Land and Food Systems, Faculty of
DSpace
UBCV
Mu, Kaiwen
Doctor of Philosophy - PhD
University of British Columbia
Phenolic compounds derived from the diet are typically sourced from cereals, fruits and vegetables and also beverages. They are documented to have biological functions that include antioxidant and anti-inflammatory activities, and can mitigate gastrointestinal disorders. This thesis focused on looking at mechanism(s) of phenolic acid induced intracellular hydrogen peroxide (H₂O₂) level and effects on intestinal epithelial cell signaling that are related to intestinal epithelial functionality. The first experiment showed that different phenolic acids varied specifically in relative stability and capacity to produce H₂O₂ when incubated in cell culture media for 24 hr. Phenolic acids varied in affinity to induce apoptosis and inhibit proliferation in non-differentiated Caco-2 cells. Subsequent studies demonstrated the effect of selective phenolic acids on extracellular/intracellular redox by controlling H₂O₂ influx activity and to relate this event to cell signaling and control of oxidative stress in differentiated Caco-2 cells. HyPer-3, a genetically encoded fluorescent H₂O₂ sensitive indicator was constructed to monitor intracellular H₂O₂ in differentiated Caco-2 cells. Results showed that extracellular generation of H₂O₂ occurred from autoxidation of phenolic acids in culture and subsequent disappearance corresponded to intracellular uptake in differentiated Caco-2 cells. Phenolic acid specific pro-oxidant activity was sufficient to activate intracellular nuclear factor-erythroid factor 2-related factor 2 (Nrf2) cell signaling; the degree of which was dependent on both the source of the phenolic acid and concentration used in culture. A Caco-2/RAW 264.7 co-culture model enabled intercellular cell signaling measurements in response to an inflammatory response by inflamed macrophage. The capacity of specific phenolic acids to regulate the inflammatory status of activated RAW 264.7 cells was dependent on the type of phenolic acid which influenced Nrf2 cell signaling, monolayer integrity, and cytokine production in Caco-2 cells. It is concluded from these experiments that phenolic acids regulate extracellular/intracellular redox due to a susceptibility for pro-oxidant activity that is specific for individual phenolic acids. The pro-oxidant activity was related to capacity to produce H₂O₂, or its cellular influx, which in turn had a role in cell signaling, cytokine production and intestinal epithelial cell functionality.
ROLE OF PHENOLIC ACIDS ON INTESTINAL EPITHELIAL CELL SIGNALING AND FUNCTIONALITY by KAIWEN MU BSc, University of Manitoba, 2015 MFS, The University of British Columbia, 2016 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) August 2022 © Kaiwen Mu, 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Role of phenolic acids on intestinal epithelial cell signaling and functionality submitted by Kaiwen Mu in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Food Science Examining Committee: Dr. David D Kitts, Food Science, UBC Supervisor Dr. Siyun Wang, Food Science, UBC Supervisory Committee Member Dr. Simone Castellarin, Plant Science, UBC University Examiner Dr. Barbara, Stefanska, Human Nutrition, UBC University Examiner Additional Supervisory Committee Members: Dr. Rickey Yada, Food Science, UBC Supervisory Committee Member Dr. Zhaoming Xu, Human Nutrition, UBC Supervisory Committee Member iii Abstract  Phenolic compounds derived from the diet are typically sourced from cereals, fruits and vegetables and also beverages. They are documented to have biological functions that include antioxidant and anti-inflammatory activities, and can mitigate gastrointestinal disorders. This thesis focused on looking at mechanism(s) of phenolic acid induced intracellular hydrogen peroxide (H2O2) level and effects on intestinal epithelial cell signaling that are related to intestinal epithelial functionality. The first experiment showed that different phenolic acids varied specifically in relative stability and capacity to produce H2O2 when incubated in cell culture media for 24 hr. Phenolic acids varied in affinity to induce apoptosis and inhibit proliferation in non-differentiated Caco-2 cells. Subsequent studies demonstrated the effect of selective phenolic acids on extracellular/intracellular redox by controlling H2O2 influx activity and to relate this event to cell signaling and control of oxidative stress in differentiated Caco-2 cells. HyPer-3, a genetically encoded fluorescent H2O2 sensitive indicator was constructed to monitor intracellular H2O2 in differentiated Caco-2 cells. Results showed that extracellular generation of H2O2 occurred from autoxidation of phenolic acids in culture and subsequent disappearance corresponded to intracellular uptake in differentiated Caco-2 cells. Phenolic acid specific pro-oxidant activity was sufficient to activate intracellular nuclear factor-erythroid factor 2-related factor 2 (Nrf2) cell signaling; the degree of which was dependent on both the source of the phenolic acid and concentration used in culture. iv A Caco-2/RAW 264.7 co-culture model enabled intercellular cell signaling measurements in response to an inflammatory response by inflamed macrophage. The capacity of specific phenolic acids to regulate the inflammatory status of activated RAW 264.7 cells was dependent on the type of phenolic acid which influenced Nrf2 cell signaling, monolayer integrity, and cytokine production in Caco-2 cells. It is concluded from these experiments that phenolic acids regulate extracellular/intracellular redox due to a susceptibility for pro-oxidant activity that is specific for individual phenolic acids. The pro-oxidant activity was related to capacity to produce H2O2, or its cellular influx, which in turn had a role in cell signaling, cytokine production and intestinal epithelial cell functionality. v Lay Summary Phenolic acids are known for exhibiting antioxidant activity, and a capacity to undergo autoxidation; the latter associated with stability character. Collectively, these are important physicochemical properties of phenolic acids and often are underreported when attempts to describe multiple biological functions using cell culture experiments. The current study emphasized the role of phenolic acids on the protection of intestinal Caco-2 cell functionality. Application of mono-culture models that included Caco-2 cells, provided mechanisms of phenolic acids contributing to the control of oxidative stress and maintenance of redox status needed to preserve intestinal epithelial cells functionality. The advantage of using a more complex Caco-2/RAW 264.7 co-culture mode enabled studying the intercellular communication between intestinal epithelial cells and macrophage cells, and allowed macrophage act as a mediator that enabling Caco-2 cells to communicate to immune system. vi Preface Some content in the Chapter 1 literature review have been published in International Journal of Molecular Sciences, 2019, 20(24), 6222, entitled “Molecular mechanisms that define redox balance function in pathogen-host interactions—is there a role for dietary bioactive polyphenols?” Kaiwen Mu is the first author who wrote the manuscript and Dr. David Kitts is the corresponding author who revised the manuscript. Dr. Danni Wang is the second author who helped edit the manuscript. Some content in the Chapter 1 literature review have been published in International Journal of Molecular Sciences, 2019, 20(7), 1755., entitled “The role of nitric oxide in regulating intestinal redox status and intestinal epithelial cell functionality” Kaiwen Mu is the first author who wrote the manuscript and Dr. David Kitts is the corresponding author who revised the manuscript. Shengwu Yu is the second author who helped edit the manuscript. Chapter 2 is the basis of a manuscript that has been submitted to a peer reviewed journal. Kaiwen Mu and David Kitts: Hydrogen peroxide produced from selective phenolic acids in cell culture underlies Caco-2 changes in cell proliferation parameters. Kaiwen Mu designed the experiments, conducted the experiments, analyzed the data, and wrote the manuscript. Dr. David Kitts provided critical suggestions and revised the manuscript. Chapter 3 is the basis of a manuscript that has been submitted to a peer reviewed journal. Kaiwen Mu and David Kitts: Application of a HyPer-3 sensor to monitor intracellular H2O2 vii generation induced by phenolic acids in differentiated Caco-2 cells. Kaiwen Mu designed the experiments, conducted the experiments, analyzed the data, and wrote the manuscript. Dr. David Kitts provided critical suggestions and revised the manuscript. Chapter 4 is the basis of an unpublished manuscript. Kaiwen Mu and David Kitts: Phenolic acids contribute to H2O2 induced regulation of intracellular Nrf2 cell signaling in differentiated Caco-2 cells. Kaiwen Mu designed the experiments, conducted the experiments, analyzed the data, and wrote the manuscript. Dr. David Kitts provided critical suggestions and revised the manuscript. Chapter 5 is the basis of an unpublished manuscript. Kaiwen Mu and David Kitts: Phenolic acids as regulators of intestinal inflammation pathways in a Caco-2 and RAW 264.7 co-culture model. Kaiwen Mu designed the experiments, conducted the experiments, analyzed the data, and wrote the manuscript. Dr. David Kitts provided critical suggestions and revised the manuscript. viii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ................................................................................................................................ v Preface ........................................................................................................................................... vi Table of Contents ....................................................................................................................... viii List of Tables .............................................................................................................................. xiv List of Figures .............................................................................................................................. xv List of Abbreviations ............................................................................................................... xxiv Acknowledgements ................................................................................................................. xxvii Dedication ................................................................................................................................. xxix Chapter 1: Introduction ............................................................................................................... 1 1.1 General introduction ..................................................................................................................1 1.2 Literature review ........................................................................................................................4 1.2.1 General introduction on phenolic compounds .........................................................................4 1.2.2 Physiological relevance and metabolism of phenolic acids .....................................................5 1.2.3 Antioxidant/Pro-oxidant activity of phenolic acids .................................................................6 1.2.4 Generation of H2O2 from dietary phenolic compounds ...........................................................7 1.3 Redox homeostasis ....................................................................................................................10 1.3.1 Overview on redox homeostasis & reactive oxygen species (ROS) functionality ................10 1.3.2 Shifts of redox homeostasis and oxidative stress ...................................................................12 1.3.3 Intracellular/Extracellular redox state ....................................................................................13 ix 1.4 H2O2 as a signaling molecule ...................................................................................................14 1.4.1 Role of H2O2 in redox cell signaling and oxidative stress .....................................................14 NF-κB signaling pathway. ..............................................................................................................................16 Nrf2 signaling pathway. .................................................................................................................................17 1.4.2 Methodologies, old and new, used to measure cellular H2O2 status in situ ...........................19 1.4.3 Aquaporin facilitated transmembrane diffusion of H2O2 .......................................................21 1.4.3.1 Localization & expression of AQPs in intestine .........................................................................21 1.4.3.2 Functionality of AQPs in the intestine ........................................................................................22 1.4.3.3 Dysregulation of AQPs and intestinal diseases ...........................................................................24 1.4.3.4 Aquaporins and dietary nutrients ................................................................................................26 1.5 Cell models used to study intestinal inflammation ................................................................27 1.5.1 Macrophage RAW 264.7 cell model ......................................................................................27 1.5.2 Caco-2 cell model ..................................................................................................................29 1.5.2.1 Intestinal cellular integrity ..........................................................................................................30 1.5.2.2 IL-8 ..............................................................................................................................................32 1.5.3 Co-culture cell model .............................................................................................................32 1.6 Hypotheses and objectives .......................................................................................................34 Chapter 2: Autoxidation of selective phenolic acids in cell culture have varying effects on non-differentiated Caco-2 intestinal cell proliferation parameters ........................................ 37 2.1 Introduction ..............................................................................................................................37 2.2 Materials and methods .............................................................................................................38 2.2.1 Materials .................................................................................................................................38 2.2.2 Phenolic acids and culture conditions ....................................................................................39 2.2.3 Quantification of phenolic acids using high performance chromatography (HPLC) ............39 2.2.4 Production of H2O2 by phenolic compounds in cell free media ............................................40 2.2.5 Cell culture .............................................................................................................................40 x 2.2.6 Cell cytotoxicity assay ...........................................................................................................40 2.2.7 Cell proliferation assay ..........................................................................................................41 2.2.8 Analysis of apoptosis and necrosis in non-differentiated Caco-2 cells .................................42 2.2.9 Detection and quantification of nuclear morphology changes in apoptosis cells ..................42 2.2.10 Statistical analysis ..............................................................................................................43 2.3 Results and discussion ..............................................................................................................43 2.3.1 Loss of phenolic acids in culture media after 24 hr incubation .............................................43 2.3.2 Autoxidation of phenolic acids to H2O2 in cell-free culture media ........................................44 2.3.3 MTT reduction assay to assess phenolic acid cytotoxicity in non-differentiated Caco-2 cells…..………………………………………………………………………………………………50 2.3.4 BrdU assay to assess anti-proliferation activity of different phenolic acids in non-differentiated Caco-2 cells ..................................................................................................................51 2.3.5 Assessment of induced apoptosis and necrosis in non-differentiated Caco-2 cells treated with phenolic acids ..............................................................................................................................53 2.4 Conclusions ...............................................................................................................................60 Chapter 3: Application of HyPer-3 sensor to determine intracellular H2O2 production in differentiated Caco-2 cells .......................................................................................................... 61 3.1 Introduction ..............................................................................................................................61 3.2 Material and methods ..............................................................................................................64 3.2.1 Materials .................................................................................................................................64 3.2.2 Cell culture .............................................................................................................................64 3.2.3 Cell transfection of HyPer-3 ..................................................................................................64 3.2.4 HyPer-3 based flow cytometry analysis .................................................................................65 3.2.5 Confocal microscopy and HyPer-3 imaging ..........................................................................65 3.2.6 Assessment of cytotoxicity ....................................................................................................66 xi 3.2.7 Statistical analysis ..................................................................................................................66 3.3 Results and discussion ..............................................................................................................67 3.3.1 HyPer-3 based assay for H2O2: characterization of parameters .............................................67 3.3.2 Determination of intracellular HyPer-3 sensitivity to extracellular exposure to H2O2 or catalase. ...............................................................................................................................................68 3.3.3 Visualization of changes in HyPer-3 fluorescence in differentiated Caco-2 cells .................70 3.4 Conclusions ...............................................................................................................................74 Chapter 4: Phenolic acids contribute to H2O2 induced regulation of intracellular Nrf2 cell signaling in differentiated Caco-2 cells ..................................................................................... 75 4.1 Introduction ..............................................................................................................................75 4.2 Materials and methods .............................................................................................................78 4.2.1 Materials .................................................................................................................................78 4.2.2 Caco-2 cell culture .................................................................................................................79 4.2.3 H2O2 disappearance kinetics in differentiated Caco-2 cells ...................................................79 4.2.4 H2O2 determination in culture media in the presence of Caco-2 cells ...................................80 4.2.5 MTT reduction assay to assess phenolic acid cytotoxicity ....................................................80 4.2.6 Confocal microscopy and HyPer-3 imaging ..........................................................................80 4.2.7 Nuclear isolation of Caco-2 cells ...........................................................................................81 4.2.8 Analysis of Nrf2 binding activity by ELISA .........................................................................82 4.2.9 Western blot analysis of Nrf2 ................................................................................................82 4.2.10 Statistical analysis ..............................................................................................................83 4.3 Results and discussion ..............................................................................................................84 4.3.1 Kinetics of H2O2 disappearance in culture media containing Caco-2 cells. ..........................84 4.3.2 Production of H2O2 from phenolic acids and subsequent depletion by Caco-2 cells ............85 xii 4.3.3 Extracellular production of H2O2 by phenolic acids influences intracellular H2O2 concentration .......................................................................................................................................87 4.3.4 Phenolics affect extracellular H2O2 that regulates intracellular cell signaling .......................90 4.4 Conclusions ...............................................................................................................................96 Chapter 5: Phenolic acids as regulators of intestinal inflammation pathways using a Caco-2 and RAW 264.7 co-culture model .............................................................................................. 97 5.1 Introduction ..............................................................................................................................97 5.2 Materials and methods .............................................................................................................99 5.2.1 Materials .................................................................................................................................99 5.2.2 Cell culture ...........................................................................................................................100 5.2.3 Co-culture for determination of intestinal inflammation .....................................................100 5.2.4 Assessment of cell viability using MTT ..............................................................................101 5.2.5 H2O2 determination ..............................................................................................................101 5.2.6 Analysis of NF-κB activation in RAW 264.7 cells using ELISA assay .............................102 5.2.7 Cytokine TNF-α, IL-6 and IL-8 determination ....................................................................102 5.2.8 Nitric oxide determination ...................................................................................................103 5.2.9 Peroxynitrite determination ..................................................................................................103 5.2.10 Isolation of Caco-2 nuclear & cytosolic fractions ...........................................................103 5.2.11 Analysis of Nrf2 binding activity by ELISA ...................................................................103 5.2.12 Aquaporin-3 expression in Caco-2 cells ..........................................................................104 5.2.13 Epithelial monolayer resistance .......................................................................................104 5.2.14 Tight junction protein expression ....................................................................................104 5.2.15 Statistical analysis ............................................................................................................105 5.3 Results and discussion ............................................................................................................106 5.3.1 Establishment of a stable co-culture model .........................................................................106 xiii 5.3.2 Assessment of different phenolic acids on changes in inflammatory biomarkers derived from RAW 264.7 cells in the Caco-2/RAW 264.7 co-culture model ...............................................111 5.3.3 Characterization of phenolic acids modulation of activated RAW 264.7 cells on Caco-2 cell functionality ......................................................................................................................................117 5.4 Conclusions .............................................................................................................................129 Chapter 6: Conclusion and future directions ......................................................................... 130 6.1 Main findings ..........................................................................................................................130 6.2 Future directions ....................................................................................................................133 Appendix A The individual HPLC chromatograms of phenolic acids ..................................................195 Appendix B Patterns of H2O2 disappearance over time when added to culture media with differentiated Caco-2 cells. ..........................................................................................................................................196 Appendix C Response of Caco-2 cells treated with different concentration of phenolic acids measured by MTT assay ........................................................................................................................................197 Appendix D Evidence of purity of the isolated nuclear fraction, and cytoplasm fraction. ...................198 Appendix E Western blot to exam the activation of nuclear translocation of Nrf2 in Caco-2 cells .....199 Appendix F Nitric oxide production from mono-culture RAW 264.7 cells ..........................................201 Appendix G Intestinal cell barrier integrity measured as TEER value for a Caco-2 monolayer over 24 hr ............................................................................................................................................................202 Appendix H Cell viability of RAW 264.7 cells or Caco-2 cells in Caco-2/RAW co-culture. ..............203 Appendix I Activation of nuclear translocation of Nrf2 in Caco-2 cells in the mono-culture or co-culture cell system in the presence or absence of inducer. ....................................................................204 Appendix J Western blot of tight junction expression in Caco-2 cells .................................................205 xiv List of Tables Table 1.1 Free radical scavenging activities of some common dietary phenolic acids assessed using chemical assays. .................................................................................................................... 7 Table 1.2 Examples of H2O2 generated by oxidation of polyphenol in culture media (Adapted from (Halliwell, 2003; 2008; Kanner, 2020) with modifications). ................................................. 9 Table 1.3 Alteration of aquaporins expression under various pathological conditions. ............... 25 Table 2.1 Parameters defining H2O2 production from four different phenolic acids1 .................. 48 Table 2.2 Autoxidation of phenolic acids yielding H2O2 production in cell-free DMEM media after 24 hr incubation in the presence or absence of catalase.1 ..................................................... 49 Table 4.1 Comparison of H2O2 level generated by phenolic acids in the presence or absence of cells1. ............................................................................................................................................. 86 Table 5.1 Comparison of H2O2 levels generated by phenolic acids under cell culture conditions in the presence of RAW 264.7 cells treated with inducer cocktail (50 ng/mL LPS + 10 ng/mL IFN-γ). Data are expressed as mean ± standard deviation (n=3). ............................................... 117 xv List of Figures Figure 1.1 Major classes of dietary polyphenols, and examples of phenolic acids. Adapted from (Rasines-Perea & Teissèdre, 2017) with modification. .................................................................. 4 Figure 1.2 Schematic of HyPer-3, a genetically encoded fluorescent, H2O2 sensitive indicator. 20 Figure 1.3 A scheme showing the functionality of aquaporins. (A) Aquaporins involved in cytoskeletal structure by altering cell volume caused by abnormal Na+/K+ flux. (B) Aquaporins involved in regulation of intestinal barrier function. (C) Aquaporins involved in cell signaling and subsequent immune response. (D) Aquaporins involved in epithelial cell migration. (E) Aquaporins involved in cell proliferation caused by AQP3 facilitated glycerol entrance. .......... 24 Figure 2.1 Percentage loss of individual phenolic acids after 24 hr incubation in DMEM in the absence of cells. Data are expressed as mean ± standard deviation (n=3). Individual chromatograms are given in Appendix A. .................................................................................... 44 Figure 2.2 Temporal patterns of H2O2 production from polyphenolics, CA (a), CGA (b), FA (c) and GA (d), at concentration of 10 µM, 100 µM, and 1000 µM, respectively in culture media (DMEM) in the absence of cells. Data are expressed as mean ± standard deviation (n=3). Experiments were performed in triplicate. See Table 2.1 for specific time course parameters. .. 47 Figure 2.3 A schematic diagram that shows possible mechanisms for the autoxidation of polyphenols. Reproduced from references (Amorati et al., 2006; Bellion et al., 2009; Metodiewa et al., 1999). .................................................................................................................................. 47 Figure 2.4 The effects of different phenolic acids, CA (a), CGA (b), FA (c) and GA (d) on cell cytotoxicity of non-differentiated Caco-2 cells according to the MTT assay. Results are expressed as mean ± standard deviation (n=3). Significant differences in cells treated with xvi phenolic acids for 24 hr compared to presence of 1 µg/mL catalase (CAT) were performed by Student’s t-test, with *** representing p<0.001, ** representing p<0.01, *representing p<0.05........................................................................................................................................................ 50 Figure 2.5 The effects of different phenolic acids and concentrations on cell proliferation of non-differentiated Caco-2 cells according to the BrdU assay. Results are expressed as mean ± standard deviation (n=3). Significant differences in cells treated with phenolic acids for 24 hr compared to absence of phenolic acids (controls) were performed by Student’s t-test, with *** representing p<0.001, **representing p<0.01, *representing p<0.05, H2O2 was used as positive control. .......................................................................................................................................... 51 Figure 2.6 The effects of equimolar (e.g., 1mM) concentration of different phenolic acids both in the presence, or absence of 1 µg/mL catalase (CAT) on cell proliferation in non-differentiated Caco-2 cells. Results are expressed as mean ± standard deviation (n=3). Results are shown as BrdU incorporation relative to control cells (cells without any treatments). Significant differences refer to treatments comparing cells treated with phenolic acids without CAT to cells treated with phenolic acid with CAT, determined using Student’s t-test with *** representing p<0.001, *representing p<0.05. H2O2 was used as positive control. ........................................... 53 Figure 2.7 Normal, apoptotic and necrotic cells treated with CA, CGA, FA, and GA at 1 mM (a) or 1 mM + 1 µg/mL catalase (CAT) (b) were imaged using confocal microscopy with blue (Ex/Em = 405/450 nm), green (Ex/Em = 490/525 nm) and red (Ex/Em = 550/650 nm) signals. Scale bars: 50 µm. ......................................................................................................................... 58 Figure 2.8 (a) Morphological analysis of DAPI-stained nucleus of non-differentiated Caco-2 cells treated with 1mM of H2O2, CA, CGA, FA, or GA in the presence or absence of 1 µg/mL catalase (CAT) for 24 hr. Bar = 20 µm. Arrows are used to identify sampled cells. (b) xvii Quantification of area of DAPI-stained nucleus of each sample in (a), and average area of 20 cells were calculated for each sample treatment. Results are expressed as mean ± standard deviation (n=20). Significant differences in cells treated with phenolic acids for 24 hr compared to absence of phenolic acids (control) were performed by Student’s t-test, with *** representing p<0.001, **representing p<0.01. Significant differences in cells treated with phenolic acids in the presence or absence of CAT were performed by Student’s t-test, with *** representing p<0.001 and *representing p<0.05. .............................................................................................. 60 Figure 3.1 The HyPer-3 based assay for H2O2: characterization of parameters. Panels A & B refer to dual-parameter histograms displaying HyPer-3 expression in differentiated Caco-2 cells. Panel A shows the blank cells only (blue dots), and panel B shows the blank cells (blue dots) and the expressed HyPer-3 in Caco-2 cells (green dots). Panel C shows the confocal microscopy image of HyPer-3, expressed in a single Caco-2 cell. .................................................................. 67 Figure 3.2 Determining the HyPer-3 sensitivity to H2O2 or catalase (CAT) exposure by quantifying HyPer-3 ratio (the ratio of EX488/FL525 and EX405/FL525 signals), in differentiated Caco-2 cells. Data are expressed as mean ± standard deviation (n=3). Data were analyzed by one-way ANOVA using SPSS® Data Software. Significant differences were compared using LSD’s test with different letters (a-e) denoting statistical significance at p < 0.05................................................................................................................................................ 69 Figure 3.3 Live-cell imaging of changes in HyPer-3 fluorescence in differentiated Caco-2 cells when treated with 100 µM H2O2. Figure (A) represents HyPer-3 transfected cells without H2O2 treatment. Figure (B) represents HyPer-3 transfected cells treated with 100 µM H2O2. Arrows. are used to identify the differences in relative fluorescence ratios between t=0 and t=200 sec in control and treated cells, respectively. .......................................................................................... 71 xviii Figure 3.4 A time course depicting cumulative quantitation of HyPer-3 (ratio of EX488/FL525 and EX405/FL525) signals up to 1200 sec following exposure to 100 µM H2O2. Data are expressed as mean ± standard deviation (n=6). ............................................................................ 72 Figure 3.5 Structure of DFP00173 ................................................................................................ 73 Figure 3.6 Determination of effective concentration of DFP00173, an AQP3 inhibitor, on inhibition of H2O2 transport channel. Left Y-axis shows the HyPer-3 sensitivity ratio for blank cells, cells treated with 100 µM H2O2, and cells pretreated with different concentrations of DFP00173 followed by treatment of 100 µM H2O2. The Y-axis on the right shows the cell viability of Caco-2 cells following these treatments, using MTT assays. Data represent mean ± standard deviation (n=3). Data were analyzed by one-way ANOVA using SPSS® Data Software. Significant differences were compared using LSD’s test with different letters (a-c) denoting statistical significance at p < 0.05. ................................................................................................ 74 Figure 4.1 Disappearance kinetics of H2O2 with different initial H2O2 amount added. Circle dots and triangle dots refer to the initial H2O2 addition level, at 1 mM and 0.1 mM, respectively. The linear regression equation for initial H2O2 level of 100 µM, and 1 mM was y = -0.1063x – 0.5743 (R2 = 0.97), and y = -0.1363x + 0.1754 (R2 = 0.97), respectively. ............................................... 85 Figure 4.2 Live-cell imaging of changes in HyPer-3 fluorescence upon treatment of CA (a), CGA (b), FA (c), and GA (d) with or without pre-treatment of DFP00173 for 20 min on differentiated Caco-2 cells relative to cells without any treatments. The figure shows the ratio of EX488/FL525 and EX405/FL525 signals on exposure to phenolic acid monitored for 20 min. Error bars are mean ± standard deviation (n=6). ................................................................................................. 89 Figure 4.3 shows relative activation of nuclear translocation of Nrf2 in Caco-2 cells by various phenolic acids. Cells were treated with CA, CGA, FA, and GA at different concentration (10 xix µM, 100 µM and 1000 µM) for 24 hr, where the control refers to cells without any treatments. The positive control has H2O2 alone at the same concentration for phenolic acids. Data are expressed as mean ± standard deviation (n=3). Significant differences were performed by Student’s t-test with ***representing p<0.001, **representing p<0.01, *representing p<0.05, by comparing sample with control. .................................................................................................... 92 Figure 4.4 shows activation of nuclear translocation of Nrf2 in Caco-2 cells by various phenolic acid (1 mM) with or without the presence of catalase. The positive control was H2O2. Data are expressed as mean ± standard deviation (n=3). Significant differences were performed by Student’s t-test with ***representing p<0.001, **representing p<0.01, *representing p<0.05, by comparing sample in the presence or absence of catalase. ........................................................... 93 Figure 4.5 shows activation of nuclear translocation of Nrf2 in Caco-2 cells by various phenolic acid (1 mM) with or without the pre-treatment of DFP00173. The positive control was H2O2. Data are expressed as mean ± standard deviation (n=3). Significant differences were performed by Student’s t-test with ***representing p<0.001, **representing p<0.01, by comparing sample with or without DFP00173 pre-treatment. .................................................................................... 93 Figure 4.6 Representative western blot gel showing the activation of nuclear translocation of Nrf2 in Caco-2 cells when treated by different phenolic acids, CA (a), CGA (b), FA (c), GA (d) (1 mM) +/- DFP00173 or +/- catalase (CAT). Bar graphs show densitometry analysis of ratio of Nrf2 relative to beta actin determined from corresponding western blots. Results are expressed as mean ± standard deviation (n=3). Different letters indicate significant differences (p<0.05) exist among different treatments. Significance between treatments was analyzed by one-way ANOVA and LSD’s test (SPSS software). Superscripts with different letters (a, b, c) are significantly different (p<0.05). ......................................................................................................................... 94 xx Figure 5.1 A schematic description of the stable co-culture method used. Transwell inserts containing differentiated Caco-2 cells were inserted onto plates that contained RAW 264.7 cells (this represented the basolateral space). To simulate gut inflammation, an inducer treatment (50 ng/mL LPS + 10 ng/mL IFN-γ) was used and added to the basolateral compartment of the co-culture system for 24 hr. Phenolic acids were individually added to the basolateral part of the co-culture and incubated for 24 hr to determine the relative effect of phenolic acids on regulation of alteration of redox triggered by inflamed RAW264.7 cells in the co-culture model ................. 101 Figure 5.2 (a) Cell viability of RAW cells after 24 hr culture in the RAW mono-culture -/+ inducer (50 ng/mL LPS + 10 ng/mL IFN-γ) or Caco-2/RAW co-culture model -/+ inducer. (b) Cell viability of Caco-2 cells after 24 hr in Caco-2 mono-culture -/+ inducer (50 ng/mL LPS + 10 ng/mL IFN-γ) or Caco-2/RAW co-culture model -/+ inducer. Experiments were performed in triplicate. Cell viability was expressed as percentage relative to mono-culture of corresponding cell line. Data are expressed as mean ± standard deviation (n=3). Significant differences were analyzed by one-way ANOVA, using SPSS software. No significant differences were observed in each treatment for each cell line. ............................................................................................ 108 Figure 5.3 IL-6 (a), TNF-α (b) and nitric oxide (c) produced by RAW cells in mono-culture model, stable co-culture model and inflamed co-culture model. IL-8 (d) produced by Caco-2 cells in mono-culture model, stable co-culture model and inflamed co-culture model. Data are expressed as mean ± standard deviation (n=3). Significance between treatment was analyzed by one-way ANOVA and LSD’s test (SPSS software). Superscripts with different letters (a, b) are significantly different (p<0.05). .................................................................................................. 110 Figure 5.4 Activation of nuclear translocation of NF-κB in RAW cells in the Caco-2/RAW co-culture cell system by various phenolic acid. Cells were treated with CA, CGA, FA and GA at xxi 100 µM for 1.5 hr in the basolateral part in the presence of inflamed RAW 264.7 cells, where -control refers to cells without any treatments. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA, followed by LSD’s test using SPSS software. Superscripts with different letters (a, b, and c) are significantly different (p<0.05). ....................................................................................................................... 112 Figure 5.5 A select number of biomarker response to inflammatory induction by inducer and mitigation of induction by different phenolic acids. IL-6 (a), TNF-α (b), nitric oxide (c), and peroxynitrite (d) were generated in RAW cells in a co-culture model in response to the inducer. The different phenolic acids tested show variable capacities (p<0.05) to mitigate the inflammatory response, specific to the biomarker monitored. Data are expressed as mean ± standard deviation (n=3). Significant differences between treatments were analyzed by one-way ANOVA, using SPSS, followed by LSD’s test (p<0.05). Superscripts with different letters (a-e) are significantly different from each other. ................................................................................. 115 Figure 5.6 Activation of nuclear translocation of Nrf2 in Caco-2 cells in the Caco-2/RAW co-culture cell system when treated with different phenolic acids at 100 µM for 24 hr, applied to the basolateral segment in the presence of activated RAW 264.7 cells, + means cells treated with inducer (LPS+IFNg). -Control refers to cells without any treatments. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA, followed by LSD’s test using SPSS software. Mean values with superscripts holding different letters (a, b, c) are significantly different (p<0.05) from each other. .......................................... 119 Figure 5.7 Caco-2 epithelial barrier integrity measured as TEER value at 24 hr in co-culture with (+) or without (-) inducer, and different phenolic acids. Data are expressed as mean ± standard deviation (n=3). Treatment means were analyzed by one-way ANOVA to detect difference, with xxii LSD’s test using SPSS software to identify the difference between sample treatments. Superscripts with different letters (a, b, c) are significantly different from each other (p<0.05)...................................................................................................................................................... 123 Figure 5.8 Expression of tight junction proteins ZO-1 and Occludin from Caco-2 cells in co-culture with (+) or without (-) inflamed RAW 264.7 cells and different phenolic acid treatments. Data are expressed as mean ± standard deviation (n=3). Treatment means were analyzed by one-way ANOVA to detect difference, with LSD’s test using SPSS software to identify the difference between treatments. Superscripts with different letters (a, b, c) are significantly different from each other (p<0.05). Full western blot gel is shown in Appendix Figure J. ....... 124 Figure 5.9 Expression of Caco-2 cell IL-8 production in the Caco-2/RAW co-culture cell system when treated with different phenolic acids in the presence of inducer applied to the basolateral part. Phenolic acids were added at 100 µM in the presence of activated RAW 264.7 cells for 24 hr. - Control refers to cells without any treatments. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA, followed by LSD’s test using SPSS software to show difference between means. Superscripts with different letters (a, b, c, and d) are significantly different (p<0.05) from treatments. ................ 126 Figure 5.10 (a) shows expression of AQP3 in Caco-2 cells in the Caco-2 mono-culture cell model treated by various phenolic acids. Cells were treated with CA, CGA, FA and GA at 100 µM for 24 hr in the basolateral part in the presence of inducer, where -control refers to cells without any treatments. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA, using SPSS software. No significant differences have been observed among the sample treatments (p<0.05). Figure 5.10 (b) shows expression of AQP3 in Caco-2 cells in the Caco-2/RAW co-culture cell model treated by various xxiii phenolic acids. Cells were treated with CA, CGA, FA and GA at 100 µM for 24 hr in the basolateral part in the presence of inflamed RAW 264.7 cells, where -control refers to cells without any treatments. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA, using SPSS software. Superscripts with different letters (a and b) are significantly different (p<0.05). ................................................... 128 xxiv List of Abbreviations 7-AAD 7-aminoactinomycin D ADHP 10-acetyl-3,7-dihydroxyphenoxazine ANOVA analysis of variance AP active protein 1 AQP aquaporin ARE antioxidant response elements ATP adenosine triphosphate Bax Bcl-2-associated X protein Bcl2 B-cell lymphoma 2 BrdU bromodeoxyuridine BSA bovine serum albumin CA caffeic acid cAMP cyclic adenosine monophosphate CAT catalase CGA chlorogenic acid Cys-S- thiolate anions Cys-SH cysteine thiol cpYFP circularly permuted yellow fluorescent protein CREB cAMP-responsive element binding protein DAPI 4′,6-diamidino-2-phenylindole DCFH-DA 2’,7’ -dichlorodihydrofluorescein diacetate DMEM Dulbecco's Modified Eagle's Medium xxv DNA deoxyribonucleic acid DPPH• 1,1-diphenyl-2-picrylhydrazyl radical DSS dextran sulfate sodium E.coli Escherichia coli ELISA enzyme-linked immunosorbent assay FA ferulic acid FBS fetal bovine serum FITC fuorescein isothiocyanate FOX ferrous oxidation assay GA gallic acid GAPDH glyceraldehyde-3-phosphate dehydrogenase GSH glutathione HBSS hanks’ balanced salt solution H2O2 hydrogen peroxide HPLC high performance liquid chromatograph IFN-γ interferon gamma IL-1β interleukin 1 beta IL-6 interleukin 6 IL-8 interleukin 8 iNOS inducible nitric oxide synthase Keap 1 Kelch-like ECH-associated protein 1 LPS lipopolysaccharides LSD least significant difference xxvi MAPK mitogen-activated protein kinase mRNA messenger ribonucleic acid MTT 3-(4,5-diethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide NADPH nicotinamide adenine dinucleotide phosphate NF-κB nuclear factor kappa B Nrf2 nuclear factor-erythroid factor 2-related factor 2 O2•- superoxide anion radical –OH hydroxyl groups •OH hydroxyl radical PBS phosphate buffered saline PKA protein kinase A PS phosphatidylserine ROS reactive oxygen species RNS reactive nitrogen species SDS sodium dodecyl sulfate SOD superoxide dismutase enzyme SO2H sulfinic SO3H sulfonic TBST Tris-buffered saline with 0.1% Tween® 20 detergent TEER transepithelial electrical resistance TMB 3,3′,5,5′-Tetramethylbenzidine TNBS 2,4,6-trinitrobenzene sulfonic acid TNF-α tumor necrosis factor alpha xxvii Acknowledgements First of all, I would like to thank my parents for giving me life and unconditional love, raising me up and shaping me into the person I am. To my dearest mom: thank you for being my best friend, my mentor, and my lifelong idol. I would also like to thank my grandparents, my uncles and aunts for always caring for me, passing on the wisdom of life to me, and giving me continuous strong support and confidence to conquer all the challenges in my life. I would like to thank the deep friendship from my friends Yigong Guo, Fan Yang, Cindy Dai and Mona Li for always being by my side to cheer me up, giving me a lot of joy, and always caring and supporting me. I would like to thank my supervisor Dr. David Kitts, for believing in my potential and giving me a PhD offer instead of a MSc offer years ago, which was an important turning point in my life. Thank you for giving me this opportunity to be part of your research team, providing me with funding support to try research ideas, as well as continuously providing me training on critical thinking skills, scientific paper writing skills, and guiding me to be my very best. Words can never truly express how grateful I am for this research journey you’ve given me. I would also like to thank my thesis advisory committee, Dr. Siyun Wang, Dr. Rickey Yada, and Dr. Zhaoming Xu for putting in very insightful feedback in all committee meetings, and their continuous support throughout these years. I appreciate Dr. Wang and her research group for providing me training on microbiology technique. A particular thank to Dr. Yufeng Yao for taking me as an intern in his lab to learn Hyper-3 extraction technique, and Dr. Jing Tao and Dr. Danni Wang for providing me technical support during this internship. It was a really enjoyable internship experience in my life. xxviii A sincere appreciation also goes to my previous colleagues Dr. Xiumin Chen, Dr. Ningjian Liang, and summer interns Sabrina Wan, Jessica Liao, and Xiwen Wang for conquering all the technical problems with me together. I give my enduring gratitude to the faculty and staff at UBC. I thank Peter Hoffman for always being there to provide technical support; Dr. EunKyoung Lee from UBC bioimaging facility for her training on confocal microscopy, and sharing her research experience with me; Andy Johnson from UBC flow cytometry facility for giving me training on flow cytometer. Last but the very important, special thanks are owned to my funders, Mitacs, LFS faculty, and Li-Chan and Nakai families for providing me financial support throughout these years. xxix Dedication Dedicated to this one-time life 1 Chapter 1: Introduction 1.1 General introduction Phenolic acids represent a relatively large group of naturally derived phytochemicals that are widely present in fruits, vegetables, and many common beverages and herbal medicines. The average daily intake of dietary phenolic compounds ranges from less than 100 mg to over 2 g (Clifford, 2004; Del Rio et al., 2013; Scalbert & Williamson, 2000). The biological effects of phenolic compounds within the gastrointestinal tract have been extensively studied due to the potentially high content that can be measured in gastrointestinal tract (Halliwell et al., 2000; Kanner & Lapidot, 2001). Over the past few decades, researchers have focused on addressing the antioxidant and anti-inflammatory properties of phenolic acids using in vitro chemical assays. In more recent years, it has also been reported that many common dietary phenolics that have antioxidant capacity, also are pro-oxidants and are a source of hydrogen peroxide (H2O2) production. Despite this awareness, many studies have underreported the significance of the generation of H2O2 in culture media from dietary phenolics in various model systems that result in biological effects that are potentially relevant to in vivo conditions. Hydrogen peroxide represents a major redox metabolite that is generated from normal metabolism in all mammalian cells (Di Marzo et al., 2018; Sies & Chance, 1970). It is recognized to be a second messenger with an important role in redox regulation and modulation of cell signaling pathways. Cell signaling is a process that enables cells to perceive and respond to changes in the extracellular microenvironment that can affect cell proliferation, development, and metabolic homeostasis (Kovacic & Pozos, 2006). One example of this is with the recognition that extracellular redox status is appreciated to be critical to maintain protein stability and 2 function (Ottaviano et al., 2008). More generally, it also has an important contributing role to the underlying causes of many chronic diseases associated with adverse changes in the extracellular redox environment (Ashfaq et al., 2006) and related changes in intracellular signal transduction. Regulation of extracellular H2O2 in concert with the intracellular microenvironment is an important component of redox homeostasis (Ursini et al., 2016). Aquaporins (AQPs) represent a family of water channel membrane proteins with a molecular weight of approximately 30 kDa, and are important to the cell by having roles in facilitating cellular transportation of water and other minor solutes in animals (Almasalmeh et al., 2014). The AQPs isomers 1, 3, 4, 5, 7, 8 and 9 in particular, are involved in the transmembrane diffusion of H2O2 in mammalian cells (Almasalmeh et al., 2014; Rodrigues et al., 2016). With intestinal cells, normal expression of AQPs is considered essential to maintain a healthy state, and either an over- or under-expression of AQPs can disrupt the redox balance thus causing intestinal diseases such as constipation or diarrhea (Ikarashi et al., 2016; Zhu et al., 2016). Although dietary nutrients are considered important to regulate intestinal health (Lv et al., 2021), polyphenolic compounds are also important to intestinal health by acting as substrates that generate H2O2 production in the endothelial cell membrane of the blood system (Erlank et al., 2011). Therefore, it is important to understand how dietary factors, in general, and phenolic acids in particular, influence the generation of H2O2 and AQP function. These initial responses to the physical-chemical factors attributed to specific polyphenolics that then regulate intestinal redox status and oxidative stress continues to be updated with new research findings. Intestinal epithelial cells have important functions that include enabling passive nutrient absorption and acting as a defense barrier to potential xenobiotic components. Experiments using mono-culture protocols of cells have traditionally provided information on basic intestinal 3 epithelial cells functionalities; however, they are limited in capacity to characterize the subtle mechanisms that pertain to cell signaling. Consequently, advances made in utilizing a co-culture of more than one cell type can enable experimentation to define changes in intercellular communication that may explain the underlying mechanism of intestinal epithelial cell functionality. In this study, both mono- and co-culture of differentiated human Caco-2 intestinal cells, and RAW 264.7 murine macrophage, respectively were used as model systems to demonstrate the impact of a changing extracellular redox balance on intercellular cell signaling and its effect on cell function homeostasis. This thesis explores the different capacities of four major and commonly found phenolic acids, namely, caffeic, chlorogenic, ferulic and gallic acids, to generate H2O2 in culture and how extracellular production of H2O2 can influence intracellular H2O2 metabolism and the subsequent redox balance in cultured macrophage and intestinal cells. The autoxidation reaction of phenolic acids occurring in culture was traced to important intracellular cell communication signaling that were related to antioxidant and anti-inflammatory cell responses specifically to RAW 264.7 macrophage and intestinal epithelial Caco-2 cells; when cultured individually and also in co-culture. 4 1.2 Literature review 1.2.1 General introduction on phenolic compounds Polyphenols are naturally occurring phytochemical compounds present in fruits and vegetables, as well as beverages including coffee, tea and wine. They represent a complex mixture that is mainly divided into two categories, including flavonoids and non-flavonoids; the flavonoids being sub-divided into anthocyanin, flavanol, flavanone, flavonol, flavonone, and isoflavones, shown in Figure 1.1. The non-flavonoids are sub-divided into phenolic acids, xanthones, stilbenes, lignans, and tannins. The average intake of polyphenol compounds can reach over 1.5 g per day, and the average intake of two major polyphenol groups; namely flavonoids and phenolic acids can reach 0.9 g and 0.8 g/day, respectively (Grosso et al., 2014). Figure 1.1 Major classes of dietary polyphenols, and examples of phenolic acids. Adapted from (Rasines-Perea & Teissèdre, 2017) with modification. PolyphenolPhenolic acidsNon-FlavonoidsFlavonoidsStilbenesHydroxybenzoic acidsHydroxycinnamic acidsFlavonolsFlavanolsFlavanonesIsoflavonesAnthocyaninsFlavononesXanthonesLignansTanninsCaffeic acidFerulic acidChlorogenic acidGallic acidVanillic acidProtocatechuic acid 5 Phenolic acid structure consists of two major groups, including benzoic acids and cinnamic acids, that are different on the C1-C6 and C3-C6 backbones. Gallic acid, p-hydroxybenzoic acid, vanillic acid, syringic acid, protocatechuic acid are representative hydroxybenzoic derivatives, whereas caffeic acid, chlorogenic acid, p-coumaric acid, ferulic acid, and sinapic acid are representatives of hydroxycinnamic acid. Phenolic acids with distinctly different structures exhibit various bioactivities. Epidemiological studies have reported on dietary intake of beverages rich in phenolic acids will exert a protective effect against major diseases that include cancer (Boudet, 2007), cardiovascular diseases (Boudet, 2007) and diet-induced obesity (Rodríguez-Pérez et al., 2019). These examples of protection of phenolic compounds are likely related to general anti-inflammatory, antioxidant, anti-allergenic, anti-thrombotic and vasodilatory effects (Carrieri et al., 2013; Chen et al., 2019; Daleprane et al., 2012; Pernin et al., 2019). On the other hand, extremely high consumption of phenolic acids will lead to toxicity, such as genotoxicity, induced cardiovascular diseases and heart failure (Ardah et al., 2014; Cory et al., 2018). 1.2.2 Physiological relevance and metabolism of phenolic acids The health implications of dietary phenolic compounds depends on the chemical structure of the phytochemical components, as well as interactions with other components in food matrix that can influence bioaccessibility and bioavailability after ingestion (Farah et al., 2008). Poor bioaccessibility of phenolic acids is due to binding to macromolecules in the food matrix, such as fibre and protein. Indeed, phenolic acids have a relatively greater bioaccessibility in liquids, such as beverages (Bento-Silva et al., 2020). The bioavailability of phenolic acids is also influence by the activity of microbiota in the large intestine and degradation enzymes present in intestinal 6 tissues, known to be critically important as major routes for the release of free phenolic acids from respective bound conjugates in vivo (Andreasen et al., 2001a; 2001b; Kroon et al., 1997; Plumb et al., 1999). Once available for absorption, phenolic acids in vivo undergo a biotransformation of metabolism in the human digestive system to produce products that differ in molecular size or polarity. The process of metabolism of phenolic acids has been extensively studies, and results show that phenolic acids reach the small intestine (Cardona et al., 2013). Hydrolysis and degradation of ingested phenolic acids in the colon occurs due to the activity of colonic enzymes from microflora (Parkar et al., 2013). The metabolite products of phenolic acids pass through the gastrointestinal barrier and enter the peripheral blood circulation (Andreasen et al., 2001a; 2001b; Kroon et al., 1997; Plumb et al., 1999). The amount of intact conjugated polyphenols in the blood is much lower than corresponding degradation products, due to the action of colonic bacteria enzymes as well as subsequent metabolism in the liver (Boudet, 2007; Rechner et al., 2002). 1.2.3 Antioxidant/Pro-oxidant activity of phenolic acids Antioxidant activity of phenolic acids has been ascribed by many researchers to involve a capacity to scavenge free radicals, or sequester reactive metal ions; the latter reduces the initiation rate of oxidation. The affinity of phenolic acids to sequester metal ions occurs by presence of aromatic hydroxyl groups (Afanas'ev et al., 1989; Brown et al., 1998; Lopes et al., 1999; Mira et al., 2002; Moran et al., 1997) which reduce transition metal ion induced initiation of peroxidation (Akagawa et al., 2003). Common examples of free radical scavenging activities of phenolic acids includes quenching hydroxyl radical (•OH) (Hanasaki et al., 1994), superoxide anion radical (O2•-) (Hatano et al., 1990; Nakagawa et al., 2002), both of which are the basis of a 7 chemical assay uses a stable, non-reactive 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical to assess sequestering capacity (Hatano et al., 1990; Nanjo et al., 1996) (Table 1.1). In relative terms, phenolic compounds have a strong capacity to scavenge free radicals, while being less reactive with H2O2. On the other hand, phenolic acids may not function in parent form in the culture media, but may exhibit pro-oxidant activity (Halliwell, 2008), depending on the conditions. Table 1.1 Free radical scavenging activities of some common dietary phenolic acids assessed using chemical assays. Phenolic compounds Free Radical Scavenging Activity Reference Protocatechuic acid Best against DPPH• & O2•- (Mathew et al., 2015) Caffeic acid Best against DPPH• & O2•- (Gülçin, 2006) Gallic acid Best against DPPH• & O2•- (Liu et al., 2014) Chlorogenic acid •OH & O2•- (Kono et al., 1997; Liang & Kitts, 2015) Ferulic acid •OH, DPPH• & O2•- (Mathew et al., 2015) Vanillic acid •OH, DPPH• & O2•- (Mathew et al., 2015) Sinapic acid •OH, DPPH• & O2•- (Mathew et al., 2015) p-coumaric acid •OH, DPPH• & O2•- (Mathew et al., 2015) DPPH•: 1,1-diphenyl-2-picrylhydrazyl radical; •OH: hydroxyl radical; O2•-: superoxide anion radical 1.2.4 Generation of H2O2 from dietary phenolic compounds Tea catechins, for example, when present in cell culture media, or buffer solutions trigger significant H2O2 production (Dashwood et al., 2002; Miura et al., 1998; Roques et al., 2002). Variable effects on mammalian cellular redox status have been attributed to phenolic acids according to how they are involved in the generation of H2O2 under different cell culture conditions. Moreover, other studies have demonstrated that high H2O2 concentrations are 8 produced from polyphenol-rich beverages, such as cocoa, green tea, black tea and coffee during processing (Long et al., 2000). These findings have been linked to the induction of cell apoptosis and a mutagenicity index, and can be eliminated in vitro when catalase is added to the reaction mixture (Alejandre-Durán et al., 1987; Fujita et al., 1985; Nakagawa et al., 2002). Experiments using healthy volunteers have shown phenolic acid intake from typical coffee drinking practices can increase urinary H2O2 levels, hence advocating that coffee consumption can influence human redox potential and reduce oxidative stress (Long et al., 2000). Polyphenolics have also been shown to produce H2O2 in the endothelial cell membrane of the blood system; however, it is yet to be determined whether phenolic acids would produce H2O2 in the human intestine (Kanner, 2020; Pellavio et al., 2017; Tamma et al., 2018). In addition, the apparent pro-oxidant effects of phenolic acids also trigger antioxidant defense systems and xenobiotic metabolizing enzymes by imposing a mild degree of oxidative stress that results in cell signaling to initiate cytoprotection (Fahey & Kensler, 2007). 9 Table 1.2 Examples of H2O2 generated by oxidation of polyphenol in culture media (Adapted from (Halliwell, 2003; 2008; Kanner, 2020) with modifications). Polyphenol Evidence Description Reference Catechols Cytotoxicity to PC12-AC cells H2O2 generation in extracellular space results in cytotoxicity (Chichirau et al., 2005) Coffee polyphenols Activation of NF-κB in human embryonic kidney cells Coffee produces high level of H2O2 (Long & Halliwell, 2000; Muscat et al., 2007) Cyanidin-3-rutoside Cytotoxicity to HL60 cells H2O2 generation was involved to this observation (Feng et al., 2007) Epigallocatechin gallate Cytotoxicity on ovarian carcinoma cell lines H2O2 generation contributed to cytotoxicity (Chan et al., 2006) Epigallocatechin gallate Suppress hepatic gluconeogenesis Suppression via H2O2 was prevented by PEG-catalase (Collins et al., 2007) Gallic acid Cytotoxicity on testicular cell lines Cytotoxic effect of gallic acids on GC-1 spg cells was due to increasing H2O2 levels (Park et al., 2008) Grape seed Addition of grape seed on Caco-2 cells culture media generate H2O2 H2O2 generation was due to oxidation of phenolics in the media (Roques et al., 2002) Green tea polyphenol Green tea extract results in cytotoxicity and genotoxicity of RAW 264.7 cells H2O2 generation contributed to this observation (Elbling et al., 2005) Green tea & red wine polyphenol Induction of apoptosis in PC 12 cells Oxidation of green tea in cell culture media generate sufficient levels of H2O2 (Chai et al., 2003) Quercetin, catechin Cytotoxicity to pancreatic β-cells H2O2 generation in culture media was involved (Lapidot et al., 2002a) Resveratrol Activation of Nrf2 in astrocytes H2O2 generation in culture media contributed to cell signaling activation (Erlank et al., 2011) NF-κB: nuclear factor kappa B; Nrf2: nuclear factor-erythroid factor 2-related factor 2 10 1.3 Redox homeostasis 1.3.1 Overview on redox homeostasis & reactive oxygen species (ROS) functionality Redox, referring to an oxidation-reduction chemical reaction is achieved through a transfer of electrons between two species. In a redox reaction, one species undergoes reduction and gains electrons, while the other species undergoes oxidation and loses electrons. Under physiological conditions, electrophiles are defined as electron pair acceptors, whereas nucleophiles are defined as electron pair donors (Ursini et al., 2016). Generally speaking, ROS are considered as electrophiles and antioxidants are nucleophiles (Phaniendra et al., 2015; Ursini et al., 2016). Reactive oxygen species are radicals or non-radicals that contain reactive oxygen as a functional group, such as O2•-, H2O2, and •OH. Reactive oxygen species are produced as a consequence of normal oxygen metabolism via a variety of cellular oxidative processes that include metabolism of arachidonic acid by lipoxygenases and cyclooxygenases; activity of nicotinamide adenine dinucleotide phosphate (NADPH) oxidases, and xanthine oxidases, as well as mitochondrial electron transport chain of respiring cells (Cho et al., 2011). Endogenous sources of ROS involve metabolically active cellular mitochondria, peroxisomes and endoplasmic reticulum (Phaniendra et al., 2015; Snezhkina et al., 2019). Reactive oxygen species have an important role in both physiological function and pathological conditions with interactions that correlate with both redox biology and oxidative stress, respectively. Redox biology denotes a small increase in ROS levels that activate signaling pathways to initiate biological processes, while oxidative stress involves residing high levels of ROS that ultimately oxidize other molecules and trigger large chain chemical reactions within the body; the result being chemically altered deoxyribonucleic acid (DNA), protein and lipids 11 that lead to cellular dysfunction, and eventually cell death (Schieber & Chandel, 2014). Reactive oxygen species damage DNA by reacting with a nitrogenous base and sugar-phosphate backbone, leading to a break in single and double-stranded DNA, thus altering protein-coding region of DNA and resulting in mutation (Nita & Grzybowski, 2016; Whitaker et al., 2017). In evolution biology, it has been proposed that ROS is a critical signal transduction mechanism that governs adaption to changes in the host’s environment (Wood et al., 2003). In prokaryotes, ROS can interact directly with various signaling molecules that activate transcription factors associated with critical cellular processes that enable cells to adapt to stress; some examples being cell proliferation and survival, antioxidant gene regulation and immune function (Kiley & Storz, 2004; Nita & Grzybowski, 2016; Snezhkina et al., 2019). Oxidative eustress denotes physiological oxidative stress (Niki, 2016; Sarsour et al., 2014), where oxidative distress refers to an excessive load that causes oxidative damage (Aschbacher et al., 2013; Li & He, 2009; Lushchak, 2014; Ursini et al., 2016). Redox homeostasis refers to a balance in the regulation of ROS generating systems and antioxidant defense systems. Redox homeostasis is required to enable proper cellular functionality, allowing the body to optimally regulate redox sensitive pathways (Li et al., 2016b; Nita & Grzybowski, 2016) that are central for many metabolic and immune systems. The presence of excess ROS corresponds to a release in bioactive molecules that include cytokines which act to down-regulate endogenous ROS production and up-regulate endogenous antioxidant production; the result being to minimize ROS production. When redox homeostasis is disrupted by adverse environmental conditions, due to an excess of ROS or a deficiency of antioxidant or antioxidant activity to evoke an oxidative stress, a scenario whereby cellular ROS concentrations exceed antioxidant capacity occurs (Nita & Grzybowski, 2016; Ursini et al., 2016). As a consequence, a 12 number of susceptible deleterious reactions occur that lead to cellular damage of intracellular DNA, protein and lipids (Nita & Grzybowski, 2016). It is therefore critical to maintain redox homeostasis and a proper function of redox sensitive signaling proteins to regulate cellular ROS and antioxidant metabolism (Snezhkina et al., 2019). An internal and external redox homeostasis is a requirement for normal cells to function optimally, whereas blood metabolites are involved in enabling communication among cells (Corkey & Shirihai, 2012). 1.3.2 Shifts of redox homeostasis and oxidative stress Former studies have proposed that both oxidant and antioxidant signaling are main features that regulate redox homeostasis (Ursini et al., 2016). The concept of a “Golden Mean” was recently proposed whereby the best option to maintain an equilibrium was to have reactions going in opposite directions, rather than a single direction (Ursini et al., 2016); the idea being that an excess in either direction will disturb homeostasis. Under physiological conditions, different challenges push the cellular homeostasis toward the oxidative state and normally there is a required feedback reaction to redirect a push that will restore homeostasis back to the mean. However, when an oxidative stimulus persists, or the feedback response is not appropriate to respond to the stimulus, the situation will trigger a permanent alteration in cellular homeostasis (Ursini et al., 2016). This is a different concept to the original proposed notion of oxidative stress, which denoted a stable alteration of redox homeostasis (Cadenas & Sies, 1985). Recently, oxidative stress was defined as a condition where the boundary of the physiologic redox steady state is perturbed (Ursini et al., 2016). In contrast, a pathological state is established by three scenarios that involve : i) a permanent harmful challenge; ii) an inadequate response to injury; iii) and an inefficient nucleophilic feedback that results in stable displacement from the redox 13 baseline level (Ursini et al., 2016). Quantification of physiological redox homeostasis is a challenge for experimentation largely because of limitations in analytical techniques that can measure this parameter. Antioxidant compounds have been established as a group of compounds that could control the levels of ROS instead of having them removed completely, thus allowing useful functions while minimizing oxidative damage (Halliwell, 2008; Rhee, 2006; Thiele et al., 2001). 1.3.3 Intracellular/Extracellular redox state The intracellular redox state is dependent on the contribution of different redox reactions and works via electrons that exchange within each couple, thus representing important cofactors in redox enzymatic reactions. The ratio of reduced and oxidized form of each system denotes changes in the cellular redox state towards both an oxidizing, or reducing condition (Filomeni et al., 2002). Extracellular redox status has a critical role in maintaining protein stability and functional activity (Ottaviano et al., 2008). It is also a primary underlying cause for many chronic diseases attributed to adverse changes in the extracellular redox environment (Ashfaq et al., 2006) and related changes in intracellular signal transduction. Shifts in the extracellular state is connected with controlled intracellular signal transductions that are associated with many pathologies and disease states, including aging, diabetes and heart disease (Ashfaq et al., 2006; Imhoff & Hansen, 2009; Iyer et al., 2009; Jonas et al., 2000; Jones, 2006; Jones et al., 2002; Moriarty et al., 2003; Samiec et al., 1998). Lipid peroxidation and oxidative protein modification are two major consequences of oxidative stress that occur in the extracellular environment and result in altered cellular integrity and interrupted cell signaling (Ottaviano et al., 2008). For example, changes in 14 extracellular redox potential has been related to cell proliferation and apoptosis (Jonas et al., 2003; Jonas et al., 2002) since extracellular redox status can trigger oxidant induced apoptosis in mitochondria compartments and/or induce intracellular signal transduction (Jiang et al., 2005). 1.4 H2O2 as a signaling molecule 1.4.1 Role of H2O2 in redox cell signaling and oxidative stress Hydrogen peroxide is a major redox metabolite that is a product of normal metabolism in all mammalian cells (Sies & Chance, 1970) and acts as a component of second messenger for redox sensing, signaling and regulation (Di Marzo et al., 2018). Although it is a strong oxidant, H2O2 is unreactive with most biological molecules due to high activation energy barriers that include reactions involving thiol proteins, as well as reactions that include glutathione peroxidase and peroxiredoxin activities (Winterbourn, 2018). Regulation of H2O2 production is therefore important event for redox homeostasis (Ursini et al., 2016). Many studies have shown how the generation of H2O2 plays a critical role in intracellular signal transduction. Serving as a messenger molecule, H2O2 diffuses across the cell membrane via AQP channels to target sites and to initiate cellular effects, including changing cell shape, initiating proliferation and the recruitment of immune cells; the overall result is a metabolic response by cells to the original stimuli (Bienert et al., 2007; Sies, 2017). Maintaining the homeostasis between levels of extracellular and intracellular H2O2 is critical for cell metabolism and cell survival, whereas a level that is beyond homeostatic concentrations will result in inflammatory responses or growth arrest, even leading to cell death (Di Marzo et al., 2018; Sies, 2017). The homeostatic concentration of H2O2 is achieved by a balance between H2O2 formation and outcomes of antioxidant systems, both enzymatic and non- 15 enzymatic. Hydrogen peroxide is generated via one- or two- electron reactions, with NADPH oxidases and mitochondrial respiratory chain activity (Sies, 2017) which regulates production. In mammals, a major source of H2O2 production is derived from the dismutation of superoxide to water, catalyzed by the superoxide dismutase enzyme (SOD). Hydrogen peroxide is removed enzymatically by several enzymes, including catalase, glutathione peroxidases, and peroxiredoxin. Superoxide dismutase enzyme is located in mitochondrial, cytosolic and extracellular spaces, respectively. Catalase is mainly located in the peroxisomes, and the glutathione peroxidases, and peroxiredoxins are present in different cell compartments which ensure that an increase or accumulation of H2O2 in specific cell compartments does not occur (Di Marzo et al., 2018). Hydrogen peroxide could also be removed non-enzymatically by dietary sources of antioxidants, such as vitamin A, vitamin C, vitamin E, or glutathione (Kanta, 2011). In summary, the H2O2 equilibrium state is achieved by all contributing factors that occur continuously during complex biochemical transformations of physiological metabolism. Hydrogen peroxide also serves as a signalling molecule at low levels, with intracellular H2O2 concentration tightly regulated. Treatment of injured tissues by peroxidases and catalases has been used as a strategy to remove H2O2 when examining the biochemical roles of H2O2. The pathways involved in response to exogenous H2O2 were established in prokaryotes and yeast, while further elucidation of mechanisms was needed to clarify activity in animals and plants (Stone & Yang, 2006). Oxidation dependent steps have been shown to signal transduction pathways, and when H2O2 exposure is present at physiological concentrations, mammalian cells respond by triggering the activation of specific biochemical pathways (Stone & Yang, 2006). For example, H2O2 can modulate activity of transcription factors, such as active protein 1 (AP-1), Nrf2, NF-κB in mammalian cells (Marinho et al., 2014). 16 Cell signaling, triggered by H2O2 is a communication process that enables cells to perceive and to respond to oxidative stress occurring initially in the extracellular microenvironment, hence ensuring controlled tissue homeostasis (Kovacic & Pozos, 2006). Some examples of important cell signaling pathways are described below. NF-κB signaling pathway. NF-κB, is a redox-sensitive nuclear transcription factor and critical for the regulation of immune and inflammation responses, cell apoptosis and cell proliferation (Pasparakis et al., 2006; Perkins & Gilmore, 2006). The pathway is initiated by triggering genes that regulate the control of cell adhesion, programmed cell death, cell proliferation, inflammation, cellular stress response and tissue remodeling (Pasparakis et al., 2006; Perkins & Gilmore, 2006). These multiple gene expressions are coordinated with the activity of several cell signaling pathways (Wu et al., 2009). The NF-κB pathway can also be activated by a variety of stimuli, including bacteria and related products, environmental hazards, cytokines and oxidative stress (Siomek, 2012). Under conditions of quiescence, NF-κB is bound to a family of inhibitory proteins, referred to as NF-κB (I-κBs) inhibitors, which are retained in the cytoplasm as an inactive protein complex (Wu et al., 2009). Phosphorylation of I-κB by a I-κB kinase complex acts to activate the NF-κB, causing I-κB degradation through the ubiquitin-proteasome pathway. The released NF-κB will translocate into the nucleus and bind to promoters of target genes, which act to regulate anti-apoptotic genes, for example. This cell mechanism ensures NF-κB activation to favor cell survival (Wu et al., 2009). Reactive oxygen species have been recognized to modulate NF-κB activation, both in a positive and negative manner, respectively (Kabe et al., 2005; Siomek, 2012). Critical to this process is the duration in which the cell is exposed to oxidative stress. Wu and others (Wu et al., 2009) used the human lens cell epithelial as a cell model to demonstrate that exposure to ROS at 17 physiologically relevant levels will result in I-κB degradation and subsequent NF-κB activation. However, sustaining an oxidative stress to cells resulted in oxidative inactivation of the proteasome, thereby attenuating I-κB degradation and subsequent activation of NF-κB. In summary, the NF-κB pathway can be activated at low level of oxidative stress, whereas inhibition also occurs at higher levels due to the inactivation of proteasome (Wu et al., 2009). As impairment of the NF-κB signaling pathway can contribute to cell death, maintaining ROS levels at a physiologically relevant level is critical for cell survival. Under certain conditions, H2O2 directly activates NF-κB through phosphorylation of IκB and is therefore a key mechanism to regulate adaptive immunity (Oliveira-Marques et al., 2009). Recent studies have suggested that H2O2 comprises both a pro-inflammatory control loop that activates the adaptive immune system, and an anti-inflammatory control loop that is important to inhibit harmful immune response (Oliveira-Marques et al., 2009). Nrf2 signaling pathway. The Kelch-like ECH-associated protein 1 (Keap1)-Nrf2-antioxidant response elements (ARE) pathway is a critically important cell signaling pathway required to protecting cells from oxidative stress (Kensler et al., 2007). Under normal conditions, the transcription factor, Nrf2, is bound to the actin-anchored protein, Keap1 and this interaction retains the Nrf2 in the cytoplasm, which in turn maintains a low basal expression of Nrf2-regulated genes (Kensler et al., 2007). Human Keap1 has 27 cysteine residues, and several are known to be primary sensors for stress signals. Modification of critical cysteine residues by oxidative stressors cause conformational changes in Keap1, which in turn liberates Nrf2 from the Nrf2-Keap 1 complex. Following release from the Keap1 complex, the Nrf2 translocates to the nucleus and activates the expression of cytoprotective genes required to trigger antioxidant enzyme synthesis needed to remove the potential stressor and to protect for cell survival (Kensler 18 et al., 2007). Hydrogen peroxide mediated oxidation of cysteine residues within proteins that trigger redox signaling is well known (Schieber & Chandel, 2014). Cysteine residues are modified upon recognition of chemical signals evoked by the presence of oxidative and electrophilic molecules. At physiological pH, cysteine residues are present in the form of thiolate anions (Cys-S-), which are susceptible to oxidation relative to the corresponding protonated cysteine thiol (Cys-SH) (Finkel, 2012). For example, during redox signaling, H2O2 oxidizes the Cys-S- to the sulfenic form (Cys-SOH), which subsequently results in allosteric changes within the protein, thereby altering protein function. The Cys-SOH can be reduced to Cys-S- by the disulfide reductases thioredoxin and glutaredoxin, respectively, to return the protein function to an original state (Winterbourn & Hampton, 2008). Thus, first-degree oxidation of cysteine residues to Cys-S- within proteins is considered to be an important reversible signal transduction mechanism (Schieber & Chandel, 2014). The thiolate oxidation in living cells takes place in nanomolar ranges of H2O2, with relatively high levels of H2O2 capable of further oxidizing thiolate anions to sulfinic (SO2H), or sulfonic (SO3H) species. In contrast to sulfenic modifications, both sulfinic and sulfonic modifications are irreversible and can result in permanent protein damage. The enzymes that are upregulated in the cell to overcome the build-up of intracellular H2O2 are the peroxiredoxins and glutathione peroxidases (Schieber & Chandel, 2014). Studies have established the role of natural polyphenols as activators for Keap1-Nrf2 signaling pathway (Zhou et al., 2019). The mechanism includes inhibition of ROS production, inhibition of Keap1-Nrf2 protein-protein interaction, as well as degradation of Keap1 in the Nrf2 pathway (Zhou et al., 2019). 19 1.4.2 Methodologies, old and new, used to measure cellular H2O2 status in situ Hydrogen peroxide and O2•- are the most widely studied sources of ROS because they are produced specifically, or as metabolic products of several enzymes with well-known biological effects to ensure cell homeostasis (Bilan et al., 2013). In order to characterize the cellular function of H2O2, it is important to develop specific methods that enable measuring concentrations in cells in the presence of other oxygen metabolites. Current methods that are used to measure H2O2, specifically, include a colorimetric assay, based on horse-radish peroxidases and artificial substrates, and a ferrous oxidation assay (FOX) that reacts in the presence of xylenol orange (Héritier et al., 2016; Li et al., 2016a; Long et al., 2000; Roques et al., 2002). There are also more sophisticated methods that include, flow cytometrics (Ubezio & Civoli, 1994), electrochemical methods (Bozem et al., 2018; Liu et al., 2019a; Sun et al., 2017), a genetically modified sensor (Panieri et al., 2017) and a flow cytometric HyPer-based assay (Lyublinskaya et al., 2018). Horse-radish peroxidases and artificial substrates (i.e. Amplex Red and 3,5,3’5’-tetramethylbenzidine), or the FOX method have been widely used for determination of H2O2 in biological fluids. Methods used to measure intracellular H2O2, are based on dihydro compounds, such as 2’,7’ -dichlorodihydrofluorescein diacetate (DCFH-DA), which is widely used due to its sensitivity and simplicity (Rhee et al., 2010). However, these methods are limited due to poor specificity since the chemical probes also react with a variety of cellular oxidants, including nitric oxide, hypochloride and peroxynitrite, in addition to H2O2. To overcome this severe limitation in quantifying cellular redox, advances in using genetically encoded redox sensitive fluorescent probes that are based on fluorescent proteins have been made. Important criteria, such as oxidant specificity, reversibility of the reaction, and intracellular targeting must be 20 accounted for (Kaludercic et al., 2014). Moreover, these redox sensitive fluorescent probes have a high redox species specificity and can be targeted intracellularly. In addition, the oxidation reaction is reversible, therefore this approach has achieved the goal of being a dynamic real-time measurement of H2O2 (Kaludercic et al., 2014). Figure 1.2 Schematic of HyPer-3, a genetically encoded fluorescent, H2O2 sensitive indicator. HyPer, refers to a genetically encoded fluorescent, H2O2 sensitive, indicator that was developed to measure intracellular H2O2 and to enable fluorescent lifetime imaging of H2O2 levels. It was developed by integrating the circularly permuted yellow fluorescent protein (cpYFP) inside the regulatory domain of an Escherichia coli H2O2 sensitive protein, OxyR (Belousov et al., 2006; Choi et al., 2001). Minimal concentrations of H2O2 that induce detectable changes in HyPer fluorescence have been reported to be 25 nM for the isolated probe, and fall in a range from 5-25 µM for HyPer in eukaryotic cytoplasm. HyPer has an advantage since it allows for monitoring the reversibility of redox reactions induced by reduction of cellular thiol-reducing systems. In comparison to HyPer, another version, HyPer-3 possesses an expanded dynamic range and a higher brightness upon expression in cells, without compromising both oxidation and reduction rates (Bilan et al., 2013; Markvicheva et al., 2011), schematic shown in + H2O2- H2O2Higher ratio of488/405 nmLower ratio of488/405 nm 21 Figure 1.2. This feature adds to the high resolution and accuracy provided by this methodology to measure intercellular H2O2 concentrations. 1.4.3 Aquaporin facilitated transmembrane diffusion of H2O2 1.4.3.1 Localization & expression of AQPs in intestine Bio-membranes are permeable to H2O2 and this quality helps maintain the intracellular and extracellular H2O2 balance (Antunes & Cadenas, 2000; Marinho et al., 2013b; Oliveira-Marques et al., 2013; Seaver & Imlay, 2001). Moreover, the permeability of the plasma membrane is also regulated by H2O2 exposure (Branco et al., 2004; Folmer et al., 2008; Pedroso et al., 2009). Aquaporins have a critical role in regulation of H2O2 transportation across biomembranes and thus are important in mediating intracellular H2O2 signalling (Bienert & Chaumont, 2014; Miller et al., 2010). Aquaporin facilitated H2O2 diffusion has been recognized to have physiological significance towards adjusting membrane permeability to H2O2 (Bienert & Chaumont, 2014). Physicochemical and experimental evidence has shown that AQPs are involved in the transportation of H2O2 and the subsequent transmission of transmembrane redox signaling processes. Passive diffusion of H2O2 across biological membranes requires specific AQP isoforms and specific roles of AQPs on H2O2 diffusion across membranes has been studied in mammalian cells (Bertolotti et al., 2013; Bienert et al., 2007; Ghouleh et al., 2013; Hara-Chikuma et al., 2012; Marchissio et al., 2012; Miller et al., 2010). Several AQPs that are documented to be involved in transmembrane diffusion of H2O2, include AQP1 (Ghouleh et al., 2013), AQP3 (Hara-Chikuma et al., 2012) and AQP8 (Bertolotti et al., 2013). Generally, AQP1, AQP3, AQP7 and AQP11 are widely found in the small intestine, and AQP1, AQP3, AQP7, and 22 AQP8 are abundantly expressed in the colon (Camilleri et al., 2019; Ricanek et al., 2015; Xiang et al., 2018; Zhang et al., 2017; Zhu et al., 2016). 1.4.3.2 Functionality of AQPs in the intestine The functionality of AQPs has been attributed to specific structures, called an aromatic/arginine selectivity filter, which selectively filters water and solutes (Verkman et al., 2014; Wang et al., 2021). The two-conserved asparagine-proline-alanine motifs allow the passage of charged ions via the pores to be controlled (Aikman et al., 2018; de Almeida et al., 2017; Kitchen et al., 2019). Initial theories suggested that H2O2 cross membranes freely by passive, non-protein-facilitated diffusion. This idea was not accepted due to the fact that there exists a H2O2 gradient across membranes of many different mammalian cell lines (Antunes & Cadenas, 2000; Makino et al., 2004), thus pointing to a more accepted view point that AQPs have critical roles on the active regulation of H2O2 transportation. To meet the physiological demands of sufficient fast fluxes, AQPs act to facilitate the transmembrane diffusion of water, which is unlikely achieved by a non-facilitated, free diffusion across biological membranes (Bienert & Chaumont, 2014). Although H2O2 and water share similar physicochemical features, the diffusion of H2O2 is relatively more difficult than water, therefore requiring a more active regulation towards permeability of H2O2 across the membrane. In addition to important functions to ensure water homeostasis, AQPs also have critical roles in the downstream signaling events that occur after mediating transmembrane transport of H2O2, another particularly physiologically important feature (Hara-Chikuma et al., 2015; Satooka & Hara-Chikuma, 2016). As mentioned, normal functioning of AQPs are critical to regulate the passive absorption and secretion of intestinal water, often termed “solvent drag”, a process that carries low 23 molecular weight soluble substrates and maintains the balance between intestinal fluid movement and intestinal bioavailability of many important nutrients (Fischbarg, 2010). As such, abnormal expression of AQPs has been connected with intestinal disease (Ikarashi et al., 2016). In addition to solvent transport, AQPs also participate in mechanisms that involve cellular proliferation, maintenance of cytoskeletal structure, cell permeability and protection of intestinal barrier, as shown in Figure 3.1 (Marchbank & Playford, 2018; Pimpão et al., 2020; Thiagarajah et al., 2007; Zhu et al., 2019). The role of AQPs in cell proliferation was attributed to a capacity to regulate the concentration of glycerol and adenosine triphosphate (ATP) biosynthesis (Thiagarajah et al., 2007). In addition, alteration of expression of intestinal AQP3 produces changes in cell membrane fluidity, that affect drug and nutrient permeability and absorption (Ikarashi et al., 2019). Studies have shown that the knockdown of AQP3 will influence intestinal barrier integrity and lower expression of enterocyte tight junction such as Claudin-1 and Occludin. Thus, there is strong evidence that AQP3 knockdown cells, are involved in paracellular permeability via expression of a tight junction protein complex (Edamana et al., 2021; Zhang et al., 2011). Furthermore, using the Caco-2 cell model and epithelial colonoids, respectively, AQP3 was shown to have H2O2-dependent responses to environmental stress (Thiagarajah et al., 2017). Aquaporins also have important roles in regulating the intestinal mucosal immune response. Specifically, AQPs interact with macrophages to mediate innate immune responses (Jablonski et al., 2004; Li et al., 2019; Tyteca et al., 2015; Yu et al., 2018) in ways that include migration and proliferation of immune cells and formation of macrophage phagosomes (Figure 1.3) (Hara-Chikuma et al., 2012; Holm et al., 2015; Holm et al., 2016; Song et al., 2011; Thiagarajah et al., 2017; Tyteca et al., 2015; Xiang et al., 2018; Zhu et al., 2011). 24 Aquaporins facilitate transportation of extracellular H2O2 through cell membranes and are involved with downstream signaling cascades (Miller et al., 2010; Vieceli Dalla Sega et al., 2014). The redox dependent signaling is likely dependent on the signal transduction pathways that are initiated at the binding of membrane receptors to corresponding ligands (Lennicke et al., 2015; Lorenzen et al., 2017). Figure 1.3 A scheme showing the functionality of aquaporins. (A) Aquaporins involved in cytoskeletal structure by altering cell volume caused by abnormal Na+/K+ flux. (B) Aquaporins involved in regulation of intestinal barrier function. (C) Aquaporins involved in cell signaling and subsequent immune response. (D) Aquaporins involved in epithelial cell migration. (E) Aquaporins involved in cell proliferation caused by AQP3 facilitated glycerol entrance. 1.4.3.3 Dysregulation of AQPs and intestinal diseases Aquaporins are widely present and expressed in different mammalian tissues and cells, including absorptive and secretory epithelial cells that have important physiological or 25 pathophysiological roles (Hachez & Chaumont, 2010). Up- or down- expression of AQPs are linked to intestinal disorders, such as constipation (Gan et al., 2019; Ikarashi et al., 2016) and diarrhea (Engevik et al., 2018; Guttman et al., 2007; Hui et al., 2018; Kassa et al., 2019; Rosa et al., 2018; Sakai et al., 2013; Zhuang et al., 2019), respectively. A human clinical trial reported that AQP expression is involved in inflammatory bowel disease pathophysiology, (Table 1.3) (Dong et al., 2020; Meli et al., 2018; Ricanek et al., 2015; Sisto et al., 2019). Table 1.3 Alteration of aquaporins expression under various pathological conditions. Intestinal disease Model Aquaporin expression Expression determination References Escherichia coli induced diarrhea Mice AQP3 decreases mRNA & protein (Zhang et al., 2017) Escherichia coli induced diarrhea Piglets AQP3, 11 decreases Protein (Zhu et al., 2017) Antibiotic associated diarrhea Rat AQP3, 4, 8 decreases mRNA (Zhang et al., 2018) Bile acid induced diarrhea Rat AQP3, 7, 8 decreases mRNA (Yde et al., 2016) Irritable bowel syndrome Rat AQP1, 3, 8 decreases mRNA (Chao & Zhang, 2018) Constipation Mice AQP3 increases Protein (Sun et al., 2018) DSS induced colitis1 Murine AQP4, 8 decreases mRNA & protein (Hardin et al., 2004) TNBS induced colitis2 Rat AQP3, 8 decreases mRNA & protein (Zhao et al., 2014) Crohn’s diseases Human AQP1, 3 decreases mRNA & protein (Ricanek et al., 2015) Ulcerative colitis Human AQP7, 8 decreases mRNA & protein (Ricanek et al., 2015) Collagenous colitis Human AQP8 decreases mRNA & protein (Escudero-Hernández, et al., 2020) 1DSS: dextran sulfate sodium; 2TNBS: 2,4,6-trinitrobenzene sulfonic acid. 26 1.4.3.4 Aquaporins and dietary nutrients As mentioned, AQPs are important to maintain intestinal function and prevent certain disorders, such as diarrhea (Gan et al., 2020; Huang et al., 2015; Ikarashi et al., 2011; Lv et al., 2021; Tesse et al., 2018). Under normal conditions, the large volume of water secreted in the small intestinal lumen is eventually absorbed before reaching the large intestine; however, laxatives that function to reduce water transport also reduce the expression of AQP3 in the colon (Ikarashi, 2011). The capacity of carbachol and genistein, respectively, to restore fluid absorption in the treatment of diarrhea is associated with an increased expression of AQP1 and AQP4 (Huang et al., 2015). In recent years, AQPs are regarded as cell targets for interaction with dietary bioactive phytochemicals (Tesse et al., 2018). The role of AQPs on osmotic water diffusion under conditions of oxidative stress and when in the presence of antioxidant compounds has been shown in Hela cells (Pellavio et al., 2017). Plant phenolics, such as naringenin, increase expression of AQP3 in the colon at messenger ribonucleic acid (mRNA) and protein levels in apical and lateral mucosal epithelial cells, respectively (Yin et al., 2018). Quercetin is another example of polyphenolic modulation of intestinal water transport, namely by preventing loss of water permeability in the mucosa and triggering expression of AQP3 and AQP8 at mRNA and protein levels (Pellavio et al., 2017). Polyphenolic compounds regulate AQP expression by multiple mechanisms that involve signaling of cyclic adenosine monophosphate (cAMP)/ Protein kinase A (PKA)/cAMP-responsive element binding protein (CREB) signal transduction pathway, NF-κB pathway, and mitogen-activated protein kinase (MAPK) signalling pathway (Dong et al., 2020; Huang et al., 2015; Zhang et al., 2020). Thus, regulation of AQPs by specific antioxidant compounds could be a novel mechanism that controls cell signaling pathways and enables cell 27 survival during stress (Tamma et al., 2018). In addition, H2O2 can mediate the interaction between polyphenolic compounds and AQPs. Polyphenols that produce H2O2 in endothelial cells membranes explain the observed regulation of intestinal oxidation resistance (Kanner, 2020; Pellavio et al., 2017; Tamma et al., 2018). The anti-inflammatory action of phloretin is a good example, with its specific capacity to inhibit AQP9 (Matsushima et al., 2014). 1.5 Cell models used to study intestinal inflammation 1.5.1 Macrophage RAW 264.7 cell model Macrophage possess critically important functional capabilities in the innate immune system. They act as sentinels of the immune system to respond to acute physiological changes, as well as continuous chronic insults derived from external sources. They are also involved in diverse activities that include organ development and maintenance of immune homeostasis which includes tissue repair and capacity to phagocytize apoptotic cells and an immune response to pathogen invasion (Wynn et al., 2013). Chronic insults to the body subvert reparative and homeostatic functions of macrophage; this explains some of the causal associations between compromised macrophage function and chronic disease states (Wynn et al., 2013). Macrophage, therefore have important roles to regulate both normal physiology and development, as well as to ward off pathophysiologic changes associated with chronic disease states. Macrophages with different phenotypes are recruited internally from monocyte reservoirs of blood, bone marrow, spleen, resident tissue progenitors, as well as de novo local proliferation, during an adaption process (Perdiguero et al., 2012). It is important to understand the hallmark of macrophage function, since there is an emerging application to employ macrophages that are aimed as therapeutic targets in many important human diseases (Ponzoni et al., 2018). Much research has 28 been directed to study whether macrophages can shift from a programed functional state to new set-points, as a consequence of changes in tissue physiology brought on to adapt to environmental stresses that require a return to homeostasis (Wynn et al., 2013). The RAW 264.7 cell is a macrophage-murine cell line that was transfected with an Abelson murine leukemia virus (Hartley et al., 2008). It is widely used in toxicology to evaluate the effectiveness of bioactivity of natural products to measure induced biochemical changes on primary cells that can be related to a de novo response (Galvez-Llompart et al., 2013). The inflamed RAW 264.7 cell model has been widely used for the purpose of investigating the anti-inflammatory potential of bioactive compounds (Bognar et al., 2013; Pan et al., 2008). Inflammation is a biological response derived from host exposed to harmful stimuli, thus acting as a host protective mechanism for defense against harmful external stimuli (Chen et al., 2018). Lipopolysaccharides (LPS), a prototypical endotoxin, has been used widely to directly activate macrophages (Berghaus et al., 2010) that respond by increasing inflammatory cytokine production, such as interleukin 6 (IL-6), tumor necrosis factor α (TNF-α), and other inflammatory mediators, such as nitric oxide, and peroxynitrite (Lawrence et al., 2002). The transcription factor NF-κB, is important in regulating immune and inflammatory responses and has an important role in the transcription of multiple inflammatory cytokines and other mediators (Ghosh et al., 1998). When NF-κB is activated, it translocates to the nucleus and induces the transcription of pro-inflammatory cytokine gene. Thereby, the inhibition of NF-κB is recognized to be a potential therapeutic treatment in curing inflammatory diseases (Ghosh et al., 1998). Nitric oxide is another bioactive molecule that has been used to investigate inflammatory responses (Avdagić et al., 2013). Transcription of inducible nitric oxide synthase (iNOS) is the major regulatory scheme for nitric oxide production (Förstermann & Sessa, 2012). Nitric oxide 29 production has been used as a biomarker to evaluate anti-inflammatory activity by a wide range of dietary components (Bognar et al., 2013; Chen et al., 2019; Pan et al., 2008). Peroxynitrite, a short-lived reactive nitrogen specie (RNS), produced by a diffusion controlled reaction between nitric oxide and superoxide radical is involved in induction of cell death, signal transduction processes, mitochondrial function and signaling of apoptosis (Szabó et al., 2007). Cytokines refer to a category of small molecular weight proteins (~5-20 kDa), including chemokines, interferons, interleukins, lymphokines and tumor necrosis factors; all of which have important roles in cell signaling as immunomodulating agents. Cytokines are produced by a broad range of cells, including immune cells, endothelial cells, fibroblasts and various stromal cells. They have significant roles in health and disease, and are established as biomarkers of inflammatory bowel diseases (Bevivino & Monteleone, 2018; Choghakhori et al., 2017; Gou et al., 2021; Knutson et al., 2013; Korolkova et al., 2015). Specifically, cytokine crosstalk has a critical role in cell-to-cell communication (Andrews et al., 2018; Meier-Schellersheim et al., 2019). Nrf2 cell signaling suppresses cytokine signaling by targeting macrophage generated ROS (Kim et al., 2020). 1.5.2 Caco-2 cell model The Caco-2 cell line is derived from a human colon adenocarcinoma cells (Sambuy et al., 2005). Non-differentiated Caco-2 cells are therefore cancer cells that are used to show efficacy of bioactive compounds to inhibit cancer cell proliferation, as well as induction of apoptosis signaling (Cilla et al., 2015; Esghaei et al., 2018; Han et al., 2016; Huang et al., 2007; Iwuchukwu et al., 2011). 30 Culturing non-differentiated Caco-2 cells for up to 21 days results in cell differentiation and formation of a monolayer of cells that express morphological and functional characteristics which mimics the mature enterocyte with an intact brush border analogous to the small intestine (Sambuy et al., 2005). Culturing Caco-2 cells on permeable filter inserts has been used extensively in the laboratory to examine the biochemical consequences of an oxidant induced loss of epithelial barrier function (Peng et al., 2007). In addition, Caco-2 cell monolayers are widely used to study nutrient or drug transportation properties across the intestinal mucosa (Cheng et al., 2008; Meunier et al., 1995; Sun et al., 2008). There are many formats where Caco-2 cells are used to study factors triggering, or mitigating intestinal inflammation (Hollebeeck et al., 2011; 2012; Kasper et al., 2016; Kuntz et al., 2009). In particular, defining the role of specific nutrients or food bioactives to protect against inflammation has been an active area of investigation in food toxicology. 1.5.2.1 Intestinal cellular integrity Intestinal epithelial cells form a continuous layer along the intestine that allows nutrient absorption, in addition to also having a very important function that includes acting as a key defense barrier to toxin exposure (Wan et al., 2019). When the intestinal epithelial barrier function is compromised, increased probability of translocation of bacteria, toxins and allergens occur (Wan et al., 2019). Transepithelial electrical resistance (TEER) is a widely accepted quantitative technique that measures the integrity of tight junction in epithelial monolayers (Srinivasan et al., 2015). The intestinal tight junctions regulate the passage of low molecular weight compounds (e.g., nutrients and toxins) via a paracellular pathway (Groschwitz & Hogan, 2009). Tight junctions act to seal adjacent epithelial cells and thus creating the selective 31 permeability for passive nutrient absorption. Some important protein components of tight junction include: Occludin, Claudin, and the Zonula Occludens (Lee, 2015). Destabilization of the protein complex results in the nonselective entry of extracellular molecules, while also contributing to a leakage phenomenon that disrupts the nutrient flux in the small intestine (Odenwald & Turner, 2017). Increased production of inflammatory mediators such as cytokines and ROS disrupt the epithelial barrier function by destabilizing tight junctions (Rao, 2008). Oxidative stress induced by various ROS such as superoxide, nitric oxide, and peroxynitrite disrupt epithelial tight junctions, by modifying proteins through thiol oxidation, protein phosphorylation, nitration and carbonylation (Rao, 2008). During the course of inflammation, a series of cytokines, that include interferon gamma (IFN-γ), TNF-α, and interleukins are produced, and cytokines such as IFN-γ and TNF-α have the capacity to downregulate the expression of tight junction proteins (Bruewer et al., 2005; Ciccocioppo et al., 2006; Mankertz et al., 2000; Prasad et al., 2005). It is important to recognize that polyphenolic compounds, in general, have a role to protect epithelial barrier function against oxidative stress by scavenging ROS (Ruan et al., 2014). In addition to free radical scavenging activity against ROS, polyphenolic compounds also protect epithelial barrier function by mitigating expression of pro-inflammatory cytokines, such as TNF-α, interleukin 1 beta (IL-1β) and interleukin 8 (IL-8); the capacity varies between individual polyphenolic compounds due to chemical structural differences (Hwang et al., 2014). In addition, polyphenolic compounds have been shown protecting the epithelial barrier function via activation of cell signaling, such as Nrf2 cell signaling which is involved in maintaining epithelial barrier function (Wen et al., 2019). 32 1.5.2.2 IL-8 Interleukin-8 is an inflammatory cytokine, and previous studies have shown that IL-8 synthesis in Caco-2 cells is upregulated by different noxious stimuli that include invading pathogenic bacteria, foreign chemicals, and oxidative stress (Németh et al., 2007). Dysregulation of inflammatory cytokines leads to serious cell damage (Németh et al., 2007). Oxidative stress, triggered by production of ROS, such as H2O2 promotes IL-8 in several cell types (Lakshminarayanan et al., 1998; Shimizu et al., 2015; Xiao et al., 2020; Yamamoto et al., 2003). IL-8 gene expression in intestinal cells is also regulated by NF-κB cell signaling. 1.5.3 Co-culture cell model In a co-culture model, the Caco-2 cell line was seeded onto the apical layer of the insert and cultured to establish differentiated monolayers of absorptive enterocytes with structural and functional properties similar to the human small intestine epithelial cells (Peng et al., 2007). These properties are beneficial for evaluating the changes in expression of the proteins regulating intestinal barrier integrity and permeability (Hidalgo et al., 1989). RAW 264.7 cells, or macrophage were chosen as the cell to co-culture with Caco-2 cells and these were applied to the basolateral layer of the insert, which allowed them to be adaptive to new environmental changes and stimuli (Sica & Mantovani, 2012). RAW 264.7 cells are advantageous in examining immune system interactions that result from induced inflammation and production of cytokines and other bioactive agents such as nitric oxide (Ferret et al., 2002). The use of a co-culture model, defined as having more than one cell type, has been used to examine how inflammation can influence intestinal epithelial cell functionality (Kämpfer et al., 2017; Tanoue et al., 2008) and gut health (Kim et al., 2021; Kim & Kim, 2019; Nielsen et al., 33 2017). To ensure that both cell lines are functioning to a maximum capacity, a few biomarkers are often selected to evaluate the stable co-culture systems; these being TEER, cell viability, and cytokine production (Kämpfer et al., 2017). 34 1.6 Hypotheses and objectives Overall research hypothesis The overall research hypothesis of my thesis is that phenolic acids, commonly found in the diet, have distinct structure-specific capacity to regulate cellular redox and cell signaling through extracellular/intracellular changes that involve H2O2 production and influx activity. Experiment 1. Hypothesis Different types of dietary phenolic acids that vary in stability and capacity to generate H2O2 in culture media account for changes in cell proliferation related responses associated with cell viability in non-differentiated Caco-2 cells. Objective 1. To compare the rate and extent of different phenolic acids to produce H2O2 from pro-oxidation reactions when cultured under standard conditions in complete culture media without cells. 2. To demonstrate that the H2O2 generated by phenolic acids in cell culture media due to pro-oxidation contributes to changes in non-differentiated Caco-2 cell viability and related biomarkers that signal cell proliferation. 35 Experiment 2. Hypothesis Different types of dietary phenolic acids that vary in capacity to generate H2O2 in differentiated Caco-2 cells correspond to changes in intracellular H2O2 influx and subsequent signaling activation that can be explained by AQP receptor activity. Objective 1. To use a novel, genetically encoded fluorescent H2O2 sensitive indicator called HyPer-3 that will enable monitoring changes in intracellular H2O2. 2. To demonstrate how H2O2 generated from phenolic acids in cell culture media that alter intracellular H2O2 levels contributes to the activation of intracellular Nrf2 cell signaling. 36 Experiment 3. Hypothesis The relative capacity of different phenolic acids to alter redox status in inflamed RAW 264.7 cells will correspond to protected Caco-2 cell functionality; demonstrated by using a Caco-2/RAW 264.7 co-culture model. Objectives 1. To establish a stable co-culture Caco-2/RAW 264.7 model that will enable differentiating how phenolic acids mitigate an inflammatory intestinal response. 2. To assess the bioactive effects attributed to different phenolic acid types in Objective 1 using a collection of relevant pro-inflammatory biomarkers in the co-culture Caco-2/RAW model. 3. To expand and correlate the results obtained in Objective 2 with protected Caco-2 cell functionality, including changes in Caco-2 monolayer integrity, cytokine production, and Nrf2 cell signalling. 37 Chapter 2: Autoxidation of selective phenolic acids in cell culture have varying effects on non-differentiated Caco-2 intestinal cell proliferation parameters 2.1 Introduction Diet derived polyphenolic compounds are typically sourced from cereals, fruits and vegetables, and also beverages, that include coffee, tea and wine; thus contributing to a surprisingly high intake of approximately 1 gram daily (Scalbert & Williamson, 2000). Epidemiological studies have shown that human consumption of beverages rich in phenolic acids result in a wide range of bioactive properties that include antioxidant, anti-inflammatory, antimicrobial, and anti-allergenic effects (Carrieri et al., 2013; Chen et al., 2019; Daleprane et al., 2012; Kumar & Goel, 2019; Pernin et al., 2019). In this study, four specific phenolic acids, namely, caffeic acid, chlorogenic acid, ferulic acid, and gallic acid, respectively, were selected for structural differences and then examined for possible characteristic physicochemical parameters that resulted in characteristic hydrogen peroxide (H2O2) production and subsequent autoxidation and related biological properties in both cell-free and cell-based systems. In vitro studies have shown that structural properties of different phenolic acids explain mostly the antioxidant activity observed to scavenging reactive oxygen species (ROS), such as superoxide anion and hydroxyl radical (Rice-Evans et al., 1995). The antioxidant activity of specific phenolic acids has been ascribed to a relative affinity to overcome radical attack by a hydrogen-atom abstraction from phenolic OH groups (Quideau et al., 2011; RiceEvans, Miller, & Paganga, 1996). Several studies have evaluated the production of H2O2 in different food systems from redox active phenolic compounds present in coffee and tea made available for 38 consumption (Akagawa et al., 2003; Bellion et al., 2009; Bopitiya et al., 2021; Chai et al., 2003; Long et al., 1999). However, this physicochemical property of phenolic acids is often underreported when evaluating multiple biological functions of phenolics that include apoptosis and inhibition of cell proliferation (Kanner, 2020). The aim of this study was to examine the capacity of four common phenolic acids, widely consumed in the Western diet, but possessing structural differences that result in variable H2O2 production during culture, on changes in proliferation of non-differentiated human intestinal carcinoma (Caco-2 cells). To achieve this objective, initial experiments were performed to compare the capacity of different phenolic acids to autoxidize in culture media without cells during typical incubation time periods. 2.2 Materials and methods 2.2.1 Materials The following chemicals were purchased from Sigma (St. Louis, MO, USA): caffeic acid (CA) (≥98% pure), chlorogenic acid (CGA) (≥98% pure), ferulic acid (FA) (≥99% pure) and gallic acid (GA) (≥99% pure). Dulbecco's Modified Eagle's Medium (DMEM), phosphate buffered saline (PBS), penicillin/streptomycin antibiotics, formic acid, methanol, ethanol, 3-(4,5-diethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), sodium dodecyl sulfate (SDS), and 4′,6-diamidino-2-phenylindole (DAPI). Fetal bovine serum (FBS) was purchased from Gibco® (Grand Island, NY, USA). Catalase, H2O2 standard and Hydrogen Peroxide Assay Kit were purchased from Cayman Chemical Company (Ann Arbor, MI, USA). Bromodeoxyuridine (BrdU) Cell Proliferation Enzyme-Linked ImmunoSorbent Assay (ELISA) Kit (colorimetric) and Apoptosis/Necrosis Assay Kit (blue, green, red) was purchased from Abcam company 39 (Abcam, Cambridge, UK). Caco-2 cells were purchased from American Type Culture Collection (Manassas, VA, USA). 2.2.2 Phenolic acids and culture conditions CA, CGA, FA and GA were first dissolved in methanol and diluted to final working concentrations of 0.01 mM, 0.1 mM, and 1 mM, respectively, in DMEM media (containing 100 U/ml of penicillin and 100 ng/mL of streptomycin (Sigma, St. Louis, MO, USA). Phenolic acids were incubated at 37oC under a 5% CO2 atmosphere and sampled from culture media at various times up to 24 hr incubation. 2.2.3 Quantification of phenolic acids using high performance chromatography (HPLC) Phenolic acids were quantified in cell-free DMEM culture media by HPLC according to previous studies (Ozturk, Tuncel, & Tuncel, 2007), with minor modifications using an Agilent 1100 (Agilent Technologies Inc., Palo Alto, CA, USA) (Ozturk et al., 2007) equipped with quaternary pumps, inline degasser, auto sampler and a diode array detector at 280 nm. Phenolic acids were separated on a Zorbax C-18 column (150 mm * 4.6 mm, 3.5 µm particle size, Agilent, USA), maintained at 30oC and detected at 280 nm. Mobile phases were: A: (methanol with 1 % of formic acid) and B: (water with 1 % of formic acid), respectively, programed to deliver a gradient of 10/90 of A/B-100/0 B for 0-10 min, programed to run at a flow rate of 1 mL/min. Peak identification of phenolic acids was performed by matching retention time of unknown phenolic acid to external phenolic acid standards and quantified from standard curve. Complete DMEM media without phenolic acids was the blank. All sample analysis was performed in triplicate. 40 2.2.4 Production of H2O2 by phenolic compounds in cell free media The first experiments measured the generation of H2O2, from four different phenolic acids, namely CA, CGA, FA and GA, respectively, in cell-free DMEM culture media at concentrations of 0.01 mM, 0.1 mM and 1 mM, respectively, as an index of autoxidation. Phenolic acid samples were incubated at 37oC under a 5% CO2 atmosphere, and collected continuously from the media at regular intervals for up to 24 hr. Hydrogen peroxide was measured using a Hydrogen Peroxide Assay Kit (Item No. 600050, Cayman Chemical Company, Ann Arbor, MI, USA) using a fluorimeter (Ex, 530-560 nm and Em, 590 nm). A standard curve constructed to quantify H2O2 concentration was linear (R2 ≥0.99) over a range of 0 µM to 10 µM. Final concentration of H2O2 generated from phenolic acids was corrected residual H2O2 present in the culture media prior to adding the test phenolics. In separate studies, catalase was added to the culture media to confirm generation of H2O2 production after 24 hr incubation from different phenolic acids tested. 2.2.5 Cell culture Caco-2 cells (HTB-37, American Type Culture Collection, Manassas, VA, USA) were cultured in DMEM media, supplemented with 10% FBS (Gibco®, Grand Island, NY, USA), 100 U/ml of penicillin and 100 µg/mL of streptomycin (Sigma, St. Louis, MO, USA), at 37oC under a 5% CO2 atmosphere. Culture media was changed every 2-3 days and sub-cultured weekly. 2.2.6 Cell cytotoxicity assay The cytotoxicity of four phenolic acids cultured in presence of non-differentiated Caco-2 cells was evaluated using the MTT assay, as described in previous studies (Chen & Kitts, 2008). 41 Briefly, samples were incubated with non-differentiated Caco-2 cells in a 96-well plate that contained a seeding density of 1×105 cells/cm2 at 37oC under atmosphere conditions of 5% CO2 for 24 hr. After removal of phenolic acids, the treated cells were incubated with 100 µL of 0.5 mg/mL MTT for 4 hr and then formazan crystals were dissolved in 100 µL of 10% SDS. Measurements were taken at an absorbance reading of 570 nm using a spectrophotometer (Multiskan Ascent, ThermoLabsystems, Finland). Cell viability was calculated according to the following equation: Cell viability (%) = absorbance sample 570nm/absorbance control 570nm × 100%. 2.2.7 Cell proliferation assay Non-differentiated Caco-2 cells were seeded in 96-well microplates at concentration of 1×105/cm2 and incubated overnight. Bromodeoxyuridine was then added to cells and incubated for 24 hr at 37 oC. Following incubation, the media and unincorporated BrdU was removed and cells were washed and then fixed using a fixing solution, which also denatured the cellular DNA, for 30 min at room temperature. The incorporation of BrdU in non-differentiated Caco-2 cells, treated with different phenolic acids was determined by ELISA (ab126556, Abcam, UK). Anti-BrdU monoclonal antibody was added to cells which were re-incubated for 1 hr at room temperature and then washed 3 times with washing buffer. Subsequently, cells were incubated with peroxidase goat-anti-mouse IgG conjugate secondary antibody for 30 min at room temperature. The cells were then washed again three times with washing buffer and a 3,3′,5,5′-Tetramethylbenzidine (TMB) peroxidase substrate was added for 30 min at room temperature. The reaction was stopped and absorbance readings were made at 450 nm using a spectrophotometer (Multiskan Ascent, ThermoLabsystems, Finland). 42 2.2.8 Analysis of apoptosis and necrosis in non-differentiated Caco-2 cells Non-differentiated Caco-2 cells were seeded in 8-well glass coverslips (2.5 × 104 cells/well) and incubated overnight. After a 24-hr sample treatment with phenolic acids, cells were washed three times with PBS. An Apoptosis/Necrosis Assay (ab176749; Abcam, Cambridge, UK) was used for detection of apoptosis and necrosis. A staining mixture containing assay buffer/apopxin/7-aminoactinomycin D (7-AAD)/CytoCalcein was added to cells and cells were incubated at room temperature for 30 min. Afterwards, the cells were washed twice using assay buffer, and the fluorescence was measured and quantified using an Olympus FV1000 with Multi-Photon laser scanning confocal microscope (Japan). Apoptotic cells showed up with green staining after stained by Apopxin Green Indicator and were visualized using the Fuorescein isothiocyanate (FITC) channel (Ex/Em = 490/525 nm). Necrosis cells were stained by 7-AAD and visualized using a red channel (Ex/Em = 550/650 nm). Healthy cells were stained by CytoCalcein and visualized using violet channel (Ex/Em = 405/450 nm). 2.2.9 Detection and quantification of nuclear morphology changes in apoptosis cells Non-differentiated Caco-2 cells were grown in 8-well plates (2.5 × 104 cells/well) and incubated overnight. After sample treatment for 24 hr with selected phenolic acids, cells were washed three times with PBS and a nuclear morphology assay was performed according to Mandelkow et al. (Mandelkow et al., 2017). Briefly, cells were incubated with 1.0 µg/mL DAPI for 10 min, and the fluorescence was measured under microscope (BX-53, Olympus Corp, Tokyo, Japan) with a 40-fold magnification. Images were analyzed using Fiji Analyzer software (Madison, Wisconsin, USA). Nuclear morphology parameters were obtained by calculating the area of the nucleus for 20 cell samples for each treatment. 43 2.2.10 Statistical analysis Data are expressed as mean ± standard deviation (n=3) and analyzed by Student’s t-test using Microsoft Excel Software (Microsoft Corp., Redmond, WA) or one-way analysis of variance (ANOVA) using IBM SPSS® Data Software (SPSS Statistics/IBM Corp, Chicago IL, USA). Significant differences among means were compared using Tukey’s test with p < 0.05 representing a statistically significant difference. All experiments were performed in triplicates. 2.3 Results and discussion 2.3.1 Loss of phenolic acids in culture media after 24 hr incubation The first analysis was performed to confirm the stability of phenolic acids by quantifying relative loss of phenolic acids after a 24 hr incubation in the cell-free culture media (Figure 2.1). The relative percentage loss of each polyphenol in ascending order was FA (1.25%); CGA (37.3%); CA (84.8%); GA (100%), thus FA was the most stable of the four phenolic acids tested in culture media. Phenolic compounds, such as delphinidin chloride, hydroxytyrosol or rosmarinic acids have been shown to be unstable when present in commonly used cell culture media over extended time periods (Grzesik et al., 2019; Long et al., 2010). Parallel to the loss of phenolic acids tested in the current study was the generation of H2O2, which was also reported previously for other polyphenolics (Grzesik et al., 2019; Long et al., 2010). An explanation for the relative instability of flavonoids in culture was attributed to structural differences, especially the number of hydroxyl groups (–OH) present on the structure (Fu et al., 2021; Maini et al., 2012). For instance, the stability of apigenin (e.g., three –OH in molecule) was found to be relatively higher than fisetin (e.g., four –OH in molecule), and moreso, quercetin (e.g., five –OH in molecule), and 44 myricetin (e.g., six –OH in molecule) (Fu et al., 2021; Liu et al., 2019b; Liu & Zhao, 2019). In the present study, GA (e.g., three –OH in molecule) was the least stable phenolic acid, followed by CA and CGA, (e.g., both having two –OH in molecule,) and FA (e.g., one –OH in molecule), respectively. Figure 2.1 Percentage loss of individual phenolic acids after 24 hr incubation in DMEM in the absence of cells. Data are expressed as mean ± standard deviation (n=3). Individual chromatograms are given in Appendix A. 2.3.2 Autoxidation of phenolic acids to H2O2 in cell-free culture media The relative temporal pattern of H2O2 generated from autoxidation of CA, CGA, FA and GA in cell-free culture media over a 24 hr incubation is shown in Figure 2.2. A wide range of individual phenolic acid concentrations (10 µM, 100 µM, and 1000 µM) were used to observe H2O2 generated from phenolic acid autoxidation reactions that are relevant to reported use in various cell culture studies, as well measured in vivo from gastrointestinal contents (Halliwell, 2008; Halliwell et al., 2000; Jenner et al., 2005; Long & Halliwell, 2000). The lowest 020406080100120FA CGA CA GAPercentage loss (%) 45 concentration of phenolic acids used in this study actually corresponds to concentrations measured in blood samples collected from subjects fed phenolics (Long et al., 2010). Parameters describing the temporal production of H2O2 production from four individual phenolic acids are summarized in Table 2.1. A phenolic acid-specific pattern for H2O2 production was shown in Figure 2.2. Noted differences in the area under the H2O2 production-time curve indicated the relative capacity of the four phenolic acids to generation of H2O2 was specific to both the type and concentration of phenolic acids tested. At equimolar concentrations of 1 mM, GA generated the highest level of H2O2 (e.g., 1081.12 µM), followed by CA (e.g., 407.89 µM), and CGA (e.g., 204.24 µM). Ferulic acid did not generate detectable levels of H2O2 at any time in the culture media. When this experiment was repeated with the addition of catalase to the culture mixture, the recovery of H2O2 was reduced (p < 0.05) to an extent that was dependent on the type of phenolic acid used (Table 2.2). Other works that have added catalase to culture media containing polyphenols also reported a decrease in the H2O2 generated by autoxidation (Bellion et al., 2009). A structure-function relationship for these findings centers around the importance of adjacent phenolic –OH groups required for H2O2 generation which is susceptible to oxidation of catechol structures (Long et al., 2010). In addition, to the exposure of oxygen, the presence of trace levels of transition metal ions in the complete culture media catalyzes the autoxidation of phenolic acids (Grzesik et al., 2019; Kanner, 2020). Furthermore, differences observed between different phenolic acid autoxidation rates has be ascribed to specific structure and electronic configuration of the hydroxyl oxygen bound to the benzene ring molecule (Kanner, 2020). Figure 2.3 is a schematic diagram that shows possible mechanisms for phenolic acid autoxidation. This involves a one- or two-step electron transfer, where electron transfer from the polyphenol (PhH) to oxygen molecule 46 produces an ortho-semiquinone anion radical (Ph•) intermediate which undergo a radical-radical reaction giving rise to o-quinone. In addition, ortho-semiquinone anion radical reacts with oxygen to produce a superoxide anion radical (O2˙¯), thus initiating a redox cycle (Brudzynski & Maldonado-Alvarez, 2015). The generation of O2˙¯ once scavenged by parent polyphenol produces o-quinone radicals and H2O2. Unlike one electron transfer, the two-step electron transfer from the parent molecule produces a o-quinone which is more thermodynamically stable due to rapid isomerization to para-quinone intermediates (Metodiewa et al., 1999). These reactions are described by the following steps (Grzesik et al., 2019; Kanner, 2020): Ph-OH + electrophiles/M+n/R• —› Ph-O• + reduced compounds (1) Ph-O• + O2 —› Ph = O + O2˙¯ (2) Ph-O• + O2˙¯—› Ph = O + H2O2 (3) Where M+n = oxidized metal ion; R• = free radical Autoxidation of polyphenols is also dependent on pH and is accelerated under alkaline conditions (Mochizuki et al., 2002). In agreement with this postulated mechanism, the pH of culture medium is 7.4, not unlike that of the small intestine, thus favoring phenolic acid autoxidation. 47 Figure 2.2 Temporal patterns of H2O2 production from polyphenolics, CA (a), CGA (b), FA (c) and GA (d), at concentration of 10 µM, 100 µM, and 1000 µM, respectively in culture media (DMEM) in the absence of cells. Data are expressed as mean ± standard deviation (n=3). Experiments were performed in triplicate. See Table 2.1 for specific time course parameters. Figure 2.3 A schematic diagram that shows possible mechanisms for the autoxidation of polyphenols. Reproduced from references (Amorati et al., 2006; Bellion et al., 2009; Metodiewa et al., 1999). 48 Table 2.1 Parameters defining H2O2 production from four different phenolic acids1 Phenolic acid Concentration tested (µM) Lag time (min) Peak H2O2 Concentration (µM) Area under the curve2 CA 10 40 min 18.96 6618 ± 464h 100 40 min 62.13 42353 ± 1839e 1000 30 min 407.89 368147 ± 2858b CGA 10 40 min 4.71 2980 ± 90i 100 40 min 25.41 18710 ± 222g 1000 40 min 204.23 168975 ± 617c FA 10 - - - 100 - - - 1000 - - - GA 10 - 16.92 24595 ± 201f 100 - 115.80 137946 ± 2827d 1000 - 1081.12 1308274 ± 12030a 1 (-) means not determined. 2Area under the curve was calculated using Graphpad Prism software (Version 9.4, San Diego, CA, USA). Data are expressed as mean ± standard deviation (n=3). Data were analyzed by one-way ANOVA using SPSS® Data Software. Significant differences were compared using Tukey’s test with different letters (a-i) denoting statistical significance at p < 0.05. 49 Table 2.2 Autoxidation of phenolic acids yielding H2O2 production in cell-free DMEM media after 24 hr incubation in the presence or absence of catalase.1 Phenolic acid Concentration H2O2 (µM) (µM) Without catalase With catalase CA 10 7.24 ± 0.07 3.60 ± 0.66** 100 61.92 ± 1.32 30.10 ± 0.89*** 1000 440.40 ± 23.18 284.64 ± 21.40** CGA 10 0.54 ± 0.22 n.d. 100 23.84 ± 1.26 14.31 ± 0.20*** 1000 194.23 ± 0.37 62.18 ± 7.44*** FA 10 n.d. n.d. 100 n.d. n.d. 1000 n.d. n.d. GA 10 18.60 ± 0.68 9.05 ± 0.48*** 100 128.95 ± 1.61 80.05 ± 1.31*** 1000 1181.12 ± 24.21 735.98 ± 10.82*** 1 Measurements for each experiment was performed in triplicate. Data are expressed as mean ± standard deviation (n=3). Significant differences in samples with or without 1 µg/mL catalase were identified using Student’s t-test (*** representing p<0.001, **representing p<0.01, *representing p<0.05). n.d.= not detectable 50 2.3.3 MTT reduction assay to assess phenolic acid cytotoxicity in non-differentiated Caco-2 cells Figure 2.4 shows the MTT results for different phenolic acids, namely CA (Figure 2.4 (a)), CGA (Figure 2.4 (b)), FA (Figure 2.4 (c)) and GA (Figure 2.4 (d)) in the presence and absence of catalase using non-differentiated Caco-2 cells. Relatively small, but no significant losses in cell viability were observed with CA and CGA, compared to a greater, significant (p<0.05) loss with GA at low- to mid-concentration ranges. Ferulic acid produced no change in cell viability at all concentrations tested. The treatment of cells with catalase in the presence of GA resulted in significant (p<0.001) increases in Caco-2 cell viability over a wide range of GA concentrations that signified almost a 50% recovery. Figure 2.4 The effects of different phenolic acids, CA (a), CGA (b), FA (c) and GA (d) on cell cytotoxicity of non-differentiated Caco-2 cells according to the MTT assay. Results are expressed as mean ± standard deviation (n=3). Significant differences in cells treated with phenolic acids for 24 hr compared to presence of 1 µg/mL catalase (CAT) were performed by Student’s t-test, with *** representing p<0.001, ** representing p<0.01, *representing p<0.05. 51 The cytotoxic effect of polyphenols described by MTT results on non-cancer cells, and the connection with H2O2 production has been reported with other polyphenols, including propyl gallate, (−)-epigallocatechin gallate and quercetin, respectively (Belščak-Cvitanović et al., 2014; Ding et al., 2018; Durgo et al., 2012). The current finding with GA agrees to reports that the cytotoxic effects of (−)-epigallocatechin gallate was attributed to the presence of GA in the (−)-epigallocatechin gallate backbone structure (Belščak-Cvitanović et al., 2014; Ding et al., 2018; Durgo et al., 2012). 2.3.4 BrdU assay to assess anti-proliferation activity of different phenolic acids in non-differentiated Caco-2 cells Figure 2.5 The effects of different phenolic acids and concentrations on cell proliferation of non-differentiated Caco-2 cells according to the BrdU assay. Results are expressed as mean ± standard deviation (n=3). Significant differences in cells treated with phenolic acids for 24 hr compared to absence of phenolic acids (controls) were performed by Student’s t-test, with *** representing p<0.001, **representing p<0.01, *representing p<0.05, H2O2 was used as positive control. 52 The effect of treating non-differentiated Caco-2 cells with a wide range of different phenolic acid concentrations on BrdU incorporation, to assess cell proliferation, is presented in Figure 2.5. Cells treated with lowest concentrations (10 µM) of phenolic acids, or corresponding H2O2 positive control, showed no significant effect on cell proliferation. Increasing concentrations of both the H2O2 positive control and GA, respectively, to a minimum of 100 µM decreased proliferation in non-differentiated Caco-2 cells. In comparison, increasing CA concentration to 500 µM reduced proliferation (p<0.05), whereas a similar significant (p<0.05) result occurred with CGA, but only at a much higher (e.g., 1000 µM) concentration. Regardless of the concentration of FA tested, no effect on cell proliferation in non-differentiated Caco-2 cells was observed. To confirm that the phenolic acid specific differences in anti-proliferation activity was attributed to H2O2 production resulting from phenolic acid autoxidation, catalase was simultaneously added with individual phenolic acids at equimolar concentrations (Figure 2.6). Results showed that the presence of catalase did not affect cell proliferation directly but was effective when added along with both CA and GA, respectively; the greatest modulating activity was observed with GA. The anti-proliferation effect of specific phenolic acids on cancer cells has previously been reported and attributed to a reduced antioxidant status of cells that resulted in a build up of ROS. Pro-oxidant activity of a series of polyphenolic compounds, including epigallocatechin gallate, protocatechuic acid, gallic acid, rutin, quercetin, and kaempferol have been demonstrated (Eghbaliferiz & Iranshahi, 2016; Lambert & Elias, 2010; Sakuma et al., 2015); albeit the underlying mechanism was not described. In this study, it was confirmed that the distinct production of H2O2 resulting from phenolic specific extent of autoxidation was a strong signal to control proliferation in non-differentiated Caco-2 cells. 53 Figure 2.6 The effects of equimolar (e.g., 1mM) concentration of different phenolic acids both in the presence, or absence of 1 µg/mL catalase (CAT) on cell proliferation in non-differentiated Caco-2 cells. Results are expressed as mean ± standard deviation (n=3). Results are shown as BrdU incorporation relative to control cells (cells without any treatments). Significant differences refer to treatments comparing cells treated with phenolic acids without CAT to cells treated with phenolic acid with CAT, determined using Student’s t-test with *** representing p<0.001, *representing p<0.05. H2O2 was used as positive control. 2.3.5 Assessment of induced apoptosis and necrosis in non-differentiated Caco-2 cells treated with phenolic acids Apoptosis is a programmed cell turnover mechanism that has critical roles in development, aging, and disease (Kaczanowski, 2016). It is initiated by a tightly regulated signaling cascade that leads to caspase activation with subsequent effects being cell shrinkage, membrane blebbing, chromosome condensation, nuclear fragmentation, DNA laddering and engulfment of the cells by phagosomes. In normal cells, the phospholipid, phosphatidylserine (PS) is located in the plasma membrane cytoplasm and during the course of apoptosis it is translocated from the inner face of plasma membrane to the outer leaflet. The appearance of PS on the cell surface allows the binding of the Apopxin, resulting in a specific green fluorescence 020406080100120- + - + - + - + - + - +Control H2O2 CA CGA FA GABrdU Incorporation (% of -control)*** ****CAT 54 (Ex/Em = 490/525 nm). This is in contrast to necrosis, where cell passive cell death attributed to environmental factors results in release of inflammatory cellular contents and loss of plasma membrane integrity. A membrane impermeable probe, 7-AAD (Ex/Em = 546/647 nm) measures cellular plasma membrane integrity by labeling the nucleus of cells that have compromised membrane integrity. The probe, CytoCalcein Violet 450 (Ex/Em = 405/450 nm) labels cytoplasm of live cells; hence, by using the Apopxin green sensor, 7-AAD, together with CytoCalcein Violet 450, it is possible to identify apoptosis, necrosis and live cells concurrently. The effects of using a concentration range of different phenolic acids herein, along with the positive H2O2 control to test effectiveness to trigger cell apoptosis and necrosis are presented in Figure 2.7. Only cells that were treated with 1 mM phenolic acids, or the H2O2 positive control, showed apoptosis for GA and the H2O2 positive control, respectively (Figure 2.7 (a)). The apoptotic effect induced by GA and H2O2 was eliminated when the experiment was repeated with the addition of catalase (Figure 2.7(b)). This finding demonstrates that GA is the only phenolic acid tested that generated sufficient H2O2 production in order to induce apoptosis and supports similar observations made for the anti-proliferation of non-differentiated Caco-2 cells when treated with GA. This result confirms that the capacity of other polyphenols reported to induce apoptosis in other sources of cancer cells (Ho et al., 2020; Ramos et al., 2011; Wei et al., 2020; Zhu et al., 2020) was linked to H2O2 production (Xiang et al., 2016). This likely also holds true for more complex polyphenols, such as anthocyanins that can induce an apoptotic signal in specific cancer cells (Lecci et al., 2014; Mendes et al., 2015) due to increased intracellular ROS (Alhosin et al., 2015; Kim et al., 2013b). Another example is gingerol, an aryl alkenone present in ginger that when under specific conditions will promote intracellular ROS generation, thereby up-regulating the expression levels of p53 and inhibiting the expression of anti-apoptotic 55 proteins. This reaction relates to the sensitization of cells to TNF-α related apoptosis-inducing apoptosis (Lee et al., 2014). Catechin and (−)-epigallocatechin gallate are other examples of polyphenols that undergo pro-oxidation that contributes to increased ROS production, accompanied by activation of AMP-activated protein kinase and subsequent inhibition of cyclooxygenase-2 expression. This mechanism was reported previously to reduce cell proliferation in HT-29 colon cancer cells (Hwang et al., 2007; Lambert & Elias, 2010). Generation of ROS attributed to polyphenol autoxidation in the presence of transition metal ions can also result in DNA damage, propagation of lipid and protein oxidation reactions (Alhosin et al., 2015). Catechin induced DNA damage observed in human leukemia HL-60 cells occurred in concert with higher levels of ROS, particularly 8-hydroxyguanine levels. This response was mitigated by adding catalase, and hence supports the findings of this study with GA, that phenolic acid induced H2O2 production can lead to MTT cytotoxicity and apoptosis (Oikawa et al., 2003). Previous studies with other polyphenols that include flavanone hesperetin, glycoside hesperidin (Palit et al., 2015), flavanones apigenin and luteolin, flavonols quercetin and kaempferol (Kim et al., 2013a; Zhang et al., 2015), isoflavones genistein and daidzein (Iwasaki et al., 2008; Jin et al., 2010; Lo et al., 2012; Yang et al., 2015), phenolic acids CGA (Rakshit et al., 2010), curcumin (Kang et al., 2005), and proanthocyanidins (Kim et al., 2012) have in common the induced apoptotic effect on various type of cancer cells. The relative susceptibility of different phenolic acids to undergo autoxidation that results in H2O2 production is strong evidence that a shift in redox balance is central to the observed bioactive properties that relate to reduced cancer cell proliferation reported in this study. Subsequent disruption of mitochondrial function, resulting in activation of apoptotic signaling would explain this outcome. Moreover, phenolic acid autoxidation that results in H2O2 56 production, also increases the concentration of intercellular electrophilic molecules that interact with glutathione cysteine residues, thus contributing to increased oxidative stress due to reduced cellular antioxidant capacity (Alhosin et al., 2015). In this study, cell shrinkage of non-differentiated Caco-2 cells treated with different phenolic acids was used as an apoptosis biomarker to signify condensation of nuclear chromatin and fragmentation into membrane-bound apoptotic bodies (Kerr et al., 1972; Saraste & Pulkki, 2000). DAPI, a nuclear counterstain used in fluorescence microscopy was used for its high affinity for DNA (Tarnowski et al., 1991), thus enabling nuclear morphology changes to be evaluated. Morphological analysis of DAPI-stained nucleus of non-differentiated Caco-2 cells treated with equimolar concentrations of 1mM for different phenolic acids and the positive H2O2 standard are presented in Figure 2.8. Treatment of cells with CA, CGA, FA, and GA in the presence or absence of catalase for 24 hr is shown in Figure 2.8 (a) with quantification of morphological changes, determining the area of DAPI-stained nucleus of each sample, and the average area of 20 cells calculated for each sample treatment (Figure 2.8 (b)). Cells treated with the positive H2O2 control and GA, respectively produced the strongest significant change in nucleus area (p<0.001). The capacity of CA to induce change was also significant (p<0.01) but not as strong as GA and the positive H2O2 control. The addition of catalase mitigated the nuclear shrinkage response observed for GA (p<0.001), CA (p<0.05) and H2O2 control (p<0.05), respectively. This finding adds further merit to the hypothesis that different capacities of phenolic acids that induce apoptosis in non-differentiated Caco-2 cells is explained by relative affinity to undergo autoxidation and generate sufficient amounts of H2O2 in culture media. 57 58 Figure 2.7 Normal, apoptotic and necrotic cells treated with CA, CGA, FA, and GA at 1 mM (a) or 1 mM + 1 µg/mL catalase (CAT) (b) were imaged using confocal microscopy with blue (Ex/Em = 405/450 nm), green (Ex/Em = 490/525 nm) and red (Ex/Em = 550/650 nm) signals. Scale bars: 50 µm. 59 60 Figure 2.8 (a) Morphological analysis of DAPI-stained nucleus of non-differentiated Caco-2 cells treated with 1mM of H2O2, CA, CGA, FA, or GA in the presence or absence of 1 µg/mL catalase (CAT) for 24 hr. Bar = 20 µm. Arrows are used to identify sampled cells. (b) Quantification of area of DAPI-stained nucleus of each sample in (a), and average area of 20 cells were calculated for each sample treatment. Results are expressed as mean ± standard deviation (n=20). Significant differences in cells treated with phenolic acids for 24 hr compared to absence of phenolic acids (control) were performed by Student’s t-test, with *** representing p<0.001, **representing p<0.01. Significant differences in cells treated with phenolic acids in the presence or absence of CAT were performed by Student’s t-test, with *** representing p<0.001 and *representing p<0.05. 2.4 Conclusions In summary, this study showed the relative capacity of different phenolic acids to regulate cell proliferation in a cancer intestinal cell, e.g., the non-differentiated Caco-2 cell, is influenced by relative stability in culture media and more specifically the extent of autoxidation that lead to H2O2 generation. The four phenolic acids chosen in this study demonstrated a range of activities that resulted in phenolic-specific differences for cytotoxicity, proliferation and apoptosis in the non-differentiated Caco-2 cell. This corresponded to the highest resistance to autoxidation for FA versus the greatest autoxidation for GA and was influenced by concentration dependent changes in rate and amount of H2O2 generated over a 24 hr period. Finally, the fact that many of the cellular responses were mitigated by the presence of catalase, confirms the importance of H2O2 generation from phenolic acid autoxidation in culture media. 61 Chapter 3: Application of HyPer-3 sensor to determine intracellular H2O2 production in differentiated Caco-2 cells 3.1 Introduction Findings from Chapter 2 revealed that hydrogen peroxide is a key molecule for redox sensitive metabolite operations that involve cell proliferation in the intestinal cancer cell. Hydrogen peroxide has also been shown to regulate cell signaling (Bienert et al., 2007; Sies, 2017). A critical physiological property of H2O2 as a messenger molecule concerns its capacity to diffuse through cell membranes to initiate immediate effects that include changes in cell morphology, initiation of cell proliferation and recruitment of immune cells when exposed to environmental stress (Bienert et al., 2007; Sies, 2017). One major example of the cascade of effects includes involvement with transcription-independent signaling, similar to Ca2+ and adenosine triphosphate (ATP) (Cordeiro & Jacinto, 2013; van der Vliet & Janssen-Heininger, 2014). Taken together, these key fundamental regulatory functions of H2O2 metabolism are vital to maintain cell homeostasis (Sies, 2014). A number of different approaches have been attempted to quantify the effects of H2O2 function in cells that involve messenger properties (Brewer et al., 2015; Logan et al., 2014; Winterbourn, 2014). One of these is HyPer, a term that describes a genetically encoded fluorescent, H2O2 sensitive probe that can measure intracellular H2O2 and enable fluorescent lifetime imaging of H2O2 levels in living cells. The procedure involves a circularly permuted yellow fluorescent protein (cpYFP) that is integrated into the regulatory domain of an Escherichia coli H2O2 sensitive protein, termed OxyR (Belousov et al., 2006; Choi et al., 2001). HyPer has two excitation peaks at 420 nm (in the violet spectral region) and 500 nm (in the blue 62 spectral regions), respectively, and one emission peak at 516 nm in the green spectral region (Lyublinskaya et al., 2018). Upon exposure to H2O2, the HyPer OxyR domain undergoes conformational changes which alters the fluorescence excitation spectrum, thereby shifting the fluorescence excitation intensity ratio metric to 500 and 420 nm, respectively. For example, excitation peaks appearing at 500 nm increase in proportion to the decrease in peaks occurring at 420 nm, thereby enabling a ratio of the two fluorescence signals correspond to a H2O2 concentration (Lyublinskaya et al., 2018). Minimal concentrations of H2O2 required to induce detectable changes in HyPer fluorescence have been reported to be in the 25 nM range for the isolated probe, and span from 5 µM to 25 µM H2O2 in the eukaryotic cytoplasm. The technique has been employed in a number of studies related to H2O2 production in both isolated cells and living organisms (Love et al., 2013; Malinouski et al., 2011; Mishina et al., 2011; Niethammer et al., 2009). HyPer was successfully used to monitor changes in redox reactions that are sensitive in cellular thiol-reducing systems (Hernández et al., 2018). In comparison to HyPer, another version, HyPer-3 also possesses an expanded dynamic range and a higher brightness when expressed in cells, without compromising both oxidation and reduction rates (Bilan et al., 2013; Markvicheva et al., 2011). This feature increases both resolution and accuracy needed for this technique to measure intracellular H2O2 concentrations. A HyPer based assay used to measure intracellular H2O2 is typically performed using microscopy for both flow cytometry and live cell imaging. Cell imaging of HyPer in cells allows visualization of H2O2 fluxes in living HyPer-expressing cells, whereas with flow cytometry, it enables large data collection of redox events associated with cell H2O2 dynamics. The capacity to transport H2O2 across membranes is vital to the intracellular concentration of H2O2 and occurs via water channels that are regulated by specific receptor 63 proteins, termed aquaporins (AQPs). The subsequent H2O2 gradients produced by AQP function defines the extra- and intracellular balance. This has an impact on triggering cell signaling that regulates metabolic responses need for cell survival (Medraño-Fernandez et al., 2016). Specifically, the AQP3 is known to be required for NADPH oxidase derived H2O2 signaling, which is stimulated by growth factors (Miller et al., 2010). In addition, AQP3 is critical for mediating H2O2 uptake in concert with downstream NF-κB cell signaling (Hara-Chikuma et al., 2015) and, therefore, has a role in controlling the extent of cell inflammation. Aquaporin-3 is also a member of the intrinsic protein family that facilitates water, glycerol, and H2O2 transport (Ishibashi et al., 1994; Miller et al., 2010). These are expressed in the gastrointestinal tract (Frigeri et al., 1995; Ramírez-Lorca et al., 1999) and function as channels involved in cytokine and growth factor signaling (Hara-Chikuma et al., 2012; 2015; Hara-Chikuma et al., 2016). Few studies have studied the functionality of AQP3 and AQP3 inhibitors. For instance, Cu2+ as well as Ni2+ ions can bind to human AQP3 (Calamita et al., 2018; Zelenina et al., 2003; Zelenina et al., 2004) and recently, novel AQP3 inhibitors have been identified (Sonntag et al., 2019) and used to characterize AQP function that includes ion transport and flux. Sonntag et al. (2019) examined the structure-activity relationship of an AQP3 inhibitor and reported that a potent inhibitor of AQP3, namely DFP00173, functions without compromising cell viability in Chinese hamster ovary cells. In the present study, two primary aims were initiated to first validate the methodology required to examine HyPer-3 expression in differentiated Caco-2 cells, and determine the appropriate conditions of using the DFP00173 inhibitor to inhibit AQP3. Both aims were focused on understanding the intracellular uptake of H2O2 in differentiated Caco-2 cells. 64 3.2 Material and methods 3.2.1 Materials The following chemicals were purchased from Sigma (St. Louis, MO, USA): Dulbecco's Modified Eagle's Medium (DMEM), phosphate buffered saline (PBS), penicillin/streptomycin antibiotics, 3-(4,5-diethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and sodium dodecyl sulfate (SDS). Fetal bovine serum (FBS) was purchased from Gibco® (Grand Island, NY, USA). Hydrogen peroxide standard and catalase was purchased from Cayman Chemical Company (Ann Arbor, MI, USA). EndoFree Mini Plasmid Kit II was purchased from TIANGEN (China). BTXPRESS electroporation solution was purchased from BTX (USA). Caco-2 cells was purchased from American Type Culture Collection (Manassas, VA, USA). DFP00173 was purchased from MedChem Express (MCE, Monmouth Junction, NJ 08852, USA). 3.2.2 Cell culture Caco-2 cells (HTB-37, American Type Culture Collection, Manassas, VA, USA) were cultured using DMEM, supplemented with 10% FBS (Invitrogen, Carlsbad, Canada), 100 U/ml of penicillin and 100 µg/mL of streptomycin (Sigma, St. Louis, MO, USA), at 37oC under a 5% CO2 atmosphere. Caco-2 cells were grown in DMEM media for 21 days to reach differentiation. This was accomplished by changing the culture media every 2-3 days weekly. The passage number for Caco-2 cells used in these experiments was 31-40. 3.2.3 Cell transfection of HyPer-3 Plasmid was isolated from HyPer-3 overexpressed Escherichia coli strain using the EndoFree Mini Plasmid Kit II (TIANGEN, China) following the manufacturer’s instructions. 65 Differentiated Caco-2 cells were harvested, washed three times with PBS and then resuspended in BTXPRESS electroporation solution (BTX, USA) at 1 × 107 cells/mL. Quantification of DNA concentration was performed using a Nanodrop spectrophotometer (Thermo Scientific, Madison, USA). Plasmid DNA was added to suspended cells at a concentration of 50 µg/mL and electroporation was performed using a ECM830 electroporation (BTX, USA), coupled with a 4 mm gap electroporation cuvette and using 165 Volts with a pulse length set at 70 msec. Transfected cells were seeded in a petri dish for a 48 hr incubation recovery period to re-establish homeostasis. 3.2.4 HyPer-3 based flow cytometry analysis A 48 hr recovery from electroporation procedure was used before transfected cells were harvested and dispersed into different tubes containing PBS for 30 min to enable adaptation of cells. Catalase or H2O2, respectively, was added to the cells which were then monitored for subsequent changes in intracellular H2O2 level using a CytoFLEX flow cytometer using both 405 nm and 488 nm lasers (Beckman Coulter, Brea, CA, USA). The HyPer-3 response was defined as the ratio between EX488/FL525 and EX405/FL525 signals. The data obtained from HyPer-3 responses were analyzed using FlowJo software (Tree Star, San Carlos, CA, USA). 3.2.5 Confocal microscopy and HyPer-3 imaging To visualize the effect of H2O2 on HyPer-3 expressed cells, live-cell imaging was performed using a confocal microscope. Transfected Caco-2 cells were seeded on 8-well plate and incubated at 37oC for 48 hr to ensure recovery from the procedure. A visual observation of the treated cells was used to ascertain cell normality. Following exposure of cells to H2O2, 66 confocal images were acquired every 20 sec for a total of 20 min using a Spinning disk Perkin Elmer confocal microscopy (Leica DMi8 inverted microscope, Leica Microsystems, Wetzlar, German), equipped with a high-sensitivity Hamamatsu 9100-02 CCD camera (Hamamatsu Photonics, Hamamatsu, Japan). Images were collected using 405 nm and 488 nm lasers, respectively, and processed by Improvision Volocity software (Improvision, Coventry, UK). The ratio of mean fluorescence intensity of 488/405 nm ratio was quantified using Image J (National Institutes of Health, Bethesda, MD). 3.2.6 Assessment of cytotoxicity Potential cytotoxic properties of AQP3 inhibitor, DFP00173, in differentiated Caco-2 cells were assessed using the MTT assay. Briefly, cells were treated with the AQP3 inhibitor, DFP00173 at 37oC under 5% CO2 for 20 min followed by incubation in culture media for 24 hr. The MTT was analyzed as described in Section 2.2.6. 3.2.7 Statistical analysis Data are expressed as mean ± standard deviation. Data were analyzed by one-way analysis of variance (ANOVA) using IBM SPSS® Data Software (SPSS Statistics/IBM Corp, Chicago IL, USA). Significant differences between means were compared using a Least Significant Difference’s (LSD’s) test with p < 0.05 representing a statistically significant difference. 67 3.3 Results and discussion 3.3.1 HyPer-3 based assay for H2O2: characterization of parameters Figure 3.1 The HyPer-3 based assay for H2O2: characterization of parameters. Panels A & B refer to dual-parameter histograms displaying HyPer-3 expression in differentiated Caco-2 cells. Panel A shows the blank cells only (blue dots), and panel B shows the blank cells (blue dots) and the expressed HyPer-3 in Caco-2 cells (green dots). Panel C shows the confocal microscopy image of HyPer-3, expressed in a single Caco-2 cell. To obtain HyPer-3 expression in differentiated Caco-2 cells, a plasmid vector was transfected into cells using standard electroporation techniques. Untreated cells revealed no expression of HyPer-3 expression, whereas successful HyPer-3 expression was obtained in differentiated Caco-2 cells Figure 3.1. From these responses, HyPer-3 with two excitation maxima at 500 nm and 420 nm, respectively, emitted a green fluorescence signal that peaked at 516 nm. Cellular transition to an oxidation state resulted in an increase in the intensity of fluorescence signal excited at 500 nm, whereas a decrease in the oxidation state corresponded to a fluorescence excited at 420 nm (Bilan & Belousov, 2016; Lyublinskaya et al., 2018). Previous studies that have monitored relevant signals given by the single channel EX488/FL525 and the EX405/FL525 channel, when expressed as a ratio have reported greater precision in quantifying the intracellular H2O2 concentration (Bilan & Belousov, 2016; Lyublinskaya et al., 2018). This (A) (B) (C) 68 approach of determining the ratio of EX488/ FL525 and EX405/FL525 signals was used in this experiment to establish high precision for monitoring HyPer-3 oxidation in differentiated Caco-2 cells. 3.3.2 Determination of intracellular HyPer-3 sensitivity to extracellular exposure to H2O2 or catalase. Preliminary experiments were performed to determine if the HyPer-3 probe was highly sensitive to the addition of H2O2 to transfected Caco-2 cells. A HyPer-3 sensitivity ratio in response to H2O2, or catalase, was measured using a flow cytometer (Figure 3.2). The addition of catalase to the media lowered the HyPer-3 ratio; whereas, the addition of H2O2 increased HyPer-3 ratio with sensitivity at concentrations greater than 0.1µM. HyPer-3 sensitivity expressed, as a ratio of 488/405nm, increased to a maximum ratio value of 6.15, when the added H2O2 concentration reached 100 µM. This result showed that increasing extracellular exposure of Caco-2 cells to H2O2 produced a noted increase in the intracellular H2O2 level, which was quantified in differentiated cells. Validation of the technique was further confirmed by showing that the activity of catalase to remove extracellular H2O2, indeed resulted in lowering the transportation of available H2O2 from the extracellular to the intracellular compartment. 69 Figure 3.2 Determining the HyPer-3 sensitivity to H2O2 or catalase (CAT) exposure by quantifying HyPer-3 ratio (the ratio of EX488/FL525 and EX405/FL525 signals), in differentiated Caco-2 cells. Data are expressed as mean ± standard deviation (n=3). Data were analyzed by one-way ANOVA using SPSS® Data Software. Significant differences were compared using LSD’s test with different letters (a-e) denoting statistical significance at p < 0.05. 70 3.3.3 Visualization of changes in HyPer-3 fluorescence in differentiated Caco-2 cells t=0s t=200st=0s t=200sEX488/FL525 EX488/FL525EX405/FL525 EX405/FL525(A) 71 Figure 3.3 Live-cell imaging of changes in HyPer-3 fluorescence in differentiated Caco-2 cells when treated with 100 µM H2O2. Figure (A) represents HyPer-3 transfected cells without H2O2 treatment. Figure (B) represents HyPer-3 transfected cells treated with 100 µM H2O2. Arrows. are used to identify the differences in relative fluorescence ratios between t=0 and t=200 sec in control and treated cells, respectively. Live-cell imaging was used to visualize the effect of H2O2 on HyPer-3 expressed cells, (Figure 3.3). Maximum HyPer-3 response was obtained using 100 µM H2O2 (Figure 3.3(B)) without resulting in cell death. t=0s t=200st=0s t=200sEX488/FL525 EX488/FL525EX405/FL525 EX405/FL525(B) 72 Figure 3.4 A time course depicting cumulative quantitation of HyPer-3 (ratio of EX488/FL525 and EX405/FL525) signals up to 1200 sec following exposure to 100 µM H2O2. Data are expressed as mean ± standard deviation (n=6). A temporal pattern of HyPer-3 cell sensitivity was presented by calculating the ratio of EX488/FL525 and EX405/FL525 signals in control and 100 µM H2O2 treated cells, respectively, Figure 3.4. Responses collected every 20 sec for up to 20 min showed a pattern of increase in HyPer-3 sensitivity attributed to the addition of 100 µM H2O2 to the transfected cells, relative to control cells. A peak response was reached at 200 sec and thereafter plateaued or decreased slowly at 400 sec; an observation that can be attributed to bleaching of the fluorescence signals. This method once standardized enabled monitoring early time dependent changes in intracellular H2O2 in differentiated Caco-2 cells. 0.01.02.03.04.00 200 400 600 800 1000 1200 1400488/405nmvalueTime (second)Control H2O2 73 3.3.4 Determination of effective concentration of DFP00173 Aquaporins are a family of small molecular weight (e.g., approx.30 kDa), water channel membrane proteins, that facilitate the transportation of water and other minor solutes in animals (Ma & Verkman, 1999). Maintaining normal expression of AQPs in intestinal tissues is critical, since the over- or the under-expression of AQPs will disrupt intestinal function and contribute to a range of intestinal disorders, such as diarrhea or constipation (Fischbarg, 2010; Ikarashi et al., 2016). An ortho-chloride derivative and effective inhibitor of AQP3, DFP00173 (Figure 3.5), was used to determine the functionality of AQP3 in Caco-2 cells, by selectively blocking extra- and intracellular H2O2 exchange (Sonntag et al., 2019). Cells pretreated with DFP00173 in the current study at concentrations greater than 0.5 µM, prior to the addition of H2O2, displayed a significant (p<0.05) reduction in HyPer-3 cell sensitivity, without impacting the cell viability. These results provide the basic information needed to conduct subsequent studies with different phenolic acids, aimed to understand the mechanism underlying the Caco-2 cell molecular responses attributed to the phenolic acid autoxidation. Figure 3.5 Structure of DFP00173 74 Figure 3.6 Determination of effective concentration of DFP00173, an AQP3 inhibitor, on inhibition of H2O2 transport channel. Left Y-axis shows the HyPer-3 sensitivity ratio for blank cells, cells treated with 100 µM H2O2, and cells pretreated with different concentrations of DFP00173 followed by treatment of 100 µM H2O2. The Y-axis on the right shows the cell viability of Caco-2 cells following these treatments, using MTT assays. Data represent mean ± standard deviation (n=3). Data were analyzed by one-way ANOVA using SPSS® Data Software. Significant differences were compared using LSD’s test with different letters (a-c) denoting statistical significance at p < 0.05. 3.4 Conclusions This chapter reports on the development and validation of using HyPer-3 expression in differentiated Caco-2 cells, transfected with a plasmid expression vector, to respond immediately to increases in extracellular H2O2 with corresponding changes in intracellular H2O2. The bidirectional flux of H2O2 was monitored successfully by altering extracellular H2O2 content in different ways, such as with the presence of added catalase, or, alternatively physically, by reducing transport by blocking H2O2 transport channel, using the AQP inhibitor DFP00173. The optimal conditions required to demonstrate the bidirectional transport of H2O2 in differentiated Caco-2 cells will be employed in subsequent experiments in following chapters that aim to determine the efficacy of different phenolic acids to regulate cell signalling by modifying H2O2 transport leading to changes in intracellular content. 75 Chapter 4: Phenolic acids contribute to H2O2 induced regulation of intracellular Nrf2 cell signaling in differentiated Caco-2 cells 4.1 Introduction Phenolic compounds represent a relatively large group of naturally derived antioxidants that are present in fruits and vegetables and have a role in regulating redox reactions that are important for intestinal cell signaling and maintenance of cell function (Liang et al., 2019; Qin & Hou, 2016). One protective role of some classes of phenolic compounds involves a reducing capacity (Amaral et al., 2009; RiceEvans et al., 1996), whereas another function involves the pro-oxidant properties which can occur when in the presence of oxygen and metal ions to yield hydrogen peroxide (H2O2) (Kanner, 2020; Lapidot et al., 2002b). In the previous chapter, oxidization of phenolic acids to produce H2O2 was shown to occur in culture media; the significance of this in respect to regulating cell redox signaling has recently been suggested (Kanner, 2020). Hydrogen peroxide is considered an important messenger involved with cell redox sensing, signaling and regulation (Di Marzo et al., 2018) and can function to trigger transcription independent events that regulate cell homeostasis (Ursini et al., 2016). For the past two decades, studies have demonstrated how the generation of H2O2 from aerobic metabolism plays a critical role in providing the specificity for intracellular signal transduction. Serving as a messenger molecule, H2O2 diffuses across cell membranes via an aquaporin (AQP) channel to directly activate redox signaling in response to oxidative stress; thereby inducing changes in cell shape, a capacity to initiate proliferation and recruitment of immune cells (Bienert et al., 2007; Sies, 2017). 76 Intracellular H2O2 concentrations are controlled by a combination of intracellular peroxidase and catalase enzyme activities that remove H2O2 (Stone & Yang, 2006), as well as cellular diffusion mechanisms that return it back across the membrane to the extracellular space. At high H2O2 concentrations, H2O2 is converted to water by catalase activity which acts to prevent toxicity to cell membrane components. Peroxidases also reduce H2O2, and glutathione peroxidase for example, are also important subcellular enzymes that control H2O2 concentrations. Since oxidation dependent steps are known to be involved in the sensitivity required to initiate signal transduction pathways, it is vital that mammalian cells regulate H2O2 to physiologic levels thus providing functions, without being toxic. Cell signaling, triggered by presence of metabolically generated H2O2 is a process of cell communication that enables a response to changes in oxidative stress induced by the extracellular microenvironment. A typical intracellular concentration of H2O2 is approximately 10 nm when generated from aerobic metabolism and at this concentration is involved in optimal development, normal tissue homeostasis and growth (Kovacic & Pozos, 2006). For example, extracellular redox status is a factor involved in maintaining protein stability and function (Ottaviano et al., 2008) thus an underlying factor for many chronic diseases attributed to adverse changes in the extracellular redox environment that initiate changes in intracellular signal transduction (Marinho et al., 2014). The Kelch-like ECH-associated protein 1 (Keap1)-nuclear factor erythroid 2-related factor 2 (Nrf2)-antioxidant response elements (ARE) pathway is an important example of a major mechanism whereby the cell redox balance controls cell signaling in order to protect cells from oxidative stress (Kensler et al., 2007). Nrf2 denotes a member of a family of basic leucine transcription factors that bind to an ARE, located on the promoter region 77 of genes and which have various roles in regulation of redox, DNA repair, and prevention of apoptosis; in addition to Phase I, II, and III drug/xenobiotic metabolism (Schmidlin et al., 2019). Healthy functional intestinal epithelial cells are important to enable passive nutrient absorption, and act as a defense barrier against potential xenobiotic components (Vancamelbeke & Vermeire, 2017). Under different harmful stimuli, such as invading pathogenic bacteria and exposure to toxic foreign chemicals, cells respond by secreting cytokines and chemokines (Malago et al., 2005; Yamamoto et al., 2003) to neutralize onset of oxidative stress. To study the human intestine, the Caco-2 cell was established as a model to examine the function of the intestinal epithelial barrier (Sambuy et al., 2005). Past research has addressed the direct scavenging activity of different phenolic acids (RiceEvans et al., 1996). More recently, a research focus on this topic has shifted to determine more precisely the indirect effects of phenolic acids on cell redox status under the influence of autoxidation reactions. The objective of the research chapter was to compare the relative capacity of different phenolic acids to bring forward changes in extracellular redox homeostasis in differentiated Caco-2 intestinal cells. The relative capacity of the different phenolic acids to undergo autoxidation was first assessed by measuring the temporal pattern of H2O2 generated from phenolic acids when present in culture media, both without the presence of cells as reported in Chapter 2, but also in culture media contained Caco-2 cells. This parallel information that includes the presence of cells was carried forward to explain the relative capacity for autoxidation of different phenolic acids and subsequent effects to activate intracellular Nrf2 cell signaling in Caco-2 cells under standard Caco-2 cell culture conditions. 78 4.2 Materials and methods 4.2.1 Materials The following chemicals were purchased from Sigma (St. Louis, MO, USA): caffeic acid (CA) (≥98% pure), chlorogenic acid (CGA) (≥98% pure), ferulic acid (FA) (≥99% pure) and gallic acid (GA) (≥99% pure). Other chemicals included Dulbecco's Modified Eagle's Medium (DMEM), phosphate buffered saline (PBS), penicillin/streptomycin antibiotics, bovine serum albumin (BSA), Bradford reagent, 3-(4,5-diethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and sodium dodecyl sulfate (SDS). Fetal bovine serum (FBS) was purchased from Gibco® (Grand Island, NY, USA). Catalase, H2O2 standard, Hydrogen Peroxide Assay Kit, Nuclear Extraction Kit, and Nrf2 Transcription Factor ELISA Assay Kit was purchased from Cayman Chemical Company (Ann Arbor, MI, USA). EndoFree Mini Plasmid Kit II was purchased from TIANGEN (China). The BTXPRESS electroporation solution was purchased from BTX (USA). Aquaporin inhibitor DFP00173 was purchased from MedChem Express (MCE, MonmouthJunction, NJ 08852, USA). Anti-Histone, anti-Glyceraldehyde-3-Phosphate Dehydrogenase (anti-GAPDH), anti-beta actin, anti-Nrf2 and goat anti-mouse IgG H&L horseradish peroxidase were purchased from Abcam company (Abcam, Cambridge, UK). Nitrocellulose membranes (0.2 µm, 7×8.4 cm), 5% non-fat milk powder, 10% Mini-PROTEAN® TGXTM Precast Protein Gels, Tris-buffered saline, Tween® 20 detergent, Tris/glycine/SDS running buffer, Tris/glycine transfer buffer and Western ECL substrate were purchased from Biorad (Bio-Rad Laboratories, Hercules, CA, USA). Caco-2 cells were purchased from American Type Culture Collection (Manassas, VA, USA). 79 4.2.2 Caco-2 cell culture Caco-2 cell culture was performed as described in Section 3.2.2. 4.2.3 H2O2 disappearance kinetics in differentiated Caco-2 cells To test the capacity of differentiated Caco-2 cells to utilize H2O2, when cultured under typical conditions, two concentrations (0.1 mM and 1mM) of H2O2 were added directly to the culture media containing cells and changes in extracellular H2O2 were measured over a 60 min time period. Quantification of H2O2 was made from a standard curve. Disappearance of the H2O2 was determined from values transformed to a log concentration and expressed as a ratio from time zero. The disappearance rate of H2O2 followed pseudo-first order kinetics and was described according to: where kapp is the apparent first-order rate constant; [H2O2] is the concentration of H2O2 in the system at any time t, and [H2O2]0 is the concentration of H2O2 in the system at time zero, respectively. A linear regression was used to fit the data and produced equations for 0.1mM H2O2 (y = -0.1063x – 0.5743; R2 = 0.97) and 1 mM H2O2 (y = -0.1363x + 0.1754; R2 = 0.97), respectively. 80 4.2.4 H2O2 determination in culture media in the presence of Caco-2 cells Caco-2 cells were seeded in 96-well plates at a density of 1×105 cells/cm2 and grown in DMEM media for 21 days to reach differentiation. To determine H2O2 generated by different phenolic acids in the cell-based system, CA, CGA, FA and GA, respectively, were tested at 1 mM in DMEM, supplemented with 100 U/ml of penicillin and 100 µg/mL of streptomycin (Sigma, St. Louis, MO, USA). Samples were incubated at 37 oC under a 5% CO2 atmosphere for 24 hr and the H2O2 determination was performed using a Hydrogen Peroxide Assay Kit (Item No. 600050, Cayman Chemical Company, Ann Arbor, MI, USA). 4.2.5 MTT reduction assay to assess phenolic acid cytotoxicity The potential cytotoxicity of four specific phenolic acids cultured with differentiated Caco-2 cells was evaluated using MTT assay. Briefly, samples were incubated with Caco-2 cells in a 96-well plate containing a seeding density of 1×105 cells/cm2 at 37oC under atmosphere conditions of 5% CO2 for 24 hr. After removal of phenolic acids, the viability of treated Caco-2 cells was evaluated as described in Section 2.2.6. 4.2.6 Confocal microscopy and HyPer-3 imaging To visualize the effect of different phenolic acids derived H2O2 on HyPer-3 expressed Caco-2 cells, live-cell imaging was performed using confocal microscopy. Transfected Caco-2 cells were seeded on 8-well plates and incubated at 37oC under standard culture conditions for up to 48 hr to equilibrate. Cells were then treated with phenolic acids, both with, or without pre-treatment of an AQP inhibitor, DFP00173. After the addition of phenolic acids to cultured cells, images were acquired every 20 sec for up to 20 min using a Spinning disk Perkin Elmer confocal 81 microscopy (Leica DMi8 inverted microscope, Leica Microsystems, Wetzlar, German), equipped with high-sensitivity Hamamatsu 9100-02 charged-coupled device camera (Hamamatsu Photonics, Hamamatsu, Japan). Images collected from lasers at both 405 nm and 488 nm were processed using Improvision Volocity software (Improvision, Coventry, UK). The ratio of mean fluorescence intensity of 488/405 nm ratio was quantified using Image J (National Institutes of Health, Bethesda, MD) as reported earlier in Chapter 3. 4.2.7 Nuclear isolation of Caco-2 cells To isolate Nrf2 from differentiated Caco-2 cells, the nuclear fraction was recovered from cell lysates without contamination from the cytoplasmic fraction. This was accomplished using a Nuclear Extraction Kit (10009277, Cayman Chemical Company, Ann Arbor, MI, USA), based on methods described by the manufacturer. Briefly, Caco-2 cells were collected by scraping them free from the plates using a rubber spatula, and then processed by centrifugation at 300 × g for 5 min at 4 oC. After discarding the supernatant, the cell pellet was re-suspended in 5 mL ice-cold PBS/Phosphatase inhibitor solution and then re-centrifuged at 300 × g for 5 min at 4 oC. This step was repeated by adding 500 µL of ice-cold 1 × Complete Hypotonic Buffer to the cell pellet and then mixed gently by pipetting. After incubation on ice for 15 min, 100 µL of 10% Nonidet P-40 Assay Reagent was added, followed by more gently mixing before centrifuging the samples again at 14,000 × for 30 sec at 4 oC. The supernatant which contained the cytosolic fraction was removed completely. The washed pellet was then resuspended in 100 µL ice-cold 1 × Complete Nuclear Extraction Buffer and vortexed vigorously for 15 sec, followed by chilling on ice for 30 min. Afterwards, tubes were centrifugation again at 14,000 × for 10 min at 4 oC, and the nuclear fraction was collected. The total protein content of the recovered nuclear fraction 82 was quantified using the Bradford reagent. The protein content was adjusted to the 2 mg/mL using ice-cold 1 × Complete Nuclear Extraction Buffer. The purity of the isolated nuclear fraction, and the cytoplasm fraction, respectively, was confirmed by checking for Histone and GAPDH expression using western blotting assay. Confirmation of the purity of the nuclear fraction was made by the observation that Histone expression was present in the nuclear fraction, but absent in the cytoplasm fraction. In contrast, GAPDH expression was observed only in the cytoplasm and not in the nuclear fraction. 4.2.8 Analysis of Nrf2 binding activity by ELISA Caco-2 cells were seeded at a density of 1×105 cells/cm2 in a 6-well plate and cultured for 21 days until differentiation was reached. Cells were then treated with different phenolic acid samples for 24 hr. Subsequently, nuclear protein was extracted using nuclear extraction kits, as described above, and Nrf2 was detected using a Nrf2 transcription factor ELISA assay kit (Cayman Chemical Company, Ann Arbor, MI, USA). 4.2.9 Western blot analysis of Nrf2 The expression of Nrf2 in Caco-2 cells was measured using western blotting, as described by Liang and Kitts (Liang & Kitts, 2018). The nuclear fractions were extracted and separated as described in Section 4.2.7. Protein concentration was adjusted to 2 mg/mL using Bradford reagent. Subsequently, samples were run using 10% SDS-polyacrylamide gel electrophoresis by a Mini-PROTEAN® II Multiscreen Apparatus (Bio-Rad Laboratories, Hercules, CA, USA). After electrophoresis, the separated proteins were transferred to a nitrocellulose membrane (0.2 µm, 7×8.4 cm; Bio-Rad Laboratories, Hercules, CA, USA) at 100 V, for 1 hr at 4 oC; this was 83 followed by a non-specific binding blocking step using a 5% non-fat milk solution, at room temperature for 1 hr. After blocking, membranes were washed three times using Tris-buffered saline with 0.1% Tween® 20 detergent (TBST) solution, with gentle shaking for 5 min for each time. Afterwards, membranes were incubated with anti-human primary antibodies Nrf2 (1:1000 dilution) (ab31163, Abcam Inc., Ontario, Canada), or anti-beta actin antibodies (1:1000 dilution) (ab115777, Abcam Inc., Ontario, Canada) dissolved in 3% BSA at 4 oC overnight. Afterwards, membranes were washed three times using TBST solution, with gentle shaking for 5 min for each time, followed by incubation again with secondary antibody horseradish peroxidase-conjugated Anti-lgG secondary antibody for 1 hr (1:1000) (ab97023, Abcam Inc., Ontario, Canada). Subsequently, membranes were washed three times with TBST, followed by reaction against Western ECL substrate (Bio-Rad Laboratories Inc., Woodinville, WA, USA) for 5 min. The ChemiDoc™ MP Imaging System (Bio-Rad Laboratories Ltd., Hercules, CA, USA) was used to visualize proteins. Image Lab 4.1 software (Bio-Rad Laboratories Ltd., Hercules, CA, USA) was used to conduct the densitometry analysis. The expression of Nrf2 was normalized by calculating the density of Nrf2 relative to beta actin. 4.2.10 Statistical analysis All sample analysis was measured in triplicate. Data are expressed as mean ± standard deviation. Data were analyzed by one-way analysis of variance (ANOVA) using IBM SPSS® Data Software (SPSS Statistics/IBM Corp, Chicago IL, USA). Significant differences between means were made using a Least Significant Difference’s (LSD’s) test with p < 0.05 representing a statistically significant difference. 84 4.3 Results and discussion 4.3.1 Kinetics of H2O2 disappearance in culture media containing Caco-2 cells. Differentiated Caco-2 cells displayed depletion of exogenously added H2O2 that followed pseudo-first order kinetics at both low (0.1mM) and high (1.0 mM) concentrations (Figure 4.1). The presence of Caco-2 cells completely depleted the added H2O2 at both 0.1 mM or 1 mM concentrations within 30 min and 40 min, respectively (Appendix Figure B). These relative rates of H2O2 disappearance are similar to other studies using the HEK293 cell model (Sobotta et al., 2013), where a H2O2 bolus was depleted within 1 hr. The short H2O2 half-life can be attributed to a rapid degradation rate by cellular enzymes, namely catalase and peroxidases (Sobotta et al., 2013). The temporal pattern for H2O2 degradation also demonstrates a very efficient mechanism for extracellular H2O2 transport to intracellular H2O2. The capacity of cells from different sources to dispose extracellular H2O2 has been examined (Hashida et al., 2002; Makino et al., 2004; Makino et al., 2008; Makinoet al., 1994; Sasaki et al., 1998), and in general follows a first-order rate constant (Wagner et al., 2013) that occurred also in this experiment with differentiated Caco-2 cells. Several peroxide systems involved in cellular H2O2 dynamics include the peroxiredoxins, glutathione peroxidases and catalase (Adimora et al., 2010; Wagner et al., 2013). The fraction of the extracellular H2O2 removed by cells depends on the flux of H2O2 uptake and the availability of co-factors that are required to catalyze enzyme degradation (Johnson et al., 2010). The biological response of cells first exposed to extracellular H2O2 is, therefore, influenced by exposure/dose (mole cell-1) or flux (mole cell-1s-1) (Antunes & Cadenas, 2001; Guelden et al., 2010; Spitz et al., 1988). 85 Figure 4.1 Disappearance kinetics of H2O2 with different initial H2O2 amount added. Circle dots and triangle dots refer to the initial H2O2 addition level, at 1 mM and 0.1 mM, respectively. The linear regression equation for initial H2O2 level of 100 µM, and 1 mM was y = -0.1063x – 0.5743 (R2 = 0.97), and y = -0.1363x + 0.1754 (R2 = 0.97), respectively. 4.3.2 Production of H2O2 from phenolic acids and subsequent depletion by Caco-2 cells In the previous chapter, it was demonstrated that phenolic acids generated H2O2 when incubated in cell culture media in the absence of cells, and that the production of H2O2 was dependent on the specific phenolic acid type and its concentration, respectively. In this study, H2O2 concentrations measured in media was related to both the type and concentration of phenolic acids (Table 4.1). This was particularly true for CA, CGA, respectively. In the case of FA, extracellular H2O2 was not detectable. In contrast, the presence of GA with cells produced detectable extracellular H2O2; however, the concentrations decreased dramatically with time indicating that uptake was greater than generation. In the case of GA, the significant differences noted between H2O2 levels both with and without cells demonstrated the capacity of GA to autoxidize and be taken up by differentiated Caco-2 cells to utilize H2O2. From this finding, a subsequent experiment was conducted to confirm that the pattern of disappearance of phenolic acid generated extracellular H2O2 was attributed to intracellular transport and uptake by Caco-2 cells. -10-8-6-4-200 10 20 30 40 50 60 70Time (min)1 mM0.1 mM ln(H2O2/H2O20) 86 Table 4.1 Comparison of H2O2 level generated by phenolic acids in the presence or absence of cells1. 1 mM 10 min 30 min 60 min 90 min 120 min 720 min 1440 min CA - Cell n.d. 1.03 ± 0.011 6.78 ± 0.51 11.28 ± 0.51 18.67 ± 1.58 309.14 ± 24.79 401.80 ± 11.21 + Cell n.d. n.d. n.d. n.d. n.d. n.d. n.d. CGA - Cell n.d. n.d. 2.72 ± 0.032 4.90 ± 0.13 8.39 ± 0.80 124.80 ± 14.06 229.69 ± 6.60 + Cell n.d. n.d. n.d. n.d. n.d. n.d. n.d. FA - Cell n.d. n.d. n.d. n.d. n.d. n.d. n.d. + Cell n.d. n.d. n.d. n.d. n.d. n.d. n.d. GA - Cell 66.45 ± 4.21 122.29 ± 2.25 152.09 ± 8.96 212.87 ± 1.03 331.33 ± 9.61 1021.59 ± 28.47 1030.62 ± 41.93 + Cell 38.49 ± 2.64** 28.99 ± 2.75*** 30.27 ± 0.97*** 16.48 ± 0.66*** 15.07 ± 0.65*** 5.16 ± 0.47*** n.d. 1 Data are expressed as mean ± standard deviation (n=3). Significant differences were performed by Student’s t-test comparing H2O2 level in the cell-based and cell-free medium. *** represents p < 0.001; **represents p < 0.01; *represents p < 0.05. n.d.= not detectable. 87 4.3.3 Extracellular production of H2O2 by phenolic acids influences intracellular H2O2 concentration Figure 4.2 shows the live-cell imaging that reflect changes in HyPer-3 fluorescence in differentiated Caco-2 cells, when incubated with CA, CGA, FA and GA, respectively, and also with and without pre-treatment of an AQP inhibitor, DFP00173. Caffeic acid slightly increased the HyPer-3 ratio, relative to control cells, and pre-treatment of DFP00173 inhibitor mitigated the increase in HyPer-3 ratio. The presence of CGA and FA, respectively, produced a slight decrease in HyPer-3 ratio relative to the control, and pre-treatment of cells with DFP00173 mitigate the decrease in observed HyPer-3 ratio. Gallic acid, on the other hand increased (p<0.05) the HyPer-3 ratio, and pre-treatment of DFP00173 reduced (p<0.05) the increase in HyPer-3 ratio. These results provide evidence for a control mechanism that regulates extracellular induced changes in intracellular H2O2 levels that is specific to the type of phenolic acid. Phenolic acids varied dramatically in relative capacity to increase extracellular H2O2 level needed to produce detectable changes in intracellular H2O2. The latter observation can be attributed in part by the activity of AQP receptors that regulate H2O2 transport, since exposure of cells to the AQP inhibitor, DFP00173, produced an effect on intracellular H2O2. It can be concluded from these findings that pre-treatment of cells with DFP00173 effectively blocked H2O2 transport between extracellular and intracellular spaces by interfering with AQP activity. This in turn influenced the balance between extracellular and intracellular H2O2. 88 01230 200 400 600 800 1000 1200Hyper-3 Fluoresence Intensity488/405 nmTime (second)Control CA Inhibitor + CA(a)01230 200 400 600 800 1000 1200Hyper-3 Fluoresence Intensity488/405 nmTime (second)Control CGA Inhibitor + CGA(b) 89 Figure 4.2 Live-cell imaging of changes in HyPer-3 fluorescence upon treatment of CA (a), CGA (b), FA (c), and GA (d) with or without pre-treatment of DFP00173 for 20 min on differentiated Caco-2 cells relative to cells without any treatments. The figure shows the ratio of EX488/FL525 and EX405/FL525 signals on exposure to phenolic acid monitored for 20 min. Error bars are mean ± standard deviation (n=6). 01230 200 400 600 800 1000 1200Hyper-3 Fluoresence Intensity488/405 nmTime (second)Control FA FA + inhibitor(c)0123450 200 400 600 800 1000 1200Hyper-3 Fluoresence Intensity488/405 nmTime (second)Control GA Inhibitor + GA(d) 90 4.3.4 Phenolics affect extracellular H2O2 that regulates intracellular cell signaling Four specific phenolic acids, namely CA, CGA, FA, GA were examined to determine relative effect on translocation of Nrf2 from cytoplasm to nucleus. A previous experiment (Appendix Figure C) showed that all phenolic acids had no apparent cytotoxicity to differentiated Caco-2 cells at the concentrations used herein required to trigger Nrf2 responses. Exposing cells to different phenolic acids, at different concentrations, over a 24 hr period was adequate to induce translocation of Nrf2 from cytoplasm to nucleus, assessed using an ELISA assay (Figure 4.3). The purity of the isolated nuclear fraction, and cytoplasm fraction was confirmed by presence of Histone and GAPDH expression using western blotting (Appendix Figure D). Treating cells with the lowest concentration of each phenolic acid, and an accompanying H2O2 standard (e.g., 10 µM), were both insufficient to trigger Nrf2 signaling. Increasing concentrations of both, for example GA and H2O2 concentrations to 100 µM, respectively, produced almost identical increases in Nrf2 cell signaling (e.g., 114.8% and 115.5%). Similarly, at this concentration, further activation of Nrf2 cell signaling was observed from CA and CGA, but not for FA. Gallic acid activated Nrf2 cell signaling to the highest level, or to 253.3% relative to control (p<0.001). This was followed by CA 170.9% (p<0.001), and CGA 128.1% (p<0.01). Treating Caco-2 cells with H2O2 at the same concentration also produced a significant increase in Nrf2 signaling that was 147.8% relative to control (p<0.01). To further characterize the effect of H2O2 generated from phenolics to directly trigger Nrf2 signaling, catalase was added as treatment since it would lower H2O2. Catalase, used at the 1 µg/mL concentration previously reported in studies described in Chapter 2 lowered (p<0.05) H2O2. Thus, incubation of Caco-2 cells with phenolic acids, in the presence of catalase reduced H2O2 produced from the autoxidation reaction sufficiently and this effect resulted in reduced 91 nuclear Nrf2 signaling (Figure 4.4). This observation also showed the capacity of catalase to mitigate the activation of Nrf2 translocation induced by autoxidation of phenolic acids. Specifically, when in the presence of catalase treatment, Nrf2 translocation induced by autoxidation of GA was lowered from 296.9% to 149.8% (p<0.001). For CA, activation of Nrf2 translocation induced by autoxidation also decreased from 204.3% to 130.7% (p<0.001). The result was similar for CGA, where activation of Nrf2 translocation induced by autoxidation of CGA was reduced (p<0.01) from 138.9% to 117.1%, or a 22% deduction. Moreover, the direct activation of Nrf2 translocation induced by the addition of H2O2 standard was also decreased (p<0.01) from 152.6% to 110.7%, (e.g., 42% reduction) when in the presence of catalase. These results confirm that the catalase treatment of cells diminished activation of Nrf2 translocation, by restricting Nrf2 cell signaling, which originally occurred due to autoxidation of phenolic acids; the extent being dependent on the type of phenolic acid. As mentioned earlier, intracellular transport of H2O2 is controlled by extracellular membrane receptors, termed AQPs, which by facilitating uptake of H2O2 could also indirectly control activation of Nrf2 cell signaling. The AQP inhibitor, DFP00173, was used to test this theory by pre-treating differentiated Caco-2 cells before individual phenolic acids were introduced. Results shown that pre-treatment of differentiated Caco-2 cells with DFP00173 was effective at modulating phenolic acid associated Nrf2 cell signaling activation (Figure 4.5). For example, pre-treatment of cells with AQP inhibitor DFP00173, reduced activation of Nrf2 translocation induced by GA significantly (p<0.001) from 279.1% to 189.2%, or, almost 90%. Activation of Nrf2 translocation induced by CA and CGA were also decreased significantly (p<0.01) from 192.6% to 151.1%, or 42%, for CA, and from 145.6% to 111.7%, or 34% for CGA, when DFP00173 was used to pre-treat cells. The activation of Nrf2 translocation induced 92 by H2O2 alone, also decreased significantly (p<0.01) from 162.3% to 127.7 %, or 35 %. Qualitative, visual changes in Nrf2 activation determined using western blot (Figure 4.6), confirmed the importance of phenolic acids to autoxidize and produce H2O2 for activation of Nrf2 translocation. The experiments also showed that AQPs are also required to facilitate H2O2 uptake and thus are important for activating intracellular Nrf2 cell signaling indirectly. Figure 4.3 shows relative activation of nuclear translocation of Nrf2 in Caco-2 cells by various phenolic acids. Cells were treated with CA, CGA, FA, and GA at different concentration (10 µM, 100 µM and 1000 µM) for 24 hr, where the control refers to cells without any treatments. The positive control has H2O2 alone at the same concentration for phenolic acids. Data are expressed as mean ± standard deviation (n=3). Significant differences were performed by Student’s t-test with ***representing p<0.001, **representing p<0.01, *representing p<0.05, by comparing sample with control. * ***********050100150200250300ControlH2O2CACGA FA GAH2O2CACGA FA GAH2O2CACGA FA GA10 µM 100 µM 1000 µMNrf2 activation (%relative tocontrol) 93 Figure 4.4 shows activation of nuclear translocation of Nrf2 in Caco-2 cells by various phenolic acid (1 mM) with or without the presence of catalase. The positive control was H2O2. Data are expressed as mean ± standard deviation (n=3). Significant differences were performed by Student’s t-test with ***representing p<0.001, **representing p<0.01, *representing p<0.05, by comparing sample in the presence or absence of catalase. Figure 4.5 shows activation of nuclear translocation of Nrf2 in Caco-2 cells by various phenolic acid (1 mM) with or without the pre-treatment of DFP00173. The positive control was H2O2. Data are expressed as mean ± standard deviation (n=3). Significant differences were performed by Student’s t-test with ***representing p<0.001, **representing p<0.01, by comparing sample with or without DFP00173 pre-treatment. 94 Figure 4.6 Representative western blot gel showing the activation of nuclear translocation of Nrf2 in Caco-2 cells when treated by different phenolic acids, CA (a), CGA (b), FA (c), GA (d) (1 mM) +/- DFP00173 or +/- catalase (CAT). Bar graphs show densitometry analysis of ratio of Nrf2 relative to beta actin determined from corresponding western blots. Results are expressed as mean ± standard deviation (n=3). Different letters indicate significant differences (p<0.05) exist among different treatments. Significance between treatments was analyzed by one-way ANOVA and LSD’s test (SPSS software). Superscripts with different letters (a, b, c) are significantly different (p<0.05). 95 The concept of oxidative stress describes the physiological deviations occurring from a steady-state redox status that underlines the term “healthy living” (Sies, 2021; Sies et al., 2022). Unlike oxidative stress which causes detrimental effect to cells, oxidative eustress evokes the cells defense systems to respond to stress thereby allowing adaptation to occur (Sies et al., 2022). This feedback, or counter regulation effect has been shown to confer resistance to repeated environmental stresses and eventually promotes an increase in lifespan in multiple organisms (Sies et al., 2022). As a consequence, a new gene expression pattern, including those that can up-regulate antioxidant enzymes is established in the cell to control oxidative stress reactions (Sies, 2021). Nrf2 cell signaling is one example of an intracellular mediator that has a role to induce protection from temporal thresholds of potential oxidants that pert urbate the oxidative balance required to maintain homeostasis (Calabrese & Kozumbo, 2021; Holmström & Finkel, 2014). The transcription factor Nrf2 is a key component of the cell response to oxidative stress, whereas Keap1/Nrf2/ARE is the prevalent antioxidant signaling pathway. Under normal conditions, the transcription factor Nrf2 is bound to the actin-anchored protein Keap1, and this interaction retains the Nrf2 in the cytoplasm while maintaining a low basal expression of Nrf2-regulated genes (Kensler et al., 2007). Human Keap1 has 27 cysteine residues, and several are known to be primary sensors for stress signals. Hence, modification on these critical cysteine residues produces conformational changes in Keap1, which liberates Nrf2 from Keap1. After being released from Keap1, Nrf2 translocated to the nucleus and transactivates the expression of cytoprotective genes, thereby enhancing cell survival (Kensler et al., 2007). The role of polyphenols on activation for Nrf2 signaling pathway has been widely studied in different cell types (Liang & Kitts, 2018; Zhou et al., 2019), and different mechanisms have been addressed 96 (Erlank et al., 2011; Kanner, 2020). In the present study, a greater examination of the role of intracellular H2O2, a by-product of phenolic acid autoxidation, was shown to be directly linked to regulation of redox signaling, a pre-requisite to control physiological oxidative stress (Sies, 2021; Sies et al., 2022). Former studies have used different delivery methods of H2O2, that include bolus exposure versus steady-state exposure, and results on cellular biological responses varied considerably (Marinho et al., 2013a; Sobotta et al., 2013). In the current study, the phenolic acids tested in cell culture media for 24 hr were shown to generate H2O2 at different rate patterns but typically did not compromise Caco-2 cell viability. This in turn enabled the demonstration that Nrf2 upregulation by H2O2, resulting from phenolic acid autoxidation, varied depending on the type of phenolic acid. Furthermore, by adding catalase to remove extracellular H2O2, it was confirmed that autoxidation of phenolic acids produces H2O2 in culture media, was a potent chemical inducer to trigger Nrf2 signaling in intestinal epithelial cells. 4.4 Conclusions This study used the HyPer-3 method, described in a previously chapter, to characterize the temporal extracellular and intracellular flux of H2O2 in differentiated Caco-2 intestinal cells. This information was used to describe the underlying mechanism for H2O2 to trigger cell signalling, relevant to antioxidant and anti-inflammatory reactions specific to differentiated Caco-2 epithelial cells. Additional experiments were performed to explain the observed phenolic acid specific effect on cell signalling mechanisms, related to autoxidation and intracellular H2O2 flux, by examining the indirect role of AQPs to influence H2O2 induced Nrf2 signaling. 97 Chapter 5: Phenolic acids as regulators of intestinal inflammation pathways using a Caco-2 and RAW 264.7 co-culture model 5.1 Introduction Intestinal epithelial cells have important roles for body function that include enabling passive nutrient absorption and acting as a defense barrier against potential xenobiotic components, pathogens and allergens. In the previous chapters, experiments were designed using a cell mono-culture model designed for Caco-2 cells to provide information on redox status and function that were altered in the presence of phenolic acids. These in vitro, cell based, approaches, albeit useful, have limitations in extrapolating data to a more complex multicellular matrix that exists in vivo. Experiments that use a co-culture of more than one cell type were developed to gain a greater understanding on how cellular information can be communicated between multiple cells to ultimately protect intestinal cell integrity and function. As sentinels in the innate immune system, macrophages exhibit adaption to environmental changes that precede changes in tissue physiology in many examples of human disease (Ponzoni et al., 2018; Wynn et al., 2013). Thus, it is important to understand the hallmarks of a macrophage response to alterations in extracellular redox. The RAW 264.7 cell, is a macrophage murine cell line that has been used to mimic murine bone marrow derived macrophages in culture, in terms of cell surface receptors as well as in response to microbial ligands involving Toll-like receptors (Berghaus et al., 2010; Ponce de León-Rodríguez et al., 2019). This cell line has a history of use to evaluate the effectiveness of bioactivity of natural products, as well as to predict potential subsequent inflammatory related effects on primary cells 98 (Galvez-Llompart et al., 2013). The responses of the RAW 264.7 cell line to environmental stress is useful to model potential human de novo responses that involve nitric oxide as a principal mediator. In this study, RAW 264.7 macrophage cells were used to co-culture with intestinal epithelial Caco-2 cells to further understand the cell-based interactions that are involved with demonstrating the potential effects of phenolic acids on regulation of extracellular redox status and cell functionality of intestinal Caco-2 cells (Ashfaq et al., 2006; Ottaviano et al., 2008). Activated RAW 264.7 macrophages cells have been characterized to respond to a number of relevant inflammatory cytokines, including prostaglandin E2, interleukin 6 (IL-6) and tumor necrosis factor (TNF-α), with a notable release of nitric oxide. An increase in inflammatory cytokine production is connected with modulation of function of tight junction proteins which result in changes in permeability in a variety of epithelial tissues (Kim et al., 2021; Rao, 2008; Tazuke et al., 2003; Utech et al., 2005; Yang et al., 2003). Nitric oxide is a well-studied inflammatory mediator and a strong free radical when reacting with superoxide to produce peroxynitrite, and subsequently can lower epithelial tight junction function (Rao, 2008). This is noteworthy, since a compromise to the integrity of gut barrier will result in a leaky gut syndrome and increased exposure to external pathogens, endotoxins, antigens, and pro-inflammatory cytokines which enter blood circulatory or lymphoid systems to trigger local intestinal pro-inflammatory responses and affect gastrointestinal function. It is vital to maintain the integrity of intestinal epithelial cells, and to prevent compromise to the gut barrier which will lead to a dysfunctional intestinal epithelial cell. Studies have demonstrated that dietary phytochemicals, such as polyphenolic compounds, reduce inflammatory cytokine induced tight junction damage (Kim et al., 2017; Suzuki & Hara, 2011; Ulluwishewa et al., 2011); however, these studies were 99 conducted using mono-culture model, and there is less known about the structure function of bioactive phenolics to protect intestinal epithelial cells using co-culture with cells that are not only of intestinal origin, but also influenced by neighboring immune cells, such as macrophage. The objective of this chapter was to obtain a detailed mechanistic understanding on how different phenolic acids, with subtle contrasting structure but known antioxidant activity, affect the intracellular regulation of inflammatory response molecules, and subsequently the capacity to protect the integrity of the gut barrier integrity. To achieve this goal, a cell-based model consisting of inflamed RAW 264.7 macrophage cells co-cultured with Caco-2 intestinal cells was used to measure the relative capacity of different phenolic acids to mitigate an immune response in inflamed macrophage cells that communicate with intestinal cells. 5.2 Materials and methods 5.2.1 Materials The following chemicals were purchased from Sigma (St. Louis, MO, USA): caffeic acid (CA) (≥98% pure), chlorogenic acid (CGA) (≥98% pure), ferulic acid (FA) (≥99% pure) and gallic acid (GA) (≥99% pure). Other chemicals included N-(1-Naphthyl)ethylenediamine dihydrochloride, sulphanilamide, phosphoric acid, Dulbecco's Modified Eagle's Medium (DMEM), bovine serum albumin (BSA), phosphate buffered saline (PBS), penicillin/streptomycin antibiotics, hanks’ balanced salt solution (HBSS), 3-(4,5-diethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), lipopolysaccharide (LPS), interferon gamma (IFN-γ) and sodium dodecyl sulfate (SDS). Fetal bovine serum (FBS) was purchased from Gibco® (Grand Island, NY, USA). Peroxynitrite Assay Kit (ab 233469), Human interleukin 8 (IL-8) ELISA Kit (ab214030), Mouse IL-6 ELISA Kit (ab222503), Mouse TNF alpha ELISA 100 Kit (ab208348), and anti-ZO-1 (ab 216880, Abcam Inc., Ontario, Canada), anti-Occludin (ab 31721, Abcam Inc., Ontario, Canada) and anti-beta actin (ab115777, Abcam, Cambridge, UK) antibodies were purchased from Abcam company. Human Aquaporin-3 ELISA kit was purchased from MyBioSource (MBS9715866, MyBioSource, San Diego, CA, USA). Hydrogen Peroxide Assay Kit, Nuclear Extraction Kit, NF-κB Transcription Factor ELISA Assay Kit, and Nrf2 Transcription Factor ELISA Assay Kit was purchased from Cayman Chemical Company (Ann Arbor, MI, USA). Caco-2 cells and RAW 264.7 (TIB-71) cells were purchased from American Type Culture Collection (Manassas, VA, USA). 5.2.2 Cell culture Caco-2 cell culture was performed as described in Section 3.2.2. RAW 264.7 cells (TIB-71, American Type Culture Collection, Manassas, VA, USA) were cultured in DMEM containing 4.5 g/L glucose, 100 U/ml of penicillin and 100 µg/mL of streptomycin (Sigma, St. Louis, MO, USA), and 10% FBS (Invitrogen, Canada) at 37oC under a 5% CO2 atmosphere with sub-culture every 2-3 days. The passage number used was 21-40. 5.2.3 Co-culture for determination of intestinal inflammation Caco-2 cells were seeded at a density of 1×105 cells/cm2 in transwell insert (0.4 µm pore size; Corning Costar Corp., USA). Cells were grown in DMEM medium for 21 days to reach differentiation with culture media changed every 2-3 days. On day 20, RAW 264.7 cells were seeded on the basolateral side of the transwell insert at a density of 1×106 cells/well and incubated overnight to facilitate adherence to the well. On day 21, differentiated Caco-2 cells on 101 the insert were co-cultured with RAW cells. To activate the RAW cells, a pro-inflammatory inducer cocktail (50 ng/mL LPS + 10 ng/mL IFN-γ) was used. Different phenolic acids were also added in the basolateral part of the co-culture model with the inducer (Figure 5.1). This model was used to determine underlying mechanisms where structurally different phenolic acids regulate Caco-2 cell inflammation and cell function, when triggered by inflamed RAW cells. Figure 5.1 A schematic description of the stable co-culture method used. Transwell inserts containing differentiated Caco-2 cells were inserted onto plates that contained RAW 264.7 cells (this represented the basolateral space). To simulate gut inflammation, an inducer treatment (50 ng/mL LPS + 10 ng/mL IFN-γ) was used and added to the basolateral compartment of the co-culture system for 24 hr. Phenolic acids were individually added to the basolateral part of the co-culture and incubated for 24 hr to determine the relative effect of phenolic acids on regulation of alteration of redox triggered by inflamed RAW264.7 cells in the co-culture model 5.2.4 Assessment of cell viability using MTT Following exposure of cells to various phenolic and inducer treatments, respectively, the medium was removed and cells were washed with PBS for three times. Cell viability was evaluated using the MTT assay, based on the method described earlier in Section 2.2.6. 5.2.5 H2O2 determination Assay on H2O2 determination from basolateral part was determination as described in Section 4.2.4. 102 5.2.6 Analysis of NF-κB activation in RAW 264.7 cells using ELISA assay The nuclear part from RAW 264.7 cells were isolated using a Nuclear Extraction Kit (10009277, Cayman Chemical Company, Ann Arbor, MI, USA), based on methods described by the manufacturer. Analysis of the NF-κB activation was performed using a NF-κB transcription factor ELISA assay kit (Cayman Chemical Company, Ann Arbor, MI, USA), based on methods described by the manufacturer. 5.2.7 Cytokine TNF-α, IL-6 and IL-8 determination Measurements of cell biomarkers, specifically TNF-α (ab208348), IL-6 (ab222503), IL-8 (ab214030) levels, were determined from supernatant collected from the basolateral location, determined using commercially available ELISA kits from the Abcam company (Abcam, Cambridge, UK), according to the manufacturer’s instructions. Each cytokine concentration was derived from a standard curve of individual biomarkers, with final calculations adjusted for sample dilutions. Normal RAW 264.7 cells and Caco-2 cells were found to produce only detectable amounts of IL-8, and IL-6, respectively. To differentiate the source of interleukin produced from each cell line, IL-8 from Caco-2 cells was measured using Human IL-8 ELISA kit (ab214030, Abcam Inc., Ontario, Canada) and IL-6 from murine macrophage was determined using Mouse IL-6 ELISA kit (ab222503, Abcam Inc., Ontario, Canada). Tumor necrosis factor alpha was determined using Mouse TNF alpha ELISA kit (ab208348, Abcam Inc., Ontario, Canada). 103 5.2.8 Nitric oxide determination To study the nitric oxide production from RAW cells, 50 µL of medium was collected from the basolateral compartment and transferred to a 96-well plate, where it was processed by adding the Griess reagent (0.1% N-(1-Naphthyl)ethylenediamine dihydrochloride and 1% sulphanilamide in 5% phosphoric acid; 1:1) to each well. The color change that occurred specifying the nitric oxide concentration was measured using a spectrophotometer (Multiskan Ascent, ThermoLabsystems, Finland) at 540 nm. 5.2.9 Peroxynitrite determination Peroxynitrite is a highly reactive, free radical generated from the reaction between nitric oxide and superoxide. Peroxynitrite concentrations were determined using the Peroxynitrite Assay Kit (ab 233469), purchased from Abcam company (Abcam, Cambridge, UK). Briefly, peroxynitrite sensor green was added to the basolateral part of the co-culture model, and culture media was collected with fluorescence readings taken using a fluorescence plate reader (Ex/Em = 490/530 nm). 5.2.10 Isolation of Caco-2 nuclear & cytosolic fractions The nuclear and cytosolic fractions collected from Caco-2 cells were isolated as described in Section 4.2.7. 5.2.11 Analysis of Nrf2 binding activity by ELISA Analysis of the Nrf2 binding activity was performed as described in Section 4.2.8. 104 5.2.12 Aquaporin-3 expression in Caco-2 cells The expression of Caco-2 AQP3 was measured from cytosolic fractions recovered from cells using the ELISA kit (MBS9715866, MyBioSource, San Diego, CA, USA). Cytosolic fractions were extracted and separated from the nuclear fraction as described in Section 4.2.7. Expression of AQP3 was measured based on manufacturer’s instructions. 5.2.13 Epithelial monolayer resistance Epithelial monolayer resistance was measured based on the methods described previously (Chen et al., 2017). Briefly, Caco-2 cells with a density of 2.5×105/cm2 were seeded in a 24-well translucent, polyethylene terephthalate membrane transwell inserts (0.4 µm) (BD Biosciences, San Jose, CA, USA). Cells were grown in DMEM medium for 21 days to reach differentiation. Transepithelial electrical resistance (TEER) values were measured using a volt-ohmmeter (Millicell® ERS, Millipore, Bedford, MA, USA). Before each of measurement, cells were washed three times with PBS, followed by a 10 min equilibration step in HBSS. TEER values were measured three times on each well. A relative epithelial resistance (%) was calculated according to the initial value taken at T=0 min. 5.2.14 Tight junction protein expression The expression of tight junction protein ZO-1 and Occludin, respectively in Caco-2 cells was measured by western blotting (Chen et al., 2017). Cytosolic fractions were extracted and protein concentration was adjusted to 2 mg/mL. Subsequently, samples were run on 4-12% SDS-polyacrylamide gel (Bio-Rad Laboratories, Hercules, CA, USA) electrophoresis using Mini-PROTEAN® II Multiscreen Apparatus (Bio-Rad Laboratories, Hercules, CA, USA). After 105 electrophoresis, the separated proteins were transferred to a nitrocellulose membrane (0.2 µm, 7×8.4 cm; Bio-Rad Laboratories, Hercules, CA, USA) and processed at 100 V for 1 hr at 4 oC. This step was followed by blocking the non-specific binding, using a 5% non-fat milk solution, at room temperature for 1 hr. After blocking, membranes were washed three times using Tris-buffered saline with 0.1% Tween® 20 detergent (TBST) solution, with gentle shaking for 5 min. Afterwards, membranes were incubated with primary antibodies, namely anti-ZO-1 (1:1000 dilution) (ab 216880, Abcam Inc., Ontario, Canada), anti-Occludin (ab 31721, Abcam Inc., Ontario, Canada) or anti-beta actin antibodies (1:1000 dilution) (ab115777, Abcam Inc., Ontario, Canada) dissolved in 3% BSA kept at 4 oC overnight. Afterwards, membranes were washed three times using TBST solution, with gentle shaking for 5 min for each time. This step was followed by incubating samples with a secondary antibody horseradish peroxidase-conjugated Anti-lgG secondary antibody for 1 hr (1:1000) (ab97023, Abcam Inc., Ontario, Canada). Subsequently, membranes were washed three times with TBST, followed by exposure to a reaction against Western ECL substrate (Bio-Rad Laboratories Inc., Woodinville, WA, USA) for 5 min. The ChemiDoc™ MP Imaging System (Bio-Rad Laboratories Ltd., Hercules, CA, USA) was used to visualize proteins from the Westerns Image Lab 4.1 software (Bio-Rad Laboratories Ltd., Hercules, CA, USA) and to conduct the densitometry analysis. The expression of ZO-1 or Occludin, was normalized by calculating the density of each of the target protein relative to beta-actin, the housekeeper protein. 5.2.15 Statistical analysis All analyses were done in triplicate. Data are expressed as mean ± standard deviation and analyzed by Student’s t-test using Microsoft Excel Software (Microsoft Corp., Redmond, WA) 106 or one-way analysis of variance (ANOVA), using SPSS® Data Software (SPSS Statistics/IBM Corp, Chicago IL, USA). Significant differences between treatments means were determined using a Least Significant Difference’s (LSD’s) test set at p < 0.05, using SPSS® Data Software (SPSS Statistics/IBM Corp, Chicago IL, USA). 5.3 Results and discussion 5.3.1 Establishment of a stable co-culture model In this chapter, two stable cell lines were used to establish a co-culture that involved both the differentiated Caco-2 intestinal cell and the RAW 264.7 macrophage cell, respectively. One experiment was performed without applying an inflammatory inducer (e.g., LPS + IFN-γ) treatment, whereas the other was used to model responses under conditions of inflammation by applying the inducer cocktail to the basolateral side in contact with RAW 264.7 cells. Similarly, the different phenolic acids tested were also added with the inflammatory inducer in contact with RAW 264.7 cells located on the basolateral side. Lipopolysaccharide from gram-negative bacteria is widely used to induce a cascade of inflammatory reactions in the RAW 264.7 macrophage cell (Funk et al., 1993). Cells were also exposed to IFN-γ to complete the cocktail for the chemical inducer. The combination of inflammatory inducers produces a synergistic effect to stimulate nitric oxide production in RAW 264.7 cells (Hamilton et al., 1989; Held et al., 1999). The potential mechanisms for this reaction includes: (1) upregulation of putative cell LPS receptors by cytokines (Wan et al., 1995); (2) induction of autocrine and paracrine responses by cytokines (Kasama et al., 1995); or (3) enhancement on expression of downstream response factor genes (Held et al., 1999). The synergistic effect of LPS and IFN-γ to induce inflammation in the RAW 264.7 cells was 107 confirmed in an early experiment using nitric oxide as a biomarker (results are shown in Appendix Figure F. In final analysis, LPS + IFN-γ treatment of RAW 264.7 cells for 24 hr was used as the optimal treatment to activate RAW 264.7 cells to produce pro-inflammatory biomarkers in this experiment. The following are selected criteria used to qualify the use of a stable co-culture under homeostasis conditions (Chen et al., 2010; Kämpfer et al., 2017): • Caco-2 and RAW 264.7 cells used in co-culture had cell viability (>80%) and equal to that of the mono-culture for each cell line; • No significant disruption in integrity of Caco-2 monolayer occurred when present in the Caco-2/RAW 264.7 co-culture, over 24 hr culture; • Immune responses from Caco-2 cells were not stimulated in the presence of non-activated RAW 264.7 cells (e.g., compared to Caco-2 mono-culture); this was determined by monitoring pro-inflammatory biomarker production of IL-8 in the basolateral compartment. • Immune responses from RAW 264.7 cells were not activated in the co-culture model with Caco-2 cells, (e.g., compared to RAW 264.7 cells mono-culture); this was determined by monitoring pro-inflammatory biomarker IL-6, TNF-α and nitric oxide in the basolateral compartment To observe the effect of inflamed macrophage RAW 264.7 cells on co-cultured epithelial Caco-2 cells, in terms of functionally and viability, the following is a list of criteria used to confirm the appropriate source of the inflammatory response in the co-culture model. • Cell viability for Caco-2 and RAW 267.4 cells in the inflamed co-culture model were greater than 80%, relative to mono-culture of each individual cell line, respectively. 108 • Activation of RAW 264.7 cells in the co-culture model with Caco-2 cells was confirmed by obtaining positive responses of pro-inflammatory biomarkers, namely IL-6, TNF-α and nitric oxide in the basolateral compartment. Figure 5.2 (a) Cell viability of RAW cells after 24 hr culture in the RAW mono-culture -/+ inducer (50 ng/mL LPS + 10 ng/mL IFN-γ) or Caco-2/RAW co-culture model -/+ inducer. (b) Cell viability of Caco-2 cells after 24 hr in Caco-2 mono-culture -/+ inducer (50 ng/mL LPS + 10 ng/mL IFN-γ) or Caco-2/RAW co-culture model -/+ inducer. Experiments were performed in triplicate. Cell viability was expressed as percentage relative to mono-culture of corresponding cell line. Data are expressed as mean ± standard deviation (n=3). Significant differences were analyzed by one-way ANOVA, using SPSS software. No significant differences were observed in each treatment for each cell line. 109 Results from the MTT assay showed no significant differences in terms of cell viability of RAW 264.7 and Caco-2 cells, respectively, when together in the co-culture model, compared to the mono-culture model, regardless of including the inducer treatment (Figure 5.2). The greater than 90% cell viability in Caco-2 cells in both mono- and co-culture models enabled a conclusion that the presence of RAW 264.7 in the co-culture model was not a factor on cell viability of Caco-2 cells. It was important in this study to ensure that different, individual cell lines in the co-culture did not compromise each other and responded typically when exposed to the chemical inducer treatment. The idea of the co-culture protocol used in this experiment was that inflamed RAW 264.7 cells would communicate with neighboring Caco-2 cells and potentially influence viability and functionality of the latter. For example, in the Caco-2/RAW 264.7 co-culture model, the production of cytokine IL-8 derived from Caco-2 cells was a specific response to multiple mediators, such as nitric oxide, TNF-α and IL-6 that were derived from the RAW 264.7 cells. The pro-inflammatory biomarkers originating from RAW cells, including IL-6, TNF-α and nitric oxide were confirmed from inflamed RAW 264.7 cells. Results on the production of pro-inflammatory biomarkers from inflamed macrophage RAW 264.7 cells, including IL-6 production, TNF-α and nitric oxide are presented in Figure 5.3 (a-c). No activation occurred in RAW 264.7 cells when co-cultured with Caco-2 cells without inducer treatment. This was confirmed by comparing mono-culture levels of RAW 264.7 IL-6, TNF-α and nitric oxide production with cell responses obtained from the co-culture. Similarly, no significant difference in the Caco-2 cell IL-8 production was observed in the mono- and co-culture model systems, respectively (Figure 5.3 (d)). 110 Figure 5.3 IL-6 (a), TNF-α (b) and nitric oxide (c) produced by RAW cells in mono-culture model, stable co-culture model and inflamed co-culture model. IL-8 (d) produced by Caco-2 cells in mono-culture model, stable co-culture model and inflamed co-culture model. Data are expressed as mean ± standard deviation (n=3). Significance between treatment was analyzed by one-way ANOVA and LSD’s test (SPSS software). Superscripts with different letters (a, b) are significantly different (p<0.05). To further verify the stability of the Caco-2/RAW 264.7 co-culture model, cell functionality of Caco-2 cells was also examined. The parameter chosen to determination Caco-2 monolayer integrity over the 24 hr culture period was the cell TEER value derived from the Caco-2 monolayer for 24 hr. This parameter was measured for both the Caco-2 mono- and the co-culture models and relative values were compared to assess changes in functional integrity (Appendix Figure G (i)). No significant difference in Caco-2 cell TEER values existed between the mono-culture and the co-culture models, respectively, over a 24 hr period. This result confirmed that the Caco-2 monolayer was not compromised when cultured in the presence of the 111 RAW 264.7 cells and, therefore could be used to assess functional integrity when exposed to different experimental treatments. 5.3.2 Assessment of different phenolic acids on changes in inflammatory biomarkers derived from RAW 264.7 cells in the Caco-2/RAW 264.7 co-culture model To test the relative effect of different phenolic acids on changes in inflammatory biomarkers generated from inflamed RAW 264.7 cells in the Caco-2/RAW co-culture model, phenolic acid samples were added specifically to the basolateral part of the co-culture system along with the inflammatory inducer cocktail. The effect of phenolic acids on activation of NF-κB pathway in inflamed RAW 264.7 cells is presented in Figure 5.4. The different inflammatory biomarkers analyzed from supernatant recovered from the basolateral location included nitric oxide, peroxynitrite, IL-6, and TNF-α production (Figure 5.5). The cell viability of each of the two cell lines in the co-culture was not compromised by the conditions used to test different phenolic acids (Appendix Figure H). NF-κB signaling pathway has a central importance with onset of inflammation and changes in cellular immunity by regulating activation of transcription of numerous target genes, such as pro-inflammatory cytokines (Hayden & Ghosh, 2008; Nam, 2006). Inhibitors that act on the NF-κB signaling pathway, therefore, making them potential therapeutic agents to be used against acute or chronic inflammation. In the current study, treatment of inducer cocktail led to a significant increase in NF-κB activation in inflamed RAW 264.7 cells in the Caco-2/RAW co-culture model (p<0.05). Treatment of CA and GA significantly mitigated the activation of NF-κB (p<0.05), whereas FA had no significant effect. Chlorogenic acid appeared to decrease slightly the activation of NF-κB, but this change was not significant (p<0.05). 112 Both CGA (Hwang et al., 2014) and GA (Huang et al., 2016) had a capacity to inhibit an inflammatory responses in inflamed RAW 264.7 cells when induced by LPS in the mono-culture model. The inflammatory response confers with others which linked the activation to upregulation of toll like receptor 4 (TLR4)/NF-κB signaling pathway (Huang et al., 2016). Figure 5.4 Activation of nuclear translocation of NF-κB in RAW cells in the Caco-2/RAW co-culture cell system by various phenolic acid. Cells were treated with CA, CGA, FA and GA at 100 µM for 1.5 hr in the basolateral part in the presence of inflamed RAW 264.7 cells, where -control refers to cells without any treatments. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA, followed by LSD’s test using SPSS software. Superscripts with different letters (a, b, and c) are significantly different (p<0.05). RAW 264.7 cells that were inflamed in the Caco-2/RAW co-culture model by exposing them to the inflammatory cocktail, produced a significant increase in cytokine IL-6 (p<0.05). Applying FA with the inflammation inducer had no effect on reducing the production of IL-6 in these cells; however, with GA treatment, a significant capacity to mitigate the RAW 264.7 IL-6 response (p<0.05) was observed; followed by CA, and CGA, respectively (Figure 5.5 (a)). 113 Using the same inducer cocktail in the co-culture model significantly increased (p<0.05) TNF-α production from inflamed RAW 264.7 cells (Figure 5.5 (b)). The application of CA, CGA, and FA produced small, insignificant changes to mitigate TNF-α production in inflamed RAW 264.7 cells. In contrast, GA produced a significantly (p<0.05) decrease in TNF-α production in inflamed macrophage. Using nitric oxide as the biomarker to signal a specific immune response from inflamed RAW 264.7 cells also showed evidence that significant increases (p<0.05) in nitric oxide in the Caco-2/RAW 264.7 co-culture model occurred (Figure 5.5 (c)). The subsequent application of different phenolic acids to already inflamed RAW 264.7 cells produced varied responses to mitigate nitric oxide production, with CA and GA being the only ones to significantly (p<0.05) reduce the production of nitric oxide; whereas, similar treatments with FA, and CGA, respectively had small and insignificant effects on nitric oxide generation compared the positive control. Another inflammatory biomarker used in this experiment with inflamed RAW 264.7 cells was the generation of peroxynitrite radical. Treating RAW 264.7 cells with inflammatory inducer significantly increased the peroxynitrite radical generated from activated RAW 264.7 cells in the Caco-2/RAW co-culture model (p<0.05) (Figure 5.5 (d)). Of particular interest was the finding that both CA and GA produced a similar efficacy to suppress (p<0.05) the inflammatory response that involved mitigating peroxynitrite radical production. In contrast, both CGA and FA were relatively equally less effective, producing no significant changes in peroxynitrite production. It is known that the combination of LPS and IFN-γ will activate RAW 264.7 cells by binding to receptors located on cell membrane, which in turn triggers activation of NADPH oxidase and the generation of ROS; the latter being important for cell signaling (Gunawardena et al., 2019). Activation of NADPH oxidase results in transfer of an electron from intracellular 114 NADPH to an extracellular O2 pool, which in turn generates a superoxide anion. Superoxide dismutase reacts with extracellular superoxide anion to produce H2O2, which in turn diffuses through plasma membrane AQP channels to be available for triggering an intracellular signaling response. On the other hand, the superoxide ion may also initiate intracellular signaling directly by accessing cell membrane anion channels. The availability of intracellular ROS and subsequent concentration is also critical for regulating NF-κB pathway and inflammation. In the current study, treatment of RAW 264.7 cells with LPS and INF-γ to produce an inflamed state resulted in significant (p<0.05) increases in a number of inflammatory biomarkers, including IL-6, TNF-α, nitric oxide and peroxynitrite, respectively. Phenolic acids were shown to have selective mitigating power on inducer generated IL-6 production; however, the capacity to reduce the inflammatory response was dependent on the type of phenolic acid. At equimolar concentrations, GA had the greatest capacity to inhibit IL-6 production in inflamed RAW 264.7 cells, followed by CA and CGA, respectively. Other workers have reported similar anti-inflammatory effect of GA on RAW 264.7 cells using TNF-α and IL-6 as biomarkers (Huang et al., 2016). It is known that IL-6 production is regulated via the NF-κB pathway, and superoxide anion has been established as a typical ROS that is involved in activating NF-κB. Others have also shown that GA had strong superoxide scavenge capacity than both CA and FA, respectively (Mathew et al., 2015). Hence, ranking different phenolic acids for relative affinity to inhibit IL-6 production can be explained by the relative capacity to scavenge superoxide anion, which in turn triggers the activation of NF-κB pathway and downstream IL-6 production. Peroxynitrite, another biomarker for inflammatory signaling, is generated by an interaction between superoxide and nitric oxide. It is likely that differences between the phenolics tested in this study that inhibited peroxynitrite production was related to the relative affinity to scavenge superoxide 115 anion. Another response by macrophages during acute inflammation is the production of cytokine TNF-α. The results of this experiment showed that the mitigating effect of GA on LPS induced TNF-α production corresponded to findings of others, that reported GA could block activation of TLR4/ NF-κB (Huang et al., 2016). The NF-κB results presented in Figure 5.4 support the results in both pro-inflammatory cytokine and nitric oxide production. Figure 5.5 A select number of biomarker response to inflammatory induction by inducer and mitigation of induction by different phenolic acids. IL-6 (a), TNF-α (b), nitric oxide (c), and peroxynitrite (d) were generated in RAW cells in a co-culture model in response to the inducer. The different phenolic acids tested show variable capacities (p<0.05) to mitigate the inflammatory response, specific to the biomarker monitored. Data are expressed as mean ± standard deviation (n=3). Significant differences between treatments were analyzed by one-way ANOVA, using SPSS, followed by LSD’s test (p<0.05). Superscripts with different letters (a-e) are significantly different from each other. 116 In the previous chapter, it was demonstrated that the stability of phenolic acids when present under in vitro culture conditions, that included media without cells, varied considerably depending on the type of phenolic acid and its concentration. Moreover, this experiment also showed that H2O2 was a product of phenolic pro-oxidation under typical culture conditions. In this study, production of H2O2 from different phenolic acids while in culture in the presence of inflamed RAW 264.7 cells was measured and is presented in Table 5.1. There was no detectable H2O2 generated from CA, CGA and FA, respectively, when cells were present. However, in the case of GA, detectable amounts of H2O2 were observed in the presence of cells. Notwithstanding this, the level of H2O2 increased early on in the incubation period from 10 min to 30 min, before decreasing thereafter over time to non-detectable levels. Treatment of RAW 264.7 cells with LPS and IFN-γ to induce inflammation can activate NADPH oxidase activity, thus it is also involved in superoxide anion generation. This is an important observation, since this response induces the NF-κB pathway and downstream inflammatory responses. Extracellular scavenging of superoxide anion by GA, coupled with formation of H2O2 was found to corresponded to a mitigating effect of GA on inflammatory responses. It could be expected that enhanced uptake of extracellular produced H2O2 by inflamed RAW 264.7 cells could occur if upregulation of plasma membrane AQP channels also occurred. This mechanism would feasibly enable triggering a H2O2 induced intracellular signaling response that would target reducing inflammation. 117 Table 5.1 Comparison of H2O2 levels generated by phenolic acids under cell culture conditions in the presence of RAW 264.7 cells treated with inducer cocktail (50 ng/mL LPS + 10 ng/mL IFN-γ). Data are expressed as mean ± standard deviation (n=3). 100 µM 10 min 30 min 60 min 90 min 120 min Blank n.d. n.d. n.d. n.d. n.d. I n.d. n.d. n.d. n.d. n.d. I + CA n.d. n.d. n.d. n.d. n.d. I + CGA n.d. n.d. n.d. n.d. n.d. I + FA n.d. n.d. n.d. n.d. n.d. I + GA 4.06 ± 0.46 8.19 ± 0.17 4.91 ± 0.31 3.90 ± 0.09 3.36 ± 0.14 n.d. = not detectable; I: means treatment of inducer cocktail 5.3.3 Characterization of phenolic acids modulation of activated RAW 264.7 cells on Caco-2 cell functionality These experiments were conducted in the Caco-2/RAW 264.7 co-culture cell model to determine if phenolic acids could modify Nrf2 cell signaling in Caco-2 cells, in response to a phenolic specific affinity to mitigate the redox reaction in inflamed RAW cells, residing in co-culture. The biomarker chosen to determine the effect was the change in Nrf2 cell signaling in Caco-2 cells. Nrf2 cell signalling in Caco-2 cells was measured 24 hr after exposure of inflamed RAW 264.7 cells treated with different phenolic acids added to the basolateral part of the co-culture that held the RAW 264.7 cells. Different responses attributed to phenolic acid induced signaling from inflamed RAW 264.7 cells on change in Caco-2 Nrf2 translocation is presented in Figure 5.6. Inflamed RAW 264.7 cells produced a significant increase (e.g., ~20%; p<0.05) in Caco-2 Nrf2 activation. The presence of GA added to the basolateral space containing inflamed RAW 264.7 cells, further increased (p<0.05) Caco-2 Nrf2 activation to >50 % of control values. 118 In comparison, there were no similar significant effects observed with either CA, CGA and FA, respectively, at equimolar concentrations, on the Caco-2 Nrf2 response. These results show that an increase in Caco-2 Nrf2 activation attributed to the inflamed RAW 264.7 cells in co-culture, was due to inflammatory response mediators originating from inflamed RAW cells, rather than the inflammatory inducer acting directly on Caco-2 cells. Appendix Figure I shows that treating Caco-2 cells with inflammatory inducer did not activate a Caco2 nuclear Nrf2 response in the mono-culture model. In Chapter 4, H2O2 was shown to be a key signaling molecule that triggered the activation of nuclear Nrf2 in Caco-2 cells. Results obtained in the present experiment confirmed this finding, as H2O2 generated from autoxidation of GA corresponded to the activation of Nrf2 of Caco-2 cells in the Caco-2/RAW cell co-culture model. Only GA was effective to generate H2O2 to the extent needed to mitigate the inflamed RAW 264.7 cell response Table 5. It was considered therefore that treatment of the inflamed RAW 264.7 cells with catalase after phenolic acid treatment would be an appropriate control for this experiment, since catalase would remove H2O2 generated from GA autoxidation and thus removing the signal molecule needed to induce nuclear Nrf2 response in Caco-2 cells. However, applying catalase to the basolateral segment of the co-culture model had a major limitation, since catalase alone triggered Nrf2 translocation directly in RAW 264.7 cells. As a result, this control treatment using H2O2 was not continued. Nrf2 is known as a master regulator of cellular responses against environmental stress, via H2O2 -upregulation of detoxification and antioxidant enzymes genes (Wen et al., 2019). Under induced stress, Keap1 leads to Nrf2 translocation from cytoplasm to the nucleus which activates the expression of target genes that encode antioxidant enzymes (Kobayashi et al., 2004). In addition, the Nrf2-Keap 1 pathway is involved in participating in regulation of 119 inflammatory pathways and tight junction proteins in intestinal barrier (Li et al., 2018; Osburn et al., 2007; Theiss et al., 2009; Wen et al., 2019). In the current study, the intestinal integrity of Caco-2 cells was analyzed using TEER value, and tight junction protein expression as biomarkers. Figure 5.6 Activation of nuclear translocation of Nrf2 in Caco-2 cells in the Caco-2/RAW co-culture cell system when treated with different phenolic acids at 100 µM for 24 hr, applied to the basolateral segment in the presence of activated RAW 264.7 cells, + means cells treated with inducer (LPS+IFNg). -Control refers to cells without any treatments. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA, followed by LSD’s test using SPSS software. Mean values with superscripts holding different letters (a, b, c) are significantly different (p<0.05) from each other. A functional test used in this study to support the biochemical changes observed in Caco-2 epithelial cell redox and inflammatory response to selected phenolic acids involved monitoring cell permeability parameters. Caco-2 epithelial cell barrier integrity was measured by recording TEER values up to 24 hr in the co-culture model, both in the absence and presence of inflammatory inducer treatment of RAW 264.7 cells and the presence of different phenolic acids 120 (Figure 5.7). Inflamed RAW 264.7 cells in the co-culture system produced a significant decrease in Caco-2 cell TEER values (p<0.05), relative to the non-inflamed cells. Treatment of cells with GA mitigated this effect and produced a significant (p<0.05) increase in Caco-2 TEER values, compared to non-treated cells. This pronounced effect of GA on TEER values was unique to other phenolic acids tested, as there was no influence of CA, CGA and FA on RAW 264.7 cells induced changes in Caco-2 cell permeability. Permeability of the intestinal epithelial barrier is controlled by multi-protein adhesive complexes located on the lateral surface of contacting epithelial cells, including apical tight junctions, subjacent adherent junctions, and desmosomes (Lechuga & Ivanov, 2017). Occludin, Claudin, and the Zonula Occludens (ZO) are well known to be important components of the tight junction protein assembly (Lee, 2015). Destabilization of these protein complexes in the small intestine results in the nonselective entry of extracellular molecules, thus leading to a condition of intestinal leakage or lost protection from pathogen, toxin and allergen exposure, and possibly altered nutrient bioavailability (Odenwald & Turner, 2017). To support the change in TEER value results observed in the previous experiment, specific tight junction protein expression from ZO-1 and Occludin, respectively, were evaluated. Figure 5.8 shows the relative expression of both ZO-1 and Occludin and relative ratios using beta-actin calculated to quantify results obtained from Caco-2 cells when co-cultured with inflamed RAW cells treated with different phenolic acids. Expression of ZO-1 was decreased in Caco-2 cells when co-cultured with inflamed RAW 264.7 cells. The presence of CA, CGA, FA treatments, respectively, in the presence of inflamed RAW 264.7 cells had no effect on modifying the suppression of Caco-2 ZO-1 expression, thus indicating that protection of ZO-1 expression was not possible with these particular phenolic acids. However, the presence of GA was indeed effective to increase (p<0.05) 121 Caco-2 cell ZO-1 expression, that otherwise had been lowered when in contact with inflamed RAW 264.7 cells. A very similar result was obtained with Occludin expression for these series of experiments. For example, inducing inflammation in RAW 264.7 cells resulted in a decreased Occludin expression (p<0.05) in the Caco-2 cells in the co-culture model. No capacity of phenolic acids, CA, CGA, FA to mitigate this effect on Occludin expression was observed. However, the presence of GA to inflamed RAW 264.7 cells increased (p<0.05) Caco-2 Occludin expression in the co-culture. The results of these experiments confirm that TEER values measured from Caco-2 cells in both a mono-culture and co-culture assembly were not different after a 24 hr incubation period, when in the presence of normal RAW 264.7 cells in co-culture. The addition of inflammatory inducer directly to the Caco-2 monolayer to the basolateral component of the Caco-2 mono-culture did not influence Caco-2 TEER value, compared to a corresponding value obtained without inducer (Appendix Figure G (ii)). It is concluded from these experiments that the decrease observed in Caco-2 cell TEER values and corresponding decrease in specific tight junction protein expressions were attributed only to signals of inflammation originating from inflamed RAW 264.7 cells in the co-culture model. There are several factors that can adversely affect intestinal permeability, including exogenous factors, such as food, or pollution components and endogenous factors that include, epithelial apoptosis and cytokine release from immune cells (Groschwitz & Hogan, 2009). In the current study, the treatment of an inflammatory cocktail to inflame RAW 264.7 cells lead to the production of many specific bioactive molecules, including TNF-α, IL-6 and reactive nitrogen species, the latter including nitric oxide and peroxynitrite, respectively; all of which could trigger a response in Caco-2 cells. 122 The direct impact of TNF-α on Caco-2 monolayer integrity has been reported previously (Tanoue et al., 2008), and TNF-α is involved in chronic inflammatory bowel disease (Murch et al., 1993), whereas anti-TNF-α antibodies are effective treatments to reduce risk of similar inflammatory diseases (Chan & Lichtenstein, 2006). The underlying mechanism of TNF-α on intestinal epithelial tight junction barrier function observed in this study corresponded to the NF-κB p50/p65 binding activity and activation of the myosin light chain kinase promoter (Ye et al., 2006). Oxidative stress is also a well-known factor that results in the disruption of epithelial tight junction function (Bailey et al., 2004; Pérez et al., 2006). Both reactive oxygen and nitrogen species, that include superoxide anion and peroxynitrite, respectively, disrupt tight junction proteins (Rao, 2008). The relative capacity of different phenolic acids to scavenge peroxynitrite radical was evident; with the greatest relative capacity being observed for GA. Hence, although phenolic acids may in general reduce oxidative stress, extending this effect to protect gap junction protein function was found to be a benefit unique for GA. The protective effect of GA on tight junction proteins corresponded to an affinity to activate Nrf2 in differentiated Caco-2 cells. Mechanisms for Nrf2 activation corresponding to preserving intestinal barrier function are related to the role of Nrf2 to suppress oxidative stress which ultimately result in intestinal mucosal injury (Wen et al., 2019). Previous studies have shown factors that upregulate Nrf2 signaling pathway are connected to increased expression of the tight junction proteins, specifically ZO-1 (Liu et al., 2017), Occludin (Liu et al., 2017) and Claudin-1 (Lau et al., 2015). The effect of GA on upregulating ZO-1 was linked to the relative high capacity to undergo autoxidation in culture media, generating H2O2, as a by-product. Hydrogen peroxide is an effective activator of Nrf2 cell signaling. Similar to the ZO-1 123 expression, GA treatment produced a significantly higher expression of Occludin compared to the control (p<0.05). This effect shown herein with in vitro cell culture, has also been shown in vivo with Sprague Dawley rats, where feeding GA significantly upregulated the Occludin expression (Park et al., 2020; Tretola et al., 2021). Moreover, Nrf2 activation can reduce inflammation by suppressing the NF-κB pathway, thus preserving intestinal barrier function (Wardyn et al., 2015). Nrf2 activation also enhances the host protection against ROS induced stress. Upregulation of NF-κB pathway is responsible for regulating inflammatory responses, whereas overt inflammation can severely damage intestinal barrier function (Chen & Kunsch, 2004). Figure 5.7 Caco-2 epithelial barrier integrity measured as TEER value at 24 hr in co-culture with (+) or without (-) inducer, and different phenolic acids. Data are expressed as mean ± standard deviation (n=3). Treatment means were analyzed by one-way ANOVA to detect difference, with LSD’s test using SPSS software to identify the difference between sample treatments. Superscripts with different letters (a, b, c) are significantly different from each other (p<0.05). 124 Figure 5.8 Expression of tight junction proteins ZO-1 and Occludin from Caco-2 cells in co-culture with (+) or without (-) inflamed RAW 264.7 cells and different phenolic acid treatments. Data are expressed as mean ± standard deviation (n=3). Treatment means were analyzed by one-way ANOVA to detect difference, with LSD’s test using SPSS software to identify the difference between treatments. Superscripts with different letters (a, b, c) are significantly different from each other (p<0.05). Full western blot gel is shown in Appendix Figure J. 125 Another example of Caco-2 intestinal cells responding to inflammatory signals originating from the inflamed co-cultured macrophage cells occurred using IL-8 production as a biomarker. The inflamed macrophage cells in the Caco-2/RAW co-culture model produced an increased (p<0.05) Caco-2 cell IL-8 production, not seen with non-inflamed cells (Figure 5.9). This approach was repeated with the presence of phenolic acids, such as CA, CGA, FA and GA, added to the basolateral location along with the inflamed RAW 264.7 cells (Figure 5.9). Activating RAW cells with inflammatory inducers triggered a Caco-2 cellular response, not observed when the same inducer was applied to the basolateral segment of the Caco-2 cell mono-culture. This confirmed that the co-culture conditions used herein enabled communication between inflamed RAW 264.7 and differentiated Caco-2 cells, and was a factor that resulted in Caco-2 IL-8 production. Gallic acid significantly mitigated this induced response in IL-8 production from Caco-2 cells to the greatest extent followed by CA and CGA (p<0.05), respectively, in the inflamed Caco-2/RAW 264.7 cell model. Ferulic acid also produced a small but not significant decreases in Caco-2 cell IL-8 production. Interpretation of these findings lead to the possibility that regulation of Caco-2 cell IL-8 production involves Nrf2 signaling and a NF-κB pathway crosstalk in Caco-2 cells. Others have shown that NF-κB pathway has a critical role in regulating IL-8 production (Romier et al., 2008). To connect the activity of Nrf2 to this plausible explanation, the dissociation of Keap1 from Nrf2 must occur to suppress the ubiquitination and degradation of IκB, thus inhibiting the activation of NF-κB pathway (Khor et al., 2006). It can also be considered that TNF-α was active to induce secretion of IL-8 in Caco-2 cells (Sonnier et al., 2010). Thus, the relatively higher capacity of GA to decrease Caco-2 cell IL-8 production could be attributed to a relatively greater affinity to 126 directly inhibit TNF-α production in inflamed RAW 264.7 cells, compared to other phenolic acids. Figure 5.9 Expression of Caco-2 cell IL-8 production in the Caco-2/RAW co-culture cell system when treated with different phenolic acids in the presence of inducer applied to the basolateral part. Phenolic acids were added at 100 µM in the presence of activated RAW 264.7 cells for 24 hr. - Control refers to cells without any treatments. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA, followed by LSD’s test using SPSS software to show difference between means. Superscripts with different letters (a, b, c, and d) are significantly different (p<0.05) from treatments. Another important underlying mechanism to consider when explaining the findings reported herein with different phenolic acids concerns the activity of AQP3. This protein is located on the cell membrane and regulates intestinal epithelial barrier function and paracellular uptake of extracellular xenobiotics that induce local inflammation (Zhu et al., 2016). As described in the previous chapter, the relevance of AQP3 to this research centers on its function as a membrane transporter of H2O2, thus controlling the transportation of H2O2 from extracellular to intracellular space. Increasing intracellular H2O2 was shown to trigger intracellular Nrf2 activation in Chapter 4. To establish this possible affect, in the co-culture experiment, it was 127 necessary to first confirm that the alteration of AQP3 in Caco-2 cells was attributed to the presence of inflamed RAW cells. There is no literature related to factors that influence AQP3 expression in Caco-2 cells in a Caco-2/RAW co-culture model. Experiments were therefore conducted with different treatments that included inflammatory inducer treatment alone, and the inducer treatment in the presence of phenolic acids on Caco-2 mono-culture. Results presented in Figure 5.10 (a) show no significant differences among different treatments that included both the presence of inflammatory inducer, or presence, or absence, of phenolic acids in a Caco-2 mono-culture. Thus, the alteration of AQP3 expression in Caco-2 cells is due more to the presence of inflamed RAW cells rather than presence of only the inflammatory inducer (Figure 5.10 (b)). The addition of CA, CGA and FA did not trigger a relative change in AQP3 in Caco-2 cells when co-cultured with inflamed RAW 264.7 cells. However, GA did produce a significant effect that increased AQP3 in Caco-2 cells in the Caco-2/inflamed RAW 264.7 co-culture model. A previous study using a HT-29 intestinal cell line reported that treatment of IFN-γ or TNF-α significantly decreased AQP3 expression, which was attributed to the phosphorylation of signal transducer and activator of transcription-1 (Peplowski et al., 2018; 2017). In addition, the binding of Specificity Protein 3 to the AQP3 promotor is a target for gene regulation in the context of inflammation, given the fact that inflammatory cytokine TNF-α enhances Specificity Protein 3-induced gene suppression (Yde et al., 2021). In the present study, inflamed RAW 264.7 cells produced cytokines, such as TNF-α, and thus the alteration of AQP3 expression in the co-cultured Caco-2 cells is likely linked by the cytokines produced by inflamed RAW 264.7 cells. Again, treatment of the co-culture with GA mitigated the decrease in AQP3 expression in inflamed RAW 264.7 cells (p<0.05). Others have also reported that upregulation of a cAMP response element-binding protein (CREB) is involved in transcriptional regulation of AQP3 128 expression, for which two binding sites have been identified in the promotor region of AQP3 gene (Itoh et al., 2003; Wang et al., 2006; Yde et al., 2021). Figure 5.10 (a) shows expression of AQP3 in Caco-2 cells in the Caco-2 mono-culture cell model treated by various phenolic acids. Cells were treated with CA, CGA, FA and GA at 100 µM for 24 hr in the basolateral part in the presence of inducer, where -control refers to cells without any treatments. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA, using SPSS software. No significant differences have been observed among the sample treatments (p<0.05). Figure 5.10 (b) shows expression of AQP3 in Caco-2 cells in the Caco-2/RAW co-culture cell model treated by various phenolic acids. Cells were treated with CA, CGA, FA and GA at 100 µM for 24 hr in the basolateral part in the presence of inflamed RAW 264.7 cells, where -control refers to cells without any treatments. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA, using SPSS software. Superscripts with different letters (a and b) are significantly different (p<0.05). 129 5.4 Conclusions In the current study, Caco-2 and RAW 264.7 cells were co-cultured to facilitate possible cell communication between intestinal epithelial (e.g., Caco-2 cells) in the presence of inflamed macrophage (RAW 264.7 cells). Pre-treatment of macrophage cells with inflammatory inducer was used to secure an in vitro cell model that mimicked an intestinal inflamed state, whereby the neighbouring macrophage responding to the inflammatory stimulus could communicate with Caco-2 epithelial cells and thus be involved in producing specific responses that would define protection of intestinal epithelial cell viability and function. The control used for this experimental was to simply not expose the co-cultured RAW 264.7 cells to the inflammatory inducer, thus eliminating any possible onset of macrophage inflammatory response molecules, such as nitric oxide. The use of nitric oxide as a biomarker enabled the evaluation of relative capacity of specific phenolic acids to potentially mitigate inflammatory responses from RAW 264.7 macrophage cells. This in turn resulted in intercellular communication between macrophage and Caco-2 cells and provided an opportunity to assess the protection of intestinal epithelial cells to macrophage inflammatory signals. The mechanism for a relative capacity of different phenolic acids to protect Caco-2 cells was related to characteristic affinities to scavenging free radicals, or trigger intracellular H2O2 concentrations required for downstream cell signaling. Thus, the selective capacity of phenolic acids to regulate the inflammatory status of activated RAW cells can be translated to their protection on Caco-2 cell functionality that included induced cytokine production, Nrf2 cell signalling, protection of Caco-2 monolayer integrity and AQP3 expression. 130 Chapter 6: Conclusion and future directions 6.1 Main findings In Chapter 2, it was demonstrated that gallic acid, ferulic acid, chlorogenic acid and caffeic acids varied in relative stability when incubated in culture media for 24 hr. This assessment was done by measuring the relative recovery of each phenolic after a 24 hr incubation period in cell culture media using high performance liquid chromatography. Simultaneously, the relative capacity of these individual phenolic acids to generate H2O2 without the presence of cells was measured using a hydrogen peroxide assay kit that contained a highly sensitive and stable probe, 10-acetyl-3,7-dihydroxyphenoxazine (ADHP). The capacity of different phenolic acids to generate H2O2 followed the relative rank of: gallic acid > caffeic acid > cholorogenic acid > ferulic acid. These findings led to an additional experiment that produced evidence that the extent of induction of apoptosis and inhibition of proliferation in non-differentiated Caco-2 cells, caused by autoxidation of phenolic acids that generated H2O2 was reduced significantly when catalase was added to the culture media. In Chapter 3, a novel method was developed to measure real time changes in intracellular H2O2. Intracellular H2O2 levels were validated using a HyPer-3 sensor methodology standardized in differentiated Caco-2 cells. HyPer-3 refers to a genetically encoded fluorescent H2O2 sensitive indicator that can be used to measure intracellular H2O2 in applications that include fluorescent lifetime imaging of H2O2 levels. It was developed by integrating the circularly permuted yellow fluorescent protein (cpYFP) inside the regulatory domain of an Escherichia coli H2O2 sensitive protein, OxyR. A plasmid expression vector was transfected into differentiated Caco-2 cells by electroporation to obtain HyPer-3 expressed Caco-2 cells. Confocal microscopy and flow cytometry, respectively, were used to visualize and quantify the 131 H2O2 uptake in differentiated Caco-2 cells. An aquaporin inhibitor, DFP00173 was also validated to test the effect of an inhibitor on aquaporin functionality. In Chapter 4, it was demonstrated that the extracellular generation of H2O2 derived from different specific phenolic acids in culture resulted in uptake of H2O2 in differentiated Caco-2 cells. This was achieved by comparing the H2O2 level in experiments with both the presence or absence of cells. As a result, the addition of phenolic acids was shown to produce H2O2 extracellularly that resulted in an increased intracellular HyPer-3 488/405 nm ratio; monitored using live cell confocal microscopy imaging. This observation was mitigated when cells were pre-treated with the aquaporin inhibitor DFP00173. Furthermore, the generation of H2O2 by phenolic acids in culture media resulted in intracellular Nrf-2 cell signaling activation. Moreover, the activation of Nrf-2 cell signaling was shown to be dependent on both the source of phenolic acid and the concentration present. The activation of Nrf-2 cell signaling, facilitated by generation of H2O2 from phenolic acids, was decreased when culture media contained catalase. Alternatively, the capacity to activate Nrf-2 signaling was dramatically lowered when cells were pre-treated with aquaporin inhibitor DFP00173. In Chapter 5, RAW 264.7 macrophage cells were co-cultured with intestinal epithelial Caco-2 cells to demonstrate the importance of extracellular redox cell communication on intracellular cell signaling and maintenance of cell function. A co-culture Caco-2/RAW model was designed to mimic intestine homeostasis and redox in an inflamed condition. A mono-culture Caco-2 was used as a control. Established cell biomarkers to confirm Caco-2 functionality, such as cell transepithelial electrical resistance (TEER) value, cytokine and nitric oxide production, and cell viability were vital to show that co-culture of distinct cells did not affect barrier integrity, nitric oxide and cytokine production, nor did it affect adversely cell 132 viability. Inducer cocktail was used to shift redox status in the Caco-2/RAW co-culture model. A significant (p<0.05) reduction in TEER value and release of pro-inflammatory cytokines were observed in the Caco-2/RAW co-culture model. Similar treatments did not alter the same biomarkers in a Caco-2 mono-culture. The presence of phenolic acids effectively modulated the release of pro-inflammatory biomarkers, including TNF-α, IL-6, nitric oxide, peroxynitrite in the co-culture when generated by activated RAW 264.7 cells. These effects were consistently related to changes in extracellular alteration of redox status, induced by different type of phenolic acids. The capacity of phenolic acids on regulation of inflammatory biomarkers generated from RAW 264.7 cells was extended to the protection on Caco-2 cell functionality, including monolayer integrity with tight junction expression, Nrf2 cell signaling, AQP3 expression and IL-8 cytokine production. Thus, these measures were also effective biomarkers of Caco-2 cell functionality. In summary, this thesis has produced a series of novel experiments to show how autoxidation of phenolic acids, common to many food sources, can occur under typical in vitro cell culture conditions. From this important initial finding, a subsequent series of experiments revealed that the autoxidation tendency of phenolic acids was uniquely associated with important intracellular cell communication signaling that regulated both antioxidant and anti-inflammatory responses in the intestinal Caco-2 cell model. A co-culture model was successfully used to further enable studying the effect of changes made to extracellular redox status on intracellular redox status. This in turn corresponded to specific cell signaling related to an acute inflammatory response; all of which were sensitive to phenolic acid autoxidation and generation of reactive oxygen (H2O2) or reactive nitrogen (NO) species. 133 6.2 Future directions In this thesis, the relative stability of the four phenolic acids and capacity to produce H2O2 was evaluated. The phenolic acid autoxidation reaction was monitored using in vitro cell culture conditions. In future studies, it will be of value to extend my findings to model systems that include the intact food system to denote the effects of food matrices on phenolic autoxidation in food and beverages such as coffee. In this experiment, four pure phenolic acids were examined individually; therefore, future work would be of value to comparing relative mixtures of phenolic acids, in addition to pure compounds, on redox regulation and anti-inflammatory responses using the cell culture models employed herein. In the co-culture model, it was shown that expression of AQP3 on Caco-2 cells was influenced by inflamed RAW 264.7 cells, as well as presence of phenolic acids. It was postulated that the TNF-α generated from inflamed RAW 264.7 cells contribute to the alteration of AQP3 in Caco-2 cells. This hypothesis was proven positive; hence, it will be worthwhile to look at the effect of TNF-α standard on expression of AQP3 in Caco-2 cells at both protein levels and gene levels. Aquaporins have a critical role in regulating the absorption and secretion of water molecules thus maintaining the stable state of the intestine. Abnormal regulation of AQPs have been shown to lead to various intestinal diseases, and plant extracts have been shown to regulate AQPs. It would be of value to investigate more on how the influence of polyphenol rich diets modify regulation of intestinal health by regulating AQP activity. 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International Immunopharmacology, 71, 321–327. http://doi.org/10.1016/j.intimp.2019.03.030 195 Appendix A The individual HPLC chromatograms of phenolic acids Appendix Figure A The chromatograms of caffeic acid (1) a, chlorogenic acid (2) a, ferulic acid (3) a, gallic acid (4) a as standard, and chromatograms of caffeic acid (1) b, chlorogenic acid (2) b, ferulic acid (3) b, gallic acid (4) b after 24 hr in culture media, and media as blank (5). Phenolic acid standards were eluted at following retention times: CA@6.46 min; CGA@5.79 min; FA@ 7.55 min and GA @3.68 min. 196 Appendix B Patterns of H2O2 disappearance over time when added to culture media with differentiated Caco-2 cells. Appendix Figure B Patterns of H2O2 disappearance over time (60 min) when added to differentiated Caco-2 cells culture media. Data are expressed as mean ± standard deviation (n=3). H2O2 concentrations were 100 µM (a) and 1000 µM (b). Data were transformed to log concentration to determine rate of disappearance presented in the text. 197 Appendix C Response of Caco-2 cells treated with different concentration of phenolic acids measured by MTT assay Appendix Figure C Response of Caco-2 cells treated with different concentration of phenolic acids measured by MTT assay, with and without the presence of catalase (CAT). Histograms represent the percentage, with respect to control cells (cells with media only), of viable cells after treated with different concentrations of CA (a), CGA (b), FA (c), and GA (d). Data are expressed as mean ± standard deviation (n=3). No significant differences in MTT values were observed for the range of concentrations used for each phenolic acid. 198 Appendix D Evidence of purity of the isolated nuclear fraction, and cytoplasm fraction. Appendix Figure D Evidence of purity of the isolated nuclear fraction, and cytoplasm fraction confirmed by presence of Histone and GAPDH expression using western blotting. Expression of Histone protein occurred only in the nuclear fraction (a) and not in cytoplasm fraction (b). Similarly, GAPDH expression was observed only in the cytoplasm (c) and not in the nuclear fraction (d). a b c d 199 Appendix E Western blot to exam the activation of nuclear translocation of Nrf2 in Caco-2 cells Lane 1 2 3 4 5 6 7 8 9 Appendix Figure E (i). Western blot of Nrf2 expression in Caco-2 cells when treated by different GA and CA (1 mM) +/- DFP00173 or +/- catalase. Lane 1: Cells without any treatments Lane 2: Cells without any treatments Lane 3: Cells treated with 1mM GA Lane 4: Cells treated with 1mM GA + CAT Lane 5: Cells pre-treated with DFP00173 followed by treatment of 1 mM GA Lane 6: Cells without any treatments Lane 7: Cells treated with 1mM CA Lane 8: Cells treated with 1mM CA + CAT Lane 9: Cells pre-treated with DFP00173 followed by treatment of 1 mM CA Lane 1 2 3 4 5 6 7 8 9 Appendix Figure E (ii). Western blot of beta actin expression in Caco-2 cells when treated by different GA and CA (1 mM) +/- DFP00173 or +/- catalase. Lane 1: Cells without any treatments Lane 2: Cells without any treatments Lane 3: Cells treated with 1mM GA Lane 4: Cells treated with 1mM GA + CAT Lane 5: Cells pre-treated with DFP00173 followed by treatment of 1 mM GA Lane 6: Cells without any treatments Lane 7: Cells treated with 1mM CA Lane 8: Cells treated with 1mM CA + CAT Lane 9: Cells pre-treated with DFP00173 followed by treatment of 1 mM CA 200 Lane 1 2 3 4 5 6 7 8 9 Appendix Figure E (iii). Western blot to exam the activation of nuclear translocation of Nrf2 in Caco-2 cells when treated by different FA and CGA (1 mM) +/- DFP00173 or +/- catalase. Lane 1: Cells without any treatments Lane 2: Cells without any treatments Lane 3: Cells treated with 1mM FA Lane 4: Cells treated with 1mM FA + CAT Lane 5: Cells pre-treated with DFP00173 followed by treatment of 1 mM FA Lane 6: Cells without any treatments Lane 7: Cells treated with 1mM CGA Lane 8: Cells treated with 1mM CGA + CAT Lane 9: Cells pre-treated with DFP00173 followed by treatment of 1 mM CGA Lane 1 2 3 4 5 6 7 8 9 Appendix Figure E (iv). Western blot of beta actin expression in Caco-2 cells when treated by different FA and CGA (1 mM) +/- DFP00173 or +/- catalase. Lane 1: Cells without any treatments Lane 2: Cells without any treatments Lane 3: Cells treated with 1mM FA Lane 4: Cells treated with 1mM FA + CAT Lane 5: Cells pre-treated with DFP00173 followed by treatment of 1 mM FA Lane 6: Cells without any treatments Lane 7: Cells treated with 1mM CGA Lane 8: Cells treated with 1mM CGA + CAT Lane 9: Cells pre-treated with DFP00173 followed by treatment of 1 mM CGA 201 Appendix F Nitric oxide production from mono-culture RAW 264.7 cells Appendix Figure F Nitric oxide production from mono-culture RAW 264.7 cells treated with 10 ng/mL IFN-γ, 50 ng/m LPS or 50 ng/mL LPS + 10 ng/mL IFN-γ for 4 hr, 8 hr, 16 hr, 20 hr, and 24 hr. Data are expressed as mean ± SD (n=3). 202 Appendix G Intestinal cell barrier integrity measured as TEER value for a Caco-2 monolayer over 24 hr Appendix Figure G (i) Intestinal cell barrier integrity measured as TEER value for a Caco-2 monolayer over 24 hr. TEER values of Caco-2 cells in mono-culture are compared with the TEER values of Caco-2 cells present in a co-culture over a 24 hr period. TEER value was expressed as percentage relative to initial value at time T=0. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by Student’s t-test. No statistically significant difference was observed on sample treatment at each time point. Appendix Figure G (ii). Barrier integrity measured as TEER of Caco-2 cells over 24 hr. TEER value of Caco-2 cells in mono-culture +/- inducer monitored for 24 hr. Data are expressed as mean ± standard deviation (n=3). TEER value was expressed as percentage relative to initial value at time T=0. Significance between treatments was analyzed by Student’s t-test. No statistically significant difference was observed on sample treatment at each time point. 203 Appendix H Cell viability of RAW 264.7 cells or Caco-2 cells in Caco-2/RAW co-culture. Appendix Figure H (a) Cell viability of RAW 264.7 cells in Caco-2/RAW co-culture model treated with CA, CGA, FA and GA at 100 µM for 24 hr in the basolateral part in the presence of activated RAW 264.7 cells, where -control refers to RAW cells in Caco-2/RAW co-culture model without treatment of inducer (50 ng/mL LPS + 10 ng/mL IFN-γ). Data are expressed as mean ± standard deviation (n=3). No significant difference has been observed compared the treated cells with control cells. (b) Cell viability of Caco-2 cells in Caco-2/RAW co-culture model treated with CA, CGA, FA and GA at 100 µM for 24 hr in the basolateral part in the presence of activated RAW 264.7 cells, where -control refers to Caco-2 cells in Caco-2/RAW co-culture model without treatment of inducer. Data are expressed as mean ± standard deviation (n=3). No significant difference has been observed compared the treated cells with control cells. 204 Appendix I Activation of nuclear translocation of Nrf2 in Caco-2 cells in the mono-culture or co-culture cell system in the presence or absence of inducer. Appendix Figure I activation of nuclear translocation of Nrf2 in Caco-2 cells in the mono-culture or co-culture cell system in the presence or absence of inducer. Data are expressed as mean ± standard deviation (n=3). Significance between treatments was analyzed by one-way ANOVA followed by LSD’s test using SPSS software. Superscripts with different letters (a and b) are significantly different (p<0.05). 205 Appendix J Western blot of tight junction expression in Caco-2 cells Appendix J (i). Western blot of ZO-1 expression in Caco-2 cells in Caco-2/RAW co-culture model in the presence or absence with inducer and treated by different phenolic acids Lane 1: Cells without any treatments Lane 2: Cells treated with inducer Lane 3: Cells treated with inducer + GA Lane 4: Cells treated with inducer + FA Lane 5: Cells treated with inducer + CGA Lane 6: Cells treated with inducer + CA Appendix J (ii). Western blot of Occludin expression in Caco-2 cells in Caco-2/RAW co-culture model in the presence or absence with inducer and treated by different phenolic acids Lane 1: Cells without any treatments Lane 2: Cells treated with inducer Lane 3: Cells treated with inducer + GA Lane 4: Cells treated with inducer + FA Lane 5: Cells treated with inducer + CGA Lane 6: Cells treated with inducer + CA Appendix J (iii). Western blot of beta actin expression in Caco-2 cells in Caco-2/RAW co-culture model in the presence or absence with inducer and treated by different phenolic acids Lane 1: Cells without any treatments Lane 2: Cells treated with inducer Lane 3: Cells treated with inducer + GA Lane 4: Cells treated with inducer + FA Lane 5: Cells treated with inducer + CGA Lane 6: Cells treated with inducer + CA
Thesis/Dissertation
eng
Food Science
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Kitts, David D.
Role of phenolic acids on intestinal epithelial cell signaling and functionality
Text