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Characterization and intervention of Campylobacter jejuni persistence and biofilm formation Feng, Jinsong 2018

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CHARACTERIZATION AND INTERVENTION OF CAMPYLOBACTER JEJUNI PERSISTENCE AND BIOFILM FORMATION  by  Jinsong Feng  MSc, Zhejiang University, 2013  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY  in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (FOOD SCIENCE)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  March 2018  © Jinsong Feng, 2018 ii  Abstract The hard-to-treat chronic bacterial infection is one of the most significant challenges to conventional antibiotic therapy. These chronic infections represent an elevated risk for the development of severe clinical consequences. Bacteria can form biofilms or persister cells to withstand harsh stresses and antibiotic treatment. In addition, both biofilm and persister cells can restore the bacterial population upon the removal of stresses and antibiotic treatment. Hence, biofilm and persister cells are proposed to be one of the major survival strategies that associate chronic bacterial infections. As one of the major causes of human gastroenteritis in the world, Campylobacter jejuni was frequently identified in food production as well as in the environment. However, how can this microaerophilic microbe survive in the aerobic environment and disseminate throughout the food chain to eventually cause campylobacteriosis is not fully understood yet. We argued that bacterial biofilm and persister cells be two particular survival state of C. jejuni that contribute to the prevalence of C. jejuni. In this dissertation, particular survival modes of C. jejuni, known as biofilm and persister cells, were characterized. We found that C. jejuni could form both mono- and multispecies biofilms and biofilm formation was significantly influenced by environmental stresses. The extracellular DNA was the factor that mediated this influence. In addition, we identified the presence of C. jejuni persister cells which accounted for ~ 0.01% of the total population. The transcriptome analysis of persister cells indicated that the low metabolic activity and bacterial dormancy could play an important role in the formation of persister cells. In the end, a synergistic treatment using ajoene and Al2O3/TiO2 nanoparticles in a combined manner was applied to generate a significant antimicrobial effect against C. jejuni. In this study, we comprehensively investigated the two major bacterial survival strategies, namely biofilm and persister cells, and applied innovative antimicrobial treatment to iii  inactivate C. jejuni. The knowledge from this study provides insight to understand the survival and distribution of C. jejuni and aids in the development of intervention strategies to reduce the prevalence of C. jejuni and other pathogens.  iv  Lay Summary Campylobacter jejuni is a leading foodborne pathogen. It is a fragile microaerophilie but widely distributed in the natural environment. The survival mechanism of C. jejuni is not clear yet. C. jejuni could form a complex matrix which was known as biofilm by excreting extracellular polymeric substances. Within a biofilm, C. jejuni could survive under stresses.  In addition, dormant C. jejuni also demonstrated a survival advantage. This particular state was known as persister cells. C. jejuni persister cells were a small proportion of normal growing cells that could survive under antibiotic treatment at lethal concentration. We speculated that biofilm and persister cells could be important survival strategy of C. jejuni. By combining a plant-based bioactive compound and metal oxide nanoparticles, we developed a synergistic antimicrobial approach that efficiently inactivated C. jejuni. This thesis provided insight into understanding the survival of C. jejuni and aided in the development of alternative antimicrobial strategies.    v  Preface The following sections are mainly based on the publications and submitted manuscripts.  Chapter 2 is the work of using biochemical and biophysical techniques to characterize C. jejuni biofilms: Feng, J., Lamour, G., Xue, R., Mirvakliki, M.N., Hatzikiriakos, S.G., Xu, J., Li, H., Wang, S. and Lu, X. Chemical, physical and morphological properties of bacterial biofilms affect survival of encased Campylobacter jejuni F38011 under aerobic stress. International Journal of Food Microbiology (2016) 238: 172-182. Dr. Lu was responsible for the design of the experiment and helped edit the manuscript. Dr. Li and Dr. Lamour provided the technical support on the application of atomic force microscopy. Dr. Mirvakliki and Dr. Hatzikiriakos provided the technical assistance for the performance of contact angle measurement. I was responsible for performing experiments, analyzing the data and drafting the manuscript.  Chapter 3 is the application of confocal micro-Raman microfluidic platform for the characterization of bacterial biofilm, which was published as Feng, J., De La Fuente-Núñez, C., Trimble, M.J., Xu, J., Hancock, R.E. and Lu, X. An in situ Raman spectroscopy-based microfluidic “lab-on-a-chip” platform for non-destructive and continuous characterization of Pseudomonas aeruginosa biofilms. Chemical Communications (2015) 51: 8966-8969. Dr. Lu was responsible for the design of the experiment and helped edit the manuscript. Dr. Xu provided technical support on the fabrication of the microfluidic device. Dr. Hancock, Dr. Trimble, and Dr. de la Fuente-Núñez provided technical assistance on the application of confocal laser scanning microscope and helped edit the manuscript. I was responsible for performing experiments, analyzing the data, and drafting the manuscript.  Chapter 4 is a follow-up study of using confocal micro-Raman microfluidic platform to study the biofilm formation of C. jejuni. The results have been published as Feng, J., Ma, L., Nie, vi  J., Konkel, M.E., Lu, X. Environmental stress-induced bacterial lysis and extracellular DNA release contribute to Campylobacter jejuni biofilm formation Applied and Environmental Microbiology (2018) 84: E:02068-17. I was responsible for experimental design under the guidance of Dr. Lu, performed the experiments, analyzed the data and drafted the manuscript. Nie helped conduct the antimicrobial tests. Dr. Lu, Dr. Ma, and Dr. Konkel helped edit the manuscript.  Chapter 5 is related to the investigation of C. jejuni persister cells. The result will be submitted for publication: Feng, J., Xue, R., Ma, L., Wang, Y., Konkel, M.E., Lu, X. Characterization and transcriptome analysis of Campylobacter jejuni persister cells. I was responsible for the design of experiment under the guidance of Dr. Lu, performed experiments, analyzed the data and drafted the manuscript. Xue and Wang helped to conduct tests. Dr. Lu, Dr. Ma, and Dr. Konkel helped to edit the manuscript.  Chapter 6 is related to the investigation of synergistic antimicrobial strategy against C. jejuni, which has been submitted for publication: Feng, J., Xue, R., Wang, S., Konkel, M.E., Lu, X. Whole transcriptome sequencing analysis of the synergistic antimicrobial effect of metal oxide nanoparticle and ajoene against Campylobacter jejuni. Dr. Lu was responsible for experimental design and helped edit the manuscript. Xue and I performed the experiments. I analyzed the data and drafted the manuscript. Dr. Konkel and Dr. Wang helped edit the manuscript.  All published contents including text, figures, and tables are used with permission. vii  Table of contents Abstract ........................................................................................................................................... ii Lay Summary ................................................................................................................................. iv Preface ..............................................................................................................................................v Table of contents ........................................................................................................................... vii List of tables ................................................................................................................................. xiv List of figures ............................................................................................................................... xvi List of supplementary materials ................................................................................................. xxix List of abbreviations ....................................................................................................................xxx Acknowledgements .................................................................................................................. xxxiii Dedication ................................................................................................................................ xxxiv Chapter 1: Literature review ....................................................................................................... 1 1.1 Campylobacter ............................................................................................................ 1 1.2 Survival mechanism of C. jejuni ................................................................................. 3 1.2.1 Bacterial stress response ......................................................................................... 3 1.2.2 Biofilm formation of C. jejuni ................................................................................ 8 1.2.3 Campylobacter dormancy ..................................................................................... 18 1.3 Linkage of Campylobacter dormancy and biofilm formation to food safety ........... 28 1.4 General hypothesis, objectives, and rationale ........................................................... 29 1.4.1 General hypothesis ................................................................................................ 29 1.4.2 Objectives ............................................................................................................. 29 1.4.3 Rationale ............................................................................................................... 30 viii  Chapter 2: Chemical, physical and morphological properties of bacterial biofilms affect survival of encased Campylobacter jejuni F38011 under aerobic stress .................................. 31 2.1 Summary ................................................................................................................... 31 2.2 Introduction ............................................................................................................... 32 2.3 Materials and methods .............................................................................................. 35 2.3.1 Bacterial strains and cultivation. ........................................................................... 35 2.3.2 Biofilm cultivation. ............................................................................................... 35 2.3.3 Survival of C. jejuni F38011 and co-cultured bacterial cells in biofilms under aerobic stress. .................................................................................................................... 36 2.3.4 Confocal laser scanning microscopy (CLSM). ..................................................... 37 2.3.5 Crystal violet biofilm assay. ................................................................................. 37 2.3.6 C. jejuni share (CJS) index in biofilm formation. ................................................. 38 2.3.7 Confocal micro-Raman spectroscopy. .................................................................. 38 2.3.8 Raman spectral processing and multivariate analysis. .......................................... 39 2.3.9 Atomic force microscopy. ..................................................................................... 40 2.3.10 Contact angle measurement. ............................................................................. 40 2.3.11 Biofilm water retention assays. ......................................................................... 41 2.3.12 Statistical analysis. ............................................................................................ 42 2.4 Results ....................................................................................................................... 42 2.4.1 The survival of C. jejuni F38011 and co-cultured bacterial cells in developed biofilms under aerobic stress. ........................................................................................... 42 2.4.2 The viability of C. jejuni F38011 cells in biofilms. .............................................. 45 2.4.3 The formation level of C. jejuni biofilms. ............................................................ 47 ix  2.4.4 The contribution of C. jejuni to biofilm formation. .............................................. 48 2.4.5 The chemical compositions of C. jejuni biofilms. ................................................ 49 2.4.6 The morphological and surface roughness of C. jejuni biofilms. ......................... 56 2.4.7 The surface wettability and free energy property of C. jejuni biofilms. ............... 61 2.4.8 The water-holding capability of C. jejuni biofilms. .............................................. 66 2.5 Discussion ................................................................................................................. 69 Chapter 3: In-situ Raman spectroscopic-based microfluidic “lab-on-a-chip” platform for non-destructive and continuous characterization of Pseudomonas aeruginosa biofilms ................. 74 3.1 Summary ................................................................................................................... 74 3.2 Introduction ............................................................................................................... 74 3.3 Materials and methods ........................................................................................... 76 3.3.1 Bacterial strains and growth conditions. ...................................................... 76 3.3.2 Fabrication of microfluidic “lab-on-a-chip” platform. ..................................... 76 3.3.3 Biofilm formation in the microfluidic “lab-on-a-chip” system. ............... 76 3.3.4         Integration of confocal micro-Raman spectroscopy with the microfluidic platform. ..........................................................................................................................  77 3.3.5 Confocal laser scanning microscope for biofilm quantification. .............. 77 3.3.6 Chemometric models. .................................................................................... 78 3.4 Results and discussion ........................................................................................... 78 3.5 Conclusions ............................................................................................................... 90 Chapter 4: Environmental stress-induced bacterial lysis and extracellular DNA release contribute to Campylobacter jejuni biofilm formation ............................................................. 91 4.1 Summary ................................................................................................................... 91 x  4.2 Introduction ............................................................................................................... 92 4.3 Materials and methods .............................................................................................. 94 4.3.1 Bacterial strains and cultivation conditions. ......................................................... 94 4.3.2 Construction of C. jejuni F38011 spoT and recA knockout mutant strains. ......... 96 4.3.3 Construction of C. jejuni F38011 spoT and recA complementary strains. ......... 100 4.3.4 Biofilm formation either in 96-well plate or on nitrocellulose membrane under different environment. ..................................................................................................... 100 4.3.5 Crystal violet biofilm assay. ............................................................................... 101 4.3.6 Fabrication of microfluidic “lab-on-a-chip” platform for biofilm formation. .... 102 4.3.7 Characterization of C. jejuni biofilm in microfluidic platform using confocal micro-Raman spectroscopy. ............................................................................................ 104 4.3.8 Quantification of the released eDNA. ................................................................. 105 4.3.9 Gel electrophoresis of the released DNA. ........................................................... 105 4.3.10 DNase I treatment on C. jejuni F38011 biofilm. ............................................ 106 4.3.11 Atomic force microscopy. ............................................................................... 106 4.3.12 Addition of DNA for biofilm formation. ........................................................ 107 4.3.13 Autolysis assay................................................................................................ 107 4.3.14 Motility test. .................................................................................................... 108 4.3.15 Quantification of cell lysis. ............................................................................. 108 4.3.16 Real-time qPCR analysis of gene expression. ................................................ 109 4.3.17 Fluorescence microscopy for the analysis of the role of eDNA in biofilm structure. 109 4.3.18 Statistical analysis. .......................................................................................... 110 xi  4.4 Results ..................................................................................................................... 110 4.4.1 Biofilm formation under different environmental conditions ............................. 110 4.4.2 Determination of chemical compositions of C. jejuni biofilms in a microfluidic “lab-on-a-chip” device .................................................................................................... 115 4.4.3 Accumulation of eDNA comes along with biofilm development ...................... 119 4.4.4 Source of eDNA during biofilm formation ......................................................... 121 4.4.5 Addition of DNA stimulates biofilm formation.................................................. 127 4.4.6 DNase I treatment prevents biofilm formation and disrupts biofilm structure ... 130 4.4.7 DNA allocates C. jejuni and Salmonella cells in a dual-species biofilm ............ 134 4.5 Discussion ............................................................................................................... 137 4.6 Conclusion .............................................................................................................. 146 Chapter 5: Characterization and transcriptome analysis of Campylobacter jejuni persister cells................................................................................................................................................. 147 5.1 Summary ................................................................................................................. 147 5.2 Introduction ............................................................................................................. 147 5.3 Materials and methods ............................................................................................ 150 5.3.1 Strains and bacterial cultivation. ......................................................................... 150 5.3.2 The minimum inhibitory concentration test. ....................................................... 151 5.3.3 Kinetics of persister formation. ........................................................................... 152 5.3.4 RNA extraction and RNA-seq analysis of C. jejuni F38011 persister cells. ...... 152 5.3.5 The prediction of type II toxin and antitoxin (TA) module in C. jejuni F38011. 153 5.4 Results and discussion ............................................................................................ 153 5.4.1 C. jejuni form multidrug tolerant persister cells ................................................. 153 xii  5.4.2 The transcriptional analysis by next-generation sequencing (RNA-seq) of persister cells of C. jejuni F38011. ................................................................................................ 155 Chapter 6: Whole transcriptome sequencing analysis of synergistic antimicrobial effect of metal oxide nanoparticles and ajoene on Campylobacter jejuni ............................................ 164 6.1 Summary ................................................................................................................. 164 6.2 Introduction ............................................................................................................. 165 6.3 Materials and methods ............................................................................................ 167 6.3.1 Chemicals and reagents ....................................................................................... 167 6.3.2 Bacterial strains and culture methods ................................................................. 167 6.3.3 Antimicrobial effects of metal oxide nanoparticles and ajoene against C. jejuni167 6.3.4     Synergistic antimicrobial effect of metal oxide nanoparticle and ajoene against C. jejuni ..............................................................................................................................  168 6.3.5 RNA-seq and real-time polymerase chain reaction (qPCR) ............................... 169 6.3.6 Statistical analysis ............................................................................................... 171 6.4 Results ..................................................................................................................... 171 6.4.1 Antibacterial effect of ajoene against C. jejuni. .................................................. 171 6.4.2 Antibacterial effect of metal oxide nanoparticles against C. jejuni. ................... 172 6.4.3     Synergistic antimicrobial effect of metal oxide nanoparticle and ajoene against C. jejuni. .............................................................................................................................  176 6.4.4      Transcriptomic response of C. jejuni treated with metal oxide nanoparticles and ajoene. ............................................................................................................................  176 6.5 Discussion ............................................................................................................... 183 6.6 Conclusion .............................................................................................................. 187 xiii  Chapter 7: Outlook .................................................................................................................. 189 References ............................................................................................................................... 190  xiv  List of tables  Table 1-1. The critical stress response genes that present in other model bacterial species but are absent in C. jejuni (Park, 2002) ...................................................................................................... 5 Table 1-2. The factors are important for biofilm initial attachment (Donlan, 2002). ................... 12 Table 2-1. Viable C. jejuni F38011 cell counts in mature biofilms with aerobic stress. .............. 44 Table 2-2. Viable non-C. jejuni (i.e. S. enterica, S. aureus, and P. aeruginosa) bacterial cell counts in mature biofilms under aerobic stress. ............................................................................ 45 Table 2-3. Contribution of C. jejuni F38011 cells to the formation of mono- and dual-species biofilms. ........................................................................................................................................ 49 Table 2-4. The band assignments of Raman spectra of C. jejuni mono-species biofilm and dual-species C. jejuni-S. enterica biofilm. ............................................................................................ 51 Table 2-5. The assignments for distinct Raman bands between the Raman spectra of C. jejuni-S. aureus and C. jejuni-P. aeruginosa biofilms. ............................................................................... 53 Table 2-6. The contact angle of different reference liquids on mono- and dual-species C. jejuni biofilms using sessile drop technique. .......................................................................................... 63 Table 2-7. The total surface energy and distribution of energy components of mono- and dual-species C. jejuni biofilms. ............................................................................................................. 65 Table 3-1. Raman band assignments of P. aeruginosa biofilm grown in a microfluidic “lab-on-a-chip” platform (De Gelder et al., 2007; Ivleva et al., 2009; Lu et al., 2012b; Tang et al., 2013; Masyuko et al., 2014).................................................................................................................... 83 Table 4-1. Bacterial strains and plasmid used in the current study. ............................................. 94 Table 4-2. Primers used in the current study. ............................................................................... 98 xv  Table 4-3. Raman band assignments for C. jejuni biofilm formed in the microfluidic platform (Naumann, 2001; Movasaghi et al., 2007; Talari et al., 2015). .................................................. 119 Table 5-1. Bacterial strains and plasmid used in the current study. ........................................... 151 Table 5-2. The functional analysis of differentially expressed genes in C. jejuni F38011 persister cells isolated by ampicillin treatment on the basis of gene ontology terms. ............................... 159 Table 5-3. GO pathway enrichment analysis of DEGs in C. jejuni F38011 persister cells isolated by ampicillin treatment. .............................................................................................................. 160 Table 5-4. The functional analysis of differentially expressed genes in C. jejuni F38011 persister cells isolated by ciprofloxacin treatment on the basis of gene ontology terms. ......................... 161 Table 5-5. GO pathway enrichment analysis of DEGs in C. jejuni F38011 persister cells isolated by ciprofloxacin treatment. ......................................................................................................... 162 Table 6-1. The primers of selected genes used in qPCR validation ........................................... 170 Table 6-2. The differentially expressed genes in C. jejuni F38011 induced by 1 mM ajoene treatment. .................................................................................................................................... 179 Table 6-3. The differentially expressed genes in C. jejuni F38011 induced by 16 mM TiO2 nanoparticles treatment. .............................................................................................................. 180  xvi  List of figures Figure 1-1. The schematic figures demonstrate distinct stages of biofilm formation. Stage 1 initial attachment: bacteria attach to substrate; Stage 2  irreversible attachment: the initial attachment is reinforced; Stage 3: bacteria start with secret extracellular polymeric substances (EPS) which lead to the formation of a thin mono-layer biofilm structure; Stage 4 biofilm maturation: bacteria multiply and progressively secrete EPS which lead to the formation of a thick multi-layer biofilm structure; Stage 5 biofilm dispersion: the structure of biofilm is broken down, and cells in biofilm are released into environment. The photomicrograph is derived from a developing Pseudomonas aeruginosa biofilm (Monroe, 2007). .................................................. 10 Figure 1-2. The microenvironment of biofilm is stressful that can stimulate the transition from normal growing cells to VBNC and persister cells.: (1) VBNC cells and persister cells stochastically present in planktonic culture at low level; (2) environmental stresses (i.e. starvation, oxidative stress, temperature fluctuation) can induce the transition from normal growing cells to VBNC and persister cells; (3) the microenvironment of biofilm is acidic and oxygen deprived which can also stimulate the transition from normal growing cells to VBNC and persister cells (Ayrapetyan et al., 2015). ....................................................................................... 20 Figure 1-3. The time-kill kinetics of resistant cells, tolerant cells and persister cells challenged by antibiotic treatment.  The susceptibility of these cells is totally different. a) The minimum inhibitory concentration (MIC) of resistant cells is substantially higher than the MIC of susceptible cells. Colored wells represent the growth of bacterial cells, whereas wells in light brown represent the complete inhibition of bacterial growth due to the presence of the antibiotic. b) The MIC of tolerant cells is almost the same as that of susceptible cells; however, the MDK99 (minimum duration for killing 99% of bacterial cells in the population) of tolerant cells is xvii  substantially higher than that of susceptible cells. c) The population of persister cells comprises a fraction of susceptible cells and a faction of tolerant cells. Hence, the MIC and MDK99 of persister population is almost the same as that of susceptible cells. However, the MDK99.99 of persister cells is substantially higher than that of susceptible cells. Concentrations and timescales are chosen for illustration purposes only (Brauner et al., 2016). .................................................. 23 Figure 2-1. The viability and localization of C. jejuni cells in mono-species C. jejuni F38011 biofilm was determined using live/dead kit coupled with confocal laser scanning microscopy. In this image, green color indicates live C. jejuni cells while red color indicates dead C. jejuni cells (n = 3). After four days exposure to aerobic stress, there is no viable C. jejuni cells could be detected using MH plating method. However, the green signal derived from viable cells still could be observed in biofilm, and most of these viable cells were localized at the bottom layer of biofilm. a) Viable and dead C. jejuni cells in mono-species biofilm showed in horizontal layout. b) Viable C. jejuni cells in mono-species biofilm showed in vertical layout. .............................. 47 Figure 2-2. The formation level of mono- and dual-species biofilms in 96-well plate was quantified by crystal violet staining assay. (white column: the biofilms formed by C. jejuni individually or with other bacteria (i.e., P. aeruginosa, S. enterica, and S. aureus); black column: biofilms formed by non-C. jejuni bacteria, including P. aeruginosa, S. enterica, and S. aureus, individually. Asterisk denotes significant difference (P < 0.05). ................................................. 48 Figure 2-3. The Raman spectra indicated the chemical variations among different biofilms. The Raman spectra were collected using a confocal micro-Raman system with 785 nm laser. The biofilms were prepared on NC membrane and air-dried for 15 mins before spectra collection. Raman spectra showed here were the average of 24 independent replicates: a) the Raman spectra of mono-species C. jejuni biofilm; b) the Raman spectra of dual-species C. jejuni-S. enterica xviii  biofilm; c) the Raman spectra of dual-species C. jejuni-S. aureus; d) the Raman spectra of dual-species C. jejuni-P. aeruginosa. ................................................................................................... 50 Figure 2-4. The minor chemical variation between C. jejuni mono-species biofilm (black) and dual-species C. jejuni-S. enterica biofilm (gray) was determined using second derivative transformations of Raman spectra. Distinct differences were observed at 425, 578, 780, 855, 997, and 1280 cm-1. ............................................................................................................................... 52 Figure 2-5. The Raman spectra of biofilms formed by non-Campylobacter bacteria (i.e., S. enterica, S. aureus, and P. aeruginosa) indicated the contribution of non-Campylobacter to the chemical composition of dual-species biofilms. The Raman spectra were collected using a confocal micro-Raman system with 785 nm laser. The biofilms were prepared on NC membrane and air-dried for 15 mins before spectra collection. Raman spectra showed here were the average of 24 independent replicates: a) the Raman spectra of S. enterica biofilm; b) the Raman spectra of S. aureus biofilm; c) the Raman spectra of P. aeruginosa biofilm. ......................................... 55 Figure 2-6. The principal component analysis for the segregation of C. jejuni mono- and dual-species biofilms based on the difference of their Raman spectra. Cross: C. jejuni biofilm; triangle: C. jejuni-S. enterica biofilm; plus: C. jejuni-S. aureus biofilm; square: C. jejuni-P. aeruginosa biofilm. .......................................................................................................................................... 56 Figure 2-7. Topographic deflection-retrace images of mono- and dual-species C. jejuni biofilms obtained by atomic force microscopy in contact mode within 8 µm × 8 µm area: a) C. jejuni; b) C. jejuni-S. enterica; c) C. jejuni-S. aureus; d) C. jejuni-P. aeruginosa. (left panels: C. jejuni-containing biofilms; right panels: non-C. jejuni-containing biofilms) (n = 20). .......................... 57 Figure 2-8. The representative topographic height-retrace images of mono- and dual-species C. jejuni biofilms were obtained by atomic force microscopy in contact mode. The images were xix  shown in 8 µm × 8 µm area: a) The image of C. jejuni biofilm; b) The images of C. jejuni-S. enterica and S. enterica biofilms; c) The image of C. jejuni-S. aureus and S. aureus biofilms; d) The image of C. jejuni-P. aeruginosa and P. aeruginosa biofilms. (left panels: C. jejuni-containing biofilms; right panels: non-C. jejuni-containing biofilms) (n = 20). .......................... 59 Figure 2-9. The root mean square (RMS) roughness of mono- and dual-species C. jejuni biofilms. The RMS roughness value of white column was derived from C. jejuni containing biofilms. The RMS roughness value of black column was derived from control biofilms which were S. enterica, S. aureus, and P. aeruginosa biofilms. Asterisk denotes significant difference (P < 0.05). ........ 60 Figure 2-10. The 3D reconstruction images of the surface structure of mono- and dual-species C. jejuni biofilms. a) the surface structure of C. jejuni biofilm; b) the surface structure of C. jejuni-S. enterica biofilm; c) the surface structure of C. jejuni-S. aureus biofilm; d) the surface structure of C. jejuni-P. aeruginosa biofilm. (n = 20) ..................................................................................... 61 Figure 2-11. Representative images of contact angle formed by three different liquids (water, formamide, and diiodomethane) on the surface of mono- and dual-species C. jejuni biofilms (n = 9). .................................................................................................................................................. 62 Figure 2-12. The water content of biofilms decreased over time which was reflected by the decrease of the intensity of water IR band at 3350 cm-1. The IR spectra of mono- and dual-species C. jejuni biofilms were collected using the Fourier transform infrared spectroscopy at 5-min intervals: a) the IR spectra of C. jejuni biofilm, b) the IR spectra of C. jejuni-S. enterica biofilm, c) the IR spectra of C. jejuni-S. aureus biofilm, d) the IR spectra of C. jejuni-P. aeruginosa biofilm. ....................................................................................................................... 67 Figure 2-13. The water holding capability of mono- and dual-species C. jejuni biofilms was reflected by the decrease of intensity of water IR band. The IR water band of different biofilms xx  was determined by Fourier transform infrared spectroscopy, as indicated by the featured absorbance band at 3350 cm-1: a) the change of the intensity of IR water band of C. jejuni biofilm, b) the change of the intensity of IR water band of S. enterica and C. jejuni-S. enterica biofilms,  c) the change of the intensity of IR water band of S. aureus and C. jejuni-S. aureus biofilms; d) the change of the intensity of IR water band of P. aeruginosa and C. jejuni-P. aeruginosa biofilms. (solid line: biofilms formed by C. jejuni with or without other bacteria, dash line: biofilms formed by S. enterica, S. aureus, and P. aeruginosa individually). Asterisk denotes significant difference (P < 0.05). ..................................................................................... 68 Figure 3-1. Schematic illustration of the Raman spectroscopic-based microfluidic “lab-on-a-chip” platform for cultivation and characterization of bacterial biofilms. ............................................. 79 Figure 3-2. Raman spectroscopy determines microfluidic chip substrate as background for biofilm characterization. (a) Prominent peaks in Raman spectra of the substrate and P. aeruginosa biofilm grown in the microchamber; (b) Variations in Raman intensities of the corresponding peaks (485, 610, 703, 785, 860, 1256, and 1402 cm-1). Shadow regions highlight variations in peak intensities of microfluidic chip substrate (as background) during P. aeruginosa biofilm development. .................................................................................................................... 80 Figure 3-3. Raman spectroscopy monitoring of the development of P. aeruginosa biofilm in the microfluidic chamber. (A) Prominent peaks appearing within the first 24 h (early stage) are shaded; (B) Variations in intensities of the corresponding Raman peaks (746, 1123, 1307, and 1580 cm-1) over time. (C) Prominent peaks appearing after 48 h (late stage) are shaded; (D) Variations in intensities of the corresponding Raman peaks (918, 968, 1167, 1223, 1333, and 1357 cm-1) over time. .................................................................................................................... 82 xxi  Figure 3-4. The representative two-dimensional principal component analysis for the segregation of P. aeruginosa biofilms at different development stages. The boundary lines could be used to cluster different groups. ................................................................................................................ 85 Figure 3-5. The loading profile of principal component analysis. Dash line is the plot of PC1 and solid line is the plot of PC2. Absolute values of peaks (x-axis) represent the contribution in each component (y-axis). ...................................................................................................................... 86 Figure 3-6. Representative confocal laser scanning microscopic images of P. aeruginosa biofilms grown in a microfluidic chamber. (A) Each panel shows reconstructions from the top in the large panel and sides in the right and bottom panels (xy, yz, and xz dimensions). Biofilm thickness (μm) increased over time. (B) All the values were measured by confocal laser scanning microscopy. Statistical significance was determined using Student’s t-test (* denotes P < 0.05)........................................................................................................................................................ 87 Figure 3-7. Correlation of biofilm thickness measured by confocal laser scanning microscopy and calculated by Raman spectroscopy coupled with partial least-squares regression. ............... 88 Figure 4-1. Schematic illustration of the fabrication of microfluidic “lab-on-a-chip” platform. (A) The pattern of microfluidic device was printed on a transparency. A total of 1 mL of SU-3050 permanent epoxy negative photoresist was dispensed on a silicon wafer and spun to achieve a thickness of 60 μm with the following program: 500 rpm for 10 sec with the acceleration of 100 rpm/sec and then 3000 rpm for 30 sec with the acceleration of 300 rpm/sec. The photoresist on the silicon wafer was then soft baked on a hot plate for 10 min at 95ºC. The transparency with a pattern was then loaded on the photoresist for UV exposure. The exposure energy was set as 150 mJ/cm2. After UV exposure, the photoresist was baked again at 65ºC for 1 min and then 95ºC for 5 min. The silicon wafer with photoresist was then washed with the SU-8 developer for 10 min xxii  to remove the unexposed photoresist. The PDMS was then molded on the basis of the pattern on the silicon wafer. The inlet and outlet were drilled on PDMS with a puncher before bond onto a glass slide using the plasma treatment. (B) The microfluidic platform for biofilm cultivation consisted of one inlet for the infusion of nutrient broth, one outlet to expel the waste and one cultivation chamber for biofilm cultivation. ............................................................................... 103 Figure 4-2. Biofilm formation and release of extracellular DNA (eDNA) by wild-type C. jejuni strains (i.e., human 10, 81116, ATCC 33560, 87-95, NCTC 11168, 1658, and F38011) under optimal, aerobic and starvation conditions. (A) The level of biofilm formation was evaluated using crystal violet staining. The stained biofilm was released by 95% ethanol and determined by monitoring the value of OD595. The concentration of eDNA during biofilm formation under optimal condition (B), aerobic condition (C) and starvation condition (D) over 3 days was quantified using SYBR Green I dye on the basis of a standard curve generated using a series of 10-fold dilutions of Lambda DNA from 80 µg/ml to 0.156 µg/ml. ........................................... 112 Figure 4-3. Biofilm formation and release of extracellular DNA (eDNA) by wild-type C. jejuni F38011 and the corresponding spoT, recA and flaAB deletion mutants under optimal, aerobic and starvation conditions. (A) The level of biofilm formation was evaluated using crystal violet staining. The stained biofilm was released by 95% ethanol and determined by monitoring the value of OD595. The concentration of eDNA during biofilm formation under optimal condition (B), aerobic condition (C) and starvation condition (D) over 3 days was quantified using SYBR Green I dye on the basis of a standard curve generated using a series of 10-fold dilutions of Lambda DNA from 80 µg/ml to 0.156 µg/ml. ............................................................................ 114 Figure 4-4. The biofilm formation of C. jejuni F38011 complementary strains including spoT, recA, and flaAB under optimal condition. ................................................................................... 115 xxiii  Figure 4-5. The Raman peaks of the microfluidic substrate had no overlap with the peaks of C. jejuni F38011 biofilm. Raman peaks of the microfluidic substrate were labeled as a highlight. 116 Figure 4-6. Confocal micro-Raman spectroscopy monitors the development of C. jejuni biofilm in the microfluidic “lab-on-a-chip” platform. C. jejuni biofilm was cultivated in a microfluidic device, and the chemical composition was determined at 72 h, 120 h, 168 h and 216 h using confocal micro-Raman spectroscopy coupled with a 532-nm laser. (A) Prominent Raman peaks during biofilm formation. (B) Variations in the intensity of the corresponding Raman peaks (746, 918, 968, 1123, 1168, 1370, 1580 and 1643 cm-1) over time. The Raman peaks derived from nucleic acids components (746 and 1580 cm-1) are shown in black color, and the Raman peaks derived from other components (i.e., proteins, lipids, and polysaccharides) are shown in gray color. ........................................................................................................................................... 118 Figure 4-7. Autolysis level of C. jejuni induced by Triton X-100 was significantly higher than that of S. Typhimurium SL1344 and autolysis level had no significant difference among C. jejuni F38011 wild-type, spoT, recA and flaAB deletion mutants. Triton X-100 was dissolved in 0.05 M Tris-HCl to achieve a final concentration of 0.02% (v/v) as the autolysis buffer. Bacterial cells were harvested in the late exponential phase and resuspended in autolysis buffer to 0.3 of OD600. The reduction of OD600 value was measured every 3 min for a total of 90 min using a microplate reader. .......................................................................................................................................... 122 Figure 4-8. The length of DNA fragment present in C. jejuni during biofilm formation was similar to that of genomic DNA extracted from C. jejuni F38011 planktonic cells. Gel electrophoresis was performed to demonstrate the length of the released DNA fragment. After 3-day biofilm cultivation, each bacterial culture in the 96-well plate was collected. A total of 10 µl of the supernatant was mixed with 2 µl of DNA loading dye solution and then loaded on 1% xxiv  agarose gel for electrophoresis. A 1-kb ladder was used as the reference. The DNA was stained using SYBRTM safe DNA gel stain and visualized on ChemiDocTM XRS gel documentation system. ........................................................................................................................................ 124 Figure 4-9. Lysis level of C. jejuni cells was stimulated by aerobic condition and inhibited by starvation condition during biofilm formation. Genomic DNA is an indicator of bacterial lysis. After 3-day biofilm cultivation, the genomic DNA in the supernatant and biofilm of C. jejuni wild-type strain, spoT, recA and flaAB deletion mutant strains were purified. The relative content of genomic DNA in the supernatant and biofilm was individually determined via real-time quantitative PCR (qPCR) using housekeeping gene rpoA. The lysis level was calculated by dividing the genomic DNA content in the supernatant to the sum of genomic DNA content in the supernatant and the biofilm. ........................................................................................................ 125 Figure 4-10. The expression of flaA and flaB genes in C. jejuni F38011 wild-type, spoT and recA deletion mutants was upregulated only at the first day of biofilm formation under aerobic condition. Real-time qPCR was performed to plot the expression profile of flaA and flaB in response to the aerobic condition (A) and starvation condition (B) in C. jejuni F38011 wild-type strain as well as spoT and recA deletion mutant strains. The rpoA gene was used as the internal control. The arbitrary fold change cut-offs were set as more than 2. ......................................... 127 Figure 4-11. Addition of genomic DNA extracted either from Campylobacter or Salmonella had a concentration-dependent stimulation effect on biofilm formation of C. jejuni F38011; the pre-coating layer formed by DNA extracted either from Campylobacter or Salmonella did not contribute to the development of biofilm formation of C. jejuni F38011. Genomic DNA of C. jejuni F38011 or S. Typhimurium SL1344 was separately extracted and added for biofilm formation. To form a pre-coating layer, 200 µl of DNA Salmonella (A) or C. jejuni (B) at xxv  different concentrations was added to each well of the 96-well plate and maintained for 4 h. The unbounded DNA was washed out before the addition of C. jejuni F38011 culture. To directly add DNA for biofilm formation, DNA of Salmonella (C) or C. jejuni (D) was mixed with C. jejuni F38011 culture to a certain final concentration, and 200 µl of this mixed culture was added into the 96-well plate. The plate was then cultivated in a microaerobic environment at 37°C for up to 72 h.............................................................................................................................................. 129 Figure 4-12. DNase I treatment before bacterial initial attachment prevented C. jejuni biofilm formation and DNase I treatment on the well-developed C. jejuni biofilm disrupted biofilm structure, leading to the reduction of biomass. To treat biofilm at the initial attachment stage, DNase I was mixed with C. jejuni culture to a final concentration of 2 units/ml and then added to the 96-well plate for biofilm formation. To treat the well-developed biofilm in the 96-well plate, 200 µl of DNase I solution (2 units/ml) was added into a well with a 3-day cultivated C. jejuni biofilm. The treatment was maintained for 15 min at room temperature. The reduction level of biofilm was evaluated using the aforementioned crystal violet staining assay. Asterisk denotes significant difference (P < 0.05). ................................................................................................ 131 Figure 4-13. Topographic images of C. jejuni F38011 biofilms confirmed that the DNase I treatment disrupted biofilm structure and dispersed encased C. jejuni F38011 cells. The images were obtained by atomic force microscopy in contact mode within 8 µm × 8 µm area at scan frequency of 0.5 Hz: (A) C. jejuni biofilm without DNase I treatment; (B) 3D reconstruction of the untreated C. jejuni biofilm; (C) C. jejuni biofilm after DNase I treatment ; D) 3D reconstruction of the treated C. jejuni biofilm. ........................................................................... 133 Figure 4-14. DNase I treatment reduced the coverage and volume of C. jejuni biofilm. The well-developed (3-day) C. jejuni F38011 biofilm on a nitrocellulose membrane was treated with xxvi  DNase I solution (2 units/ml) for 15 min and then air-dried for the analysis of atomic force microscopy. (A) Coverage reduction caused by DNase I treatment; (B) Volume reduction caused by DNase I treatment. Asterisk denotes significant difference (P < 0.05). ................................ 134 Figure 4-15. Spatial distribution of C. jejuni cells, Salmonella cells and extracellular DNA (eDNA) within a Campylobacter-Salmonella dual-species biofilm formed in the microfluidic platform. Fluorescence microscopy was applied to determine the spatial distribution of eDNA and bacterial cells in a dual-species Campylobacter–Salmonella biofilm. After 3-days cultivation, 30 nM of DAPI solution was injected into the microfluidic device to stain eDNA in the biofilm. Images were collected at multi-channels: 405 nm (blue color for DAPI signal), 488 nm (green color for GFP signal), and 543 nm (red color for RFP signal). Within this Campylobacter-Salmonella dual-species biofilm, C. jejuni cells were mainly located at the bottom while Salmonella cells were mainly located at the top layer. The eDNA mainly assembled and formed several eDNA-rich areas and maintained the spatial distance between C. jejuni and Salmonella in the biofilm. .................................................................................................................................. 136 Figure 4-16. The mutations on flaA and flaB significantly decreased the motility of C. jejuni F38011 while the mutations on spoT or recA did not influence the motility of C. jejuni F38011. A total of 5 µl of the overnight bacterial culture was spotted onto the Brucella media supplemented with 0.4% agar. After 2-day cultivation in microaerobic condition at 37ºC, the halo area was measured. Asterisk denotes significant difference (P < 0.05). ................................................... 140 Figure 5-1. The presence of C. jejuni persister cells was examined by antibiotics over time. The late-exponentially growing culture of C. jejuni was treated with antibiotics (~10 times MIC). The presence of biphasic killing curve indicated that a high tolerant subpopulation could survive the xxvii  antibiotic treatment. (A) Ampicillin treatment at concentration of 100 µg/ml. (B) Ciprofloxacin treatment at concentration of 1 µg/ml. ........................................................................................ 155 Figure 5-2. The hierarchical clustering of genes expression profile of C. jejuni F38011 cells. Each row was referred to a single gene. Each column was referred to a sample or a replicate. The “amp-4h” represented C. jejuni F38011 persister cells isolated by 4 hours ampicillin treatment; “cip-4h” represented C. jejuni F38011 persister cells isolated by 4 hours ciprofloxacin treatment; “control-0h” represented C. jejuni F38011 normal growing cells prior antibiotic treatment; “control-4h” represented C. jejuni F38011 normal growing cells cultivated for 4 hours without antibiotic treatment. .................................................................................................................... 157 Figure 6-1. The individual ajoene treatment could generate a bacteriostatic effect on C. jejuni cocktail at 22°C (A) but a bactericidal effect at 37°C (B). Different colors indicate different samples (red line: control group without treatment; green line: samples treated with DMSO at the concentration of 1 mM; blue line: samples treated with ajoene at the concentration of 0.06 mM; purple line: samples treated with ajoene at the concentration of 0.125 mM; black line: samples treated with ajoene at the concentration of 0.25 mM; orange line: samples treated with ajoene at the concentration of 0.5 mM; light blue line: samples treated with ajoene at the concentration of 1 mM).......................................................................................................................................... 172 Figure 6-2. Synergistic antimicrobial effect of ajoene and metal oxide nanoparticles against C. jejuni at 22°C. Panels: (A) Antimicrobial effect of TiO2 nanoparticles; (B) Antimicrobial effect of Al2O3 nanoparticles; (C) Synergistic antimicrobial effect of 0.06 mM ajoene and TiO2 nanoparticles; and (D) Synergistic antimicrobial effect of 0.06 mM ajoene and Al2O3 nanoparticles. Different symbols indicate different concentrations of metal oxide nanoparticles xxviii  (red line: 0 mM; green line: 0.5 mM; blue line: 1 mM; purple line: 2 mM; black line: 4 mM; orange line: 8 mM; light line: 16 mM). ...................................................................................... 174 Figure 6-3. Synergistic antimicrobial effect of ajoene and metal oxide nanoparticles against C. jejuni at 37°C. Panels: (A) Antimicrobial effect of TiO2 nanoparticles; (B) Antimicrobial effect of Al2O3 nanoparticles; (C) Synergistic antimicrobial effect of 0.06 mM ajoene and TiO2 nanoparticles; and (D) Synergistic antimicrobial effect of 0.06 mM ajoene and Al2O3 nanoparticles. Different symbols indicate different concentrations of metal oxide nanoparticles (red line: 0 mM; green line: 0.5 mM; blue line: 1 mM; purple line: 2 mM; black line: 4 mM; orange line: 8 mM; light blue line: 16 mM). .............................................................................. 175 Figure 6-4. RNA-seq results were validated by qPCR. The expression profiles of these 7 genes were selected as the representatives from the treatment of 1 mM ajoene, 16 mM Al2O3 nanoparticles, 16 mM TiO2 nanoparticles, 0.06 mM ajoene and 4 mM Al2O3 nanoparticles, and 0.06 mM ajoene and 4 mM TiO2 nanoparticles. ......................................................................... 177 Figure 6-5. Transcriptional response of C. jejuni F38011 in response to the different treatments. The differentially expressed genes were categorized on the basis of the functional terms. Panels: (A) Up-regulated genes induced by the treatment of 1 mM ajoene: genes were clustered on the basis of transcription-translation term; (B) Up-regulated genes induced by the treatment of 1 mM ajoene: genes were clustered on the basis of energy utilization term; (C) Down-regulated genes induced by the treatment of 1 mM ajoene: genes were clustered on the basis of integral cell membrane term; and (D) Up-regulated genes induced by the treatment of 16 mM TiO2: genes were clustered on the basis of integral cell membrane term. The clusters are shown in white color in panel (A) and (C) indicated that the differentially expressed genes were absent in the certain functional terms. ......................................................................................................................... 181 xxix  List of supplementary materials Table A-1 was the supplementary material of RNA-seq data for chapter 5. Table A-2 was the supplementary material of RNA-seq data for chapter 6.   Both Table A-1 and Table A-2 were linked to this dissertation in clRcle.    xxx   List of abbreviations AFM – atomic force microscope  AMP - Ampicillin ANOVA – Analysis of variance BLAST – Basic local alignment search tool CCD – Charge-coupled device cDNA – Complementary deoxyribonucleic Acid CFU – Colony forming unit CIP - Ciprofloxacin CJS index – Campylobacter jejuni share index CLSM – Confocal laser scanning microscope Cm - Chloramphenicol CmR – Chloramphenicol resistance Ct – Cycle threshold DAPI – 4',6-diamidino-2-phenylindole DEG – Differentially expressed genes DMSO – Dimethyl sulfoxide DNA – Deoxyribonucleic acid eDNA – Extracellular deoxyribonucleic acid EDTA –Ethylenediaminetetraacetic acid ELISA – Enzyme-linked immunosorbent assay EPS – Extracellular polymeric substance FDA – Food and drug administration xxxi  FDR – False discovery rate GBS – Guillain-Barré syndrome gDNA – genomic DNA GFP – Green fluorescent protein KD – Kilo daltons Kan - Kanamycin KanR – Kanamycin resistance  LB agar/broth – Luria-Bertani agar/broth MDK – Minimum duration of killing  MH agar/broth – Mueller-Hinton agar/broth MIC – Minimum inhibitory concentration mRNA – Messenger ribonucleic acid NC membrane – Nitrocellulose membrane OD – Optical density  PBS – Phosphate buffered saline PCA – Principal component analysis PC – Principal component PCR – Polymerase chain reaction PDMS – Polydimethylsiloxane PI – Propidium iodide PLSR – Partial least-squares regression RFP – Red fluorescent protein  RMS roughness – Root mean square roughness xxxii  RNA – Ribonucleic acid rRNA – Ribosomal ribonucleic acid RNA-seq – Ribonucleic acid sequencing ROS – Reactive oxygen species RT-qPCR – Real-time quantitative polymerase chain reaction SEM – Scanning electron microscopy TCA cycle– Tricarboxylic acid  Tn insertion –Transposon insertion ToF-SIMS – Time-of-flight secondary ion mass spectrometry  TSB – Tryptic soy broth UTI – Urinary tract infections TA system – Toxin-antitoxin system UV-vis – Ultraviolet-visible VBNC state– Viable but non-culturable state XLD agar – Xylose lysine deoxycholate agar   xxxiii  Acknowledgements I want to express my sincere gratitude to my supervisor, Dr. Xiaonan Lu, for his invaluable mentorship, patience, encouragement, and support throughout the time of my Doctor of Philosophy program. His rigorous attitude to research and immense passion for challenges set an example for me to be a good scientist.   I would also like to thank my committee members, Dr. Eunice Li-Chan, Dr. Robert Hancock, and Dr. Jie Xu, who have been providing professional advices and selfless help throughout my research project. Their comments and suggestions remarkably improve the quality of the entire research projects.   I also want to thank the members in Lu’s lab, Dr. Lina Ma, Shaolong Feng, Yaxi Hu, Mohammed Hakeem, Luyao Ma, Jiaqi Li, Gracia Windiasti, Lu Han, Vivian Nie, Gianna Wang, for their technical support, thoughtful help, encouragement, patience, and friendship.   I want to thank the financial support from China Scholarship Council.  Lastly, I would like to thank my family for their endless love and support. They are my core motivation throughout this journey.   xxxiv  Dedication This thesis is dedicated to my family for their endless love and support. 1  Chapter 1: Literature review 1.1 Campylobacter  Campylobacter jejuni has been recognized as one of the leading causes of human gastrointestinal diseases worldwide. In the United States, approximately 1.4-2.3 million cases of Campylobacter infections were reported per year during the past several decades (Samuel et al., 2004). Among the 18 species of Campylobacter identified to date, C. jejuni is responsible for over 80% of Campylobacter-associated illnesses, and C. coli accounts for approximately 10% of the cases. Recently, C. lari is recognized as an emerging species that is responsible for less than 1% of the infection cases (Teh et al., 2014). C. jejuni-mediated diseases, known as campylobacteriosis, generally occurs several days after the ingestion of Campylobacter and are usually featured by fever, nausea, abdominal pain, loose to watery stools containing blood and fecal leukocytes (Butzler and Oosterom, 1991). The infectious dose of C. jejuni can be as low as 500 cells (Wilson et al., 2008). Campylobacteriosis is one of the most frequently reported foodborne illnesses in Canada, outnumbering the cases caused by other common foodborne pathogens, such as Listeria monocytogenes, Salmonella, and Shiga toxigenic Escherichia coli (Kalmokoff et al., 2006). According to a report from European Center for Disease Prevention and Control, campylobacteriosis remained to be the most reported zoonotic infection in humans in Europe since 2005 (Team, 2012). Campylobacteriosis usually is self-limiting, but up to 10% of the cases require medical intervention, and the symptoms can last for several weeks. Severe chronic sequelae of campylobacteriosis shows a close association with a high incidence of Guillain-Barré syndrome (GBS), an autoimmune disease as one of the leading causes of flaccid paralysis in the post-polio era. Poultry product is the primary source of foodborne Campylobacter infections due to poor processing practice or direct contamination of raw 2  materials (Bryan and Doyle, 1995). It was estimated that C. jejuni contaminated over 90% of the domestic chicken carcasses at the time of sale (Kramer et al., 2000).  The paradox associated with C. jejuni is that this microbe is frequently isolated from food products and difficult to remove from the agri-food systems; however, C. jejuni is a microaerophilic bacterium and regarded as fragile towards the stresses. It is challenging for C. jejuni to survive in the aerobic environment (Park, 2002; Young et al., 2007). The understanding of the survival mechanism of C. jejuni in the unfavorable environment is of highly interest.  Bacterial stress response system is one of the most well recognized survival strategies that facilitate C. jejuni to adapt to and survive under different stress conditions. C. jejuni has various stress response systems that are regulated by different regulators, such as the heat-shock response regulator dnaK (Thies et al., 1999), the stringent response regulator spoT (Gaynor et al., 2005), and oxidative stress regulators csrA and ahpC (Baillon et al., 1999; Fields and Thompson, 2008). Moreover, C. jejuni can form a mono-species biofilm or reside in the multi-species biofilm. C. jejuni cells residing in a biofilm matrix are more tolerant to the stresses than its planktonic state (Reeser et al., 2007; Ica et al., 2012). In the natural environment, biofilms may arise in water supplies and plumbing systems of animal husbandry facilities and food processing plants, which may explain the prevalence of C. jejuni in the food system either directly or indirectly via farm animals (Buswell et al., 1998; Siringan et al., 2011). In addition, C. jejuni cells were identified to enter a state with a low metabolic activity that is highly tolerant to the environmental stresses as well as antimicrobial treatments (Cappelier et al., 1999a; Cappelier et al., 1999b).  3  1.2 Survival mechanism of C. jejuni  1.2.1 Bacterial stress response In the natural environment, bacteria struggle with various stresses, such as temperature fluctuation, nutrient deficiency, availability of oxygen and the presence of toxic chemicals. Bacterial survival is the process of adaptation to these environmental stresses. Bacterial stress response system enables bacteria to respond to stresses by regulating the expression of metabolically associated genes, such as heat-shock response, cold-shock response, oxidative response, and stringent response. The specific regulations of stress response system in different bacteria vary significantly. For example, the oxidative stress response of microaerophilic bacteria is more complex than that of aerobic bacteria. Typically, bacterial stress response systems follow several distinctive regulatory patterns: (1) Stress response is mediated by sigma factors (σ factor), a protein that serves as a transcription initiation factor for the synthesis of RNA. Sigma factors are activated by stresses. They will specifically recognize and interact with the promoter of stress-associated genes to regulate the transcription. For example, sigma factors sigH is responsible for the regulation of heat shock in Mycobacterium tuberculosis. The heat shock response is triggered by high temperature. The activation of sigH will specifically recognize and positively regulate the expression of heat shock genes dnak and clpB, which enables M. tuberculosis to adapt to the high-temperature environment (Raman et al., 2001); (2) DNA repressors mediate bacterial stress response by binding to DNA controlling element and regulating the expression profile of associated genes. For example, Bacillus subtilis contains a transcriptional repressor hrcA, which can bind to DNA controlling element via a helix-turn-helix motif. The hrcA is triggered in response to heat shock and it will in turn conduct transcriptional regulation on heat-shock operons dnaK and groESL (Wiegert and Schumann, 2003); (3) Stress 4  response can be mediated by intracellular proteolysis. For example, inner membrane protein RseA is the central regulatory factor of signal transduction cascade in E. coli. The extracytoplasmic stress can induce proteolysis of RseA that rapidly activates the stress response (Ades et al., 1999); (4) Small RNAs can regulate bacterial stress response. Small RNAs are a type of non-coding RNA in the range of 50-250 nucleotides. Some small RNAs can specifically target at the mRNAs of stress response regulons, which stimulates or inhibits the translation. Many well-recognized stress response regulons in E. coli are identified under the regulation of small RNAs. For example, RyhB 90-nt RNA is responsible for bacterial response to iron starvation. RyhB 90-nt RNA will inhibit the translation of a set of iron-storage and iron-usage genes in response to the low availability of iron. This process is critical for E. coli to adapt to iron starvation (Massé and Gottesman, 2002).  C. jejuni possesses essential stress response operons that enable the survival of this microbe under different stress conditions, but not all well-recognized stress response operons have been identified in C. jejuni (Table 1-1). In the natural environment, both high oxygen level (~21% oxygen) and starvation (nutrient deficiency) are the primary negative factors on the survival of C. jejuni. Hence, both oxidative stress response and starvation response are critical to the survival and fitness of C. jejuni in the environment and agri-food systems.    5  Table 1-1. Summary of critical stress response genes that are present in other model bacterial species but absent in C. jejuni (Park, 2002)  Genes  Functions Distribution   C. jejuni E. coli B. subtilis Oxidative stress  soxRS positively regulates the response to superoxide stress - + - oxyR positively regulates the response to peroxide stress  - + - sodA Manganese cofactor of superoxide dismutase in response to superoxide stress   - + + katG catalase-peroxidase in response to peroxide stress - + - Osmotic stress     proU or opuC Osmotic regulatory uptake of compatible solutes  - + + osAB synthesis of osmotic regulatory trehalose - + - betAB or gbsAB synthesis of osmotic regulatory choline-glycine betaine pathway - + + 6  Genes  Functions Distribution     C. jejuni E. coli B. subtilis Starvation      rpoS sigma factor is involved in stationary phase and general stress  - + - relA stringent response regulator is involved in response to amino acid, glucose, and oxygen starvation  - + + Heat and cold shock     rpoH alternative sigma factor regulates the response to heat shock - + - cspA essential protein for cold shock - + + Global regulation     lrp Global regulator for general metabolism - + + “-“ indicates the absence of specific gene in the corresponding bacteria; “+“ indicates the presence of specific gene in the corresponding bacteria  1.2.1.1 Response of C. jejuni to starvation  Individual nutrient deficiency can trigger the starvation response. In response to starvation, Bacteria conduct a series of physiological regulations, such as low metabolic activity, delayed growth, occurrence of proteolysis (Moore, 2001) and the shrink of cell volume (Dykes et al., 7  2003). The activation of the starvation response not only increases the bacterial adaptation to the nutrient-limited environment, but also elevates bacterial tolerance to a wide range of stresses, such as heat shock, oxidative stress, and osmotic stress (Rees et al., 1995). Hence, the starvation response is critical to the fitness and adaption of bacteria in the unfavorable environment. Most of the Gram-negative bacteria contain sigma factor rpoS and homolog of relA/spoT were the regulators that responsible for the starvation response (Loewen et al., 1998). However, both sigma factor rpoS and relA homolog are absent in the genome of C. jejuni model strain NCTC 11168 (Parkhill et al., 2000). The absence of these two sigma factors might be the reason why most of C. jejuni strains are more susceptible to heat shock and oxidative stress in the stationary phase and nutrient-deprived environment than other bacteria (Kelly, 2001). Currently, spoT is the only well-characterized general regulator in C. jejuni that is responsible for the stringent response. The spoT-mediated response is critical for C. jejuni to survive under the nutrient-deprived or high oxygen level environment (Gaynor et al., 2005).    1.2.1.2 Response of C. jejuni to oxidative stress  Exposure to a high oxygen environment can induce the generation and accumulation of reactive oxygen species (ROS) in bacteria, which will impact the intracellular redox balance and subsequently damage the intercellular biomacromolecules (e.g., lipids, nucleic acids, and proteins). Accordingly, bacteria have a series of responses that can neutralize ROS, reduce the oxidative stress and repair the damage. As a microaerophilic bacterium, C. jejuni can grow in the presence of a certain level of oxygen. The adaption to aerobic metabolisms indicates that C. jejuni possesses inherent cellular defense against the oxidative stress (Jones et al., 1993). C. jejuni contains three enzymes that have been identified to be essential for antioxidant, including 8  superoxide dismutase encoded by sodB (Pesci et al., 1994), catalase encoded by katA (Grant and Park, 1995), and alkyl hydroperoxide reductase encoded by ahpC (Baillon et al., 1999). The regulatory pattern of these genes was well recognized in E. coli. Both soxRS and oxyR were identified to be involved in the antioxidant of E. coli. Specifically, the soxRS regulons are responsible for the neutralization of superoxide or nitric oxide stress (Greenberg et al., 1990; Nunoshiba et al., 1992) while the oxyR regulon is responsible for the neutralization of peroxide stress (Storz and Imlayt, 1999). However, these oxidative stress regulators and their homologs have not been identified in C. jejuni yet. Instead, C. jejuni possesses several alternative regulators to combat the oxidative stress. For example, C. jejuni contains perR that can sense and respond to the peroxide stress. Transcriptomic analysis indicated that perR regulon can conduct the regulation of a total of 104 genes involved in a variety of physiological metabolisms, including energy metabolism, DNA repair, multidrug efflux pumps and synthesis of antioxidants (Palyada et al., 2009). In addition, several putative regulons, such as cosR (Hwang et al., 2011) and csrA (Fields and Thompson, 2008) have also be identified in C. jejuni that can mediate its response to oxidative stress.   1.2.2 Biofilm formation of C. jejuni  1.2.2.1 Overview of bacterial biofilms In the natural environment, bacteria typically survive as a community, such as films, mats, sludge or biofilms, rather than as dispersed single cells (Joshua et al., 2006). Previous studies indicated that biofilm formation was a dynamic biological cycle, including several distinct stages (Figure 1-1): (1) initial attachment: planktonic cells attach to a substrate; (2) irreversible attachment: the attached cells are immobilized; (3)-(4) maturation and maintenance: bacterial 9  cells multiply and continuously secrete extracellular polymer substances (EPS) to develop the biofilm from a thin mono-layer to a thick multi-layer structure; (5) dispersal: biofilm structure breaks down and the sessile bacterial cells are released into the environment to colonize new sites.    10   Figure 1-1. The schematic figures demonstrate distinct stages of biofilm formation. Stage 1 initial attachment: bacteria attach to the substrate; Stage 2  irreversible attachment: the initial attachment is reinforced; Stage 3: bacteria start secreting extracellular polymeric substances (EPS) that lead to the formation of a thin mono-layer biofilm structure; Stage 4 biofilm maturation: bacteria multiply and progressively secrete EPS that lead to the formation of a thick multi-layer biofilm structure; Stage 5 biofilm dispersal: the structure of biofilm is broken down, and cells in the biofilm are released and dispersed into the environment to colonize new sites. The photograph is derived from a developing biofilm by Pseudomonas aeruginosa (Monroe, 2007).   11  Initial attachment is critical for biofilm formation and can be influenced by many factors, such as mechanical properties of the substrate, hydrodynamic condition of the environment, metabolic activity of bacteria cells and the presence of adherence organelles (e.g., flagella, pili, and capsules). For example, hydrophobic substrate with a rough surface is more likely to facilitate bacterial attachment. In addition, the pre-coating of biomacromolecules (e.g., nucleic acids, proteins, lipids, and polysaccharides) on the substrate also contributes to the immobilization of bacterial cells. In contrast, the presence of surfactants that reduce the surface hydrophobicity will prevent the bacterial attachment (Chae et al., 2006; Patel et al., 2007; Simões et al., 2008). Hydrodynamic condition is a critical environmental factor that influences bacterial initial attachment. For example, both high flow velocity (e.g., turbulent flow) and strong shear force can prevent the initial attachment by washing the reversibly attached cells away from the substrate (Stoodley et al., 1999; Simões et al., 2007). Moreover, bacteria contain adherence organelles (e.g., flagella and pili) and produce EPS that can contribute to bacterial attachment (Pratt and Kolter, 1998; Vatanyoopaisarn et al., 2000; Parsek and Greenberg, 2005). The factors that influence bacterial initial attachment are summarized in Table 1-2.   12  Table 1-2. Summary of factors that affect biofilm initial attachment (Donlan, 2002). Adhesion surface Fluidic environment Bacterial cell texture or roughness   fluidic velocity cell surface hydrophobicity  hydrophobicity  liquid pH extracellular organelles (i.e. flagella) surface chemistry  temperature  extracellular polymeric substances surface charge presence of antimicrobials quorum sensing surface conditioning  cations cell surface charge  1.2.2.2 Hydrodynamic condition, bacterial physiological properties, EPS and biofilms In the natural environment, biofilm formation is usually identified in hydrodynamic condition. However, in most of the studies, biofilms were cultivated in static conditions, such as in a 96-well microplate, in a glass tube, or on different packaging materials. The static cultivation cannot include the influence of shear flow and nutrient exchange on biofilm formation. In contrast, hydrodynamic cultivation can simulate the real hydrodynamic condition as natural settings for biofilm formation (Purevdorj et al., 2002; Kirisits et al., 2007). For example, the biofilm formation of rpoS-deficient E. coli in a flow condition demonstrated a considerable difference compared to that in static cultivation. The structure variation between the biofilms formed in hydrodynamic condition and that in static condition might be associated with a few factors. For example, continuous flow prevented the accumulation of cell signaling molecules, impaired the quorum sensing effect, and subsequently inhibited the biofilm formation (Ito et al., 2008). Several commercially available macro-scale flow chambers have been applied in the 13  studies of bacterial biofilms. However, most of these flow chambers shared similar disadvantages, such as inaccurate control of hydrodynamic parameters, consumption of large volumes of reagents, and low compatibility to advanced detection techniques (Ica et al., 2012). “Lab-on-a-chip” is also known as microfluidic chip when it applied small volumes of fluids to interconnect various laboratory functions on a single integrated chip. Compared to macro-scale chambers, microfluidic chips demonstrate numerous advantages, such as precise and high-efficient control of hydrodynamic parameters, consumption of small volumes of reagents, flexibility of customized design and high compatibility to different detection and characterization techniques. All of these make microfluidic chips to be a desired platform for the cultivation and characterization of bacterial biofilms (Kim et al., 2012). The surface hydrophobicity and adherence organelles of bacteria (e.g., hydrophobicity and extracellular filamentous appendages) are critical factors that can influence bacterial biofilm formation. The chemical composition of the bacterial cell membrane is related to the surface hydrophobicity. Moreover, both bacterial aggregation and attachment are highly dependent upon hydrophobic interactions. A high proportion of non-polar hydrophobic domains on bacterial surface can enhance the initial attachment of bacteria to the substrate due to the strong hydrophobic interaction between bacteria and the adhesion surface (Donlan, 2002).  Bacteria have different types of extracellular organelles, such as flagella, pili, capsule, and fimbriae, all of which are responsible for bacterial adherence and motility. Flagella are helical structures that originate from cytoplasm and extend through the cell wall and are responsible for bacterial motility. Flagella can generate a driving force to overcome the repulsive force during bacterial attachment (Fang et al., 2000; Donlan, 2002). In addition, flagellum can bind to both biotic and abiotic materials by forming adhesive interactions (Newell et al., 1985; 14  Vatanyoopaisarn et al., 2000). Other filamentous appendages, such as pili and fimbriae, also demonstrate adherence capability. Previous studies indicated that pili and pilus could generate electrostatic adsorption in certain environment to bind bacterial cell onto the substrate (Keizer et al., 2001; Craig et al., 2006). Hence, bacteria with adherence organelles usually have a better attachment than those without adherence organelles (Sauer et al., 2000).  EPS are the major constituents of biofilm and account for up to 90% of total volume of biofilm (Røder et al., 2016). EPS are comprised of macromolecules, such as polysaccharides, nucleic acids, proteins, and lipids. The composition of EPS in different bacterial biofilms extensively varies from each other. For example, exopolysaccharides and proteins are the major components of EPS in biofilms formed by E. coli, Staphylococcus, Streptococcus and Vibrio (Vu et al., 2009). One previous study reported that 75-89% of the EPS are comprised of exopolysaccharides and proteins (Tsuneda et al., 2003). In some cases, extracellular DNA is the major constituents of biofilm EPS, such as P. aruguinosa biofilm (Whitchurch et al., 2002), although the specific role of these individual EPS molecules is not fully clear yet. EPS demonstrate various physiological advantages for the survival of bacteria in biofilms, such as storage of nutrient, maintenance of hydration, prevention and inhibition of the penetration of antimicrobials (Sutherland, 2001; Davies, 2003). Hence, identification and characterization of EPS components provide insights into understanding the mechanism of the protection of biofilm to the encased bacteria.  The identification and characterization of EPS is highly dependent on the isolation methods. Centrifugation, filtration, sonication and enzymatic treatment are the commonly used methods for the isolation of EPS from bacterial biofilms. Ion exchange resin is also applied under certain circumstances to isolate proteins and carbohydrates from EPS (Tapia et al., 2009). However, 15  most of these isolation methods can only extract specific components. In addition, some EPS fractions are tightly bound to bacterial cells. Harsh extraction procedures may damage cell membrane and introduce artifacts due to the release of bacterial intracellular substances. For example, extraction using high concentration of sodium hydroxide released cytoplasmic components into the extracts (Brown and Lester, 1980).  Staining is an alternative method that has been applied to investigate the chemical compositions of EPS and their spatial distribution within a biofilm. Crystal violet (CV) is one of the well recognized staining methods that can nonspecifically stain EPS as well as the sessile bacterial cells in the biofilms. The result of CV staining can only reflect the formation level of a biofilm but not the chemical composition of EPS (Reeser et al., 2007). Confocal laser scanning microscope (CLSM) coupled with fluorescent dyes is another important tool for in-situ identification of specific EPS compositions in the biofilms. In addition, CLSM can also be used to investigate the viability of the encased cells in biofilms when it is coupled with live/dead bacterial cell staining (SYTO 9 for live cells and propidium iodide for dead cells) (Joshua et al., 2006). Other advanced techniques, such as super-resolution imaging, also demonstrate the potential for the study of bacterial biofilm (Berk et al., 2012). However, none of these aforementioned techniques can identify and characterize biofilm EPS in a non-destructive manner. Raman spectroscopy can determine the chemical composition of a biological system without any sample preparation. When it is coupled with a confocal microscope and a digital stage for mapping, Raman spectroscopy can be used to determine the chemical composition in-situ (Ivleva et al., 2008) as well as the spatial distribution (Ivleva et al., 2009) within a biofilm in a non-destructive manner. 16  The structure of biofilm can influence the survival of the bacterial cells in the biofilms. For example, the compacted multi-layer EPS can usually lead to the development of a thick biofilm that efficiently delays the penetration and diffusion of antimicrobials (Mah and O'Toole, 2001). In addition, a biofilm with compacted structure will more likely to have a good water holding capacity which is critical to the survival of bacterial cells in the biofilms under desiccation. (Tang et al., 2011). Biomechanical properties of EPS are closely associated with the biofilm structure. Therefore, the biomechanical profiles of EPS will be valuable for the characterization of a bacterial biofilm. Atomic force microscopy (AFM) is one of the promising tools that can investigate the topographic information of a biological sample (e.g., a biofilm) in the scale of nanometers. In addition, AFM can also be applied to determine the mechanical properties of biological samples. Several studies have successfully characterized a series of mechanical parameters of bacterial biofilms using AFM, including cohesive strength, hydrophobicity, and surface elasticity (Ahimou et al., 2007; Scheuring and Dufrêne, 2010).   1.2.2.3 Campylobacter biofilms Campylobacter can form biofilms on different materials, such as stainless steel, glass and plastics (Dykes et al., 2003; Asakura et al., 2007b). The capability of biofilm formation is different among various Campylobacter species (Sulaeman et al., 2010) and strains (Kim et al., 2017). For example, both clinical isolates C. jejuni F38011 (Feng et al., 2016) and NCTC 11168 (Kalmokoff et al., 2006) can form relatively intensive biofilms under different environmental conditions. In contrast, C. jejuni strain RM 1221 can barely form a biofilm even under the optimal laboratory condition (Brown et al., 2015b).   17  Biofilm formation of C. jejuni is influenced by various factors. A previous study reported that the formation of C. jejuni biofilm was significantly inhibited under thermophilic and high osmotic conditions (Reeser et al., 2007). Reuter and colleagues identified that C. jejuni developed a biofilm more rapidly under the aerobic condition than that under the microaerobic condition (Reuter et al., 2010), and this observation was recently confirmed by another study (Turonova et al., 2015). In addition, food residues, such as chicken juice (Brown et al., 2014) and pork juice (Li et al., 2017), could also enhance the formation of C. jejuni biofilms. Molecular understanding of C. jejuni biofilm formation is still in its infancy, even though several genes have been identified to regulate biofilm formation, such as the flagella synthesis genes and stress response genes (Kalmokoff et al., 2006; Reeser et al., 2007; Svensson et al., 2014). Reeser and others identified that the biofilm formation by flagella knockout mutant (ΔflaAB) of C. jejuni was significantly lower compared to that of the wild-type counterpart (Reeser et al., 2007). Furthermore, the genes responsible for survival during stationary phase or under the starvation condition also influence the biofilm formation of C. jejuni. Deletion of these genes could increase the formation level of C. jejuni biofilms (Candon et al., 2007; McLennan et al., 2008). Campylobacter can co-develop a biofilm with other bacteria. A previous study reported that a mixture of C. jejuni, Enterococcus faecalis, and Staphylococcus simulans could develop an intensive multi-species biofilm (Teh et al., 2010). Multi-species Campylobacter biofilms and mono-species Campylobacter biofilms are significantly different from physiological and mechanical perspectives (Teh et al., 2014). For example, mono-species C. jejuni biofilms consumed less oxygen and were more susceptible to strong shear stress compared to that of multi-species C. jejuni biofilms (Ica et al., 2012). Another study identified that Campylobacter 18  could co-exist with P. aeruginosa in a dual-species biofilm. The formation level of this multi-species biofilm was significantly higher than that of mono-species C. jejuni biofilm (Hilbert et al., 2010).  Besides forming a biofilm alone, C. jejuni can also reside in a pre-established biofilm. Hanning and colleagues inoculated C. jejuni in the mature biofilms isolated from a poultry farm. C. jejuni cells could survive for a longer time in this biofilm under aerobic condition compared to that as the planktonic cells (Hanning et al., 2008). In another study, Trachoo and others validated that C. jejuni could reside in a multi-species biofilm isolated from a poultry house. C. jejuni cells in this multi-species biofilm could withstand a dramatic temperature fluctuation (i.e., 12°C and 23°C) and maintained their viability over a week (Trachoo et al., 2002). A similar result was obtained in another study that C. jejuni could be incorporated into the biofilm formed by aquatic microorganisms. Within this biofilm, C. jejuni could survive a longer period under stresses compared to floating single cells (Buswell et al., 1998).   1.2.3 Campylobacter dormancy 1.2.3.1 Overview of bacterial dormancy The survival of bacteria in nature is usually challenged by various stresses, such as high oxygen condition, desiccation, temperature fluctuation and the presence of antimicrobial compounds. Bacteria can accordingly develop different survival strategies to adapt to these stresses. Bacterial dormancy is a period that bacteria minimize the metabolic activity and stop the growth (Lewis, 2007). Entering an inactive state will aid bacteria in conserving energy and withstanding different types of stresses. As a result, the dormant bacteria are difficult to be eradicated, potentially leading to the recurrent human infections, such as E. coli-associated 19  urinary tract infections (UTI) (Jacobsen et al., 2008) and Mycobacterium tuberculosis-associated lung diseases (Parrish et al., 1998).  Bacterial persisters and bacterial “viable but non-culturable state” (VBNC) are two well-known types of bacterial dormancy. Both persister cells and VBNC cells demonstrate high tolerance against antimicrobial treatment as well as environmental stresses. A recent review paper drafted by Ayrapetyan and others for the first time argued that these two types of bacterial dormancy are closely related to each other as part of the “dormancy continuum” (Ayrapetyan et al., 2015). For example, both persister cells and VBNC cells were identified at a high level in similar conditions, such as in the microenvironment of a biofilm (e.g., low oxygen, high acidity and limited nutrients) (Stewart and Franklin, 2008). It was suspected that bacteria cells might firstly turn into persisters in response to a short period of stress and then enter VBNC state if the stress is maintained for an elevated period. According to a previous study, the viability of the encased bacterial cells in the biofilm progressively switched from the culturable state (i.e., normal growing cells and persister cells) to non-culturable state (VBNC cells) under a long-term exposure to stress, indicating the transition from normal growing cells and persister cells to VBNC cells (Feng et al., 2016). The relationship between biofilms, VBNC cells, and persister cells is summarized in Figure 1-2.  20   Figure 1-2. The stressful microenvironment of biofilm stimulates the transition of bacteria from the normal growing cells to VBNC and persister cells: (1) VBNC cells and persister cells stochastically present in planktonic culture at low level; (2) environmental stresses (i.e., starvation, oxidative stress, temperature fluctuation) can induce the transition of bacteria from normal growing cells to VBNC and persister cells; (3) the microenvironment of biofilm is acidic and has limited oxygen, which can also stimulate the transition of bacteria from the normal growing cells to VBNC and persister cells (Ayrapetyan et al., 2015).   1.2.3.2 Persister cells Bacterial cells can survive under the antibiotic treatment without developing resistance. These cells are known as persisters or persister cells. Generally, persisters are a small fraction of the bacterial population. In some case, persisters can account for approximately 1% of the total population (Keren et al., 2004b). The number of persister cells in a specific bacterial population might vary significantly due to different growth states (i.e., lag phase, log phase, stationary phase, and death phase) and cultivation conditions. For example, persister cells comprise only a small 21  proportion of exponentially growing bacterial cells. In contrast, the ratio and the amount of the persister cells can be high in the population at stationary phase as well as in a biofilm (Wood et al., 2013).  Persister cells were firstly identified from S. aureus, in which ~1% of the S. aureus cells survived under the treatment by lethal-dose penicillin. The survived cells were able to restore the population after the removal of penicillin without acquiring resistance (Lewis, 2010). Compared to antibiotic-resistant cells whose resistance capacity is due to genetic mutation, persister cells have the identical genetic background to the normal growing cells. It was proposed that persisters were in a dormancy state. Due to the slow growth and low metabolic activity, they were more tolerant to antibiotic treatment compared to the normally growing cells (Lewis, 2012). Brauner and colleagues systematically analyzed and discussed the difference between antibiotic-resistant cells and persister cells (Brauner et al., 2016). The mechanism of resistance was mainly due to the mutation of antibiotic binding targets. In contrast, persister cells still contain the active antibiotic-binding targets. Hence, the tolerance of persister cells must occur due to a distinctive mechanism. Two critical parameters, namely minimum inhibitory concentration (MIC) and minimum duration of killing (MDK), can be used to differentiate between normal growing cells, resistant cells and persister cells (Figure 1-3). Persister cells shared the similar MIC and MDK99 (minimal duration required to kill 99% of the cells) as that of the normal growing cells when they were challenged using antibiotics. The complete inactivation of persister cells required a more extended period of treatment, leading to a higher MDK99.99 (minimal duration required to kill 99.99% of the cells) than that of the normal growing cells. Accordingly, the killing curve of persister cells under antibiotic treatment follows an obvious biphasic killing curve with a distinctive survival plateau. Theoretically, resistant bactterial cells could grow in the presence of 22  antibiotics. Hence, the MIC of resistant cells will be much higher than that of persister cells as well as normal growing cells.    23   Figure 1-3. Time-kill kinetics of resistant cells, tolerant cells and persister cells challenged using antibiotic treatment. The antibiotic susceptibility of these cells is totally different. a) The minimum inhibitory concentration (MIC) of resistant cells is substantially higher than that of the susceptible cells. Colored wells represent the growth of bacterial cells, whereas wells in light brown represent the complete inhibition of bacterial growth due to the presence of antibiotics. b) MIC of the tolerant cells is almost the same as that of the susceptible cells; however, the MDK99 (minimum duration for killing 99% of bacterial cells in the population) of tolerant cells is substantially higher than that of the susceptible cells. c) The population of persister cells comprises a fraction of susceptible cells and a faction of tolerant cells. Hence, MIC and MDK99 of persister population is almost the same as that of the susceptible cells. However, the MDK99.99 of persister cells is substantially higher than that of the susceptible cells. Concentrations and timescales are selected for illustration purposes only (Brauner et al., 2016). 24  The mechanism of the formation of persister cells has not been well characterized yet (Lewis, 2010). Currently, two possible mechanisms have been proposed, including the stochastic mechanism and the responsive mechanism (Harms et al., 2016).  Many bacteria have evolved a stochastic protection mechanism, known as bet-hedging strategy, to increase their fitness in stresses, such as lethal dose of antibiotic treatment, high level of oxidative stress and dramatic temperature fluctuation (Veening et al., 2008a; Veening et al., 2008b). For example, the bet-hedging strategy was responsible for the sporulation of B. subtilis which ensured the preservation of clonal lineage under stresses (Chung et al., 1994; González-Pastor et al., 2003; Maamar et al., 2007). Bacterial persistence have been documented as an example of a bacterial bet-hedging strategy. Because persister cells are phenotypic variants of normal growing cells which have the identical genetic background as their kin population. In addition, the switch from normal growing cells to persister cells usually occur stochastically. It is reasonable to believe that the stochastic mechanism can possibly lead to the formation of persister cells (Keren et al., 2004b; Germain et al., 2015).   Bacteria can adapt to and survive in adverse environment by adjusting metabolism, and this process is known as an active response (Chung et al., 1994). The responsive mechanisms of the formation of persister cells depend upon the active response. Transposon (Tn) insertion mutation is one efficient method to investigate the active response associated persister cells formation by screening the candidate genes, predicting the corresponding functions, and analyzing the metabolic pathways. The application of Tn for S. aureus persister cells identified 13 genes that were mainly distributed among the metabolism of oxidative phosphorylation, tricarboxylic acid (TCA) cycle, cell cycle, and glycolysis. The insertion mutation of these genes could significantly reduce the formation level of S. aureus persister cells (Wang et al., 2015). A 25  similar experiment was conducted for E. coli persister cells. The application of Tn sequencing revealed a set of genes involved in motility and amino acid biosynthesis that were closely associated with the formation of gentamicin-tolerant persister cells. Deletion of these genes significantly reduced the formation level of E. coli persister cells but did not influence the MIC of the mutants against gentamicin (Shan et al., 2015). The size of Tn mutant library is important for the screening of the candidate genes. A small set of Tn mutant library only contains the representative genes or region of interest which may loss critical genes or relevant regions. Keio collection could significantly improve the efficiency and accuracy of Tn screening by generating a large size of the mutant library. Hansen and colleagues applied Keio collection to investigate the candidate genes for the formation of E. coli persister cells. They generated a library of 3985 E. coli deletion strains and identified that most of the candidate genes were global regulators, such as dnaKJ (chaperones), hns (global regulator), and dksA (regulator of rRNA transcription). This study provided supporting evidence to the responsive mechanism of the formation of persister cells (Hansen et al., 2008).  The influence of toxin-antitoxin (TA) systems on the formation of persister cells is another supporting evidence to the responsive mechanism. TA systems comprise a pair of closely linked genes to encode a stable “toxin” protein and a cognate “antitoxin” (protein for type II, IV, V TA system; antisense RNA for type I, III TA system). The concept of TA systems is originally identified in plasmids as a gene-stable and transferable element that enables the daughter generations to inherit plasmid after cell division. The absence of plasmid will induce the degradation of antitoxin and the release of toxin. The released toxin will then kill the dividing cells, known as post-segregational killing (Hayes, 2003). TA systems have been correlated to the formation of persister cells. Keren and colleagues applied transcriptome analysis to plot the gene 26  expression profile of E. coli persister cells. The expression of RelE toxin was significantly higher in E. coli persister cells than that in the normal growing cells (Keren et al., 2004a). Another transcriptome analysis showed a similar result that the overexpression of MazF toxin was along with a higher formation level of persister cells (Vázquez-Laslop et al., 2006). Although the activation of TA systems was usually under the control of transcriptional and post-transcriptional regulations, the details of different regulations might vary due to different types of TA systems. For example, the type I TA system tisAB in E. coli is under the control of SOS response. The deletion mutation on this SOS-TA locus (tisAB-istR) could significantly increase the formation level of persister cells (Dörr et al., 2010). In addition, the type II TA systems can be activated by intercellular proteolysis (degradation by intracellular proteases, such as Lon and ClpP) (Brzozowska and Zielenkiewicz, 2013). Generally, the release of toxins can adjust bacterial physiology and induce bacteriostatic growth state that enhances the tolerance of cells against antibiotics. However, deletion mutation of a single TA locus did not show any persisters-like phenotype, indicating that individual TA system only had considerable influence on the formation of persister cells (Hansen et al., 2008; De Groote et al., 2009). Conlon and colleagues recently confirmed this hypothesis using a 10 TA loci deletion mutant of E. coli. They observed a cumulative decrease of the formation of persister cells along with the progressive deletion of these 10 TA (Conlon et al., 2016). Therefore, there may be a synergistic effect among different TA loci that together influence the formation of persister cells.   1.2.3.3 VBNC cells Bacteria can enter a dormant state, called “viable but non-culturable” (VBNC) state. VBNC cells are alive but cannot form colonies on the routine laboratory media (Oliver, 2005). 27  VBNC cells are typically more tolerant to different stresses, such as starvation, temperature fluctuation, and oxidative stress, than the normal growing cells. VBNC cells have a low metabolic activity as characterized by the reduction of nutrient transport, weak respiration and low level of biosynthesis (Oliver and Bockian, 1995). Compared to the dead cells, VBNC cells have a much higher level of free adenosine triphosphate (ATP), indicating that VBNC cells are still alive (Tholozan et al., 1999).  Currently, the investigation of VBNC cells is still in its infancy. The investigation of molecular perspectives has identified several candidate genes that can influence the formation of VBNC E. coli O157:H7 cells, including stx1, rfbE, mobA and 16S rRNA genes (Yaron and Matthews, 2002). A comprehensive transcriptome analysis of Vibrio cholerae persister cells demonstrated that toxic (e.g., ctxAB, rtxA and hlyA) and virulence (e.g., tcpA and TTSS) genes were still expressed in its VBNC state (Vora et al., 2005). Thus, VBNC pathogenic cells are regarded as virulent. This statement was supported by another study in which enterotoxigenic E. coli H10407 was identified to produce enterotoxin and retain pathogenicity in the VBNC state (Pommepuy et al., 1996).    1.2.3.4 Campylobacter persister cells and VBNC cells The existence of Campylobacter persister cells has not been reported yet. However, VBNC state of Campylobacter cells has been identified and reported in the previous studies. Tholozan and coauthors reported that C. jejuni was able to survive in the microcosm water in VBNC state. The subsequent analysis revealed that these C. jejuni VBNC cells demonstrated a lower membrane potential and internal potassium content than that of the normal growing cells (Tholozan et al., 1999). In another study, normal growing C. jejuni cells were identified to turn 28  into VBNC cells during the incubation in phosphate buffered saline at 4°C (Magajna and Schraft, 2015b). In addition, starvation and low temperature were more efficient to induce the normal growing C. jejuni cells to enter VBNC state (Magajna and Schraft, 2015a).   1.3 Linkage of Campylobacter dormancy and biofilm formation to food safety Campylobacter can survive a longer period in the biofilm or in the dormant state (i.e., VBNC cells and persister cells) compared to the normal growing single cells. This indicates the potential health risk of C. jejuni biofilm and dormant cells. Currently, the linkage between Campylobacter dormancy (i.e., VBNC cells and persister cells) and biofilm formation was not clear yet. The microenvironment in the biofilm is able to induce the formation of persister cells and VBNC states of bacteria. For example, the microenvironment in biofilm has limited nutrients and is highly acidic, both of which could induce the formation of dormant Campylobacter cells. Therefore, biofilm is supposed to be one of the important reservoirs that not only induces the formation of dormant Campylobacter cells but also offers additional protection to the encased dormant cells against various stress conditions (Ayrapetyan et al., 2015).  Epidemiological studies have revealed that many campylobacteriosis cases are linked to the poor processing practice and cross-contamination of poultry products. Fresh produce is recently reported to be responsible for a relatively large amount of campylobacteriosis cases (Sivapalasingam et al., 2004). Contamination of fresh produce can occur during harvesting, processing, packaging, distribution, and at the retail level. Thus, the presence of Campylobacter in food processing environment can be a source for its contamination to agri-food products.  Bacteria can form biofilms in the food processing environment, such as fish processing, poultry processing, dairy processing, and ready-to-eat food processing environment (Srey et al., 29  2013). Commercial sanitizers may fail to completely inactivate C. jejuni residing in the biofilms (Chmielewski and Frank, 2003). The compact structure of biofilm can physically reduce the penetration of sanitizers. Some EPS components can neutralize sanitizers via chemical reactions. In addition, cells in a biofilm are in a state of low metabolic activity and are more tolerant to sanitizers than the planktonic cells. Hence, biofilm formation and bacteria in a low metabolic activity can enable Campylobacter to survive in food processing environment and potentially contribute to the dissemination of this microbe in agri-food systems.   1.4 General hypothesis, objectives, and rationale 1.4.1 General hypothesis Biofilm formation and persister cells are tolerant to stresses that enable the survival of C. jejuni in the unfavorable environment.   1.4.2 Objectives The overall objective of this study is to identify and characterize biofilm formation and persister cells of C. jejuni and develop effective antimicrobial strategies against C. jejuni. The individual objectives are listed as below. Objective 1: To identify and characterize mono- and multi-species C. jejuni-containing biofilms Objective 2: To investigate the relationship between stress response and biofilm formation of C. jejuni under different environmental stresses Objective 3: To identify and characterize C. jejuni persister cells  Objective 4: To investigate effective antimicrobial strategies that can inactivate C. jejuni  30  1.4.3 Rationale C. jejuni is a fragile microaerophilic bacterium, but it is the one of the leading causes of foodborne illness worldwide. The mechanism of how this microbe can successfully survive under the stress conditions and be transported via foods is not fully known yet. Biofilm and persister cells are particular survival states that enable bacteria to survive in the unfavorable environmental conditions. It is reasonable to hypothesize that C. jejuni may survive in the biofilm or as persister cells in response to different stress conditions.   31  Chapter 2: Chemical, physical and morphological properties of bacterial biofilms affect survival of encased Campylobacter jejuni F38011 under aerobic stress  2.1 Summary Campylobacter jejuni is a microaerophilic pathogen and leading cause of human gastroenteritis. The presence of C. jejuni biofilms might be one of the major strategies that responsible for the survival and dissemination of this microbe in an aerobic environment. In this study, Staphylococcus aureus, Salmonella enterica, or Pseudomonas aeruginosa was mixed with C. jejuni F38011 as cultures to form dual-species biofilms. After four days’ exposure to aerobic stress, no viable C. jejuni cells could be detected from mono-species C. jejuni biofilm. In contrast, at least 4.7 log CFU/cm2 of viable C. jejuni cells could be detected from dual-species biofilms. To elucidate the mechanism of protection mode, the chemical, physical and morphological features of biofilms were characterized. Dual-species biofilms contained a higher level of extracellular polymeric substances with a more diversified chemical composition, especially for polysaccharides and proteins than that of mono-species C. jejuni biofilm. The structure of dual-species biofilms was more compact, and their surface was >8 times smoother than that of mono-species C. jejuni biofilm which was indicated by the result of atomic force microscopy. Under desiccation stress, the water content of dual-species biofilms decreased slowly and remained at higher levels for a longer time than mono-species C. jejuni biofilm. The surface of all biofilms was hydrophilic, but the total surface energy of dual-species biofilms (ranging from 52.5 to 56.2 mJ/m2) was lower than that of mono-species C. jejuni biofilm, leading to more resistance to wetting by polar liquids. This knowledge could aid in developing 32  intervention strategies to decrease the survival and dispersal of C. jejuni into foods or environment.  2.2 Introduction Campylobacter jejuni is a Gram-negative, microaerophilic bacterium and is one of the leading causes of foodborne gastrointestinal diseases worldwide. Campylobacter infection causes acute gastroenteritis characterized by inflammation, abdominal pain, fever and diarrhea (Young et al., 2007). Previous reports indicated that C. jejuni infection cases in Canada outnumbered reported cases of Escherichia, Listeria, Shigella and Salmonella infections combined (Kalmokoff et al., 2006). The paradox associated with C. jejuni is that this bacterium is prevalent in the environment and difficult to eliminate from the food chain; however, as a microaerophile, C. jejuni is sensitive to aerobic stress and does not multiply in the aerobic environment. Studies have confirmed that bacteria shed from biofilms could continue to contaminate foods, potentially leading to food poisoning (Kumar and Anand, 1998; Donlan and Costerton, 2002). Under this condition, C. jejuni may survive within a biofilm microenvironment and further lead to food contamination (Ica et al., 2012), even though there remain controversies about how C. jejuni can resist environmental stress (e.g., temperature fluctuation, aerobic, or shear stress) and form biofilms alone (Teh et al., 2014). In the natural environment, bacterial cells mainly reside in a multispecies culture. According to the previous reports, C. jejuni biofilms are present in the gastrointestinal tract of poultry, in water supply and plumbing systems in animal husbandry facilities and food processing plants (Trachoo et al., 2002; Newell and Fearnley, 2003; Hermans et al., 2011; Siringan et al., 2011) along with other foodborne pathogens including Staphylococcus aureus, Salmonella enterica, and Pseudomonas aeruginosa. The biofilms formed 33  by these microorganisms are believed to protect C. jejuni against antimicrobial treatments and aerobic stress (Joshua et al., 2006; Ica et al., 2012). Biofilms have a complex chemical composition. In the particulate fraction of a biofilm, up to 90% is composed of extracellular polymeric substances (EPS) including polysaccharides, proteins, nucleic acids, lipids, and humic-like substances. Specific chemical components of a biofilm may contribute to its resistance to exogenous stress. For example, hydrophilic polysaccharides and proteins in EPS can hold water and keep entrained microbial cells hydrated limiting the impact of desiccation stress (Roberson and Firestone, 1992; Tamaru et al., 2005). Enzymes within biofilms could inactivate stress inducers and neutralize these in a biofilm microenvironment (Davies, 2003). Unfortunately, it has been difficult to characterize the chemical profiles of biofilms because common methods, such as crystal violet (Reeser et al., 2007) and Congo red staining (Reuter et al., 2010), are destructive and can only be used to evaluate the biofilm formation level. Innovative spectroscopic methods, particularly Raman spectroscopy coupled with confocal technique can provide in situ and nondestructive determination of the chemical composition of bacterial biofilms and changes in the composition of biofilms in response to various forms of stress (Ivleva et al., 2008; Ivleva et al., 2010; Lu et al., 2012a).  Besides chemical composition, morphological properties of bacterial biofilms are also important in determining their resistance to the environmental stress. Joshua and coauthors compared biofilms produced by wild-type and mutant C. jejuni strains using scanning electron microscopy (SEM) (Joshua et al., 2006). Reuter and coworkers evaluated surface adhesion and microstructure of C. jejuni mono-species biofilm formed under microaerobic and aerobic environment using light microscopy after staining (Reuter et al., 2010). Both studies confirmed 34  that the assemblage structure of biofilms was associated with the survival of encased sessile cells under environmental stress. Due to the destructive sample preparation process (e.g., chemical fixation for SEM, staining for light microscopy), artifacts may be introduced that affect the accurate characterization of biofilms. Atomic force microscopy (AFM) offers an alternative characterization methodology. By recording interaction signals between the probing tip and biofilm surface, AFM can generate high-resolution topographic images that accurately reflect the structural details of morphological information of a biofilm in a nano-scale without sample preparation (Scheuring and Dufrêne, 2010; Ivanov et al., 2011; La Storia et al., 2011; Lim et al., 2011).  Physical properties of biofilms, such as surface wettability (hydrophobicity/hydrophilicity), surface roughness, surface free energy, and water holding capability, play a role in the response of bacterial biofilms to a variety of stresses, such as desiccation and shear stress (Bove et al., 2012; Ng and Kidd, 2013). Wettability is related to the surface area of biofilm that could contact water while a high water holding capability maintains a high relative humidity in biofilms, both of which are important to protect encased cells from desiccation (Allison et al., 1990). Surface roughness predicts the susceptibility of biofilms to shear force, thus the smoother the biofilm surface, the less it is influenced by mechanical shearing forces (Beech et al., 2002; Li and Logan, 2004).  Few studies have been conducted to investigate the effect of mixed bacterial culture on C. jejuni-containing biofilms and the susceptibility of C. jejuni cells in these multispecies biofilms. Therefore, this study aims to characterize chemical, physical and morphological properties of dual-species C. jejuni-containing biofilms and correlate these to the stress resistance of encased C. jejuni cells compared to that of mono-species C. jejuni biofilm. The knowledge will be 35  important to further understand the ecology of C. jejuni and its survival in the environment and subsequently develop innovative mitigation strategies to more successfully eliminate biofilms and reduce public health risk associated with this microbe.   2.3 Materials and methods 2.3.1 Bacterial strains and cultivation.  C. jejuni F38011 (human clinical isolate), Staphylococcus aureus (a clinical isolate used in our previous study) (Lu et al., 2013b), Salmonella enterica serovar Enteritidis FDA 3512H, and Pseudomonas aeruginosa PAO1 were used in this study. C. jejuni strain was stored at -80°C in Mueller-Hinton (MH) broth (BD Difco) containing 12% glycerol and 75% defibrinated sheep blood. Routine cultivation was conducted either on MH agar supplemented with 5% defibrinated sheep blood or in MH broth with constant shaking at 37°C under microaerobic conditions (85% N2, 10% CO2, 5% O2). S. aureus, S. enterica, and P. aeruginosa were individually cultivated overnight in 5 ml tryptic soy broth (TSB) (BD Difco) at 37°C to achieve a concentration of ca. 9 log CFU/ml.   2.3.2 Biofilm cultivation.  One milliliter of overnight bacterial culture was centrifuged at 8,000 ×g for 10 min at 22°C. The supernatant was discarded, and the bacterial pellets were washed twice and resuspended in sterile phosphate buffered saline (PBS) (pH = 7.0). The resuspended culture was then diluted to ~107 CFU/ml. For dual-species biofilm formation, the mixed culture of C. jejuni F38011 was generated by addition of a second bacterial strain listed above on the basis of the same volume and concentration. Biofilms were cultivated at both solid-air interface and solid-liquid interface. 36  Nitrocellulose membrane (0.45 mm pore size, 47 mm diameter; Sartorius Stedim-type filters) was used as a substrate for biofilm formation at the solid-air interface, as described elsewhere (Lu et al., 2012). C. jejuni monoculture or mixed culture (100 µl) was deposited onto the surface of a sterile nitrocellulose membrane with a surface area of ~3×3 cm2, which was placed onto an agar plate supplemented with 5% defibrinated sheep blood and incubated under a microaerobic environment at 37°C. The membrane was aseptically transferred to a fresh agar plate every 24 h for up to 72 h. 0.2 ml of C. jejuni monoculture or mixed culture was added to each well of sterile 96-well polystyrene plate for the cultivation of biofilms at the liquid-solid interface. The plate was incubated under a microaerobic environment at 37°C for up to 72 h.   2.3.3 Survival of C. jejuni F38011 and co-cultured bacterial cells in biofilms under aerobic stress.  The survival of C. jejuni and co-cultured bacterial cells in mono-species and dual-species biofilms under aerobic stress were determined by selective agar. Briefly, mature biofilms (cultivated under the microaerobic condition for 72 h) formed on nitrocellulose membrane were placed under aerobic environment at 22°C for up to 5 days. Every 24 h, biofilms were detached from nitrocellulose membrane using 0.1% trypsin solution (20 ml) for incubation at 22°C for 20 min. This treatment did not affect bacterial cell viability (data not shown). Following detachment, the bacterial suspension was serially diluted and spread onto selective agar plate. Campy Cefex agar is used for enumeration of viable C. jejuni cells (Neal-McKinney et al., 2012). Campy-Cefex agar contains 43 g/l Brucella agar, 0.5 g/l ferrous sulfate, 0.2 g/l sodium bisulfite, 0.5 g/l sodium pyruvate, 33 mg/l cefoperazone, and 0.2 g/l cycloheximide, with a supplement of 5% defibrinated sheep blood (Oyarzabal et al., 2005). Mannitol salt agar (BD BBL) is used for the 37  enumeration of viable S. aureus cells. Xylose lysine deoxycholate (XLD) agar (BD Difco) is used for enumeration of viable S. enterica and P. aeruginosa cells. The selective agar for C. jejuni was placed under a microaerobic environment at 37°C, while selective agars for co-cultured bacterial strains were placed under aerobic environment at 37°C.   2.3.4 Confocal laser scanning microscopy (CLSM).  The survival state of C. jejuni cells within a biofilm was further confirmed using CLSM. The SYTO 9 dye (with a green color for live cells) and propidium iodide dye (with a red color for non-viable cells) were diluted according to the manufacturer's instructions and then mixed in equal volume proportions. After exposure to aerobic environment for four days, nitrocellulose membrane with a developed biofilm was transferred from an agar plate to a sterile petri dish with 2 ml of the mixed dye solution, followed by incubation at 22°C for 30 min in the absence of light. The unbound dye was rinsed off of the nitrocellulose membrane with PBS (pH 7.0), and images of stained biofilms were collected using confocal microscopy (FV3000, Olympus, Tokyo, Japan). The wavelengths of excitation laser were set at 488 nm and 543 nm for green channel and red channel, respectively. Images were collected using a 40.0 × 1.0 oil immersion objective lens at a scan speed of 400 Hz.   2.3.5 Crystal violet biofilm assay.  Crystal violet staining was applied to quantify biofilm formation at the liquid-solid interface. After 72 h cultivation, a 96-well plate was washed with sterile deionized water and dried at 37°C for 5 min. Then, 0.2 ml of 0.5% (w/v) crystal violet solution was added to each well of 96-well plate, and the plate was incubated at 22°C for 10 min. Unbound crystal violet was washed off 38  with sterile deionized water, and the plate was dried at 22°C for another 5 min. Bound crystal violet was dissolved in 0.2 ml of 95% ethanol (v/v) for 10 min. Released crystal violet suspension was measured using a microplate reader at 595 nm (SpectraMax M2, Molecular Devices, Sunnyvale, USA). Broth without bacterial inoculation was stained using the same method as control and subtracted for background correction.  2.3.6 C. jejuni share (CJS) index in biofilm formation.  The CJS index is used to semi-quantify the contribution of encased C. jejuni cells to the formation of dual-species biofilm compared to the formation of mono-species biofilm. The calculation of CJS index is adapted from a previous publication (Naves et al., 2008): CJS = AB− NCSC AC− CSCO�  , in which AB is the optical density of crystal violet stained dual-species biofilms, AC is the optical density of crystal violet stained mono-species C. jejuni biofilm, NCS is the optical density of crystal violet stained mono-species non-C. jejuni biofilm (i.e., S. aureus, S. enterica, and P. aeruginosa), CS is the optical density of crystal violet staining without inoculation, C is the viable C. jejuni cell counts in the mature dual-species biofilm, CO is the viable C. jejuni cell counts in the mature mono-species C. jejuni biofilm.  2.3.7 Confocal micro-Raman spectroscopy.  This photonic system includes a Raman spectrometer (Renishaw, Gloucestershire, United Kingdom), a Leica microscope (Leica Biosystems, Wetzlar, Germany) and a diode near-infrared (λ=785 nm) laser (Renishaw, Gloucestershire, United Kingdom). The spectrometer has an 39  entrance aperture of 50 µm and a focal length of 300 mm and is equipped with 1200-line/mm grating. Raman scattering signals were collected and dispersed by a diffraction grating and finally recorded as a Raman spectrum by a 576-by-384-pixel charge-coupled-device (CCD) array detector, with the size of each pixel 22 by 22 µm. Mono-species and dual-species C. jejuni biofilms formed at the solid-air interface were directly transferred onto the microscope stage, which was focused under the collection assembly, and spectra were collected using a 50× objective (numerical aperture [NA] = 0.75, working distance [WD] = 0.37 mm) with a wavenumber range of 1800-400 cm-1. The spectral collection was conducted over a total of 60 s (exposure time) at eight different locations for each biofilm with ~25 mW of incident laser power. Exposure to laser illumination during Raman spectral collection did not cause damage or variations in chemical components of biofilm samples (data not shown).   2.3.8 Raman spectral processing and multivariate analysis.  The polynomial background fits combined with baseline subtractions were carried out to remove fluorescence background derived from biofilms. Spectral binning (2 cm-1) and smoothing (9-point Savitzky-Golay algorithm) were then applied (Feng et al., 2014). Due to the potential minor differences among Raman spectra derived from biological variation among biofilm samples, a second derivative transformation algorithm was applied to amplify the minor spectral variations and separate out overlapping bands (Lu et al., 2011a). Unsupervised PCA models were constructed to quantify the variation among different biofilm samples. Mahalanobis distances in the PCA models were calculated to evaluate the variation among different biofilms (Lu et al., 2013b). All these analyses were conducted using MATLAB (Mathworks, USA).   40  2.3.9 Atomic force microscopy.  The variations in morphological properties between mono-species and dual-species C. jejuni biofilms formed at the solid-air interface were determined using a Cypher atomic force microscope (Asylum Research, Santa Barbara, U.S.A.) and TR400PB tip cantilevers from Olympus (Tokyo, Japan; nominal spring constant: k = 0.02 N/m). Topographic images were collected in contact mode in ambient air. The nitrocellulose membrane with a mature biofilm grown (cultivated under a microaerobic condition at 37°C for 72 h) was transferred from agar plate onto AFM specimen disc (15 mm diameter, Ted Pella, Redding, CA). After drying in biological safety cabinet at 22°C at <30% relative humidity for 30 min without air blowing, the specimen disc coated with biofilm was put into an enclosed sample chamber at 22°C at <60% relative humidity. Topographic images were collected at five random locations on the biofilm surface with a surface area of 8 µm × 8 µm at a scan frequency of 1 Hz. The AFM system was operated using Igor Pro 6.31 software (Wavemetrics Inc., Lake Oswego, U.S.A.) and the AFM images were analyzed off-line using WSxM 5.0 software (Nanotec Electronica S.L., Madrid, Spain). Surface root-mean-square (RMS) roughness of biofilms was calculated using height images with a surface area of 8 µm × 8 µm.  2.3.10 Contact angle measurement.  The wettability (hydrophobic/hydrophilic) of biofilm surfaces were determined by contact angle measurement using a sessile drop method (Lamour et al., 2010; Syamaladevi et al., 2013). In this study, sterile deionized water, formamide, and diiodomethane were used as reference liquids. Briefly, mature biofilms (cultivated under the microaerobic condition for 72 h) formed at the solid-air interface were dried at 22°C for 30 min before contact angle measurement. Then, one µl 41  liquid droplet was deposited onto the biofilm surface and allowed to settle for 5 s. A high-resolution digital camera (D90, Nikon, Tokyo, Japan) was used to capture profile images of contact angles at the equilibrium under a light source. Contact angle (θ) was collected at three random locations for each sample and experiment was conducted in triplicate.  Images were analyzed by software FTA32 Version 2.0 (First Ten Ångstroms, Portsmouth, U.S.A.), as described by Mirvakili and Beyenal (Beyenal et al., 2004; Mirvakili et al., 2013). Biofilm wettability was estimated by contact angle formed by deionized water. Biofilm surface free energy properties [i.e., total surface energy (γS), Lewis acid-base component (γSAB), Lifshitz-van der Waals (γSLW), electron-donor (γS-) and electron acceptor (γS+)] were calculated according to Young-Dupré equation and van Oss approach (Briandet et al., 2001; van Oss, 2002) as follows: cos 𝜃𝜃 = −1 + 2�(𝛾𝛾𝑆𝑆𝐿𝐿𝐿𝐿𝛾𝛾𝐿𝐿𝐿𝐿𝐿𝐿) 𝛾𝛾𝐿𝐿� + 2�(𝛾𝛾𝑆𝑆+𝛾𝛾𝐿𝐿−) 𝛾𝛾𝐿𝐿� + 2�(𝛾𝛾𝑆𝑆−𝛾𝛾𝐿𝐿+) 𝛾𝛾𝐿𝐿�  𝛾𝛾𝑆𝑆𝐴𝐴𝐴𝐴 = 2�(𝛾𝛾𝑆𝑆+𝛾𝛾𝑆𝑆−) 𝛾𝛾𝑆𝑆 = 𝛾𝛾𝑆𝑆𝐴𝐴𝐴𝐴 + 𝛾𝛾𝑆𝑆𝐿𝐿𝐿𝐿  2.3.11 Biofilm water retention assays.  Attenuated total reflectance-Fourier transform infrared (FT-IR) spectroscopy was applied to determine water holding capability of mono-species and dual-species C. jejuni biofilms formed at the solid-air interface. After 72 h cultivation, nitrocellulose membranes with developed biofilms were removed from agar plates and immediately mounted onto the crystal cell of Spectrum 100 FT-IR spectrometer (PerkinElmer, Norwalk, U.S.A.). FT-IR spectra of each biofilm were recorded at 22°C at intervals of 5 min until no changes in spectral features. Previous work has shown that spectral features of the nitrocellulose membrane did not affect FT-42  IR spectral features of biofilms since the penetration distance of the evanescent wave derived from mid-IR is less than the thickness of biofilm (Lu et al., 2012a).   2.3.12 Statistical analysis.  All the experiments were conducted in at least three replicate trials. Results were reported as the averages of replicates ± the standard deviation with significance (P < 0.05) by one-way analysis of variance (ANOVA).  2.4 Results 2.4.1 The survival of C. jejuni F38011 and co-cultured bacterial cells in developed biofilms under aerobic stress.  In mature biofilms, the presence of S. enterica and S. aureus in dual-species biofilms did not affect the growth of C. jejuni, and the cell counts of culturable C. jejuni in C. jejuni-S. enterica and C. jejuni-S. aureus dual-species biofilms were not significantly different (P > 0.05) compared to that in mono-species C. jejuni biofilm thought the biofilm development. However, dual-species biofilm containing P. aeruginosa had a significantly lower (P < 0.05) number of culturable C. jejuni cells, about two orders of magnitude lower compared to the mono-species C. jejuni biofilm (Table 2-1). On the other hand, the presence of C. jejuni in dual-species biofilms did not affect the growth of co-cultured bacterial strains. The co-cultured bacterial cell counts in dual-species biofilms were not significantly different (P > 0.05) compared to their mono-species biofilm (Table 2-2). In C. jejuni-S. enterica and C. jejuni-S. aureus biofilms, the viable cell counts of C. jejuni were about one order of magnitude less than that of co-cultured bacterial strain. In C. jejuni-P. aeruginosa biofilm, the viable cell counts of C. jejuni were about three orders of magnitude less than that of co-cultured bacterial strain. In general, C. jejuni was not the 43  dominant strain compared to the co-cultured strains. Under aerobic stress, C. jejuni F38011 cell counts in mono- and dual-species biofilms decreased over exposure time, but survival time and rate of decrease varied significantly (Table 2-1). C. jejuni cells in mono-species biofilm and C. jejuni-P. aeruginosa biofilm survived for the shortest time, with no culturable C. jejuni cells detected when the biofilms were exposed to aerobic stress at four days and three days, respectively. The initial cell counts of C. jejuni in dual-species C. jejuni-P. aeruginosa biofilms were two orders of magnitude lower than that in mono-species C. jejuni biofilm. The reduction of C. jejuni cells in C. jejuni-P. aeruginosa biofilm under aerobic condition was more dramatic than that in the mono-species C. jejuni biofilm. A large number of C. jejuni cells in the other two dual-species biofilms were still culturable at day 5, with the C. jejuni cell counts in C. jejuni-S. enterica and C. jejuni-S. aureus biofilms at 3.9 and 4.2 log CFU/cm2, respectively. In contrast, the survival of non-C. jejuni strains were not affected by aerobic stress. Taken together, the cell counts of S. enterica, S. aureus, and P. aeruginosa did not significantly decrease under aerobic stress.    44   Table 2-1. Viable C. jejuni F38011 cell counts in mature biofilms with aerobic stress. Time Biofilms / Viable cell counts (log CFU/cm2) C. jejuni C. jejuni + S. enterica C. jejuni + S. aureus C. jejuni + P. aeruginosa Mature (72-h cultivation, Day 0) 8.1 ± 0.1 7.8 ± 0.2 8.2 ± 0.1 5.9 ± 0.2 Day 1 7.4 ± 0.3 7.0 ± 0.3 7.2 ± 0.3 4.6 ± 0.2 Day 2 5.3 ± 0.3 5.9 ± 0.3 6.9 ± 0.7 3.9 ± 0.2 Day 3 4.9 ± 0.1 5.0 ± 0.3 5.2 ± 0.3 ND Day 4 ND* 4.7 ± 0.1 4.8 ± 0.1 ND Day 5 ND 3.9 ± 0.1 4.2 ± 0.1 ND * ND: non-detectable, the limit of detection is 2.7 log CFU/cm2 Day 1 to Day 5: exposure time of mature biofilm to aerobic environment    45  Table 2-2. Viable non-C. jejuni (i.e. S. enterica, S. aureus, and P. aeruginosa) bacterial cell counts in mature biofilms under aerobic stress. Time Biofilms / Viable cell counts (log CFU/cm2) C. jejuni + S. enterica S. enterica C. jejuni + S. aureus S. aureus C. jejuni + P. aeruginosa P. aeruginosa Mature (72-h cultivation, Day 0) 9.4 ± 0.1 9.5 ± 0.2 9.1 ± 0.3 9.0 ± 0.2 8.4 ± 0.1 8.4 ± 0.1 Day 1 9.5 ± 0.1 9.6 ± 0.1 9.2 ± 0.1 9.2 ± 0.1 8.5 ± 0.3 8.5 ± 0.2 Day 2 9.5 ± 0.1 9.5± 0.2 9.1 ± 0.1 9.2 ± 0.0 8.3 ± 0.3 8.4 ± 0.3 Day 3 9.5± 0.1 9.5 ± 0.1 9.4 ± 0.4 9.3 ± 0.2 8.5 ± 0.7 8.3 ± 0.3 Day 4 9.5± 0.0 9.4 ± 0.1 9.4 ± 0.4 9.2 ± 0.1 7.9 ± 0.3 8.2 ± 0.3 Day 5 9.5± 0.1 9.4 ± 0.1 9.2± 0.2 9.2 ± 0.1 8.1± 0.8 7.9 ± 0.3 Day 1 to Day 5: exposure time of mature biofilm to aerobic environment   2.4.2 The viability of C. jejuni F38011 cells in biofilms.  The viability of C. jejuni F38011 cells in mono-species biofilms under aerobic stress was further determined using live/dead kit coupled with confocal laser scanning microscopy (CLSM). After four days exposure to aerobic condition, no viable cell could be detected by a plating 46  method. However, live cells (green signal) could still be observed in CLSM images (Figure 2-1A). This could due to the amount of live C. jejuni cells in mono-species biofilm were lower than the limit of detection of plating assay (2.7 log CFU/cm2) or these cell were under the non-culturable state. From the vertical layout, the signal of viable cells intensely observed at the bottom layer of biofilm, indicating survived C. jejuni cells tend to habit the bottom of biofilm. This particular preference of localization of viable C. jejuni cells in biofilms could because bottom biofilm was away from the air-biofilm interface with a low level of oxygen and was suitable for the survival of C. jejuni cells (Figure 2-1B).   47   Figure 2-1. The viability and localization of C. jejuni cells in mono-species C. jejuni F38011 biofilm was determined using live/dead kit coupled with confocal laser scanning microscopy. In this image, green color indicates live C. jejuni cells while red color indicates dead C. jejuni cells (n = 3). After four days exposure to aerobic stress, there is no viable C. jejuni cells could be detected using MH plating method. However, the green signal derived from viable cells still could be observed in biofilm, and most of these viable cells were localized at the bottom layer of biofilm. a) Viable and dead C. jejuni cells in mono-species biofilm showed in horizontal layout. b) Viable C. jejuni cells in mono-species biofilm showed in vertical layout.   2.4.3 The formation level of C. jejuni biofilms.  The formation level of mono- and dual-species C. jejuni biofilms in 96-well plate were evaluated using crystal violet staining assay (Figure 2-2). Mono-species C. jejuni culture only formed a thin biofilm. In contrast, the formation level of all dual-species C. jejuni biofilms was 48  significantly (P < 0.05) higher. Among these dual-species biofilms, the biofilm formed by C. jejuni with P. aeruginosa had the largest biomass, which was approximately 13.5 times higher than that of mono-species C. jejuni biofilm (Figure 2-2). In addition, the biomass of C. jejuni-S. enterica biofilm was similar to that of C. jejuni-S. aureus biofilm but significantly higher (P < 0.05) than that of mono-species C. jejuni biofilm by ~ 4 times.   Figure 2-2. The formation level of mono- and dual-species biofilms in 96-well plate was quantified by crystal violet staining assay. (white column: the biofilms formed by C. jejuni individually or with other bacteria (i.e., P. aeruginosa, S. enterica, and S. aureus); black column: biofilms formed by non-C. jejuni bacteria, including P. aeruginosa, S. enterica, and S. aureus, individually. Asterisk denotes significant difference (P < 0.05).  2.4.4 The contribution of C. jejuni to biofilm formation.  C. jejuni share (CJS) index was applied to evaluate the weight of C. jejuni in the dual-species biofilms (i.e., with S. aureus, S. enterica, and P. aeruginosa) regarding contribution to 49  biomass. By subtracting the biomass formed by non-C. jejuni strain (i.e., S. aureus, S. enterica and P. aeruginosa) in dual-species biofilms, the contribution of C. jejuni to dual-species biofilm could be roughly estimated. Subsequently, the contribution of C. jejuni to biofilm formation could be determined by comparing the contribution of C. jejuni to mono- and dual-species biofilms. According to Table 2-3, the contribution of C. jejuni to biofilm formation was not affected by the presence of S. aureus, P. aeruginosa, or S. enterica. Table 2-3. Contribution of C. jejuni F38011 cells to the formation of mono- and dual-species biofilms. C. jejuni share (CJS) index in mono- and dual-species biofilms is summarized.  C. jejuni C. jejuni + S. enterica C. jejuni + S. aureus C. jejuni + P. aeruginosa 1.00 1.07 0.99 0.97 The value is obtained as the ratio of biomass formed by C. jejuni alone in the dual-species biofilm to that formed by C. jejuni in the mono-species biofilm.   2.4.5 The chemical compositions of C. jejuni biofilms. Raman spectra of mono- and dual-species C. jejuni biofilms were collected over a wavenumber region from 1800 to 400 cm-1. A representative Raman spectrum of each biofilm was an average of 24 spectra collected from three independent experiments (Figure 2-3). According to the previous studies of band assignments for bacteria and other biological systems (Movasaghi et al., 2007; Lu et al., 2012a), spectral regions depicting four important chemical 50  components in biofilms are 1800-1500 cm-1: proteins, 1500-1200 cm-1: fatty acids, 1200-900 cm-1: polysaccharides, and 900-400 cm-1: a unique fingerprinting region of mixed constituents.   Figure 2-3. The Raman spectra indicated the chemical variations among different biofilms. The Raman spectra were collected using a confocal micro-Raman system with 785 nm laser. The biofilms were prepared on NC membrane and air-dried for 15 mins before spectra collection. Raman spectra showed here were the average of 24 independent replicates: a) the Raman spectra of mono-species C. jejuni biofilm; b) the Raman spectra of dual-species C. jejuni-S. enterica biofilm; c) the Raman spectra of dual-species C. jejuni-S. aureus; d) the Raman spectra of dual-species C. jejuni-P. aeruginosa.  C. jejuni-S. enterica biofilm shared a similar Raman spectral pattern as that of mono-species C. jejuni biofilm at the bands of 425, 578, 670, 780, 973, 997, 1100, 1336, 1445, and 1653 cm-1, but with higher signal intensity. Table 2-4  summarizes the major Raman band 51  assignments of mono- and dual-species C. jejuni biofilms, noting the spectral features of both EPS and encased cells within biofilms. Second derivative transformations were performed to magnify the minor variations in raw Raman spectra between mono-species C. jejuni biofilm and C. jejuni-S. enterica biofilm (Figure 2-4). Distinct differences were observed at 425, 578, 780, 855, 997, and 1280 cm-1, as summarized in Table 2-4.  Table 2-4. The band assignments of Raman spectra of C. jejuni mono-species biofilm and dual-species C. jejuni-S. enterica biofilm. Raman shift (cm-1) Band assignment 425 Symmetric stretching vibration of phosphate 578 tryptophan/cytosine, guanine 670 ring-breathing modes in DNA base 780 ring breathing of nucleotide 855 ring-breathing modes in RNA base 973 C-C backbone of proteins 997 C-O vibration and C-C backbone of polysaccharides 1100 C-C vibration mode of amide III 1280 Backbone of nucleic acids and proteins 1336 CH3CH2 wagging of nucleic acids 1445 CH3CH2 bending mode of lipids and proteins 1653 amide I and C=C lipid stretch  52   Figure 2-4. The minor chemical variation between C. jejuni mono-species biofilm (black) and dual-species C. jejuni-S. enterica biofilm (gray) was determined using second derivative transformations of Raman spectra. Distinct differences were observed at 425, 578, 780, 855, 997, and 1280 cm-1.  The chemical compositions of C. jejuni-S. aureus and C. jejuni-P. aeruginosa biofilms were significantly different from each other, and  both of them were varied from that of the mono-species C. jejuni biofilm, specifically at bands of lipids, proteins, and polysaccharides. Table 2-5  summarizes the differences observed in spectral features for these biofilms.    53  Table 2-5. The assignments for distinct Raman bands between the Raman spectra of C. jejuni-S. aureus and C. jejuni-P. aeruginosa biofilms. Biofilms Raman shift (cm-1) Band assignment C. jejuni-S. aureus 1519 C=C band stretch of polysaccharides  1154 C-C stretching of proteins  774 symmetric breathing of proteins  749 symmetric breathing of lipids C. jejuni-P. aeruginosa 1613 tyrosine  1560 tryptophan  1482 ring breathing mode of nucleic acids  1454 CH3 bending of phospholipids  1403 methyl group in proteins  1345 CH deformation of polysaccharides  1243 amide III  1169 tyrosine  761 ring breathing of tryptophan  588 phospholipids  546 lipids   411 phospholipids  The Raman spectra of biofilms formed by non-Campylobacter bacteria (i.e., S. enterica, S. aureus, and P. aeruginosa) were regarded as control. Representative Raman spectra of these biofilms were shown in Figure 2-5. Biofilms formed by non-C. jejuni strains (i.e., S. enterica, S. 54  aureus and P. aeruginosa) shared similar Raman spectral pattern as that of dual-species biofilms(i.e., S. enterica + C. jejuni, S. aureus + C. jejuni, and P. aeruginosa + C. jejuni), respectively. The Raman spectra of P. aeruginosa biofilm only showed two distinct Raman bands at 516 and 1524 cm-1 (Table 2-4 and 5) that were not observed in the dual-species P. aeruginosa + C. jejuni biofilm. In addition, the band intensities of Raman spectra of S. enterica and S. aureus biofilms were lower than that of the dual-species biofilms (i.e., S. enterica + C. jejuni and S. aureus + C. jejuni) respectively. The intensities of Raman bands were associated with the quantity of certain functional groups. Hence, the intensities of biofilm Raman bands reflected the quantity of different chemical compositions in different biofilms. In general, dual-species biofilms contained higher biomass than that of mono-species biofilms which were consistent with the result of crystal violet staining assay.  55   Figure 2-5. The Raman spectra of biofilms formed by non-Campylobacter bacteria (i.e., S. enterica, S. aureus, and P. aeruginosa) indicated the contribution of non-Campylobacter to the chemical composition of dual-species biofilms. The Raman spectra were collected using a confocal micro-Raman system with 785 nm laser. The biofilms were prepared on NC membrane and air-dried for 15 mins before spectra collection. Raman spectra showed here were the average of 24 independent replicates: a) the Raman spectra of S. enterica biofilm; b) the Raman spectra of S. aureus biofilm; c) the Raman spectra of P. aeruginosa biofilm.     The principal component analysis (PCA) was employed to differentiate of mono- and dual-species C. jejuni biofilms based on the difference of their Raman spectral patterns (Figure 2-6). Each of biofilm had distinctive features as signified by the formation of tight clusters with interclass distances for the biofilms from different species ranging from 4.63 to 13.02 based on 56  Mahalanobis distance measurements computed between the centroids of groups. Clusters with interclass distance values higher than three are considered to be significantly different (P < 0.05) from each other (Lu et al., 2011b).  Figure 2-6. The principal component analysis for the segregation of C. jejuni mono- and dual-species biofilms based on the difference of their Raman spectra. Cross: C. jejuni biofilm; triangle: C. jejuni-S. enterica biofilm; plus: C. jejuni-S. aureus biofilm; square: C. jejuni-P. aeruginosa biofilm.  2.4.6 The morphological and surface roughness of C. jejuni biofilms. The surface mechanical properties of mono- and dual-species C. jejuni biofilms were determined using AFM in contact mode. Although AFM contact mode might rupture the surface of biofilm, the trace and retrace images collected from the same spot were perfectly matched (data are not shown), indicating that the interaction between AFM and biofilm surface did not scratch the biofilm, and the morphological properties and surface roughness collected by AFM 57  were reliable. The representative topographic images of different biofilms were shown in Figure 2-7. The deflection images demonstrated the detailed topographic information of biofilm surface. Specifically, the surface of mono-species C. jejuni biofilm was loosely structured (Figure 2-7A). In contrast, the surface of dual-species C. jejuni biofilms was compacted and well organized. In addition, the congested pits (~1×1 μm2) were randomly arranged on the surface of dual-species C. jejuni-S. enterica (Figure 2-7B) and C. jejuni-P. aeruginosa (Figure 2-7D) biofilms; while the surface of dual-species C. jejuni-S. aureus biofilm had small shallow pits (Figure 2-7C).  Figure 2-7. Topographic deflection-retrace images of mono- and dual-species C. jejuni biofilms obtained by atomic force microscopy in contact mode within 8 µm × 8 µm area: a) C. jejuni; b) C. jejuni-S. enterica; c) C. jejuni-S. aureus; d) C. jejuni-P. aeruginosa. (left panels: C. jejuni-containing biofilms; right panels: non-C. jejuni-containing biofilms) (n = 20).  Topographic information of biofilms formed by non-C. jejuni bacteria (i.e., S. enterica, S. aureus and P. aeruginosa) was also measured using AFM (Figure 2-7) (n = 20). The surface of these biofilms was all compact. In addition, the surface pattern on the surface of mono-species P. 58  aeruginosa biofilm was similar as that on the surface of dual-species biofilm (Figure 2-7D). In contrast, the surface structure of S. enterica and S. aureus biofilms showed differences with their dual-species biofilm counterparts (i.e., S. enterica + C. jejuni and S. aureus + C. jejuni) (Figure 2-7B, C). Although S. enterica biofilm had a similar surface pattern (pits with the size of 1 × 1 μm2) as that of dual-species C. jejuni-S. enterica biofilm, these patterns on the surface of S. enterica biofilm were loosely organized. While, compared to dual-species C. jejuni- S. aureus biofilm, the surface of S. aureus biofilm contained more bumps or protrusions on the surface, but small shallow pits spreading on C. jejuni-S. aureus biofilm could not be observed. The root mean square (RMS) roughness of biofilms were calculated from the AFM height images (Figure 2-8). The RMS roughness of mono-species C. jejuni biofilm was 257.7 nm, while the RMS roughness of C. jejuni-S. enterica biofilm was 17.9 nm; the RMS roughness of C. jejuni-S. aureus biofilm was 30.7 nm; the RMS roughness of C. jejuni-P. aeruginosa biofilm was 27.4 nm  (Figure 2-9). This result was consistent with surface morphological properties of biofilms, which indicated that the surface structure of mono-species C. jejuni biofilm was rougher and less structured than that dual-species C. jejuni biofilms.  59   Figure 2-8. The representative topographic height-retrace images of mono- and dual-species C. jejuni biofilms were obtained by atomic force microscopy in contact mode. The images were shown in 8 µm × 8 µm area: a) The image of C. jejuni biofilm; b) The images of C. jejuni-S. enterica and S. enterica biofilms; c) The image of C. jejuni-S. aureus and S. aureus biofilms; d) The image of C. jejuni-P. aeruginosa and P. aeruginosa biofilms. (left panels: C. jejuni-containing biofilms; right panels: non-C. jejuni-containing biofilms) (n = 20). 60   Figure 2-9. The root mean square (RMS) roughness of mono- and dual-species C. jejuni biofilms. The RMS roughness value of white column was derived from C. jejuni containing biofilms. The RMS roughness value of black column was derived from control biofilms which were S. enterica, S. aureus, and P. aeruginosa biofilms. Asterisk denotes significant difference (P < 0.05).  The RMS roughness of biofilms formed by or non-C. jejuni bacteria (i.e., S. enterica, S. aureus and P. aeruginosa) were 29.0 nm, 42.8 nm, and 30.2 nm, respectively (Figure 2-9). Compared to the dual-species biofilms, the RMS roughness of biofilms formed by S. enterica and S. aureus were significantly (P < 0.05) higher. The RMS roughness of P. aeruginosa biofilm was slightly higher compared to its dual-species biofilm counterpart, but no significant difference (P > 0.05) was observed.  61  The three-dimensional reconstruction of the surface structure of mono- and dual-species C. jejuni biofilms were shown in Figure 2-10 which highlighted the variations of surface morphology among different biofilms.    Figure 2-10. The 3D reconstruction images of the surface structure of mono- and dual-species C. jejuni biofilms. a) the surface structure of C. jejuni biofilm; b) the surface structure of C. jejuni-S. enterica biofilm; c) the surface structure of C. jejuni-S. aureus biofilm; d) the surface structure of C. jejuni-P. aeruginosa biofilm. (n = 20)  2.4.7 The surface wettability and free energy property of C. jejuni biofilms.  The contact angle measurement was applied to determine the surface wettability of mono- and dual-species C. jejuni biofilms formed on NC membrane. The wettability test was conducted using three reference liquids (i.e., water, formamide, and diiodomethane) (Van Oss, 1993). The contact angle of these reference liquids on biofilms could be used to evaluate the surface 62  hydrophobicity qualitatively. In general, if the contact angle of a water droplet on a surface was higher than 90°, then this surface could be regarded as hydrophobic. The higher the water contact angle was, the more hydrophobic the surface was. The representative images of the contact angle of different reference liquids on mono- and dual-species C. jejuni biofilms were shown in Figure 2-11. The water droplets were quickly spread on the surface of mono-species biofilm, forming a contact angle of 13.2°. Dual-species biofilms were more repellent to water droplets, and the contact angle of water on these biofilms was significantly higher (P < 0.05) than that on mono-species C. jejuni biofilm, ranging from 19.6° to 21.8°. Taken together, water contact angle on all biofilms was lower than 90° (Table 2-6), indicating that these biofilms all had a hydrophilic surface and the hydrophilicity of mono-species biofilms was higher than that of dual-species biofilms. The contact angle was higher when the less polar liquids were applied. Specifically, the contact angles of formamide on biofilms ranged from 19.7° to 28.3°; the contact angle of diiodomethane on biofilms ranged from 62.4º to 82.6º.  Figure 2-11. Representative images of contact angle formed by three different liquids (water, formamide, and diiodomethane) on the surface of mono- and dual-species C. jejuni biofilms (n = 9).   63  Table 2-6. The contact angle of different reference liquids on mono- and dual-species C. jejuni biofilms using sessile drop technique. Culture Contact angle Water Formamide Diiodomethane C. jejuni 13.2º ± 2.2º 19.7º ± 2.7º 82.6º ± 4.2º C. jejuni + S. enterica 20.5º ± 2.4º* 25.0º ± 2.5º* 65.7º ± 3.4º* S. enterica 16.5º ± 3.2º 23.7º ± 2.6º 71.5º ± 5.1º C. jejuni + S. aureus 19.6º ± 1.8º* 22.8º ± 2.2º* 66.6º ± 2.9º* S. aureus 19.2º ± 2.4º 20.1º ± 3.7º 74.5º ± 2.4º C. jejuni + P. aeruginosa 21.8º ± 2.7º* 28.3º ± 2.8º* 62.4º ± 1.9º* P. aeruginosa 21.6º ± 2.8º 27.1º ± 4.2º 65.4º ± 2.8º *Significant difference (P < 0.05) was observed between mono-species C. jejuni biofilm and dual-species C. jejuni biofilms. The data was shown as the mean value ± standard deviation. (n=9)   The contact angle measurement was also applied on biofilms formed by non-C. jejuni bacteria (i.e., S. enterica, S. aureus and P. aeruginosa). In general, the water contact angles of reference liquids on these biofilms were significantly different (P < 0.05) from that of dual-species biofilms (Table 2-6). The high contact angle on mono-species biofilms formed by non-C. 64  jejuni bacteria indicated that the hydrophilicity of biofilms formed by non-C. jejuni bacteria was higher than that of dual-species C. jejuni biofilms.  The surface energy of biofilms can be calculated from contact angle measurement using Young-Dupré equation (Table 2-7). Compared to mono-species C. jejuni biofilm, the total surface energy of dual-species biofilms was much lower. In addition, the apolar component (Lifshitz-Van der Waals) and the polar component (Lewis acid-base) of the surface energy of mono- and dual-species C. jejuni biofilms varied extensively. Specifically, the apolar component of surface energy of dual-species biofilms ranged from 24.7 to 27.1 mJ/m2, which was significantly higher (P < 0.05) than that of mono-species C. jejuni biofilm (16.1 mJ/m2). This result was consistent with the observation of contact angle measurement in which mono-species biofilm repelled apolar liquid (i.e., diiodomethane) more than that of dual-species biofilms.    65  Table 2-7. The total surface energy and distribution of energy components of mono- and dual-species C. jejuni biofilms. Biofilms Total surface energy  (mJ/m2) Surface energy component distribution (mJ/m2) Lifshitz-Van der Waals (apolar component) Lewis acid-base (polar component) C. jejuni 62.9 16.1 46.7 C. jejuni + S. enterica 55.0 25.2 29.8 S. enterica 57.5 22.0 35.4 C. jejuni + S. aureus 56.2 24.7 31.5 S. aureus 59.4 20.4 39.0 C. jejuni + P. aeruginosa 52.5 27.1 25.4 P. aeruginosa 53.9 25.5 28.5  For biofilms formed by non-C. jejuni (i.e., S. enterica, S. aureus and P. aeruginosa), the total surface energy of S. aureus and P. aeruginosa biofilms were higher than their dual-species biofilm counterparts, but S. enterica biofilm had lower total surface energy compared to C. 66  jejuni-S. enterica biofilm. In addition, the apolar component of surface energy of biofilms formed by non-C. jejuni was lower than that of dual-species biofilms, ranging from 20.4 to 25.5 mJ/m2. The polar component of surface energy of biofilms formed by non-C. jejuni was higher than that of dual-species biofilms, ranging from 28.5 to 39.0 mJ/m2.  2.4.8 The water-holding capability of C. jejuni biofilms.  The water holding capability of biofilms was critical for the survival of biofilm under desiccation condition. The water holding capability of mono- and dual-species biofilms was evaluated by the decreased water content which was determined using FT-IR spectroscopy (Figure 2-12). Water demonstrated a distinct IR absorbance band at 3350 cm-1, the O-H stretch. All biofilms shared the similar water content after three days cultivation on NC membrane, and the intensity of water IR band was ~ 0.3 a.u. (Figure 2-13). Along with exposure of biofilms to the atmosphere, the intensity of water IR progressively decreased. The intensity of water IR band of mono-species C. jejuni biofilm decreased rapidly to 0.04 a.u. within 25 min. In contrast, the water holding capacity of dual-species C. jejuni biofilms was higher. The decrease rate of the intensity of water IR band of dual-species biofilm was much more slowly. Even after 25-min exposure to the atmosphere, the intensity of water IR band of dual-species biofilms was still maintained at a high level which was 0.25 a.u. for C. jejuni-S. enterica biofilm, 0.18 a.u. for C. jejuni-S. aureus biofilm and 0.20 a.u. C. jejuni-P. aeruginosa biofilm, respectively.  67   Figure 2-12. The water content of biofilms decreased over time which was reflected by the decrease of the intensity of water IR band at 3350 cm-1. The IR spectra of mono- and dual-species C. jejuni biofilms were collected using the Fourier transform infrared spectroscopy at 5-min intervals: a) the IR spectra of C. jejuni biofilm, b) the IR spectra of C. jejuni-S. enterica biofilm, c) the IR spectra of C. jejuni-S. aureus biofilm, d) the IR spectra of C. jejuni-P. aeruginosa biofilm.  68   Figure 2-13. The water holding capability of mono- and dual-species C. jejuni biofilms was reflected by the decrease of intensity of water IR band. The IR water band of different biofilms was determined by Fourier transform infrared spectroscopy, as indicated by the featured absorbance band at 3350 cm-1: a) the change of the intensity of IR water band of C. jejuni biofilm, b) the change of the intensity of IR water band of S. enterica and C. jejuni-S. enterica biofilms,  c) the change of the intensity of IR water band of S. aureus and C. jejuni-S. aureus biofilms; d) the change of the intensity of IR water band of P. aeruginosa and C. jejuni-P. aeruginosa biofilms. (solid line: biofilms formed by C. jejuni with or without other bacteria, dash line: biofilms formed by S. enterica, S. aureus, and P. aeruginosa individually). Asterisk denotes significant difference (P < 0.05).  69  No significant difference (P > 0.05) was observed for water holding capability of biofilms formed by P. aeruginosa with or without C. jejuni. In contrast, the water capability of biofilms formed by S. enterica and S. aureus was significantly lower than their dual-species biofilm counterparts (Figure 2-13).   2.5 Discussion C. jejuni could form biofilms on the surface of different materials, including plastics (Trachoo et al., 2002; Asakura et al., 2007a; Reeser et al., 2007), stainless steel (Sanders et al., 2007; Hanning et al., 2008), and glass (Kalmokoff et al., 2006). The biofilm formation capability of C. jejuni varied a lot due to different strains. For example, C. jejuni RM 1221 was unable to form a biofilm even in a well-controlled laboratory environment; in contrast, C. jejuni NCTC 11168 could form a relatively intense biofilm under the same condition (Brown et al., 2015b). C. jejuni F38011 used in this study is a human clinical isolate. This strain could only form a thin biofilm at both solid-air interface (on the surface of NC membrane) and solid-liquid interface (in 96-well plate). The biofilm formation capability of C. jejuni F38011 was similar to other C. jejuni strains reported in the previous studies (Gunther and Chen, 2009; Teh et al., 2010); therefore the result derived from this strain could be representative.  Environmental conditions are critical for the biofilm formation of C. jejuni. The aerobic condition was reported to stimulate the biofilm formation of C. jejuni at the air-solid interface (Reuter et al., 2010). The high flow rate can generate a high shear force which would increase the structural porosity of C. jejuni biofilm formed at liquid-solid interface (Ica et al., 2012). A photonic-based microfluidic platform was recently developed to elucidate the influence of hydrodynamic condition on biofilm formation (Feng et al., 2015). In the current study, these 70  factors were not included because this will complicate the evaluation of the protection of biofilm to encased C. jejuni against aerobic stress. In the current study, the viability of C. jejuni cells in mono-species biofilm could not be detected using plating method over four day’s exposure to aerobic stress (Table 2-1). However, CLSM result demonstrated a large number of cells at the bottom of biofilm were still alive (Figure 2-1 A and B). According to previous studies, C. jejuni might lose cultivability and enter the “viable but non-culturable” state in response to unfavorable conditions, such as aerobic stress, desiccation, and starvation (Lázaro et al., 1999; Tholozan et al., 1999). Hence, we speculated that C. jejuni cells at the bottom of biofilm might share a viable similarity to VBNC cell and had enhanced tolerance to the aerobic stress. C .jejuni could also develop multispecies biofilm with other bacteria (Ica et al., 2012) or resides in a pre-established biofilm (Buswell et al., 1998; Trachoo et al., 2002; Sanders et al., 2007; Hanning et al., 2008). Sanders and coauthors reported that the survival of C. jejuni cells was prolonged by residing in pre-existing biofilms (Sanders et al., 2007). In another study, C. jejuni cells in the pre-established biofilms by microbes in the aquatic environment could survive a doubled longer period than that as dispersed single cells (Buswell et al., 1998). Our current study demonstrated that C. jejuni could form a dual-species biofilm with other bacteria. However, C. jejuni was not the leading species to form the biofilm. Compared to mono-species C. jejuni biofilm, the formation level of dual-species C. jejuni biofilms was significantly higher (Figure 2-2 and Figure 2-3). In addition, the dual-species biofilm provided more protection to C. jejuni cells than that of mono-species C. jejuni biofilm which enabled C. jejuni cells to maintain the culturable state for a longer period under aerobic stress (Table 2-1).  71  An interesting observation was that although dual-species C. jejuni-P. aeruginosa biofilm was as intense as other dual-species biofilms, the survival period of C. jejuni cells in this biofilm were the shortest (Table 2-1). Gram-negative bacteria could secret outer membrane vesicles, and this vesicle could inhibit the growth of other bacteria (Flemming and Wingender, 2010). The membrane vesicles of P. aeruginosa contained various compounds (e.g., B-band lipopolysaccharide with hemolysin, phospholipase C, and alkaline phosphatase) that could inhibit the growth of other bacteria (Kadurugamuwa and Beveridge, 1995). In a nutrient-limited environment, such as in a biofilm, we believed that C. jejuni and P. aeruginosa were in a competitive relationship. In the early stage of biofilm formation, P. aeruginosa cells could multiply rapidly and take most of nutrient and space which limited the growth of C. jejuni cells. Along with the biofilm development, P. aeruginosa could progressively secrete secondary metabolites (e.g., hemolysin, phospholipase C, and alkaline phosphatase) which might be toxic to C. jejuni cells. This would further negatively affect the survival of C. jejuni in the biofilm.  The cells in biofilms usually were more tolerant to stresses. However, the mechanism of this tolerance was not well characterized yet. Researchers had proposed several possible reasons : (1) the chemical compositions of biofilm could chemically react with and neutralize the stresses (Allison and Matthews, 1992); (2) the chemical composition of biofilm could serve as nutrient reservoirs that prolonged the survival of encased biofilm cells (Decho et al., 2005);the particular structure of biofilm can physically trap stresses and delay the penetration of these stresses (Ica et al., 2012). Hence, the understanding of the chemical composition and physical structure of biofilm would be critical to understanding the tolerance of biofilm. Biofilms were mainly composed of proteins, polysaccharides, lipids and nucleic acids (Flemming and Wingender, 2010). These components could react with and neutralize different stresses. In the previous 72  studies, Raman spectroscopy has been applied to determine chemical components of mono-species C. jejuni biofilm (Lu et al., 2012a; Lu et al., 2012b). In this study, Raman spectroscopy was applied to characterize not only mono-species but also dual-species biofilms. We found that the chemical compositions of dual-species biofilms were quite different from that of mono-species biofilm (Figure 2-3). Specifically, Raman bands at 1519 and 1345 cm-1 could be assigned to polysaccharides which were significant components in C. jejuni-S. aureus and C. jejuni-P. aeruginosa biofilms, but were not prominent in mono-species C. jejuni biofilm. As indicated by the high intensity of Raman bands derived from dual-species biofilms, we believed that dual-species biofilms contained more content of organic substances than that of mono-species biofilm. In addition, Raman spectral patterns of biofilms formed by non-C. jejuni bacteria (i.e., S. enterica, S. aureus and P. aeruginosa) were highly similar to that of dual-species biofilms counterparts, indicating that non-C. jejuni bacteria contributed more to the chemicals compositions of dual-species biofilms than that of C. jejuni did.  The relationship between chemical compositions and its structural properties of the biofilm was also discussed. The previous study found that the presence of a non-cellular protein was one of the prerequisites for the formation of biofilm and closely associated with the stability of biofilm (McSwain et al., 2005). In the current study, the variation of chemical composition could also be correlated with the variation of structural properties between mono- and dual-species biofilms. The results of AFM, FTIR and contact angle measurement (Figure 2-7, Figure 2-9, Figure 2-13 and Table 4) showed that dual-species biofilms had a compact structure with a smoother surface, a higher water holding capability and lower apolar surface energy than that of mono-species C. jejuni biofilm. These distinct surface features of dual-species biofilms could be due to the higher level of polysaccharides and proteins content in dual-species biofilms than that 73  in mono-species C. jejuni biofilm (Figure 2-3). In addition, this also suggested that polysaccharides and proteins might contribute more to the structural properties of dual-species biofilms than other components (e.g., lipids and nucleic acids). We speculated that the presence of non-C. jejuni bacteria (i.e., S. enterica, S. aureus and P. aeruginosa) could enhance the amount and diversity of biofilm chemical compositions, and these constituents might fill the space of multicellular structure of biofilm, enhance water holding capability and influence the surface energy.  In conclusion, this study confirmed that mono-species C. jejuni F38011 culture could form a thin biofilm and protect C. jejuni cells against aerobic stress for a short period. The presence of S. enterica, S. aureus, and P. aeruginosa during biofilm formation could significantly remold the on the chemical, physical and morphological perspectives. The dual-species biofilms (1) contained a higher amount of EPS with a more complex chemical compositions; (2) were more compact with a smoother surface; (3) were less hydrophilic but with a higher ratio of apolar component/polar component of surface energy; (4) could hold the water for a longer period. These features were mainly derived from the non-C. jejuni bacteria (i.e., S. enterica, S. aureus and P. aeruginosa) in the dual-species culture, and might allow C. jejuni F38011 cells to survive the aerobic stress.  74  Chapter 3: In-situ Raman spectroscopic-based microfluidic “lab-on-a-chip” platform for non-destructive and continuous characterization of Pseudomonas aeruginosa biofilms  3.1 Summary The hydrodynamic condition was one of the critical factors that could influence the biofilm formation. We developed and validated a Raman spectroscopic-based microfluidic “lab-on-a-chip” platform for the characterization of bacterial biofilms. This innovative Raman-microfluidic platform could precisely control the flow conditions and mimic the natural hydrodynamic environment.  The biofilm formation of Pseudomonas aeruginosa was quantified by this label-free platform, and the evaluation of biofilm formation level was well correlated to that derived from a reference techniques confocal laser scanning microscopy. In addition, this Raman-microfluidic platform could also discriminate the distinct formation stages of biofilms.   3.2 Introduction A biofilm is a consortium of bacteria in which cells associate with each other and attach to a surface (de la Fuente-Núñez et al., 2013). These sessile cells are embedded within a matrix of secreted extracellular polymeric substances (EPS), including exopolysaccharides, proteins, lipids and nucleic acids, which comprise up to 90% of the biofilm (Hall-Stoodley et al., 2004). EPS not only mechanically support the structure of biofilm, but also protect biofilm cells against stresses  (Davies, 2003). Biofilms on medical devices and food processing surfaces (e.g., infusion tubes and water pipes) are highly resistant to antimicrobial treatments and disinfectants and thus represent one of the major health risks (Hall-Stoodley et al., 2004; Conlon et al., 2015).  75  The study of biofilm development is often limited to methods that involve static cultivation conditions, with the low shear flow and no nutrient exchange. On the other hand, cultivation under flow conditions more closely mimics the environment of biofilm formation due to hydrodynamic influences on the structure of biofilm and the accumulation of cell signaling (Kirisits et al., 2007). For example, the biofilm formation of rpoS-deficient Escherichia coli was impaired using hydrodynamic cultivation, compared to that under static conditions (Ito et al., 2008). The commonly used macro-scale flow cells require large volumes of media, resulting in a relatively expensive system that will not allow for spatial and temporal control of biofilm formation (Webb et al., 2003). By precisely controlling the hydrodynamic conditions, microfluidic platforms can closely simulate the appropriate environmental conditions and allow substantial reductions in the use of reagents. Microfluidic platforms have been recently applied to the study of bacterial biofilms in a high-throughput manner (Benoit et al., 2010; Kim et al., 2012).  The characterization of biofilms in a microfluidic platform is still a challenge. Most of the studies used confocal laser scanning microscopy (CLSM) coupled with staining for the quantitative studies of biofilm development (Shumi et al., 2010; Song et al., 2014). However, the staining process might influence the structure of biofilm. Furthermore, the CLSM assay could not monitor the chemical variations of biofilm continuously. We considered an alternative approach to investigate the biofilm formation using Raman spectroscopy that could observe vibrational, rotational and other low-frequency energies of a molecule in a biological system. When coupled with confocal imaging techniques, Raman spectroscopy can be used in situ to determine the chemical composition and 76  localization of bacterial biofilms in three dimensions, without staining of bacterial cells (Ivleva et al., 2008, 2009).   3.3 Materials and methods  3.3.1 Bacterial strains and growth conditions.  P. aeruginosa PAO1 wild type was cultured in tryptic soy broth (TSB) at 37°C.  3.3.2 Fabrication of microfluidic “lab-on-a-chip” platform.  The Poly-dimethylsiloxane (PDMS) based microfluidic system was fabricated in the Advanced Materials and Process Engineering Lab at UBC using classic soft lithographic techniques (Qin et al., 2010). The microfluidic platform consists of a glass substrate and a PDMS layer. The PDMS layer consists of in/outlet of channels with cultivation chamber. The dimensions of in/outlet were 400µm (width) × 40µm (height).The microchamber for biofilm cultivation is designed as a circle with dimensions of 300µm (radius) × 40µm (height). The PDMS layer was bonded to glass slide after oxygen plasma treatment. The microfluidic device was connected to a synergy pump using tubing.   3.3.3 Biofilm formation in the microfluidic “lab-on-a-chip” system.  An overnight culture of P. aeruginosa PAO1 was diluted to a concentration of ~107 CFU/ml and introduced into microchamber using a syringe pump. Bacterial culture was maintained in the cultivation chamber by stop pumping for two h to allow the attachment of P. aeruginosa PAO1 cells onto the glass surface of the microchamber. Unattached cells 77  were removed by perfusing TSB medium. The development of biofilm was set in a hydrodynamic condition by flowing media at 0.2 µl/min for 72 h.  3.3.4 Integration of confocal micro-Raman spectroscopy with the microfluidic platform.   A confocal Raman microscope system (Renishaw, Gloucestershire, UK) with 532 nm green diode laser was applied for the characterization of chemical compositions and formation level of P. aeruginosa biofilms. The spectrometer was equipped with a 1200-line/mm grating. Laser (0.2 mW laser power on the sample) was introduced through a 50× objective (Leica Biosystems, Wetzlar, Germany) into the microchamber and focused on the biofilm. While Raman signal was collected and dispersed by a diffraction grating, and finally recorded by using a 578- by 385-pixel charge-coupled device (CCD) array detector. An integration time of 30 s was applied for spectral collection over a simultaneous Raman shift range of 1800 to 400 cm-1 in an extended mode. The Raman spectrometer was controlled via WiRE software which was also responsible for spectra acquisition and processing (Renishaw, UK).   3.3.5 Confocal laser scanning microscope for biofilm quantification. Confocal laser scanning microscopy (CLSM) was applied as a reference technique to quantify the formation level of biofilm. Biofilm was stained using a LIVE/DEAD BacLight Bacterial Viability Kit (Molecular Probes, Eugene, OR). A mixture of 1 µM of Syto-9 (green fluorescence for live cells) and 5 µM of propidium iodide (PI; red fluorescence for dead cells) was injected into microchamber at 2 µl/min for 2 hours. 78  Images were then taken on a Fluoview FV1000 confocal laser scanning microscope (CLSM) (Olympus, Melville, NY) with the multi-laser channel at 488nm (green fluorescence) and 543 nm (red fluorescence). The bio-volume of biofilm, three-dimensional reconstruction, and live/dead cells distribution were conducted using Imaris software (Bitplane, South Windsor, CT).   3.3.6 Chemometric models. The chemical information obtained from Raman spectroscopy was correlated with the result from CLSM using partial least-squares regression (PLSR) model in MATLAB (Mathworks, USA).   3.4 Results and discussion  Here, we report the in-situ characterization of Pseudomonas aeruginosa biofilms cultivated in a microfluidic platform using confocal micro-Raman spectroscopy in a non-destructive and continuous manner. The multi-channel microfluidic chip was connected to a pump with bio-compatible tubing. The nutrient broth was continuously infused from the inlet and expelled through the outlet during the biofilm formation. The cultivation chamber containing the biofilm was loaded onto a sample stage, which motorized the chip location at a spatial resolution of 2 µm in the horizontal phase and a 3 µm in vertical phase. The confocal micro-Raman microscope was integrated with the microfluidic platform. Laser introduction and Raman signal collection were conducted through the same 50× objective. The Raman scattering signal was processed through an aperture, passed through a polarizer, and finally collected by a CCD detector (Figure 3-1).  79   Figure 3-1. Schematic illustration of the Raman spectroscopic-based microfluidic “lab-on-a-chip” platform for cultivation and characterization of bacterial biofilms.   To demonstrate the chemical composition of the biofilm, we need to clarify the Raman signals from chip substrate (i.e., glass slide and polydimethylsiloxane (PDMS) layer) first. The Raman spectra of the substrate were collected by focusing the Raman laser in the microfluidic chip with broth. The substrate of microfluidic chip generated distinct Raman peaks at 485, 610, 703, 785, 860, 1125, and 1402 cm-1. After initial attachment of bacterial cells to the substrate, biofilm started to develop and cover the substrate. The intensity of Raman peaks due to the substrate decreased significantly by 24 h (Figure 3-2). Although biofilm continuously accumulated, the peak intensities from the substrate remained relatively constant, indicating no overlap between biofilm peaks and 80  substrate peaks. Therefore, peaks that were different from substrate peaks and changed during biofilm development could be regarded as deriving from P. aeruginosa biofilm.  Figure 3-2. Raman spectroscopy determines microfluidic chip substrate as background for biofilm characterization. (a) Prominent peaks in Raman spectra of the substrate and P. aeruginosa biofilm grown in the microchamber; (b) Variations in Raman intensities of the corresponding peaks (485, 610, 703, 785, 860, 1256, and 1402 cm-1). Shadow regions highlight variations in peak intensities of microfluidic chip substrate (as background) during P. aeruginosa biofilm development.  The characteristic Raman peaks of biofilm were averaged and evident in the wavenumber range of 400 to 1800 cm-1 in Figure 3-3. Peaks at 746, 1123, 1307 and 1580 cm-1 were prominent and could be observed after 24 h cultivation (Figure 3-3A). Peaks at 746 and 1580 cm-1 were assigned as specific ring structures in nucleic acids (i.e., adenine, 81  thymine, guanine), while peaks at 1123 and 1580 cm-1 referred to C-C stretching and CH3/CH2 twisting or bending respectively which widely present in carbohydrates, proteins, and lipids (Table 3-1). We defined the first 24 h as the “early stage” of biofilm development. The results demonstrated that nucleic acids, proteins, lipids, and carbohydrates were synthesized when biofilm started to form. Compared to peaks corresponding to other molecules (i.e., proteins, lipids, and carbohydrates), the intensity of peaks corresponding to nucleic acids was higher, indicating that nucleic acids were preferentially synthesized at this stage. Consistent with previous reports, extracellular DNA has been proposed to serve as an important structural component binding surrounding substances and supporting the growth of P. aeruginosa biofilms when biofilms initially established (Whitchurch et al., 2002). Our findings validated that extracellular DNA served as the fundamental material in an early developed biofilm in the fluidic environment. After 36 h cultivation, the intensity of the major early peaks (i.e., at 746, 1123, 1307 and 1580 cm-1) increased significantly (P < 0.05) and then remained relatively constant to 45 h. The significant change occurred at 36 h could be regarded as a stage switch of biofilm development. Accordingly, we defined 36 h to 45 h as the “mid stage” of biofilm development. The major compositions of biofilm at “mid stage” were almost the same as that of “early stage,” but with a higher amount. It indicated that the biofilm had been preliminarily established and synthesis of basic components was temporarily ceased. The intensity of the major early peaks (i.e. at 746, 1123, 1307 and 1580 cm-1) increased significantly (P < 0.05) up to a maximum at 48 h and then remained relatively constant (Figure 3-3B), indicating that 48 h was another critical time point for the stage switch of biofilm development, and the synthesis of basic components in P. 82  aeruginosa biofilm was paused after 48 h. This result indicated that accumulation of basic components into biofilm followed a periodic pattern rather than a continuous pattern.  Figure 3-3. Raman spectroscopy monitoring of the development of P. aeruginosa biofilm in the microfluidic chamber. (A) Prominent peaks appearing within the first 24 h (early stage) are shaded; (B) Variations in intensities of the corresponding Raman peaks (746, 1123, 1307, and 1580 cm-1) over time. (C) Prominent peaks appearing after 48 h (late stage) are shaded; (D) Variations in intensities of the corresponding Raman peaks (918, 968, 1167, 1223, 1333, and 1357 cm-1) over time. 83  Table 3-1. Raman band assignments of P. aeruginosa biofilm grown in a microfluidic “lab-on-a-chip” platform (De Gelder et al., 2007; Ivleva et al., 2009; Lu et al., 2012b; Tang et al., 2013; Masyuko et al., 2014). Peaks (cm-1) Assignment Nucleic acids Proteins Lipids Carbohydrates 746 T ring str     918  Proline; hydroxyproline  Glycogen 968   Lipids  1123  C-C str  C-N, C-C str  C-C str, C-O-C glycosidic link; ring breath, sym  1167  C-C str   1223  Amide III    1307  CH3/CH2 bend CH3/CH2 bend  1333  δ(CH)   δ(CH)  1357 G ring str    1580 G, A ring str     Abbreviations. Bend: bending, breath: breathing, def: deformation, scis: scissoring, str: stretching, asym: asymmetric, sym: symmetric.  84  P. aeruginosa biofilm also showed Raman peaks at 918, 968, 1167, 1223, 1333, and 1357 cm-1 (Figure 3-3). Peaks at 918, 1167, 1223, and 1333 cm-1 were assigned to carbohydrates and proteins, while peaks at 968 and 1357 cm-1 were derived from lipids and nucleic acids (Table 3-1). The intensity of these peaks was too weak to be observed until 45 h, but increased substantially from 45 h to 48 h, and then kept relatively constant until 72 h (Figure 3-3C). After 48 h of cultivation, biofilm was considered to enter “late stage” development using these peaks as indicators. Compared to the peaks shown in the spectra of biofilm at 24 h cultivation, peaks at 918, 968, 1167, 1223, 1333, and 1357 cm-1 in the spectra of biofilm at 48 h cultivation demonstrated 3.1, 3.2, 6.0, 3.7, 3.5 and 1.7 fold increases in intensity, respectively (Figure 3-3D). The intensity of peaks assigned to proteins and carbohydrates (918, 1167, 1223, and 1333 cm-1) increased more than those assigned to nucleic acids (968 and 1357 cm-1), indicating proteins and carbohydrates accounted for the largest proportion of synthesized substances at this stage. Taken together, we defined biofilm developmental stages according to the appearance of prominent peaks and the significant increases in peak intensity. The results indicated that P. aeruginosa biofilm produced different substances at two different stages (i.e., early stage and late stage).  To confirm the variations of P. aeruginosa biofilms developed at different time points shown in the Raman spectra, principal component analysis (PCA) was utilized. PCA was able to cluster samples on the basis of chemical information and enable further differentiation. Figure 3-4 demonstrates analytical groups for different biofilm samples according to the score plot of principal component 1 (PC1) and component 2 (PC2) from the PCA model. The loading profiles of PC1 and PC2 accounted for 92.85% and 4.78% 85  of the total variation in spectra, respectively (Figure 3-5). The separating lines, derived from a supportive vector machine classification algorithm, clearly separated clusters due to biofilms at 24 h, biofilms at 36 h to 45 h, and biofilms at 48 h to 72 h into three groups. The Mahalanobis distance between these groups ranged from 5.57 to 12.83. Clusters with interclass distance values higher than 3 are considered to be significantly different (P < 0.05) from each other (Lu et al., 2013a). This result further confirmed the obvious stage switches occurred at 24-36 h (early stage) and 45-48 h (late stage) during biofilm development within the first 72 h (Figure 3-3). We accordingly defined the biofilm grown between 24 h and 48 h as the “mid stage.”  Figure 3-4. The representative two-dimensional principal component analysis for the segregation of P. aeruginosa biofilms at different development stages. The boundary lines could be used to cluster different groups. 86   Figure 3-5. The loading profile of principal component analysis. Dash line is the plot of PC1 and solid line is the plot of PC2. Absolute values of peaks (x-axis) represent the contribution in each component (y-axis).   As a parallel study, CLSM was applied to quantify the extent of formation of P. aeruginosa biofilm. CLSM coupled with Cyto-9 dye added at various time points to identify biomass of biofilm, optical sectioning, and reconstruction to give a 3D perspective.  The formation level of biofilm increased as a function of cultivation time (Figure 3-6A). At 24 h, the biofilm consisted of a thin, nearly confluent layer of bacteria without complex structures. At 36 h, the confluent layer had increased more than double in depth. Between 42 and 45 h, the biofilm remained relatively similar to that seen at 36 h, although it must be pointed out that the necessity to stain biofilms for this method means that different biofilms were imaged at each time point. At 48 h, the biofilm increased in thickness, and denser microcolonies started to form. Biofilms were very mature after 72 h 87  of growth, which is consistent with the results obtained using a more conventional large volume flow cell apparatus (de la Fuente-Núñez et al., 2014). Based on CLSM images, the mean biofilm thickness quantifiably reflect the development of biofilm (Figure 3-6B). The total height of cultivation chamber in the microfluidic chip was 50 µm. At 24 h, mean biofilm thickness was 5.24 µm. Up to 36 h, it had a 2.4-fold increase to 12.71 µm and remained constant until 45 h. The mean thickness of biofilm reached a maximum of 24.75 µm at 48 h cultivation, which was 1.95-fold greater than that of biofilm at 36 h.   Figure 3-6. Representative confocal laser scanning microscopic images of P. aeruginosa biofilms grown in a microfluidic chamber. (A) Each panel shows reconstructions from the top in the large panel and sides in the right and bottom panels (xy, yz, and xz dimensions). Biofilm thickness (μm) increased over time. (B) All the values were measured by confocal laser scanning microscopy. Statistical significance was determined using Student’s t-test (* denotes P < 0.05). 88   Both the Raman and CLSM results demonstrated that the formation level of P. aeruginosa biofilm increased significantly (P < 0.05) after 24 h (endpoint of the early stage) and 48 h (starting point of the late stage). Therefore, the correlation between the Raman and CLSM results was examined. Partial least squares regression (PLSR) model was constructed (Figure 3-7). When fitted the calculated biofilm thickness (from Raman spectra) to the measured biofilm thickness (from CLSM) in the PLSR model, these two sets of data showed a close correlation, with a regression coefficient (R-square) of 0.9783. Thus, the PLSR result confirmed that chemical variations (Raman) and thickness variations (CLSM) of P. aeruginosa biofilms cultivated in the microfluidic chip occurred concurrently.   Figure 3-7. Correlation of biofilm thickness measured by confocal laser scanning microscopy and calculated by Raman spectroscopy coupled with partial least-squares regression.  89  According to previous reports, biofilm development had four major stages, including attachment, accumulation, maturation, and dispersion (Monroe, 2007). Our current study depicted two important stage switches from attachment to early accumulation (early stage to mid stage) and then to maturation (mid stage to late stage) based on chemical and thickness assessments. However, no evidence was obtained to demonstrate any stage switch from maturation to dispersion. This was most likely due to the fact that dispersion usually occurred at the end of a long period of cultivation and was induced by intensive stresses (e.g., starvation and accumulation of toxic wastes) or regulated by signaling molecules (Bjarnsholt et al., 2010; McDougald et al., 2012). In the current study, biofilm was developed in a fluidic environment in which nutrients were supplied continuously. In addition, wastes were continuously expelled to reduce the accumulation of toxic substances and signaling molecules. Hence, it is logical to expect a longer maturation time in this hydrodynamic condition than that in a static condition. Cultivation for 72 h may not be sufficient time to monitor any biofilm switch to the dispersion stage. Another explanation was that accumulation and dispersion within a biofilm might occur simultaneously when the biofilm was fully mature (Klausen et al., 2006). Hence, the biomass and thickness were in a dynamic balance for a long period, and the maturation and dispersion stages could not be differentiated. Long-Term monitoring might be necessary to enable completion of the biofilm dispersion stage. Identification of a specific molecule synthesized at the dispersion stage would provide further evidence for identifying this important stage.    90  3.5 Conclusions This study presented an attempt to develop a non-destructive and label-free in-situ platform to characterize bacterial biofilms in a precisely controlled hydrodynamic environment. The Raman spectroscopy-based microfluidic “lab-on-a-chip” platform demonstrated the ability to characterize and distinguish P. aeruginosa biofilms in different developmental stages (i.e., early, mid, and late stages). In addition, Raman results were well correlated with CLSM analyses, demonstrating its feasibility for quantifying biofilm thickness and determining chemical composition simultaneously. Future work was required to apply this platform to screen antimicrobials for the inactivation of biofilms in a high-throughput manner.   91  Chapter 4: Environmental stress-induced bacterial lysis and extracellular DNA release contribute to Campylobacter jejuni biofilm formation  4.1 Summary Campylobacter jejuni is a microaerophilic bacterium and supposed to persist in a biofilm to antagonize the environmental stress. This study investigated the influence of environment on C. jejuni biofilm formation and the corresponding mechanisms. We report an extracellular DNA (eDNA)-mediated mechanism of biofilm formation in response to aerobic and starvation stresses. The eDNA was determined to be a major constitutions of C. jejuni biofilm and closely associated with bacterial lysis. The deletion mutation on the stress response genes spoT and recA enhanced the aerobic influence by stimulating lysis and increasing eDNA release. Flagella were also involved in biofilm formation but mainly contributed to attachment rather than induction of lysis. The addition of genomic DNA from either Campylobacter or Salmonella resulted in a concentration-dependent stimulation effect on biofilm formation but not due to forming a pre-coating DNA layer. Enzymatic degradation of DNA by DNase I disrupted biofilm structure and dispersed the encased bacteria. In a dual-species biofilm, eDNA separated Campylobacter and Salmonella at distinct spatial locations that protect Campylobacter away from the oxygen stress. Our findings demonstrated an essential role and multi-functions of eDNA in biofilm formation of C. jejuni, including facilitating initial attachment, establishing and maintaining biofilm structure and allocating bacteria cells.   92  4.2 Introduction  Biofilms are structured bacterial communities encased in a self-produced extracellular polymeric matrix. It is mainly composed of proteins, polysaccharides, lipids and nucleic acids. As one of the well-recognized bacterial survival modes, biofilm owns various physiological capabilities in response to environmental stresses and exhibits inherent tolerance to the host defense system (Costerton et al., 1999). Bacterial cells encased in a biofilm demonstrate significantly elevated tolerance to most of the conventional disinfectants and antimicrobial agents (Fux et al., 2005). Such survival behavior is of potential risk because over 60% of the chronic bacterial infections are associated with biofilm formation (Costerton et al., 1999).  Campylobacter jejuni is recognized as one of the leading causes of bacterial foodborne illness worldwide. Raw meat, untreated water, unpasteurized milk and animals (e.g., birds and pet) are the major reservoirs of C. jejuni (Acheson and Allos, 2001). The paradox associated with this fastidious bacterium is that C. jejuni is vulnerable to environmental stress, but the incidence of Campylobacter infections is high and progressively increases. For example, the reported cases of Campylobacter infection in the United States increased by 9% from 2006 to 2015 (CDC, 2016). It is suggested that biofilm may contribute to the survival and distribution of C. jejuni in the natural environment (Buswell et al., 1998).  C. jejuni is capable of forming a mono-species biofilm on different substrates (Reeser et al., 2007; Li et al., 2017) as well as residing in a well-developed multispecies biofilm (Hanning et al., 2008). C. jejuni cells in the biofilm could survive aerobic stress, and their viability could be maintained twice as long as that in a planktonic state (Feng et al., 2016). In addition, the biofilm is able to facilitate the horizontal transfer of antibiotic resistance genes into Campylobacter, such as the ones resistant to kanamycin and chloramphenicol (Bae et al., 2014). It is, therefore, 93  reasonable to speculate that biofilm is the protection vehicle where C. jejuni resides for the survival under the natural environment. The biofilm formation may also explain the high prevalence of Campylobacter-associated foodborne diseases worldwide. Recent studies suggest that environmental stresses, such as high oxygen level and relatively low temperature, can stimulate C. jejuni biofilm formation to a relatively high level (Reeser et al., 2007; Reuter et al., 2010). The molecular investigation has identified several critical genetic factors that can affect C. jejuni biofilm formation, such as Campylobacter planktonic growth regulator cprRS, stringent response regulator spoT and global regulator csrA (Gaynor et al., 2005; Reeser et al., 2007; Fields and Thompson, 2008). However, there is still a gap to correlate these genetic factors with the formation of C. jejuni biofilm in response to the environmental stresses.  DNA presents in abundance in the environment as a consequence of lysed dead organisms or via active secretion from the living organisms (Nielsen et al., 2007). Bacteria can utilize these free DNA as an important supply of nutrients or integrate the free DNA into the genome for acquiring resistance capacity (Lorenz and Wackernagel, 1994; Thomas and Nielsen, 2005). According to a previous study, Pseudomonas aeruginosa progressively released DNA into the environment during biofilm formation (Das and Manefield, 2012). Our recent study identified that the addition of meat juice with a high content of DNA (e.g., chicken juice or pork juice) not only supported the growth of C. jejuni cells but also boosted the level of biofilm formation (Li et al., 2017). Therefore, we speculate that eDNA might mediate the biofilm formation in response to different environments. Therefore, the current study aims to characterize the role of eDNA in C. jejuni biofilm formation in response to two common environmental stresses, namely aerobic condition, and starvation condition.   94  4.3 Materials and methods 4.3.1 Bacterial strains and cultivation conditions.  The bacterial strains and plasmid used in the current study are summarized in Table 4-1. Routine cultivation of C. jejuni was conducted either on Mueller-Hinton (MH) agar supplemented with 5% defibrinated sheep blood (MHB agar) or in MH broth with constant shaking at 37°C under a microaerobic condition (85% N2, 10% CO2, 5% O2). When necessary, kanamycin, chloramphenicol or tetracycline was supplemented either into MHB agar or MH broth at a final concentration of 50 µg/ml, 8 µg/ml or 10 µg/ml, respectively. Salmonella and Escherichia coli strains were cultivated in Luria-Bertani (LB) broth (BD Difco) at 37°C under aerobic condition. Where indicated, kanamycin or ampicillin was supplemented at a final concentration of 50 µg/ml and 100 µg/ml, respectively. Table 4-1. Bacterial strains and plasmid used in the current study. Strain or plasmid Description Reference Strains   C. jejuni F38011 human clinical isolate (Feng et al., 2016) C. jejuni Human 10 human clinical isolate (Li et al., 2017) C. jejuni 81116 human clinical isolate (Neal‐McKinney et al., 2010) C. jejuni ATCC 33560 product, quality control strain ATCC company C. jejuni 87-95 human clinical isolate Laboratory collection obtained from Dr. Michael Konkel (Washington State University) C. jejuni NCTC 11168 human clinical isolate (Parkhill et al., 2000) 95  Strain or plasmid Description Reference C. jejuni 1658 environmental isolate Laboratory collection obtained from Dr. Gölz, Greta (Free University Berlin) C. jejuni F38011ΔspoT spoT gene deletion mutant of C. jejuni F38011 strain, KanR This study C. jejuni F38011ΔrecA recA gene deletion mutant of C. jejuni F38011 strain, CmR This study C. jejuni F38011ΔflaAB flaA and flaB genes deletion mutant of C. jejuni F38011 strain, mobility deficiency mutant, TetR (Neal‐McKinney et al., 2010) C. jejuni F38011::spoT spoT gene complementary strain of C. jejuni F38011, KanR&CmR This study C. jejuni F38011::recA recA gene complementary strain of C. jejuni F38011, CmR&KanR This study C. jejuni F38011::flaAB flaA and flaB genes complementary strain of C. jejuni F38011, TetR&CmR (Neal‐McKinney et al., 2010) C. jejuni GFP green fluorescent protein expression strain of C. jejuni F38011, KanR (Mixter et al., 2003) 96  S. Typhimurium SL1344 Human clinical isolate (Knodler et al., 2010) Strain or plasmid Description Reference S. Typhimurium SL1344 -RFP Red fluorescent protein expression of S. Typhimurium SL 1344 strain, StrR (Knodler et al., 2010) E. coli DH5α product, generation of recombinant plasmids Invitrogen Plasmid   pUC19 product, suicide vector, AmpR Invitrogen pUC18K2 cloning vector, KanR (Gaynor et al., 2005) pRY111 cloning vector, CmR (Buelow et al., 2011) A gift from Dr. Michael Konkel (Washington State University) pRY107 cloning vector, KanR A gift from Dr. Michael Konkel (Washington State University) CmR strands for chloramphenicol resistance (8 µg/ml); AmpR strands for ampicillin resistance (100 µg/ml); KanR strands for kanamycin resistance (50 µg/ml); StrR strands for streptomycin resistance (100 µg/ml). TetR strands for tetracycline resistance (10 µg/ml)  4.3.2 Construction of C. jejuni F38011 spoT and recA knockout mutant strains.  C. jejuni F38011 spoT deletion mutant was generated via homologous recombination and subsequent insertion of a kanamycin resistance cassette. The gene sequence of spoT in C. jejuni F38011 was identical to the gene sequence of spoT (Cj1272c) in C. jejuni 11168, which was 97  confirmed by nucleotide BLAST. A 430-bp upstream cassette of the spoT gene was PCR-amplified using the primer pair of spoT-FF/spoT-FR. Similarly, a 476-bp downstream cassette of the spoT gene was PCR-amplified using the primer pair of spoT-RF/spoT-RR. The kanamycin resistance gene (KanR) was amplified using the primer pair kan-F/kan-R from the plasmid pUC18K2 (a gift from Dr. Erin Gaynor at the University of British Columbia). The vector pUC19 was digested with EcoRI and XbaI. All the four fragments above were purified using the Gel/PCR purification kit (Froggabio), followed by multiple fragment ligation using NEBuilder® HiFi DNA Assembly Cloning Kit (New England Biolabs® INC.). The pUC19-spoT::KanR disruption construction was naturally transformed into C. jejuni F38011, as C. jejuni is a naturally competent bacterium (Davis et al., 2008). Transformants were selected on MHB agar plates supplemented with kanamycin (50 µg/ml). The deletion of spoT gene and insertion of KanR was identified by PCR.  C. jejuni F38011 recA deletion mutant was generated via homologous recombination and subsequent insertion of a chloramphenicol resistance cassette. The gene sequence of recA in C. jejuni F38011 was identical to the sequence of recA (Cj1673c) in C. jejuni 11168, which was confirmed by nucleotide BLAST. A 428-bp upstream cassette of recA gene was PCR-amplified using the primer pair of recA-FF/recA-FR. Similarly, a 626-bp downstream cassette of recA gene was PCR-amplified using the primer pairs of recA-RF/recA-RR. The chloramphenicol resistance gene (CmR) was amplified using the primer pair of cm-F/cm-R from the plasmid pRY111 (a gift from Dr. Brett Finlay at University of British Columbia). The vector pUC19 was digested with EcoRI and XbaI. All the four fragments above were purified using the Gel/PCR purification kit (Froggabio), followed by the multiple fragment ligation using NEBuilder® HiFi DNA Assembly Cloning Kit (New England Biolabs® Inc.). The pUC19-recA::CmR disruption construction was 98  naturally transformed into C. jejuni F38011. Transformants were selected on MHB agar plates supplemented with chloramphenicol (8 µg/ml). The deletion of recA gene and insertion of CmR was identified by PCR. The primer used for mutant construction was listed in Table 4-2.   Table 4-2. Primers used in the current study.  Primer Sequence (5’-3’) spoT-FF CGGAATTCAAGTGGAGAGCCTTATGCGG spoT-FR CTTGGTACCGTCTATGGGCTATTGGGGCA spoT-RF GCGGATCCAGCCAGACGTATTAGACAAGTAGC spoT-RR GATCTAGATCTCAAAATAATCTACCGCCGA kan-F TGTATATGCCCCAATAGCCGGTACCCGGGTGACTAACTAGGAGGAATAA kan-R GCTACTTGTCTAATACGTCTGACGGATCCCCGGGTCATTATTCCCTCCAGGTACTA recA-FF TTGTAAAACGACGGCCAGTGATTCAACGCCTTTTCCGCCAAATC recA-FR AGCAACGCGATCTAGCTATCGCGGCCTAGGGTACC GGAGAGGGTTTAAGCCGTGA recA-RF ATATTAGTTCGATTCAACAT GGATCCACATCAAGCGCATGTTCTGC recA-RR CAAGCTTGCATGCCTGCAGGTCGACTCTAG99  ATGCTGTGCGTAAAAGTGCAT Primer Sequence (5’-3’) cm-F TCACGGCTTAAACCCTCTCCGGTACCTTACGCCCCGCCCTGCCATCATCGCAGTA cm-R GCAGAACATGCGCTTGATGTGGATCCATCGAGATTTTCAGGAGCTAAGGAAGCTAA  flaA-F GCTTATGCTATAAAAGCAGGTTCA  flaA-R GTCAACCTTACCTATAGTCACACCA flaB-F AACAGGAGTTCGTGCAACTT flaB-R CATCCGATGTTTTTCCAGACTTTA rpoA-F CGAGCTTGCTTTGATGAGTG rpoA-R AGTTCCCACAGGAAAACCTA spoT-CF CGGTATCGATAAGCTTGATATCGAATTCGCGCTGTAGGATCAAACCCT spoT-CR GCTCCACCGCGGTGGCGGCCGCTCTAGAAGAGCTGTGGAAATTGATGCAG recA-CF CGGTATCGATAGGCTTGATATCGAATTCACCACTTGGAACTATGGCCG recA-CR GCTCCACCGCGGTGGCGGCCGCTCTAGATTGCTCCACTCAAAGCGACT    100   4.3.3 Construction of C. jejuni F38011 spoT and recA complementary strains.  The complementary plasmid for spoT gene was derived from the pRY111 vector (a gift from Dr. Konkel at Washington State University). The insertion fragment containing upstream (500 bp) and downstream (150 bp) regions of spoT gene were PCR-amplified using primer pairs of spoT-CF/spoT-CR. The amplicon containing spoT gene was ligated with EcoRI/XbaI-digested pRY111 using NEBuilder® HiFi DNA Assembly Cloning Kit (New England Biolabs® Inc.). The complementary plasmid pRY111-spoT was then transformed into the C. jejuni F38011 ΔspoT mutant. Transformants were selected on MH agar supplemented with chloramphenicol (8 µg/ml). The presence of the vectors in the complementary strain was confirmed by PCR. The complementary plasmid for recA gene was derived from the pRY107 vector (a gift from Dr. Konkel at Washington State University). The insertion fragment containing upstream (500 bp) and downstream (100 bp) regions of recA gene were PCR-amplified using primer pairs of recA-CF/recA-CR. The amplicon containing recA gene was ligated with EcoRI/XbaI-digested pRY107 using NEBuilder® HiFi DNA Assembly Cloning Kit (New England Biolabs® Inc.). The complementary plasmid pRY107-recA was transformed into the C. jejuni F38011 ΔrecA mutant. Transformants were selected on MH agar supplemented with Kanamycin (20 µg/ml). The presence of the vectors in the complementary strain was confirmed by PCR.  4.3.4 Biofilm formation either in 96-well plate or on nitrocellulose membrane under different environment.  An overnight culture of C. jejuni was collected, washed and diluted to 0.003 of OD600 (~107 CFU/ml) in MH broth and then cultivated in sterile polystyrene 96-well plate in an optimal 101  growth environment for biofilm formation. A total of 200 µl of the diluted bacterial culture was added to each well of a sterile polystyrene 96-well plate. The 96-well plate was incubated in a microaerobic environment (85% N2, 10% CO2, 5% O2) at 37°C for up to 72 h. To cultivate biofilm in 96-well plate at the starvation condition, C. jejuni overnight culture was diluted to 0.003 of OD600 in phosphate buffered saline (PBS, pH ~7.0 to 7.2). A total of 200 µl of the diluted bacterial culture was added to each well of a 96-well plate and incubated in a microaerobic condition at 37°C for up to 72 h. C. jejuni overnight culture was washed and diluted to 0.003 of OD600 in MH broth. A total of 200 µl of the diluted bacterial culture was added to each well of a 96-well plate for biofilm cultivation. The plate was incubated under the aerobic environment (79% N2, 21% O2) at 37°C for up to 72 h.  An overnight culture of C. jejuni was washed and diluted to 0.003 of OD600 in MH broth. A total of 100 µl of the diluted bacterial culture was deposited onto the membrane at a surface area of ~3×3 cm2 nitrocellulose membrane (0.45-mm pore size, 47-mm diameter; Sartorius Stedim-type filters) for biofilm formation. The membrane was incubated on MHB agar under a microaerobic environment at 37°C and aseptically transferred to a fresh MHB agar plate every 24 h for up to 72 h.  4.3.5 Crystal violet biofilm assay.  Crystal violet staining assay was applied to quantify the formation level of biofilms developed in 96-well plate (Feng et al., 2015). After 72-h cultivation, each biofilm in the 96-well plate was washed with sterile deionized water and air dried for 15 min. A total of 200 µl of 0.5% (w/v) crystal violet solution was added to each well of the 96-well plate to stain the biofilm for 15 min. Unbound crystal violet was then washed off using sterile deionized water. Bound crystal violet 102  was dissolved in 200 µl of 95% ethanol (v/v) for 10 min. Signals from the released crystal violet were measured using a microplate reader at 595 nm (SpectraMax M2, Molecular Devices). MH broth without bacterial inoculation was stained using the same method as the control. The control signal was subsequently subtracted for background correction.  4.3.6 Fabrication of microfluidic “lab-on-a-chip” platform for biofilm formation.  Polydimethylsiloxane (PDMS)-based microfluidic device was fabricated using the soft lithographic technique (Qin et al., 2010). The schematic image of the fabrication procedure and microfluidic pattern design is described in Figure 4-1. The in/outlet-connected cultivation chamber was in the center of the device. The dimensions of inlet and outlet were 400 µm (width) × 60 µm (height) and the cultivation chamber had a circular shape with a dimension of 300 µm (radius) × 60 µm (height). The pattern was molded with PDMS and bonded to a glass slide via oxygen plasma treatment. A syringe pump was applied to control the hydrodynamic condition (e.g., flow rate) in the microfluidic device.  103   Figure 4-1. Schematic illustration of the fabrication of microfluidic “lab-on-a-chip” platform. (A) The pattern of microfluidic device was printed on a transparency. A total of 1 mL of SU-3050 permanent epoxy negative photoresist was dispensed on a silicon wafer and spun to achieve a thickness of 60 μm with the following program: 500 rpm for 10 sec with the acceleration of 100 rpm/sec and then 3000 rpm for 30 sec with the acceleration of 300 rpm/sec. The photoresist on the silicon wafer was then soft baked on a hot plate for 10 min at 95ºC. The transparency with a pattern was then loaded on the photoresist for UV exposure. The exposure energy was set as 150 mJ/cm2. After UV exposure, the photoresist was baked again at 65ºC for 1 min and then 95ºC for 5 min. The silicon wafer with photoresist was then washed with the SU-8 developer for 10 min 104  to remove the unexposed photoresist. The PDMS was then molded on the basis of the pattern on the silicon wafer. The inlet and outlet were drilled on PDMS with a puncher before bond onto a glass slide using the plasma treatment. (B) The microfluidic platform for biofilm cultivation consisted of one inlet for the infusion of nutrient broth, one outlet to expel the waste and one cultivation chamber for biofilm cultivation.   An overnight culture of C. jejuni F38011 and Salmonella enterica serovar Typhimurium SL1344 was individually washed twice using PBS and diluted to 0.03 of OD600 (~108 CFU/ml) in MH broth. C. jejuni F38011 culture was either individually introduced into the microfluidic chip to form a mono-species biofilm or mixed with S. Typhimurium SL1344 to form a dual-species biofilm. Bacterial culture in the microfluidic device was maintained for 2 h to allow for initial bacterial attachment. Biofilm cultivation was conducted by continuously flowing MH broth at a rate of 0.0002 µl/min in aerobic condition at room temperature.   4.3.7 Characterization of C. jejuni biofilm in microfluidic platform using confocal micro-Raman spectroscopy.  A confocal micro-Raman spectroscopic system (Renishaw, Gloucestershire, UK) with a 532-nm diode green laser was applied to characterize the chemical composition of C. jejuni F38011 biofilm in the microfluidic device. Raman laser was introduced into the cultivation chamber through a 50× objective (Leica Biosystems, Wetzlar, Germany) and focused onto the biofilm with the laser illumination power of 0.2 mW. Raman scattering signal was collected and dispersed by a diffraction grating, and then recorded using a 578 pixel by 384 pixels charge-coupled device (CCD) array detector. An integration time of 20 s was applied for spectral 105  collection over a simultaneous Raman shift range from 400 to 1800 cm-1. Raman spectrometer was equipped with a 1200-line/mm grating and controlled via WiRE software for spectral acquisition and processing (Renishaw, UK).   4.3.8 Quantification of the released eDNA.  The amount of the released eDNA during biofilm formation was quantified using SYBR Green I dye (Invitrogen) according to the manufacturer's protocol. Briefly, 200 µl of bacterial culture was removed from the 96-well plate and pelleted by centrifugation at 12,000 ×g for 2 min. The supernatant was collected for further analysis. SYBR Green I dye was diluted 100 times using TE buffer (10 mM Tris HCl, 1 mM EDTA, pH 8) as the working solution. A total of 5 µl of the SYBR Green I working solution was mixed with 95 µl of the collected supernatant in a well of a black 96-well plate (Greiner Bio-One) and the plate was incubated on an orbital shaker for 5 min. The fluorescence signal was recorded using a TECAN (Infinite 200 PRO, Tecan Life Sciences) with the excitation wavelength at 485 nm and emission wavelength at 535 nm. The amount of eDNA was calculated via a standard curve generated using Lambda DNA (Invitrogen, a series of 10 dilutions from 80 µg/ml to 0.156 µg/ml).  4.3.9 Gel electrophoresis of the released DNA.  Gel electrophoresis was performed to demonstrate the length of the released DNA fragment. After 3-day biofilm cultivation, each bacterial culture in 96-well plate was collected and centrifuged at 16,000 ×g for 5 min. A total of 10 µl of the supernatant was mixed with 2 µl of DNA loading dye solution (FroggaBio) and then loaded in 1% agarose gel for electrophoresis. A 1-kb ladder (Invitrogen) was used as the reference. The DNA was stained using SYBRTM safe 106  DNA gel stain (Life TechnologiesTM) according to the manufacturer’s protocol, and the DNA band was visualized on ChemiDocTM XRS gel documentation system (BIO-RAD).   4.3.10 DNase I treatment on C. jejuni F38011 biofilm.  In order to determine the role of eDNA in biofilm formation, DNase I treatment was applied either at the initial bacterial attachment stage or on a well-developed biofilm. The treatment was conducted either in 96-well plate or on a nitrocellulose membrane. To treat biofilm at the initial attachment stage, DNase I (Thermo Scientific™ DNase I) was diluted using DNase and protease-free water and added into the bacterial culture at a final concentration of 2 units/ml before biofilm formation. To test the influence of DNase I on the well-developed biofilm in 96-well plate, the supernatant was removed and then 200 µl of DNase I solution (2 units/ml) was added. The treatment was maintained for 15 min at room temperature. The reduction of biofilm was evaluated using the aforementioned crystal violet assay. To test the influence of DNase I on the well-developed biofilm on a nitrocellulose membrane, the biofilm was immersed in DNase I solution (2 units/ml) for 15 min at room temperature and then washed with PBS. The treated biofilm was air-dried and then analyzed using atomic force microscopy.   4.3.11 Atomic force microscopy.  The morphological variation of the biofilm due to DNase I treatment was determined using a Cypher atomic force microscope (Bruker, InnovaTM high-resolution system) with TR400PB tip cantilevers (Bruker, nominal spring constant: k = 0.02 N/m). C. jejuni F38011 biofilm developed on a nitrocellulose membrane was air-dried for 30 min before loading onto the AFM specimen disc (15 mm diameter, Ted Pella) for characterization. Topographic images were collected in the 107  contact mode at 8 random locations on the surface of the biofilm with an area of 8 µm × 8 µm. The scan frequency was maintained at 0.5 Hz. The AFM system was driven using NanoDrive software (Bruker, v8.06) and the AFM images were analyzed off-line using NanoScope software (Bruker, v1.5).   4.3.12 Addition of DNA for biofilm formation.  Genomic DNA of C. jejuni F38011 or S. Typhimurium SL1344 was individually extracted from the overnight bacterial culture using Presto™ Mini gDNA Bacteria Kit (FroggaBio) according to the manufacturer’s protocol. Genomic DNA was quantified using a NanoDrop 2000 spectrophotometer (Thermo Scientific). Addition of DNA for biofilm formation was conducted in two manners: 1) to form a pre-coating layer, 200 µl of DNA solution at different concentrations (20, 10, 5, 2.5 and 0 µg/ml) was individually added into each well of the 96-well plate and maintained for 4 h. The unbounded DNA was then washed out using sterile PBS before bacterial inoculation. 2) DNA was mixed with bacterial culture to a certain final concentration (20, 10, 5, 2.5 and 0 µg/ml) and 200 µl of this mixed culture was cultivated in 96-well plate. The plate was then cultivated in a microaerobic environment at 37°C for up to 72 h.  4.3.13 Autolysis assay.  Autolysis assay was adapted from a previous study with modifications (Kreth et al., 2009). Briefly, autolysis buffer was prepared by diluting Triton X-100 with 0.05 M Tris-HCl to achieve a final concentration of 0.02% (v/v). Bacterial cells were harvested in the late exponential phase by centrifugation at 8,000 ×g for 5 min at 4°C, washed twice with chilled water, and resuspended in autolysis buffer to 0.3 of OD600. The reduction of absorbance (OD600) was measured using the 108  microplate reader (SpectraMax M2, Molecular Devices, Sunnyvale, USA) every 3 min for a total of 90 min.   4.3.14 Motility test.  Motility of C. jejuni cells was assessed on the soft agar plates as described previously (Kalmokoff et al., 2006). Briefly, 5 µl of the overnight C. jejuni culture was spotted onto the Brucella media supplemented with 0.4% agar. The plate was then incubated under a microaerobic condition at 37°C for 2 days. The halo size of C. jejuni cells on the soft agar plate was measured. The results were compared to demonstrate the relative motility among different C. jejuni strains.   4.3.15 Quantification of cell lysis.  Genomic DNA is an indicator of bacterial lysis. The cell lysis was quantified via real-time quantitative PCR (qPCR) as described in a previous study (Ma and Wood, 2009). Briefly, C. jejuni F38011 wild-type strain and spoT, recA and flaAB deletion mutant strains were individually inoculated in the 96-well plate for biofilm formation as described above. After 3-day biofilm cultivation, the supernatant was collected. Biofilm was detached using 0.1% trypsin solution (Sigma), washed twice with PBS, and pelleted by centrifugation at 10,000 ×g for 2 min. The genomic DNA either in the supernatant or the biofilm cells were purified using PicoPure® DNA extraction kit (Applied Biosystems). The qPCR was performed on ABI Prism 7000 Fast instrument (Life Technologies) using a primer pair of a housekeeping gene rpoA (Ritz et al., 2009). The percentage of lysis was calculated by dividing the genomic DNA in the supernatant to the sum of genomic DNA in the supernatant and the encased cells in the biofilm.  109   4.3.16 Real-time qPCR analysis of gene expression.  The real-time qPCR was performed to plot the expression profile of flaA and flaB in response to the aerobic and starvation conditions in C. jejuni F38011 wild-type strain as well as spoT and recA deletion mutant strains. The total RNA was purified from C. jejuni F38011 wild-type strain and spoT and recA deletion mutant strains using RNeasy mini kit (Qiagen) according to the manufacturer's protocol. Complementary DNA (cDNA) was reverse transcript using RNA as the template by using SensiFASTTM cDNA Synthesis Kit (Bioline) according to the manufacturer’s protocol. The qPCR analysis was performed in triplicate using SensiFAST SYBR Lo-ROX Kit (FroggaBio) on ABI Prism 7000 Fast instrument (Life Technologies). The rpoA gene was used as the internal control. The arbitrary fold change cut-offs were set as more than 2.  4.3.17 Fluorescence microscopy for the analysis of the role of eDNA in biofilm structure.  Fluorescence microscopy was applied to investigate the spatial distribution of eDNA and bacterial cells in a developed dual-species Campylobacter–Salmonella biofilm. The eDNA was stained using 4’, 6-diamidino-2-phenylindole (DAPI, Invitrogen) according to the manufacturer's protocol. After 3-days cultivation, the DAPI working solution was prepared as 30 nM in PBS and injected into the microfluidic device with a well-developed dual-species Campylobacter-Salmonella biofilm at a rate of 0.0002 µl/min. The microfluidic device was incubated at room temperature for 15 min and then rinsed with flowing PBS at a rate of 0.002 µl/min for 10 min. Images were collected using an Axiovert 200 microscope (Carl Zeiss) equipped with an Axiocam camera (Carl Zeiss) at multi-channels: 405 nm (blue color for DAPI signal), 488 nm (green color for GFP signal), and 543 nm (red color for RFP signal). Analysis of three-110  dimensional reconstruction and spatial distribution was conducted using ImageJ software (The National Institutes of Health, USA) and ZEN software (Zeiss, blue edition), respectively.  4.3.18 Statistical analysis.  All the experiments were performed at least in three biological replicates. Results were reported as the averages of replicates ± the standard deviation with significance (P < 0.05) by one-way analysis of variance (ANOVA).  4.4 Results   4.4.1 Biofilm formation under different environmental conditions Biofilm formation of a wide range of C. jejuni strains under different environmental conditions (i.e., optimal, aerobic and starvation conditions) was comprehensively evaluated. Under the optimal condition, most of C. jejuni wild-type strains including 3 clinical isolates (C. jejuni human 10, C. jejuni 1658 and C. jejuni 87-95) and 4 reference strains (C. jejuni 81116, C. jejuni ATCC 33560, C. jejuni NCTC 11168 and C. jejuni F38011) were able to form relatively intensive biofilms (Figure 4-2A). Among these wild-type strains, C. jejuni F38011 formed the highest level of biofilm, approximately 2.5 times higher than the lowest level of biofilm formed by C. jejuni human 10. The biofilm formation of most C. jejuni wild-type strains (i.e., C. jejuni Human 10, 81-116, NCTC11168, 1658, and F38011) was significantly (P < 0.05) stimulated by aerobic condition compared to that under optimal condition. The stimulation effect on the biofilm formation ranged from 142% for C. jejuni human 10 to 20% for C. jejuni NCTC 11168. The stimulation effect on the biofilm formation by C. jejuni F38011 was 30%. In contrast, biofilm formation of C. jejuni ATCC 33560 and C. jejuni 87-95 under the aerobic condition was 111  at the same level as that under the optimal condition. Starvation condition significantly (P < 0.05) inhibited the biofilm formation for almost all C. jejuni wild-type strains except C. jejuni human 10. The inhibition effect on biofilm formation ranged from 79% for C. jejuni NCTC 11168 to 34% for C. jejuni 1658. The inhibition effect on the biofilm formation by C. jejuni F38011 was 56%. C. jejuni F38011 was used as the representative strain for the following study due to its intense biofilm formation and remarkable response to different environmental conditions.    112   Figure 4-2. Biofilm formation and release of extracellular DNA (eDNA) by wild-type C. jejuni strains (i.e., human 10, 81116, ATCC 33560, 87-95, NCTC 11168, 1658, and F38011) under optimal, aerobic and starvation conditions. (A) The level of biofilm formation was evaluated using crystal violet staining. The stained biofilm was released by 95% ethanol and determined by monitoring the value of OD595. The concentration of eDNA during biofilm formation under optimal condition (B), aerobic condition (C) and starvation condition (D) over 3 days was quantified using SYBR Green I dye on the basis of a standard curve generated using a series of 10-fold dilutions of Lambda DNA from 80 µg/ml to 0.156 µg/ml.   113  Stress response deficiency mutants (mutation on stringent response regulator spoT and mutation on DNA repair system recA) and motility deficiency mutant (mutation on flagellin protein flaAB) were generated using C. jejuni F38011 as the parental strain, and their corresponding biofilm formation was tested under different environmental conditions (Figure 4-3). Under the optimal condition, the biofilm formation of recA and flaAB deletion mutants was significantly (P < 0.05) lower than that of their parental counterpart by 52% and 55%, respectively, whereas the biofilm formation of spoT deletion mutant was significantly (P < 0.05) higher than that of its parental counterpart by 24%. These deletion mutants demonstrated a similar response to the environmental stress. Thus, the biofilm formation of the deletion mutants was stimulated under aerobic condition and impaired under starvation condition. Compared to the wild-type strain, the biofilm formation of spoT and recA deletion mutants under aerobic condition was significantly (P < 0.05) higher by 50% and 17%, respectively, whereas the biofilm formation of flaAB deletion mutant was significantly (P < 0.05) lower by 48%. Under the starvation condition, the biofilm formation of spoT and recA deletion mutants was significantly (P < 0.05) higher by 149% and 72%, respectively, whereas the biofilm formation of flaAB deletion mutant was lower by 12%. The biofilm formation of the complementary strains (i.e., spoT, recA, and flaAB) was also tested under an optimal condition in which their biofilm formation was restored to the same level as their wild-type counterpart (Figure 4-4). We believed that the complementation restored the capacity of biofilm formation of C. jejuni F38011 mutants. These complementary strains are supposed to have the same response as their wild-type counterpart to the environmental stress regarding biofilm formation. 114   Figure 4-3. Biofilm formation and release of extracellular DNA (eDNA) by wild-type C. jejuni F38011 and the corresponding spoT, recA and flaAB deletion mutants under optimal, aerobic and starvation conditions. (A) The level of biofilm formation was evaluated using crystal violet staining. The stained biofilm was released by 95% ethanol and determined by monitoring the value of OD595. The concentration of eDNA during biofilm formation under optimal condition (B), aerobic condition (C) and starvation condition (D) over 3 days was quantified using SYBR Green I dye on the basis of a standard curve generated using a series of 10-fold dilutions of Lambda DNA from 80 µg/ml to 0.156 µg/ml.  115   Figure 4-4. The biofilm formation of C. jejuni F38011 complementary strains including spoT, recA, and flaAB under optimal condition.   4.4.2 Determination of chemical compositions of C. jejuni biofilms in a microfluidic “lab-on-a-chip” device A microfluidic “lab-on-a-chip” device coupled with confocal micro-Raman spectroscopy was applied to characterize the chemical compositions of the biofilm over a long period of cultivation (up to 216 h) in a continuous and non-destructive manner. The Raman spectral 116  pattern of C. jejuni F38011 biofilm was different from that of the microfluidic substrate (glass and PDMS). The microfluidic substrate could generate intensive Raman scattering signal at 485, 610, 703, 785, 860, 1250, and 1402 cm-1 (Figure 4-5). After the initial attachment, C. jejuni F38011 biofilm progressively accumulated and covered the substrate. In the meanwhile, the intensity of Raman peaks derived from the substrate heavily decreased. Only peaks at 485, 610, 703 and 1402 cm-1 from the substrate could still be detected at low levels. In contrast, Raman peaks derived from the biofilm appeared at different wavenumbers and demonstrated a higher intensity than that from the substrate.   Figure 4-5. The Raman peaks of the microfluidic substrate had no overlap with the peaks of C. jejuni F38011 biofilm. Raman peaks of the microfluidic substrate were labeled as a highlight.  117  The characteristic Raman spectrum of C. jejuni F38011 biofilm showed prominent peaks at 746, 918, 968, 1123, 1168, 1310, and 1580 cm-1 after 72-h cultivation in the microfluidic chip (Figure 4-6A). Peaks at 746 and 1580 cm-1 were assigned to thymine ring and pyrimidine ring structures of nucleic acids, while peaks at 918, 968, 1123, 1168 and 1310 cm-1 were derived from proline ring, lipid representative band, C-N stretching vibration, C=C vibration, CH3/CH2 twisting or bending mode of lipids, respectively (Table 4-3). From 72 h to 168 h, the intensity of the prominent Raman peaks (i.e. 746, 918, 968, 1123, 1168, 1310, 1580 cm-1) significantly (P < 0.05) declined by ~30% at 120 h and then rebounded back at 168 h. Up to 216 h, the intensity of these peaks reached to the highest levels, which were significantly (P < 0.05) higher than that at 72 h by 15% (Figure 4-6B). Based on Raman band assignment, nucleic acids, lipids, proteins, and polysaccharides were the major compositions of the mono-species C. jejuni biofilm. The amount of these components could increase or decrease due to the dynamic development of the biofilm (i.e., dispersion and regrowth), which was reflected by the change of the intensity of Raman peaks from biofilms. The intensity of Raman peaks assigned to nucleic acids was significantly (P < 0.05) higher intensity than those derived from proteins, polysaccharides, and lipids, indicating that nucleic acids were the major components in a developed mono-species C. jejuni biofilm (Figure 4-6B).  118   Figure 4-6. Confocal micro-Raman spectroscopy monitors the development of C. jejuni biofilm in the microfluidic “lab-on-a-chip” platform. C. jejuni biofilm was cultivated in a microfluidic device, and the chemical composition was determined at 72 h, 120 h, 168 h and 216 h using confocal micro-Raman spectroscopy coupled with a 532-nm laser. (A) Prominent Raman peaks during biofilm formation. (B) Variations in the intensity of the corresponding Raman peaks (746, 918, 968, 1123, 1168, 1370, 1580 and 1643 cm-1) over time. The Raman peaks derived from nucleic acids components (746 and 1580 cm-1) are shown in black color, and the Raman peaks derived from other components (i.e., proteins, lipids, and polysaccharides) are shown in gray color.   119  Table 4-3. Raman band assignments for C. jejuni biofilm formed in the microfluidic platform (Naumann, 2001; Movasaghi et al., 2007; Talari et al., 2015). Raman shift (cm-1) Band assignment 746 T ring breathing mode of DNA/RNA base 918 the amino acid, proline ring 968 lipid representative band 1125 skeletal of acyl backbone in lipid and C-N stretching in protein vibration 1168 lipids υ(C=C) υ(COH) 1310 CH3/CH2 twisting or bending mode of lipid/collagen 1370 saccharide representative band 1453 umbrella mode of methoxyl in protein 1580 pyrimidine ring in nucleic acids  4.4.3 Accumulation of eDNA comes along with biofilm development  Since eDNA was identified as the major component of mono-species C. jejuni biofilm by confocal micro-Raman spectroscopy, we hypothesized that the release of eDNA was closely associated with the development of C. jejuni biofilm. Accumulation of eDNA during biofilm formation was quantified using specific fluorescent double-stranded DNA stain SYBR Green I. The released eDNA could be detected from all C. jejuni strains including wild-type and mutant strains since the first day of biofilm formation (Figure 4-2B, C and D; Figure 4-3B, C and D). However, the concentration and accumulation pattern of eDNA varied among different strains and were influenced by the environmental condition as well. 120  Under the optimal condition, C. jejuni 81116 and ATCC 33560 produced the highest amount of eDNA among all wild-type strains and their eDNA concentrations reached to 13.3 and 23.7 µg/ml in a 3-day developed biofilm, respectively (Figure 4-2B). In addition, spoT deletion mutant produced the highest eDNA among all the mutant strains and its eDNA concentration reached to 13.7 µg/ml in a 3-day developed biofilm (Figure 4-3B). From day 1 to day 3, eDNA accumulated in the biofilm of wild-type C. jejuni 81116 and ATCC 33560 from ~4 µg/ml to ~23 µg/ml, while the eDNA concentration in the biofilm of C. jejuni human 10, 87-95, NCTC 11168, 1658 and F38011 remained relatively constant and was below 10 µg/ml (Figure 4-2B). For C. jejuni mutant strains, spoT and recA deletion mutants released a similar amount of eDNA to their wild-type counterpart during biofilm formation at day 1 and day 2, but the released DNA was significantly increased at day 3. Specifically, the concentration of eDNA reached to 13.7 µg/ml for spoT mutant and 8.89 µg/ml for recA mutant at day 3. In comparison, flaAB mutant shared a similar eDNA release pattern to its wild-type parental counterpart during the biofilm formation, and its eDNA concentration was below 6.5 µg/ml (Figure 4-3B). The release of eDNA was stimulated in a well-developed (3-day) biofilm under aerobic condition (Figure 4-2C and Figure 4-3C). For C. jejuni wild-type strains, the release of eDNA in C. jejuni human 10, ATCC 33560, F38011 and 1658 was significantly higher (P < 0.05) than that under the optimal condition and their concentrations reached to 18.1, 28.7, 18.1 and 14.1 µg/ml, respectively. In contrast, the eDNA concentration of C. jejuni 87-95 was not influenced by aerobic condition and remained constant at the same low level as that under the optimal condition (~3.5 µg/ml) during biofilm formation. A distinct release pattern of eDNA was observed for C. jejuni NCTC 11168 as its eDNA concentration progressively decreased from 13.4 µg/ml in a 1-day developed biofilm to 5.5 µg/ml in a 3-day developed a biofilm. For mutant 121  strains, both spoT and recA deletion mutants produced more significantly (P < 0.05) higher amount of eDNA under aerobic condition than that under the optimal condition and their concentrations reached to 29.6 and 20.5 µg/ml, respectively, in a 3-day developed a biofilm. In contrast, C. jejuni F38011 flaAB deletion mutant produced less eDNA under aerobic condition than that under optimal condition. Starvation condition significantly (P < 0.01) inhibited the release of eDNA for all C. jejuni strains, including wild-type and deletion mutants, that the eDNA concentration was less than 8 µg/ml (Figure 4-2D and Figure 4-3D).  Taken all together, a synchronous relationship between eDNA accumulation and biofilm formation was observed. The massive accumulation of eDNA usually came along with a high level of C. jejuni biofilm formation under different environmental conditions. In addition, a threshold of eDNA concentration ranging from 10 to 20 µg/ml was identified to associated with the high level of biofilm formation.   4.4.4 Source of eDNA during biofilm formation  Bacterial lysis can release DNA into the environment. Therefore, we speculated that bacterial lysis is responsible for the accumulation of DNA during biofilm formation. The autolysis capacity of C. jejuni was tested using 0.02% Triton X-100 autolysis solution, and the reduction rate of OD600 was recorded over time (Figure 4-7). The autolysis capacity of Salmonella was used as the reference. S. Typhimurium SL1344 could persist in Triton X-100 solution over 90 min, and only 10% of the total population was lysed. In comparison, C. jejuni was extremely vulnerable to Triton X-100 induced autolysis pressure that over 55% of C. jejuni cells were lysed within 70 min. In addition, the autolysis capacity of C. jejuni F38011 mutants (i.e., spoT, recA, and flaAB) was at the similar level to that of the wild-type counterpart.  122   Figure 4-7. Autolysis level of C. jejuni induced by Triton X-100 was significantly higher than that of S. Typhimurium SL1344 and autolysis level had no significant difference among C. jejuni F38011 wild-type, spoT, recA and flaAB deletion mutants. Triton X-100 was dissolved in 0.05 M Tris-HCl to achieve a final concentration of 0.02% (v/v) as the autolysis buffer. Bacterial cells were harvested in the late exponential phase and resuspended in autolysis buffer to 0.3 of OD600. The reduction of OD600 value was measured every 3 min for a total of 90 min using a microplate reader.  123  The release of genomic DNA is an important indicator of bacterial lysis. Using DNA gel electrophoresis assay, the DNA collected from C. jejuni F38011 biofilm showed the same length as the genomic DNA extracted from C. jejuni F38011 (Figure 4-8). We further evaluated the relative lysis level of C. jejuni cells under various conditions using qPCR (Figure 4-9). Under the optimal condition, C. jejuni F38011 wild-type strains, recA, and flaAB deletion mutants shared the similar lysis level that ~20% to 25% of the total population was lysed in a 3-day developed a biofilm. Further, spoT deletion mutant showed a high lysis level which 35.8% of the population was lysed in a 3-day developed biofilm. Compared to the optimal condition, aerobic condition significantly (P < 0.05) stimulated bacterial lysis that the lysis level ranged from 32.7% to 54.2%. Among these strains, the lysis level of recA deletion mutant was promoted most from 23.6% (optimal condition) to 54.2% (aerobic condition). Under the starvation condition, bacterial lysis was significantly (P < 0.05) inhibited. Although spoT deletion mutant maintained a relatively high lysis level that accounted for 26.5% of the total population, the lysis level was still lower than that under the optimal condition, which was 35.7%. Other C. jejuni F38011 strains (i.e., wild-type, recA, and flaAB) shared a similarly low level of lysis, which accounted for ~15% of the total population.   124   Figure 4-8. The length of DNA fragment present in C. jejuni during biofilm formation was similar to that of genomic DNA extracted from C. jejuni F38011 planktonic cells. Gel electrophoresis was performed to demonstrate the length of the released DNA fragment. After 3-day biofilm cultivation, each bacterial culture in the 96-well plate was collected. A total of 10 µl of the supernatant was mixed with 2 µl of DNA loading dye solution and then loaded on 1% agarose gel for electrophoresis. A 1-kb ladder was used as the reference. The DNA was stained using SYBRTM safe DNA gel stain and visualized on ChemiDocTM XRS gel documentation system.   125   Figure 4-9. Lysis level of C. jejuni cells was stimulated by aerobic condition and inhibited by starvation condition during biofilm formation. Genomic DNA is an indicator of bacterial lysis. After 3-day biofilm cultivation, the genomic DNA in the supernatant and biofilm of C. jejuni wild-type strain, spoT, recA and flaAB deletion mutant strains were purified. The relative content of genomic DNA in the supernatant and biofilm was individually determined via real-time quantitative PCR (qPCR) using housekeeping gene rpoA. The lysis level was calculated by dividing the genomic DNA content in the supernatant to the sum of genomic DNA content in the supernatant and the biofilm.  126  Interestingly, flaAB deletion mutant had a similar level of lysis to that of its parental counterpart but released less DNA. We, therefore, speculated that the expression of flaA and flaB gene might influence the release of eDNA. Accordingly, the expression profiles of flaA and flaB were determined using qPCR, and arbitrary fold change cut-offs were set as more than 2 (Figure 4-10). Under aerobic condition, both flaA and flaB genes were significantly (>2 fold and P < 0.05) upregulated among C. jejuni F38011 wild-type (2.8 fold for flaA and 2.2 fold for flaB), spoT (3.2 fold for flaA and 4.1 fold for flaB) and recA (5.3 fold for flaA and 3.0 fold for flaB) deletion mutant strains, but the upregulation could only be detected at the first day of biofilm formation. The up-regulation of flaA gene reached to 2.8 fold in the wild-type strain, 3.2 fold in spoT deletion mutant and 5.3 fold in recA deletion mutant while the up-regulation of flaB gene reached to 2.2 fold in the wild-type strain, 4.1 fold in spoT deletion mutant and 3.0 fold in recA deletion mutant. The expression profile of both flaA and flaB genes were at the same levels among wild-type, spoT and recA deletion mutant strains under starvation condition compared to that under optimal condition, indicating that the flaA and flaB genes might play a role under oxidative stress rather than starvation stress.    127   Figure 4-10. The expression of flaA and flaB genes in C. jejuni F38011 wild-type, spoT and recA deletion mutants was upregulated only at the first day of biofilm formation under aerobic condition. Real-time qPCR was performed to plot the expression profile of flaA and flaB in response to the aerobic condition (A) and starvation condition (B) in C. jejuni F38011 wild-type strain as well as spoT and recA deletion mutant strains. The rpoA gene was used as the internal control. The arbitrary fold change cut-offs were set as more than 2.  4.4.5 Addition of DNA stimulates biofilm formation  We identified a clear correlation between eDNA concentration and biofilm formation (Figure 4-2 and Figure 4-3), but the consequence of DNA release and biofilm formation was not fully clear yet. DNA addition assay was conducted to investigate whether eDNA was the inducing factor or a by-product of biofilm formation. In the natural environment, bacterial cells usually inhabit in a multi-species bacterial community. Therefore, DNA released by other bacterial species may also contribute to biofilm formation. In the current study, genomic DNA of C. jejuni F38011 and S. Typhimurium SL 1344 was supplemented either by direct addition into the bacterial culture or by forming a pre-coating layer for the subsequent biofilm formation in the 128  96-well plate. Direct addition of DNA demonstrated a concentration-dependent stimulation effect on C. jejuni biofilm formation and this effect could be triggered not only by C. jejuni DNA but also Salmonella DNA (Figure 4-11C and D). For C. jejuni F38011 wild-type strain, the stimulation effect on biofilm formation was triggered when the concentration of the added DNA reached to 10 µg/ml. For spoT deletion mutant, the stimulation effect was observed when the concentration of the added DNA reached to 20 µg/ml. For recA deletion mutant, the stimulation effect started from 5 µg/ml and the addition of 10 µg/ml DNA could increase the biofilm formation to the level as that of the wild-type strain. For flaAB mutant, the stimulation effect started from the concentration of 2.5 µg/ml and the addition of 10 µg/ml DNA restored biofilm formation to the level as that of the wild-type strain. When the concentration of the added DNA reached to 20 µg/ml, biofilm formation of C. jejuni F38011 wild-type and mutant strains was promoted to a similarly high level, indicating that 20 µg/ml was close to the saturation concentration of DNA that could maximize the biofilm formation in the environment. In contrast, forming a pre-coated layer did not enhance biofilm formation regardless of the DNA concentration to generate this pre-coated layer (Figure 4-11A and B). The biofilm formation level of C. jejuni F38011 wild-type, spoT, recA and flaAB deletion mutants on a pre-coated DNA layer was the same as that formed on the untreated substrate. Thus, eDNA was the leading factor for biofilm accumulation and eDNA derived from Salmonella could also stimulate the formation of mono-species C. jejuni biofilm. Although the initial attachment was the prerequisite for biofilm formation, the pre-coated layer of DNA had little influence on the subsequent biofilm development.  129   Figure 4-11. Addition of genomic DNA extracted either from Campylobacter or Salmonella had a concentration-dependent stimulation effect on biofilm formation of C. jejuni F38011; the pre-coating layer formed by DNA extracted either from Campylobacter or Salmonella did not contribute to the development of biofilm formation of C. jejuni F38011. Genomic DNA of C. jejuni F38011 or S. Typhimurium SL1344 was separately extracted and added for biofilm formation. To form a pre-coating layer, 200 µl of DNA Salmonella (A) or C. jejuni (B) at different concentrations was added to each well of the 96-well plate and maintained for 4 h. The unbounded DNA was washed out before the addition of C. jejuni F38011 culture. To directly add DNA for biofilm formation, DNA of Salmonella (C) or C. jejuni (D) was mixed with C. jejuni 130  F38011 culture to a certain final concentration, and 200 µl of this mixed culture was added into the 96-well plate. The plate was then cultivated in a microaerobic environment at 37°C for up to 72 h.  4.4.6 DNase I treatment prevents biofilm formation and disrupts biofilm structure DNase I treatment was performed to elucidate the role of eDNA in biofilm formation. The treatment was conducted at two distinct stages, namely initial attachment stage and maturation stage (Figure 4-12). Treatment at the initial attachment stage significantly (P < 0.05) prevented biofilm formation. Compared to the untreated group, DNase I treatment reduced the biofilm formation level of C. jejuni F38011 wild-type (65%), spoT deletion mutant (74%), recA deletion mutant (61%) and flaAB deletion mutant (66%). In comparison, DNase I treatment at the maturation stage significantly (P < 0.05) disrupted the well-developed biofilm. The treatment reduced the biofilm biomass of C. jejuni F38011 wild-type (77%), spoT deletion mutant (64%), recA deletion mutant (43%), and flaAB deletion mutant (63%).  131   Figure 4-12. DNase I treatment before bacterial initial attachment prevented C. jejuni biofilm formation and DNase I treatment on the well-developed C. jejuni biofilm disrupted biofilm structure, leading to the reduction of biomass. To treat biofilm at the initial attachment stage, DNase I was mixed with C. jejuni culture to a final concentration of 2 units/ml and then added to the 96-well plate for biofilm formation. To treat the well-developed biofilm in the 96-well plate, 200 µl of DNase I solution (2 units/ml) was added into a well with a 3-day cultivated C. jejuni biofilm. The treatment was maintained for 15 min at room temperature. The reduction level of biofilm was evaluated using the aforementioned crystal violet staining assay. Asterisk denotes significant difference (P < 0.05). 132   Atomic force microscopy was applied to further investigate the effect of DNase I treatment on C. jejuni F38011 biofilm. The topographic images of the treated and untreated biofilms were collected in contact scanning mode. Trace and retrace images were well matched (data not shown), indicating that AFM tips in the contact mode did not scratch biofilm surfaces and the morphological properties derived from AFM characterization were highly reliable. The topographic image of C. jejuni F38011 biofilm demonstrated a compact structure and smooth surface. On the top surface of the biofilm, protruding patterns were observed in cell shape with a size of 1.5 × 0.2 µm2. These cell-shaped patterns were squeezed and highly organized (Figure 4-13A and B). DNase I treatment resulted in a morphological variation where the top surface of the biofilm was altered from smooth to rough and from compact to loose. The cell-shaped pattern could still be observed but was concave after the treatment (Figure 4-13C and D). 133   Figure 4-13. Topographic images of C. jejuni F38011 biofilms confirmed that the DNase I treatment disrupted biofilm structure and dispersed encased C. jejuni F38011 cells. The images were obtained by atomic force microscopy in contact mode within 8 µm × 8 µm area at scan frequency of 0.5 Hz: (A) C. jejuni biofilm without DNase I treatment; (B) 3D reconstruction of the untreated C. jejuni biofilm; (C) C. jejuni biofilm after DNase I treatment ; D) 3D reconstruction of the treated C. jejuni biofilm.  The volume and coverage area of the biofilms were also determined on the basis of the 3D reconstruction of biofilm topographic images. According to Figure 4-14, DNase I treatment 134  significantly disrupted biofilm and resulted in the detachment that the volume of the biofilm was reduced from 53.93 μm3 to 28 μm3 and the coverage area of the biofilm was reduced from 20.19 μm2 to 2.68 μm2. Taken all together, these findings demonstrated the role of eDNA in biofilm formation, which not only facilitated the initial attachment but also maintained the integrity of biofilm structure.   Figure 4-14. DNase I treatment reduced the coverage and volume of C. jejuni biofilm. The well-developed (3-day) C. jejuni F38011 biofilm on a nitrocellulose membrane was treated with DNase I solution (2 units/ml) for 15 min and then air-dried for the analysis of atomic force microscopy. (A) Coverage reduction caused by DNase I treatment; (B) Volume reduction caused by DNase I treatment. Asterisk denotes significant difference (P < 0.05).  4.4.7 DNA allocates C. jejuni and Salmonella cells in a dual-species biofilm Multi-species biofilm is the dominant type in the natural environment (Elias and Banin, 2012). In the current study, Campylobacter-Salmonella biofilm was used as a representative model to investigate the role of eDNA in a dual-species biofilm. A green fluorescent protein 135  (GFP)-tagged C. jejuni F38011 strain was mixed with a red fluorescent protein (RFP)-tagged S. Typhimurium SL 1344 strain and then injected into the microfluidic “lab-on-a-chip” platform. After 3-days cultivation, the biofilm was stained using DAPI, followed by imaging (Figure 4-148). Campylobacter could co-exist with Salmonella and form a dual-species biofilm. Within this dual-species biofilm, C. jejuni cells were mainly located at the bottom layer while S. Typhimurium cells were mainly located at the top layer. Shown in blue color, a large amount of eDNA was identified in this dual-species biofilm. The eDNA mainly assembled and formed several eDNA-rich areas, although discretely distributed eDNA could still be observed as well.  136   Figure 4-15. Spatial distribution of C. jejuni cells, Salmonella cells and extracellular DNA (eDNA) within a Campylobacter-Salmonella dual-species biofilm formed in the microfluidic platform. Fluorescence microscopy was applied to determine the spatial distribution of eDNA and bacterial cells in a dual-species Campylobacter–Salmonella biofilm. After 3-days cultivation, 30 nM of DAPI solution was injected into the microfluidic device to stain eDNA in the biofilm. Images were collected at multi-channels: 405 nm (blue color for DAPI signal), 488 nm (green color for GFP signal), and 543 nm (red color for RFP signal). Within this Campylobacter-Salmonella dual-species biofilm, C. jejuni cells were mainly located at the bottom while Salmonella cells were mainly located at the top layer. The eDNA mainly assembled and formed 137  several eDNA-rich areas and maintained the spatial distance between C. jejuni and Salmonella in the biofilm.  The view from spatial perspective identified that eDNA-rich area formed a stalk-like structure and occupied a large space. C. jejuni cells were usually associated with the eDNA-rich area and covered by the stalk-like structure. In contrast, Salmonella cells were not directly interacted with eDNA, but distributed around the eDNA-rich structure. Therefore, we speculated that eDNA was responsible for allocating different species of bacteria by maintaining a spatial distance between each other.   4.5 Discussion C. jejuni is a fastidious microaerobic bacterium and extremely vulnerable to the environmental stress. However, this microbe is highly prevalent in the environment and difficult to remove from the food chain. Campylobacteriosis is still the most frequently reported foodborne illness in Canada, outnumbering the reported cases of Salmonella, Listeria monocytogenes, and Shiga toxigenic E. coli infections combined together (Canada, 2017). C. jejuni can antagonize stresses by activating internal stress response system. Previous studies demonstrated that stringent response conducted global regulation on bacterial metabolism in reaction to the stresses, especially nutrient starvation. The spoT gene in C. jejuni 81-176 was reported to be essential for the stringent response. Deletion of this gene significantly inhibited the expression of the genes related to redox balance, metabolism, energy production and conversion pathway (Gaynor et al., 2005). Oxidative stress is a lethal challenge for microaerophilic bacteria because it can induce DNA damage and exert subsequently negative 138  influences on the microbes (Storz and Imlayt, 1999; Cabiscol Català et al., 2000). A 38-kDa protein encoded by the recA gene was identified to mediate both DNA repair and homologous recombination, aiding C. jejuni to maintain physiological activities when it encountered the oxidative stress-induced DNA damage. Disruption of the recA gene significantly impaired the viability of C. jejuni in the DNA damage-induced environment (Gaasbeek et al., 2009). However, bacterial cells (e.g., C. jejuni) can only withstand a limited level of stress. As a self-produced bacterial community, biofilm has unique physiological properties, such as tolerance to dehydration, persistence under the harsh environmental condition and resistance to antibiotic treatment, all of which provide remarkable protection to the encased bacteria cells . Apart from the inner stress response system, C. jejuni could also survive by forming a biofilm or residing in a mature biofilm against the unfavorable condition. In our previous study, C. jejuni could survive a longer period under oxidative stress by forming a biofilm than that as planktonic cells. After 3-day exposure to a high content of oxygen, no viable C. jejuni cell could be detected from its planktonic culture, but ~5 log CFU/cm2 of C. jejuni cells were still culturable in the biofilm (Feng et al., 2016). Although biofilm formation of C. jejuni has been defined under different conditions, the correlation between stress response system and biofilm formation of C. jejuni has only partially been investigated (Reeser et al., 2007; Reuter et al., 2010). In the current study, we further investigated the influence of stress response of C. jejuni on the biofilm formation.  Most of the C. jejuni wild-type strains shared similar biofilm-forming capability in response to stress. In short, these strains produced more biofilm under aerobic condition and less biofilm under starvation condition (Figure 4-2A). This observation was in agreement with a previous study that the biofilm formation of C. jejuni increased under the oxygen-enriched condition (Reuter et al., 2010). In addition, another study also reported that the biofilm formation 139  of C. jejuni under nutrient-limited condition (e.g., Brucella or Bolton medium) was significantly inhibited due to the slow growth of C. jejuni cells (Reeser et al., 2007).  Biofilm formation of C. jejuni F38011 spoT deletion mutant was increased by 26% compared to that of its parental counterpart under the optimal condition (Figure 4-3A), which was consistent to a previous study that the mutation of the spoT gene showed an increased biofilm formation of C. jejuni 81-176 (McLennan et al., 2008). In contrast, biofilm formation of the recA deletion mutant and flaAB deletion mutant was reduced by ~52% and 55%, respectively, compared to their parental counterparts under the optimal condition. Our study demonstrated that the deletion of recA inhibited C. jejuni biofilm formation. The flagellum is known to be responsible for bacterial attachment onto the surface of a substrate. The loss of flagellar apparatus significantly impairs biofilm formation (Pratt and Kolter, 1998; Joshua et al., 2006; Kalmokoff et al., 2006; Reeser et al., 2007). Consistent with these studies, the deletion of both flaA and flaB genes in C. jejuni F38011 resulted in a significant loss of motility as well as a reduced biofilm formation (Figure 4-3A and Figure 4-16).  140   Figure 4-16. The mutations of flaA and flaB significantly decreased the motility of C. jejuni F38011 while the mutations on spoT or recA did not influence the motility of C. jejuni F38011. A total of 5 µl of the overnight bacterial culture was spotted onto the Brucella media supplemented with 0.4% agar. After 2-day cultivation in microaerobic condition at 37ºC, the halo area was measured. Asterisk denotes significant difference (P < 0.05).  Compared to C. jejuni F38011 flagella deletion mutant (i.e., flaAB) strain, C. jejuni F38011 stress response deletion mutants (i.e., spoT and recA) demonstrated a distinctive response to the environmental stress in terms of biofilm formation. Compared to the wild-type strain, the biofilm 141  formation of spoT and recA deletion mutants under starvation condition significantly increased by 149% and 72%, respectively, whereas the change in biofilm formation of flaAB deletion mutant was not significant. Therefore, we believe that stress response is one of the critical factors to affect biofilm formation of C. jejuni more than flagellum does under specific stress condition. Stress response systems mainly regulate the physiological metabolism inside bacterial cells, whereas biofilm formation occurred outside of bacterial cells. There is likely a factor that can mediate this inside-outside transition. DNA is present in abundance in the environment as a consequence of the lysed dead organisms or via active secretion from the living organisms (Nielsen et al., 2007). Bacteria can use these free DNA as an important supply of nutrients or integrate these free DNA into the genome for acquiring resistant capacity (Lorenz and Wackernagel, 1994; Thomas and Nielsen, 2005). Previous studies identified that bacteria progressively released DNA during biofilm formation. For example, DNA content in a 3-day developed P. aeruginosa biofilm reached to 20-25 µg/ml and the concentration of DNA could be up to 220 µg/mg (eDNA/cellular DNA) when the biofilm cultivation extended to 5 days (Steinberger and Holden, 2005; Das and Manefield, 2012).  Our current study also identified the presence of eDNA during the biofilm formation of C. jejuni. By Raman spectroscopic analysis, the content of eDNA in the biofilm was determined to be significantly higher than other major biofilm components, such as proteins, lipids, and polysaccharides. In addition, the content of eDNA increased or decreased along with the growth or dispersion of the biofilm, respectively (Figure 4-6A and B), demonstrating that eDNA was an important constitutions of C. jejuni biofilm.  Bacterial lysis is regarded as the important source of the release of eDNA (Allesen‐Holm et al., 2006; Rice et al., 2007). As shown in Figure 4-7 and 4-8), C. jejuni F38011 was 142  vulnerable to the induced lysis pressure and the length of the released eDNA fragment was equal to the length of genomic DNA extracted from C. jejuni F38011. Taken all together, there was a high possibility that bacterial lysis was the source of the released DNA during the biofilm formation of C. jejuni. However, autolysis assay could not fully explain the release of genomic DNA during the biofilm formation of C. jejuni F38011 wild-type strain and deletion mutants in response to different stresses. Because Triton X-100 induced a much stronger lysis pressure than that of the environmental stress, autolysis assay only reflected the tendency of bacterial lysis but not the precise proportion of the lysed C. jejuni cells during biofilm formation. Accordingly, qPCR was performed to evaluate the lysis level of C. jejuni F38011 biofilms under different environmental conditions (Figure 4-9). Specifically, aerobic condition significantly (P < 0.05) increased the lysis rate by over 32% and starvation condition significantly (P < 0.05) decreased the lysis rate by over 25%. The recA deletion mutant was vulnerable to the aerobic condition, with 54% of the total population lysed in a 3-day biofilm. The aerobic condition can generate oxidative pressure and induce DNA damage (Storz and Imlayt, 1999). The high lysis rate of recA deletion mutant is highly likely due to the lack of function at DNA repair system. The quantitative analysis of eDNA released during the biofilm formation revealed a synchronous response to the environmental stresses (Figure 4-2 and Figure 4-3). For example, the release of eDNA and biofilm formation increased simultaneously under aerobic condition. However, C. jejuni ATCC 33560 was an exception. Although over 10 µg/ml of eDNA can be detected from the biofilm of C. jejuni ATCC 33560 under aerobic conditions, its biofilm formation levels were significantly less (P < 0.05) than that of other C. jejuni strains, such as C. jejuni F38011 and NCTC 11168, whose eDNA production was ~10 µg/ml. According to a previous study, C. jejuni ATCC 33560 contains a single-nucleotide deletion that might lead to the non-function of CmeR 143  (Hyytiäinen and Hänninen, 2012). CmeR is well characterized as a transcriptional repressor of efflux pump of CmeABC (Lin et al., 2005) and also involved in various metabolic regulations, such as the control of membrane transporters and biosynthesis of periplasmic proteins and capsule (Guo et al., 2008). Therefore, C. jejuni ATCC 33560 is more vulnerable and easily lysed under stress conditions, increasing released eDNA. However, the heavy loss of viable cells reduces the initial attachment and subsequently impairs the biofilm formation which might be responsible for the low biofilm formation of C. jejuni ATCC 33560 under different stress conditions.  Mutations in the stress response system (spoT and recA) enhanced the impact of stresses on eDNA secretion and biofilm formation, which was in agreement with the result of cell lysis (Figure 4-9). Although the deletion mutation of flagellar apparatus (flaA and flaB) did not directly affect the stress response capacity of C. jejuni, both motility and chemotaxis were significantly impaired (Lertsethtakarn et al., 2011). Hence, the lysis level of flaAB deletion mutant was also increased due to the accumulation of redox pressure induced by the aerobic condition. We believe that bacterial lysis was the consequence of stress response, which eventually releases the DNA into the environment. The accumulation of eDNA then facilitated the development of biofilm as the constitutions. To our surprise, not only the DNA from Campylobacter but also Salmonella could mediate this regulation on biofilm formation. Thus, eDNA was essential to the initial attachment because DNase I treatment at the initial attachment stage almost eliminated biofilm formation. In addition, DNase I treatment on the well-developed biofilm disrupted over 70% of the biomass, confirming that eDNA was the major constitutions in a developed C. jejuni biofilm (Figure 4-12). AFM analysis revealed that the degradation of eDNA in the biofilm disrupted biofilm structure and resulted in a reduction of ~87% biofilm 144  coverage and ~48% biofilm volume (Figure 4-13 and 4-14). Taken together, eDNA was involved in biofilm formation by performing multi-functions. At the initial stage, eDNA facilitated bacterial initial attachment and established the basis for biofilm formation. At the developing stage, eDNA was included into the biofilm as the major constitutions to build the biofilm structure. In a developed biofilm, eDNA was responsible for maintaining the biofilm structure.   Although the flaAB deletion mutant shared a similar lysis rate to that of the wild-type strain under the environmental stresses, its DNA release and the levels of biofilm formation were significantly (P < 0.05) lower (Figure 4-3). Previous studies reported that both eDNA and flagella were responsible for bacterial attachment and biofilm formation. DNA could facilitate the attachment via an acid-base interaction and flagella-mediated auto-agglutination and immobilize bacteria cell onto a surface (Ritchie et al., 1983; Lillard, 1986; Das et al., 2010; Brown et al., 2015a). The deletion mutation in flagella synthesis gene flaA and flaB in C. jejuni resulted in a biofilm-repressed phenotype (Reeser et al., 2007; Reuter et al., 2010). We believed that the low biofilm formation of the flaAB mutant was due to both the deficiency of eDNA and the lack of flagella, but this could not explain why flaAB deletion mutant released a low amount of eDNA. Interestingly, it was reported that the expression of flagellin A (flaA) and flagellin B (flaB) was activated since biofilm formation and their expression level was significantly higher in the biofilms compared to that in the planktonic cells (Kalmokoff et al., 2006). Hence, we hypothesized that there might be a correlation between the synthesis of flagellin and eDNA release. However, the outcome of qPCR assay did not completely support this hypothesis. Aerobic condition up-regulated the expression levels of flaA and flaB genes in C. jejuni F38011 wild-type, spoT and recA deletion mutant strains, but up-regulation was only shown at the first 145  day of biofilm formation. In contrast, the expression profiles of flaA and flaB under starvation condition was maintained at the similar levels as that under optimal condition during biofilm formation. Taken together, although the up-regulation of the flaA and flaB genes occurred along with the increase of eDNA release under aerobic stress, the down-regulation of flaA and flaB genes was not observed under the starvation condition where eDNA release was inhibited. Therefore, the correlation between flagellar and DNA release might be more specific to aerobic stress. In the natural environment, Campylobacter is frequently isolated from the environment where Salmonella also appears, such as poultry farm and sewage water (Craven et al., 2000; Slader et al., 2002). Our previous study demonstrated that C. jejuni survived a longer period in a Salmonella-C. jejuni dual-species biofilm than that in a mono-species C. jejuni biofilm under aerobic condition (Feng et al., 2016). In the current study, we identified that the distinct spatial distribution of bacteria cells might be responsible for this survival advantage in a dual-species biofilm and eDNA played a role in maintaining spatial distribution by allocating different species of bacteria cells at different locations (Figure 4-16). In a well-developed dual-species biofilm, released DNA was identified to assemble and form stalk-like structure. At the bottom layer of the biofilm, eDNA tended to interact with C. jejuni cells and form a cover structure on top of C. jejuni cells. In contrast, the stalk-like eDNA structure tended to repel Salmonella cells and suspend Salmonella cells at the top layer of the biofilm. Therefore, C. jejuni was allocated at the bottom layer of biofilm away from the aerobic condition, and the top space was occupied by eDNA and Salmonella cells that further limit the penetration of oxygen. In the natural environment, the penetration of oxygen would be limited by this unique structure, which facilitates the survival of C. jejuni cell under aerobic condition.  146   4.6 Conclusion In this study, a comprehensive investigation of C. jejuni biofilm formation in response to the environmental stresses was conducted. Oxidative stress and starvation stress could significantly influence the biofilm formation of a broad range of C. jejuni isolates, and the synchronous relationship was observed between biofilm formation and eDNA released from bacterial lysis. We propose that environmental stresses may induce a high rate of bacterial lysis and the subsequently released DNA from the dead bacterial cells to promote biofilm formation. This study for the first time reveals the essential role and multi-functions of eDNA in the biofilm formation of C. jejuni and provides insights into understanding their molecular mechanisms. The knowledge can aid in developing the intervention strategies to limit the prevalence and distribution of C. jejuni in the environment.   147  Chapter 5: Characterization and transcriptome analysis of Campylobacter jejuni persister cells   5.1 Summary Persister cells account for a small fraction of bacterial populations that demonstrate antibiotic tolerance without developing a resistance mechanism. The presence of persister cells is proposed to be responsible for hard-to-treat infections. As a leading foodborne pathogen, Campylobacter jejuni is one of the major causes of human gastroenteritis worldwide. However, the information of Campylobacter persister cells is rarely reported. In this study, we validated the presence of C. jejuni persister cells and these persister cells demonstrated a multi-drug tolerance. The proportion of persister cells in the whole population varied due to different strains.  Among different C. jejuni isolates tested in this study, a clinical isolate C. jejuni F38011 produced the highest level of persister cells, accounting for ~0.1% of the whole population. The transcriptome analysis by next-generation sequencing (RNA-seq) identified that the genes associated with ATP utilization and amino acid synthesis were considerably down-regulated in the persister cells of C. jejuni F38011. The shutdown of these genes indicated the low metabolic activity and the stop of growth which might well explain the tolerance of C. jejuni persister cells. This study validated the presence of C. jejuni persister cells and provided insight into understanding the formation mechanism of persister cells.   5.2 Introduction The emergence and spread of antibiotic-resistant bacteria is a serious health risk which could infect human and cause hard to treat diseases  (Neu, 1992). However, more and more evidence pointed out that antibiotic-resistant bacteria were not the only cause of chronic 148  infections. Bacteria can form a highly drug-tolerant subpopulation namely persister cells that might also contribute to the recalcitrance of infections to the chemotherapies (Monack et al., 2004; Mulcahy et al., 2010; Conlon, 2014). Persister cells are phenotypic variants of normal growing bacterial cells that are tolerant to antibiotics but not due to mutations. Hence, the genetic background of persister cells is identical to that of normal growing cells (Bigger, 1944; Keren et al., 2004b). Many pathogens have been validated to be able to form persister cells, such as Escherichia coli, Staphylococcus aureus, Salmonella enterica serovar Typhimurium, and Pseudomonas aeruginosa (Keren et al., 2004b). Several mechanisms have been proposed to decipher the formation of persister cells. The one with the most supportive evidence was that persister cells were the cells in low metabolic activity (i.e., slow or no growth) in response to stresses (Lewis, 2012). Brauner and colleagues systematically discussed the characteristics of antibiotic-resistant cells and persister cells (Brauner et al., 2016). They concluded that the survival mechanism of persister cells under antibiotic treatment was different from that of antibiotic-resistant cells. Specifically, the survival of antibiotic-resistant cells under antibiotic treatment was due to the mutation of antibiotic binding sites. In contrast, persister cells contained intact antibiotic binding sites. However, these persister cells were low in metabolic activity (i.e., slow or non-growing cells) which led to a bad binding between target sites and antibiotics. A study using time-lapse microscopy and microfluidic chamber to investigate the formation of  E. coli persister cells proved that E. coli persister cells were non-growing cells (Balaban et al., 2004). Another study revealed the similar mechanism of formation of persister cells from the molecular perspective that the expression level of biosynthesis and energy metabolism genes was considerably down-regulated in the persister cells of E. coli. In addition, fluorescent-labeled bacterial cells demonstrated a low level 149  of fluorescence when they transited from normal growing cells to persister cells  (Shah et al., 2006). All these studies indicated that low metabolic activity was one of the major features of persister cells and might be responsible for the tolerance of persister cells. Recent studies found the presence of toxin-antitoxin (TA) modules was also get involved in the formation of persister cells. TA modules comprised a pair of closely-linked genes encoding a stable “toxin” protein and a cognate “antitoxin” (the TA were proteins for type II, IV, V TA system; the TA were antisense RNA for type I, III TA system). The expression of RelE toxin in persister cells of E. coli was significantly higher than that in the normal growing cells of E. coli (Keren et al., 2004a). Another transcriptome analysis revealed that the over-expression of MazF toxin was observed along with the enhanced formation level of persister cells by over 10 times simultaneity (Vázquez-Laslop et al., 2006). Generally, a high proportion of persister cells was usually identified with the over-expression of toxins. However, the deletion of a single TA locus would not influence the formation of persister cells which indicated that that one set of TA module had limited functional effect on the formation of persister cells (Hansen et al., 2008; De Groote et al., 2009; Shan et al., 2015). Conlon and colleagues recently proved this hypothesis. They generated a 10 TA loci knockout mutant of E. coli and found a cumulative decrease of the formation level of persister cells along with each deletion of TA locus (Conlon et al., 2016). Hence, these TA systems might have a synergistic effect on influencing the formation of persister cells.  Campylobacter has been recognized as one of the leading causes of human gastrointestinal disease worldwide. Among the 18 species of Campylobacter identified so far, C. jejuni contributed to over 80% of Campylobacter-associated illness. The infectious dose of Campylobacter could be as low as 500 cells, and the infection caused by Campylobacter was 150  known as campylobacteriosis (Wilson et al., 2008). Campylobacteriosis has become one of the most reported foodborne illnesses in Canada, outnumbering the infections caused by Listeria monocytogenes, Salmonella, and Shiga toxigenic E. coli combined (Kalmokoff et al., 2006). C. jejuni infection is normally self-limiting within a week, and antibiotic treatment (i.e., azithromycin, ampicillin, ciprofloxacin, tetracycline, erythromycin) could rapidly eliminate the C. jejuni and resolve the disease. However, more and more cases of C. jejuni infections shared similarity with hard to treat diseases which need continuous antibiotic treatment, and the symptoms can last for several weeks (Schwerer, 2002). Hence, these C. jejuni cells must be highly tolerant to antibiotics. It is reasonable to speculate that these infections might be caused by some C. jejuni cells in a particular survival state, such as persister cells (Cappelier et al., 1999a; Cappelier et al., 1999b). The knowledge about persister cells of C. jejuni is still in its infancy. The aims of this study are 1) to identify the presence of C. jejuni persister cells; 2) to investigate the formation mechanism of these persister cells.   5.3 Materials and methods 5.3.1 Strains and bacterial cultivation.  C. jejuni isolates used in this study are listed in Table 5-1. C. jejuni was cultured at 37°C in a microaerobic chamber (85% N2, 10% CO2, 5% O2) on Mueller-Hinton (MH) agar supplemented with 5% defibrinated sheep blood (MHB agar) or in MH broth with constant shaking.    151  Table 5-1. Bacterial strains and plasmid used in the current study. Strain Description Reference MIC (µg/ml) Ampicillin  Ciprofloxacin C. jejuni F38011 human clinical isolate (Feng et al., 2016) 8 0.08 C. jejuni Human 10 human clinical isolate (Li et al., 2017) 4 0.08 C. jejuni 81116 human clinical isolate (Neal‐McKinney et al., 2010) 8 0.08 C. jejuni 1554 human clinical isolate Dr. Michael Konkel (Washington State Univ.)  8 0.08  5.3.2 The minimum inhibitory concentration test.  The minimum inhibitory concentrations (MIC) of ampicillin and ciprofloxacin against different C. jejuni isolates were determined using the microtiter broth dilution method as described previously (Wiegand et al., 2008). Briefly, overnight C. jejuni culture was diluted in MH broth to a final concentration of ~8 log CFU/ml and challenged by ampicillin or ciprofloxacin in a 96-well microplate. The treatment was maintained for 24 hours at 37°C in a microaerobic condition. The optical density of C. jejuni suspension was then measured using a microplate reader at 540 nm (SpectraMax M2, Molecular Devices, Sunnyvale, USA). The MIC values of different antibiotics against C. jejuni were defined as the lowest concentration of antibiotics that could inhibit the visible growth of C. jejuni cells. In addition, these MIC values were compared with 152  the breakpoint of MIC against resistant strains to reflect the susceptibility of C. jejuni cells used in this study (Luber et al., 2003; Ge et al., 2013).    5.3.3 Kinetics of persister formation.  C. jejuni cells were grown to a late-exponential phase and diluted in MH broth to ~8 log CFU/ml. Then, C. jejuni culture was challenged by either ampicillin (100 μg/ml, ~10x MIC) or ciprofloxacin (1 μg/ml, ~10x MIC). The treatment was maintained at 37°C in a microaerobic chamber. At the designated time points, an aliquot of the sample was collected, washed, serially diluted with sterile phosphate buffered saline (PBS, pH ~7.0 to 7.2) and plated on MHB plate. The viable C. jejuni cells number was enumerated accordingly.   5.3.4 RNA extraction and RNA-seq analysis of C. jejuni F38011 persister cells.  C. jejuni F38011 persister cells and normal growing cells were collected (4 hours antibiotics treatment for persister cells; 4 hours cultivation for normal growing cells) by centrifugation at 8,000 ×g for 5 min at 4°C. The cell pellet was then washed twice with cold PBS. The total RNA was extracted using a RiboPureTM RNA purification kit (Life Technologies, Grand Island, NY, USA) and purified using a MICROBExpressTM bacterial mRNA enrichment kit (Life Technologies, Grand Island, NY, USA). The purified mRNA was sequenced in a 2×150 paired-end configuration on Illumine HiSeq 2000 platform (Life Technologies). The raw sequence data was compiled and subjected to CLC genomics workbench software (CLCBio, Cambridge, MA) for analysis. The sequence reads were mapped to the reference genome of C. jejuni F38011. The analyzed transcriptomes were sorted by false discovery rate (FDR)-adjusted P values (<0.05) and a relative expression change (>2 fold).  153   5.3.5 The prediction of type II toxin and antitoxin (TA) module in C. jejuni F38011.  The type II TA modules of C. jejuni F38011 were predicted using TADB: an updated database of bacterial type II toxin-antitoxin loci (2.0 version) (Shao et al., 2010). Briefly, the annotated genome sequence of C. jejuni F38011 was downloaded from GenBank (Accession: CP006851.1) and uploaded onto TADB. The parameters for TA prediction was set as follow: the Expect value (E value) was set as 0.01; the maximum length of potential toxin and antitoxin were set as 500 amino acids; the maximum distance (or overlap) between potential toxin and antitoxin was set as from -50 to 200 nucleotides. The result of TA prediction was validated by another TA prediction tool RASTA-Bacteria according to its guidelines (Sevin and Barloy-Hubler, 2007).  5.4 Results and discussion 5.4.1 C. jejuni form multidrug tolerant persister cells Persister cells are phenotypic variants of normal growing cells that demonstrate the elevated tolerance to the treatment of antibiotics. The biphasic killing curve of bacterial cells under antibiotic treatment is a widely accepted signs that the persister cells present in the whole population. Both ampicillin and ciprofloxacin at bactericide concentration could rapidly eliminate the sensitive C. jejuni population and generate a killing curve with a sharp decrease viable cells. According to the MIC of ampicillin and ciprofloxacin against different C. jejuni isolates, including C. jejuni F38011, 81116, 1554 and human 10 (Table 5-1), the MIC of ampicillin was lower than 10 μg/ml (the breakpoint concentration of ampicillin for resistant strain) while the MIC of ciprofloxacin was lower than 1μg/ml (the breakpoint concentration of ciprofloxacin for resistant strain). Hence, none of these wild-type isolates were resistant strains.  154  Hence, it was possible to investigate the presence of persister cells using the killing curve method. In this study, ampicillin and ciprofloxacin were used to evaluate the presence and the formation level of persister cells of different C. jejuni isolates. The concentration of these two antibiotics was maintained at ~10 times of MIC which was 100 μg/ml for ampicillin and 1 μg/ml for ciprofloxacin. It should note that ampicillin and ciprofloxacin were distinct in the mechanism of action. Ampicillin is one of the beta-lactam antibiotics in the penicillin group, which inactivates bacteria by interfering the activity of enzyme transpeptidase and inhibiting the cell wall synthesis. Ciprofloxacin belongs to the fluoroquinolone class that inactivates bacteria by inhibiting DNA gyrase and cell division. Hence, the persister cells survived in both ampicillin and ciprofloxacin treatment could be regarded as multi-drug tolerant. Generally, the killing curves of both ampicillin and ciprofloxacin against several C. jejuni isolates including, C. jejuni 81116, 1554 and F38011 followed a classic biphasic pattern in which the susceptible population was rapidly eliminated, leaving a high tolerant subpopulation. In contrast, C. jejuni human 10 was rapidly eliminated to the level of the limit of detection of plating method by both ampicillin and ciprofloxacin. This results indicated that C. jejuni could form persister cells, but the capability of persister cells formation varied due to different strains. For the ampicillin-treated group, C. jejuni F38011 demonstrated the highest formation level of persister cells among four C. jejuni isolates (i.e., C. jejuni human 10, 1554 and 81116) in which persister cells of C. jejuni F38011 accounted for ~0.1% (~ Log 4 CFU/ml) of the total population. The level of persister cells of C. jejuni 8116 and 1554 was almost the same, which accounted for ~0.01% of the total population (Figure 5-1A). For the ciprofloxacin-treated group, persister cells of C. jejuni F38011, 81116, and 1554 demonstrated the similar formation level which accounted for ~0.05% of total population (Figure 5-1B).  155   Figure 5-1. The presence of C. jejuni persister cells was examined by antibiotics over time. The late-exponentially growing culture of C. jejuni was treated with antibiotics (~10 times MIC). The presence of biphasic killing curve indicated that a high tolerant subpopulation could survive the antibiotic treatment. (A) Ampicillin treatment at the concentration of 100 µg/ml. (B) Ciprofloxacin treatment at the concentration of 1 µg/ml.   5.4.2 The transcriptional analysis by next-generation sequencing (RNA-seq) of persister cells of C. jejuni F38011. Among all C. jejuni isolates tested for persister cells, C. jejuni F38011 demonstrated the highest formation level in both ampicillin and ciprofloxacin-treated groups. Due to this fact, C. jejuni F38011 was selected as the representative strain for the transcriptional analysis of persister cells. According to the killing kinetics of antibiotics, the killing curve of ampicillin and ciprofloxacin against C. jejuni F38011 was flatted out after 4 hours treatment (Figure 5-1). This indicated that persister cells of C. jejuni F38011 started to be the majority and accounted for a high proportion of the total population from 4 hours treatment. C. jejuni normal growing cells at 4 h (without the addition of antibiotics) were collected as the control. Since various regulations 156  were involved in the growth of bacteria and bacteria in different growth stages would show distinct expression profiles. In order to clarify the gene expression which was closely associated with the formation of persister cells, the global expression profile of the normal growing cells at 0 h (prior to the antibiotic treatment) and 4 h was measured and analyzed. According to the hierarchical clustering image (Figure 5-2), the gene expression profile of “control-0h” and “control-4h” were closely clustered and separated away from that of persister cells, indicating that the gene expression due to bacterial growth could be differentiated from that due to the formation of persister cells.  157   Figure 5-2. The hierarchical clustering of genes expression profile of C. jejuni F38011 cells. Each row was referred to a single gene. Each column was referred to a sample or a replicate. The “amp-4h” represented C. jejuni F38011 persister cells isolated by 4 hours ampicillin treatment; “cip-4h” represented C. jejuni F38011 persister cells isolated by 4 hours ciprofloxacin treatment; 158  “control-0h” represented C. jejuni F38011 normal growing cells prior antibiotic treatment; “control-4h” represented C. jejuni F38011 normal growing cells cultivated for 4 hours without antibiotic treatment.   Compared to normal growing cells (“control-4h”), C. jejuni F38011 persister cells isolated by ampicillin treatment (“amp-4h”) contained 109 differentially expressed genes (> 2 fold change, adjusted P-value < 0.01), including 92 up-regulated genes and 17 down-regulated genes. Further analysis by GO enrichment function found that these differentially expressed genes were mainly associated with central metabolism of bacteria. To be specific, the genes involved in the synthesis of oxidoreductase, nitrate reductase, and inorganic anion transmembrane transporter were significantly (> 2 fold change, adjust P-value < 0.01) up-regulated while the genes involved in the synthesis of tryptophan were significantly (> 2 fold change, adjust P-value < 0.01) down-regulated (Table 5-2). In addition, GO pathway analysis identified that these differentially expressed genes were mainly distributed on the pathways of nitrogen metabolism, peptidoglycan biosynthesis, bacterial secretion system, caprolactam degradation, and D-glutamine and D-glutamate metabolism (Table 5-3).    159  Table 5-2. The functional analysis of differentially expressed genes in C. jejuni F38011 persister cells isolated by ampicillin treatment on the basis of gene ontology terms. Gene ontology term Cluster frequency  Corrected P-value Genes oxidoreductase activity, acting on other nitrogenous compounds as donors 4/55 genes, 7.3% 0.00221 CJH_RS06780, CJH_RS03870, CJH_RS03875, CJH_RS03865 nitrate reductase activity  3/55 genes, 5.5% 0.00962 CJH_RS03870, CJH_RS03875, CJH_RS03865 inorganic anion transmembrane transporter activity  3/55 genes, 5.5% 0.17261 CJH_RS05870, CJH_RS02610, CJH_RS02585 tryptophan synthase activity 2/ 55 genes, 3.6% 0.19766 CJH_RS01710, CJH_RS01705    160  Table 5-3. GO pathway enrichment analysis of DEGs in C. jejuni F38011 persister cells isolated by ampicillin treatment.  Pathway DEGs with pathway annotation  P-value Pathway ID Nitrogen metabolism 4/76, 5.26% 005955841 ko00910 Peptidoglycan biosynthesis 4/76, 5.26% 0.04126756 ko00550 Bacterial secretion system 5/76, 6.58% 0.05178325 ko03070 Caprolactam degradation 1/76, 1.32% 0.05608856 ko00930 D-Glutamine and D-glutamate metabolism 2/76, 2.63% 0.08653091 ko00471  Compared to normal growing cells (“control-4h”), C. jejuni F38011 persister cells isolated by ciprofloxacin treatment (“cip-4h”) contained 139 differentially expressed genes (> 2 fold change, adjusted P-value < 0.01), including 79 up-regulated genes and 60 down-regulated genes. Further analysis by GO enrichment function identified that the genes responsible for the synthesis of oxidoreductase, NADH dehydrogenase, and the utilization of pyridoxal phosphate were significantly (> 2 fold change, adjusted P-value < 0.01) down-regulated. While the genes associated with the synthesis of amidine-lyase were significantly (> 2 fold change, adjusted P-value < 0.01) up-regulated (Table 5-4). In addition, GO pathway analysis identified that these differentially expressed genes were mainly distributed on the pathways of alanine, aspartate and glutamate metabolism, oxidative phosphorylation, arginine biosynthesis, and D-Glutamine and D-glutamate metabolism (Table 5-5).   161  Table 5-4. The functional analysis of differentially expressed genes in C. jejuni F38011 persister cells isolated by ciprofloxacin treatment on the basis of gene ontology terms.  Gene ontology term Cluster frequency  Corrected P-value Genes oxidoreductase activity, acting on NAD(P)H 7/84 genes, 8.3% 0.00270 CJH_RS08075, CJH_RS08065, CJH_RS08060, CJH_RS08045, CJH_RS08055, CJH_RS08050, CJH_RS08070 NADH dehydrogenase activity 5/84 genes, 6.0% 0.02313 CJH_RS08045, CJH_RS08055, CJH_RS08050, CJH_RS08070, CJH_RS08065 pyridoxal phosphate binding  5/84 genes, 6.0% 0.69163 CJH_RS01595, CJH_RS06960, CJH_RS03015, CJH_RS01120, CJH_RS01495 amidine-lyase activity 3/84 genes, 3.6% 0.16215 CJH_RS00115, CJH_RS06965, CJH_RS04595    162  Table 5-5. GO pathway enrichment analysis of DEGs in C. jejuni F38011 persister cells isolated by ciprofloxacin treatment.  Pathway DEGs with pathway annotation  P-value Pathway ID Alanine, aspartate and glutamate metabolism 8/100, 8% 0.0006002362 ko00250 Oxidative phosphorylation 11/100, 11% 0.007054049 ko00190 Arginine biosynthesis 4/100, 4% 0.01571895 ko00220 D-Glutamine and D-glutamate metabolism 2/100, 2% 0.1382485 ko00471  We noticed that C. jejuni F38011 persister cells isolated by ampicillin treatment shared various down-regulated genes with C. jejuni F38011 persister cells isolate by ciprofloxacin treatment. There shared down-regulated genes were mainly involved in energy metabolism and amino acid synthesis. However, they could not be clustered due to the low frequency of pathway annotation (Table A-1A for ampicillin group and 1B for ciprofloxacin group independent file). In addition, a specific term of genes associated with the functions of ATP binding (i.e. CJH_RS05510, CJH_RS00725, CJH_RS04985, CJH_RS06245, CJH_RS02020, CJH_RS06235, CJH_RS00715, CJH_RS07595, CJH_RS04600, CJH_RS08050, and CJH_RS08045) and amino acid synthesis (i.e. CJH_RS01710, CJH_RS01705, CJH_RS03780, CJH_RS05180, CJH_RS02190, CJH_RS06960, and CJH_RS01595) was found to be significantly down-regulated in both ampicillin-isolated and ciprofloxacin-isolated C. jejuni F38011 persister cells. The shutdown of ATP utilization and amino acid synthesis typically indicated a low metabolic 163  activity. Previous studies indicated that the bacteria with a low level of metabolic activity usually were more tolerant than normal growing cells(Betts et al., 2002; Voskuil et al., 2004; Asakura et al., 2007b). For example, dormant bacterial cells were highly tolerant to antibiotic treatment due to the low metabolic activity (Levin and Rozen, 2006; Dörr et al., 2010). Therefore, we speculated that the tolerance of C. jejuni persister cells against ampicillin and ciprofloxacin was due to the low metabolic activities. Type II TA modules were proposed to play important roles in the formation of persister cells  (Gerdes et al., 2005). For example, the activation of hipBA TA module could increase the formation level of E. coli persister cells (Keren et al., 2004a). For S. Typhimurium, 14 type II TA loci had been identified to contribute to the formation of persister cells (Helaine et al., 2014). However, no type II TA modules were predicted either by TADB or RASTA-bacteria, indicating a high probability that the well-recognized type II locus was absent in in C. jejuni F38011 genome. There might be some uncharacterized type II modules that were responsible for the formation of C. jejuni F38011 persister cells.  In this study, the presence of C. jejuni persister cells was validated by the antibiotic treatment. The transcription profile of these C. jejuni F38011 persister cells shared a high similarity as that of dormant cells which were low in metabolic activities. However, the signature TA modules that responsible for the formation of persister cells in other bacteria (i.e., E. coli and Salmonella) were not present in C. jejuni F38011. These findings provided new insights into understanding the survival of C. jejuni as persister cells and would aid the investigation of anti-persister cells treatments.   164  Chapter 6: Whole transcriptome sequencing analysis of synergistic antimicrobial effect of metal oxide nanoparticles and ajoene on Campylobacter jejuni  6.1 Summary Campylobacter jejuni is one of the leading foodborne pathogens worldwide. The Campylobacter infections are usually associated with the consumption of contaminated poultry meat. Antibiotic are commonly used in poultry farm to prevent the contamination of Campylobacter in chicken. Surveillance studies found a close correlation between the use of antibiotic in poultry and emergence of antibiotic-resistant Campylobacter. Hence, alternative antimicrobial approaches are highly desired. The significance of our research is in developing an alternative antimicrobial approach against C. jejuni. In this study, two metal oxide (i.e., Al2O3 and TiO2) nanoparticles and ajoene, a garlic-derived organosulfur compound, were identified to be effective antimicrobials against Campylobacter jejuni. By combining ajoene and metal oxide nanoparticle, a significant synergistic antimicrobial effect was achieved. Whole transcriptome sequencing (RNA-seq) analysis was applied to reveal the antimicrobial mechanism and identify the roles of ajoene and metal oxide nanoparticles in the synergistic treatment. Ajoene and metal oxide nanoparticles mediated a two-phase antimicrobial mechanism. Low concentration of ajoene served as the inducing factor at the first phase that caused damage to cell membranes and increased the susceptibility of C. jejuni. Metal oxide nanoparticles served as the active factor at the second phase that directly targeted the injured cells and physically disrupted cell structure. The knowledge of this study can be applied to reduce the prevalence and dissemination of C. jejuni in the poultry industry as well as in the environment.  165  6.2 Introduction Metal oxide nanoparticles have been widely used in our daily life. For example, aluminum oxide (Al2O3) nanoparticles have been approved and used as the material of personal care products (Sadiq et al., 2009). Titanium dioxide (TiO2) is a common additive in many personal care commodities (e.g., toothpaste), pharmaceuticals and food products, such as chewing gums and candies (Weir et al., 2012). Recent studies have demonstrated that metal oxide nanoparticles could efficiently inactivate a wide range of foodborne pathogens, including Salmonella, Escherichia coli O157:H7, Listeria monocytogenes, and Campylobacter, due to their unique electrical, chemical and physical properties (Chen et al., 2014). However, the individual treatment of metal oxide nanoparticles against drug-resistant bacteria might fail. For example, TiO2 nanoparticles could not completely inactivate the drug-resistant Cupriavidus metallidurans due to the overexpression of membrane restoration elements (Simon-Deckers et al., 2009). In addition, the high dose and very-frequently use of nanoparticles could also lead to negative outcomes. For example, Al2O3 nanoparticles were found to increase the efficiency of horizontal transfer of antibiotic resistance genes (conjugative transfer of RP4 plasmid) from E. coli to Salmonella by up to 200 fold  (Qiu et al., 2012). Under this circumstances, the modification of metal oxide nanoparticle or the combination treatment with other antimicrobials to achieve a synergistic treatment were highly desired.  Ajoene is an organosulfur compound derived from oil-macerated or ether-extracted garlic oil. As the major components of garlic oil, it has been used in traditional medicine to combat illness for hundreds of years (Goncagul and Ayaz, 2010).  Previous studies found that ajoene could significantly inactivate a broad range of Gram-positive and Gram-negative bacteria, including Cronobacter sakazakii (Feng et al., 2014), Helicobacter pylori (Ohta et al., 1999), Bacillus 166  cereus and Bacillus subtilis (Naganawa et al., 1996) and Staphylococcus aureus (Yoshida et al., 1998). When it was combined with tobramycin, an aminoglycoside antibiotic derived from Streptomyces tenebrarius, a strong synergistic antimicrobial effect against Pseudomonas aeruginosa was observed, and this combination treatment was even effective against biofilm (Jakobsen et al., 2012). Compared to other garlic-derived thiosulfinates (i.e., allicin), ajoene demonstrated a more potential to be applied in food industry due to its high stability (Ankri and Mirelman, 1999).  Transcriptome analysis using next-generation sequencing could offer the profiling of gene expression in a high-throughput manner, genome annotation and discovery of non-coding RNA. It has been applied in the investigation of bacterial responses (e.g., E. coli O157:H7, L. monocytogenes and Salmonella) to various stresses, including the oxidative stress (Wang et al., 2009), inorganic and organic acids (King et al., 2010), lysates of lettuce leaves (Kyle et al., 2010), chlorine dioxide (Pleitner et al., 2014), hyperosmotic and low temperature (Durack et al., 2013), dehydration (Gruzdev et al., 2012), starvation in peanut oil (Deng et al., 2012), and chlorine (Wang et al., 2010). In the current study, we tested the individual and synergistic antimicrobial effect of ajoene and metal nanoparticles (Al2O3 and TiO2 nanoparticles) against C. jejuni, a leading bacterial cause of human gastroenteritis. The mechanism of the stress and sub-lethal injury of C. jejuni by those above single and combined antimicrobial treatments were investigated using high-throughput whole transcriptome sequencing (RNA-seq) analysis. The knowledge from this study can aid the development of innovative antimicrobial treatments to reduce campylobacteriosis and other foodborne illnesses.    167  6.3 Materials and methods  6.3.1 Chemicals and reagents Al2O3 nanoparticles and TiO2 nanoparticles were purchased from Sigma-Aldrich (St Louis, MO, USA). The size of Al2O3 nanoparticles was in the range of with the size of 30-60 nm and size of TiO2 nanoparticles were around 21 nm. Ajoene was synthesized according to the protocols described in our previous study (Feng et al., 2014).   6.3.2 Bacterial strains and culture methods Four C. jejuni isolates including, F38011, ATCC 33560, y110539, and z110526, were used in this study. All of these strains were stored at -80°C in Mueller-Hinton (MH) broth containing 75% citrated bovine blood and 12% glycerol. C. jejuni cells were routinely cultivated either on MH agar plates supplemented with 5% citrated bovine blood or in 5 ml of MH broth at 37°C for overnight under a microaerobic condition (85% N2, 10% CO2, 5% O2). One milliliter of each C. jejuni culture (~ca. 9 log CFU/mL) was centrifuged at 8,000 ×g for 10 min at 4°C. The supernatant was discarded, and C. jejuni pellets were washed three times using sterile PBS (pH 7.0) and resuspended in sterile MH broth. An equal volume (2 mL) of each C. jejuni culture was combined as a cocktail to an initial concentration of ~8 log CFU/ml for the subsequent antimicrobial tests.  6.3.3 Antimicrobial effects of metal oxide nanoparticles and ajoene against C. jejuni The stock solution of Al2O3 nanoparticle and TiO2 nanoparticles were prepared by diluting Al2O3 nanoparticle suspension (20% w/v in H2O) and TiO2 nanoparticles (in a powder form) independently with sterile deionized water to a final concentration of 1 M. The stock solution 168  was stored at room temperature. Ajoene was dissolved in DMSO to a final concentration of 0.1 M and stored at 4°C. Different volumes of ajoene were added to C. jejuni culture, resulting in the final concentrations of 0.06, 0.125, 0.25, 0.5, and 1 mM. The antimicrobial tests of ajoene and metal oxide nanoparticle against C. jejuni were conducted as follow: the working stock of metal oxide nanoparticle suspensions was filtered through an aluminum oxide membrane filter (20 nm pore size, Anodisc; Whatman Inc., Clifton, NJ, USA) to harvest a nanoparticle-free solution. This water and DMSO (1 mM) were used as control groups. The stock solution of ajoene and metal oxide nanoparticles were mixed with C. jejuni culture to a series of final concentrations of 0, 0.5, 1, 2, 4, 8, and 16 mM. The treatments were conducted at both 22°C and 37°C for up to 24 h in a microaerobic condition. At 0, 2, 4, 7, 10, and 24 h, viable C. jejuni cells were enumerated on MH agar plates supplemented with 5% of defibrinated sheep blood.  6.3.4 Synergistic antimicrobial effect of metal oxide nanoparticle and ajoene against C. jejuni The synergistic antimicrobial treatment was conducted by challenging C. jejuni culture with the combination of ajoene and metal oxide nanoparticles (i.e., Al2O3 nanoparticles and TiO2 nanoparticles). The concentration of ajoene in the combination treatment was maintained at 0.06 mM, while the metal oxide nanoparticles were diluted to a series of final concentration from 0, 0.5, 1, 2, 4, 8, to 16 mM. The treatment was conducted at both 22°C and 37°C in a microaerobic condition with constant shaking. At 0, 2, 4, 7, 10, and 24 h, the viable C. jejuni cells were enumerated on MH blood agar plates supplemented with 5% of defibrinated sheep blood.  169  6.3.5 RNA-seq and real-time polymerase chain reaction (qPCR) C. jejuni F38011 was used as the representative strain for RNA-seq analysis. Overnight C. jejuni F38011 culture was diluted to a OD540 ~0.3, washed with sterile PBS, resuspended in MH broth and then challenged by (1) 1 mM ajoene, (2) 16 mM Al2O3 nanoparticles, (3) 16 mM TiO2 nanoparticles, (4) a combination of 0.06 mM ajoene and 4 mM Al2O3 nanoparticles, and (5) a combination of 0.06 mM ajoene and 4 mM TiO2 nanoparticles, respectively, for 1 h at 37°C in microaerobic conditions. The samples were collected by centrifugation at 8,000 ×g for 5 min at 4°C. The total RNA was extracted using a RiboPureTM RNA purification kit (Life Technologies, Grand Island, NY, USA).  The rRNA was removed using a MICROBExpressTM bacterial mRNA enrichment kit (Life Technologies, Grand Island, NY, USA). The purified mRNA was sequenced on an Ion Torrent sequencing system (Life Technologies).The raw sequencing data were compiled and analyzed using CLC genomics workbench software (CLCBio, Cambridge, MA). The transcriptomes data were sorted by false discovery rate (FDR)-adjusted P values (< 0.05) and a relative fold change of expression (> 2 fold). The differentially expressed genes were submitted to DAVID for cluster analysis. An aliquot of the purified mRNA was used to generate cDNA using SuperScript™ II Reverse Transcriptase (Invitrogen). The quantitative PCR (qPCR) was performed in triplicate using Power SYBR green PCR Master Mix (Applied Biosystems, Warrington, United Kingdom) on ABI Prism 7000 Fast instrument (Life Technologies). The primers used for qPCR were listed in Table 6-1. The amplification efficiency of each gene was determined using a standard curve method and the fold change of each gene was determined using the comparative Ct method (Schmittgen and Livak, 2008).  170  Table 6-1. The primers of selected genes used in qPCR validation  Primer Sequence (5’-3’) rpoA RT-F CGAGCTTGCTTTGATGAGTG rpoA RT-R AGTTCCCACAGGAAAACCTA slyD RT-F TGCGGTTCAAACTTTACCAA slyD RT-R GTTTCGCCATTTTCACCTTC CJH_03855 (Cj0768) RT-F GGGTACGTGAAATGCCTTTT CJH_03855 (Cj0768) RT-R AGCTTGCGATAATAGGAGGG CJH_05030 (Cj1004) RT-F ACAACATAATTTCAAAGCGCC CJH_05030 (Cj1004) RT-R TTTCCTTCCAAGCTCCATCT CJH_02460 (Cj0689) RT-F ATGCTTGAAAGTGCTGCAAA CJH_02460 (Cj0689) RT-R GGATTAGCACTAAGTCCGCT CJH_08660 (Cj1662) RT-F CGTGGTGCAAAATTTAAGCG CJH_08660 (Cj1662) RT-R TGATTGCTTGTGTTTTGGCT CJH_07030 (Cj1385) RT-F AGTCTTGTGCCTTTGATGGA CJH_07030 (Cj1385) RT-R CJH_02840 (Cj0561) RT-F CJH_02840 (Cj0561) RT-R CJH_08840 (Cj0439) RT-F CJH_08840 (Cj0439) RT-R GGACTAAAGGCAGCTTGTTC TTCCTGTGTTTTAGCCTCCA TAATATCCCTTGCACCCACA AGCGGAAGAGATGAAAATGC GCGTTCTTTTGCACCCTTAT 171  6.3.6 Statistical analysis All of the experiments were performed at least three times. The results are expressed as the means of the results of three independent replicates ± the standard deviations. The differences between samples were shown to be significant (P < 0.05) by one-way analysis of variance (ANOVA) using the Matlab software.   6.4 Results 6.4.1 Antibacterial effect of ajoene against C. jejuni.  Ajoene demonstrated a concentration-dependent antimicrobial effect against C. jejuni cocktail (Figure 6-1). However, the antimicrobial effect of ajoene varied due to different treatment temperatures (i.e., 22°C and 37°C). For example, viable C. jejuni cells were reduced to non-detectable levels after 7 h treatment by 1 mM ajoene at 37°C. In contrast, the same treatment could only generate a ~1 log CFU/mL reduction at 22°C. It was obvious that the temperature could influence the metabolic activity of the bacterial cell. Typically, the metabolic activity of bacteria was higher under high temperature than that under low temperature. Hence, we speculated that ajoene was more effective in inactivating the bacteria with high metabolic activity.  172   Figure 6-1. The individual ajoene treatment could generate a bacteriostatic effect on C. jejuni cocktail at 22°C (A) but a bactericidal effect at 37°C (B). Different colors indicate different samples (red line: control group without treatment; green line: samples treated with DMSO at the concentration of 1 mM; blue line: samples treated with ajoene at the concentration of 0.06 mM; purple line: samples treated with ajoene at the concentration of 0.125 mM; black line: samples treated with ajoene at the concentration of 0.25 mM; orange line: samples treated with ajoene at the concentration of 0.5 mM; light blue line: samples treated with ajoene at the concentration of 1 mM).  6.4.2 Antibacterial effect of metal oxide nanoparticles against C. jejuni.  We observed a concentration-dependent antimicrobial effect of individual metal oxide nanoparticle (i.e., Al2O3 and TiO2 nanoparticles) against C. jejuni. Compared to Al2O3, TiO2 nanoparticles treatment could cause a better antimicrobial effect against C. jejuni when they were applied at the same concentration (Figure 6-2 and Figure 6-3). For example, 16 mM TiO2 nanoparticles treatment at 22°C could completely inactivate C. jejuni cells within 24 h. In contrast, Al2O3 nanoparticles treatment at same concentration and temperature could only cause 173  ~2 log CFU/mL reduction of C. jejuni cells by 24 h. Similar to ajoene, the antimicrobial effect of Al2O3 and TiO2 nanoparticles also followed a temperature-dependent pattern. For example, the antimicrobial effect of 16 mM TiO2 nanoparticles at 37°C was significantly (P < 0.05) higher than that at 22°C. At 37°C, 16 mM TiO2 nanoparticles treatment could completely inactivate C. jejuni cells within 10 h (Figure 6-3A). In order to achieve the same antimicrobial effect, the treatment at 22°C had to be extended to 24h (Figure 6-2A).   174   Figure 6-2. Synergistic antimicrobial effect of ajoene and metal oxide nanoparticles against C. jejuni at 22°C. Panels: (A) Antimicrobial effect of TiO2 nanoparticles; (B) Antimicrobial effect of Al2O3 nanoparticles; (C) Synergistic antimicrobial effect of 0.06 mM ajoene and TiO2 nanoparticles; and (D) Synergistic antimicrobial effect of 0.06 mM ajoene and Al2O3 nanoparticles. Different symbols indicate different concentrations of metal oxide nanoparticles (red line: 0 mM; green line: 0.5 mM; blue line: 1 mM; purple line: 2 mM; black line: 4 mM; orange line: 8 mM; light line: 16 mM).  175   Figure 6-3. Synergistic antimicrobial effect of ajoene and metal oxide nanoparticles against C. jejuni at 37°C. Panels: (A) Antimicrobial effect of TiO2 nanoparticles; (B) Antimicrobial effect of Al2O3 nanoparticles; (C) Synergistic antimicrobial effect of 0.06 mM ajoene and TiO2 nanoparticles; and (D) Synergistic antimicrobial effect of 0.06 mM ajoene and Al2O3 nanoparticles. Different symbols indicate different concentrations of metal oxide nanoparticles (red line: 0 mM; green line: 0.5 mM; blue line: 1 mM; purple line: 2 mM; black line: 4 mM; orange line: 8 mM; light blue line: 16 mM).  176  6.4.3 Synergistic antimicrobial effect of metal oxide nanoparticle and ajoene against C. jejuni.  A synergistic antimicrobial effect was observed for the combined treatment of ajoene and metal oxide nanoparticles (i.e., Al2O3 and TiO2 nanoparticles) at both 22°C and 37°C (Figure 6-2C and Figure 6-3D). The concentration of metal oxide nanoparticles to start a synergistic antimicrobial effect against C. jejuni was 0.05 mM. The higher concentration of metal oxide nanoparticles in the combination treatment the better the synergistic antimicrobial effect was. For example, ajoene with 1 mM of Al2O3 or TiO2 nanoparticles achieved a bactericidal effect within 10 h. In comparison, the synergistic treatment completely inactivated C. jejuni within 4 h when the concentration of Al2O3 or TiO2 nanoparticles reached to 16 mM. The influence of temperature on the antimicrobial effect almost disappeared in the combination treatment. Thus, the antimicrobial effect of combination treatment at 22°C was similar to that at 37°C. In sum, the synergistic bactericidal effect was mainly associated with the exposure time and antimicrobial concentration rather than temperature.     6.4.4 Transcriptomic response of C. jejuni treated with metal oxide nanoparticles and ajoene.  The synergistic antimicrobial mechanism of the combination of ajoene and metal oxide nanoparticles against C. jejuni was investigated using RNA-seq analysis. The differentially expressed genes (FDR-adjusted P values (< 0.05) and a relative fold change of expression > 2 fold) derived from different treatment groups were summarized in the Table A-2 (independent file). The RNA-seq results were further validated by qPCR. The expression profiles of selected genes (CJH_02840, CJH_07030, CJH_08840, CJH_03855, CJH_05030, CJH_08660 and 177  CJH_02460) determined by qPCR were consistent with that determined by RNA-seq (Figure 6-4).   Figure 6-4. RNA-seq results were validated by qPCR. The expression profiles of these 7 genes were selected as the representatives from the treatment of 1 mM ajoene, 16 mM Al2O3 nanoparticles, 16 mM TiO2 nanoparticles, 0.06 mM ajoene and 4 mM Al2O3 nanoparticles, and 0.06 mM ajoene and 4 mM TiO2 nanoparticles.     178   The differentially expressed genes of C. jejuni F38011 due to different treatment were categorized based on the functional terms using DAVID analysis (Huang et al., 2009) and listed in Table 6-2 and Table 6-3. The ajoene treatment induced a relatively wide range of transcriptional response in C. jejuni F38011, including 34 up-regulated genes and 18 down-regulated genes. The up-regulated genes could be categorized into two groups on the basis of functional terms: (1) the function responsible for transcription-translation and (2) the function responsible for ATP utilization (Figure 6-5A and B). In addition, a set of genes responsible for efflux pump, including cmeA, cmeB, and cmeC, and an oxidative stress response gene katA were also significantly (FDR-adjusted P values (< 0.05) and a relative fold change of expression > 2 fold) up-regulated (Table A-2). However, due to the low frequency of corresponding functional terms, these genes were not clustered. Down-regulated genes were clustered in one group that referred to the term of the integral cell membrane (Figure 6-5C). In addition, a DNA repair-associated gene recN and a chemotaxis-associated gene cheY were also significantly (FDR-adjusted P values (< 0.05) and a relative fold change of expression > 2 fold) down-regulated (Table A-2). Taken together, low concentration of ajoene (1 mM) could induce a mild but not lethal stress in C. jejuni F38011.   179  Table 6-2. The differentially expressed genes in C. jejuni F38011 induced by 1 mM ajoene treatment.  Regulation category and annotation cluster Term and function Fold enrichment  Benjamini FDR Upregulation    1 (enrichment score, 11.56) GO:0019843; rRNA binding  18 0.00 GO:0003723; RNA binding  16 0.00 GO:0019843; rRNA binding  14 0.00 GO:0005840; ribosome  14 0.00 GO:0030529; intracellular ribonucleoprotein complex  11 0.00 GO:0005840; ribosome 13 0.00 GO:0006412; translation   8.7 0.00 GO:0003735; structural constituent of ribosome 6.9 0.00 GO:0005840; ribosome    8.1 0.00 GO:0015934; large ribosomal subunit 22 0.02 2 (enrichment score, 0.12) GO:0005524; ATP binding 1.2 1.00 GO:0000166; nucleotide binding 1 1.00 GO:0005524; ATP binding 0.8 1.00 downregulation    Regulation category and Term and function Fold Benjamini 180  annotation cluster enrichment  FDR 1 (enrichment score, 0.27) GO:0016021; integral component of membrane 1.5 0.93  GO:0016021; transmembrane helix 1.3 1.00  GO:0016021; transmembrane 1.3 1.00  GO:0005886; plasma membrane 1.2 1.00  Table 6-3. The differentially expressed genes in C. jejuni F38011 induced by 16 mM TiO2 nanoparticles treatment. Regulation category and annotation cluster Term and function Fold enrichment  Benjamini FDR Upregulation    1 (enrichment score, 0.89) GO:0016021; transmembrane helix 3.1 0.70 GO:0016021; transmembrane 3.1 0.46 GO:0005886; plasma membrane 2.8 0.42 GO:0016021; integral component of membrane 1.8 0.57  181   Figure 6-5. Transcriptional response of C. jejuni F38011 in response to the different treatments. The differentially expressed genes were categorized on the basis of the functional terms. Panels: (A) Up-regulated genes induced by the treatment of 1 mM ajoene: genes were clustered on the basis of transcription-translation term; (B) Up-regulated genes induced by the treatment of 1 mM ajoene: genes were clustered on the basis of energy utilization term; (C) Down-regulated genes 182  induced by the treatment of 1 mM ajoene: genes were clustered on the basis of integral cell membrane term; and (D) Up-regulated genes induced by the treatment of 16 mM TiO2: genes were clustered on the basis of integral cell membrane term. The clusters are shown in white color in panel (A) and (C) indicated that the differentially expressed genes were absent in the certain functional terms.   The treatment of Al2O3 nanoparticles barely induced any transcriptional response in C. jejuni F38011 regardless of the presence of ajoene. The individual treatment of 16 mM Al2O3 nanoparticles alone induced 2 differentially expressed genes, which were CJH_08660 (up-regulated by 3.7 fold) and CJH_05300 (down-regulated by 7.4 fold). The combined treatment of 4 mM Al2O3 nanoparticles with 0.06 mM ajoene induced 2 differentially expressed genes (CJH_03855, down-regulated by 3.7 fold, and CJH_00775, up-regulated by 7.8 fold). However, there was no overlap between the differentially expressed genes induced by individual treatment of 16 mM Al2O3 nanoparticles and that induced by the combined treatment of 4 mM Al2O3 nanoparticles with 0.06 mM ajoene.  The individual treatment of 16 mM TiO2 nanoparticles induced 6 up-regulated genes and 1 down-regulated gene in C. jejuni F38011. The up-regulated genes were categorized in a functional group that referred to the term of the integral cell membrane (Figure 6-5D). The combination treatment of 4 mM TiO2 nanoparticles with 0.06 mM ajoene only resulted in one up-regulated gene (CJH_08660 up-regulated by 3.5 fold).  There was a clear difference between the transcriptional response of C. jejuni F38011 to individual treatment of ajoene and individual treatment of Al2O3 nanoparticles or TiO2 nanoparticles. The gene CJH_08660 that encoded a protein for integral cell membrane was up-183  regulated in both ajoene-treated group and Al2O3 nanoparticles-treated group (Table A-2). The treatment of ajoene and the treatment of TiO2 nanoparticles resulted in the up-regulation of 2 common genes, CJH_08660 (encode integral membrane protein) and CJH_02460 (encode 50S ribosomal protein L24). Taken all together, the up-regulation of CJH_08660 was detected from all three treatment groups (i.e., ajoene, Al2O3 nanoparticles and TiO2 nanoparticles).  The differentially expressed genes (i.e., CJH_03855 and CJH_00775) induced by the combined treatment of ajoene and Al2O3 nanoparticles were unique, as they were not detected in either ajoene-treated group or Al2O3 nanoparticles-treated group. Combination treatment of ajoene and TiO2 nanoparticles induced only one differentially expressed gene (CJH_08660), which was also detected in all individual treatment groups.   6.5 Discussion Developing new antimicrobial and intervention strategies are critical to reducing the prevalence and dissemination of Campylobacter in the food industry as well as environment. In the current study, we investigate the potential of using natural product-derived compounds (ajoene) and metal oxide nanoparticles as antimicrobials to inactivate C. jejuni. Both individual treatment of ajoene and metal oxide nanoparticles demonstrated antimicrobial effect against C. jejuni and the antimicrobial effect was concentration and temperature dependent (Figure 6-1, 6-2 and Figure 6-3).  In order to achieve a better antimicrobial effect, Brown and colleagues functionalized silver and gold nanoparticles with ampicillin. They found that this modified nanocomposite demonstrated a strong bactericidal effect against multidrug-resistant Staphylococcus aureus. (Brown et al., 2012) In our previous study, ajoene was synthesized and showed a significant 184  antimicrobial effect against Cronobacter sakazakii at the concentration of 3.88 mM (Feng et al., 2014). Ajoene could easily penetrate the bacterial cell membrane and alter the conformational structure of thiol-containing proteins. Since the mechanism of action of ajoene and nanoparticles were generally different, there would be a potential to achieve a synergistic antimicrobial effect by combining these two compounds. In the current study, we identified a synergistic antimicrobial effect of using a combination treatment of ajoene and metal oxide nanoparticles against C. jejuni. Although individual treatment of either 0.06 mM ajoene or 1 mM nanoparticles (both Al2O3 and TiO2 nanoparticles) could only inhibit the growth of C. jejuni, the combination treatment could completely inactivate C. jejuni within 12 h (Figure 6-2 and Figure 6-3). An interesting observation was that the antimicrobial effect of the combination treatment was not influenced by temperature.     RNA-seq analysis was then applied to plot the transcriptional responses of C. jejuni to different treatments. The treatment of individual ajoene induced a relatively broad range of transcriptional response in C. jejuni F38011. The up-regulated genes are mainly involved in two pathways responsible for transcription-translation and ATP utilization (Table 6-2). Besides, several stress response genes, including dnak, groEL, katA, cmeA, cmeB, and cmeC, were also up-regulated (Table A-2). Dnak and groEL are general stress response genes that can mediate heat and starvation tolerance (Konkel et al., 1998; Klančnik et al., 2006). While cmeA, cmeB, and cmeC together encode an efflux pump that mediates the intrinsic tolerance to a broad range of antimicrobials (Lin et al., 2002; Gibreel et al., 2007). The katA gene can mediate the tolerance of bacterial cells to oxidative stress (Grant and Park, 1995; Van Vliet et al., 1999). On the other hand, down-regulated genes were mainly involved in a pathway responsible for the integrity of cell membranes. In addition, a DNA repair associated gene recN and a chemotaxis associated 185  gene cheY were also significantly down-regulated (Table A-2), suggesting that treatment of ajoene at a low concentration not be lethal stress. The major antimicrobial mechanism of ajoene was proposed to be the inhibition of thiol-containing enzymes via the interaction with thiol groups (Ankri and Mirelman, 1999; Ilić et al., 2011). This interaction was reversible due to its feature of non-covalence. Hence, a low concentration of ajoene would be hard achieve a bactericidal effect, which was validated by a previous study that low concentration of ajoene (< 20 μg/ml) only inhibited the growth of bacteria (Naganawa et al., 1996) Thiol groups, which are also extensively found in the membrane proteins and cell wall-bound proteins, might serve as the reducing compounds to protect the bacterial cell from the oxidative stress (Navarre and Schneewind, 1999; Möller and Hederstedt, 2006; Michelon et al., 2010). Therefore, the interaction between ajoene and thiol groups of membrane proteins might decrease the integrity of cell membrane and increase the susceptibility of cells. In agreement with these studies, the antimicrobial tests found that the treatment of ajoene for a short period (1 h) at a relatively low concentration (0.25 mM) only induced mild stress, rather than immediately lethal stress in C. jejuni (Figure 6-1 and Table 6-2). The RNA-seq analysis found that the individual treatment of ajoene could induce the up-regulation of RNA binding and ATP binding associated genes, but inhibit the metabolism of the integral cell membrane and chemotaxis (Table 6-2). Thus, ajoene could increase the susceptibility of C. jejuni to stress by impairing the integrity of cell membrane and the chemotaxis of the cells on the basis of a transcriptional-dependent mechanism.  In this study, individual treatment of metal oxide nanoparticles (Al2O3 nanoparticles and TiO2 nanoparticles) barely induced the transcriptional response of C. jejuni F38011. The treatment of Al2O3 nanoparticles only induced 2 differentially expressed genes, while the treatment of TiO2 nanoparticles induced 7 differentially expressed genes, including 4 up-186  regulated genes with the similar function to maintain the integrity of cell membrane. Previous studies had proposed several antimicrobial mechanisms of metal oxides nanoparticles. The adhesion of metal oxide nanoparticles onto the surface of bacterial cells was believed to be one of the leading causes of antimicrobial effect. According to Li and coauthors, Al2O3 nanoparticles had a positive surface charge at neutral pH that which could interact with the negatively charged surface of E. coli cells due to electrostatic interaction. (Li and Logan, 2004) In another study, Pakrashi and colleagues confirmed this statement and identified that Al2O3 nanoparticles coagulated at the cell membrane, disrupted cellular structure and subsequently led to the leakage of Bacillus licheniformis cells (Pakrashi et al., 2011). In addition, TiO2 nanoparticles were proposed to a photo-killing mechanism. For example, TiO2 nanoparticles were highly effective in inactivating P. aeruginosa, E. coli, and S. aureus within 1 h of UV illumination (Maness et al., 1999). Photocatalysis of TiO2 nanoparticles could enhance the peroxidation of the bacterial cell membrane and shut down respiration of cells (Foster et al., 2011). Our current study illustrated the significant antimicrobial effect of TiO2 nanoparticles against C. jejuni without UV illumination (Figure 6-2A and Figure 6-3A). Hence, we speculated that the adhesion to and physical disruption of the bacterial cell membrane might be a universal antimicrobial mechanism shared by different types of metal oxide nanoparticles. Previous studies indicated that inducing the generation of ROS could be another important antimicrobial mechanism for metal oxide nanoparticles. For example, the treatment of ZnO nanoparticles could lead to significant up-regulation of oxidative stress genes in C. jejuni (Xie et al., 2011). However, we did not observe any gene associated with the oxidative stresses in response to either Al2O3 nanoparticles or TiO2 nanoparticles in this study. 187  Although the combination treatment of ajoene and metal oxide nanoparticles could generate a synergistic antimicrobial effect against C. jejuni, it barely induced any transcriptional response. The combination treatment of Al2O3 nanoparticles with ajoene only induced 2 differentially expressed genes (CJH_03855 and CJH_00775), but these 2 genes were not shown in the individual treatment group. The combination treatment of TiO2 nanoparticles and ajoene only induced 1 differentially expressed gene (CJH_08660) that presented in all individual treatment group. Therefore, metal oxide nanoparticles were regarded as the leading antimicrobial factor in the combination treatment because the combination treatment inactivated C. jejuni mainly via the physical disruption conducted by metal oxide nanoparticles. Taken all together, the antimicrobial mechanism of synergistic treatment could be divided into two phases, inducing phase mediated by ajoene and reaction phase mediated by metal oxide nanoparticles. The treatment of ajoene damaged the cell membrane and increased the susceptibility of C. jejuni to stresses. Subsequently, the treatment of metal oxide nanoparticles might adhere to the injured cell membrane and physically disrupt C. jejuni cells.  6.6 Conclusion In conclusion, we identified that the combination treatment of metal oxide nanoparticles and ajoene could generate a significant synergistic antimicrobial effect against C. jejuni. RNA-seq analysis was applied to investigate the antimicrobial mechanism of this combination treatment. We propose a two-phase antimicrobial mechanism of synergistic treatment of ajoene and metal oxide nanoparticles, utilizing the injury of cell membrane mediated by ajoene and physical disruption mediated by metal oxide nanoparticles. This study provided a novel 188  intervention strategy to inactivate and limit the prevalence of C. jejuni and other foodborne pathogens in the food processing environment.   189  Chapter 7: Outlook In this dissertation, we found that C. jejuni could survive under stresses as biofilm or persister cells, indicating the importance of this two survival mode. Future work could be focused on the correlation between C. jejuni biofilm and persister cells. The microenvironment of biofilm was high acidic with limited nutrient which might facilitate the formation of C. jejuni persister cells. The chemical compositions and physical structure of C. jejuni biofilm might influence the microenvironment of biofilm and subsequently affect the formation of persister cells. In addition, the identification of candidate genes which were responsible for the formation of C. jejuni persister cells could be further extended. Previous studies proposed that type Ⅱ TA modules played an important role in the formation of persister cells. These type Ⅱ TA modules and their homologs were absent in C. jejuni F38011, although this strain could form a high level of persister cells. We speculated that the formation of C. jejuni persister cells could be mediated by genes with similar functions as TA modules. Persister cells were in a state with low of metabolic activity; they could still express virulence gene and should be regarded as a potential risk. Currently, the detection of persister cells was still a challenge. Hence, a rapid and accurate detection method for persister cells could be a future direction. This sensitive detection method could benefit the consumers as well as food industry.   190  References  Acheson, D., and Allos, B.M. (2001) Campylobacter jejuni infections: update on emerging issues and trends. Clinical infectious diseases 32: 1201-1206. Ades, S.E., Connolly, L.E., Alba, B.M., and Gross, C.A. 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