Transmission Electron Microscopy (TEM): Staining Methods and Cryo-TEM of Vitrified Solutions. Macromolecules 1998, 31, 6259–6265. (66) PAMAM Dendrimers. Dendritech Inc., 2018. https://www.dendritech.com/pamam.html (accessed 2019-10). (67) Maiti, P. K.; Çaǧin, T.; Lin, S.-T.; Goddard, W. A. Effect of Solvent and pH on the Structure of PAMAM Dendrimers. Macromolecules 2005, 38, 979–991. (68) Sherje, A. P.; Jadhav, M.; Dravyakar, B. R.; Kadam, D. Dendrimers: A Versatile Nanocarrier for Drug Delivery and Targeting. Int. J. Pharm. 2018, 548, 707–720. (69) Chauhan, A. S. Dendrimers for Drug Delivery. Molecules 2018, 23, 938. (70) Santos, A.; Veiga, F.; Figueiras, A. Dendrimers as Pharmaceutical Excipients: Synthesis, Properties, Toxicity and Biomedical Applications. Materials 2020, 13, 65. (71) Lesniak, W. G.; Mishra, M. K.; Jyoti, A.; Balakrishnan, B.; Zhang, F.; Nance, E.; Romero, R.; Kannan, S.; Kannan, R. M. Biodistribution of Fluorescently Labeled PAMAM Dendrimers in Neonatal Rabbits: Effect of Neuroinflammation. Mol. Pharm. 2013, 10, 4560–4571. 213 (72) Kesharwani, P.; Jain, K.; Jain, N. K. Dendrimer as Nanocarrier for Drug Delivery. Prog. Polym. Sci. 2014, 39, 268–307. (73) Li, J.; Liang, H.; Liu, J.; Wang, Z. Poly(amidoamine) (PAMAM) Dendrimer Mediated Delivery of Drug and PDNA/SiRNA for Cancer Therapy. Int. J. Pharm. 2018, 546, 215–225. (74) Caliari, S. R.; Burdick, J. A. A Practical Guide to Hydrogels for Cell Culture. Nat. Methods 2016, 13, 405–414. (75) Madduma-Bandarage, U. S. K.; Madihally, S. V. Synthetic Hydrogels: Synthesis, Novel Trends, and Applications. J. Appl. Polym. Sci. 2021, 138, e50376. (76) Sun, X.; Agate, S.; Salem, K. S.; Lucia, L.; Pal, L. Hydrogel-Based Sensor Networks: Compositions, Properties, and Applications—A Review. ACS Appl. Bio Mater. 2021, 4, 140–162. (77) Tibbitt, M. W.; Anseth, K. S. Hydrogels as Extracellular Matrix Mimics for 3D Cell Culture. Biotechnol. Bioeng. 2009, 103, 655–663. (78) Lowe, S. B.; Tan, V. T. G.; Soeriyadi, A. H.; Davis, T. P.; Gooding, J. J. Synthesis and High-Throughput Processing of Polymeric Hydrogels for 3D Cell Culture. Bioconjugate Chem. 2014, 25, 1581–1601. (79) Dragan, E. S. Design and Applications of Interpenetrating Polymer Network Hydrogels. A Review. Chem. Eng. J. 2014, 243, 572–590. (80) Peppas, N. A.; Slaughter, B.V.; Kanzelberger, M. A. Hydrogels. In Polymer Science: A Comprehensive Reference; Elsevier B.V., 2012; pp 385–395. (81) Weaver, V. M.; Petersen, O. W.; Wang, F.; Larabell, C. A.; Briand, P.; Damsky, C.; Bissell, M. J. Reversion of the Malignant Phenotype of Human Breast Cells in Three-Dimensional Culture and in Vivo by Integrin Blocking Antibodies. J. Cell Biol. 1997, 137, 231–245. 214 (82) Rowland, C. E.; Brown, C. W.; Medintz, I. L.; Delehanty, J. B. Intracellular FRET-Based Probes: A Review. Methods Appl. Fluoresc. 2015, 3, 042006. (83) Quan, K.; Yi, C.; Yang, X.; He, X.; Huang, J.; Wang, K. FRET-Based Nucleic Acid Probes: Basic Designs and Applications in Bioimaging. TrAC, Trends Anal. Chem. 2020, 124, 115784. (84) Hong, S.; Pawel, G. T.; Pei, R.; Lu, Y. Recent Progress in Developing Fluorescent Probes for Imaging Cell Metabolites. Biomed. Mater. 2021, 16, 044108. (85) Algar, W. R.; Ancona, M. G.; Malanoski, A. P.; Susumu, K.; Medintz, I. L. Assembly of a Concentric Förster Resonance Energy Transfer Relay on a Quantum Dot Scaffold: Characterization and Application to Multiplexed Protease Sensing. ACS Nano 2012, 6, 11044–11058. (86) Wu, M.; Petryayeva, E.; Algar, W. R. Quantum Dot-Based Concentric FRET Configuration for the Parallel Detection of Protease Activity and Concentration. Anal. Chem. 2014, 86, 11181–11188. (87) Wu, M.; Algar, W. R. Concentric Förster Resonance Energy Transfer Imaging. Anal. Chem. 2015, 87, 8078–8083. (88) Tsoi, K. M.; Dai, Q.; Alman, B. A.; Chan, W. C. W. Are Quantum Dots Toxic? Exploring the Discrepancy Between Cell Culture and Animal Studies. Acc. Chem. Res. 2013, 46, 662–671. (89) Yong, K.-T.; Law, W.-C.; Hu, R.; Ye, L.; Liu, L.; Swihart, M. T.; Prasad, P. N. Nanotoxicity Assessment of Quantum Dots: From Cellular to Primate Studies. Chem. Soc. Rev. 2013, 42, 1236–1250. (90) Bradburne, C. E.; Delehanty, J. B.; Gemmill, K. B.; Mei, B. C.; Mattoussi, H.; Susumu, K.; Blanco-Canosa, J. B.; Dawson, P. E.; Medintz, I. L. Cytotoxicity of Quantum Dots Used for in Vitro Cellular Labeling: Role of QD Surface Ligand, Delivery Modality, Cell Type, and Direct Comparison to Organic Fluorophores. Bioconjugate Chem. 2013, 24, 1570–1583. 215 (91) Svenson, S.; Tomalia, D. A. Dendrimers in Biomedical Applications—Reflections on the Field. Adv. Drug Delivery Rev. 2012, 64, 102–115. (92) Xu, J.; Corneillie, T. M.; Moore, E. G.; Law, G.-L.; Butlin, N. G.; Raymond, K. N. Octadentate Cages of Tb(III) 2-Hydroxyisophthalamides: A New Standard for Luminescent Lanthanide Labels. J. Am. Chem. Soc. 2011, 133, 19900–19910. (93) Algar, W. R.; Wegner, D.; Huston, A. L.; Blanco-Canosa, J. B.; Stewart, M. H.; Armstrong, A.; Dawson, P. E.; Hildebrandt, N.; Medintz, I. L. Quantum Dots as Simultaneous Acceptors and Donors in Time-Gated Förster Resonance Energy Transfer Relays: Characterization and Biosensing. J. Am. Chem. Soc. 2012, 134, 1876–1891. (94) Green, N. M. Avidin. Adv. Protein Chem. 1975, 29, 85–133. (95) Green, N. M. [5] Avidin and Streptavidin. Methods Enzymol. 1990, 184, 51–67. (96) Jevprasesphant, R.; Penny, J.; Jalal, R.; Attwood, D.; McKeown, N. B.; D’Emanuele, A. The Influence of Surface Modification on the Cytotoxicity of PAMAM Dendrimers. Int. J. Pharm. 2003, 252, 263–266. (97) Jain, K.; Kesharwani, P.; Gupta, U.; Jain, N. K. Dendrimer Toxicity: Let’s Meet the Challenge. Int. J. Pharm. 2010, 394, 122–142. (98) Luong, D.; Kesharwani, P.; Deshmukh, R.; Mohd Amin, M. C. I.; Gupta, U.; Greish, K.; Iyer, A. K. PEGylated PAMAM Dendrimers: Enhancing Efficacy and Mitigating Toxicity for Effective Anticancer Drug and Gene Delivery. Acta Biomater. 2016, 43, 14–29. (99) van der Poll, D. G.; Kieler-Ferguson, H. M.; Floyd, W. C.; Guillaudeu, S. J.; Jerger, K.; Szoka, F. C.; Fréchet, J. M. Design, Synthesis, and Biological Evaluation of a Robust, Biodegradable Dendrimer. Bioconjugate Chem. 2010, 21, 764–773. (100) Wijagkanalan, W.; Kawakami, S.; Hashida, M. Designing Dendrimers for Drug Delivery and Imaging: Pharmacokinetic Considerations. Pharm. Res. 2011, 28, 1500–1519. 216 (101) Twibanire, J. K.; Grindley, T. B. Polyester Dendrimers: Smart Carriers for Drug Delivery. Polymers 2014, 6, 179–213. (102) Huang, D.; Wu, D. Biodegradable Dendrimers for Drug Delivery. Mater. Sci. Eng., C 2018, 90, 713–727. (103) Abbina, S.; Vappala, S.; Kumar, P.; Siren, E. M. J.; La, C. C.; Abbasi, U.; Brooks, D. E.; Kizhakkedathu, J. N. Hyperbranched Polyglycerols: Recent Advances in Synthesis, Biocompatibility and Biomedical Applications. J. Mater. Chem. B 2017, 5, 9249–9277. (104) Buckhout-White, S.; Spillmann, C. M.; Algar, W. R.; Khachatrian, A.; Melinger, J. S.; Goldman, E. R.; Ancona, M. G.; Medintz, I. L. Assembling Programmable FRET-Based Photonic Networks Using Designer DNA Scaffolds. Nat. Commun. 2014, 5, 5615. (105) Brown, C. W.; Buckhout-White, S.; Díaz, S. A.; Melinger, J. S.; Ancona, M. G.; Goldman, E. R.; Medintz, I. L. Evaluating Dye-Labeled DNA Dendrimers for Potential Applications in Molecular Biosensing. ACS Sens. 2017, 2, 401–410. (106) Rosano, C.; Arosio, P.; Bolognesi, M. The X-Ray Three-Dimensional Structure of Avidin. Biomol. Eng. 1999, 16, 5–12. (107) Pons, T.; Uyeda, H. T.; Medintz, I. L.; Mattoussi, H. Hydrodynamic Dimensions, Electrophoretic Mobility, and Stability of Hydrophilic Quantum Dots. J. Phys. Chem. B 2006, 110, 20308–20316. (108) Petryayeva, E.; Jeen, T.; Algar, W. R. Optimization and Changes in the Mode of Proteolytic Turnover of Quantum Dot−Peptide Substrate Conjugates through Moderation of Interfacial Adsorption. ACS Appl. Mater. Interfaces 2017, 9, 30359–30372. (109) Pehlivan, Z. S.; Torabfam, M.; Kurt, H.; Ow-Yang, C.; Hildebrandt, N.; Yüce, M. Aptamer and Nanomaterial Based FRET Biosensors: A Review on Recent Advances (2014–2019). Microchim. Acta 2019, 186, 563. 217 (110) Stanciu, L. A.; Wei, Q.; Barui, A. K.; Mohammad, N. Recent Advances in Aptamer-Based Biosensors for Global Health Applications. Annu. Rev. Biomed. Eng. 2021, 23, 433–459. (111) Liu, L.; Han, Z.; An, F.; Gong, X.; Zhao, C.; Zheng, W.; Mei, L.; Zhou, Q. Aptamer-Based Biosensors for the Diagnosis of Sepsis. J. Nanobiotechnol. 2021, 19, 216. (112) Zhao, Y.; Yavari, K.; Liu, J. Critical Evaluation of Aptamer Binding for Biosensor Designs. TrAC, Trends Anal. Chem. 2022, 146, 116480. (113) Holliger, P.; Hudson, P. J. Engineered Antibody Fragments and the Rise of Single Domains. Nat. Biotechnol. 2005, 23, 1126–1136. (114) Anderson, G. P.; Glaven, R. H.; Algar, W. R.; Susumu, K.; Stewart, M. H.; Medintz, I. L.; Goldman, E. R. Single Domain Antibody–Quantum Dot Conjugates for Ricin Detection by Both Fluoroimmunoassay and Surface Plasmon Resonance. Anal. Chim. Acta 2013, 786, 132–138. (115) Wegner, K. D.; Lindén, S.; Jin, Z.; Jennings, T. L.; el Khoulati, R.; van Bergen en Henegouwen, P. M. P.; Hildebrandt, N. Nanobodies and Nanocrystals: Highly Sensitive Quantum Dot-Based Homogeneous FRET Immunoassay for Serum-Based EGFR Detection. Small 2014, 10, 734–740. (116) Bhuckory, S.; Mattera, L.; Wegner, K. D.; Qiu, X.; Wu, Y.-T.; Charbonnière, L. J.; Reiss, P.; Hildebrandt, N. Direct Conjugation of Antibodies to the ZnS Shell of Quantum Dots for FRET Immunoassays with Low Picomolar Detection Limits. Chem. Commun. 2016, 52, 14423–14425. (117) Gao, S.; Guisán, J. M.; Rocha-Martin, J. Oriented Immobilization of Antibodies onto Sensing Platforms - A Critical Review. Anal. Chim. Acta 2022, 1189, 338907. (118) Wu, Y.-T.; Qiu, X.; Lindbo, S.; Susumu, K.; Medintz, I. L.; Hober, S.; Hildebrandt, N. Quantum Dot–Based FRET Immunoassay for HER2 Using Ultrasmall Affinity Proteins. Small 2018, 14, 1802266. 218 (119) Caputi, A. P.; Navarra, P. Beyond Antibodies: Ankyrins and DARPins. From Basic Research to Drug Approval. Curr. Opin. Pharmacol. 2020, 51, 93–101. (120) Wu, M.; Massey, M.; Petryayeva, E.; Algar, W. R. Energy Transfer Pathways in a Quantum Dot-Based Concentric FRET Configuration. J. Phys. Chem. C 2015, 119, 26183–26195. (121) Geißler, D.; Stufler, S.; Löhmannsröben, H.-G.; Hildebrandt, N. Six-Color Time-Resolved Förster Resonance Energy Transfer for Ultrasensitive Multiplexed Biosensing. J. Am. Chem. Soc. 2013, 135, 1102–1109. (122) Selvin, P. R.; Hearst, J. E. Luminescence Energy Transfer Using a Terbium Chelate: Improvements on Fluorescence Energy Transfer. Proc. Natl. Acad. Sci. U. S. A. 1994, 91, 10024–10028. (123) Qiu, X.; Guo, J.; Jin, Z.; Petreto, A.; Medintz, I. L.; Hildebrandt, N. Multiplexed Nucleic Acid Hybridization Assays Using Single-FRET-Pair Distance-Tuning. Small 2017, 13, 1700332. (124) Qiu, X.; Guo, J.; Xu, J.; Hildebrandt, N. Three-Dimensional FRET Multiplexing for DNA Quantification with Attomolar Detection Limits. J. Phys. Chem. Lett. 2018, 9, 4379–4384. (125) Qiu, X.; Xu, J.; Cardoso Dos Santos, M.; Hildebrandt, N. Multiplexed Biosensing and Bioimaging Using Lanthanide-Based Time-Gated Förster Resonance Energy Transfer. Acc. Chem. Res. 2022, 55, 551–564. (126) Cardoso Dos Santos, M.; Colin, I.; Ribeiro Dos Santos, G.; Susumu, K.; Demarque, M.; Medintz, I. L.; Hildebrandt, N. Time-Gated FRET Nanoprobes for Autofluorescence-Free Long-Term in Vivo Imaging of Developing Zebrafish. Adv. Mater. 2020, 32, 2003912. (127) Troscianko, J.; Stevens, M. Image Calibration and Analysis Toolbox – a Free Software Suite for Objectively Measuring Reflectance, Colour and Pattern. Methods Ecol. Evol. 2015, 6, 1320–1331. 219 (128) Carocci, A.; Catalano, A.; Lauria, G.; Sinicropi, M. S.; Genchi, G. Lead Toxicity, Antioxidant Defense and Environment. In Reviews of Environmental Contamination and Toxicology; Springer, Cham, 2016; Vol. 238, pp 45–67. (129) Genchi, G.; Sinicropi, M. S.; Lauria, G.; Carocci, A.; Catalano, A. The Effects of Cadmium Toxicity. Int. J. Environ. Res. Public Health 2020, 17, 3782. (130) Chen, S.; Chen, Y.; Chen, Y.; Yao, Z. InP/ZnS Quantum Dots Cause Inflammatory Response in Macrophages Through Endoplasmic Reticulum Stress and Oxidative Stress. Int. J. Nanomed. 2019, 14, 9577–9586. (131) Kays, J. C.; Saeboe, A. M.; Toufanian, R.; Kurant, D. E.; Dennis, A. M. Shell-Free Copper Indium Sulfide Quantum Dots Induce Toxicity in Vitro and in Vivo. Nano Lett. 2020, 20, 1980–1991. (132) Huang, X.; Tang, M. Research Advance on Cell Imaging and Cytotoxicity of Different Types of Quantum Dots. J. Appl. Toxicol. 2021, 41, 342–361. (133) Xia, B.; Lin, G.; Zheng, S.; Zhang, H.; Yu, Y. Differential Effects of PEGylated Cd-Free CuInS2/ZnS Quantum Dot (QDs) on Substance P and LL-37 Induced Human Mast Cell Activation. Ecotoxicol. Environ. Saf. 2022, 245, 114108. (134) Derfus, A. M.; Chan, W. C. W.; Bhatia, S. N. Probing the Cytotoxicity of Semiconductor Quantum Dots. Nano Lett. 2004, 4, 11–18. (135) He, Y.; Fan, C.; Lee, S. Silicon Nanostructures for Bioapplications. Nano Today 2010, 5, 282–295. (136) Liu, J.; Erogbogbo, F.; Yong, K.-T.; Ye, L.; Liu, J.; Hu, R.; Chen, H.; Hu, Y.; Yang, Y.; Yang, J.; et al. Assessing Clinical Prospects of Silicon Quantum Dots: Studies in Mice and Monkeys. ACS Nano 2013, 8, 7303–7310. (137) Peng, F.; Su, Y.; Zhong, Y.; Fan, C.; Lee, S.-T.; He, Y. Silicon Nanomaterials Platform for Bioimaging, Biosensing, and Cancer Therapy. Acc. Chem. Res. 2014, 47, 612–623. 220 (138) Gonzalez, C. M.; Veinot, J. G. C. Silicon Nanocrystals for the Development of Sensing Platforms. J. Mater. Chem. C 2016, 4, 4836–4846. (139) Dohnalová, K.; Gregorkiewicz, T.; Kůsová, K. Silicon Quantum Dots: Surface Matters. J. Phys.: Condens. Matter 2014, 26, 173201. (140) Zhou, Z.; Brus, L.; Friesner, R. Electronic Structure and Luminescence of 1.1-and 1.4-nm Silicon Nanocrystals: Oxide Shell versus Hydrogen Passivation. Nano Lett. 2003, 3, 163–167. (141) Rodríguez Núnez, J. R.; Kelly, J. A.; Henderson, E. J.; Veinot, J. G. C. Wavelength-Controlled Etching of Silicon Nanocrystals. Chem. Mater. 2012, 24, 346–352. (142) Lioudakis, E.; Othonos, A.; Nassiopoulou, A. G. Ultrafast Transient Photoinduced Absorption in Silicon Nanocrystals: Coupling of Oxygen-Related States to Quantized Sublevels. Appl. Phys. Lett. 2007, 90, 171103. (143) Dohnalová, K.; Žídek, K.; Ondič, L.; Kůsová, K.; Cibulka, O.; Pelant, I. Optical Gain at the F-Band of Oxidized Silicon Nanocrystals. J. Phys. D: Appl. Phys. 2009, 42, 135102. (144) Mastronardi, M. L.; Maier-Flaig, F.; Faulkner, D.; Henderson, E. J.; Kü, C.; Lemmer, U.; Ozin, G. A. Size-Dependent Absolute Quantum Yields for Size-Separated Colloidally-Stable Silicon Nanocrystals. Nano Lett. 2012, 12, 337–342. (145) Dasog, M.; Yang, Z.; Regli, S.; Atkins, T. M.; Faramus, A.; Singh, M. P.; Muthuswamy, E.; Kauzlarich, S. M.; Tilley, R. D.; Veinot, J. G. C. Chemical Insight into the Origin of Red and Blue Photoluminescence Arising from Freestanding Silicon Nanocrystals. ACS Nano 2013, 7, 2676–2685. (146) Milliken, S.; Thiessen, A. N.; Cheong, I. T.; O’Connor, K. M.; Li, Z.; Hooper, R. W.; Robidillo, C. J. T.; Veinot, J. G. C. “Turning the Dials”: Controlling Synthesis, Structure, Composition, and Surface Chemistry to Tailor Silicon Nanoparticle Properties. Nanoscale 2021, 13, 16365–16820. 221 (147) Islam, M. A.; Sinelnikov, R.; Howlader, M. A.; Faramus, A.; Veinot, J. G. C. Mixed Surface Chemistry: An Approach to Highly Luminescent Biocompatible Amphiphilic Silicon Nanocrystals. Chem. Mater. 2018, 30, 8925–8931. (148) Sarwat, S.; Stapleton, F. J.; Willcox, M. D. P.; O’Mara, P. B.; Tilley, R. D.; Gooding, J. J.; Roy, M. Feasibility of Silicon Quantum Dots as a Biomarker for the Bioimaging of Tear Film. Nanomaterials 2022, 12, 1965. (149) Yang, D.; Cui, Z.; Wen, Z.; Piao, Z.; He, H.; Wei, X.; Wang, L.; Mei, S.; Zhang, W.; Guo, R. Recent Updates on Functionalized Silicon Quantum-Dot-Based Nanoagents for Biomedical Applications. ACS Mater. Lett. 2023, 5, 985–1008. (150) Cheng, X.; McVey, B. F. P.; Robinson, A. B.; Longatte, G.; O’Mara, P. B.; Tan, V. T. G.; Thordarson, P.; Tilley, R. D.; Gaus, K.; Gooding, J. J. Protease Sensing Using Nontoxic Silicon Quantum Dots. J. Biomed. Opt. 2017, 22, 087002. (151) Furuta, K.; Fujii, M.; Sugimoto, H.; Imakita, K. Energy Transfer in Silicon Nanocrystal Solids Made from All-Inorganic Colloidal Silicon Nanocrystals. J. Phys. Chem. Lett. 2015, 6, 2761–2766. (152) Abdelhameed, M.; Aly, S.; Lant, J. T.; Zhang, X.; Charpentier, P. Energy/Electron Transfer Switch for Controlling Optical Properties of Silicon Quantum Dots. Sci. Rep. 2018, 8, 17068. (153) Cao, J.; Zhang, H.; Pi, X.; Li, D.; Yang, D. Enhanced Photoluminescence of Silicon Quantum Dots in the Presence of Both Energy Transfer Enhancement and Emission Enhancement Mechanisms Assisted by the Double Plasmon Modes of Gold Nanorods. Nanoscale Adv. 2021, 3, 4810–4815. (154) Kim, H.; Jeen, T.; Tran, M. V.; Algar, W. R. Polyacrylamide Gel Electrophoresis of Semiconductor Quantum Dots and Their Bioconjugates: Materials Characterization and Physical Insights from Spectrofluorimetric Detection. Analyst 2018, 143, 1104–1116. (155) Krause, K. D.; Tsai, H.-Y.; Rees, K.; Kim, H.; Algar, W. R. Preparation and Characterization of Quantum Dot-Peptide Conjugates Based on Polyhistidine Tags. In 222 Peptide Conjugation: Methods and Protocols; Humana, New York, NY, 2021; Vol. 2355, pp 175–218. (156) Takagahara, T.; Takeda, K. Theory of the Quantum Confinement Effect on Excitons in Quantum Dots of Indirect-Gap Materials. Phys. Rev. B 1992, 46, 15578. (157) Yu, Y.; Fan, G.; Fermi, A.; Mazzaro, R.; Morandi, V.; Ceroni, P.; Smilgies, D.-M.; Korgel, B. A. Size-Dependent Photoluminescence Efficiency of Silicon Nanocrystal Quantum Dots. J. Phys. Chem. C 2017, 121, 23240–23248. (158) Hessel, C. M.; Reid, D.; Panthani, M. G.; Rasch, M. R.; Goodfellow, B. W.; Wei, J.; Fujii, H.; Akhavan, V.; Korgel, B. A. Synthesis of Ligand-Stabilized Silicon Nanocrystals with Size-Dependent Photoluminescence Spanning Visible to Near-Infrared Wavelengths. Chem. Mater. 2012, 24, 393–401. (159) Kovalev, D.; Diener, J.; Heckler, H.; Polisski, G.; Künzner, N.; Koch, F. Optical Absorption Cross Sections of Si Nanocrystals. Phys. Rev. B 2000, 61, 4485–4487. (160) Sychugov, I.; Fucikova, A.; Pevere, F.; Yang, Z.; Veinot, J. G. C.; Linnros, J. Ultranarrow Luminescence Linewidth of Silicon Nanocrystals and Influence of Matrix. ACS Photonics 2014, 1, 998–1005. (161) Pons, T.; Medintz, I. L.; Wang, X.; English, D. S.; Mattoussi, H. Solution-Phase Single Quantum Dot Fluorescence Resonance Energy Transfer. J. Am. Chem. Soc. 2006, 128, 15324–15331. (162) Wilcoxon, J. P.; Samara, G. A.; Provencio, P. N. Optical and Electronic Properties of Si Nanoclusters Synthesized in Inverse Micelles. Phys. Rev. B 1999, 60, 2704–2714. (163) Hua, F.; Swihart, M. T.; Ruckenstein, E. Efficient Surface Grafting of Luminescent Silicon Quantum Dots by Photoinitiated Hydrosilylation. Langmuir 2005, 21, 6054–6062. (164) Mastronardi, M. L.; Hennrich, F.; Henderson, E. J.; Maier-Flaig, F.; Blum, C.; Reichenbach, J.; Lemmer, U.; Wang, D.; Kappes, M. M.; Ozin, G. A. Preparation of Monodisperse Silicon 223 Nanocrystals Using Density Gradient Ultracentrifugation. J. Am. Chem. Soc 2011, 133, 11928–11931. (165) Porrès, L.; Holland, A.; Pålsson, L.-O.; Monkman, A. P.; Kemp, C.; Beeby, A. Absolute Measurements of Photoluminescence Quantum Yields of Solutions Using an Integrating Sphere. J. Fluoresc. 2006, 16, 267–272. (166) Brouwer, A. M. Standards for Photoluminescence Quantum Yield Measurements in Solution (IUPAC Technical Report). Pure Appl. Chem. 2011, 83, 2213–2228. (167) Arango, M.-T.; Quintero-Ronderos, P.; Castiblanco, J.; Montoya-Ortíz, G. Cell Culture and Cell Analysis. In Autoimmunity: From Bench to Bedside; El Rosario University Press, 2013; pp 741–754. (168) Segeritz, C.-P.; Vallier, L. Cell Culture: Growing Cells as Model Systems in Vitro. In Basic Science Methods for Clinical Researchers; Elsevier Inc., 2017; pp 151–172. (169) Baker, B. M.; Chen, C. S. Deconstructing the Third Dimension – How 3D Culture Microenvironments Alter Cellular Cues. J. Cell Sci. 2012, 125, 3015–3024. (170) Barbosa, M. A. G.; Xavier, C. P. R.; Pereira, R. F.; Petrikaitė, V.; Vasconcelos, M. H. 3D Cell Culture Models as Recapitulators of the Tumor Microenvironment for the Screening of Anti-Cancer Drugs. Cancers 2022, 14, 190. (171) Visse, R.; Nagase, H. Matrix Metalloproteinases and Tissue Inhibitors of Metalloproteinases: Structure, Function, and Biochemistry. Circ. Res. 2003, 92, 827–839. (172) Eckhard, U.; Huesgen, P. F.; Schilling, O.; Bellac, C. L.; Butler, G. S.; Cox, J. H.; Dufour, A.; Goebeler, V.; Kappelhoff, R.; Auf dem Keller, U.; et al. Active Site Specificity Profiling of the Matrix Metalloproteinase Family: Proteomic Identification of 4300 Cleavage Sites by Nine MMPs Explored with Structural and Synthetic Peptide Cleavage Analyses. Matrix Biol. 2016, 49, 37–60. 224 (173) Edwards, D. R.; Handsley, M. M.; Pennington, C. J. The ADAM Metalloproteinases. Mol. Aspects Med. 2008, 29, 258–289. (174) Balduyck, M.; Zerimech, F.; Gouyer, V.; Lemaire, R.; Hemon, B.; Grard, G.; Thiebaut, C.; Lemaire, V.; Dacquembronne, E.; Duhem, T.; et al. Specific Expression of Matrix Metalloproteinases 1, 3, 9 and 13 Associated with Invasiveness of Breast Cancer Cells in Vitro. Clin. Exp. Metastasis 2000, 18, 171–178. (175) Chang, C.; Werb, Z. The Many Faces of Metalloproteases: Cell Growth, Invasion, Angiogenesis and Metastasis. Trends Cell Biol. 2001, 11, S37–S43. (176) Paquette, B.; Bisson, M.; Baptiste, C.; Therriault, H.; Lemay, R.; Cantin, A. M. Invasiveness of Breast Cancer Cells MDA-MB-231 through Extracellular Matrix Is Increased by the Estradiol Metabolite 4-Hydroxyestradiol. Int. J. Cancer 2005, 113, 706–711. (177) Stark, A. M.; Anuszkiewicz, B.; Mentlein, R.; Yoneda, T.; Mehdorn, H. M.; Held-Feindt, J. Differential Expression of Matrix Metalloproteinases in Brain- and Bone-Seeking Clones of Metastatic MDA-MB-231 Breast Cancer Cells. J. Neuro-Oncol. 2007, 81, 39–48. (178) Endres, M.; Kneitz, S.; Orth, M. F.; Perera, R. K.; Zernecke, A.; Butt, E. Regulation of Matrix Metalloproteinases (MMPs) Expression and Secretion in MDA-MB-231 Breast Cancer Cells by LIM and SH3 Protein 1 (LASP1). Oncotarget 2016, 7, 64244–64259. (179) Mochizuki, S.; Okada, Y. ADAMs in Cancer Cell Proliferation and Progression. Cancer Sci. 2007, 98, 621–628. (180) Giebeler, N.; Zigrino, P. A Disintegrin and Metalloprotease (ADAM): Historical Overview of Their Functions. Toxins 2016, 8, 122. (181) Leight, J. L.; Alge, D. L.; Maier, A. J.; Anseth, K. S. Direct Measurement of Matrix Metalloproteinase Activity in 3D Cellular Microenvironments Using a Fluorogenic Peptide Substrate. Biomaterials 2013, 34, 7344–7352. 225 (182) Suk, J. S.; Xu, Q.; Kim, N.; Hanes, J.; Ensign, L. M. PEGylation as a Strategy for Improving Nanoparticle-Based Drug and Gene Delivery. Adv. Drug Delivery Rev. 2016, 99, 28–51. (183) Zhang, R.-L.; Pratiwi, F. W.; Chen, B.-C.; Chen, P.; Wu, S.-H.; Mou, C.-Y. Simultaneous Single-Particle Tracking and Dynamic pH Sensing Reveal Lysosome-Targetable Mesoporous Silica Nanoparticle Pathways. ACS Appl. Mater. Interfaces 2020, 12, 42472–42484. (184) Shi, D.; Beasock, D.; Fessler, A.; Szebeni, J.; Ljubimova, J. Y.; Afonin, K. A.; Dobrovolskaia, M. A. To PEGylate or Not to PEGylate: Immunological Properties of Nanomedicine’s Most Popular Component, Polyethylene Glycol and Its Alternatives. Adv. Drug Delivery Rev. 2022, 180, 114079. (185) Shi, L.; Zhang, J.; Zhao, M.; Tang, S.; Cheng, X.; Zhang, W.; Li, W.; Liu, X.; Peng, H.; Wang, Q. Effects of Polyethylene Glycol on the Surface of Nanoparticles for Targeted Drug Delivery. Nanoscale 2021, 13, 10748–10764. (186) Yoon, H. Y.; Lee, D.; Lim, D.-K.; Koo, H.; Kim, K. Copper-Free Click Chemistry: Applications in Drug Delivery, Cell Tracking, and Tissue Engineering. Adv. Mater. 2022, 34, 2107192. (187) Badv, M.; Bayat, F.; Weitz, J. I.; Didar, T. F. Single and Multi-Functional Coating Strategies for Enhancing the Biocompatibility and Tissue Integration of Blood-Contacting Medical Implants. Biomaterials 2020, 258, 120291. (188) Kutner, N.; Kunduru, R. K.; Rizik, L.; Farah, S. Recent Advances for Improving Functionality, Biocompatibility, and Longevity of Implantable Medical Devices and Deliverable Drug Delivery Systems. Adv. Funct. Mater. 2021, 31, 2010929. (189) Xiao, Z.; Zhao, S.; Zhang, X.; Wei, G.; Su, Z. Recent Advances in Peptide Engineering of PEG Hydrogels: Strategies, Functional Regulation, and Biomedical Applications. Macromol. Mater. Eng. 2022, 307, 2200385. 226 (190) Leight, J. L.; Tokuda, E. Y.; Jones, C. E.; Lin, A. J.; Anseth, K. S. Multifunctional Bioscaffolds for 3D Culture of Melanoma Cells Reveal Increased MMP Activity and Migration with BRAF Kinase Inhibition. Proc. Natl. Acad. Sci. U. S. A. 2015, 112, 5366–5371. (191) Fairbanks, B. D.; Schwartz, M. P.; Halevi, A. E.; Nuttelman, C. R.; Bowman, C. N.; Anseth, K. S. A Versatile Synthetic Extracellular Matrix Mimic via Thiol-Norbornene Photopolymerization. Adv. Mater. 2009, 21, 5005–5010. (192) Sridhar, B. V.; Brock, J. L.; Silver, J. S.; Leight, J. L.; Randolph, M. A.; Anseth, K. S. Development of a Cellularly Degradable PEG Hydrogel to Promote Articular Cartilage Extracellular Matrix Deposition. Adv. Healthcare Mater. 2015, 4, 702–713. (193) Jiang, Y.; Chen, J.; Deng, C.; Suuronen, E. J.; Zhong, Z. Click Hydrogels, Microgels and Nanogels: Emerging Platforms for Drug Delivery and Tissue Engineering. Biomaterials 2014, 35, 4969–4985. (194) Wang, Y.; Tang, Z.; Correa-Duarte, M. A.; Pastoriza-Santos, I.; Giersig, M.; Kotov, N. A.; Liz-Marzán, L. M. Mechanism of Strong Luminescence Photoactivation of Citrate-Stabilized Water-Soluble Nanoparticles with CdSe Cores. J. Phys. Chem. B 2004, 108, 15461–15469. (195) Zimnitsky, D.; Jiang, C.; Xu, J.; Lin, Z.; Tsukruk, V. V. Substrate- and Time-Dependent Photoluminescence of Quantum Dots Inside the Ultrathin Polymer LbL Film. Langmuir 2007, 23, 4509–4515. (196) Wu, M.; Algar, W. R. Acceleration of Proteolytic Activity Associated with Selection of Thiol Ligand Coatings on Quantum Dots. ACS Appl. Mater. Interfaces 2015, 7, 2535–2545. (197) Algar, W. R.; Blanco-Canosa, J. B.; Manthe, R. L.; Susumu, K.; Stewart, M. H.; Dawson, P. E.; Medintz, I. L. Synthesizing and Modifying Peptides for Chemoselective Ligation and Assembly into Quantum Dot-Peptide Bioconjugates. In Nanomaterial Interfaces in Biology: Methods and Protocols; Humana Press, Totowa, NJ, 2013; Vol. 1025, pp 47–73. 227 (198) Zhang, F.; Lees, E.; Amin, F.; Rivera_Gil, P.; Yang, F.; Mulvaney, P.; Parak, W. J. Polymer-Coated Nanoparticles: A Universal Tool for Biolabelling Experiments. Small 2011, 7, 3113–3127. (199) Sapsford, K. E.; Algar, W. R.; Berti, L.; Gemmill, K. B.; Casey, B. J.; Oh, E.; Stewart, M. H.; Medintz, I. L. Functionalizing Nanoparticles with Biological Molecules: Developing Chemistries That Facilitate Nanotechnology. Chem. Rev. 2013, 113, 1904–2074. (200) Arkenberg, M. R.; Nguyen, H. D.; Lin, C.-C. Recent Advances in Bio-Orthogonal and Dynamic Crosslinking of Biomimetic Hydrogels. J. Mater. Chem. B 2020, 8, 7835–7855. (201) Li, Y.; Wang, X.; Han, Y.; Sun, H.-Y.; Hilborn, J.; Shi, L. Click Chemistry-Based Biopolymeric Hydrogels for Regenerative Medicine. Biomed. Mater. 2021, 16, 022003. (202) Battigelli, A.; Almeida, B.; Shukla, A. Recent Advances in Bioorthogonal Click Chemistry for Biomedical Applications. Bioconjugate Chem. 2022, 33, 263–271. (203) Romagnoli, M.; Mineva, N. D.; Polmear, M.; Conrad, C.; Srinivasan, S.; Loussouarn, D.; Barillé-Nion, S.; Georgakoudi, I.; Dagg, Á .; Mcdermott, E. W.; et al. ADAM8 Expression in Invasive Breast Cancer Promotes Tumor Dissemination and Metastasis. EMBO Mol. Med. 2014, 6, 278–294. (204) Mullooly, M.; McGowan, P. M.; Kennedy, S. A.; Madden, S. F.; Crown, J.; O’Donovan, N.; Duffy, M. J. ADAM10: A New Player in Breast Cancer Progression? Br. J. Cancer 2015, 113, 945–951. (205) Zheng, X.; Jiang, F.; Katakowski, M.; Zhang, Z. G.; Lu, Q.; Chopp, M. ADAM17 Promotes Breast Cancer Cell Malignant Phenotype through EGFR-PI3K-AKT Activation. Cancer Biol. Ther. 2009, 8, 1045–1054. (206) Nagase, H.; Fields, C. G.; Fields, G. B. Design and Characterization of a Fluorogenic Substrate Selectively Hydrolyzed by Stromelysin 1 (Matrix Metalloproteinase-3). J. Biol. Chem. 1994, 269, 20952–20957. 228 (207) Deng, S.-J.; Bickett, D. M.; Mitchell, J. L.; Lambert, M. H.; Blackburn, R. K.; Luke, C. H.; Neugebaueruer, J.; Pahel, G.; Weiner, M. P.; Moss, M. L. Substrate Specificity of Human Collagenase 3 Assessed Using a Phage-Displayed Peptide Library. J. Biol. Chem. 2000, 275, 31422–31427. (208) Moss, M. L.; Rasmussen, F. H. Fluorescent Substrates for the Proteinases ADAM17, ADAM10, ADAM8, and ADAM12 Useful for High-Throughput Inhibitor Screening. Anal. Biochem. 2007, 366, 144–148. (209) L. Moss, M.; H. Rasmussen, F.; Nudelman, R.; J. Dempsey, P.; Williams, J. Fluorescent Substrates Useful as High Throughput Screening Tools for ADAM9. Comb. Chem. High Throughput Screening 2010, 13, 358–365. (210) Miller, M. A.; Barkal, L.; Jeng, K.; Herrlich, A.; Moss, M.; Griffith, L. G.; Lauffenburger, D. A. Proteolytic Activity Matrix Analysis (PrAMA) for Simultaneous Determination of Multiple Protease Activities. Integr. Biol. 2011, 3, 422–438. (211) Nguyen, E. H.; Zanotelli, M. R.; Schwartz, M. P.; Murphy, W. L. Differential Effects of Cell Adhesion, Modulus and VEGFR-2 Inhibition on Capillary Network Formation in Synthetic Hydrogel Arrays. Biomaterials 2014, 35, 2149–2161. (212) Gnach, A.; Lipinski, T.; Bednarkiewicz, A.; Rybka, J.; Capobianco, J. A. Upconverting Nanoparticles: Assessing the Toxicity. Chem. Soc. Rev. 2015, 44, 1561–1584. (213) Deng, R.; Wang, J.; Chen, R.; Huang, W.; Liu, X. Enabling Förster Resonance Energy Transfer from Large Nanocrystals through Energy Migration. J. Am. Chem. Soc 2016, 138, 15972–15979. (214) Pini, F.; Francés-Soriano, L.; Andrigo, V.; Natile, M. M.; Hildebrandt, N. Optimizing Upconversion Nanoparticles for FRET Biosensing. ACS Nano 2023, 17, 4971–4984. (215) Bhuckory, S.; Lahtinen, S.; Höysniemi, N.; Guo, J.; Qiu, X.; Soukka, T.; Hildebrandt, N. Understanding FRET in Upconversion Nanoparticle Nucleic Acid Biosensors. Nano Lett. 2023, 23, 2253–2261. 229 (216) Schoonen, L.; Maassen, S.; Nolte, R. J. M.; van Hest, J. C. M. Stabilization of a Virus-Like Particle and Its Application as a Nanoreactor at Physiological Conditions. Biomacromolecules 2017, 18, 3492–3497. (217) Hajebi, S.; Yousefiasl, S.; Rahimmanesh, I.; Dahim, A.; Ahmadi, S.; Kadumudi, F. B.; Rahgozar, N.; Amani, S.; Kumar, A.; Kamrani, E.; et al. Genetically Engineered Viral Vectors and Organic-Based Non-Viral Nanocarriers for Drug Delivery Applications. Adv. Healthc. Mater. 2022, 11, 2201583. (218) Vervoort, D. F. M.; Heiringhoff, R.; Timmermans, S. B. P. E.; van Stevendaal, M. H. M. E.; van Hest, J. C. M. Dual Site-Selective Presentation of Functional Handles on Protein-Engineered Cowpea Chlorotic Mottle Virus-Like Particles. Bioconjugate Chem. 2021, 32, 958–963. 230 Appendices Appendix A A.1 Dye quantum yield measurements The quantum yields of dyes were estimated by comparison to standards, as described previously.51,52 Integrated fluorescence intensity was plotted against absorbance at the excitation wavelength for a series of dilutions of dye and standard. Eqn. A.1 shows how the slopes (I/A) of these plots relate to quantum yield, where the 𝛷 is quantum yield, 𝐼 is the integrated PL intensity, 𝐴 is absorbance at the excitation wavelength, and 𝑛 is the refractive index of the solvent. The subscripts “std” and “X” indicate the standard and dye, respectively. 𝛷𝑋 = 𝛷𝑠𝑡𝑑𝐼𝑋𝐴𝑋𝐴𝑠𝑡𝑑𝐼𝑠𝑡𝑑𝑛𝑋2𝑛𝑠𝑡𝑑2 (A.1) The quantum yields of A488, A546, and Cy5 labels on hybridized DNA were measured in borate buffer (50 mM with 400 mM NaCl, pH 8.6). Fluorescein in 0.1 M NaOH was used as a standard (𝛷 = 0.91)165,166 to measure the quantum yield of A488 and A546. Excitation (and measured absorbance) was at 315 nm and the PL intensity was integrated between 480−700 nm. A546 was then used as a new standard to evaluate the quantum yield of Cy5. Excitation (and measured absorbance) was measured at 564 nm and the PL intensity was integrated between 576−750 nm. Figure A.1A shows plots of measured fluorescence versus absorbance for fluorescein (standard) and A488- and A546-labelled (and hybridized) DNA. Assuming a quantum yield of 0.91 for fluorescein,165,166 the quantum yields of A488 and A546 were determined to be 0.54 and 0.46. 231 Figure A.1B shows analogous plots for A546- and Cy5-labelled (and hybridized) DNA, where the pre-hybridized-DNA-conjugated A546 was used as a reference standard to determine the quantum yield of Cy5. The Cy5 quantum yield was 0.19. Figure A.1 Plots for estimating dye quantum yields: (A) A488 and A546 (with a fluorescein standard) labels on double-stranded oligonucleotides (Blk1-A488/Prb1 and Blk2-A546/Prb2 hybrids); (B) Cy5 (with A546 repurposed as a reference) as a label on a double-stranded oligonucleotide (Blk3-Cy5/Prb3 hybrid). 232 Appendix B B.1 PL emission spectra of calibration data set Figure B.1 shows the emission spectra of each (L, M, N) permutation. The values for L, M, and N were 0, 2, 3.5, or 5, and were the average number of A488, A546, and Cy5 per dendrimer. Figure B.1 Emission spectra for 64 different (L, M, N) permutations. This figure shows the full data set of spectra for Figure 3.1A in the main text of Chapter 2. 233 B.2 Correlation of experimental PL ratios and predictions from mathematical fitting The 64 data points (64 × 3 PL ratios) for different (L, M, N) combinations in Figure 3.1A were fitted with empirical functions (Eqns. 3.13, 3.19, and 3.25) using the coefficients in Table 3.2. The correlation between the experimental PL ratio values and those calculated from mathematical fits of the PL ratio space had a slope close to unity, indicating a good quality of fit (Figure B.2A). Similarly, the 27 standard data points (27 × 3 PL ratios; Table B.1) for different [l, m, n] combinations in Figure 3.3C were fitted with empirical functions (Eqns. 3.13, 3.19, and 3.25) using the coefficients in Table 3.3. The correlation again had a slope close to unity, consistent with a good fit (Figure B.2B). The experimentally measured PL ratio values of the 13 random samples were used to obtain calculated l, m, and n by solving Eqns. 3.13, 3.19, and 3.25 with the coefficients in Table 3.3. The upper bound for l, m, and n was 10 and lower bound was –3. The actual and calculated l, m, and n values are summarized in Table B.2. The calculated values were within ± 0.5 of the actual values in ≥ 9 of the 13 cases for each of l, m, and n. Note: Different initial guess values (e.g. 0.05, 0.001, 1, and –0.05) were attempted when finding a set of 𝑙𝑥, 𝑚𝑥, and 𝑛𝑥 parameters for fitting PL ratio data. The 𝑙𝑥, 𝑚𝑥, and 𝑛𝑥 changed along with different initial values; however, the calculated l, m, and n obtained from solving the equations (with the same upper and lower bounds) were nearly the same, where all differences were less than 0.00001. 234 Figure B.2 Correlations between the PL ratios predicted from mathematical fits of the experimental data and the actual experimentally measured PL ratios. (A) The 64 (L, M, N) permutations for the data in Figure 3.1A. (B) The 27 [l, m, n] permutations for the data in Figure 3.3C (displacement assay). 235 Table B.1 The actual value of each l, m, and n and PL ratios of the calibration data set (27 combinations) in Figure B.2B and Figure 3.3C (circle points). Actual [l, m, n] ρA488/Tb ρA546/Tb ρCy5/Tb [0, 0, 0] 0.241 0.868 1.227 [2.5, 0, 0] 0.175 0.820 1.059 [5, 0, 0] 0.062 0.766 1.025 [0, 0, 2.5] 0.281 1.069 0.636 [2.5, 0, 2.5] 0.216 1.092 0.646 [5, 0, 2.5] 0.076 1.030 0.610 [0, 0, 5] 0.322 1.398 0.145 [2.5, 0, 5] 0.222 1.424 0.067 [5, 0, 5] 0.089 1.278 0.079 [0, 2.5, 0] 0.307 0.553 1.029 [2.5, 2.5, 0] 0.196 0.528 0.851 [5, 2.5, 0] 0.085 0.469 0.867 [0, 2.5, 2.5] 0.332 0.725 0.541 [2.5, 2.5, 2.5] 0.227 0.682 0.529 [5, 2.5, 2.5] 0.097 0.690 0.539 [0, 2.5, 5] 0.379 0.933 0.103 [2.5, 2.5, 5] 0.244 0.841 0.067 [5, 2.5, 5] 0.121 0.849 0.065 [0, 5, 0] 0.348 0.152 0.743 [2.5, 5, 0] 0.262 0.112 0.711 [5, 5, 0] 0.118 0.145 0.698 [0, 5, 2.5] 0.363 0.204 0.365 [2.5, 5, 2.5] 0.269 0.199 0.380 [5, 5, 2.5] 0.128 0.169 0.370 [0, 5, 5] 0.437 0.268 0.064 [2.5, 5, 5] 0.309 0.237 0.051 [5, 5, 5] 0.137 0.212 0.046 236 Table B.2 The difference of actual value and calculated value of each l, m, and n and experimental PL ratios. This PL ratio data was plotted in Figure 3.3C as the star points. Actual [l, m, n] ρA488/Tb ρA546/Tb ρCy5/Tb Calculated [l, m, n] [0, 0, 1] 0.290 0.894 0.993 [–0.52, 0.51, 0.87] [0, 1.5, 1.5] 0.296 0.832 0.790 [0.02, 1.23, 1.53] [0, 3, 0] 0.266 0.480 0.921 [0.96, 2.71, 0.07] [4, 0, 4] 0.135 1.146 0.265 [4.25, 0.49, 4.08] [0, 1, 1.5] 0.245 0.893 0.800 [1.06, 0.76, 1.52] [2.5, 0, 3] 0.174 1.088 0.450 [3.14, 0.42, 3.18] [3, 4, 0] 0.210 0.269 0.824 [2.67, 4.05, –0.24] [0, 5, 1] 0.378 0.159 0.619 [–0.16, 5.14, 0.79] [2.5, 1.5, 1] 0.192 0.787 0.932 [2.21, 0.80, 0.69] [3, 4 ,5] 0.224 0.485 0.058 [3.37, 4.01, 5.08] [1, 3, 5] 0.345 0.805 0.074 [0.75, 2.70, 5.07] [4, 3.5, 2] 0.152 0.449 0.555 [4.12, 3.37, 1.77] [3, 3, 3] 0.222 0.603 0.404 [2.77, 2.94, 2.97] 237 B.3 Detection limits of dendrimer 4, QD520 and QD605 in serum Figure B.3 compares the detection of low concentrations of dendrimer 4 in 50% v/v serum versus CdSe/CdS/ZnS QD520 and QD605. Time-gated emission was measured for dendrimer 4 (60 µs delay time, 2000 µs integration time, 340 nm/20 nm excitation wavelength/bandwidth). Prompt emission was measured for the QDs (405 nm/5 nm excitation wavelength/bandwidth for QD520; 464 nm/5 nm for QD605). The estimated detection limits were ~0.2 nM for Tb, ~5 nM for QD520, and ~0.05 nM for QD605. Note that the ~0.2 nM detection limit is for the Tb as dendrimer 4. The detection limit for the (5, 5, 5) cFRET probe (i.e. dendrimer 5) was noted to be ≤ 10 nM in the main text. This concentration is higher for two main reasons: the Tb emission in the (5, 5, 5) probe was quenched by FRET; and the criterion for this detection limit was the resolution of FRET-sensitized dye emission, which was less intense than the Tb emission. 238 Figure B.3 Detection limits for Tb (dendrimer 4) versus CdSe/CdS/ZnS QD520 and QD605 in 50% v/v serum. (A) Examples of PL emission spectra for (i) dendrimer 4, (ii) QD520, and (iii) QD605. (B) Plots of PL emission intensity versus concentration for (i) dendrimer 4, (ii) QD520, and (iii) QD605. The signal detection limit (defined as three standard deviations of the noise above the average blank spectrum) is shown as a dashed horizontal line. Emission intensities were at 490 nm for Tb, and summed between 518–524 nm for QD520 and 596–608 nm for QD605. 239 B.4 Comment on dye photobleaching Significant photobleaching of the dyes was not observed in measurements, including the kinetic experiments over a duration >1.5 h and repeated excitation cycles for lifetime measurements (between 51 000–72 000 pulses at 2.5–12 µJ per pulse, dependent on excitation wavelength). In general, the dyes are expected to bleach prior to the Tb. 240 Appendix C C.1 TEM Analysis TEM images were used to analyze the size distribution of SiNC(676) 1. The average diameter of SiNC(676) 1 was 4.2 nm, estimated from 313 nanocrystals (Figure C.1). Figure C.1 TEM of SiNC(676) 1. (A) Bright field TEM image. (B) Dark field TEM image. (C) Size distribution of SiNCs measured from TEM images. The SiNCs and TEM images were provided from Prof. Veinot’s group at the University of Alberta. 241 C.2 Spectroelectrophoresis of SiNC(605) 1 PL electropherograms of SiNC(605) 1 were collected at multiple wavelengths between 530 and 710 nm. The migration time increased as the wavelength increased (Figure C.2A). In turn, the emission spectrum gradually red-shifted by around 80 nm as the migration time increased (Figure C.2B−C). These data revealed size polydispersity in the population of SiNC(605) 1, where larger SiNCs had longer emission wavelengths on average, consistent with expectations from quantum confinement. Figure C.2 Spectroelectrophoresis of SiNC(605) 1. (A) PL electropherograms measured at different emission wavelengths. PL emission measurements were made with continuous (not pulsed) excitation. (B) PL emission spectra as a function of migration time for the same experiment as panel A. (C) Plot of the peak PL emission wavelength versus migration time. 242 C.3 Absorption, PL emission and excitation, and EEMs of SiNC(717) 1 Figure C.3A shows the extinction spectrum of SiNC(717) 1. Figure C.3B shows that the emission peak of SiNC(717) 1 shifts to longer wavelengths and decreases in intensity as the delay time increases. In contrast, Figure C.3C shows the excitation spectra did not shift with delay time, although the intensity still decreased as the delay time increased. Figure C.4 shows the TG EEMs of SiNC(717) 1 with 2 ms and 20 μs integration time. The delay times varied between 0−300 μs. Figure C.3 SiNC(717) 1. (A) Extinction spectrum. (B) Emission spectra with (i) various delay and 2 ms integration time, and (ii) various delay and 20 μs integration time. (C) Excitation spectra with (i) various delay and 2 ms integration time, and (ii) various delay and 20 μs integration time. 243 Figure C.4 EEMs of SiNC(717) 1: (A) various delay with a fixed integration time (2 ms); (B) various delay with a fixed integration time (20 μs). 244 C.4 Absorption, PL emission and excitation, and EEMs of SiNC(605) 1 Figure C.5A shows the extinction spectrum of SiNC(605) 1. Figure C.5B shows that the emission peak of SiNC(605) 1 shifts to longer wavelengths and decreases in intensity as the delay time increases. Figure C.5C shows that the excitation spectra did not shift, but still decreased in intensity as the delay time increase. Figure C.6 shows the TG EEMs of SiNC(605) 1 with 2 ms and 20 μs integration time. The delay times were between 0−150 μs. Figure C.5 SiNC(605) 1. (A) Extinction spectrum. (B) Emission spectra with (i) various delay and 2 ms integration time, and (ii) various delay and 20 μs integration time. (C) Excitation spectra with (i) various delay and 2 ms integration time, and (ii) various delay and 20 μs integration time. 245 Figure C.6 EEMs of SiNC(605) 1: (A) various delay with a fixed integration time (2 ms); (B) various delay with a fixed integration time (20 μs). 246 C.5 Extinction coefficient of SiNC(676) 1 The concentration of SiNC(676) 1 was estimated by combining the results of TEM images and TGA. First, the average diameter of the SiNC was determined by measuring the nanocrystal size from the TEM images. The average mass per nanocrystal was calculated from the diameter and the density of Si crystal (2.33 g/cm3). Second, the quantity of Si element in a SiNC(676) 1 stock solution (dispersed in water) was determined from the TGA results, which provides the mass of Si element per unit volume (mg/mL). The concentration of SiNC were obtained from dividing the TGA results by the mass of SiNC. The nominal absorbance value of SiNCs at 350 nm is thought to be a combination of absorbance and scattering from SiNCs, collectively referred to as extinction. The extinction coefficient of SiNC(676) 1 was estimated from a plot of the measured absorbance values versus the concentration. A linear fit was applied with a constraint, intercept at y = 0. The slope of the linear fit was used as the extinction coefficient of the SiNC(676) 1 at 350 nm, and was 12 160 M−1 cm−1. Figure C.7 Nominal absorption values (at 350 nm) versus various concentrations of SiNC(676) 1. 247 C.6 Quantum yield of SiNC(676) 1 and 2 The quantum yields of SiNC(676) 1 and SiNC(676) 2 were estimated by comparison to fluorescein. Integrated PL intensities were plotted as function of the absorbance at the excitation wavelength. Linear fits were applied with constraining the y-intercept to a value of zero. The slopes of the linear fits were proportional to their quantum yield. The quantum yield of the fluorescein reference is reported to be 0.91,165,166 and the quantum yields of SiNC(676) 1 and SiNC(676) 2 were 0.086 and 0.029, respectively. Figure C.8 Plot for estimating quantum yield of SiNC 1 and 2 using fluorescein as a standard. 248 C.7 Partitioning and dissociation of BHQs SiNC(676) 1 were mixed with 1.0 equivalents of BHQ1, BHQ2, and BHQ3 individually. Figure C.9A shows the emission spectra of SiNC(676) 1 with partitioned BHQ. Compared to control sample without BHQ (SiNC(676) 1 only; orange), the SiNC PL intensity was quenched with corresponding ET efficiencies of 63%, 38%, and 98% for BHQ1, BHQ2, and BHQ3, respectively. After adding DMSO to the samples (the final concentration of DMSO was 41.5% v/v), the ET efficiencies decreased to 10%, 3.3%, and 26% for BHQ1, BHQ2, and BHQ3, respectively. Since DMSO would much better solubilize the BHQ, dissociation of the dyes from the SiNC was expected. This dissociation would not alter inner filter effects but would result in loss of ET. Thus, the results suggested the major contribution to quenching of SiNC PL by BHQs was ET rather than inner filter effects. The experiment was complicated by DMSO-induced quenching of SiNC, but a control sample accounted for this behaviour. Figure C.9 BHQs dissociation test. (A) Without added DMSO, BHQs are partitioned on the surface of SiNC. ET occurs between SiNCs and BHQs, SiNCs are quenched. (B) After adding DMSO, BHQs dissociate from the surface of SiNCs. ET efficiency reduced as dissociation taken place. 249 C.8 SiNC(676) 1 partitioned with BHQ2 The emission spectrum shift (0 μs delay, 2 ms integration time) of SiNC(676) 2 with partitioned BHQ2 was monotonically hypsochromic as the equivalents of BHQ2 increased (Figure C.10A). The wavelength-dependent quenching efficiency with partitioned BHQ2 was higher at longer wavelengths (Figure C.10B). Figure C.10 SiNC(676) 1 with various equivalents of partitioned BHQ2: (A) Emission spectra (0μs delay, 2 ms integration time) and (B) ET efficiency versus wavelength. TG emission spectra (variable delay, 20 µs integration time) of SiNC(676) 2 partitioned with various equivalents of BHQ2 were measured. The temporal trajectory for the peak shift and FWHM were similar to those observed with BHQ3 (Figure C.11B−C). The gradual temporal shift in the trajectory for the peak PL wavelength was small and hyposochromic, and the FWHMs narrowed at a slightly faster rate with more equivalents of BHQ2. 250 Figure C.11 TG spectral snapshots (variable delay, 20 µs integration) of SiNC(676) 1 with partitioned BHQ2. (A) Emission spectra (only 0 µs delay, 20 µs integration time are shown). (B) Emission peak shift versus delay time. (C) FWHM versus delay time. (D) Quenching efficiency as a function wavelength and delay time. PL lifetimes were analyzed for the same three wavelength windows (540−600 nm, 600−660 nm, and 696−756 nm). The PL lifetime was greatest in the longer wavelength window and decreased with an increasing number of equivalents of partitioned BHQ2 (Figure C.12A). PL decay obtained by the box-car method (Figure C.12B) has the same trends. The ET efficiencies derived in the three wavelength windows using the box-car method (Figure C.12C) increased as wavelength increased, similar to the PL intensity data (Figure C.10B). 251 Figure C.12 Lifetime measurements of SiNC(676) 1 partitioned with BHQ2. (A) PL decay of SiNC(676) 1 with various equivalents of partitioned BHQ2 at 540−600 nm, 600−660 nm, and 696−756 nm. (B) Box-car measurements at various delay at 540−600 nm, 600−660 nm, and 696−756 nm. (C) ET efficiency at different wavelength windows. Calculated from panel B. 252 C.9 Absorption spectra of SiNC(676) 2 conjugated with BHQ1 and BHQ3 Figure C.13 shows the absorption spectra of purified SiNC(676) 2 with conjugated BHQ1 and BHQ3 samples. The samples were washed with 60% EtOH (aq) via 30 kDa centrifugal filters. The excess BHQ was expected to pass through the 30 kDa membrane. The filtrates gradually turned nearly colourless after several cycles of washing. The absorption spectra for the purified samples show the absorbance features of BHQ1 and BHQ3, which indicated successful conjugations. Figure C.13 Absorption spectra of SiNC(676) 2 with conjugated (A) BHQ1 and (B) BHQ3, after purification. 253 C.10 Absorption spectra of SiNC(676) 2 conjugated with sCy5.5 Figure C.14 shows the absorption spectra of purified SiNC(676) 2 with conjugated sCy5.5 samples. The samples were washed with 1× DPBS via 30 kDa centrifugal filters. The excess sCy5.5 was expected to pass through the 30 kDa membrane. The absorption spectra for purified samples show the absorbance feature of sCy5.5, which indicated successful conjugations. Figure C.14 Absorption spectra of SiNC(676) 2 with conjugated sCy5.5, after purification. 254 C.11 Lifetime data and ET efficiency Tables C.1−C.6 (following pages) summarize PL lifetime fitting parameters and the resulting ET efficiencies. Table C.7 summarizes the ensemble ET efficiencies for partitioned samples with estimation via both PL intensity data and TR PL data. Table C.1 Lifetime of SiNC(676) 1 partitioned with variable equivalent of BHQ1. Equiv. Method λ Range (nm) τ1 (μs) A1 (%) τ2 (μs) A2 (%) τAvg (μs) ET (%) 0 TR 540−756 41.1 80.6 100.0 19.4 52.6 0.0 540−600 29.7 93.4 94.2 6.6 34.0 0.0 600−660 43.7 85.9 94.8 14.1 50.9 0.0 696−756 77.2 77.5 141.7 22.5 91.7 0.0 Box-car 540−600 7.5 76.2 32.1 23.8 13.3 0.0 600−660 14.6 52.8 53.4 47.2 32.9 0.0 696−756 29.4 35.4 101.4 64.6 75.9 0.0 0.33 Box-car 540−600 7.8 75.6 32.0 24.4 13.7 0.0* 600−660 14.1 54.7 51.9 45.3 31.2 5.2 696−756 25.8 39.7 97.4 60.3 69.0 9.1 0.67 TR 540−756 37.4 81.7 96.8 18.3 48.3 8.1 540−600 26.7 91.9 81.1 8.1 31.1 8.6 600−660 41.0 86.3 92.4 13.7 48.0 5.6 696−756 64.6 66.4 127.2 33.6 85.6 6.7 0.67 Box-car 540−600 7.9 75.5 32.1 24.5 13.8 0.0* 600−660 14.0 55.2 51.6 44.8 30.9 6.2 696−756 24.5 41.2 95.7 58.8 66.4 13 3.3 TR 540−756 32.3 81.2 87.5 18.8 42.7 19 540−600 23.5 90.3 72.4 9.7 28.3 17 600−660 35.6 83.1 81.6 16.9 43.4 15 696−756 44.2 56.0 104.3 44.0 70.7 23 255 3.3 Box-car 540−600 5.7 83.5 27.8 16.5 9.3 30 600−660 9.3 66.0 43.3 34.0 20.8 37 696−756 13.4 55.5 70.3 44.5 38.7 49 6.7 Box-car 540−600 4.8 89.3 25.5 10.7 7.0 48 600−660 6.7 78.7 38.1 21.3 13.4 59 696−756 11.2 68.7 60.1 31.3 26.5 65 13 TR 540−756 22.0 83.2 72.0 16.8 30.4 42 540−600 17.9 88.1 60.7 11.9 22.0 32 600−660 23.5 80.2 66.7 19.8 32.1 37 696−756 23.9 78.0 88.0 22.0 38.0 59 13 Box-car 540−600 3.4 96.8 22.8 3.2 4.0 70 600−660 4.5 93.1 32.0 6.9 6.3 81 696−756 7.6 83.8 44.1 16.2 13.5 82 27 Box-car 540−600 3.1 98.1 22.0 1.9 3.5 74 600−660 3.7 96.9 29.0 3.13 4.5 86 696−756 6.1 89.2 34.8 10.8 9.2 88 47 Box-car 540−600 3.9 95.5 21.9 4.5 4.7 65 600−660 3.8 96.8 27.7 3.2 4.6 86 696−756 0.9 99.0 34.0 1.0 1.3 98 * The ET efficiency was mathematically below 0%. 256 Table C.2 Lifetime of SiNC(676) 1 partitioned with variable equivalent of BHQ2. Equiv. Method λ Range (nm) τ1 (μs) A1 (%) τ2 (μs) A2 (%) τAvg (μs) ET (%) 0 TR 540−600 26.9 91.1 83.3 8.9 32.0 0.0 600−660 43.2 84.3 91.2 15.7 50.7 0.0 696−756 68.8 61.6 124.6 38.4 90.2 0.0 Box-car 540−600 7.3 75.3 30.9 24.7 13.2 0.0 600−660 14.5 54.0 52.5 46.0 32.0 0.0 696−756 32.0 41.3 103.9 58.7 74.2 0.0 0.33 TR 540−600 27.2 91.9 82.5 8.1 31.7 0.82 600−660 41.9 86.4 93.0 13.6 48.8 3.7 696−756 55.4 50.0 111.5 50.0 83.5 7.5 0.33 Box-car 540−600 8.0 74.8 31.3 25.2 13.8 0.0* 600−660 14.6 56.5 50.9 43.5 30.4 5.0 696−756 24.1 43.5 90.1 56.5 61.4 17 0.67 Box-car 540−600 7.8 75.4 30.9 24.6 13.5 0.0* 600−660 14.6 56.4 50.0 43.6 30.0 6.1 696−756 22.1 43.9 85.0 56.1 57.4 23 1.3 Box-car 540−600 8.0 75.0 30.6 25.0 13.7 0.0* 600−660 14.0 57.3 48.5 42.7 28.7 10 696−756 20.8 45.6 81.0 54.4 53.5 28 2.7 TR 540−600 27.3 93.8 92.1 6.2 31.3 2.0 600−660 40.8 86.0 88.3 14.0 47.5 6.4 696−756 59.2 63.6 115.2 36.4 79.6 12 2.7 Box-car 540−600 8.1 75.5 30.9 24.5 13.7 0.0* 600−660 14.9 58.9 49.3 41.1 29.1 9.1 696−756 19.5 44.3 77.6 55.7 51.9 30 4.7 Box-car 540−600 7.6 76.6 29.1 23.4 12.6 4.2 600−660 13.7 58.8 45.0 41.2 26.6 17 696−756 17.2 48.1 69.2 51.9 44.1 41 257 6.7 TR 540−600 25.9 94.6 90.4 5.4 29.4 8.0 600−660 37.5 87.7 83.0 12.3 43.1 15 696−756 47.4 69.1 105.4 30.9 65.4 28 6.7 Box-car 540−600 8.0 75.6 28.6 24.4 13.0 1.1 600−660 13.1 59.2 42.8 40.8 25.2 21 696−756 13.6 47.6 60.9 52.4 38.4 48 20 Box-car 540−600 6.5 78.4 25.7 21.6 10.6 19 600−660 10.4 58.0 37.1 42.0 21.6 32 696−756 11.7 51.3 53.8 48.7 32.2 57 40 Box-car 540−600 6.5 77.8 24.7 22.2 10.6 20 600−660 9.5 59.5 34.8 40.5 19.8 38 696−756 10.6 55.2 49.9 44.8 28.2 62 * The ET efficiency was mathematically below 0%. 258 Table C.3 Lifetime of SiNC(676) 1 partitioned with variable equivalent of BHQ3. Equiv. Method λ Range(nm) τ1 (μs) A1 (%) τ2 (μs) A2 (%) τAvg (μs) ET (%) 0 TR 540−756 42.3 80.6 103.4 19.4 54.2 0.0 540−600 28.7 91.6 85.4 8.4 33.4 0.0 600−660 44.9 85.9 96.1 14.1 52.1 0.0 696−756 73.1 60.0 126.0 40.0 94.3 0.0 Box-car 540−600 8.0 74.3 32.9 25.7 14.4 0.0 600−660 15.3 51.8 54.0 48.2 34.0 0.0 696−756 31.8 37.1 103.1 62.9 76.7 0.0 0.13 Box-car 540−600 7.5 76.8 32.4 23.2 13.2 8.2 600−660 13.2 54.2 51.5 45.8 30.7 9.7 696−756 23.4 35.1 91.0 64.9 67.3 12 0.20 TR 540−756 45.4 82.1 105.4 17.9 56.2 0.0* 540−600 28.3 91.5 85.2 8.5 33.2 0.8 600−660 46.1 84.5 90.4 15.5 53.0 0.0* 696−756 76.2 72.7 130.6 27.3 91.1 3.4 0.20 Box-car 540−600 7.5 76.7 32.6 23.3 13.4 7.4 600−660 12.5 54.4 50.3 45.6 29.7 13 696−756 21.7 37.3 90.2 62.7 64.7 16 0.33 Box-car 540−600 7.3 77.7 31.7 22.3 12.7 12 600−660 11.8 57.1 49.7 42.9 28.1 17 696−756 16.2 39.1 83.9 60.9 57.4 25 0.47 Box-car 540−600 6.5 79.9 30.8 20.1 11.4 21 600−660 12.0 58.0 49.7 42.0 27.8 18 696−756 14.8 41.0 81.2 59.0 54.0 30 0.67 TR 540−756 35.4 81.4 93.8 18.6 46.3 15 540−600 22.4 89.8 71.5 10.2 27.4 18 600−660 37.2 82.4 84.6 17.6 45.6 13 696−756 50.4 52.0 109.6 48.0 78.8 16 259 0.67 Box-car 540−600 6.8 80.6 31.2 19.4 11.5 20 600−660 11.1 60.6 48.4 39.4 25.8 24 696−756 11.4 46.8 76.3 53.2 45.9 40 1.0 Box-car 540−600 6.4 82.6 30.1 17.4 10.5 27 600−660 10.1 63.8 46.7 36.2 23.4 31 696−756 12.0 51.0 74.7 49.0 42.7 44 1.3 TR 540−756 26.3 78.5 81.2 21.5 38.1 30 540−600 16.5 88.2 59.9 11.8 21.7 35 600−660 32.2 79.7 78.3 20.3 41.6 20 696−756 44.1 55.2 106.9 44.8 72.3 23 1.3 Box-car 540−600 6.0 84.4 29.2 15.6 9.6 33 600−660 8.7 66.8 44.1 33.2 20.5 40 696−756 9.6 59.8 70.9 40.2 34.3 55 * The ET efficiency was mathematically below 0%. 260 Table C.4 Lifetime of SiNC(676) 2 conjugated with variable equivalent of BHQ1. Equiv. Method λ Range (nm) τ1 (μs) A1 (%) τ2 (μs) A2 (%) τAvg (μs) ET (%) 0 Box-car 540−600 8.3 38.1 31.7 61.9 22.8 0.0 600−660 18.2 41.5 57.3 58.5 41.1 0.0 696−756 37.9 35.1 117.5 64.9 89.6 0.0 2.9 Box-car 540−600 7.4 45.0 30.4 55.0 20.0 12 600−660 14.9 44.0 53.9 56.0 36.7 11 696−756 29.3 29.0 99.5 71.0 79.1 12 4.8 Box-car 540−600 6.5 47.9 28.7 52.1 18.1 21 600−660 12.1 41.3 48.2 58.7 33.3 19 696−756 33.7 39.9 111.1 60.1 80.2 10 9.6 Box-car 540−600 4.4 51.5 23.6 48.5 13.7 40 600−660 7.9 42.6 39.3 57.4 25.9 37 696−756 25.4 38.5 94.7 61.5 68.0 24 14.9 Box-car 540−600 3.2 55.8 20.3 44.2 10.8 53 600−660 6.1 48.9 34.7 51.1 20.7 50 696−756 16.2 37.6 80.8 62.4 56.5 37 17.8 Box-car 540−600 3.1 59.9 19.4 40.1 9.6 58 600−660 5.6 52.8 32.3 47.2 18.2 56 696−756 20.5 45.6 81.8 54.4 53.9 40 261 Table C.5 Lifetime of SiNC(676) 2 conjugated with variable equivalent of BHQ3. Equiv. Method λ Range (nm) τ1 (μs) A1 (%) τ2 (μs) A2 (%) τAvg (μs) ET (%) 0 Box-car 540−600 10.5 41.3 36.0 58.7 25.5 0.0 600−660 22.2 42.4 61.4 57.6 44.8 0.0 696−756 51.8 45.5 128.2 54.5 93.4 0.0 0.16 Box-car 540−600 8.8 40.0 34.7 60.0 24.3 4.6 600−660 14.8 31.8 54.5 68.2 41.9 6.5 696−756 21.0 19.0 98.1 81.0 83.4 11 0.25 Box-car 540−600 8.1 38.1 33.2 61.9 23.6 7.2 600−660 14.9 36.7 56.1 63.3 41.0 8.5 696−756 23.3 26.2 101.2 73.8 80.9 13 0.50 Box-car 540−600 8.0 40.7 32.8 59.3 22.7 11 600−660 13.7 37.9 53.0 62.1 38.1 15 696−756 20.1 27.8 89.4 72.2 70.1 25 1.1 Box-car 540−600 5.2 37.4 27.9 62.6 19.4 24 600−660 8.2 33.7 45.2 66.3 32.7 27 696−756 8.8 26.1 68.5 73.9 53.0 43 4.7 Box-car 540−600 2.6 52.2 20.5 47.8 11.1 56 600−660 0.0 50.9 38.2 49.1 18.8 58 696−756 2.9 70.9 40.6 29.1 13.9 85 262 Table C.6 Lifetime of SiNC(676) 2 conjugated with variable equivalent of sCy5.5. Equiv. Method λ Range (nm) τ1 (μs) A1 (%) τ2 (μs) A2 (%) τAvg (μs) ET (%) 0 Box-car 566−598 17.9 62.5 45.7 37.5 28.3 0.0 600−632 24.8 60.2 61.2 39.8 39.3 0.0 634−666 27.5 46.6 72.3 53.4 51.4 0.0 668−700 24.7 36.2 85.2 63.8 63.3 0.0 702−734 45.5 50.3 134.8 49.7 89.9 0.0 736−768 22.3 11.5 114.2 88.5 104 0.0 3.6 Box-car 566−598 17.0 72.8 47.8 27.2 25.4 10 600−632 14.8 51.7 47.8 48.3 30.7 22 634−666 23.9 56.5 71.2 43.5 44.5 13 668−700 17.7 68.7 81.6 31.3 37.7 40 702−734 16.7 67.6 89.1 32.4 40.1 55 736−768 14.8 63.3 101.7 36.7 46.7 55 4.7 Box-car 566−598 15.1 66.6 42.1 33.4 24.1 15 600−632 27.2 79.4 75.0 20.6 37.0 5.8 634−666 25.1 57.1 70.4 42.9 44.5 13 668−700 14.1 76.9 75.1 23.1 28.2 55 702−734 13.1 69.5 69.0 30.5 30.1 66 736−768 14.7 65.4 95.1 34.6 42.5 59 6.0 Box-car 566−598 11.0 68.3 36.6 31.7 19.1 32 600−632 18.7 58.7 52.3 41.3 32.6 17 634−666 14.1 55.1 60.2 44.9 34.8 32 668−700 11.0 81.0 62.8 19.0 20.8 67 702−734 12.8 80.1 72.3 19.9 24.7 73 736−768 23.9 73.2 132.6 26.8 53.1 49 263 Table C.7 ET efficiencies for SiNC(676) 1 partitioned with various equivalents of BHQ1 and BHQ3 dyes, estimated from PL intensity data and TR PL data. Dye Equiv. λ Range (nm) ET (PL Int.) (%) ET (TR) (%) BHQ1 0 540−756 0.0 0.0 0.67 540−756 4.9 8.1 3.3 540−756 46 19 13 540−756 83 42 BHQ3 0 540−756 0.0 0.0 0.20 540−756 15 0.0* 0.67 540−756 49 15 1.3 540−756 70 30 * The ET efficiency was mathematically below 0%.
Thesis/Dissertation
eng
Chemistry
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Algar, W. Russ
Development and characterization of photoluminescent materials towards applications of concentric Fӧrster resonance energy transfer probes in bioanalysis
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