Investigating the Stimulatory Mechanisms of Phlorizin, Phloretin and Chlorogenic Acid Polyphenols on Akkermansia Muciniphila in Vitro

Home , Chlorogenic acid, Phloretic acid, Phlorizin

Investigating the stimulatory mechanisms of phlorizin, phloretin and chlorogenic acid polyphenols on Akkermansia muciniphila in vitro

Ayano Hojo

A Thesis presented to The University of Guelph

In partial fulfilment of requirements for the degree of Master of Science in Food Science

Guelph, Ontario, Canada

ABSTRACT

INVESTIGATING THE STIMULATORY MECHANISMS OF PHLORIZIN, PHLORETIN AND CHLOROGENIC ACID POLYPHENOLS ON AKKERMANSIA MUCINIPHILA IN VITRO

Ayano Hojo Advisor: University of Guelph, 2019 Dr. Gisèle LaPointe

Plant polyphenol extracts are shown to have prebiotic-like, stimulatory effect on

Akkermansia muciniphila. A. muciniphila is a potentially health beneficial commensal gut microbe that utilizes mucin for energy. However, the exact mechanism of the stimulation is unknown. In this study, mechanisms that may lead to competitive advantages for A. muciniphila were tested using pure forms of phlorizin, phloretin, and chlorogenic acid in vitro. The polyphenols had no significant effect on the production of mucin by the host cells. No significant inhibition of the bacterial growth by phlorizin or chlorogenic acid were observed up to 1000 μM.

However, phloretin significantly inhibited the growth of mucus-associated competitors of

A. muciniphila except for Escherichia coli at 250 μM. The polyphenols tested may not directly affect mucin production by the host or function as prebiotics. Rather, the stimulation of

A. muciniphila may be due to its higher tolerance for polyphenols relative to competitors.

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ACKNOWLEDGEMENTS

I am very grateful for my advisor, Dr. Gisèle LaPointe, for her mentorship and support thorough out this journey. I admire her teaching approach that encouraged me to think critically and be independent. Her doors were always open for questions and discussions. The meetings I had with Gisèle were challenging at times but always guided me to the next steps. I truly respect her interdisciplinary expertise and passion in research. Working together, I gained so much experience both technically and personally as an academic researcher.

I would like to thank my advisory committee members, Dr. Massimo Marcone and Dr.

Sampathkumar Balamurugan, for their valuable inputs. I would also like to thank Dr. Michelle

Edwards for all the statistical advice and directions. As well, I was fortunate to have our lab research associate Dr. Ajila Matheyambath for her expertise in HPLC. Without her I would have had difficult times with the HPLC experiments.

Many thanks to my friends and everyone from Dr. LaPointe’s lab and CRIFS for being by my side. I was very comfortable to talk about my problems and frustrations at stressful times.

We all shared ups and downs, and I felt that I was a part of a community. I also enjoyed all the foods that brightened up my days. Special thanks go to our CRIFS building manager Nafiseh

Jam, who often brought delicious sweets and ice creams. Being at CRIFS, I was able to meet and bond with people with whom I wish I can keep in touch in the future.

Finally, I need to thank my family for their continuing support for my education.

Whenever I was bad-tempered from being busy or things not going well, they were very understanding. I always had a good night’s sleep and being at home for sure kept me healthy!

Thank you so much for everyone who made this opportunity possible.

DECLARATION

I, Ayano Hojo, was the principal author of this thesis. All experimental designs, experimental procedures and analysis of results were constructed and performed by me under the supervision of Dr. Gisèle LaPointe.

TABLE OF CONTENTS

ABSTRACT ...... ii

ACKNOWLEDGEMENTS ...... iii

DECLARATION...... iv

TABLE OF CONTENTS ...... v

LIST OF TABLES ...... ix

LIST OF FIGURES ...... xii

LIST OF ABBREVIATIONS ...... xiii

LIST OF APPENDICES ...... xv

Chapter 1. Literature Review ...... 1

1.1 Introduction ...... 1

1.2 Apple polyphenols...... 2

1.2.1 Apple polyphenol consumption and health benefits ...... 2

1.2.2 Chemical structure and composition of apple polyphenols ...... 5

1.2.3 Bioavailability of apple polyphenols ...... 12

1.3 A. muciniphila and mucus-associated gut microbiota ...... 16

1.3.1 A. muciniphila as a beneficial commensal gut microbe ...... 16

1.3.2 Mucin-degrading and mucus-residing gut microbes ...... 19

1.4 Polyphenol and gut microbiota interactions ...... 24

1.4.1 Polyphenols as prebiotics and antibacterial compounds ...... 24

1.4.2 Proposed prebiotic or stimulatory mechanisms of polyphenols on A. muciniphila 29

Chapter 2. Hypothesis and Objectives ...... 39

2.1 Hypothesis ...... 39

2.2 Objectives ...... 39

Chapter 3. Materials and Methods ...... 40

3.1 Polyphenols used in the study ...... 40

3.2 Mucin gene expression and production by HT29-MTX cells in presence of polyphenols

...... 40

3.2.1 Cell culture conditions ...... 40

3.2.2 Sulforhodamine B (SRB) assay ...... 41

3.2.3 Polyphenol exposure to HT29-MTX cells ...... 42

3.2.4 RNA and protein extraction ...... 42

3.2.5 RT-qPCR for evaluation of the expression of selected mucin genes ...... 43

3.2.6 ELLA for quantification of total mucin-like glycoprotein ...... 48

3.3 Inhibitory effect of phlorizin, phloretin and chlorogenic acid on select bacteria ...... 50

3.3.1 Bacteria viable counts and optical density ...... 50

3.3.2 Broth minimal inhibitory concentration (MIC) ...... 51

3.4 In vitro growth of bacteria in mixed culture with the presence of polyphenols...... 51

3.4.1 In vitro mixed culture...... 51

3.4.2 PMA-qPCR for enumeration of bacteria ...... 52

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3.4.3 HPLC for polyphenol degradation analysis ...... 57

3.5 Statistical analysis ...... 58

Chapter 4. Results ...... 59

4.1 The effect of polyphenols on the expression of mucin genes and mucin production by

HT29-MTX cells ...... 59

4.2 The MIC of phlorizin, phloretin, and chlorogenic acid for the selected mucus-associated

gut bacteria ...... 63

4.3 The effect of polyphenols on the abundance of mucus-associated gut bacteria in in vitro

mixed culture ...... 65

Chapter 5. Discussion ...... 73

5.1 Effect of polyphenols on human epithelial cells ...... 73

5.1.1 Cytotoxicity of polyphenols ...... 73

5.1.2 Do polyphenols indirectly stimulate mucin production by the host cells? ...... 75

5.1.3 The use of HT29-MTX, RT-qPCR and ELLA for evaluating mucin stimulating

activity by food components ...... 78

5.2 Polyphenols and bacterial cell wall structure in relation to antibacterial activity ...... 80

5.3 Competition between A. muciniphila and other mucus-associated species in the presence

of polyphenols ...... 87

5.3.1 Indirect inhibitory activity of polyphenols against competitors favours

A. muciniphila ...... 87

5.3.2 Impact on other mucus-associated SCFA-producing species ...... 91

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5.3.3 Simultaneous stimulation of E. coli by polyphenols and the level of LPS ...... 93

5.4 Limitations of the study...... 103

5.5 Summary, conclusions and future perspectives ...... 105

REFERENCES ...... 109

APPENDICES ...... 137

LIST OF TABLES

Table 1: Average consumption of polyphenols and contribution of major foods and apples to the polyphenol intake depending on the population ...... 4

Table 2: Content of flavonoids per 100 g of fresh dessert apples with skin, and their relative proportion contributing to total flavonoid weight ...... 8

Table 3: Content of phenolic acids per 100 g of fresh dessert apples with skin, and their relative proportion contributing to total flavonoid weight...... 9

Table 4: Content of polyphenols in milligrams per 100 grams of dry weight pomace. Polyphenols were extracted using methanolic and acetonic extraction methods and quantified using HPLC . 10

Table 5: Polyphenols contained in apple pomace extract produced from enzymatic liquefaction using pectinases and cellulases ...... 11

Table 6: Beverage or meal containing defined amounts of apple polyphenols orally administered to ileostomist and % recovery from the ileal fluid...... 13

Table 7: Proportion of phlorizin and its metabolites out of total dihydrochalcone recovered in ileal fluid after 24 hours of drinking apple cider ...... 15

Table 8: MUC genes expression by the healthy intestinal tract categorized into subfamily of membrane bound or secreted (gel) forming mucins ...... 22

Table 9: Gut bacteria species known to degrade mucin in the gut ...... 23

Table 10: Bacteria species found to be involved in chlorogenic acid degradation ...... 36

Table 11: List of primers used for the mucin expression study ...... 45

Table 12: Standard curve of target genes constructed from pooled cDNA ...... 47

Table 13: 1:2 Dilution series of pooled cDNA (20 uL of 37.5 ng/uL)...... 47

Table 14: Evaluation of growth in THIO broth by OD at 600 nm and viable counts after 24 hours

...... 50

Table 15: Annealing time and temperature for each target primer ...... 53

Table 16: Target-specific primers used for taxonomic group/species included in this study...... 54

Table 17: Ct values of target and non-target gDNA ...... 56

Table 18: Standard curve and detection limit of target specific primers ...... 57

Table 19: Retention times of the standards used in the HPLC ...... 58

Table 20: Comparing the viability of HT29-MTX cells at increasing DMSO concentrations compared to the control (0 % DMSO) by SRB assay ...... 60

Table 21: The mean viability of HT29-MTX cells in the presence of phlorizin, phloretin, and chlorogenic acid at three concentrations relative to the control (0.2 % DMSO) by SRB assay ... 60

Table 22: The fold change expression of five mucin genes in the presence of 100 µM of phlorizin, phloretin and chlorogenic acid after 12 or 24 hours exposure compared to the control.

...... 61

Table 23: The effect of DMSO concentration on the viability of gut bacteria after 48 hours of exposure compared to the control ...... 63

Table 24: The effect of a) phlorizin, b) phloretin, and c) chlorogenic acid concentration on the viability (% compared to control) of gut bacteria ...... 64

Table 25: Log CFU/mL reduction of each group or species in the mixed culture in the presence of 250 µM of a) phlorizin, b) phloretin, and c) chlorogenic acid up to 7 days compared to the control without polyphenols (0.5 % DMSO) ...... 67

Table 26: Antimicrobial activity of phlorizin, phloretin, chlorogenic acid, and caffeic acid against probiotic and pathogenic species using a) MIC broth method or b) agar disc/well diffusion method unless otherwise stated ...... 85

Table 27: List of polyphenol a) extracts or b) pure or defined mixed of polyphenols that have been studied for their effect on the abundance of A. muciniphila in vitro or in vivo ...... 96

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LIST OF FIGURES

Figure 1: a) Basic structure of flavonoid and its 8 derivatives b) two main derivatives of phenolic acid...... 7

Figure 2: Chemical structure of phlorizinand phloretin-2’-O-glucuronide ...... 15

Figure 3: Suggested multi-factorial prebiotic and antibacterial effect of polyphenols on the growth of A. muciniphila...... 30

Figure 4: Degradation pathway of phlorizin by gut microbiota ...... 34

Figure 5: Proposed degradation of chlorogenic acid by gut microbiota ...... 34

Figure 6: Standard curve for the quantification of mucin by ELLA ...... 49

Figure 7: Total mucin-like glycoprotein measured using ELLA in a) the spent medium (secreted mucin) or b) the cell lysates (surface associated mucin) of HT29-MTX cells in the presence of

0.2 % of DMSO (control) or 100 µM of polyphenols ...... 62

Figure 8: Relative abundance of bacteria in a) the control (0.2 % DMSO) and in b) the 250 µM phloretin mixed culture at 24 hours incubation excluding E. coli...... 69

Figure 9: Growth of bacteria in the control broth (0.5 % DMSO) up to 7 days determined by

PMA-qPCR ...... 70

Figure 10: Absorbance of methanol-extracted phlorizin mixed culture showing persistence of phlorizin at day 7 of the incubation...... 71

Figure 11:Absorbance of methanol-extracted phloretin mixed culture showing persistence of phloretin at day 7 of the incubation...... 71

Figure 12: Absorbance of methanol-extracted chlorogenic acid mixed culture showing complete conversion of chlorogenic acid to caffeic acid at 48 hours...... 72

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LIST OF ABBREVIATIONS

BCA Bicinchoninic acid assay

BSA Boivin serum albumin

CFU Colony forming units

DMEM Eagle's minimal essential medium

DMSO Dimethyl sulfoxide

EGCG Epigallocatechin gallate

ELISA Enzyme linked immunosorbent assay

ELLA Enzyme linked lectin assay

FAA Fastidious anaerobic agar

FBS Fetal bovine serum

GI Gastrointestinal

HPLC High performance liquid chromatography

HFD High fat diet

IBD Inflammatory bowel disease

IgG Immunoglobulin G

LAB Lactic acid bacteria

LFD Low fat diet

LPS Lipopolysaccharide

MIC Minimal inhibitory concentration

MTX Methotrexate

OD Optical density

PAC Proanthocyanidins

PBS Phosphate buffer solution

PMA Propidium monoazide

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PVA Polyvinyl alcohol qPCR quantitative PCR

RegIII γ Regenerating islet-derived 3-gamma

ROS Reactive oxygen species

RT-qPCR Reverse transcriptase quantitative PCR

SCFA Short chain fatty acid

SHIME Simulator of human intestinal microbial ecosystem

SRB Sulforhodamine B

TCA Trichloroacetic acid

THIO Thioglycolate

WGA Wheat germ agglutin

LIST OF APPENDICES

Table A 1: Additional list of primers that were used for amplifying mucin and reference genes.

...... 137

Table A 2: Threshold cycle (Ct) obtained from gradient qPCR of mucin genes tested ...... 138

Table A 3: M values of GAPDH and cyclophilin for gene stability test ...... 138

Table A 4: Concentrations of gDNA used for the gradient qPCR ...... 139

Table A 5: Threshold cycle (Cq) obtained from gradient qPCR and melting peak temperature (in brackets) at various temperature for each primer on all bacterial DNA extracted in this study . 140

Table A 6: The difference between the Ct values of the live and compromised (comp) cells with or without the PMA treatment...... 144

Calculation A 7: Maximum concentration of phlorizin (472.44 g/mol), phloretin (274. 27 g/mol), and chlorogenic acid (354.311 g/mol) that can be dissolved in 0.2 % DMSO ...... 145

Table A 8:The fold change expression of the mucin genes in the presence of 100 µM of phlorizin, phloretin and chlorogenic acid for 30 minutes, 6, 12 or 24 hours compared to the control using Pfaffl method ...... 146

Calculation A 9: Concentration of undissociated form of caffeic acid in 250 µM concentration, pH of 5.0, and pKa of 4.64...... 146

Table A 10: The amount of phlorizin (436.4 g/mol), phloretin (274. 27 g/mol) and chlorogenic acid (354.311 g/mol) used in this study in milligrams assuming the gut volume is 3 L ...... 147

Table A 11: The amount of food required to obtain 100 mg or 250 mg of a) phlorizin and b) chlorogenic acid. Highest value in a range or mean was used for the calculation...... 147

Chapter 1 Literature Review

1.1 Introduction

Apples are one of the popular fruits consumed in Canada that contribute to the intake of dietary fruit polyphenols. In apple and apple by-products such as apple pomace, phlorizin and chlorogenic acid are present in relatively high concentration and have lower bioavailability compared to other polyphenols. Polyphenols have been associated with various health benefits, and recently, interactions with gut microbiota indicate their potential as prebiotics.

A. muciniphila is a gut microbe species that resides in the mucous layer and is involved in protection against metabolic and inflammatory bowel disease. Polyphenol extracts from fruits, teas and wine have been shown to promote the growth of A. muciniphila in mice or human in vivo models. In addition, the two polyphenols, phlorizin and chlorogenic acid, in pure form fed to mice have been shown to stimulate the growth of A. muciniphila. However, the mechanism of how polyphenols stimulate A. muciniphila is not yet clear, which prompted this study. Some of the suggested explanations include increased mucin production by the host cells and the suppression of mucus-associated competitors through the antibacterial property of polyphenols. To understand the mechanism, the use of pure forms of polyphenol is practical, rather than using complex extracts that contain varying amounts and types of polyphenols.

1.2 Apple polyphenols

1.2.1 Apple polyphenol consumption and health benefits

In Canada, apples are the third most accessible fresh fruit for consumption at 10.16 kg available per person in 2017 (Agriculture and Agri-Food Canada, 2017). Accordingly, apples are estimated to contribute 29 % of the total fruit polyphenol consumption in the North American diet (Burkholder-Cooley et al. 2016). The average consumption of polyphenols in diet is around

1000 mg based on various populations (Table 1). Similar to the North American diet, apples are one of the major contributors of fruit polyphenol intake in Polish, French, and Brazilian populations (Table 1). In return, apple pomace, left over solid residue after juicing, is produced as fruit waste. In 2009, out of 455,361 tons of apple produced in Canada, 11,384–13,661 tons

(20 - 30 %) cumulated as apple pomace (Dhillon et al. 2013). To utilize this waste, dietary fibre, pectin, polyphenols, and enzymes are extracted and utilized in animal feed or in food industry

(Sudha et al. 2007; Bhushan et al. 2008). Apple pomace is rich in fibre and polyphenols, and it have been tested for use in baked food products (Wang and Thomas 1989; Sudha et al. 2007).

Reviews of human intervention and epidemiological studies conclude with the potential antidiabetic and antioxidant effects of polyphenols (Dragsted 2003; Kim et al. 2016). For apple polyphenols, intervention studies indicate their possible roles in improving glucose tolerance

(Johnston et al. 2002), cardiovascular health (Jensen et al. 2009) and hypertension (Bondonno et al. 2012). In epidemiological studies, it is difficult to observe the efficacy of the apple polyphenols alone. Instead, the consumption of whole apples is shown to be inversely correlated with obesity, body weight and chronic inflammation, positively correlating with cardiovascular health (Chun et al. 2008; Larsson et al. 2013; Guo et al. 2017), and reducing the risk of mortality due to cardiovascular disease and cancer (Mink et al. 2007; Hodgson et al. 2016). Overall, the

consumption of apple products or apple polyphenols has been shown to be associated with health benefits (Boyer and Liu 2004; Biedrzycka and Amarowicz 2008; Hyson 2011; Bondonno et al.

2017).

Specifically, some of the examples of apple polyphenols that have gained attention by researchers for their functional potential are phlorizin and chlorogenic acid. Phlorizin was shown to have the most inhibitory activity against the intestinal sodium coupled glucose transporter 1 out of the other apple polyphenols tested, and the treatment with phlorizin resulted in the improvement of postprandial glucose response in high fat diet (HFD) mice (Schulze et al. 2014).

Likewise, apple polyphenol extract has been shown to reduce the plasma insulin level in healthy individuals (Schulze et al. 2014). Chlorogenic acid is also found in coffee and green coffee bean extracts, and the literature regarding their health benefits is reviewed by Tajik et al. (2017). The review supports its involvement in host lipid and glucose metabolism and anti-inflammatory and antioxidant properties that may have anticancer, antidiabetic, and antiobesity effects (Tajik et al.

2017).

Table 1: Average consumption of polyphenols and contribution of major foods and apples to the polyphenol intake depending on the population. The database used for calculating the polyphenol consumption was Phenol-Explorer except for Taguchi et al. (2015), Zujko et al. (2012), and Fukushima et al. (2009) that used their own database. yo = years old

Population Average Major contributors Contribution of Reference polyphenol of total polyphenol apples to consumption per intake (%) polyphenol day (mg) intake (%) Polish; 45-69 yo 1756.5 ± 695.8 coffee (40); tea Third highest Grosso et al. (n =10477) (27) chocolate (8) contributor of 2014 flavonoid intake (8) Japanese; 52-89 1492 ± 665 coffee (43); tea n/a Taguchi et al. yo (n = 610) (27) 2015 French; 45-60 1193 ± 510 coffee (44); tea (9); Highest Pérez-Jiménez yo (n = 4942) apples (9) contributor of et al. 2011 fruit polyphenol (45) Polish; 20-74 yo Men: 1172.5 ± coffee; tea Highest Zujko et al. (Men: n = 3132; 354 contributor of 2012 Women n = Women: 1031 ± fruit polyphenol 3529) 320 (60) Japanese; 10−59 853 ± 512 coffee (50); green n/a Fukushima et yo (n = 8767) (only beverage) tea (34) al. 2009 North American 801 ± 356 coffee consumers: Second highest Burkholder- (U.S. and coffee (65.3), fruit contributor of Cooley et al. Canada); (n = (8.6) fruit juice fruit polyphenol 2016 77441) (8.4) (29) non-coffee consumers: fruit (27.4); fruit juice (27.1); vegetables (13.9) Italian; type 2 683.3 ± 5.8 n/a n/a Vitale et al. diabetes; (n= 2017 2573) Brazilians; 10 460.15 ± 341.33 coffee (41); black Highest Corrêa et al. years and older bean (18.2); boiled contributor of 2015 (n = 34003) corn (12.5) fruit polyphenol (34.64) Spanish 332.7 ± 237.9 red wine (17.7); n/a Karam et al. (Mallorca); artichoke (6.2); soy 2018 Adult (n= 211) milk (5.4) Average 997.5

1.2.2 Chemical structure and composition of apple polyphenols

Polyphenols are found in plant-based food and beverages, such as fruits, vegetables, grains, chocolates, teas, and coffees. Polyphenols are compounds with at least one or more aromatic and hydroxyl group. There are three main classes of polyphenol based on chemical structure: flavonoids, phenolic acids, and stilbenes. Although phenols and phenolic acid describe a single aromatic ring with a hydroxyl group, the terms are generally used interchangeably with polyphenols in the literature (Zhang and Tsao 2016). To this date, there have been over 4,000 flavonoids identified from various plant sources, and flavonoids are the most prevalent class of polyphenols in the human diet and published research (Spencer 2008; Pandey and Rizvi 2009).

Flavonoids have two phenol rings (A and B rings) and an oxygen containing heterocycle ring (C ring) and are further classified into flavonols, flavones, flavanones, isoflavones, flavan-3-ols, anthocyanidins, flavanonols and dihydrochalcones (Figure 1a). Phenolic acids are aromatic rings with a carboxyl group and are derivatives of hydroxybenzoic or hydroxycinammic acids (Pandey and Rizvi 2009; Khoddami et al. 2013) (Figure 1b). Stilbenes are characterized by their 1,2- diphenylethylene structure (Sirerol et al. 2016).

The profile of polyphenols in apples is well described and conserved, but the concentrations of each polyphenol and the total polyphenol content can vary from 10 mg to

50 mg of polyphenols per 100 g of fresh apples (Manach et al. 2004). Generally, polyphenols are concentrated in the skin of the apple for protection against UV radiation and pathogen invasion

(Solovchenko and Schmitz‐Eiberger 2003). The top three flavonoids with the highest proportion that contribute to the total flavonoid weight in dessert apples with skin are procyanidin dimer B2

(39.71 %), epicatechin (22.4 %), and phlorizin (7.2 %) (Table 2). As for the phenolic acid content, chlorogenic acid accounts for the highest proportion at 70.37 % of the total phenolic

acid in weight (Table 3). Chlorogenic acid is also the most abundant polyphenol in commercial clear and cloudy apple juice products ranging from 52.9 – 135.4 mg/L and in apple cider ranging from 117.3 – 487.6 mg/L (Kahle et al. 2005).

Interestingly, phlorizin is a polyphenol unique to apples (Manach et al. 2004; Marks et al.

2009; D’Archivio et al. 2010; Gwiazdowska et al. 2015), and it is the most abundant polyphenol extracted from apple pomace using methanolic and acetonic extract methods along with quercetin-3-galactoside (Table 4). A similar result was found in apple pomace extract produced from enzymatic liquefaction using pectinases and cellulases, with phlorizin having the highest concentration at 78.9 mg / g of extract (Table 5). As well, in apple by-products such as pomace, phlorizin is present in concentrations of 36 mg to 142 mg per 100 g of dry weight, higher than the concentration of fresh apples (Lu and Foo 1997; Suárez et al. 2010).

Figure 1: a) Basic structure of flavonoid and its 8 derivatives (Braune et al. 2016) b) Two main derivatives of phenolic acid (Khoddami et al. 2013).

Table 2: Content of flavonoids per 100 g of fresh dessert apples with skin, and their relative proportion contributing to total flavonoid weight (Neveu et al. 2010). *Mean calculated from collection of literature

Classification Polyphenol Mean (mg/100 g) Proportion (%) Flavan-3-ols (+)-Epicatechin 8.37 ± 3.67 22.4 (+)-Catechin 1.22 ± 0.83 3.3 Procyanidin dimer B2 14.6 ± 9.19 39.1 Flavonols Quercetin 0.13 ± 0.06 0.3 Quercetin 3-O-arabinoside 1.40 ± 1.12 3.7 Quercetin 3-O-galactoside 2.36 ± 1.20 6.3 Quercetin 3-O-glucoside 0.64 ± 0.77 1.7 Quercetin 3-O-rhamnoside 1.33 ± 1.57 3.5 Rutin (Quercetin 3-O-rutinoside) 0.22 ± 0.06 0.6 Quercetin 3-O-xyloside 0.78 ± 0.58 2.1 Dihydrochalcones 3’-hydroxyphloretin 2’-O-glucoside 0.11 ± 0.12 0.3 Phloretin 2’-O-xylosyl-glucoside 2.58 ± 2.09 6.9 Phlorizin (phloretin-2’-O-glucoside) 2.69 ± 1.92 7.2 Anthocyanins Cyanidin 3-O-arabinoside 0.06 ± 0.07 0.2 Cyanidin 3-O-galactoside 0.81 ± 0.88 2.2 Cyanidin 3-O-xyloside 0.06 ± 0.09 0.2 Total 37.36 100

Table 3: Content of phenolic acids per 100 g of fresh dessert apples with skin, and their relative proportion contributing to total flavonoid weight (Neveu et al. 2010).*Mean calculated from collection of literature.

Classification Polyphenol *Mean content (mg/100 g) Proportion (%) Hydroxybenzoic Gentisic acid 0.22 ± 0.08 1.2 acids Syringic acid 0.90 ± 1.21 4.7 Hydroxycinnamic 4-Caffeoylguinic acid 0.54 ± 0.44 2.8 acids 4-p-Coumaroylquinic acid 2.25 ± 1.92 11.9 Chlorogenic acid 13.37 ± 11.26 70.4 5-p-Coumaroylquinic acid 1.05 ± 0.07 5.5 Caffeic acid 0.33 ± 0.45 1.7 Ferulic acid 0.07 ± 0.10 0.4 p-Coumaric acid 0.27 ± 0.21 1.4 Total 19.0 100

Table 4: Content of polyphenols in milligrams per 100 grams of dry weight pomace. Polyphenols were extracted using methanolic and acetonic extraction methods and quantified using HPLC. 1(Suárez et al. 2010); 2 (Lu and Foo 1997); n/a-not detected or available

Polyphenol Methanolic1 Acetonic1 Acetonic2 Epicatechin 8.845 8.821 64.0 B2 procyanidin dimer 7.487 6.567 n/a Chlorogenic acid 1.6612 17.056 n/a Caffeic acid 2.227 1.968 28.0 Quercetin 3-O-galactoside 25.371 21.301 161.0 Quercetin 3-O-glucoside & 12.228 10.326 87.0 Quercetin 3-O- rutinoside Quercetin-3-D-xyloside 7.397 5.951 53.0 Quercetin-3-O-α-arabinofuranoside 18.510 14.646 98.0 Quercetin 3-rhamnoside 13.178 10.558 47.0 Phloretin-2’-xyloglucoside 17.072 17.004 17.0 Phlorizin 38. 005 36.238 142.0 3-Hydroxyphloridzin n/a n/a 27.0 Protocatechuic acid 0.13433 0.11819 n/a

Table 5: Polyphenols contained in apple pomace extract produced from enzymatic liquefaction using pectinases and cellulases (Fridrich et al. 2007).

Polyphenol mg/g apple pomace extract

Epicatechin 17.7 Catechin 2.7 B1 procyanidin dimer 6.2 B2 procyanidin dimer 18.4 Chlorogenic acid 19.2 Caffeic acid 4.0 Quercetin 3-O-galactoside (hyperoside) 8.1 Quercetin 3-O-glucoside (isoquercetin) 12.3 Quercetin 3-O- rutinoside (rutin) 49.1 Quercetin-3-D-xyloside (reynoutrin) 18.1 Quercetin-3-O-α-arabinofuranoside (avicularin) 3.5 Quercetin 3-rhamnoside (quercitrin) 25.1 Phloretin-2’-xyloglucoside 31.7 Phlorizin 78.9

1.2.3 Bioavailability of apple polyphenols

Most polyphenols in plants are naturally found with glycosides, esters, or polymers, which stabilize the structure in plants and also reduce the bioavailability in humans (Manach et al. 2004; Espín et al. 2017). This may be because the attached sugar or ester linkage are too hydrophilic, or the molecule is too large and cannot be passively absorbed (Hollman et al. 1999).

Bioavailability is defined as the fraction of dose that is absorbed into the systemic circulation

(Heaney 2001) or is the quantity of dose absorbed that reaches a specific tissue site at which it exerts a health beneficial function (D’Archivio et al. 2010). It is estimated that approximately

90 % to 95 % of dietary polyphenols are not absorbed by the small intestine and instead are likely to reach the colon (Clifford 2004). More accurately, the amount of polyphenols and associated metabolites contained in ileal fluid of ileostomists can be used to estimate the amount of polyphenols or polyphenol metabolites that reach the large intestine (Olthof et al. 2001).

Based on ileostomy studies, chlorogenic acid and dihydrochalcones (including phlorizin) have relatively higher recovery rate compared to other polyphenols, at 61.8 % to 71 % and 38.8 % respectively (Table 6). The high recovery rate of chlorogenic acid may be due to the lack of esterase activity observed in intestine, liver and plasma extracts, and the esterase activity is only present in fecal samples (Plumb et al. 1999). In addition to the chemical structure of polyphenols, factors such as food matrix, processing, and host related factors including gut microbiota can affect the bioavailability of polyphenols (D’Archivio et al. 2010).

Table 6: Beverage or meal containing defined amounts of apple polyphenols orally administered to ileostomist and % recovery from the ileal fluid. Higher recovery indicates lower bioavailability.

Polyphenols % recovered in ileum Reference (+) Catechin 2.3 Borges et al. 2013 (-) Epicatechin 4.2 Borges et al. 2013 Procyanidin B2 dimer 22 Borges et al. 2013 Quercetin 19.3–35.5 Walle et al. 2000 Walle et al. 2000 Chlorogenic acid 67 Olthof et al. 2001 71 Stalmach et al. 2010 61.8 Borges et al. 2013 70.07 Hagl et al. 2011 Caffeic acid 5 Olthof et al. 2001 Dihydrochalcone 38.8 Borges et al. 2013 (Phloretin-2’-xyloglucoside, 38.6 Marks et al. 2009 phlorizin and their metabolites

More specifically for phlorizin, a study by Marks et al. (2009) determined absorption and metabolism of phlorizin contained in apple cider by healthy and ileostomist volunteers. Ileal fluids of the ileostomists were collected and showed that 38.6 % of dihydrochalcone contained in the apple cider was recovered (Marks et al. 2009). Phlorizin was most likely cleaved into phloretin, removing the glucose, by lactase phlorizin hydrolase or β-glucosidase of small intestine epithelial cells (Day et al. 1998; Day et al. 2000). Although there is no research, lactose intolerant individuals with low levels of lactase phlorizin hydrolase are expected to have less efficient absorption of phlorizin (Montgomery et al. 1991; Ehrenkranz et al. 2005). Then, phloretin was glucuronidated or sulfonated into related metabolites, where phloretin-2-O- glucronide counted for most of the metabolites in the ileal fluid (Table 7). The structure of phlorizin and phloretin-2’-O-glucuronides are similar, and the only difference is the double bonded oxygen on the glucose (Figure 2). Still, phloretin was present in the ileal fluid, at an approximately 3,000 times greater amount than the phloretin measured in the apple cider, which showed that phloretin produced from phlorizin is not all glucuronidated or sulfonated (Marks et al. 2009). However, there was no significant difference between the excretion level of the dihydrochalcones and its metabolites in the urine of healthy and ileostomist volunteers, which indicated that the absorption of phlorizin occurred most significantly in the small intestine

(Marks et al. 2009). Overall, although phlorizin appeared to be converted into metabolites by the small intestine, they are incompletely absorbed and reach the large intestine.

Table 7: Proportion of phlorizin and its metabolites out of total dihydrochalcone recovered in ileal fluid after 24 hours of drinking apple cider (Marks et al. 2009).

Metabolite Proportions (%) Phloretin-2-(2-O-xylosyl)glucoside 17.8 Phloretin-O-(O-xylosyl)hexoside 4.03 Phloretin-2-O-glucuronide 39.8 Phloretin-O-glucuronide (peak 4) 1.46 Phloretin-O-glucuronide (peak 5) 7.20 Phloretin-O-glucuronide-O-sulfate 7.96 Phloretin 13.6 Phloretin-O-sulfate (peak 8) 7.63 Phloretin-O-sulfate (peak 9) 0.486

Figure 2: Chemical structure of phlorizin (left) and phloretin-2’-O-glucuronide (right) (PubChem).

1.3 A. muciniphila and mucus-associated gut microbiota

1.3.1 A. muciniphila as a beneficial commensal gut microbe

Gut microbiota, defined as the “community of microorganisms” in the gut (Macke et al.

2017), contains 150 times more genes than the entire human genome in our body (Qin et al.

2010), and the composition has been associated with various health and disease conditions such as metabolic disease, autoimmune disease, respiratory disease, colorectal cancer, and psychological disease (Wang et al. 2017). The composition of gut microbiota varies interpersonally and intrapersonally, possibly from a range of factors such as age (Odamaki et al.

2016), host genetics (Goodrich et al. 2014), medication (Falony et al. 2016) and food (Graf et al.

2015). There is yet a consensus for which key species or functions are essential for healthy gut microbiota (Marchesi et al. 2016). The commensal or “normal” gut microbiota are microbes residing on the intestinal epithelial surface that are in symbiosis with the host, meaning that there is a broad range of interactions such as mutualistic, commensal, and parasitic relationships

(Tlaskalová-Hogenová et al. 2011; Jang and Benbow, 2013). The main phyla of the commensal gut microbiota consists of Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria,

Verrucomicrobia, and Fusobacteria (Eckburg et al. 2005; Rinninella et al. 2019).

A. muciniphila is the only known genus member of the Verrucomicrobia phylum in the gut (Geerlings et al. 2018). The colonization of A. muciniphila begins early in life and stabilizes to approximately 108 cells/g feces or 1 % to 3 % of gut microbiota, and the abundance decreases with age (Collado et al. 2007; Derrien et al. 2008). It resides abundantly in the distal colon and in the intestinal mucous layers as it prefers higher pH and uses and degrades mucin as energy and carbon source (Derrien et al. 2008; Van Herreweghen et al. 2017). Originally, A. muciniphila has been described as strictly anaerobic (Derrien et al. 2004), but it has been shown to be oxygen

tolerant in in vitro broth medium (Ouwerkerk et al. 2016). This is most likely because the gut bacteria in the mucous layer are in close contact with the oxygen that can diffuse from the host epithelial cells (Ouwerkerk et al. 2016).

Preclinical trials show that the abundance of A. muciniphila is inversely correlated with metabolic diseases and is proposed to be the “next-generation beneficial microbes” (Cani and de

Vos 2017). It has been associated with protection against metabolic syndrome that can increase the risk of developing type 2 diabetes and cardiovascular disease, such as obesity and insulin resistance, by promoting the secretion of mucin by the host cell and increasing the thickness of mucous layer, protecting against lipopolysaccharide (LPS) absorption or endotoxemia (Huang

2009; Everard et al. 2013). This is contrary to the assumption that mucin degradation is commonly associated with pathogenesis (Derrien et al. 2010). For instance, A. muciniphila is more abundant in healthy individuals than in obese individuals (Karlsson et al. 2012) or inflammatory bowel disease (IBD) patients (Png et al. 2010). One possible explanation to the increased mucin production is the conversion of degraded mucin into short chain fatty acids

(SCFA) that are utilized by mucus secreting epithelium cells as an energy source to produce more mucin (Zhou 2017). As well, higher abundance of A. muciniphila and fecal microbiome richness were correlated with a healthier metabolic profile, including blood glucose and triglyceride level and fat distribution in human volunteers (Dao et al. 2016). Most importantly, a randomized, double-blind, placebo-controlled pilot human study supported that the daily administration of 1010 CFU of live or pasteurized A. muciniphila improved the metabolic markers (insulin resistance and sensitivity and plasma cholesterol) in 32 overweight, obese or insulin resistant individuals (Depommier et al. 2019).

Furthermore, Plovier et al. (2017) isolated and identified Amuc_1100, a pili-like protein on the outer membrane of A. muciniphila. It binds to the toll-like receptor 2 (TLR2) which is involved in maintenance of host homeostasis and metabolism, partly explaining the beneficial role of A. muciniphila in maintaining the gut barrier function. Also, Amuc_1100 is only denatured at 70 oC and was stable during pasteurization. As a result, all live and pasteurized

A. muciniphila or Amuc_1100 isolated protein alone was able to normalize the LPS concentration of HFD mice compared to the control group. The ability of pasteurized

A. muciniphila to exhibit beneficial effect was a key to overcoming its oxygen sensitive properties. In addition, despite of A. muciniphila being a Gram negative bacteria with LPS,

A. muciniphila is only shown to induce an equivalent proinflammatory interlukin-8 response at a

100 folds higher cell concentration compared to Escherichia coli K12 derived cells in Caco-2 cells (Reunanen et al. 2015).

At the same time, there is evidence that links the presence of A. muciniphila with negative health implications. Higher abundance was associated with multiple sclerosis (Jangi et al. 2016) and colorectal cancer (Weir et al. 2013) patients compared to healthy individuals. As well, the proinflammatory cytokine response was enhanced when Salmonella typhimurium colonized the gut in presence of A. muciniphila compared to S. typhimurium alone based on a mice model (Ganesh et al. 2013). There was a reduction in the number of goblet cells compared to mice colonized with only A. muciniphila or S. typhimurium, which showed the ability of

A. muciniphila to disturb the mucus homeostasis of the host and compromise the gut barrier together with the pathogenic species (Ganesh et al. 2013).

1.3.2 Mucin-degrading and mucus-residing gut microbes

There are four types of intestinal epithelial cells reviewed by Peterson and Artis (2014): enterocytes, enteroendocrine cells, Paneth cells, and goblet cell. Enterocytes are the most abundant type of intestinal epithelial cells that are responsible for the absorption, digestion and metabolism of nutrients. Enteroendocrine and Paneth cells are involved in the secretion of hormones and antimicrobial proteins, respectively. Mucin, a glycoprotein that is the major component of the mucus, is secreted by goblet cells.

There are two types of mucins: secreted (includes gel or non-gel forming) and membrane-bound mucin. Membrane-bound protein contains hydrophobic transmembrane component and phosphorylation sites involved in signal induction that are lacking in secreted mucins (Macha et al. 2015). As well, the pattern of mucin expression differs depending on the tissue type (Table 8). MUC2 and MUC4 genes are predominantly expressed in the colon (Aslam et al. 1999). MUC2 forms firm and sterile inner mucous layer and outer loose layer of the mucous where the commensal bacteria can attach and reside (Johansson et al. 2011). Mucus- associated or degrading bacteria are in an environment supplied with a consistent source of nutrients and can withstanding the fecal stream that are advantageous over luminal bacteria for survival (Derrien et al. 2010; Donaldson et al. 2016). That being said, the degradation of mucin must be modulated in order to not diminish the protective function of the mucous layer (Derrien et al. 2010). Mucins have several key functions in aiding physiological processes according to

Hollingsworth and Swanson (2004):

1. Physical barrier –secreted gel-forming mucins can form the outer layer of the mucous layer

and provide protection for the epithelium cells against pathogen invasion, and the sieve-like

structure limits passage of molecules.

2. Hydration and lubrication –hydroscopic property keeps moisture and eases the transition of

food and feces throughout the GI tract.

3. Maintenance of local molecular environment –neutral and charged moieties contribute to

local concentrations, hydrations, ionic exchanges, and chemical compositions of the mucous

layer. Mucin may sequester bioactive molecules such as cytokines, chemokines, and growth

factors. Negatively charged moieties from sulphation and sialylation repels and allows

passage of negatively charged molecules but retains positively charged molecules.

4. Signal transduction and function as ligands –cell-surface associated mucins are involved in

signal transduction and secreted mucins can interact with passing molecules and microbiota.

5. Maintenance of gut microbiota – the oligosaccharide component of mucin accounts for the

80 % of mass in mucin, and the diverse “oasis” of oligosaccharide component provides

adhesion site, nutrient and protection for the gut microbiota (Derrien et al. 2010).

The ability of mucus-degrading bacteria to utilize mucin may be essential to the colonization and the persistence in the gut microbiota. For example, in a mice model, the persistence of Bacteroides thetaiotaomicron in the gut was compromised with the deletion of extracytoplasmic function sigma transcription factor responsible for activating the O-glycan utilizing gene in B. thetaiotaomicron (Martens et al. 2008). In a SHIME model, the presence of mucin accounted for 26 % of the variation in the microbial community, with increased

A. muciniphila, Bacteroides, and Ruminococcus abundance (Van Herreweghen et al. 2018). The effect of glycan is also evident in “enterotypes” that may be shaped by diet based glycans, where a diet rich in meat can select for Bacteroides, plant fibre can select for Prevotella, and the absence of both may select for host glycan consuming species (Koropatkin et al. 2012).

There are other mucin-degrading species besides A. muciniphila identified (Table 9), and potential mucus-associated bacterial groups have been identified based on mucosal-simulator of human intestinal microbial ecosystem (M-SHIME) by Van den Abbeele et al. (2013). The major groups of bacteria associated with the mucin beads of M-SHIME were Clostridium cluster XIVa,

Clostridium cluster IV, Bacteroidetes, and Proteobacteria (Van den Abbeele et al. 2013).

Clostridium cluster XIVa includes the Lachnospiraceae and Ruminococcaceae families and have also been known as the Eubacterium rectale–Clostridium coccoides group (Nava et al. 2011).

Clostridium cluster IV includes Faecalibacterium prausnitzii, some Eubacterium and

Ruminococcus species, and Flavonifractor plautii that degrades phloretin (Schoefer et al. 2003).

Both Clostridium Cluster XIVa and IV are known to degrade complex carbohydrates into SCFA such as acetate, propionate, and butyrate, which are the main sources of energy for host colonocytes (Hayashi et al. 2006; Biddle et al. 2013; Van den Abbeele et al. 2013). In addition, a pilot clinical study showed that members of the Enterobacteriaceae family, such as E. coli, were present in the colon mucosal layer, where lower microbial diversity and higher presence of

Enterobacteriaceae were associated with individuals with diverticular disease than healthy individuals (Linninge et al. 2018). More specifically, E. coli K-12 MG1655 strain, representing commensal E. coli, was found to colonize the mucous layer in a mice model (Miranda et al.

2004).

Table 8: MUC genes expression by the healthy intestinal tract categorized into subfamily of membrane bound or secreted (gel) forming mucins (Andrianifahanana et al. 2006)

Gene Subfamily Locus Tissues MUC 1 Membrane 1q21 Colorectum; Small intestine; Duodenum; Stomach MUC 2 Secreted 11p15.5 Colorectum; Small intestine; Duodenum MUC 3 Membrane 7q22 Colorectum; Small intestine; Duodenum; Stomach MUC 4 Membrane 3q29 Colorectum; Esophagus MUC5AC Secreted 11p15.5 Stomach MUC5B Secreted 11p15.5 Esophagus MUC6 Secreted 11p15.5 Duodenum; Stomach MUC11 Unclassified 7q22 Colorectum MUC12 Membrane 7q22 Colorectum MUC13 Membrane 3q13.3 Colorectum; Stomach MUC17 Membrane 7q22 Colorectum; Small intestine; Duodenum MUC 20 Membrane 3q29 Colorectum; Small intestine; Duodenum; Stomach; Esophagus

Table 9: Gut bacteria species known to degrade mucin in the gut (Derrien et al. 2010; Tailford et al. 2015).

Phylum Species Firmicutes Streptococcus mutans Streptococcus anginosus Streptococcus sobrinus Streptococcus sanguinis Streptococcus oralis Clostridium septicum Ruminococcus torques Ruminococcus gnavus Bacteroidetes Bacteroides thetaiotaomicron Bacteroides vulgatus Bacteroides fragilis Bacteroides caccae Prevotella sp. Actinobacteria Streptomyces sp. Bifidobacterium bifidum Bifidobacterium longum subsp. longum B. longum subsp. infantis Bifidobacterium breve Proteobacteria Vibrio cholerae Helicobacter pylori Verrucomicrobia A. muciniphila

1.4 Polyphenol and gut microbiota interactions

1.4.1 Polyphenols as prebiotics and antibacterial compounds

Food can impact the composition and the health outcomes associated with the gut microbiota. Particularly, a prebiotic is “a substrate that is selectively utilized by host microorganisms conferring a health benefit”, which can be applied to undigested components of food, including non-carbohydrate substrates, that interacts with the gut microbiota and provide health benefits (Gibson et al. 2017). The definition of prebiotic was first introduced in 1995 by

Gibson and Roberfroid, mainly focused on nondigestible oligosaccharides. Today, accepted and potential prebiotics include oligosaccharides, polyunsaturated fatty acids and phenolics, which require more studies to be considered as potential prebiotics for gut microbiota (Lee et al. 2006;

Boto-Ordóñez et al. 2014; Gibson et al. 2017). This decision was supported, as mentioned before, because of the estimate suggesting that 90 % to 95 % of dietary polyphenols are not absorbed by the small intestine, and instead are likely exposed to the gut microbiota (Clifford

2004).

Oligosaccharides and polysaccharides are the best well known and established prebiotics that have been demonstrated to stimulate health beneficial Bifidobacterium or have bifidogenic effects in the gut (Slavin 2013). Examples of these carbohydrates that have bifidogenic effects in human studies are inulin from artichokes (Costabile et al. 2010; Ramnani et al. 2010), fructooligosaccharides and galactooligosaccharides (Liu et al. 2017), and gum arabic (Calame et al. 2008). Bifidobacterium strains by themselves have been accepted as probiotics that are defined as “live microorganisms which, when administered in adequate amounts, confer a health benefit on the host” (Hill et al. 2014). The health benefits associated with Bifidobacterium are well established, and reviewed health beneficial properties include reduction of diarrhea in

infants, reduction of fecal transit time aiding in constipation, prevention of pathogenic bacteria colonization, and potential improvements in IBD and colorectal cancer (Picard et al. 2005;

O’Callaghan and van Sinderen 2016). In Canada, Bifidobacterium is considered as probiotic in food, but no strain specific claims are currently accepted and only non-strain specific general probiotic functional claims, such as “contribution to healthy gut flora” can be made (CFIA

2019). Other probiotic health benefits may include improvement of the gut barrier and immune function, suppression of pathogenic bacteria, and increased production of SCFA (Slavin 2013).

In nature, polyphenols are produced by plants as secondary metabolites and act as antimicrobial compounds for protection against pathogen invasion (Pandey and Rizvi 2009).

Consequently, polyphenols are proposed to have the potential to selectively promote the growth of beneficial bacteria and supress the pathogenic species in the gut (Cueva et al. 2010; Hervert-

Hernández and Goñi 2011; Etxeberria et al. 2013). Polyphenols and gut microbiota have a

“reciprocal interaction”, where polyphenols may modulate gut microbiota composition, and gut microbiota may degrade polyphenols (Valdés et al. 2015; Ozdal et al. 2016). In addition, the degraded phenolics may exhibit different antibacterial activity than that of the parent compound

(Parkar et al. 2008) or have anti-inflammatory activity that benefits the host (Karlsson et al.

2005). However, this antimicrobial activity does not fit with the definition of a prebiotic given by

Gibson et al. (2017). as it is not being utilized by particular bacteria, although it may indirectly support the growth of beneficial bacteria via suppression of undesired bacteria and may be referred as “prebiotic-like” effects (Laparra and Sanz 2010; Markowiak and Śliżewska 2017).

Currently, there is no consensus on the mechanism of action for the antibacterial activity of polyphenols, but there are several suggested mechanisms (Gyawali and Ibrahim 2012; Pernin et al. 2018). The antibacterial mechanisms of plant metabolites, including flavonoids, are

reviewed extensively elsewhere (Cushnie and Lamb 2011; Gyawali and Ibrahim 2012;

Radulović et al. 2013; Farhadi et al. 2019) and summarized as:

• Disruption of the cell membrane including the peptidoglycan cell wall, plasma membrane

and outer membrane for the Gram negative bacteria. E.g. epigallocatechin gallate (EGCG)

has been demonstrated to disrupt the lipid membrane (Ikigai et al. 1993).

• Interference with intracellular processes such as gene expression, protein synthesis and

energy metabolism. E.g. Flavonoids isolated from Dorstenia species inhibited the DNA,

RNA and protein synthesis of S. aureus determined by radiolabeled thymidine, uridine, and

methionine (Dzoyem et al. 2013).

• Interference in intercellular interactions such as quorum sensing and biofilm formation. E.g.

rutin at sub-MIC concentrations (50 % of MIC) prevented the formation of biofilms and

reduced exopolysaccharide production by E. coli and S. aureus (Al-Shabib et al. 2017).

The disruption of the cell membrane appears to the main target of action (Radulović et al. 2013), and one flavonoid may have multiple mechanisms of action (Cushnie and Lamb 2005). The antibacterial mechanisms of the flavonoids are likely to be conserved as the basic structures are shared among flavonoids (Cushnie and Lamb 2011).

Still, there may be structural dependency in the degree of antibacterial activity.

Deglycosylated aglycones tend to have higher antibacterial potential than the glycosylated polyphenol or the parent compound in general (Parkar et al. 2008; Cueva et al. 2010; Duda-

Chodak 2012; Duda-Chodak et al. 2015), which suggest that phloretin would have higher antibacterial activity than phlorizin. On the other hand, chalcones such as phlorizin and phloretin are shown to have higher antibacterial activity with increased hydroxyl (OH) group (Farhadi et al. 2019). In this case, phlorizin would be expected to have higher antibacterial activity. In

general, flavonoids may have higher antibacterial potential with increasing number of the OH groups on the B-ring (Puupponen-Pimiä et al. 2001). Structures containing the pyrogallol

(3 - OH) group was found to have greater antibacterial activity than catechol or resorcinol groups

(2 - OH) towards anaerobic and facultatively anaerobic pathogens (Taguri et al. 2006).

On the contrary, there is evidence that favours higher antibacterial activity by increasing hydrophobicity, or decreasing OH groups, for Gram negative bacteria such as E. coli (Bouarab-

Chibane et al. 2019). For example, E. coli and Pseudomonas fluorescence are more susceptible to structures with decreasing number of OH groups, as hydrobenzoic acid was more effective than gallic acid (Gutiérrez-Larraínzar et al. 2012). In another study, propyl gallate was more antibacterial than methyl gallate against Gram negative E. coli, S. typhimurium, B. fragilis,

Enterobacter cloacae but no similar trend was observed for Gram positive bacteria including

B. infantis, Lactobacillus acidophilus, and Clostridium spp.(Chung et al. 1998).

Moreover, Gram positive bacteria tend to be more susceptible to the antibacterial activity of the polyphenols than Gram negative bacteria (Ikigai et al. 1993; Cueva et al. 2010; Gyawali and Ibrahim 2012; Bouarab-Chibane et al. 2019), while some suggest that there is no link between Gram-staining and the resulting antimicrobial activity of polyphenols (Taguri et al.

2006), or disagrees with the trend and show that Gram negative bacteria are more susceptible

(Chung et al. 1998; Borges et al. 2013). The contradictions in the literature may be due to the antibacterial mechanism of polyphenols being dependent on both the chemical structure of the polyphenol and the strain of bacteria. For instance, Pernin et al. (2019) developed three models of mechanisms depending on the chemical structure:

1. Reduction of pH (chlorogenic acid and gallic acid)

2. Reduction of pH + undissociated forms (protocatechuic acid, p-hydroxybenzoic acid, vanillic

acid, caffeic acid)

3. Reduction of pH + undissociated forms + dissociated forms (ferulic acid, p-coumaric acid)

Undissociated forms of phenolic acid may act similar to organic acids and accumulate in the membrane or the cytoplasm and cause cell acidification, and dissociated forms may also disturb the cell membrane or interact with particular cell receptors (Pernin et al. 2019). In addition,

Bouarab-Chibane et al. (2019) was able to apply quantitative structure-activity relationship model for Gram-negative bacteria (E. coli and Salmonella enteritidis) with lipophilicity and charges of polyphenols as the main descriptors, but the models were not able to be applied to

Gram positive bacteria (Staphylococcus aureus and Bacillus subtilis). Because Gram positive and negative bacteria have fundamentally different cell surface characteristics, this emphasized the cell surface characteristics as one of the potential key factors in understanding the polyphenol and bacteria interaction (Bouarab-Chibane et al. 2019).

Furthermore, the antibacterial activity of polyphenols as natural antimicrobial compounds has been researched for food spoilage, pathogenic, and probiotic bacteria but studies on the commensal gut bacteria are limited (Duda-Chodak et al. 2015). It is worth noting that pure tea polyphenols (caffeic acid, epicatechin, catechin, and gallic acid, etc) appeared to inhibit pathogenic Clostridium (Clostridium perfringens and Clostridium difficile) but not the commensal Clostridium spp. or Bifidobacterium spp., indicating that commensal bacteria may have more resistance to the dietary polyphenols (Lee et al. 2006). As well, most of the literature on the commensal gut bacteria reported have only used the MIC method (Lee et al. 2006; Parkar et al. 2008; Cueva et al. 2010) which is based on visible growth and cannot discriminate between bactericidal or bacteriostatic effects (Pankey and Sabath 2004).

1.4.2 Proposed prebiotic or stimulatory mechanisms of polyphenols on A. muciniphila

The use of polyphenols as prebiotic for A. muciniphila has been proposed based on findings suggesting growth stimulation by various polyphenols (Anhê, Varin, et al. 2015; Anhê,

Roy, et al. 2015; Anhê et al. 2016; Eid et al. 2017; N. Zhang et al. 2018). The stimulatory effect of polyphenol extract from various sources or pure polyphenols, on A. muciniphila in both in vitro and in vivo models, indicate that the overall effect on the gut microbiota composition varies depending on the source. For example, red wine grape extract was shown to have more antibacterial effect than black tea extract tested in one study using identical conditions in the

Twin-SHIME (Kemperman et al. 2013). This may be due to the fact that, although the use of extract can reduce cofounding variables such as fibre, protein, and sugar (Anhê et al. 2016), it still contains variable types and concentrations of polyphenols depending on the source and the processing steps (Neveu et al. 2010) that make it difficult to deduce which polyphenol is responsible for the effect. In addition, the prebiotic and antibacterial effects contributing to the stimulation of A. muciniphila may be multi-factorial (Figure 3). Hence it is important to note that each polyphenol may have a different profile of mechanisms against A. muciniphila depending on its chemical structure.

Figure 3: Suggested multi-factorial prebiotic and antibacterial effect of polyphenols on the growth of a b c d A. muciniphila. Gibson et al. (2017) Roopchand et al. (2015); Henning et al. (2017); Anhê et al. (2015) and Kemperman et al. (2013); eShen et al. (2017); fMorgan et al. (2012); gNeyrich et al. (2017). ↑ increase; ↓ decrease.

For the study of mechanisms, one approach is to separately study the major polyphenols in a pure form (Baldwin et al. 2016; Ozdal et al. 2016). For example, in vivo studies show the ability of pure forms of the two prominent apple polyphenols, phlorizin and chlorogenic acid, to promote A. muciniphila growth. In a db/db induced obese mice model, 20 mg of phlorizin per kilogram body weight administered intragastrically for 10 weeks shifted the gut microbiota composition closer to the control healthy mice (Mei et al. 2016). In addition, qPCR of

A. muciniphila showed that the abundance in db/db mice treated with phlorizin became similar to that of control mice (Mei et al. 2016). As for chlorogenic acid, administration in drinking water significantly increased the abundance of A. muciniphila quantified by qPCR for both colitis- induced and healthy mice (Z. Zhang et al. 2017)

Polyphenols utilized as energy or carbon source, directly stimulating A. muciniphila, would fulfill the current prebiotic definition (Gibson et al. 2017) and would have similar prebiotic function as the best accepted prebiotic, namely oligosaccharide (Slavin 2013). As well, antioxidant activity, although it may not be specific to A. muciniphila, may also provide direct benefit for survival (Roopchand et al. 2015). Obligate anaerobes such as A. muciniphila (Derrien et al. 2004) rely on enzymes that react with oxidants for the metabolism, and the formation of free radicals from oxygen can occur upon exposure to air and can cause oxidative stress (Imlay

2002). Additionally, mucus-associated bacteria residing close to the host epithelial cells are exposed to higher levels of oxygen than the luminal bacteria (Donaldson et al. 2016).

Flavonoids, such as quercetin, can scavenge the free radicals and prevent oxidative stress

(Balasaheb Nimse and Pal 2015).

Moreover, A. muciniphila may also degrade polyphenols and change the antibacterial property of the polyphenols. Ellagitannin contained in pomegranate extract has been shown to be

degraded into ellagic acid, and then into smaller molecules by A. muciniphila (Henning et al.

2017). Although the growth of A. muciniphila was inhibited by pomegranate extract, it was able to degrade ellagitannin in the extract into ellagic acid which does not inhibit A. muciniphila

(Henning et al. 2017). It showed that A. muciniphila can degrade polyphenols and be resistant to the antimicrobial properties of polyphenols, which would be a competitive advantage over non- resistant species. At the same time, because the pomegranate extract has been shown to increase the abundance of A. muciniphila in healthy volunteers (Li et al. 2015), the lack of direct growth stimulation indicated that pomegranate extract was not being utilized as energy or carbon source.

A similar observation was made by Shen et al. (2017) where despite of the stimulation of

A. muciniphila by capsaicin in vivo, A. muciniphila alone in presence of capsaicin was inhibited at high concentration in vitro. These studies indicate that although A. muciniphila may be inhibited by the extract or the polyphenol by itself, it can be stimulated in vivo or in the microbiota.

The potential degradation pathway of the two apple polyphenols, phlorizin and chlorogenic acid, by the gut microbiota has been suggested (Figure 4; Figure 5). The pathways were constructed using defined or fecal culture (Gonthier et al. 2006; Zhang et al. 2012; Tomas-

Barberan et al. 2014), and the degradation products were analyzed using high performance liquid chromatography (HPLC). In food, 5-O-caffeoylquinic acid (common name chlorogenic acid) accounts for the majority of chlorogenic acid, along with 3-O-caffeoylquinic acid

(neochlorogenic acid) and 4-O-caffeoylquinic acid (cryptochlorogenic acid) isomers (Bajko et al.

2016). Although Figure 5 shows the degradation pathway of neochlorogenic acid, the principal degradation product of both chlorogenic acid and neochlorogenic acid appears to be

3-(3-hydroxyphenyl)-propanoic acid (Gonthier et al. 2006; Tomas-Barberan et al. 2014); therefore, the degradation pathways are most likely similar.

Figure 4: Pathway of degradation of phlorizin by gut microbiota (Zhang et al. 2012; Schoefer et al. 2003)

Figure 5: Proposed degradation of chlorogenic acid by gut microbiota (Tomas‐Barberan et al. 2014)

Specifically, Eubacterium ramulus and Clostridium orbiscidens have been shown to be capable of degrading phloretin into phloretic acid, but C. orbiscidens does not deglycosylate phlorizin into phloretin (Schneider and Blaut 2000; Schoefer et al. 2003). In addition, phloroglucinol generated from the degradation is proposed to be converted into SCFA, and ATP is assumed to be produced based on similar metabolism by Pelobacter acidigallici and

Eubacterium oxidoreducans (Krumholz et al. 1987; Brune and Schink 1992). In 2010,

C. orbiscidens and Eubacterium plautii were unified as Flavonifractor plautii (Carlier et al.

2010).

There are several bacteria species proposed to be involved in the metabolism of chlorogenic acid (Table 10). The degradation ability may be strain specific as some isolates of

E coli were found to only hydrolyze chlorogenic acid (Couteau et al. 2001) whereas other isolates were found to further metabolize dihydrocaffeic acid into 3-(3-hydroxyphenyl)- propanoic acid (Peppercorn and Goldman 1971). Likewise, the rate or the ability of stimulating reaction appears to be species or strain dependent (Raimondi et al. 2015). For example,

Peptostreptococcus sp. was able to reduce 6 % of caffeic acid into dihydrocaffeic acid whereas

C. perfringens reduced 10 % of caffeic acid over the same time period (Peppercorn and Goldman

1971).

Table 10: Bacteria species found to be involved in chlorogenic acid degradation.

Parent Form Species Reaction Metabolite Reference Formed Chlorogenic E. coli Hydrolysis Caffeic acid Couteau et acid Bifidobacterium Quinic acid al. 2001 animalis subsp. lactis Lactobacillus gasseri B. animalis subsp. Hydrolysis Caffeic acid Raimondi animalis and lactis Quinic acid et al. 2015 Lactobacillus Hydrolysis Caffeic acid Bel-Rhlid johnsonii NCC 533 (cinnamoyl esterase Quinic acid et al. 2013 activity) Bifidobacterium None bifidum Bifidobacterium breve Bifidobacterium catenulatum B. longum Bifidobacterium pseudocatenulatum Caffeic acid Peptostreptococcus Reduction Dihydrocaffeic Peppercorn sp. acid and Clostridium Reduction Dihydrocaffeic Goldman perfringens acid 1971 Streptococcus Decarboxylation 4-vinylcaechol (Enterococcus) faecium L. johnsonii NCC Decarboxylation 4-vinylcaechol

533 (hydroxycinnamate Bel-Rhlid decarboxylase) et al. 2013 Dihydrocaffeic E. coli Reduction 3-(3- acid Streptococcus hydroxyphenyl)- (Enterococcus) propanoic acid faecalis var liquefaciens

Besides having a direct interaction between the polyphenols and the gut microbiota, polyphenols may be able to indirectly affect the growth of A. muciniphila through the changes in the host expression of mucin and the suppression of competitors for mucin. Capsaicin has been shown to stimulate growth of A. muciniphila, as well as the gene expression of Muc2, a gene of host cells that codes for production of mucin (Shen et al. 2017). The authors suggested that

A. muciniphila could have been indirectly stimulated by increased production of mucin, as mucin is an energy source for A. muciniphila. Similarly, mice fed with cranberry extract had increased abundance of A. muciniphila and mucin in feces or Muc2 gene expression in the tissue (Anhê,

Roy, et al. 2015), and mice fed with berry polyphenols had increased the fecal mucin level (Taira et al. 2015). However, it is important to note that since A. muciniphila is involved in the stimulation of mucin (Everard et al. 2013), the increase in gene expression or level of mucin may have been from the increased level of A. muciniphila and cannot be assumed from the polyphenol. Furthermore, another study has found that there was no significant change in the gene expression of Muc2 in jejunum or colon tissue despite having a stimulatory effect on

A. muciniphila (Roopchand et al. 2015). These contradictory results emphasize the possibility that each polyphenol stimulates A. muciniphila through potential multi-factorial prebiotic mechanisms (Anhê, Varin, et al. 2015). Additionally, as mentioned before, the ability of the gut bacteria to utilize glycans can shape the colonization and the composition of the gut microbiota

(Van Herreweghen et al. 2018). Due to the antibacterial nature of the polyphenols, it is possible to suppress the competitors for host glycan mucin that may provide a competitive advantage for the A. muciniphila to survive in the gut microbiota (Anhê, Varin, et al. 2015).

There have been other potential mechanisms suggested, such as the upregulation of the antimicrobial peptide production by the host cell and the changes in structural characteristics of

the mucous that may result in the stimulation of A. muciniphila growth (Anhê, Roy, et al. 2015).

Evidence for these mechanisms are demonstrated with rhubarb extract that altered the gene expression of antimicrobial peptide regenerating islet-derived 3-gamma (RegIII γ) (Neyrinck et al. 2017) and the ability of galloylated catechin to form cross links and change the structural characteristics of the mucous (Georgiades et al. 2014).

To conclude, the literature suggests that polyphenols may exhibit one or more of these mechanisms depending on the chemical structure of the polyphenol. Although polyphenols from difference sources appear to stimulate A. muciniphila in animal models, the stimulatory mechanism is unclear as to whether the polyphenols are being directly utilized by A. muciniphila, how the antibacterial activity of the polyphenols may be affecting the competitors of

A. muciniphila, or whether the polyphenols can change mucin production by host cells. To investigate the mechanisms, the use of pure polyphenols that are known to stimulate

A. muciniphila, such as phlorizin and chlorogenic acid, would be appropriate. The use of pure forms of polyphenols would allow study of mechanisms by a single polyphenol at a conserved concentration, which is not possible with an extract.

Chapter 2 Hypothesis and Objectives

2.1 Hypothesis

Phlorizin, phloretin, and chlorogenic acid will induce mucin production by the host goblet cells or have selective antibacterial activity against other mucus-associated bacteria that will contribute to competitive advantages for A. muciniphila.

2.2 Objectives

1) Use the mucin-producing HT29-MTX cell line to determine whether polyphenols induce

mucin gene expression (MUC1, MUC5AC, MUC5B, MUC13, and MUC20) and mucin-like

glycoprotein production by the host goblet cells using RT-qPCR and enzyme linked lectin

assay (ELLA).

2) Determine the inhibitory effect of each polyphenol on A. muciniphila and other mucus-

associated species in vitro using the minimal inhibitory concentration (MIC) assay.

3) Use planktonic mixed culture to determine the impact of pure polyphenols on the relative

abundance of A. muciniphila and other mucus-associated bacteria.

Chapter 3 Materials and Methods

3.1 Polyphenols used in the study

All three polyphenols used in this study were purchased from Sigma-Aldrich (St. Louis,

USA): phlorizin dihydrate (from apple wood, ≥ 99 %), phloretin (≥ 99 %), and chlorogenic acid

(≥ 95 %). Chlorogenic acid and phlorizin are present in high proportion in apple or apple pomace and have low bioavailability. Phlorizin and phloretin were used since phloretin-2’-O- glucuronides, which are structurally similar to phlorizin, followed by phloretin were the major metabolites found in the ileal fluid of human volunteers after consuming apple cider (Marks et al.

2009).

3.2 Mucin gene expression and production by HT29-MTX cells in presence of

polyphenols

3.2.1 Cell culture conditions

The HT29-MTX cell line was obtained from the CRIFS culture collection. The cells were grown in 75 cm2 tissue culture treated flasks containing 15 ml of Dulbecco's Modified Eagle

Medium (DMEM) supplemented with 10 % fetal bovine serum (FBS), 1 % L-glutamate

(200 mM) and 1 % penicillin streptomycin (10,000 U/mL). The cells were incubated in 5 % CO2 incubator at 37 oC. The media was changed every 2 days after washing the cells with 6 ml of phosphate-buffered saline (PBS) solution for approximately 1 minute, gently swirling the flask.

The cells were passaged when they reached confluency ≥ 80 % using 2 ml of 0.25 % trypsin-

EDTA solution. For the experiments, cells in passages between 40 to 50 were used. In the past studies, HT29-MTX cells have been used in passages between 20 to 67 (Béduneau et al. 2014;

Pan et al. 2015; Castiaux et al. 2016; Akbari et al. 2017).

3.2.2 Sulforhodamine B (SRB) assay

Sulforhodamine B (SRB) assays were conducted on HT29-MTX cells to test the cytotoxicity of the polyphenols and the solvent dimethyl sulfoxide (DMSO) that was used to dissolve the polyphenols. DMSO concentrations from 0.1 % to 1 % with 0 % as positive control were tested for the appropriate DMSO concentration. Polyphenols at concentrations of 100 µM,

50 µM, and 25 µM with 0.2 % DMSO as positive control were tested for the cytotoxicity test of phlorizin, phloretin, and chlorogenic acid.

The procedure for the SRB assay followed J. Zhang et al (2018) with modifications. Cells were seeded at 2 x 104 cells per well (tissue culture treated 96 well flat bottom plates) with 6 technical replicates for each treatment. After 24 hours of incubation at confluency ≥ 80 %,

100 µL of treatment in FBS and antibiotic free media (DMEM-) per well was added and incubated for another 24 hours. Then, the media was removed, and 200 µL of DMEM- and

50 µL of cold 50 % trichloroacetic acid (TCA) in distilled water per well were added and incubated at 4 oC for 1.5 hours to fix the cells. TCA was removed, and the cells were washed with 280 µL of distilled water per well for 5 times and air dried overnight. After drying, 50 µL of

SRB dye (dye content 75 %, Sigma-Aldrich) diluted to 0.4 % w/v in 1 % acetic acid was added and slowly shaken on microplate shaker for 30 minutes. SRB dye was removed, and the cells were washed with 300 µL of 1 % acetic acid per well for 4 times and air dried overnight. Lastly, the dye was dissolved using 100 µL of 10 mM tris buffer per well, and the absorbance was measured at 570 nm using a spectrophotometer (Multiskan™ GO Microplate Spectrophotometer,

Thermo Scientific, Wilmington, USA).

The viability of the cells was calculated using the equation below after subtracting the average absorbance value of the blank (Orellana and Kasinski 2016). Experimental replicates were conducted at different times using cells from different frozen stock at different passage number.

퐴푏푠표푟푏푎푛푐푒 표푓 푆푎푚푝푙푒 푤푒푙푙 % 퐶푒푙푙 푉푖푎푏푖푙푖푡푦 = × 100 % 퐴푏푠표푟푏푎푛푐푒 표푓 0 % 퐷푀푆푂 (푝표푠푖푡푖푣푒 푐표푛푡푟표푙)

3.2.3 Polyphenol exposure to HT29-MTX cells

The protocol for studying the mucin-stimulating activity is described by Verhoeckx et al.

(2015). Briefly, HT29-MTX cells were seeded at 5 ×105 cells per well (1 mL of 5 ×105 cells per well) in 12 well tissue culture treated flat bottom plates. For each well, 2 mL of the media was added and was changed every 2 days. The experiments were performed at 21 days after reaching

100 % confluency, when the proportion of mucus-secreting cells reached 100 % and remained stable (Lesuffleur et al. 1993). Twenty-four hours prior to the experiment, the media was changed to DMEM- to minimized interference. At the start of the experiment, the cells were rinsed with 2 mL of PBS for 2 times, and 100 μM of phlorizin, phloretin, and chlorogenic acid dissolved in 2 mL of DMEM- were added to the wells. After 12 or 24 hours, the cells for RNA and protein extractions were collected separately from different well in duplicates for each treatment. Three experimental replicates were performed as described in the SRB assay.

3.2.4 RNA and protein extraction

Total RNA was extracted using RNeasy Plus Mini Kit (Qiagen, Toronto, Canada). The cells were washed twice with 2 mL of PBS for 30 seconds each, detached by 500 µL of 0.25 % trypsin-EDTA for 5 minutes and scraped with pipette tips. The rest of the extraction followed the manufacturer’s protocol using QIAshredder (Qiagen) for the homogenization step. The quality and the integrity of the extracted RNA were determined using Nanodrop spectrophotometer

(NanoDrop 1000 spectrophotometer, Thermo Scientific) and RNA IQ Assay Kit (Thermo

Scientific). The RNA extracts used had 260/280 and 260/230 ratios around 2 and the IQ value was ≥ 9.0. The concentration was quantified by RNA BR Assay Kit (Thermo Scientific), and

750 ng of RNA was converted to cDNA using QuantiTect Reverse Transcription (Qiagen).

Total protein from the cells was extracted with M-PER lysis buffer (Thermo Scientific) supplemented with Thermo Scientific™ Halt™ Protease Inhibitor Cocktails (Thermo Scientific) following manufacturer’s instruction after removing the media and washing the cells once with

2 mL of PBS. The removed spent media and the total protein extract from the cell lysates were mixed separately and frozen at -80 oC until ELLA was performed (Wan et al. 2014).

3.2.5 RT-qPCR for evaluation of the expression of selected mucin genes

The expression levels of mucin 1 (MUC1), mucin 5AC (MUC5AC), mucin 5B

(MUC5B), mucin 13 (MUC13), and mucin 20 (MUC20) with cyclophilin as a reference gene were compared between the 100 μM polyphenol treatments to the control (0.2 % DMSO) at each time points. The primers used are listed in Table 11. SYBR Green based qPCR was performed following manufacture’s instruction. Briefly, total of 20 µL reaction per well containing 10 µL of

SsoAdvanced Universal Syber Green SuperMix (BIO-RAD, Mississauga, Canada), 1 µL each of

10 µM forward and reverse primers (final concentration of 500 nM), 5 µL of cDNA at diluted to

1:20 (total 9.375 ng) were prepared in triplicates for cDNA converted from each RNA extract.

The cycle was run on CFX96 Touch System (BIO-RAD) programmed as following: 95.0 oC for

30 seconds, 40 cycles of 95.0 oC (10 seconds) and 60oC (20 seconds). Melting curve analysis on the PCR products were conducted from 65.0 to 95.0 oC at 0.5 oC / 5 seconds. The data generated was analyzed using Bio-Rad CFX Maestro software (BIO-RAD). The expression was

normalized to cyclophilin and fold change expression of the mucin genes were compared to the control using Pfaffl method (Pfaffl 2001).

(퐸 )∆퐶푡푡푎푟푔푒푡(푐표푛푡푟표푙−푠푎푚푝푙푒) ratio (fold change) = 푡푎푟푔푒푡 (Pfaffl, 2001) ∆퐶푡푟푒푓(푐표푛푡푟표푙−푠푎푚푝푙푒) (퐸푟푒푓)

Table 11: List of primers used for the mucin expression study

Target Gene Primer Sequence (5’-3’) Amplicon (bp) Reference cyclophilin F: TCCTAAAGCATACGGGTCCTGGCAT 165 Chen et al. R: CGCTCCATGGCCTCCACAATATTCA 1999 MUC1 F: CGTAGCCCCTATGAGAAGGTT 95 Graziani et R: CCCTACAAGTTGGCAGAAGTG al. 2016 MUC5AC F: CGACCTGTGCTGTGTACCAT 240 Plaisancié et R: CCACCTCGGTGTAGCTGAA al. 2013 MUC5B F: GACAGAGACGACAATGAG 154 Wan et al. R: CCTGATGTTTTCAAAAGTTTC 2014 MUC13 F: GACATAATCACCGCTTCATCTC 105 Sperandio et R: TGATTGATTGTCTTCTGTGGTG al. 2013 MUC20 F: GTGCAGGTGAAAATGGAGGT 152 Cairns et al. R: ACGCAGTAAGGAGACCTGGA 2017

For the selection of target mucin genes, gradient qPCR and melting curve analysis were conducted using primers for each target mucin gene (Table A 1; Table A 2). Genes with < 30 Ct value with 1:10 diluted cDNA were chosen for the RT-qPCR experiment. The annealing temperature at 60 oC was chosen based on the lowest Ct values observed for the selected genes with no primer dimer formation.

For the reference gene selection, cDNA transcribed from RNA extracted from cells obtained from the control and with the treatments of phlorizin, phloretin, and chlorogenic acid at

30 min, 6 hours, 12 hours, and 24 hours were checked for gene expression stability using geNorm method (Hellemans et al. 2007) for cyclophilin and GAPDH. Both genes had M values below 0.5 (Table A 3), which is considered a stably expressed reference gene in a homogenous tissue (Hellemans et al. 2007). Standard curves for each chosen gene were constructed using the pooled cDNA of all RNA extracts (all polyphenol and control treatments for both time points) starting from 1:5 dilution and continued by 2-fold dilutions (Table 12; Table 13).

Table 12: Standard curve of target genes constructed from pooled cDNA

Target Gene Efficiency (%) R2 Slope Intercept Cyclophilin 93.7 0.98 3.483 15.104 MUC1 94.9 0.98 3.451 23.519 MUC5AC 101.2 0.98 3.294 25.946 MUC5B 95.2 0.98 3.444 27.033 MUC13 110.4 0.99 3.096 25.014 MUC20 92.7 0.97 3.510 19.945

Table 13: 1:2 Dilution series of pooled cDNA (20 uL of 37.5 ng/uL).

Dilution Factor from original cDNA 1/5 1/10 1/20 1/40 1/80 cDNA concentration (ng/uL) 7.5 3.75 1.875 0.9375 0.49875 Total cDNA added (ng) (5 uL) 37.5 18.75 9.375 4.6875 2.343

3.2.6 ELLA for quantification of total mucin-like glycoprotein

ELLA with wheat germ agglutin (WGA), specific to the sialic acid N-acetylneuraminic acid and the glucose derivative N-acetylglucosamine present in human mucin, was performed

(Thompson et al. 2011). All reagents used in ELLA were purchased from Sigma-Aldrich unless otherwise specified. The method for ELLA was based on Trompette et al. (2004) and Martínez-

Maqueda et al. (2012) with modifications. MaxiSorp ELISA 96 well plate (Thermo Fisher) was coated with 100 µl of the diluted mucin standards or samples in carbonate-bicarbonate buffer

(pH 9.4) at 4 oC overnight. For the standard curve, mucin from porcine stomach Type III was 2- fold diluted from 12.5 ng/mL to 0.78125 ng/mL with 0 ng/mL as a blank control (Figure 6). For the samples, the cell lysates were diluted 1:20,000, and the spent media was diluted 1:200 (12 hours) and 1:300 (24 hours). The wells were washed 6 times with PBS containing 0.1 % Tween

20 (PBST), blocked with 0.5 % polyvinyl alcohol (PVA, 87-90 % hydrolyzed, average molecular weight 30,000-70,000) in PBS for 2 hours at room temperature, and again washed 6 times with

PBST. Commonly used BSA may contain glycoprotein contaminants, such as γ-globulin IgG, and PVA has been shown and suggested to be used as a blocking agent for ELLA (Thompson et al. 2011). 100 µL of 6 ug/mL biotinylated wheat germ agglutin (WGA, lectin from Triticum vulgaris) in PBST was added and incubated for 1 hour at 37 oC and washed 6 times with PBST.

Then,100 µL of 1 ng/mL avidin-peroxidase in PBST was added and incubated for 1 hour at room temperature. Colorimetric reaction of the TMB substrate (Thermo Fisher) was stopped with 2 M sulfuric acid and absorbance was measured at 450 nm using a spectrophotometer (Multiskan™

GO Microplate Spectrophotometer, Thermo Scientific). Total BSA equivalent protein was quantified using BCA for the cell lysates (Thermo Fisher).

0.7

0.6 ) 0.5 y = 0.0266x + 0.3043 0.4 R² = 0.9797 0.3

0.2 Absorbance nm Absorbance (450 0.1 0 0 2 4 6 8 10 12 14 Mucin ng/mL

Figure 6: Standard curve for the quantification of mucin by ELLA with 6 µg/mL WGA and 1 ng/mL avidin-peroxidase with 0.5 % PVA as a blocking buffer

3.3 Inhibitory effect of phlorizin, phloretin and chlorogenic acid on select bacteria

3.3.1 Bacteria viable counts and optical density

For this study, all bacteria were grown in an anerobic chamber at 37 oC. Mucus- associated gut bacteria were obtained from the CRIFS culture collection, where Lachnospiraceae species, F. plautii, and E. coli were isolated from a fecal sample of one donor. Viable counts and optical density of each bacteria grown in thioglycolate (THIO) broth for 24 hours were determined (Table 14). Briefly, the bacteria were sub-cultured twice from frozen stock on fastidious anaerobic agar (FAA). The plate was incubated for approximately 48-72 hours for each subculture. A loopful was inoculated into the THIO broth with a 1 µL inoculating loop.

After 24 hours of incubation, optical density (OD) at 600 nm was measured using a spectrophotometer and viable counts were taken on FAA after 48-72 hours of incubation, except for A. muciniphila which was incubated for 7 days. The experiment was repeated three times using a bacterial colony obtained from a frozen stock of pure culture on different days.

Table 14: Evaluation of growth in THIO broth by OD at 600 nm and viable counts after 24 hours

Taxonomic group Species OD600 Log (CFU/mL) Lachnospiraceae Clostridium symbiosum 0.838 ± 0.017 8.724 ± 0.087 (Clostridium Clostridium hylemonae 0.790 ± 0.025 7.173 ± 0.067 Cluster XIVa) Blautia sp. 1.089 ± 0.032 8.355 ± 0.227 Ruminococcaceae F. plautii 0.384 ± 0.076 8.420 ± 0.226 (Clostridium cluster IV) Proteobacteria E. coli 0.818 ± 0.047 8.892 ± 0.044 Bacteroidetes B. thetaiotaomicron 0.897 ± 0.042 8.100 ± 0.078 Verrucomicrobia A. muciniphila 0.724 ± 0.074 8.655 ± 0.211 Actinobacteria B. longum 0.469 ± 0.014 8.482 ± 0.016

3.3.2 Broth minimal inhibitory concentration (MIC)

The broth MIC method for anaerobic bacteria by Leber (2016) was followed with modifications. 100 µL of the treatments dissolved in THIO broth were aliquoted in a 96 well tissue culture treated plates. Then 100 µL of 2 x 106 CFU/mL, adjusted from the 24 hours culture described in the previous section (3.3.1), were inoculated into each well. For the MIC assay of solvent DMSO, final concentrations of 1.25 %, 2.5 %, 5 %, and 10 % DMSO and 0 % DMSO as a control were prepared. For the polyphenol MIC assay, phlorizin, phloretin, and chlorogenic acid at final concentrations of 1000 µM, 500 µM, 250 µM, 125 µM, and 62.5 µM with corresponding DMSO solvent controls at 2 %, 1 %, 0.5 %, 0.25 % and 0.125 % reflectively were prepared. The plates were incubated for 46-48 hours, and the ODs were measured at 600 nm.

The viability was calculated by dividing the polyphenol treatment OD by the corresponding controls. Three experimental replicates were conducted with four technical replicates. For phloretin at 1000 µM and 500 µM, controls without bacteria inoculation were prepared to adjust for the background absorbance.

3.4 In vitro growth of bacteria in mixed culture with the presence of polyphenols

3.4.1 In vitro mixed culture

In vitro mixed culture of the bacteria was prepared at a final concentration of 1 x 106

CFU/mL for each bacterium (total 8 x 106 CFU/mL) in 80 mL of THIO broth in the presence of

250 µM of phlorizin, phloretin, and chlorogenic acid and 0.5 % DMSO as the control. The

CFU/mL concentrations of each bacteria were adjusted from the 24 hours culture. The mixed culture was incubated at 37 oC in the anaerobic chamber. At time points 0 h (immediately after inoculation), 1, 2, 4 and 7 days, 500 µL of the broth were collected for PMA-qPCR and HPLC analysis. Three experimental replicates were conduced for PMA-qPCR, and two experimental

replicates were performed for HPLC simultaneously with the PMA-qPCR experiments. The pH of the mixed cultures was taken in a separate experiment using a pH meter (Accumet™ AB150 pH Benchtop Meters, Fisher Scientific)

3.4.2 PMA-qPCR for enumeration of bacteria

Cells were treated with PMA to prevent amplification of DNA from dead or compromised (permeable) cells (Fujimoto and Watanabe 2013; Davis 2014). PMAxx dye

(Biotium, Fremont, USA) was used, and the manufacturer’s protocol was followed with modifications under an anaerobic condition until exposure to light. Five µL of 2.5 mM PMA solution diluted in water was added to 500 µL of broth in a 1.5 mL microcentrifuge tube (final

PMA concentration of 25 µM). PMA added cell suspension was incubated for 15 minutes on ice in the dark with occasional agitation. Then, it was exposed to the UV light (PhAST Blue,

GenIUL) for 15 minutes and again incubated on ice in the dark for 15 minutes. Finally, the cells were pelleted by centrifugation at 5,000 × g for 10 minutes, and the supernatant was discarded.

The PMA treated cell pellets were stored at -20 oC until DNA was extracted using Dneasy ultraclean microbial kit (Qiagen) following manufacturer’s instructions. The quality and the quantity of DNA were checked using Nanodrop spectrophotometer (Thermo Scientific) and running gel electrophoresis.

SYBR Green based qPCR was performed following manufacturer’s instructions as described in the previous section (3.2.5) with modifications. Initial 95 oC was extended to

3 minutes, and the appropriate annealing temperature and time for each primer (Table 15) were used. The primers used are listed in Table 16. The Ct values were used to calculate the log

CFU/mL concentration on the standard curves. The log reductions compared to the control were calculated by subtracting the control from the polyphenol treatment.

Table 15: Annealing time and temperature for each target primer

Primer Target Tm (oC) Tm (sec)

Lachnospiraceae 60 50

F. plautii 53 25

E. coli 65 25

B. thetaiotaomicron 65 15

A. muciniphila 65 25

B. longum 65 25

Table 16: Target-specific primers used for taxonomic group/species included in this study.

Target Primers Product Target gene References size (bp) Lachnospiraceae ClcoF:CGGTACCTGACTAAGAAGC 429 16S rRNA Rinttilä et ClcoR:AGTTT(C/T)ATTCTTGCGAACG al. 2004 F. plautii CleptF: GCACAAGCAGTGGAGT 239 16S rRNA Matsuki et CleptR3: CTTCCTCCGTTTTGTCAA al. 2004 E. coli 401F: TGATTGGCAAAATCTGGCCG 211 Putative Walker et 611R: GAAATCGCCCAAATCGCCAT allantoin al. 2017 transporter (ybbW) B. thetaiotaomicron BPPF:GGTGTCGGCTTAAGTGCCAT 140 16S rRNA Rinttilä et BPPR:CGGA(C/T)GTAAGGGCCGTGC al. 2004 CGGACGTAAGGGCCGTGC A. muciniphila AP4F: ACTCCATCCGTATCCGCAAC 230 Pili-like This study AP4R: CTTGGGCTGGTTGAAGTGGA surface protein: Amuc_1100 B. longum BifF: TCGCGTCCGGTGTGAAAG 243 16S rRNA Rinttilä et BifR: CCACATCCAGCATCCAC al. 2004

For determining primer specificity and optimal annealing temperature (Table 17), gradient qPCR and melting curve analysis were conducted for each primer on DNA extracted from 24-h culture of all bacteria studied (Table A 4). AM1 and AM2 primers that are supposedly specific to A. muciniphila and used in past studies (Derrien 2007; Collado et al. 2007;

Schneeberger et al. 2015; Dao et al. 2016; Fabbiano et al. 2018; Olivier-Van Stichelen et al.

2019) had nonspecific amplification on F. plautii (Table 17); therefore, the AP4 primer set was designed using the gene for pili-like surface protein Amuc_1100 (Plovier et al. 2017) on NCBI

Primer Blast.

For the construction of standard curves (Table 18), PMA treated DNA extracted from the

24-h cultures of each bacteria (108 or 107 CFU/mL) were 10-fold diluted. To determine the detection limit (Table 18), 24 hours cultures were diluted to 104 to 105, treated with PMA, and then the DNA was extracted to determine the threshold value where Ct values ≤ 30 were accepted. The efficacy of the PMA treatment was evaluated by comparing live cells and compromised cells (heat treated or isopropanol treated) with or without the PMA treatment from the 24 hours culture (Table A 6). Heat was applied at 95 oC for 5 minutes. Cells for the isopropanol treatments were centrifuged at 7,000 × g for 10 minutes to remove the supernatant, exposed to 500 µL of 70 % isopropanol for 15 minutes, centrifuged at 7,000 × g for 10 minutes again to decant the isopropanol and re-suspended in PBS (Taskin et al. 2011). PMA treatments followed the procedure as described earlier in this section.

Table 17: Ct values of target and non-target gDNA. Target gDNA had (bolded) Cq values around 17-22 and non-target gDNA had at least 9 Cq values higher (~30) than the target gDNA indicating no cross amplification (Desfossés-Foucault et al. 2012). The annealing condition follows Table 15.

Primer C. sym C. hyl Blau F. plau E. coli B. the A. muc B. long NTC

Temperatures (Co)

ClcoF and ClcoR 20.94 18.02 20.74 > 40 > 40 > 40 > 40 > 40 > 40

CleptF and CleptR3 > 40 > 40 > 40 22.36 > 40 > 40 > 40 > 40 > 40

401F and 611R > 40 > 40 > 40 > 40 20.93 > 40 > 40 35.53 > 40

BPPF and BPPR > 40 > 40 38.31 > 40 > 40 20.21 > 40 30.06 > 40

AM1 and AM2 39.41 32.98 38.78 19.23 31.86 > 40 17.49 35.19 > 40

(89.0) (89.0)

AP4F and AP4R > 40 > 40 > 40 > 40 39.21 > 40 15.93 > 40 > 40

BifF and BifR > 40 > 40 > 40 39.14 38.67 > 40 38.77 19.54 > 40

Table 18: Standard curve and detection limit of target specific primers

Primer Target Efficiency R2 Intercept Detection Limit (log cfu/mL) Lachnospiraceae 88.0 0.998 42.663 104 F. plautii 90.9 0.994 45.849 104 E. coli 87.2 0.998 47.688 104 B. thetaiotaomicron 91.6 0.999 43.395 104 A. muciniphila 83.7 0.997 46.173 105 B. longum 83.6 0.996 45.934 105

3.4.3 HPLC for polyphenol degradation analysis

Methanol extraction method by Tomas-Barberan et al. (2014) was followed. 500 µL of

50 % MeOH/water (v/v) was added to 500 µL of broth and mixed with vortex. Then it was centrifuged at 13,000 × g at 4 oC for 10 minutes, and the supernatant was collected and filtered through 0.22 µm polyvinylidene fluoride filter. The extracts were stored in HPLC vials at 4 oC until HPLC was conducted.

The conditions for HPLC were based on Bai et al. (2016). The Eclipse plus C18 column

3.5 µM, 150 mm x 4.6 mm (Agilent) was equipped with an Agilent 1260 Infinity Micro

Degasser, Agilent 1200 Series Quaternary Pump, Agilent 1200 Series Autosampler Thermostat,

Agilent 1200 Series Thermostatted Colum Compartment, and Agilent 1200 Series Diode Array

Multiple Wavelength Detectors. The HPLC program consisted of a flow rate at 1.0 mL/min, column temperature at 20 oC, the mobile phase A as 1 % acetic acid/water, and the mobile phase

B as methanol. The gradient elution was set 95 % A (0 minutes); 95 % - 70 % A (0 -10 minutes);

70 % - 50 % A (10 – 25 minutes); 50 % – 30 % A (25 – 35 minutes); 30 % – 95 % A (35 – 40 minutes). Absorbances were measured at 320 nm and 280 nm. Two additional chemicals,

3-(4-hydroxyphenyl) propionic acid (phloretic acid) and 3-(3-hydroxyphenyl)propionic, were purchased from Sigma-Aldrich as standards to determined their retention times (Table 19).

Table 19: Retention times of the standards used in the HPLC

Chemical Name Retention Time (min) Chlorogenic Acid 10.932 Caffeic Acid 12.565 3-(4-hydroxyphentyl-propionic acid (Phloretic acid) 14.343 3-(3-hydroxyphenyl)propionic acid 16.244 Phlorizin dihydrate 22.531 Phloretin 30.039

3.5 Statistical analysis

For all data, normal distribution and equal variation were confirmed. ANOVA was conducted to compare the viability of HT29-MTX cells from the SRB assay, the hold changes in mucin gene expression from the RT-qPCR, the total mucin glycoprotein content from the ELLA, the viability of bacteria from the MIC assay, and the log CFU change from the mixed culture.

Then, Tukey Honest Significance test or Dunnett test (confidence level 95 %) were conducted to determine the significant difference to the control. All statistical analyses were performed using

R (version 3.5.2).

Chapter 4 Results

4.1 The effect of polyphenols on the expression of mucin genes and mucin production by

HT29-MTX cells

There was a significant effect of DMSO on the viability of HT29-MTX cells (P < 0.05) as all concentrations except 0.2 % significantly decreased the viability compared to the control

(Table 20). The cytotoxicity increased with increasing DMSO concentration (Table 20). Using

0.2 % DMSO as a solvent, phlorizin, phloretin, and chlorogenic acid up to 100 µM had no significant effect on the viability of HT29-MTX cells compared to the control (Table 21). In addition, at 100 µM, there was no significant fold change in the expression of the MUC1,

MUC5AC, MUC5B, MUC13, and MUC20 genes in the presence of polyphenols after 12 or 24 hours exposure, except MUC1 in response to phloretin at 12 hours (Table 22). Similarly, there was no significant difference in glycoprotein-like mucin content of the spent medium or the cell lysate compared to the control (Figure 7). There was an increase in the level of mucin-like glycoprotein content in the spent medium at 24 hours compared to 12 hours (Figure 7b).

Table 20: Comparing the viability of HT29-MTX cells at increasing DMSO concentrations compared to the control (0 % DMSO) by SRB assay *Pair-wise significant difference to the control (P < 0.05, n=3).

DMSO (%) Viability (%) 0.1 *85.73 ± 10.38 0.2 102.1 ± 6.4 0.3 *82.00 ± 7.96 0.4 *84.67 ±12.24 0.5 *85.44 ± 11.43 0.6 *83.37 ± 10.96 0.7 *72.28 ± 12.96 0.8 *76.89 ± 11.16 0.9 *68.15 ± 6.18 1 *45.12 ± 19.68

Table 21: The mean viability of HT29-MTX cells in the presence of phlorizin, phloretin, and chlorogenic acid at three concentrations relative to the control (0.2 % DMSO) by SRB assay. *Pairwise significant difference to the control (P < 0.05; n=3).

Polyphenol Concentration (µM) Viability (%) Phlorizin 100 100.6 ± 2.6 50 99.2 ± 2.9 25 98.9 ± 3.9 Phloretin 100 97.9 ± 3.1 50 98.4 ± 4.6 25 97.8 ± 4.3 Chlorogenic Acid 100 100.2 ± 1.0 50 100.4 ± 0.5 25 99.7 ± 0.7

Table 22: The fold change expression of five mucin genes in the presence of 100 µM of phlorizin, phloretin and chlorogenic acid after 12 or 24 hours exposure compared to the control. *Significant fold change compared to the control (P < 0.05; n=3). Fold change was calculated using Pfaffl method (Pfaffl, 2001).

Mucin gene expression (fold change) Time Polyphenol MUC1 MUC5AC MUC5B MUC13 MUC20 (h) 12 Phlorizin 1.067 ± 1.144 ± 1.242 ± 1.085 ± 0.988 ± 0.746 0.164 0.286 0.129 0.082 Phloretin *1.344 ± 1.782 ± 1.275 ± 1.072 ± 1.036 ± 0.05 1.123 0.066 0.065 0.103 Chlorogenic 1.184 ± 1.754 ± 1.281 ± 1.144 ± 1.059 acid 0.088 0.616 0.028 0.075 ±0.079 24 Phlorizin 1.006 ± 1.135 ± 1.085 ± 0.939 ± 1.073 ± 0.020 0.224 0.074 0.091 0.017 Phloretin 1.068 ± 1.175 ± 1.048 ± 0.916 ± 0.951 ± 0.149 0.250 0.056 0.122 0.040 Chlorogenic 1.063 ± 1.569 ± 1.367 ± 0.956 ± 1.062 ± acid 0.066 0.501 0.472 0.183 0.088

a) 1200

1000

800

600

400

like glycoprotein glycoprotein like (ng/mL) -

200 mucin 0 12:D 12:Pz 12:Pl 12:Ch 24:D 24:Pz 24:Pl 24:Ch Time (hours):Polyphenol b) 25

15 (ug) 10

glycoprotein (ng) per BSA equlavent equlavent (ng) per BSA glycoprotein 0 12:D 12:Pz 12:Pl 12:Ch 24:D 24:Pz 24:Pl 24:Ch Time (hours):Polyphenol

Figure 7: Total mucin-like glycoprotein measured using ELLA in a) the spent medium (secreted mucin) or b) the cell lysates (surface associated mucin) of HT29-MTX cells in the presence of 0.2 % of DMSO (control) or 100 µM of polyphenols. D – DMSO; Pz – Phlorizin; Pl – Phloretin; Ch –Chlorogenic acid. 12 – 12 hours; 24 –24 hours. *Significant difference to the control (P < 0.05).

4.2 The MIC of phlorizin, phloretin, and chlorogenic acid for the selected mucus-

associated gut bacteria

There was a significant effect of DMSO up to 10 % concentration on the viability of all bacteria (P < 0.05), with B. thetaiotaomicron being the most sensitive strain with < 50 % growth at 5 % DMSO (Table 23). There was no significant inhibitory effect of phlorizin and chlorogenic acid up to 1000 µM concentration on the growth of all bacteria except C. symbiosum, which was slightly inhibited, and B. longum, which was slightly stimulated at 1000 µM of phlorizin (Table

24ac). On the contrary, phloretin at 500 µM inhibited the growth of all bacteria, except E. coli, to

< 50 % growth (Table 24b). At 250 µM of phloretin, A. muciniphila showed tolerance with a viability of 103.7 ± 24.5 % while the growth of Lachnospiraceae, B. thetaiotaomicron, and

B. longum appear to be inhibited (Table 24b).

Table 23: The effect of DMSO concentration on the viability of gut bacteria after 48 hours of exposure compared to the control. *Significant difference to the control (P < 0.05; n=3).

Species DMSO concentration (%) 1.25 2.5 5 10 C. symbiosum 92.9 ± 7.6 *84.6 ± 12.1 *61 ± 11.4 *10.9 ± 0.4 C. hylemonae 85.2 ± 10.2 *75.01 ± 4.1 *58.8 ± 3.2 *42.7 ± 3.3 Blautia sp. 98.1 ± 1.9 97.3 ± 2.4 *90.9 ± 3.2 *6.5 ± 0.7 F. plautii 98 ± 6.6 92.8 ± 7.4 *54.5 ± 20.1 *15.7 ± 1.2 E. coli 103.6 ± 2.6 95.8 ± 2.1 *72.0 ± 2.4 *32.7 ± 1.7 B. thetaiotaomicron 87.91 ± 3.0 *60.9 ± 10.0 *18.8 ± 1.4 *13.4 ± 0.1 A. muciniphila 101.6 ± 5.7 109.2 ± 3.9 *81.8 ± 9.1 *16.2 ± 0.2 B. longum 94.8 ± 0.8 83.2 ± 7.1 *36.4 ± 12.6 *7.4 ± 0.5

Table 24: The effect of a) phlorizin, b) phloretin, and c) chlorogenic acid concentration on the viability (% compared to control) of gut bacteria. *Significant difference to the control (P < 0.05; n=3). **Dunnett test P value < 0.05 but ANOVA not significant. a) Phlorizin concentration (µM) Species 62.5 125 250 500 1000 C. symbiosum 101.0 ± 8.9 95.5 ± 6.4 91.5 ± 0.8 87.3 ± 6.9 **73.2 ± 20.5 C. hylemonae 99.4 ± 8.9 100.0 ± 9.2 95.6 ± 11.2 91.4 ± 6.9 100.4 ± 13.0 Blautia sp. 98.3 ± 1.6 101.6 ± 1.6 100.4 ± 2.9 102.9 ± 4.9 102.9 ± 6.1 F. plautii 92.8 ± 2.6 88.9 ± 1.9 91.3 ± 4.9 95.4 ± 6.9 103.6 ± 13.1 E. coli 94.5 ± 9.6 93.2 ± 4.6 93.0 ± 8.2 93.2 ± 9.7 109.0 ± 6.4 B. thetaiotaomicron 104.0 ± 5.0 100.2 ± 2.4 101.0 ± 4.0 99.1 ± 2.3 90.5 ± 10.8 A. muciniphila 100.3 ± 6.3 102.3 ± 7.6 100.1 ± 3.8 103.5 ± 4.3 96.9 ± 8.2 B. longum 104.1 ± 4.0 105.4 ± 2.9 106.8 ± 4.1 106.8 ± 7.1 **116.1± 6.7 b) Phloretin concentration (µM) Species 62.5 125 250 500 1000 C. symbiosum 92.0 ± 2.7 95.5 ± 1.8 62.2 ± 35.3 *4.4 ± 1.6 *5.7 ± 3.7 C. hylemonae 114.7 ± 16.2 111.1 ± 14.6 88.2 ± 18.3 *37.8 ± 20.1 *22.8 ± 6.1 Blautia sp. 94.5 ± 5.9 *80.2 ± 6.7 *33.2 ± 27.3 *3.0 ± 2.2 *4.1 ± 3.3 F. plautii 104.1 ± 4.8 119.2 ± 16.8 99.1 ± 3.8 *24.2 ± 29.8 *3.2 ± 0.6 E. coli 94.2 ± 4.5 94.9 ± 5.5 95.4 ± 4.5 92.5 ± 7.1 102.4 ± 11.8 B.thetaiotaomicron 107.4 ± 8.1 94.4 ± 21.1 65.5 ± 34.9 *10.8 ± 11.5 *12.3 ± 0.4 A. muciniphila 109.6 ± 22.6 114.4 ± 25.7 103.7 ± 24.5 54.4 ± 31.9 *17.0 ± 10.9 B. longum 103.7 ± 3.2 94.1 ± 16.5 88.9 ± 16.0 *41.7 ± 41.8 *11.0 ± 8.7

c) Chlorogenic acid concentration (µM) Species 62.5 125 250 500 1000 C. symbiosum 99.4 ± 0.5 99.7 ± 1.2 97.9 ± 2.3 95.6 ± 6.4 91.9 ± 6.4 C. hylemonae 100.6 ± 0.4 97.1 ± 2.1 92.3 ± 4.7 92.1 ± 0.8 108.7 ± 6.2 Blautia sp. 100.6 ± 0.6 99.9 ± 2.1 99.7 ± 1.6 103.8 ± 5.7 105.1 ± 9.8 F. plautii 99.4 ± 3.2 98.7 ± 3.3 100.3 ± 2.7 101.7 ± 2.5 103.0 ± 4.1 E. coli 99.6 ± 3.9 98.2 ± 7.3 98.7 ± 7.6 100.6 ± 8.8 110.6 ± 9.4 B. thetaiotaomicron 105.5 ± 3.9 101.5 ± 1.1 102.0 ± 2.9 101.0 ± 0.8 95.0 ± 13.0 A. muciniphila 95.9 ± 6.6 96.1 ± 5.5 93.6 ± 8.7 97.4 ± 7.1 95.1 ± 9.7 B. longum 99.3 ± 0.9 100.9 ± 2.6 100.2 ± 2.5 105.0 ± 5.0 107.7 ± 2.7

4.3 The effect of polyphenols on the abundance of mucus-associated gut bacteria in

in vitro mixed culture

Out of the three polyphenols tested, phloretin had the highest growth inhibitory activity, and 250 µM concentration was chosen based on the MIC assay that showed the tolerance of

A. muciniphila (Table 24b), which was reflected in the mixed culture experiment (Table 25b).

Lachnospiraceae, F. plautii, and B. thetaiotaomicron, were consistently reduced in the range of

1.5 to 3.3 logs beginning from 24 h of incubation, whereas A. muciniphila had less than 1 log reduction at all time points (Table 25b). The significant 1 log or more reduction of

Lachnospiraceae and F. plautii at 0 h immediately after the inoculation in the phloretin treatment indicate bactericidal inhibition compared to other bacteria that may be inhibited by bacteriostatic effect (Table 25b). Looking at the changes in proportion of the total bacteria excluding E. coli,

Lachnospiraceae (39 %) and B. longum (42 %) dominated the control mixed culture but

A. muciniphila (48 %) dominated the phloretin mixed culture (Figure 8). The other two polyphenols did not show significant antibacterial activity in the MIC assay at 250 µM (Table

24ac) and expectedly did not have a significant effect on the abundance of all the species in the mixed culture (Table 25ac). There were no major differences in the pH of THIO broth containing the polyphenols or the control solvent (0.2 % DMSO), where in the absence of bacteria pH was around 6.7 and with bacteria, pH was reduced to 5.0. The growth curve was at stationary phase for all bacteria up to day 7 (Figure 9).

HPLC analysis showed that phlorizin was present in the THIO broth with or without the bacteria up to 7 days (Figure 10), where no potential degradation products were detected, such as phloretin or phloretic acid. On the other hand, phloretin was completely degraded in the THIO broth without bacterial inoculation but was still present in the bacteria inoculated broth up to 7 days (Figure 11). Still, no phloretic acid was found with or without bacterial inoculation.

Chlorogenic acid was present in the control THIO broth without the bacteria but was completely converted to caffeic acid with the presence of bacteria within 48 hours of incubation, but no 3-(3- hydroxyphenyl)propionic acid was detected (Figure 12).

Time of incubation Target 0 h 24 h 48 h 4 days 7 days Lachnospiraceae 0.3 ± 0.4 -0.29 ± 0.4 -0.4 ± 0.6 -0.5 ± 0.7 -0.9 ± 1.1 F. plautii 0.0 ± 0.2 -0.2 ± 0.4 -0.3 ± 0.5 -0.2 ± 0.3 -0.2 ± 0.6 E. coli 0.3 ± 0.6 0.4 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.1 B. thetaiotaomicron -0.1 ± 0.5 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.1 0.0 ± 0.1 A. muciniphila 0.1 ± 0.1 0.0 ± 0.1 0.0 ± 0.1 0.1± 0.1 0.0± 0.2 B. longum 0.3 ± 0.6 0.0 ± 0.1 -0.1± 0.4 0.0 ± 0.2 -0.1 ± 0.2 b)

Time of incubation Target 0 h 24 h 48 h 4 days 7 days

Lachnospiraceae *-1.5 ± 0.3 *-3.3 ± 0.9 *-3.1 ± 0.5 *-2.9 ± 0.7 *-2.4 ± 0.4

F. plautii *-1.0 ± 0.3 *-2.8 ± 0.6 *-3.1 ± 0.3 *-3.2 ± 0.4 *-2.2 ± 0.1

E. coli -0.2 ± 0.3 0.0 ± 0.1 -0.1 ± 0.1 0.0 ± 0.0 -0.2 ± 0.2

B. thetaiotaomicron *-0.6 ± 0.18 *-1.6 ± 0.5 *-2.4 ± 1.0 *-2.3 ± 0.4 *-2.4 ± 0.1

A. muciniphila *-0.3 ± 0.1 *-0.7 ± 0.2 *-0.8 ± 0.3 *-0.6 ± 0.0 *-0.5 ± 0.0

B. longum -0.7 ± 0.3 *-2.3 ± 0.4 *-2.2 ± 0.1 -0.4 ± 1.3 -1.0 ± 0.7

Time of incubation Target 0 h 24 h 48h 4 days 7 days

Lachnospiraceae 0.1 ± 0.1 -0.2 ± 0.2 -0.1 ± 0.2 -0.5 ± 0.7 0.1 ± 0.3

F. plautii 0.0 ± 0.1 0.0 ± 0.0 0.0 ± 0.2 0.0 ± 0.2 -0.1 ± 0.5

E. coli 0.2 ± 0.0 0.0 ± 0.1 -0.1 ± 0.1 0.0 ± 0.1 0.1 ± 0.1

B. thetaiotaomicron 0.1 ± 0.1 0.0 ± 0.1 0.0 ± 0.0 0.0 ± 0.0 -0.1 ± 0.1

A. muciniphila 0.0 ± 0.1 0.0 ± 0.1 0.0 ± 0.1 0.1 ± 0.0 0.0 ± 0.1

B. longum 0.2 ± 0.2 0.0 ± 0.2 -0.1 ± 0.3 0.1 ± 0.3 -0.1 ± 0.4

B. longum, 42% Lachnospiraceae, 39%

A. muciniphila, 2% F. plautii, 6% B. thetaiotaomicron, 11%

Lachnospiraceae, 1% F. plautii, 1%

B. longum, 19% B. thetaiotamicron, 31%

A. muciniphila, 48%

Figure 8: Relative abundance of bacteria in a) the control (0.2 % DMSO) and in b) the 250 µM phloretin mixed culture at 24 hours incubation excluding E. coli. Total bacteria were calculated as the sum of target species or group excluding E. coli in CFU. CFU was calculated based on the standard curve of PMA- qPCR.

6 Log(CFU/mL)

4 0 1 2 4 7 Days

Lachnospiraceae F. plautii E. coli B. thetaiotaomicron A. muciniphila B. longum

Figure 9: Growth of bacteria in control broth (0.5 % DMSO) up to 7 days quantified by PMA-qPCR.

Figure 10: Absorbance of methanol extracted fraction of mixed culture containing phlorizin showing persistence of phlorizin (retention time 23.330) at day 7 of the incubation.

Figure 11:Absorbance of methanol extracted fraction of mixed culture containing phloretin showing persistence of phloretin (retention time 30.599) at day 7 of the incubation.

Figure 12: Absorbance of methanol extracted fraction of mixed culture containing chlorogenic acid showing complete conversion of chlorogenic acid to caffeic acid (retention time 12.536) at 48 hours.

Chapter 5 Discussion

5.1 Effect of polyphenols on human epithelial cells

5.1.1 Cytotoxicity of polyphenols

The cytotoxicity of the solvent DMSO and polyphenols were determined by SRB assay, a colorimetric reaction that measures the dyed cellular protein content by absorbance and correlates with the viability of cells (Vichai and Kirtikara 2006). The MTT (3-(4,5- dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay is another colorimetric assay that is regarded as the golden standard for determining cytotoxicity (van Tonder et al. 2015). The assay depends on the cells to convert tetrazolium salt MTT to insoluble purple formazan, only enumerating metabolically active viable cells (Edmondson et al. 1988). The results between SRB and MTT assays appear to be similar (Rubinstein et al. 1990; Vajrabhaya and Korsuwannawong

2018), or the SRB assay has higher sensitivity and better linear correlation for cell number changes of HT29 cells than the MTT assay (Keepers et al. 1991). This is why the SRB assay was selected.

As polyphenols are not soluble in a polar solvent, DMSO is a common solvent of choice for water insoluble polyphenols (Parkar et al. 2008; Djikic, 2016). In this study, DMSO concentrations at 0.2 % for HT29-MTX had no significant difference with the 0 % DMSO control. A similar result was found by Djukic (2016) with HT29 cells, where the viability of

HT29 cells were significantly different from the 0 % DMSO at 0.13 %, 0.5 %, 1 %, and 2 %, and the concentration of DMSO was inversely associated with cell viability. Only the viability of

HT29 at 102.1 % with 0.25 % DMSO was found to be not significantly different from the 0 %

DMSO, and this solvent concentration was chosen for dissolving the polyphenols (Djukic, 2016).

Because DMSO can cause both antioxidant and prooxidant reactions, a low concentration is recommended for studying antioxidant compounds (Sanmartín-Suárez et al. 2011).

The maximum concentration of polyphenols that could be dissolved in 0.2 % DMSO was

100 µM (Appendix 7). At this concentration, there was no statistical difference in the viability of

HT29-MTX cells exposed to phlorizin, phloretin and chlorogenic acid compared to the control.

This result is supported by Choi et al. (2015), who found no significant difference in the viability of HT29 cells exposed to chlorogenic acid or caffeic acid for 24 hours up to 200 µM concentration compared to the control using the SRB assay. Furthermore, a study by D’Agostino et al. (2012) showed that the toxicity of polyphenols on HT29 cells may depend on the mucin- polyphenol interaction and the structure of the polyphenol. EGCG can be toxic to HT29 cells without the mucous layer but less toxic to H29-MTX cells with the mucous, possibly due to the polyphenols binding with the mucin proteins, protecting the cells from the compound

(D’Agostino et al. 2012). Epicatechin did not have a significant toxic effect to either cell line, which suggested that the galloyl ring in ECGC may be responsible for the cytotoxic effect

(D’Agostino et al. 2012). In a similar study, EGCG was found to be able to pass Caco-2 cells in the monolayer but not through the Caco-2/HT29-MTX co-culture, supporting the interaction between polyphenols and the mucous layer (Guri et al. 2015). Hence, the low toxicity of the phlorizin, phloretin, and chlorogenic acid on HT29-MTX cells observed may have been due to protection by the mucous layer or their structure not being cytotoxic.

Although this study did not show that polyphenols have a cytotoxic effect against carcinogenic cell line HT29-MTX cells, polyphenols have been shown to be cytotoxic and cause apoptosis of cancer cells (Curti et al. 2017; Abotaleb et al. 2018). As well, polyphenols can have antiproliferative activity at concentrations below the cytotoxic level (Kuntz et al. 1999). Still the

same study showed that most of the 30 flavonoid compounds tested at a concentration of 150 µM did not have cytotoxic activity against HT29 and Caco-2 cell lines, where the viability of the cells was ≥ 80 % (Kuntz et al. 1999).

5.1.2 Do polyphenols indirectly stimulate mucin production by the host cells?

The target mucin genes, MUC1, MUC5AC, MUC5B, MUC13, and MUC20 were chosen based on the Ct values of 1:10 diluted pooled cDNA being less than 30. Considering that the standard curve needs to be constructed with 1:2 dilutions, mucin genes with Ct values greater than 30 (MUC2, MUC3, MUC4, MUC12, MUC15) were not ideal for this study (Table A 8).

Ideally, MUC2 and MUC4 would have been the appropriate mucin genes to study as they are highly expressed in a normal colonic tissue, rather than MUC5AC and MUC5B genes that are normally expressed only in a gastric tissue (Andrianifahanana et al. 2006). Time points at 12 and

24 h were chosen because there was no apparent difference in the mucin gene expression or mucin production pattern at the earlier time points of 30 minutes and 6 h (Table A 8).

The exposure to 100 μM of phlorizin, phloretin, and chlorogenic acid did not significantly affect the expression of mucin genes or mucin production by the HT29-MTX cells in this study, leading to the rejection of the hypothesis that the chosen polyphenols stimulate mucin production by the host cells and provide mucin for A. muciniphila. This result is supported by a similar study by Volstatova et al. (2019) that used co-culture of Caco-2/HT29-MTX cells, exposed them to 10 μM of chlorogenic acid, epicatechin gallate, and quercetin, and showed significantly increased level of MUC17 for only the latter two polyphenols. No changes were observed with MUC3 and MUC13 (Volstatova et al. 2019), similar to the present study. There was also a 3-fold decrease in MUC2 expression for chlorogenic acid even though the authors did not mention any significance level (Volstatova et al. 2019). Still, the level of MUC2 in the spent

medium measured by ELISA was not significantly different to the control (Volstatova et al.

2019), which is in accordance with the result obtained by ELLA in this study.

Polyphenols have been shown to regulate the production of mucin by other epithelial tissues, such as respiratory and gastric tissues. Using IL-1β-induced mucin hypersecreting normal human nasal epithelial cells or NCI-H292 human airway epithelial cells, 50 μM of EGCG or 10 μM of 6-gingerol were shown to suppress MUC5AC expression and secretion, by inhibiting proteins involved in the MAP kinase pathway that mediates the IL-1β-induced

MUC5AC gene expression (Kim et al. 2008; Kim et al. 2009). Likewise, curcumin can suppress

MUC5AC expression in MUC5AC hypersecreting NCI-H292 cells or mucus hypersecreting ovalbumin induced chronic asthmatic mice (Tang et al. 2018; Zhu et al. 2019). On the contrary, chebulinic acid found in an Indian fruit has been shown to stimulate mucin secretion in the gastric ulcer induced rat model (Mishra et al. 2013). Despite no apparent change in mucin gene expression or secretion by the HT29-MTX colon cell line, polyphenols may have the ability to regulate mucin production in vivo, in other epithelial tissues, or in mucin-hypersecreting tissues.

Furthermore, polyphenols may stimulate mucin production during in vitro culture through the production of reactive oxygen species (ROS), although ROS were not measured in the present study. Polyphenols in a tissue culture media are unstable and can produce ROS such as H2O2 due to the higher concentration of oxygen exposed in in vitro experiments compared to in vivo conditions (Halliwell 2003). This is problematic as goblet cells can secrete mucin in response to ROS (Peterson and Artis 2014). To illustrate, Bellion et al. (2009) showed polyphenol-mediated ROS formation in in vitro tissue culture media (DMEM, 5 % FCS,100

U/mL penicillin,100 μg/mL streptomycin). Phlorizin, phloretin, and chlorogenic acid at 100 μM concentration after 24 hours of incubation produced 1.9 μM, 2.4 μM, and 32.5 μM of H2O2

respectively, where the chlorogenic acid appears to be a potent H2O2 producer in the culture media (Bellion et al. 2009). However, caffeic acid was shown to produce a significant amount of

H2O2 only when pH was equal or lower than 7 over 24 hours in PBS (Bellion et al. 2009).

Assuming that chlorogenic acid and its derivative caffeic acid behave similarly, chlorogenic acid is not likely to produce a significant amount of ROS at physiological pH at which the cell cultures are maintained. The concentration of 100 μM used in this study for phlorizin, phloretin, and chlorogenic acid probably did not form ROS and expression and production of the mucin were not affected.

The lack of evidence supporting the direct induction of mucin production by polyphenols suggests that the increased mucin level observed in in vivo studies may be due to the increased A. muciniphila level that is known to promote mucin production (Everard et al. 2013). Previous studies using in vivo mice models have shown that polyphenols can promote mucin 2 (Muc2) gene expression or mucin production simultaneously with the stimulation of A. muciniphila in mice (Pierre et al. 2013; Anhê, Varin, et al. 2015; Taira et al. 2015; Anhê et al. 2017; Shen et al.

2017; Singh et al. 2018). In contrast, Muc2 and Muc3 expression were not significantly increased by grape extracts in the absence of A. muciniphila increase (S. Zhang et al. 2017). Interestingly, in some instances, Muc2 was not upregulated with the polyphenol treatment despite the increased level of A. muciniphila (Roopchand et al. 2015). Moreover, mice fed a HFD or a low fat diet

(LFD) supplemented with grape extract polyphenol or grape proanthocyanidins (PAC) had significant A. muciniphila blooms without changes in the expression of host genes related to metabolic health (L. Zhang et al. 2018). This showed that A. muciniphila is stimulated before host gene expression is altered, further suggesting that the polyphenols indirectly promote mucin

secretion by supporting the growth of A. muciniphila in the gut environment, rather than directly altering mucin gene expression.

5.1.3 The use of HT29-MTX, RT-qPCR and ELLA for evaluating mucin stimulating activity

by food components

HT29 cell lines, such as HT29-MTX, are suitable for studying mucin-stimulating activity of food components in vitro (Verhoeckx et al. 2015). The HT29 cell line was isolated from colon adenocarcinoma cells of a 44 year-old Caucasian female in 1964 (Fogh and Trempe 1975).

Stepwise exposure of the HT29 cells to increasing concentrations of an anticancer drug, methotrexate (MTX), selects for MTX resistant HT29 cells that have differentiated into mucus- secreting goblet cells (Lesuffleur et al. 1993). There are other GI cell lines available, such as

Caco-2 cells and IPEC-J2 cells, but they produce no or low amounts of mucin that do not resemble the in vivo condition and are not practical to use to study mucin secretion or gene expression (Verhoeckx et al. 2015). HT29-FU cells have been shown to have a more colonic like phenotype, expressing predominantly MUC2 and MUC4 genes, whereas HT29-MTX cells have more gastric tissue-like phenotype, expressing predominantly MUC3 and MUC5AC cells.

Having said that, the maximum proportion of HT29-FU cells that expresses mucin genes is only

20 %, whereas HT29-MTX can reach 100 % and remain stable over time (Lesuffleur et al.

1993). As well, even though the co-culture of Caco-2 and HT29-MTX cells reflects a more physiologically relevant model, the proportions may slightly change after confluency due to the

Caco-2 cells having a faster doubling time than the HT29-MTX cells (Araújo and Sarmento

2013), introducing an additional variable into the in vitro model.

However, in vitro models such as HT29-MTX cells do not completely represent the normal human intestinal tissue, hence the gene expression and protein response to the

polyphenols may be affected by additional factors in vivo. The HT29 cell line is a carcinogenic cell line and does not have the same gene expression compared to healthy colon cells (Grootaert et al. 2015). It is structurally closer to the small intestine (expresses brush border-associated hydrolase) than the large intestine, despite being a colonic cell (Martínez-Maqueda et al. 2015).

HT29 and Caco-2 cells have a different protein profile compared to scrapings of non-tumorous regions of the small and large intestine from a pancreatic and colonic cancer patient (Lenaerts et al. 2007). Likewise, the expression pattern of the common intestinal cell lines used, including

HT29, were clustered differently from biopsy samples of human intestinal tissue using PCA analysis, although HT29 cells appeared to correlate better than other cell lines to the biopsied samples (Bourgine et al. 2012).

Considering the above limitations, the HT29-MTX cell line has been used to study the mucin stimulating activity of food components in combination with RT-qPCR and ELLA. For example, Martínez-Maqueda et al. (2012) and Plaisancié et al. (2013) used HT29-MTX cells and showed that bioactive peptides from dairy and wheat sources stimulate the expression of MUC2,

MUC4, and MUC5AC genes and increase the amount of total mucin-like glycoprotein in the spent media using ELLA. Some peptides showed both stimulation of the mucin genes and increased the amount of total mucin-like glycoprotein, whereas some peptides only had an effect on the amount of total mucin-like glycoprotein (Martínez-Maqueda et al. 2013). This is likely because RT-qPCR is gene specific and can reveal changes in the expression of one mucin gene whereas ELLA shows overall changes in total mucin secretion. Because ELLA is not specific to one type of mucin, it has been shown to be more accurate for quantifying the total amount of mucin than ELISA, except that it is unsuitable for quantifying specific mucin types (Abdullah et al. 2012). ELLA has been used to quantify total glycoprotein-like mucin in spent medium of

HT29-MTX cell culture (Martínez-Maqueda et al. 2012) as well as the cell lysate of HT29-MTX

(Wan et al. 2014). Moreover, the use of cell culture instead of an in vivo model allows distinction from other stimuli of mucin production, including the gut microbiota (Peterson and Artis 2014) and their associated products such as LPS, toxins, and SCFA (Burger-van Paassen et al. 2009;

Cornick et al. 2015). Especially with the A. muciniphila stimulating polyphenols, it is difficult to deduce the direct effect of the polyphenols on host mucin production as A. muciniphila itself can enhance mucin production by the host cell (Everard et al. 2013).

5.2 Polyphenols and bacterial cell wall structure in relation to antibacterial activity

At 2.5 % DMSO, the viability of the tested bacteria was relatively high, above 80 %, except for C. hylemonae and B. thetaiotaomicron at 75.01 % and 60.9 %. Thus, DMSO at a maximum concentration of 2 % and lower were used to dissolve the polyphenols for the MIC assay. In order to reach the concentration of 1000 µM for phlorizin, phloretin, and chlorogenic acid, at least 2 % DMSO was needed due to the solubility of the polyphenols in DMSO.

There were no MIC values obtained even at the highest concentration of 1000 µM for phlorizin and chlorogenic acid, but phloretin had 50 % growth inhibitory effect at 500 µM for all bacteria except E. coli. This result agrees with previous literature that showed that aglycones have higher antibacterial potential than the glycosylated polyphenols in general (Parkar et al.

2008; Duda-Chodak 2012). Specifically, in another MIC assay, the phloretin treatment had significantly lower MIC values for S. aureus, Listeria monocytogenes, and S. typhimurium compared to the phlorizin treatment (Barreca et al. 2014). Similar to phlorizin, chlorogenic acid has been noted to have low antimicrobial activity (Pernin et al. 2019). According to the antimicrobial mechanisms of phenolic acids proposed by Pernin et al. (2019), there are three models based on the findings with L. monocytogenes. Chlorogenic acid belongs to model 1 that

depends only on the decrease in pH (Pernin et al. 2019). In the present study, the pH of the media with and without chlorogenic acid were both 6.7, with no significant decrease in the pH.

Compared to the other two models, phenolics grouped in model 1 have low antimicrobial activity, possibly due to the steric hinderance of their structure preventing diffusion or the low partition coefficient preventing the solubilization in the plasma membrane (Pernin et al. 2019).

Model 1 may also be applicable to phlorizin, with higher steric hinderance compared to phloretin, due to the glucose moiety.

Caffeic acid was fitted with model 2 exhibiting inhibition through the decrease in pH and by the action of the undissociated form (Pernin et al. 2019). In mixed culture, chlorogenic acid was completely converted to caffeic acid. The most antimicrobial model 3 takes into account the dissociated form in addition to both pH and the undissociated form, such as for p-coumaric and ferulic acid (Pernin et al. 2019). As model 2 and 3 suggest, smaller phenolic acids, such as caffeic acid, may be more antibacterial than the larger esterified compounds such as chlorogenic acid. Still, the MIC of caffeic acid is not necessarily lower than that of chlorogenic acid (Table

26). This was also evident in the mixed culture, where chlorogenic acid was completely converted to caffeic acid and had no significant inhibition. Assuming that the chlorogenic acid was completely converted to caffeic acid, the concentration of the undissociated form of caffeic acid would have only been 76 µM based on the pH of the medium being 5.0 and the pKa of caffeic acid as 4.62 using the Henderson-Hasselbalch Equation (Calculation A 9). It is possible that the concentrations were too low to show any inhibitory effect for both undissociated caffeic acid or the intact chlorogenic acid, or the bacteria selected were not susceptible to the low concentration. With other species, such as Shigella dysenteriae and Streptococcus pneumoniae,

chlorogenic acid is capable of disrupting the plasma membrane and cause cell leakage at 50 µM

(Lou et al. 2011).

Expanding on the models proposed by Pernin et al. (2019), phloretin had relatively higher antibacterial activity possibly due to its smaller molecular size and higher hydrophobicity than phlorizin and chlorogenic acid. The cell walls of Gram positive and negative bacteria are hydrophobic (Delcour 2009). Especially for the Gram negative bacteria, where the cell membrane is less permeable than for Gram positive bacteria, the antibiotic must penetrate into the bacteria through the LPS and phospholipid bilayer either by hydrophobic structure or by diffusion through porin channels if the antibiotic structure is hydrophilic (Delcour 2009).

Consequently, for phenolic compounds, the hydrophobicity and electronic charge of the structure appear to be the factors determining the antibacterial potency (Bouarab-Chibane et al. 2019).

Specifically, for E. coli, increased hydrophobicity or lipophobicity of the polyphenol has been correlated with the increased antibacterial activity based on the 35 polyphenols tested (Bouarab-

Chibane et al. 2019). Assuming the commensal gut bacteria in this study follow the same correlation, phloretin would be more hydrophobic and have greater inhibitory activity than phlorizin or chlorogenic acid.

Having said that, E. coli in this study had remarkably higher tolerance for phloretin compared to the other bacteria tested. The high tolerance of E. coli against phloretin has been previously observed by Barreca et al. (2014) who showed that E. coli ATCC 10536 was resistant to 1000 µg/mL (3646 µM) of phloretin. Likewise, of the 6 food borne pathogens or spoilage bacteria tested against 35 polyphenols, E. coli was least susceptible following Pseudomonas aeruginosa with only about half of the polyphenols showing 20 % inhibition (Bouarab-Chibane et al. 2019). The high tolerance may be due to it being a Gram negative bacterium equipped with

efflux pumps that can develop antibacterial resistance (Li and Nikaido 2004). The role of the efflux pumps in developing tolerance against polyphenols is evident from a study of an E. coli mutant strain lacking the tolC gene being more susceptible to the polyphenols than the wild-type strain (Cueva et al. 2010). While it is important to note that the same mutant also lacked the lpxC gene responsible for biosynthesis of lipid A, which may also have played a role (Cueva et al.

2010). In addition, the wall of Gram positive bacteria is generally more permeable to antibiotics.

The outer membrane of Gram negative bacteria acts as a molecular sieve that prevents diffusion of larger molecules regardless of the polarity (Lambert 2002; Cama et al. 2019). In the present study, Gram positive or Gram variable species including C. symbiosum, C. hylemonae,

Blautia sp., F. plautii and B. longum (Johnson et al. 1995; Kitahara et al. 2000) were significantly inhibited by phloretin compared to Gram negative E. coli and A. muciniphila but not B. thetaiotaomicron at 500 µM. Of the Gram-negative bacteria tested, E. coli had the highest tolerance, which may be due to the previously-mentioned cell surface composition of lipid and protein that can determine the permeability (Delcour 2009). As an example, lipid A of E. coli is hexa-acylated (Ingram et al. 2010) whereas B. thetaiotaomicron is penta-acylated (Berezow et al.

2009). A study on the relationship between the degree of acetylation and the permeability of LPS in different strains of E. coli showed that the lower degree of acetylation was associated with higher permeability (Li et al. 2013).

Overall, the importance of hydrophobicity of the polyphenol and the cell surface suggest that the mechanism of antibacterial action for most polyphenols may be due to the disturbance of the cell surface structure (Bouarab-Chibane et al. 2019). For instance, lactic acid bacteria (LAB) are not inhibited by more hydrophobic polyphenols (quercetin and kaempferol) but are inhibited by the less hydrophobic myricetin compared to E. coli that was not inhibited by myricetin

(Puupponen-Pimiä et al. 2001). Coincidently, higher tolerance of EGCG by LAB is associated with low cell surface hydrophobicity and high exopolysaccharide level (Nakayama et al. 2015), suggesting that the cell surface of Gram-positive bacteria such as LAB is less hydrophobic and may be more susceptible to less hydrophobic polyphenol structures. This is in contrast to Gram negative bacteria such as E. coli that are susceptible to more hydrophobic polyphenols (Bouarab-

Chibane et al. 2019). However, the degree of hydrophobicity for Gram positive and negative bacteria should not be generalized, and there are some who suggest there is no relationship between antibacterial activity and Gram strain (Taguri et al. 2006). Investigating cell surface hydrophobicity among species and strains in relation to the antibacterial activity of polyphenols may help clarify the conflicting results.

Lastly, there is a limitation to only using the MIC broth assay in determining antibacterial activity, as there is no one standardized method and interpretation between studies using different assays is difficult (Balouiri et al. 2016). Comparing results from the broth-based assay studies, Gram negative bacteria appear to be more resistant to the antibacterial activity of the selected polyphenols (Table 27). This trend agrees with the present results as E. coli and

A. muciniphila appeared to tolerate phloretin better than other species. On the contrary, with the agar-based methods, Gram positive bacteria such as S. aureus are not necessary more susceptible to the polyphenols and can even show higher tolerance than E. coli (Table 26), which may be due to the semi-quantitative nature of the agar disc or well diffusion tests (Balouiri et al. 2016).

In addition, various strains of E. coli can auto-aggregate in static broth culture (Hasman et al.

1999). This would reduce the surface area of cells exposed to the antibacterial substances in the broth, conferring an advantage over other species and perhaps produce different results from agar-based methods.

Polyphenol MIC Species (Gram stain) Reference Concentration (µM) Phlorizin 1058 S. aureus ATCC 6538 (+) Barreca et > 2117 L. monocytogenes ATCC 13932 (+); al. 2014 S. typhimurium ATCC 13311(-); P. aeruginosa ATCC 27853 (-); P. aeruginosa ATCC 15442 (-); E. coli ATCC 10536 (-) Phloretin 28.5 S. aureus ATCC 6538 (+) 228 L. monocytogenes ATCC 13932 (+) 456 S. typhimurium ATCC 13311 (-) > 3646 P. aeruginosa ATCC 27853 (-); P. aeruginosa ATCC 15442 (-); E. coli ATCC 10536 (-) Phlorizin 265 S. aureus (+) Parkar et al. 2117 E. coli (-); S. typhimurium (-); Lactobacillus 2008 rhamnosus (+) Chlorogenic 353 S. aureus (+) Acid 705 L. rhamnosus (+) 2822 E. coli (-); S. typhimurium (-) Caffeic Acid 694 S. aureus (+) 1388 L. rhamnosus (+) 2775 E. coli (-); S. typhimurium (-) Caffeic acid > 2775 E. coli O157:H7 (-); S. typhimurium DT104 Si et al. (-) 2006

b) Polyphenol Concentration Species (Gram stain) Reference & Method Phlorizin > 10 µL/disc E. coli CECT 434 (-); P. aeruginosa ATCC 10145 Saavedra et al. (-); S. aureus CECT 976 (+); L. monocytogenes 2010 ATCC 15313 (+) Chlorogenic 1.41 E. coli CM871 (-) Puupponen- acid µmol/well Pimiä et al. > 1.41 L. rhamnosus (+); Lactobacillus reuteri (+); 2001 µmol/well Lactobacillus paracasei (+); L. johnsonii (+); Lactobacillus crispatus (+); Lactobacillus plantarum (+); B. lactis (+); E. faecalis (+); S. enterica (-); E. coli 50 (-) Chlorogenic 56.45 µM Streptococcus pneumoniae (+); Shigella Lou et al. acid dysenteriae (-) 2011(Pour plate 112.90 µM S. aureus (+); B. subtilis (+); S. typhimurium (-) method) 225.79 µM E. coli (-) Chlorogenic 10 µL/disc E. coli CECT 434 (-); P. aeruginosa ATCC 10145 Saavedra et al. acid (-); S. aureus CECT 976 (+); L. monocytogenes 2010 ATCC 15313 (+) Caffeic acid 4.62 E. coli CM871(-); S. enterica (-); E. coli 50 (-) Puupponen- µmol/well Pimiä et al. 2001 > 4.62 L. rhamnosus (+); L. reuteri (+); L. paracasei (+); µmol/well L johnsonii (+); L. crispatus (+); L. plantarum (+); B. lactis (+); E. faecalis (+); Caffeic acid > 27.75 L. acidophilus (+) Hervert- µmol/disc Hernández et al. 2009

Caffeic acid 0.17 E. coli ATCC 35218 (-); Serratia marcescens Vaquero et al. nmol/well 2007 0.83 E. coli ATCC 25922 (-) nmol/well 8.34 S. aureus ATCC 29213 (+) nmol/well 16.7 P. aeruginosa ATCC 27853 (-); Proteus mirabilis nmol/well (-) > 82.3 S. aureus ATCC 25923 (+); nmol/well Klebsiella pneumoniae (-); Flavobacterium sp. (-) Caffeic acid 10 µL/disc E. coli CECT 434 (-); P. aeruginosa ATCC 10145 Saavedra et al. (-); S. aureus CECT 976 (+); L. monocytogenes 2010 ATCC 15313 (+)

5.3 Competition between A. muciniphila and other mucus-associated species in the

presence of polyphenols

5.3.1 Indirect inhibitory activity of polyphenols against competitors favours A. muciniphila

None of the polyphenols tested had a stimulatory effect on the growth or survival of any of the bacteria tested, including A. muciniphila, and this lack of direct stimulation by the polyphenol is evident from previous studies that compared the growth of A. muciniphila in pure in vitro cultures to in vivo mice models. For instance, a pomegranate extract that stimulated

A. muciniphila in a human study (Li et al. 2015) did not enhance but inhibited the growth of pure

A. muciniphila culture in THIO broth incubated over 6 days (Henning et al. 2017). Likewise, capsaicin only showed an inhibitory effect on A. muciniphila in pure culture, despite having a stimulatory effect on A. muciniphila in the in vivo mice model (Shen et al. 2017).

Phlorizin, phloretin, and chlorogenic acid or caffeic acid all persisted over the 7 days of incubation, as they were not depleted by the bacteria as substrates. Phlorizin contains glucose in the structure, which can be deglycosylated, and the glucose can used by species such as

E. ramulus (Schneider and Blaut 2000) or possibly by bacteria with β-glucosidases such as

E. coli and B. longum (Braune et al. 2016). However, no formation of the aglycone counterpart of phlorizin, namely phloretin, was detected, as phlorizin persisted in the mixed culture up to 7 days. This showed that none of the bacteria cleaved the glucose attached to phlorizin that could have been directly used as an energy source. Chlorogenic acid, on the other hand, was converted into caffeic acid, most likely by E. coli that has been found to have an esterase activity (Couteau et al. 2001), although there was no significant change in the growth of any bacteria. According to

Henning et al. (2017), A. muciniphila can degrade ellagitannin, which is inhibitory to its growth, into ellagic acid which has no significant effect on growth (Henning et al. 2017). Hence, the

degradation of polyphenols by gut bacteria may primarily alter the antibacterial activity of the polyphenols, rather than functioning to provide nutritional substrates, as evident from the chlorogenic acid conversion in this study.

However, the THIO broth used to grow the mixed culture was nutrient rich and all bacterial growth was stable at stationary phase up to 7 days, which could have affected gene expression and metabolic activity. Gut microbes such as Lachnospiraceae, Ruminococcaceae,

Bacteroidetes, and A. muciniphila are more abundant in the large intestine than the upper GI tract

(Pereira and Berry 2017; Van Herreweghen et al. 2017). The availability of simple nutrients decreases along the GI tract, and in the large intestine, the ability to break down complex and partially digested food is essential for colonization (Pereira and Berry 2017). The THIO broth used in the present study contains 0.5 % glucose and no mucin, which does not completely represent the nutrient availability in the large intestine. It is known that the genes involved in mucin degradation and the uptake of glucose are downregulated in A. muciniphila in the absence of mucin (Ottman et al. 2017). In addition, the presence of mucin can alter the interaction between A. muciniphila and other butyrate producing species. For example, butyrate producing

Anaerostipes caccae, belonging to the Lachnospiraceae, enhanced the mucin-degrading activity of A. muciniphila that in return supported butyrate production by A. caccae via the acetyl-CoA pathway (Chia et al. 2018). While the regulation and association of mucin degradation activity to the expression of other genes are unclear, it is possible that altered metabolism could have affected the expression of genes involved in the polyphenol degradation or potential utilization.

In addition, the inhibitory concentration of phloretin against F. plautii may have prevented the degradation of phloretin into the smaller phenolic acid that could have had less antibacterial activity. F. plautii is known to degrade phloretin into 3-(4-hydroxyphenyl)propionic

acid in in vitro (Schoefer et al. 2003) but degradation was not observed in the present study.

Degradation has been observed below the growth inhibitory concentration of 300 µM (Schoefer et al. 2003), close to the 250 µM used in the present study. Another phloretin degrading species,

E. ramulus, is capable of growing at higher concentration of phloretin at 5000 µM which may be due to it being able to degrade phloretin faster than F. plautii (Schoefer et al. 2003). As well,

L. Zhang et al. (2018) hypothesized that the cross-feeding of the polyphenol may be a possibility for growth promotion. At a lower concentration or in the presence of E. ramulus, phloretin could have been degraded into phenolic acid, which may have altered the growth of other bacteria including A. muciniphila.

Still, the mixed culture with the mucus-associated species showed that A. muciniphila was more tolerant to phloretin at 250 µM concentration than the other species except E. coli.

B. thetaiotaomicron and B. longum are known mucin-degraders (Tailford et al. 2015), and suppression of these species would potentially allow A. muciniphila to access more mucin. Since the metabolism of glycan, including dietary and host mucin, can impact the composition of the gut microbiota (Koropatkin et al. 2012), less competition for mucin may benefit A. muciniphila and support its growth.

If the stimulation of the A. muciniphila is dependent on the indirect inhibitory activity of the polyphenols on other competitor gut microbes, then the concentration and the type of polyphenol may be a factor in determining the stimulatory activity. It is clear that phloretin had more antibacterial activity than the phlorizin or chlorogenic acid in this study. As such, regardless of using similar extracts, the effect on the A. muciniphila can be contradictory. For instance, grape pomace polyphenol extract fed to HFD mice in one study resulted in a significant stimulation of A. muciniphila (L. Zhang et al. 2018) whereas another study that also fed grape

pomace polyphenol extract to HFD mice resulted in no significant change in the A. muciniphila abundance (Van Hul et al. 2017). The former used concord grape pomace and the latter used red- wine grape pomace (Van Hul et al. 2017; L. Zhang et al. 2018). It is possible that the extract used by L. Zhang et al. (2018) had a higher proportion and concentration of inhibitory polyphenol responsible for providing favourable condition for A. muciniphila, such as phloretin in the present study, than the extract produced by Van Hul et al. (2017). Similarly, tea polyphenols had different effects in two studies using HFD mice where Liu et al. (2016) had increased A. muciniphila abundance but Axling et al. (2012) had no apparent change in the

A. muciniphila abundance. Although it is important to note that the experimental conditions were not identical, polyphenol extracts from the same food or beverage may not reproduce the same results.

Choosing to work with pure polyphenols, rather than the extracts, demonstrated more clear action of a particular polyphenol on A. muciniphila in the present study. As an example,

L. Zhang et al. (2018) compared the A. muciniphila abundance in mice supplemented with

360 mg/kg of grape PAC daily and grape extract containing an equivalent amount of PAC and showed both groups resulted in stimulation of A. muciniphila. Unfortunately, there was no data published on the effect of PAC on other species compared to the grape extract (L. Zhang et al.

2018); therefore, it is unclear whether they imposed the same gut microbial change. It is known that catechin, the monomers of PAC, significantly increased the level of Clostridium coccoides–

Eubacterium rectale (Lachnospiraceae), Bifidobacterium spp. and E. coli in a batch culture, granted that there was only 0.1 to 0.5 log increase compared to the control which may not be significant in vivo (Tzounis et al. 2008). The effect of the polyphenol concentration may also be apparent by feeding two different concentrations of pure resveratrol to HFD mice (Chen et al.

2019). The higher concentration at 100 mg/kg body weight per day increased the relative abundance of A. muciniphila, greater than the low concentration at 50 mg/kg body weight (Chen et al. 2019). The increase and decrease in the abundance of other groups such as Clostridium cluster IV (Ruminococcaceae) and Desulfovibrio (Proteobacteria) appears to be more pronounced at higher concentration, though only slightly without any statistical significance

(Chen et al. 2019). At a lower concentration of 15 mg/kg body weight fed to high fat high sugar diet (HFHSD) mice, no significant change in the A. muciniphila abundance was observed

(Etxeberria et al. 2015).

Overall, the absence of the tested polyphenols selectively stimulating or being utilized by

A. muciniphila or other bacteria disagrees with the current prebiotic definition (Gibson et al.

2017). Instead, the results support the hypothesis that polyphenols, at least phloretin, has selective antibacterial activity against competitors that may be indirectly favouring the

A. muciniphila.

5.3.2 Impact on other mucus-associated SCFA-producing species

C. symbiosum, C. hylemonae, and Blautia sp. belonging to the Lachnospiraceae family and F. plautii from the Ruminococcaceae family were more greatly inhibited by phloretin relative to A. muciniphila. These two families are found to be associated with the mucous layer and produce butyrate (Van den Abbeele et al. 2013; Rivière et al. 2016). Theoretically, the suppression of these butyrate producers would reduce the level of butyrate in the gut that is used by the host colonocytes as a primary energy source (Donohoe et al. 2011; Morgan et al. 2012).

Specifically, butyrate and propionate can increase MUC2 expression by the goblet cells through acetylation or methylation of the MUC2 promoter histone (Burger-van Paassen et al. 2009). In the previous studies using extracts or pure polyphenols that had stimulatory effect on

A. muciniphila, Lachnospiraceae and Ruminococcaceae or their associated genus or species were stimulated, had no significant change in the abundance, or showed inhibition (Table 27).

These varying results indicate that the inhibition of two families does not necessarily have a negative impact on the abundance of A. muciniphila. Still, none of the studies measured the

SCFA when these families were suppressed (Table 27), thus the level of SCFA may be a factor affecting A. muciniphila abundance through indirectly regulating mucin production by the host cells.

Bifidobacterium and B. thetaiotaomicron are mucin-degraders (Tailford et al. 2015) known to produce acetate from carbohydrate metabolism (Rivière et al. 2016). Acetate is found to promote goblet cell differentiation by HT29-MTX cells, and F. prausnitzii, a member of the

Ruminococcaceae family that consumes acetate, can reduce the acetate level and suppress goblet cell differentiation in vivo in a mouse model that may help maintain cell type proportions and homeostasis (Wrzosek et al. 2013). Acetate is a substrate needed by the butyrate producers to produce butyrate through the acetyl-CoA pathway (Mahowald et al. 2009). In other words, a reduction in the acetate level can indirectly result in the reduction of the butyrate level. In the present study, both B. longum and B. thetaiotaomicron were inhibited by phloretin. Similar to

Lachnospiraceae and Ruminococcaceae, Bacteroidetes or Bacteroides and Bifidobacterium were stimulated, inhibited or had no significant change in their abundance with no clear correlation to

A. muciniphila stimulation by polyphenols (Table 27). Perhaps, as the balance between acetate, which promotes goblet cell differentiation, and butyrate, which promotes mucous secretion, both appear to be involved in mucous production, the proportions of acetate and butyrate producers may have contributed to a preferred mucous environment for A. muciniphila. Besides,

A. muciniphila can also produce acetate and propionate from mucin degradation (Derrien et al.

2004). Even though acetate and propionate are not a primary energy source, they are produced from mucin degradation and may benefit the host cells for producing mucin (Zhou 2017), as propionate can also enhance MUC2 expression similar to butyrate (Burger-van Paassen et al.

2009). If this is the case, A. muciniphila may be able to compensate for the loss of acetate and butyrate producers due to the treatment of polyphenols.

Comparing HFHSD or HFD mice to standard chow or LFD mice, identical polyphenol extracts stimulated Bifidobacterium or Actinobacteria in the former diet group and inhibited in the latter group despite both groups inducing A. muciniphila growth (Anhê et al. 2017; L. Zhang et al. 2018). Bifidobacterium seems to be consistently inhibited in healthy human subjects or

SHIME inoculated with feces of healthy volunteers regardless of the polyphenol extract used when A. muciniphila is stimulated (Donohoe et al. 2011; Kemperman et al. 2013; García-Villalba et al. 2017; Wu et al. 2018). Mice on a HFD diet have lower numbers of Bifidobacterium than mice on standard chow diet (Cani et al. 2007), and the fecal microbiota of obese individuals contain lower Bifidobacterium abundance than that of lean individuals (Schwiertz et al. 2010).

The baseline abundance of Bifidobacterium being lower in diet-induced obese mice compared to lean mice or humans may have resulted in an opposing effect of polyphenols on their abundance.

Thus, the relatively high proportion of B. longum used in the present study compared to the relative abundance of Actinobacteria at 5-7 % in human gut (Koliada et al. 2017) may have resulted in their inhibition.

5.3.3 Simultaneous stimulation of E. coli by polyphenols and the level of LPS

The growth of E. coli, which belongs to Proteobacteria phylum, was not affected by phloretin and was the most resistant to this polyphenol. Accordingly, the majority of polyphenol extracts or pure polyphenols that stimulated A. muciniphila appear to simultaneously increase the

abundance of Proteobacteria or its associated gut microbes (Table 27). Particularly, the genus

Escherichia was significantly stimulated in healthy volunteers consuming pomegranate extract

(Li et al. 2015). The only two studies by Singh et al. (2018) and Shen et al. (2017) that showed significant reduction in E. coli or Proteobacteria, could be because mice fed a HFD diet are associated with higher LPS producing bacteria at their baseline level compared to a standard diet

(Cani et al. 2007). This evidence suggests that Proteobacteria such as E. coli are less susceptible to the inhibitory activity of polyphenols in both in vitro and in vivo environments in the presence of other gut microbiota.

In addition to being tolerant against to polyphenols, stimulation of mucin degraders such as A. muciniphila may be benefiting E. coli through increased nutrient availability of mucin- derived sugars. Despite the fact that the commensal E. coli can reside in the mucous layer

(Conway et al. 2004; Miranda et al. 2004), they do not have the ability to degrade mucin

(Hoskins et al. 1985). Mucin degraders such as B. thetaiotaomicron can digest complex polysaccharides and preferably transport oligosaccharides into the cells, and the remaining mono- and disaccharides can be consumed by E. coli (Conway and Cohen 2015). For example, a human gut commensal E. coli K-12 MG1655 has been shown to preferably use mucin-derived sugars in a mice model (Chang et al. 2004). A. muciniphila can use mucin-derived monosaccharides such as fucose, galactose, and N-acetylglucosamine, but appears not to be able to grow solely on N-acetylneuraminic acid (Ottman et al. 2017) which may be utilized by the

MG1655 strain of E. coli (Chang et al. 2004). Coincidently, none of the polyphenol extracts or pure polyphenols that inhibited or did not affect A. muciniphila abundance had any stimulation of Proteobacteria or E. coli (Table 27).

At the same time, Proteobacteria are estimated to contribute 5.2 % to 14 % of LPS biosynthesis in healthy individuals, following Bacteroidetes at 79 % to 92.4 % (d’Hennezel et al.

2017). As one of the major genera in the gut microbiota, Bacteroides does produce LPS but the structure of LPS is different than that of pathogenic LPS producers such as E. coli and do not cause a potent proinflammatory response (Jacobson et al. 2018). E. coli is one of the largest contributors to LPS biosynthesis (d’Hennezel et al. 2017). Species such as E. coli belonging to the Enterobacteriaceae family are thought to be involved in causing inflammation by releasing

LPS as endotoxins (Morgan et al. 2012). The production and secretion of mucin is one of the inflammatory responses during bacterial inflammation caused by bacterial LPS (Smirnova et al.

2003). However, A. muciniphila is suppressed in individuals with IBD, suggesting that inflammatory conditions may not benefit A. muciniphila (Png et al. 2010).

E. coli can be a commensal gut bacteria that consists of phylogenetic groups that are both non-pathogenic (A and B1) and pathogenic (B2 and D) (Katouli 2010), and the inflammatory response may be strain-specific (Kittana et al. 2018). Of the polyphenol studies that stimulated taxa associated with Proteobacteria, none of them increased the inflammatory markers or endotoxin levels (Roopchand et al. 2015; Song et al. 2016; S. Zhang et al. 2017; Anhê et al.

2018). In addition, the “Restaurant” hypothesis by Conway and Cohen (2015) suggests that the commensal E. coli resides in the mucous layer and receives nutrients locally while they compete with the invading potentially pathogenic strains. To illustrate, pre-colonization or colonization of the MG1655 strain protected against the colonization or eliminated pre-colonized E. coli

EDL933 strain O157:H7 (Miranda et al. 2004). The MG1655 strain appeared to only colonize the mucous layer whereas the EDL933 strain was also found close to the host epithelial cells

(Miranda et al. 2004). Overall, not all strains of E. coli are likely to cause inflammation.

Table 27: List of polyphenol a) extracts or b) pure or defined mixed of polyphenols that have been studied for their effect on the abundance of A. muciniphila in vitro or in vivo. Changes in the abundance of Lachnospiraceae, Ruminococcaceae, Bacteroides, Proteobacteria, and Bifidobacterium related taxonomic groups and SCFA levels are also noted. Increase (↑), decrease (↓), no change (=) and change (Δ) within the taxonomic group compared to the baseline period or vehicle control *statistically significant difference. High fat high sugar or sucrose diet (HFHSD); high fat diet (HFD); Low fat diet (LFD); Standard chow diet (SCD) a)

Extract Subject Dosage & Microbial Observation Reference Duration camu camu Mice on 200 *↑ A. muciniphila Anhê et al. (Myrciaria dubia) HFHSD mg/kg/day = Lachnospiraceae 2019 8 weeks ↓ Ruminococcaceae *↑ Bifidobacterium Canarium album Mice on HFD 15 mg/kg/d *↑ A. muciniphila N. Zhang et al. 4 weeks Δ Lachnospiraceae 2018 ↓ Ruminococcaceae *↓ Bacteroides = Proteobacteria = Actinobacteria Chokeberry (juice SHIME 6.5 g/L *↑ A. muciniphila Wu et al. 2018 not extract) 2 weeks ↑ Lachnospiraceae ↑ Ruminococcaceae *↑ Proteobacteria ↓ Bifidobacterium ↓ acetate ↑ propionate ↑ butyrate Cinnamon bark Mice on HFD 2 g/kg/day = A. muciniphila Van Hul et al. 8 weeks *↑ Roseburia 2017 (Lachnospiraceae) ∆ Ruminococcaceae ∆ Bacteroidaceae = Proteobacteria = SCFA (all 3) Cloudberry; Mice on 200 *↑ A. muciniphila Anhê et al. Alpine bear berry; HFHSD mg/kg/day = Lachnospiraceae 2018 Lingonberry 8 weeks = Ruminococcaceae ↑ Proteobacteria ↓ Actinobacteria = SCFA (all 3) Cranberry Mice on Gavage 200 *↑ A. muciniphila Anhê et al. HFHSD or mg/kg/day = Ruminococcus 2017 SCD 8 weeks = Clostridium

= Bacteroides HFHSD: *↑ Bifidobacterium SCD: ↑ Lachnospiraceae *↓ Bifidobacterium Cranberry Mice on HFD 200 *↑ A. muciniphila Singh et al. mg/kg/day *↑ Lachnospiraceae 2018 12 weeks ↑ Faecalibacterium *↓ E. coli = Bifidobacteria = acetate *↑ propionate = butyrate (concord) grape Mice on HFD 1 % of feed *↑ A. muciniphila Roopchand et (complexed with 13 weeks *↓ Lachnospiraceae al. 2015 soy protein) *↓ Ruminococcaceae *↑ Bacteroidetes *↑ Enterobacteriaceae (Red wine) grape SHIME 1000 mg/day ↑ A. muciniphila Kemperman et 2 weeks ↓ Lachnospiraceae al. 2013 ↓ Ruminococcaceae ↓ Bacteroides ↑ Klebsiella (Proteobacteria) ↓ Bifidobacterium = acetate = propionate ↓ butyrate (table) grape Mice on HFD 5 % of feed *↑A. muciniphila Baldwin et al. 11 weeks Δ Lachnospiraceae 2016 = Ruminococcaceae = Bifidobacterium Grape Pomace Mice on HFD 8.2 g/kg/day = A. muciniphila Van Hul et al. 8 weeks *↑ Roseburia 2017 (Lachnospiraceae) ∆ Lachnospiraceae ∆ Ruminococcaceae ↑ Bacteroidetes ↓ Proteobacteria ∆ Bifidobacteriaceae = SCFA (all 3)

Grape pomace Mice on HFD 1 % of diet *↑ A. muciniphila L. Zhang et al. (complexed with or LFD 14 days HFD: 2018 soy protein) *↓ Firmicutes = Bacteroidetes *↑ Blautia ↓ Clostridium IV *↑ Proteobacteria *↓ Actinobacteria LFD: *↓ Firmicutes (only in cecum) *↑ Clostridium XIVa *↑ Blautia *↓ Clostridium IV ∆ Flavonifractor *↓ Bacteroidetes *↑ Proteobacteria ↑ E. coli ↓ Actinobacteria Green tea Mice on HFD 4 % of feed = A. muciniphila Axling et al. 22 weeks 2012 Milk thistle seed Batch culture 0.4 g flour *↓ A. muciniphila Choe et al. of mice feces equivalents = Firmicutes 2019 per mL *↓ Bacteroidetes *↓ Enterobacteriaceae *↓ Bifidobacteria Pomegranate Healthy 1000 mg/day *↑ A. muciniphila Li et al. 2015 humans 4 weeks = Firmicutes = Bacteroidetes *↑ Escherichia *↓ Bifidobacterium Pomegranate Mice on 0.25 % of feed = A. muciniphila S. Zhang et al. HFHSD 4 weeks = Lachnospiraceae 2017 *↑ Ruminococcaceae *↓ Bacteroides *↓ Enterobacteriaceae = Bifidobacterium Pomegranate TWIN- 1.8 g/day *↑ A. muciniphila García- SHIME 3 weeks Δ Clostridium cluster Villalba et al. XIVa 2017 *↑ Bacteroides *↓ Bifidobacterium *↓ SCFA (all) ascending colon at 7 days.

Rhubarb Mice 0.3 % of feed ↑ A. muciniphila Neyrinck et al. challenged 17 days ↓ Lachnospiraceae 2017 with alcohol ↓ Blautia or SCD ↓ Ruminococcaceae ↓ Bacteroides ↓ Proteobacteria Tea infusions Mice on HFD In drinking ↑ A. muciniphila Liu et al. 2016 (green, oolong, water Δ Lachnospiraceae black) 13 weeks *↓ Clostridium leptum (Ruminococcaceae) *↓ Bacteroides acidifaciens (Black) tea SHIME 1000 mg/day ↑ A. muciniphila Kemperman et 2 weeks ↓ Lachnospiraceae al. 2013 ↓ Ruminococcaceae ↓ Bacteroides ↑ Klebsiella (Proteobacteria) ↓ Bifidobacterium Δ acetate = propionate = butyrate

Extract Subject Dosage & Microbial Observation Reference Duration Betacyanins Mice on HFD 200 ↑ A. muciniphila Song et al. (from red pitaya) mg/kg/day ↑ Roseburia/ 2016 14 weeks Ruminococcus / Anaerostipes (Lachnospiraceae) ↑ Bacteroides ↑ Escherichia ↓ Bifidobacterium Caffeic acid Colitis-induced 1 mM in *↑ A. muciniphila Zhang et mice drinking = Firmicute al. 2016 water = Bacteroides 15 days = Proteobacteria Capsaicin Mice on HFD 0.01 % of ↑ A. muciniphila Shen et al. diet *↑ Bacteroides 2017 9 weeks *↓ Proteobacteria Chlorogenic acid Colitis-induced 2 % of diet; ↑ A. muciniphila Zhang et mice model 20 days = Bacteroides al. 2019 = Parasutterella (Proteobacteria) = Actinobacteria Chlorogenic acid In vitro batch 80.8 mg / *↑ C. coccoides– Mills et al. culture of human 150 mL of Eubacterium rectale 2015 feces batch group culture (Lachnospiraceae) (Ruminococcaceae) = Bacteroides *↑ Bifidobacterium Chlorogenic acid Colitis-induced or 3.54 mg/kg *↑ A. muciniphila Z. Zhang et healthy mice per day = Lachnospiraceae al. 2017 = Blautia = Ruminococcaceae = Flavonifractor = Bacteroides ↑ Proteobacteria = Escherichia-shigella Epigallocatechin- Overweight/obese 282 mg/day = A. muciniphila Most et al. 3-gallate + human + = Firmicutes 2017 resveratrol 80 mg/day = Faecalibacterium 20 weeks prausnitzii (Ruminococcaceae) = Bacteroidetes = γ-Proteobacteria

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= Actinobacteria Genistein Humanized mice 4 weeks *↑ A. muciniphila Paul et al. (from breast *↑ Ruminococcus 2017 cancer patients) torques(Lachnospiraceae) *↓ Blautia *↓ Bacteroides ↑ E. coli Grape C57BL/6J mice 360 *↑ A. muciniphila L. Zhang et proanthocyanin on LFD mg/kg/d of al. 2018 diet 10 days Phlorizin db/db mice 20 *↑ A. muciniphila Mei et al. mg/kg/day *↑ acetate 2016 10 weeks *↑ propionate *↑ butyrate Procyanidin B2 Rabbits on HFD 150 ↑ A. muciniphila Xing et al. mg/kg/d ∆ Lachnospiraceae 2019 12 weeks ∆ Ruminococcaceae = Flavonifractor ↑ Bacteroidetes Δ Proteobacteria ↑ Bifidobacterium Pterostilbene Zucker (fa/fa) rats 15 *↑ A. muciniphila Etxeberria mg/kg/day *↓ Firmicutes et al. 2017 6 weeks *↓ Lachnospiraceae ↑ Bacteroidetes = Proteobacteria Quercetin Mice on HFHSD 30 ↑ A. muciniphila Etxeberria mg/kg/day = Lachnospiraceae et al. 2015 6 weeks = Ruminococcaceae = Bacteroidetes = Proteobacteria ↑ acetate ↑ propionate ↑ butyrate Quercetin + Mice on HFHSD 15 ↑ A. muciniphila Etxeberria trans-resveratrol mg/kg/day = Lachnospiraceae et al. 2015 + 30 = Ruminococcaceae mg/kg/day = Bacteroidetes 6 weeks = Proteobacteria = acetate = propionate = butyrate

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Resveratrol Rat on HFD 100 *↑ A. muciniphila Chen et al. mg/kg/d ↑ Clostridium cluster 2019 6 weeks XVIa *↑ Clostridium cluster IV ↑ Bacteroides *↓ Desulfovibrio (Proteobacteria) = acetate = propionate ↑ butyrate trans-resveratrol Mice on HFHSD 15 ↓ A. muciniphila Etxeberria mg/kg/day = Lachnospiraceae et al. 2015 6 weeks = Ruminococcaceae = Bacteroidetes = Proteobacteria Vanillin Mice on HFD 0.1 % of *↑ A. muciniphila Guo et al. diet *↓ Clostridium leptum 2017 (Ruminococcaceae) *↑ Actinobacteria ↓ Deltaproteobacteria (Proteobacteria) *↑ acetate *↑ propionate *↑ butyrate

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5.4 Limitations of the study

Despite the stimulatory effect of phlorizin and chlorogenic acid observed in the previous in vivo mice models (Mei et al. 2016; Z. Zhang et al. 2017; Zhang et al. 2019), no significant differences in the growth of any bacteria tested was observed at 250 µM. Using the dose conversion ratio by Reagan-Shaw et al. (2008), human equivalent doses with 60 kg of body weight would be 97.3 mg of phlorizin (Mei et al. 2016) and 17.2 mg of chlorogenic acid (Z.

Zhang et al. 2017) per day. Assuming that the human adult gut volume is 3 L (Parkar et al. 2008;

Henning et al. 2017), the concentrations in the gut would be 205 µM and 48.5 µM respectively, less than the 250 µM concentration used. The concentrations used in the present study were most likely not the reason why there was no stimulation of A. muciniphila. At higher or lower concentrations, no difference in the growth was observable with the MIC assay.

The lack of stimulatory effect by phlorizin and chlorogenic acid may be due to other factors missing in in vitro conditions, such as the pre-digestion of the polyphenols, diversity and the heterogenous distribution of the gut microbiota, host-gut microbiota interaction, the presence of the mucous layer, and the low simple nutrient availability as discussed previously (Pereira and

Berry 2017). Phlorizin is mainly glucuronated or sulfated by host enzymes, which are structurally different from phlorizin or phloretin, and can reach the large intestine (Marks et al.

2009). In addition, an estimated 1,000 – 1,150 species of gut bacteria are found in the human intestine while individuals carry about 160 species (Qin et al. 2010), with an estimated 1,952 uncultured candidate species based on a metagenome assembly (Almeida et al. 2019). Only 8 species were selected to represent those associated with the mucous layer, with only one strain representative of each species. Specifically, some of other species known to be involved in the degradation of polyphenols were not included, including Eubacterium ramulus that can degrade

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phloretin into phloretic acid (Schneider and Blaut 2000). Thus, the simplistic microbiota used in this study should not be generalized to the in vivo gut microbiota. In addition, the distribution of the mucus-associated bacteria is known to be spatially heterogenous in the GI tract (Donaldson et al. 2016), which was not reflected in the broth cultures. As well, the host-microbiota interaction was absent, despite the fact that some mucus-associated species are capable of influencing goblet cell differentiation and mucin secretion through the production of SCFA, which can indirectly impact the growth of A. muciniphila (Burger-van Paassen et al. 2009; Wrzosek et al. 2013).

Likewise, as mentioned before, the absence of the mucous layer does not take into account the polyphenol and mucin interaction which may protect the host cells (D’Agostino et al. 2012) and potentially the mucus-associated gut bacteria from polyphenol activities. However, by separating the host and the gut microbiota, the direct interaction with the polyphenols individually were able to be targeted in this study.

Furthermore, there are other potential stimulatory mechanisms of polyphenols such as modifying the structure of the mucus, the antioxidant activity, and stimulation of antimicrobial peptides that were not considered in this study (Anhê, Varin, et al. 2015). Galloylated catechin has been shown to crosslink with mucin and potentially modulate the mucous environment for gut microbiota (Georgiades et al. 2014). Antioxidant properties of polyphenols may help with the survival of obligative anaerobes, especially for mucus-associated species as the oxygen level increases closer to the host epithelial cells (Roopchand et al. 2015; Donaldson et al. 2016).

Approximately 40 % of the antioxidant activity observed in a grape pomace extract was measured in feces of mice fed with the grape pomace extract, which indicated that the antioxidant activity was present throughout the GI tract (Kuhn et al. 2018). Additionally, rhubarb extract fed to mice challenged with alcohol showed that it was able to stimulate the growth of

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A. muciniphila, as well as induce gene expression of RegIII γ that has been positively correlated with the abundance of A. muciniphila (Neyrinck et al. 2017).

Estimating the gut volume to be around 3 L (Parkar et al. 2008; Henning et al. 2017), concentration of 100 μM or 250 μM used in the mucin study or the mixed culture would be equivalent to consuming around 100 mg or 250 mg of one of the polyphenols (Table A 10). The amount of food required to consume 100 mg or 250 mg phlorizin would be unrealistic in a daily diet (Table A 11); however, because various polyphenols and extracts have been shown to stimulate A. muciniphila (Table 27), the total consumption of polyphenols from the diet is relevant to consider. The average total polyphenol consumption per day is approximately 1000 mg per day based on several studies on various populations (Table 1), where the average for the

North American population was about 801 mg per day (Burkholder-Cooley et al. 2016). It is possible for the polyphenols together to reach 250 mg total intake in a meal and influence the

A. muciniphila growth, as phloretin was shown to inhibit the growth of its competitors at 250 μM or 250 mg.

5.5 Summary, conclusions and future perspectives

In this study, phlorizin and chlorogenic acid were chosen as polyphenols as they are contained in apple that are 1) one of the most common fruit consumed in various populations and is the second highest contributor of fruit polyphenol intake in the North American diet

(Burkholder-Cooley et al. 2016) and 2) present at relatively high concentrations and have low bioavailability in apple (Table 2; Table 3; Table 6). Phloretin was also studied as it is one of the major metabolites of phlorizin collected in ileal fluid (Table 7). In order to investigate the stimulatory mechanism of polyphenols on A. muciniphila demonstrated by numerous in vivo studies (Table 27), pure forms of the polyphenols were utilized to examine their effect on the

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mucin production by the host cells and the antibacterial activity against mucus-associated commensal competitors in vitro. Pure forms were used as they are more practical in deducing and understanding their interaction with the host cells or A. muciniphila and specific gut microbes, being able to control the concentrations and the type of polyphenols (Baldwin et al.

2016; Ozdal et al. 2016).

There was no significant effect of the tested the polyphenols on mucin production or expression by the HT29-MTX cells. Phloretin was shown to inhibit the growth of other mucus- associated commensal gut microbiota more effectively than A. muciniphila in vitro, both in the

MIC assay and the mixed culture numerated by PMA-qPCR. Still, no evidence of the direct stimulation and utilization of polyphenols were observed in this study, indicating the lack of prebiotic effect and supporting the selective antibacterial effect that competitively favors

A. muciniphila. The lack of mechanism demonstrated by phlorizin was possibly due to it being less antibacterial than the phloretin, and the chlorogenic acid or caffeic acid may be due to the absence of susceptible gut bacteria. Ultimately, polyphenols may indirectly alter host mucin production, such as the level of SCFA produced by the gut microbiota, through changing the composition or the activity of the gut microbiota. As well, the presence of mucin would better mimic the mucous environment that may expose the gut bacteria to polyphenols. It would be of interest to use in vitro models such as the M-SHIME to investigate whether the mucous layer would enhance or diminish the antibacterial effect of the polyphenols against the competitors of

A. muciniphila.

Furthermore, dietary polyphenols are contained in a food matrix and are processed, and the study of the interaction between the polyphenols and the gut microbiota must be approached comprehensively (Tomás-Barberán and Espín 2019). For instance, inulin and pomegranate

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extract individually did not affect the abundance of Actinobacteria in HFHSD mice, but in combination had significant increase (S. Zhang et al. 2017), suggesting a synergic effect on the gut microbiota. Similarly, dietary intervention often involves combinations of foods. In a double- blinded randomised controlled trial, 25 patients with type 2 diabetes supplemented with “a combination of functional foods” composed of fiber and polyphenol rich food (nopal, chia seeds, soy protein, inulin, and maltodextrin) increased the level of A. muciniphila and F. prausnitzii with improved metabolic markers (Medina-Vera et al. 2019).

In addition, apple polyphenols have multiple mechanisms in promoting health, not just through the gut microbiota. Masumoto et al. (2016) conducted a mouse model study using absorbable oligomeric procyanidin (< 5) and non-absorbable polymeric procyanidin (5 ≤) extracted from apple juice to see their effect on the diabetic inflammatory conditions and gut microbiota of HFHSD mice. Both groups of mice treated with the absorbable or the non- absorbable procyanidins successfully alleviated diabetic symptoms, such as reducing weight gain and hyperglycemia and intestinal permeability, and lowering serum cytokine levels, even though the food intake was the same as untreated control group. However, only the group of mice treated with non-absorbable procyanidin had significantly higher abundance of A. muciniphila population, by eight folds compared to the no treatment group. This study shows that the apple polyphenols have health beneficial functions with or without interacting with the gut microbiota.

This research helped to understand the proposed mechanism of polyphenols as stimulant for A. muciniphila. Additionally, gaining more knowledge on the mechanism behind how polyphenols modulate gut microbiota would support its application in potential “diet-based therapies” (Anonye et al. 2017). Likewise, polyphenols may be degraded differently depending on the gut microbiota of the individual (Li et al., 2015). Six out of twenty volunteers consuming

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pomegranate extract did not produce urolithin A, in their fecal and urine sample, with the producers having 33 times and 47 times higher abundance of A. muciniphila before and after the intervention than the non-producer group (Li et al., 2015). Consequently, by understanding which gut bacteria are responsible for the degradation, the presence of specific degradational products could act as biomarkers of specific microbial ecology (Espin et al 2017, Anhê et al

2016; Tomás-Barberán et al. 2016). Overall the result of this study supported the hypothesis that

A. muciniphila may have a higher tolerance against phloretin relative to other mucus-associated gut bacteria, but not the stimulation of mucin production by the polyphenols, that would be advantageous for A. muciniphila over the competitors in the presence of polyphenols.

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APPENDICES

Table A 1: Additional list of primers that were used for amplifying mucin and reference genes.

Target Gene Primer Sequence (5’-3’) Amplicon (bp) Reference

GAPDH F: TGCACCACCAACTGCTTAGC 87 Hruz et al. R: GGCATGGACTGTGGTCATGAG 2011 MUC2 F: GCTGCTATGTCGAGGACACC 90 Graziani et R: GGGAGGAGTTGGTACACACG al. 2016 MUC3 F: GTGGAGATCCTGTCCCTGAG 102 Graziani et R: CACCTGCTCATACTCGCTCTC al. 2016 MUC4 F: GCGTTCTTATACCACGTTCCA 144 Plaisancié et R: CTTGTAGCCATCGCATCTGA al. 2013 MUC12 F: CTACGTTGGTTACCAGTGCTTG 83 Sperandio et R: TCATACCTAAAGTGGCGTTGAG al. 2013 MUC15 F: GCTTACTCTTGTGGGCTACT 110 Yang and Li R: GTGCATTGTCTAATCGCAGAAC 2014

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Table A 2: Threshold cycle (Ct) obtained from gradient qPCR of mucin genes tested, with 1:10 diluted pooled cDNA.

Threshold cycle (Ct) at temperature (oC) 69.2 68 66.4 64.5 62 60.9 58 55 Cyclophilin 18.13 18.02 17.90 17.72 MUC1 28.39 28.43 28.04 28.11 MUC5AC 30.30 29.66 29.81 30.14 MUC5B > 40 31.45 29.67 30.27 MUC13 32.44 27.83 27.83 27.57 MUC20 24.15 23.03 22.79 22.19 GAPDH 19.86 19.60 19.37 19.49 MUC2 37.33 36.28 36.14 36.61 MUC3 33.92 34.26 33.20 33.20 MUC4 34.84 36.68 35.0 36.18 MUC12 34.28 33.86 33.23 33.23 MUC15 36.66 35.69 34.73 34.26

Table A 3: M values of GAPDH and cyclophilin for gene stability test based on geNorm method, analysed using Bio-Rad CFX Maestro software.

Gene Name Evaluation Average M Stability # of samples Value (Ln(1/AvgM))

GAPDH Ideal 0.35426975 1.0377 16 cyclophilin Ideal 0.35426075 1.0377 16

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Table A 4: Concentrations of gDNA used for the gradient qPCR, where 5 µL of working DNA solution was added to the qPCR reaction.

Species Original Dilution Working Final amount concentration Factor concentration added to the (ng/µL) (ng/µL) reaction (ng)

C. symbiosum 313.9 1: 10,000 0.03139 0.15695 C. hylemonae 91.7 1: 1,000 0.0917 0.4585 Blautia sp. 217.7 1: 10,000 0.02177 0.10885 F. plautii 109.5 1: 1,000 0.1095 0.5475 E. coli 249.9 1: 10,000 0.2499 0.12495 B. thetaiotaomicron 160.1 1: 1,000 0.1601 0.8005 A. muciniphila 117.5 1: 1,000 0.1175 0.5875 B. longum 40.6 1: 1,000 0.0406 0.203

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Table A 5: Threshold cycle (Cq) obtained from gradient qPCR and melting peak temperature (in brackets) at various temperature for each primer on all bacterial DNA extracted in this study. Non-template control (NTC) contains molecular grade water at a volume equal to that of the volume of DNA added (5 µL). Bolded are the lowest Ct values(s) observed for each intended target. a) ClcoF and ClcoR specific for Lachnospiraceae (Clostridium cluster XIVa group).