Characterizing effects of prebiotics and human milk oligosaccharides on the intestinal epithelial barrier

by

You (Richard) Wu

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy

Laboratory Medicine and Pathobiology University of Toronto

© Copyright by You Wu 2017

[ii]

Characterizing effects of prebiotics and human milk oligosaccharides on the intestinal epithelial barrier

You (Richard) Wu

Doctor of Philosophy

Laboratory Medicine and Pathobiology

University of Toronto

2017

Abstract

Prebiotics are non-digestible compounds that enhance the growth of certain microbes within the

gut microbiota and confer benefits on the host, but whether they can also elicit direct immune-

regulatory effects is unknown. This thesis addresses this gap through three specific aims: (1) to

characterize the effects of prebiotics on the intestinal epithelial barrier, (2) to delineate the

underlying signaling mechanisms underlying barrier- and immune-regulation, and (3) to evaluate

the effects of human milk oligosaccharides using relevant models of human disease.

In the first part of this thesis, two prebiotics, inulin and short-chain fructooligosaccharides

(scFOS), were tested in an in vitro bacterial challenge system with enterohemorrhagic

Escherichia coli serotype O157:H7. Inulin and scFOS increased the resistance of Caco-2Bbe1

monolayers, reduced permeability and increased the expression of select tight junction proteins.

These changes were associated with the activation of protein kinase C isoform δ - a host kinase

enzyme that controls multiple cell functions.

The second part of this thesis expands on PKCδ signaling and characterizes the global signaling

of inulin and scFOS using Caco-2Bbe1 cells. This was performed using a kinome peptide array

to profile kinase phosphorylation levels, which revealed several immune pathways and

[iii]

functional networks that were regulated by prebiotics. These findings were then validated in vivo

using a neonatal endotoxemia model, which showed that prebiotics dampened intestinal

inflammation without altering the composition of gut microbiota.

In the third part of this thesis, I demonstrate a unique mechanism whereby HMOs promote

barrier function by inducing the production of mucus. This finding was confirmed using a

neonatal mouse model of necrotizing enterocolitis (NEC), where HMOs prevented the

development of NEC by enhancing intestinal goblet cell production.

Taken together, these data demonstrate that prebiotics are not biologically inert. In fact,

prebiotics directly trigger host cell signaling to alter epithelial barrier integrity and gut

inflammation – indicating previously unrecognized mechanisms of prebiotics and HMOs.

[iv]

Acknowledgements

Foremost, I would like to thank my family for their loving support throughout this incredible

journey. My mother and father, Susan Jiang and Zhiping Wu, whom despite knowing absolutely

nothing about cell biology, have always given me their utmost attention to be the most tuned-in

listeners of my work. To Gary and Tracy, my “left and right arms”, I appreciate you simply

being there when I needed you.

Second, I thank both the past and present members of the Sherman Lab. I must thank Kathene

Johnson-Henry for her encouragements, wisdom and willingness to listen, allowing me to

confide to her my various concerns as a graduate student. I thank all the valuable lab mates:

Kathryn, Linda and Lee, for being so patient in my early transition from medicine to graduate

training; Thomas, for helping me draw the connection to clinical relevance; Ana and Will, for the

endless entertainment and wisdom both inside and outside of work; Pekka and Ebi, for the

wonderful conversations and debates about meat versus vegetable.

Thirdly, I owe my deepest gratitude to my supervisor, Philip Sherman for being an outstanding

mentor. The excitement and enthusiasm that he shares for science have been absolutely

infectious. He helped me see the positives of science and reminded me of its ultimate purpose

and where this pipeline leads to - people. His nurturing helped me cultivate the skill of “thick-

skin” - where no rejections or reviewer comments are bad enough to put me down. “Get up, do

something else, then come back and try again” is now my life motto.

Fourth, I thank my committee members, David Hwang and Nicola Jones for providing the

guidance for my PhD; to Agostino, Peter, Yuhki and rest of the Pierro lab, for the incredible

collaborations and friendships; to the Friday journal club, for all the fun and wonderful

discussions; to the lab neighbors of the 21st floor, for all the coffees, cookies, “pick-me-ups” in

the hallway that made my training enjoyable. I thank Monique, for teaching me the mastery of

the ancient relic “rotovap” and importantly, for being so strong of a person.

Lastly, I thank my grandmother Jie, whose battle with cancer took a toll on her life, but whose

story forever fills a social consciousness to my scientific and clinical career, and forever reminds

me about the needs of patients and the endless questions of human disease.

[v]

Table of Contents

Acknowledgements ......................................................................................................... iv

Table of Contents ............................................................................................................. v

List of Abbreviations ...................................................................................................... viii

List of Figures ............................................................................................................... xiii

List of Tables ................................................................................................................ xvi

1 Introduction .................................................................................................................. 1

1.1 Host-microbe interactions in health and disease ................................................... 3

1.2 Dietary impacts on microbiota ............................................................................... 7

1.2.1 Infant microbiota ......................................................................................... 7

1.2.2 Adult microbiota ........................................................................................ 13

1.3 Prebiotics as microbiota-targeted therapeutics ................................................... 16

1.4 Prebiotic metabolites ........................................................................................... 21

1.4.1 Prebiotic utilization.................................................................................... 21

1.4.2 Polysaccharide utilization loci ................................................................... 22

1.4.3 Microbiome population shifts .................................................................... 25

1.5 Prebiotic-derived metabolites: short-chain fatty acids ......................................... 27

1.6 Direct innate immune response to prebiotics ...................................................... 32

1.6.1 Intestinal epithelial barrier ......................................................................... 33

1.6.2 Pattern recognition receptors ................................................................... 45

[vi]

1.6.3 Innate immunity in health and disease ..................................................... 53

1.7 Direct innate immune modulation by prebiotics ................................................... 59

2 Hypothesis and Objectives ........................................................................................ 63

3 Protein Kinase C δ Signaling is Required for Dietary Prebiotic-Induced

Strengthening of Intestinal Epithelial Barrier Function ............................................... 64

3.1 Abstract ............................................................................................................... 65

3.2 Introduction ......................................................................................................... 67

3.3 Materials and Methods ........................................................................................ 69

3.4 Results ................................................................................................................ 76

3.5 Discussion ........................................................................................................... 96

4 Prebiotics Modulate Pathogen-Induced Inflammatory Processes Through

Regulation of Host Kinase Activities ........................................................................ 101

4.1 Abstract ............................................................................................................. 102

4.2 Introduction ....................................................................................................... 104

4.3 Materials and Methods ...................................................................................... 106

4.4 Results .............................................................................................................. 113

4.5 Discussion ......................................................................................................... 148

5 Dietary Human Milk Oligosaccharides Protect Experimental Necrotizing

Enterocolitis by Inducing Mucin Production ............................................................. 153

5.1 Abstract ............................................................................................................. 154

5.2 Introduction ....................................................................................................... 156

[vii]

5.3 Materials and Methods ...................................................................................... 159

5.4 Results .............................................................................................................. 167

5.5 Discussion ......................................................................................................... 195

6 Discussion and Future Directions ............................................................................ 199

6.1 Re-definition of “prebiotics” ............................................................................... 201

6.2 Limitations and Future Directions ...................................................................... 205

6.3 Significance of the research undertaken ........................................................... 210

References .................................................................................................................. 211

[viii]

List of Abbreviations

Abbreviations Terms

A/E Attaching and effacing

AMPs Antimicrobial peptides

BF Breastfed

BPs Binding proteins

CBP Creb-binding protein

CC3 Cleaved caspase 3

CCL C-C motif chemokine ligand

CD Crohn’s Disease

CDC Cell division control protein

CE Carbohydrate esterase

CFU Colony-forming unit

CXCL C-X-C motif chemokine ligand

DAPI 4',6-diamidino-2-phenylindole

DCs Dendritic cells

DMEM Dulbecco's modified Eagle medium

DMSO Dimethyl sulfoxide

DP Degrees of polymerization

DPPs Differentially phosphorylated peptides

DSS Dextran sodium sulfate

EDTA Ethylenediaminetetraacetic acid

EGF Epidermal growth factor

[ix]

EGFR Epidermal growth factor receptor

EHEC Enterohemorrhagic Escherichia coli O157:H7

ERK1/2 P44/42 extracellular-regulated kinases

FBS Fetal bovine serum

FDR False discovery rate

FF Formula-fed

FITC Fluorescein-labeled isothiocyanate

FOS Fructooligosaccharides

GCs Goblet cells

G-CSF Granulocyte colony stimulating factor

GH Glycoside hydrolases

GI Gastrointestinal

GLP Glucagon-like peptide

GO Gene ontologies

GOS Galactooligosaccharides

GPR G-coupled protein receptor

GTP Guanosine-5'-triphosphate

GUK Guanylate kinase domain

HMOs Human milk oligosaccharides

HPAEC-PAD High-performance anion-exchange chromatography with

pulsed amperometric detection

IBD Inflammatory bowel disease

IECs Intestinal epithelial cells

[x]

IESCs Intestinal epithelial stem cells

IFN-γ Interferon-gamma

IgA/G/M Immunoglobulin A/G/M

IGF Insulin-like growth factor

IκBα Inhibitor of kappa B alpha

Iκκ IκB kinase

Iκκα IκB kinase alpha

IL Interleukin

IRAK Interleukin-1 receptor-associated kinase

IRFs Interferon regulatory factors

KDa Kilodalton

KEGG Kyoto encyclopedia of genes and genomes

LPL Lipoprotein lipases

LPS Lipopolysaccharide

MAPKs Mitogen-activated protein kinases

MDCK Madin-Darby canine kidney cells

MIF Migration inhibiting factor

MOI Multiplicity of infection

MUC Mucin

MW Molecular weight

MyD88 Myeloid differentiation primary response gene 88

NEC Necrotizing enterocolitis

NF-κB Nuclear factor kappa B

[xi]

NGF Nerve growth factor

OTU Operational taxonomic unit

PAMPs Pathogen-associated molecular patterns

PCoA Principle coordinates analysis

PCs Paneth cells

PDI Protein disulfide isomerase

PFA Paraformaldehyde

PI3K Phosphatidylinositol-3-kinase

PKC Protein kinase C

PL Polysaccharide lyases

PRRs Pattern recognition receptors

PTMs Post-translational modifications

PUL Polysaccharide utilization loci

RACK Receptor for activated C kinase

RALDH Retinaldehyde dehydrogenase

RhoA Ras homolog gene family member A

RIPK Receptor for receptor-interacting serine/threonine-protein

kinase

ROCK Rho-associated protein kinase

rRNA Ribosomal RNA

SAM Severe acute malnutrition

SCFAs Short-chain fatty acids

scFOS Short-chain fructooligosaccharides

[xii]

SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis

SH3 Src-homology 3

siRNA Silencer RNA

SPDEF SAM pointed domain containing ETS transcription factor

Sus Starch utilization system

TAB TAK-1-binding protein

TAK TGFβ-activated kinase

TER Transepithelial electrical resistance

TFF3 Trefoil factor 3

TGFβ Transforming growth factor beta

TIR Toll/IL-1R homology domain

TJ Tight junctions

TLRs Toll-like receptors

TMAO Trimethylamine oxide

TNF-α Tumor necrosis factor alpha

TRAF-6 TNF receptor associated factor-6

VEGF Vascular endothelial growth factor

ZO Zona occludens

[xiii]

List of Figures

Chapter 1

Figure 1.1: Environmental factors affecting the development of gut microbiota. ........... 10

Figure 1.2: Structures of the three main categories of prebiotics .................................. 19

Figure 1.3: Starch utilization system employed by B. thetaiotathemicron ..................... 23

Figure 1.4: Local and systemic impacts of bacterial-derived metabolites SCFAs. ........ 30

Figure 1.5: The cell morphology of small intestine villus-crypt unit. .............................. 35

Figure 1.6: Intestinal TJ complexes .............................................................................. 41

Figure 1.7: Zonula occludens binding domains ............................................................. 43

Figure 1.8: MyD88-dependent and MyD88-independent pathways of TLR pathways .. 48

Figure 1.9: Transwell system for the measurement of TER. ......................................... 56

Figure 1.10: Direct immune-modulatory effects of prebiotics ........................................ 61

Chapter 3

Figure 3.1: Inulin and scFOS reduce EHEC O157:H7-induced barrier disruption in

Caco-2Bbe1 monolayers. ............................................................................................. 78

Figure 3.2: Characterization of 2D-grown intestinal organoids. .................................... 80

Figure 3.3: Inulin and scFOS regulate TJ protein expression ....................................... 82

Figure 3.4: ScFOS alters host kinase activities across multiple immune regulatory

pathways ....................................................................................................................... 86

Figure 3.5: Inulin and scFOS induce activation of host PKC signaling in a time- and

dose-dependent manner ............................................................................................... 89

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Figure 3.6: Host signaling response to prebiotic inulin and scFOS ............................... 91

Figure 3.7: Inhibition of PKC phosphorylation abolishes prebiotic-mediated protection of

epithelial barrier function ............................................................................................... 94

Chapter 4

Figure 4.1: Kinome response of prebiotic-treated IECs to EHEC O157:H7 challenge. 115

Figure 4.2: Kinome differences between inulin and scFOS. ....................................... 117

Figure 4.3: Biological functions of prebiotic-induced kinome responses. .................... 121

Figure 4.4: Comparison of the effect inulin and scFOS have on canonical pathways. 124

Figure 4.5: Functional validation of NF-κB pathway in IECs. ...................................... 128

Figure 4.6: Functional validation of MAPK pathway in IECs. ...................................... 130

Figure 4.7: Effect of inulin and scFOS on LPS-induced murine endotoxemia. ............ 133

Figure 4.8: Effects of inulin and scFOS on colonic microbiota of LPS-treated mouse

pups. ........................................................................................................................... 137

Figure 4.9: Effects of inulin on colonic microbiota of LPS-treated mouse pups. ......... 139

Figure 4.10: Effects of scFOS on colonic microbiota of LPS-treated mouse pups. ..... 141

Figure 4.11: Effects of scFOS on colonic microbiota of LPS-treated mouse pups. ..... 143

Figure 4.12: Effects of inulin and scFOS on metagenome functional content of LPS-

treated mouse pups. ................................................................................................... 145

Chapter 5

Figure 5.1: The composition of HMOs in the pooled human milk. ............................... 168

Figure 5.2: HMO prevent the NEC in neonatal mice. .................................................. 170

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Figure 5.3: HMO increase cell proliferation and the number of muc-2 producing cells.

.................................................................................................................................... 173

Figure 5.4: HMO induce mucin production in LS174T and Caco-2Bbe1 cells. ........... 176

Figure 5.5: HMO protect Caco-2Bbe1 monolayers from EHEC-induced disruption. ... 179

Figure 5.6: HMO rescue Caco-2Bbe1 TJ-mediated barrier function. .......................... 181

Figure 5.7: HMO-mediated protection of the epithelial barrier is size and dose-

dependent. .................................................................................................................. 183

Figure 5.8: Inhibition of PDI prevents HMO-mediated protection of the intestinal

epithelial barrier. ......................................................................................................... 186

Figure 5.9: HMO increase the expression of PDI. ....................................................... 188

Figure 5.10: Inhibition of PDI abolishes the protective effect of HMO on NEC

development. .............................................................................................................. 191

Figure 5.11: Rutin on healthy mouse pups. ................................................................ 193

[xvi]

List of Tables

Table 1.1: Dysbiosis in human disease ........................................................................... 6

Table 1.2: Major bioactive components present in mature breast milk. ........................ 12

Table 1.3: List of current prebiotic candidates and their structures. .............................. 17

Table 1.4: TLR localization and ligands. ....................................................................... 46

Table 1.5: Innate immune cytokines and chemokines .................................................. 51

Table 1.6: TJs linked to hereditary diseases and infectious agents .............................. 55

Table 4.1: Quality statistics for metagenome functional content prediction from 16S

rDNA sequences using PICRUSt. ............................................................................... 147

[1]

Chapter

1 Introduction

This chapter was published, in part, as:

Abrahamsson TR, Wu RY, Sherman PM. Microbiota in functional gastrointestinal disorders

in infancy: implications for management. Nestlé Nutrition Institute Workshop Series, 2017;

88: 107-115.

Wu RY, Jeffrey M, Johnson-Henry KC, Green-Johnson J, Sherman PM. Impact of

Prebiotics, Probiotics and Gut Derived Metabolites on Host Immunity. LymphoSign Journal,

2016; 4(1): 1-24.

Johnson-Henry KC, Abrahamsson TR, Wu RY, Sherman PM. Probiotics, prebiotics, and

synbiotics for the prevention of necrotizing enterocolitis. Advances in Nutrition, 2016; 7(5):

928-937.

Wu RY, Sherman P. Host-intestinal microbe interactions in human health and disease.

University of Toronto Medical Journal. 2015; 92(3): 30-34.

Abrahamsson TR, Wu RY, Jenmalm MC. Gut microbiota and allergy: the importance of the

pregnancy period. Pediatric Research, 2015; 77(1-2): 214-219.

[2]

Foreword

The intestinal microbiota plays a crucial role in host well-being and disruption in the gut

microbiota (referred to as dysbiosis) is linked to a variety of human diseases. Therapeutic efforts

aimed at restoring microbial imbalances include the use of dietary prebiotics, which are non-

digestible food substances metabolized by specific members of the intestinal microbiota to alter

the composition and/or functions of the intestinal microbiome. Bacterial breakdown of prebiotics

is both glycan- and bacteria-dependent, and through this process, metabolites including short-

chain fatty acids are produced which can elicit numerous effects both locally and systemically.

Although it is traditionally believed that prebiotics benefit the host by manipulating the

microbiome and facilitating the production of short-chain fatty acids, more recent evidence

suggests that prebiotics may directly stimulate cytokine and chemokine production in the host

intestinal epithelia. However, the signaling mechanism of specific prebiotics on the host

intestinal epithelia has not been investigated and thus forms the subject of the studies presented

in this thesis. My overarching hypothesis is that prebiotics, besides altering bacterial functions,

directly trigger host cell signaling to provide intestinal homeostasis to regulate inflammation and

barrier protection. To approach this, this thesis will first introduce the prior studies and theories

that helped formulate my questions, and then detail my experiments, results and interpretations

in Sections 3-5.

[3]

1.1 Host-microbe interactions in health and disease

Historical context

During the 19th

century, when studying the anthrax epidemic, Louis Pasteur noted that the

growth of Bacillus anthracis was reduced by the presence of other microorganisms. He described

this phenomenon as “la lutte pour la vie” or “battle for life” (Sams et al., 2014). Pasteur predicted

that certain microbes are beneficial for health, and this was supported in 1907 when Eli

Mechnikov, a Nobel Prize laureate, made the seminal observation that peasants who regularly

consumed lactic acid-producing bacteria in fermented dairy products lived longer and healthier.

Mechnikov reasoned “the dependence of the intestinal microbes on the food makes it possible to

adopt measures to modify the flora in our bodies and to replace the harmful microbes with useful

microbes” (Wallace et al., 2011). This concept of balancing “harmful versus beneficial” or “good

versus bad” microorganisms forms the basis of the current understanding of host-microbe

interactions.

Human microbiota

Every one of us harbours a complex collection of microorganisms in our body referred to as the

microbiota. The most complex microbiota lies in the gastrointestinal (GI) tract, which consists of

over 1014

microbial cells (i.e. 1.3 times that of human somatic and germ cells) that collectively

express 150 times more genes than human cells combined (Ley et al., 2006). Although the

majority of studies have focused on the bacterial populations, the GI microbiota encompasses

other microbial domains including Archaea, viruses, fungi and protozoa (Lloyd-Price et al.,

2016). Methanobrevibacter smithii, for example, is an Archaea species documented in healthy

[4]

individuals that plays an important role in the carbohydrate metabolization of select bacterial

communities (Samuel et al., 2007).

The GI microbiota also harbours extensive populations of viruses, with more than 109

viral

particles recoverable per gram of human feces (Minot et al., 2013). Even though the majority of

these viruses are bacteriophages (viruses that infect and replicate within bacteria), virome

composition is highly unique amongst individuals (Virgin, 2014). Unlike viruses and Archaea,

protozoa and fungi are eukaryotic microorganisms that are also present in the GI microbiota. For

example, the fungus Saccharomyces boulardii is present in healthy individuals and may protect

against cholera infection (Hatoum et al., 2012). Despite the growing evidence for Archaea,

viruses, fungi and protozoa within the gut microbiota, knowledge surrounding their precise

composition and functionality remains limited.

The community most intensively characterized within the GI microbiota is the bacterial

population. To characterize diverse bacterial compositions, substantial efforts have been made to

catalogue the plethora of bacteria found in the GI tract. Previously, this was performed with

classic culture-dependent techniques using isolated bacterial strains. These traditional methods of

identification are now replaced by high-throughput 16S rRNA genome sequencing - a technique

that allows investigators to rapidly profile the microbiome in detail and overcome challenges

with culturing bacterial species. From this large collection of data, over 1,000 bacterial species

have now been identified (Rajilić-Stojanović and de Vos, 2014), at least 160 of which are readily

found among healthy individuals (Qin et al., 2010). It is also evident that the bacterial taxa

belong to the two predominant phyla: Bacteroidetes and Firmicutes (Huttenhower et al., 2012).

[5]

Dysbiosis in disease

Impairment in the microbial balance, or dysbiosis, can trigger disease pathogenesis through

changes in microbial diversity. For instance, the replacement of existing microbiota through co-

housing or transplantation from colitogenic donors (Blanton et al., 2016; Wlodarska et al., 2014)

causes colitis in otherwise healthy mice, indicating that exposure to pathogenic bacteria is

sufficient to initiate mucosal inflammation. On the other hand, germ-free animals devoid of

microbial communities develop poorly with severe disruption in the development of lymphoid

follicles, T-cell function and an increased susceptibility to infection (Olszak et al., 2012).

Therefore, the gut microbiota is important not only in the progression of disease, but is also

crucial for normal physiological development. Using next generation sequencing, a wide

spectrum of human disease has now been linked with intestinal dysbiosis (Table 1.1). However,

the next challenge is how to harness this wealth of information to improve human health using

microbial manipulations.

[6]

Table 1.1: Dysbiosis in human disease

Diseases Dysbiotic microbiota

Irritable bowel

syndrome

Increased Firmicutes (Ruminococcus, Clostridium and Dorea species)

Decreased Bifidobacterium and Faecalibacterium species

Colorectal

cancer

Increased Fusobacterium members

Altered Coprococcus, Eubacterium rectale, Roseburia and

Faecalibacterium prausnitzii

Obesity

Increased Lactobacillus species, Methanobrevibacter smithii,

Faecalibacterium prausnitzii

Decreased Bacteroides, Akkermansia mucinophila

Type 2 diabetes Increased Clostridium, Akkermansia mucinophila, Bacteroides and

Desulfovibrio

Ulcerative

colitis

Increased Proteobacteria, Fusobacteria and Spirochaetes

Decreased Firmicutes, Lentisphaerae and Verrucombicroa

Necrotizing

enterocolitis

Increased Proteobacteria, emergence of Cronobacter sakazakii and

enteropathogenic Escherichia coli

Cardiovascular

disease Increased Proteobacteria

Severe acute

malnutrition

Increased Proteobacteria (genera Klebsiella, Escherchia)

Decreased Bacteroidetes (genera Bifidobacteria)

*Table adapted from: Magno da Costa Maranduba C et al. Intestinal microbiota as modulators of the immune

system and neuroimmune system: impact on the host health and homeostasis. Journal of Immunology Research.

2015; 2015: 1-15.

[7]

1.2 Dietary impacts on microbiota

1.2.1 Infant microbiota

Studying how microbial communities are initially established in infants provides clues to the

factors that impact the microbiome. The newborn, believed to be largely sterile at birth,

immediately begins a chaotic progression towards acquiring a functional microbiota. Factors that

influence initial microbial colonization in the GI tract include mode of delivery (i.e. Caesarean

section versus vaginal birth) (Hansen et al., 2014), antibiotic use (Alm et al., 2008), maternal

microbiome (Matsumiya et al., 2002) and environmental exposures (Hanski et al., 2012) (Figure

1.1). For example, vaginally-delivered babies are predominantly colonized by vagina-residing

microbes including Lactobacillus and Prevotella, whereas Caesarean-delivered babies have more

potentially pathogenic skin-derived bacteria like staphlyococci and actinobacteria. In addition,

perinatal use of antibiotics has been shown to disrupt bacterial diversity in newborn babies

(Walker, 2010).

Dietary influences on the infant microbiome

Amongst the factors impacting gut microbiota, diet instills long-lasting impacts on the

microbiome (Albenberg and Wu, 2014). Studies characterizing the microbiome during the first 3

years of age reveal considerable differences in bacterial taxa that are specifically linked to infant

dietary intakes (Koenig et al., 2011). By 18 months of age, breastfed infants have almost double

the proportion of Bifidobacteria with more diverse Bifidobacterium species than formula-fed

infants (Roger et al., 2010). However, despite this direct correlation, recent studies revealed large

variations in Bifidobacteria of breastfed infants and in some locations, Bifidobacteria may

[8]

actually be completely absent in the infant stools (Lewis and Mills, 2017). This suggests that

while breastfeeding provides a propensity for microbial shifts, differences in non-diet factors

such as glycan composition, genetics, and rate of feeding may place selective pressure on the

intestinal colonization. For instance, babies of secretor mothers (those that express

fucosyltransferase 2) were shown to have greater relative abundance of Bifidobacteria than non-

secretor mothers (Lews et al., 2015), suggesting that maternal genetics may also significantly

influence the bifidogenic effects of breastfeeding. The dessimination of these environmental

effects across geography is an ongoing endeavor in the field of infant microbiome.

Breast milk as the gold standard

Exclusive breast milk feeding for the first 6 months of life is recognized as the gold standard for

infant feeding (Ballard and Morrow, 2013). This is because, in addition to being a complete

nutritional source supporting the infant growth, breast milk also contains a plethora of bioactive

components including proteins, enzymes, growth factors, immunoglobulins, and

oligosaccharides that each could protect the developing baby (Table 1.2). In addition, live

bacteria such as staphylococci, streptococci, bifidobacteria, and lactic acid-producing bacteria

are also identified in breast milk (Walker, 2010). Microbes from maternal skin can be routinely

inoculated into mammary ducts during breastfeeding. Alternatively, it has also been proposed

that milk microbes could originate from maternal gut via the entero-mammary pathway (Gomez-

Gallego et al., 2016). Currently, the origin of breast milk microbiota and its biological function

on the infant are both unclear (Fernández et al., 2013; Gomez-Gallego et al., 2016).

Unlike formula milk, which is commercially standardized to contain nutrient and micronutrient

contents within a small range, breast milk composition is dynamic with considerable

[9]

heterogeneity present both within mothers, as well as between mothers and populations (Walker,

2010). Colostrum, the breast milk produced during the first few days post-partum, is higher in

lipids (Khan et al., 2013), carbohydrates (Bode, 2012), growth factors, secretory IgA and

lactoferrin than mature milk 2-6 months post-partum (Ballard and Morrow, 2013).

There are substantial interpersonal variations in macronutrient compositions between mothers

due to blood type, secretor status, maternal weight, as well as environmental factors such as

nursing frequency and dietary intakes (Nommsen et al., 1991; Wacklin et al., 2011). Recently,

several groups have also identified inter-personal differences in genes expressed by cells present

in breast milk, which further highlights the high heterogeneity in milk contents (Twigger et al.,

2015).

[10]

Figure 1.1: Environmental factors affecting the development of gut microbiota.

At birth, the neonatal intestine is largely sterile, where factors including mode of delivery, diet

environment (i.e. maternal microbes, diet, and exposure to antibiotics) influence the progression

towards a diverse and stable adult gut microbiota.

[11]

[12]

Table 1.2: Major bioactive components present in mature breast milk.

Component Function

Macromolecules (g/dL)

Protein (1.2) Provision of nutrients and energy

Fat (3.2) Provision of nutrients and energy

Lactose (7.8)

Oligosaccharides (5-10)

Provision of nutrients and energy

Microbiota substrates, anti-adhesives, immune effects

Cells

Macrophages Protection against infections

Stem cells Regeneration

Immunoglobulins

IgA/sIgA Pathogen inhibition

IgG Anti-microbial, activates phagocytosis, anti-inflammatory

IgM Agglutination, complement activation

Cytokines & chemokines

IL-6 Acute phase response, B-cell activation, pro-inflammatory

IL-7 Increased thymic size and output

IL-8 (CXCL8) Recruitment of neutrophils, pro-inflammatory

IL-10 Repressing inflammation, antibody production, tolerance

IFNγ Pro-inflammatory, stimulates Th1 response

TGFβ Anti-inflammatory, stimulation of T cell, phenotype switch

TNFα Stimulates inflammatory immune activation

C-CSF Trophic factor

MIF Prevents macrophage movement, increase activity

Growth factors

EGF Stimulate proliferation and maturation

VEGF Promote angiogenesis and tissue repair

NGF Promote neuron growth and maturation

IGF Stimulate growth and development

Erythropoietin Erythropoesis, intestinal development

Lactoferrin Acute phase protein, chelates iron, anti-bacterial

*Table adapted from: Ballard O, Morron A. Human Milk Composition: Nutrients and Bioactive Factors. Pediatr

Clin North Am. 2013; 60(1): 49-74.

[13]

1.2.2 Adult microbiota

Diet alters the gut microbiome

With weaning and the introduction of solid foods (~4-6 months of age is the current norm for

breastfed infants in North America), the infant microbiota eventually transitions to an adult

composition by 2-3 years of age with increased abundance of Bacteroides, streptococci and

clostridia (Palmer et al., 2007). Unlike infants, the individual gut microbiota of adults is largely

stable (Faith et al., 2013), and this long-term composition is classified into several broad

“enterotypes” that are intimately associated with food consumption (Wu et al., 2011). For

instance, children from Burkina Faso, whose diets consist mainly of carbohydrates, fiber and

non-animal proteins, have higher Prevotella and lower Bacteroides compared to children living

in Europe who consume a Western diet consisting of high animal protein, fats, sugar and low

fiber content (De Filippo et al., 2010). Similar fluctuations in the microbiota can also be

triggered by short-term dietary changes, such as the extreme deprivation of carbohydrates (David

et al., 2014). Besides altering microbial abundance, dietary exposures also influence bacterial

function. For example, in a comparison between healthy human vegans and omnivores, diet had

a surprisingly small impact on microbial composition. Nevertheless, the production of bacterial

metabolites was divergent between the two groups (Wu et al. 2016), indicating that dietary

factors not only regulate the growth of select microbial communities, but can also alter bacterial

gene expression.

[14]

Diet-induced dysbiosis influences health and disease

The diet-microbiota relationship is closely connected with human disease. The contrast that

exists in the microbiome between Agrarian and Western diets is mirrored by the varying

incidence of chronic diseases amongst the two populations. The microbiome associated with the

Western diet is correlated with higher rates of obesity and chronic inflammatory diseases.

Conversely, diets high in vegetables and fibers are linked with lower levels of disease states and

frailty (Wu et al., 2011). For example, obese individuals have decreased bacterial diversity and

altered levels of Firmicutes and Bacteroidetes compared to lean counterparts (Turnbaugh et al.,

2008, 2009). In fact, transferring the gut microbiota of obese humans to germ-free mice can

induce higher energy balance and fat accumulation despite constant food intake (Turnbaugh et

al., 2006), thereby suggesting that obesity is associated with an “obesogenic” microbiota.

However, due to differences in technique and study design, the specific microbial changes in

obesity have not always been replicated (Sze and Schloss, 2016). Therefore, the link between

obesity and microbiome remains an active area of ongoing investigation.

Dysbiotic disease mechanisms

These diet-driven chronic diseases are likely due to the functional activity of microbiome-

derived metabolites. For instance, the high consumption of lipids and red meats increases the

levels of choline and L-carnitine, respectively. Both are microbial substrates that are readily

metabolized by the intestinal microbiota to form the atherosclerosis-promoting molecule

trimethylamine oxide (TMAO) (Koeth et al., 2013; Wang et al., 2011). This is also supported by

studies showing that meat-eaters produce higher levels of TMAO after L-carnitine consumption

due to the different composition of the gut microbiota (Koeth et al., 2013). Therefore,

[15]

modulation of diet plays a role in the maintenance of well-being by modulating the composition

and the function of the host gut microbiota.

[16]

1.3 Prebiotics as microbiota-targeted therapeutics

Prebiotic definition

The relationship between diet, microbial communities and human health and disease has

generated tremendous interest in microbiota-targeted strategies to improve human health

(Bindels et al., 2015; Jain and Walker, 2014). Amongst these proposed strategies is the idea of

dietary prebiotics initially described by Gibson and Roberfroid (Gibson and Roberfroid, 1995).

Prebiotics are defined as “non-digestible food ingredients that resist intestinal digestion and

absorption, and through their use as substrate by the gut microbiota, modulate the composition

and activity of gut microbiota, thus conferring a benefit on the host” (Bindels et al., 2015).

Sources of prebiotics

Common examples of prebiotic compounds are plant-derived fructans, such as inulin and

fructooligosaccharides (FOS), commercially-derived galactooligosaccharides (GOS) and human

milk oligosaccharides (HMOs). Inulin and FOS/oligofructose are energy-storage carbohydrate

polymers commonly found in plants and vegetables, including asparagus, leafy green vegetables,

garlic, leek and onions, with the highest abundance in chicory root (Cichorium intybus). On the

other hand, GOS are linear galactose chains commercially synthesized by the enzymatic trans-

galactosylation and hydrolysis of lactose sugars (Bindels et al., 2015). HMOs can be extracted

from human breast milk through the serial removal of macronutrients (i.e. fats and proteins).

Besides these 3 main categories, numerous alternative candidates for prebiotics have been

introduced with ongoing research underway (Table 1.3). However, such candidates are not the

core focus of the current thesis.

[17]

Table 1.3: List of current prebiotic candidates and their structures.

Prebiotic Linkages Monosaccharides

Inulin β-(2,1) Fructose

Glucose

Fructooligosaccharides β-(2,1) Fructose

Glucose

Galactooligosaccharides β-(1,4) Galactose

Glucose

Human milk

oligosaccharides

β-(1,3)

β-(1,6)

α-(1,2)

α-(1,3)

α-(1,4)

α-(2,3)

α-(2,6)

Glucose

Fructose

Galactose

Sialic acid

N-acetylglucosamine

Resistant starch* α-(1,4)

α-(1,6) Glucose

Pectin* α-(1,4)

D-galacturonic acid

Galactose

Aplose

Keto-deoxyoctulosonic acid

Hydroxycinnamic acid

Rhamnose

Arabinose

Fucose

Arabinoxylan* β-(1,4) Xylopyranose

*Indicates candidate prebiotics that are currently under evaluation.

[18]

Prebiotics versus dietary fibers

The non-digestible aspect of prebiotics overlaps with the concept of dietary fiber. Dietary fibers,

such as non-digestible starch, are the complex carbohydrates that form part of the plant cell wall

that resists hydrolysis and digestion and therefore, can travel the GI tract undigested (DeVries,

2003). Dietary fibers are classified into soluble and insoluble fiber based on their physical

properties. Soluble fibers (i.e. pectins, gums and FOS) dissolve in water and are fermented by

colonic microbiota, whereas insoluble fibers (i.e. lignins and cellulose) do not solubilize in

water, have limited fermentation capacities and mainly serve as a colonic bulking agent (Wong

and Jenkins, 2007). Although most prebiotic compounds can be classified as soluble dietary

fibers, not all dietary fibers are considered prebiotic agents.

Structure of Prebiotics

The structures of prebiotics vary depending on the sources. Inulin and FOS are comprised of

repeating monomers of fructose connected to a terminal glucose via β-(2,1) glycosidic linkages

(Vogt et al., 2015). Inulin and FOS differ in length, with a degree of polymerization of more than

and less than 10 for inulin and FOS, respectively. Short-chain FOS or scFOS have a chain length

of 2-5. GOS are galactose polymers that are structurally linked by β-(1,4) glyosidic linkages. By

contrast, HMOs are heavily branched oligosaccharides that contain up to five sugars: glucose

(Glc), galactose (Gal), fucose (Fuc), sialic acid (Sia) and N-acetyl-glucosamine (GlcNac) (Bode,

2012). HMO side chains are built on lactose at the reducing end and elongated by the addition of

lacto-N-biose or N-acetyllactosamine in β-(1,3) or β-(1,6) linkages. Elongated side chains then

terminate with sialic acid and fucose moieties: Fuc in α-(1,2), α-(1,3) or α-(1,4) linkages, and Sia

residues in α-(2,3) or α-(2,6) linkages.

[19]

Figure 1.2: Structures of the three main categories of prebiotics

FOS and GOS are linear non-branching polymers of fructose and galactose sugar units organized

in β-(2,1) and β-(1,4) glycosidic linkages with a glucose terminal end. HMOs are

oligosaccharides that are made up of five different sugar units. Figure adapted from Bode et al.,

2016.

[20]

[21]

1.4 Prebiotic metabolites

1.4.1 Prebiotic utilization

Due to the complexity of prebiotic structures, the breakdown of prebiotic requires a cadre of

degradation enzymes to hydrolyze glycosidic linkages. Given that humans express only a few of

these enzymes, most of the prebiotic consumed travels along the GI tract undigested to reach the

colon intact. In fact, with the exception of starch, lactose and sucrose, the majority of

polysaccharides ingested are metabolized by colonic microbes whose genomes encode the

required glycoside hydrolases, polysaccharide lyases and carbohydrate esterases (Flint et al.,

2012; Sela et al., 2008). These enzymes are responsible for the bacterial sensing, importing and

degradation of oligosaccharide structures (Comstock, 2009).

One of the best described examples of oligosaccharide utilization is the polysaccharide

degradation process employed by Bacteroides species. Bacteroides members such as B.

thetaiotamicron express a large collection of oligosaccharide degrading enzymes. For instance,

in order to breakdown the α-(1,4) and α-(1,6) glycosidic linkages in resistant starch, a dietary

fiber that is currently evaluated as a potential prebiotic, B. thetaiotamicron employs a 4-enzyme

starch utilization system (Sus) as shown in Figure 1.3. Not surprisingly, as the number of unique

polysaccharide linkages increases, the more enzymes will be required in its degradation. Xylan,

which has a total of 11 unique linkages, requires approximately 21 bacterial enzymes for

degradation in a Sus-like system (Koropatkin et al., 2012). The concerted activities of Sus

enzymes in Bacteroides provide the current paradigm of prebiotic degradation.

[22]

1.4.2 Polysaccharide utilization loci

The entire repertoire of degradation enzymes is expressed within bacterial gene clusters known

as polysaccharide utilization loci (PUL). Although many PUL are common between bacterial

species, many PUL are highly specific and render select species as primary metabolizers. For

example, when closely related members from the genus Bacteroides are grown on a prebiotic

inulin agar base, most members were excellent inulin metabolizers and increased bacterial

growth with the exception of Bacteroidales vulgatus, which is an inulin “non-metabolizer”

(Rakoff-Nahoum et al., 2014). Interestingly, when the agar substrate is switched from inulin to

xylan, the inulin metabolizer B. thetaiotamicron failed to grow while inulin non-metabolizers

like B. vulgatus demonstrated enhanced proliferation (Rakoff-Nahoum et al., 2014). This

difference in response is due to differences in the expression of glycan degradation enzymes. For

instance, B. thetaiotamicron is an excellent metabolizer of β-(2,6)-fructans because it specifically

encodes the β-(2,6) endo-fructanase BT1760 (Sonnenburg et al., 2010). Therefore, these

experiments show that bacterial fermentation of prebiotics is dependent on both the bacterial

species as well as the type of prebiotic the microorganism is exposed to. Consequently,

microbiota changes introduced by prebiotics are both substrate- and microbiota-specific.

[23]

Figure 1.3: Starch utilization system employed by B. thetaiotathemicron

Non-digestible starches are bound to bacterial membranes by the starch utilization system (Sus)

E and F proteins, and starch fragments are imported within bacteria by SusC. Enzymatic

breakdown is carried out by SusA and SusB glycoside hydrolases (GH). Figure adapted from

Koropatkin et al., 2012.

[24]

[25]

1.4.3 Microbiome population shifts

The substrate- and species-specific nature of prebiotic utilization establishes ecological niches

that can have a profound impact on the gut microbiome. One such impact is Bifidogenesis, or the

expansion of Bifidobacterium, a genus of Gram-positive saccharolytic bacteria containing

numerous members with reported health effects in the host. Although the characterization of

Bifidobacterium polysaccharide utilization enzymes is not fully revealed, in vitro fermentation

studies have identified the involvement of selective transporters (i.e. ABC transporters) and

several degradation enzymes (i.e. β-(2-1)-galactosidases, α-sialidase and α-fucosidases). A well-

documented example is B. longum subsp. infantis, which expresses numerous enzymes that

together break down the plethora of prebiotic structures. B. infantis expresses β-

fructofuranosidases for the digestion of inulin and FOS and lacS carriers and β-galactosidases for

GOS. To tackle the complexity of HMO structures, the microorganism also expresses various

glycosidases (i.e. α-sialidases and α-fucosidases) (Sela et al., 2008), specific binding proteins

(BPs), as well as ABC transporters for the breakdown of HMOs (Smilowitz et al., 2014).

Bifidogenic effects in humans

The bifidogenic effect of prebiotics is well-supported by human studies. Infants receiving daily

formula containing a 1.25 to 4 g mixture of inulin and FOS have a higher abundance of

bifidobacteria in stools (Boehm, 2002; Boehm and Moro, 2008; Gonzalez et al., 2008). The

youngest segment of the population tested were babies at 6 days of age, who showed a

significant increase in both lactobacilli and bifidobacteria when taking a mixture of GOS/FOS at

8 g/L for 28 days (Moro et al., 2002). The same GOS/FOS mixture induces a microbial

composition that closely resembles the Lactobacillus and Bifidobacterium populations of

[26]

breastfed infants (Haarman and Knol, 2006; Knol et al., 2005). Similar findings are seen in

healthy adults where inulin at doses from 5-34 g/day or FOS at a range of 5-20 g/day

consistently demonstrate bifidogenic shifts in the colonic microbiota (Meyer and Stasse-

Wolthuis, 2009).

Structure-specific effects on the gut microbiome

Although the consumption of prebiotics induces bifidogenic effects in most cases, the extent of

expansion varies between prebiotics – a finding similar to the in vitro setting. FOS is a preferable

fermentation substrate, whereas inulin and maltodextrin are relatively poor for Bifidobacterium

metabolization. Even at a high dose of 10 g/day, a few studies found that long-chain inulin could

not produce Bifidogenic effects in the gut microbiome (Bouhnik et al., 2004). This structure-

specific manipulation of the intestinal microbiota also applies to bacterial function. As

demonstrated in the context of severe acute malnutrition, mothers whose children exhibit

stunting have lower levels of sialyated HMOs. When both sialyated and non-sialyated prebiotics

were fed to the malnourished mice, although there were no large differences in the bacterial

communities, numerous bacterial strains responded transcriptionally by regulating genes

involved in metabolism (Charbonneau et al. 2016). Interestingly, such changes were marked by

improvements in host lean-body mass and bone growth in HMO-fed animals, but not in animals

receiving either inulin or FOS. Similarly, sialyated HMOs, but not GOS, protect against

intestinal pathology in a neonatal rat model of NEC (Autran et al. 2016). Given that more than

200 unique HMO structures are present (Bode, 2012), further characterization of the structure-

specific functions of these HMOs is warranted.

[27]

1.5 Prebiotic-derived metabolites: short-chain fatty acids

The bifidogenic effects of prebiotics are associated with numerous health benefits, which are

believed to be partly mediated by the metabolites produced during prebiotic fermentation such as

short-chain fatty acids (SCFAs) (Vogt et al., 2015). Structurally, SCFAs are 1-6 carbons in

length (Figure 1.4), with the majority (>95%) of SCFAs being butyrate (4 carbons), propionate

(3 carbons) and acetate (2 carbons) at a ratio of 1:1:3 in the colon (Brestoff and Artis, 2013;

Macfarlane and Macfarlane, 2003). The levels of SCFAs fluctuate depending on the composition

of the resident gut microbiota as well as the prebiotic metabolized. For instance, many

Bacteroides members generate predominantly butyrate along with hydrogen and carbon dioxide

gases, whereas for some of the Bifidobacterial members, the main metabolites produced are

lactate and acetate (Pokusaeva et al., 2011). In addition, while xylan breakdown generates mostly

acetate, the majority of SCFAs produced in inulin breakdown is butyrate. Germ-free animals

devoid of a functional metabolizing microbiota are completely deficient in intestinal SCFAs

(Maslowski et al., 2009).

Levels of SCFAs have important implications on host health through impacts on host immunity

and energy metabolism, which are not only demonstrated in local tissues, but also systemically

(Arpaia et al., 2013; Brestoff and Artis, 2013). Animals low in SCFAs, such as germ-free mice

or mice deprived of fiber intake, have defective immune responses and mount more severe

inflammation in response to dextran sodium sulfate- (DSS) or Citrobacter rodentium-induced

colitis (Kim et al., 2013; Maslowski et al., 2009). Despite the numerous supports for their

benefits, it was recently shown that butyrate may also generate deleterious effects on crypt cell

homeostasis and inhibit wound healing (Kaiko et al., 2016).

[28]

One potential mechanism for how SCFAs regulate immunity is the binding of host cell receptors

GPR-41 (G-coupled Protein Receptor 41) and GPR-43 – a small family of G protein coupled

receptors expressed by various cell types including colonocytes, monocytes, neutrophils and

macrophages (Le Poul et al., 2003). SCFAs directly activate GPR-41 and -43, which result in the

decreased expression of pro-inflammatory cytokines and increased expression of the anti-

inflammatory cytokines IL-10 and IL-23 in dendritic cells (Liu et al., 2012). Grp43-/-

mice

develop severe DSS colitis despite normalized tissue levels of SCFAs (Maslowski et al., 2009).

Similarly, one recent study using a mouse model of peanut allergy described a GRP-43-mediated

mechanism of SCFAs-induced induction of oral tolerance, whereby SCFAs activation of GRP-43

enhanced retinaldehyde dehydrogenase (RALDH) activity in tolerogenic CD103+ dendritic cells

(DC) and stimulated Treg production (Tan et al., 2016).

The majority of intestinal SCFAs (>90%) are readily absorbed by colonocytes and used as an

energy source. However, a small portion of SCFAs is taken up into systemic circulation via the

superior and inferior mesenteric veins to mediate effects on distant organs (Brestoff and Artis,

2013). Both GRP-41 and -43 receptors are expressed in the liver, adipose tissues and skeletal

muscle (Canfora et al., 2015). In fact, several mouse studies demonstrate that SCFAs enhance

weight loss and reduce adiposity (Frost et al., 2014; Gao et al., 2009). These effects are likely to

be multifactorial in nature, since numerous reports have documented SCFAs-mediated effects on

satiety, energy expenditure, adiposity and liver function. For instance, in both humans and

rodents, SCFAs exposure stimulates the release of glucagon-like peptide-1 (GLP-1) – a gut

hormone produced by enteroendocrine L-cells that is involved in satiety (Tolhurst et al., 2012).

Oral feeding of butyrate in obese mice also accelerates fat loss via increased energy expenditure

and fat oxidation in skeletal muscles due to the higher abundance of type 1 muscle fibers (Gao et

[29]

al., 2009). Likewise, ex vivo studies using human adipose tissues also demonstrate higher

expression of lipoprotein lypases (LPL) and enhanced glycerol release with SCFAs exposure –

indicating reduced adiposity via lipolysis (Canfora et al., 2015). Whether these mechanisms are

potential ways to combat human obesity warrants further investigation.

[30]

Figure 1.4: Local and systemic impacts of bacterial-derived metabolites SCFAs.

Main intestinal SCFAs (acetate, propionate and butyrate) directly bind GPR-41/43 receptors on

colonocytes and immune cells to affect immune function. SCFAs are also taken up into the

systemic circulation via superior and inferior mesenteric veins to elicit distant effects on liver,

muscle and adipose tissues.

[31]

[32]

1.6 Direct innate immune response to prebiotics

Although health benefits related to prebiotic consumption have been largely attributed to the

bifidogenic effects and induction of SCFAs (Vogt et al., 2015), a recent concept is that prebiotic

oligosaccharides may also elicit direct effects via contact with host intestinal tissues (Roberfroid

et al., 2010). In other words, prebiotics could elicit direct effects in the GI tract independent of

microbial fermentation.

The component of the host immune system responsible for initial recognition of foreign

substances is the innate immune system (Takeuchi and Akira, 2010). As an early response to

noxious stimuli, the innate immune system incorporates several mechanisms to provide a first

line of defense, discrimination between self- versus non-self and an ability to mount appropriate

immune responses through the induction of both cytokines and chemokines. In Section 1.6, I

will discuss the innate immune mechanisms within the GI tract specifically relevant to the

breadth of this thesis. In Section 1.7, I will consider how prebiotics have the potential to directly

regulate these immune mechanisms.

[33]

1.6.1 Intestinal epithelial barrier

The first line of the innate immune system is the anatomical and chemical barrier that separates

the host from luminal foreign substances. This includes anatomical barriers such as the skin, as

well as a chemical barrier including secreted molecules such as lysozyme and antimicrobial

peptides. The following sections will discuss individual components of the intestinal epithelial

barrier.

Intestinal cell lineages

Within the GI tract, the first line of defense against antigens present in luminal contents is the

intestinal barrier, made up of a single layer of polarized epithelial cells organized spatially into

intestinal crypts and villi. Besides providing a physical separation, the intestinal barrier facilitates

nutrient digestion and absorption and mounts innate immune responses to various insults present

in the lumen of the GI tract (Kagnoff, 2014). To perform these diverse functions, the intestinal

barrier contains several specialized cell lineages that are spatially distributed. The four main cell

types include enterocytes, enteroendocrine cells, goblet cells (GCs) and Paneth cells (PCs)

(Figure 1.5).

Enterocytes are polarized epithelial cells found in the intestinal barrier and are specialized in

nutrient absorption via fluid-phase endocytosis. Enteroendocrine cells release peptide hormones

that regulate GI functions such as food consumption and motility and enable the GI tract to

improve bacterial clearance. The intestinal epithelium also contains specialized secretory PCs

and GCs, situated within the crypts and villi, respectively. Both cell types secrete soluble factors

to either destroy or reduce the ability of enteric pathogens to adhere to the surface of the

intestinal epithelium (Kagnoff, 2014).

[34]

PCs secrete antimicrobial peptides (AMPs) including defensins, cathelicidins, and C-type lectins

into crypts which disrupt bacterial membranes to destroy pathogens (Peterson and Artis, 2014).

GCs cells secrete abundant amounts of mucins, which are large, O-glycosylated glycoproteins

that coat the entire mucosal surface to entrap luminal microbes and prevent bacterial attachment

to the apical surface of intestinal epithelial cells (IECs) (Johansson and Hansson, 2016). Mice

deficient in Muc2, the main isotype of mucin secreted in the GI tract, develop spontaneous colitis

and are more susceptible to colorectal cancers (Van der Sluis et al., 2006).

Each of the specialized cell types in the gut undergoes continuous turnover and is replenished by

the intestinal epithelial stem cells (IESCs) located at the base of the crypt, which generate a

steady supply of committed cell-specific progenitors. Collectively, this forms a dynamic mucosal

barrier that continuously self-regenerates to cover approximately 400 m2

of surface area.

[35]

Figure 1.5: The cell morphology of small intestine villus-crypt unit.

The intestinal epithelium is comprised of diverse cell types, including: enterocytes, goblet cells

(GC), Paneth cells (PC), enteroendocrine cells, and intestinal epithelial stem cells (IESC)

organized into crypts and villus. DC denotes dendritic cells.

[36]

[37]

Structural integrity of the villus-crypt unit

The individual cells types in the GI tract are anchored together seamlessly into a single-layered

sheet of epithelium. The key to maintaining this continuous structure is the intercalating network

of intercellular TJ proteins that seal the intestinal lining. The primary role of the TJs is to

function as a diffusion barrier to control the paracellular passage of molecules and ions (Peterson

and Artis, 2014). TJs also create a molecular fence that juxtaposes the neighbouring membranes

to prevent lateral diffusion of membrane components into adjacent cells. This creates cell

polarity, which allows subcellular organelles to organize into apical and basolateral

compartments. Furthermore, TJ structures facilitate host cell signaling by engaging with adaptor

and signaling proteins to affect cellular responses to various external stimuli.

Studies using electron microscopy revealed TJ complexes as a collection of transmembrane

strands anchored to plaque proteins and the cytoskeleton of adjacent cells (Zihni et al., 2016).

The main types of transmembrane proteins observed are the tetraspanning claudin and occludin

family of proteins (Figure 1.6).

Claudins

The claudin family consists of 26 members that range in molecular size between 20-34

kilodaltons (kDa) and in number of amino acids between 207 and 305. Claudins are spatially

located in the intercellular space between adjacent cells and are structurally composed of

intracellular N-terminal and C-terminal domains and two extracellular loop domains that thread

back-and-forth across the membrane to form four transmembrane domains. Claudins of adjacent

cells are thought to dimerize via the edges of the extracellular domains (Zihni et al., 2016). In

Latin, “claudin” refers to “to close”, but considerable work reveals that claudins act as both para-

[38]

cellular barriers (“barrier claudins”) and para-cellular pores (“leaky claudins”), and are the main

determinants of epithelial permeability (Gunzel and Yu, 2013). A total of 19 claudin members

are expressed throughout the GI tract in both humans and mice, but with considerable

heterogeneity with respect to their ion permeability. For instance, claudin-2 is permissive to

cations and considered a pore-forming claudin (Amasheh et al., 2002), whereas claudin-17 is an

anion pore, and referred as a pore-closing claudin (Krug et al., 2012). The relative distribution

and expression of individual claudins together regulates the electrical conductance of the cell

monolayer, which can be readily measured in filter-grown polarized epithelial cell monolayers

using chopstick voltage electrodes.

Occludins

The second main class of transmembrane proteins are occludins, which are tetraspanning

proteins approximately 65 kDa in size and containing 522 amino acids (Cummins, 2012). Like

claudins, occludins have intracellular N- and C-terminal domains, four transmembrane domains,

and two overhanging extracellular loop domains that reside in the intercellular spaces (Figure

1.6) (Feldman et al., 2005). In Latin, “occludin” refers “to occlude”, but its role in barrier

function is much more complex than barrier sealing. Madin-Darby canine kidney (MDCK) cells

overexpressing occludin have higher trans-epithelial electrical resistance, but also exhibit higher

paracellular fluxes (Feldman et al., 2005; McCarthy et al., 1996). On the other hand, knockdown

of occludin expression in MDCK cells does not affect the TJ ultrastructure of cell monolayers at

steady state (Yu, 2005). However, these cells have lower protein levels of TJ claudin-1 and -7

and a reduced transepithelial electrical resistance (TER), indicating that occludins mediate the

expressions and assembly of other TJ proteins.

[39]

Similarly, although occludin-knockout mice are completely viable and exhibit intact expression

of TJ proteins in the gut, the animals display severe pathologies including infertility,

inflammation, growth retardation, infertility, and exhibit TJ disruptions in other epithelial tissues

(Saitou et al., 2000). These results suggest that the core function of occludin is likely involved in

the host stability of TJ complexes.

Junctional plaque proteins

To provide cytosolic anchorage, the C-terminal domains of claudins and occludins are tethered to

a family of intracellular scaffolding proteins (Zihni et al., 2016). One predominant example is the

zonula occludens family which contains three known members that are 220 kDa in size with

1,748 amino acids: ZO-1, ZO-2 and ZO-3 (Dörfel and Huber, 2012). Structurally, ZO proteins

consist of an N-terminal PDZ domain, a Src-homology 3 (SH3) domain and a guanylate kinase

(GUK) domain. The N-terminus domain provides three binding sites for the various

transmembrane TJ proteins: PDZ1 bound by claudins, PDZ2 bound by ZO-2 and ZO-3, PDZ3

bound by junctional adhesion molecules (JAMs) and GUK domain bound by occludins (Figure

1.7). The C-terminus domain is bound to the actin cytoskeleton inside of the epithelial cell.

There is substantial evidence that both the expression and localization of ZO proteins are critical

to cell viability and epithelial barrier function (Dörfel and Huber, 2012). Knockout animals of

ZO-1 and ZO-2 are embryonically lethal (Katsuno et al., 2008). MDCK cells under ZO-1

knockout or RNA interference have altered intercellular junctions and disruptions in TJ protein

localization (Tokuda et al., 2014; Van Itallie et al., 2009). Moreover, changes in ZO-1

localization also affect the barrier integrity of epithelial monolayers. Studies by Cario and

colleagues (2004) demonstrated that apical delocalization of ZO-1 produces a barrier-sealing

[40]

effect and is correlated with a higher TER value in monolayers. Apart from maintaining an

epithelial barrier, ZO proteins are also bound by kinases and phosphatases that can alter the

phosphorylation status of various TJ proteins to regulate functional activities.

TJ-mediated cell signaling

In addition to the role of TJs in maintaining the physical barrier as a structural complex, TJ also

engage in extensive cross-talk with a vast number of second messengers (Zihni et al., 2016).

These interactions are imparted via direct intracellular signaling pathways given that numerous

TJ proteins are bound or can readily recruit signaling mediators including kinases, phosphatases,

GTP-binding proteins and transcription regulators. One example that illustrates TJ signaling is

the mechanism by which TJs directly alter cytoskeleton architecture: loss of ZO-1 induces the

formation of actin stress fibers (Terry et al., 2011). One proposed mechanism is that ZO-1

recruits the junction-regulating proteins JACOP and p114RhoGEF, whose concerted activity

triggers a RhoA-ROCK2 signaling pathway that modulates cell tension (Tornavaca et al., 2015).

Similarly, ZO-1 also facilitates the recruitment of cell division control protein 42 (CDC42) to

trigger formation of the actin cytoskeleton (Oda et al., 2014) as well as inducing cellular

differentiation (Zihni et al., 2016).

[41]

Figure 1.6: Intestinal TJ complexes

The intestinal epithelium is held together by intercellular TJ that consist of transmembrane

glycoproteins (claudins and occludins) tethered onto cytosolic plaque proteins (ZOs). Figure

adapted from Zihni et al., 2016.

[42]

[43]

Figure 1.7: Zonula occludens binding domains

Zonula occludens acts as a scaffolding protein to provide anchorage for other TJ proteins

including claudins (PDZ-1), ZOs (PDZ2), JAMs (PDZ3), Occludins (GUK domain) and C

terminal domains attached to actin cytoskeleton. Figure adapted from Thevenin et al., 2013.

[44]

[45]

1.6.2 Pattern recognition receptors

In addition to imposing a physical barrier, the intestinal epithelium fulfills an important role in

the host immune response by discriminating self versus non-self within luminal contents. To do

this, IECs express pattern recognition receptors that recognize pathogen-associated and damage-

associated molecular patterns. The four families of pattern recognition receptors include the

transmembrane proteins Toll-like receptors (TLRs) and C-type lectin receptors, as well as the

cytosolic proteins retinoic acid-inducible gene-I-like receptors and NOD-like receptors. My PhD

thesis focuses on the regulation of TLRs by prebiotics using complementary in vitro and in vivo

models of intestinal injury, and therefore will be discussed further.

Toll-like receptors

TLRs are the best-characterized pattern recognition receptors, and are expressed not only in

immune cells, such as macrophages and dendritic cells, but are also present in other cell types

including epithelial cells, goblet cells and Paneth cells (Barton and Kagan, 2009). The structure

of TLRs consists of an N-terminal ligand domain, a transmembrane domain and a C-terminal

cytoplasmic Toll/IL-1R (TIR) domain for signal transduction (Botos et al., 2011). So far, there

are 10 known TLRs in humans and 12 in mice, each of which is involved in the recognition of

different sets of ligands (Table 1.4). During binding, a ligand links the extracellular domains to

form an M shape allowing for the dimerization of the two intracellular TIR domains of the TLRs.

This re-arrangement initiates downstream signaling to recruit adapter proteins, such as myeloid

differentiation factor 88 (MyD88) and TIR-domain-containing adapter-inducing interferon-β

(TRIF) (Manavalan et al., 2011).

[46]

Table 1.4: TLR localization and ligands.

TLR Localization Ligand Origin of ligands

TLR1 Plasma

membrane Triacyl lipoprotein Bacteria

TLR2 Plasma

membrane Lipoprotein

Bacteria, viruses, parasites,

host

TLR3 Endolysosome dsRNA Viruses

TLR4 Plasma

membrane LPS Bacteria, viruses, host

TLR5 Plasma

membrane Flagellin Bacteria

TLR6 Plasma

membrane Diacyl lipoprotein Bacteria, viruses

TLR7 (human

TLR8) Endolysosome ssRNA Virsues, bacteria, host

TLR9 Endolysosome CpG-DNA Viruses, bacteria, protozoa,

self

TLR10 Endolysosome Unknown Unknown

TLR11 Plasma

membrane

Profilin-like

molecule Protozoa

*Table adapted from: Takeuchi O, Akira S. Pattern recognition receptors and inflammation. Cell. 2010; 140(6): 805-

820.

[47]

MyD88-dependent pathway

Following dimerization of TIR-TIR domains, one of the first adaptor proteins recruited to the

TIR domain, with the exception of TLR3, is MyD88 (Akira and Takeda, 2004). In the inactive

state, MyD88 is localized in the cytosol in a repressed state (Figure 1.8). Once active, MyD88

forms a complex with IL-1 receptor associated kinase family members (IRAK) through death

domain interactions. This binding phosphorylates IRAK-4 and the subsequent phosphorylation

of IRAK-1, which leads to the dissociation from MyD88 and association with TNF receptor

associated factor-6 (TRAF-6) (Gay et al., 2014). Next, the IRAK-1-TRAF-6 complex interacts

with the TAK1 protein complex (consisting of TAB1, TAB2 or TAB3), which activates the IκB

kinase (Iκκ) complex. The Iκκ complex is the central regulator of the NF-κB inflammation

cascade: its activation leads to downstream phosphorylation of NF-κB and the mitogen-activated

protein kinases (MAPKs) JNK and p38 (Akira and Takeda, 2004).

MyD88-independent pathway

In the Myd88-independent pathway, otherwise known as the TRIF-dependent pathway, the

adaptor protein recruited following TIR dimerization is the TIR-domain-containing adaptor

protein TRIF (Figure 1.8) (Akira and Takeda, 2004). TRIF recruits the Iκκ-TBK1 complex to

initiate the activation of interferon-regulatory factor 3 (IRF-3). IRFs are transcription factors

expressed within the cytosol. Once activated, IRF-3 translocates to the nucleus and recruits the

transcriptional co-activators p300 and Creb-binding protein (CBP) to mediate gene regulation

(Kawasaki and Kawai, 2014).

[48]

Figure 1.8: MyD88-dependent and MyD88-independent pathways of TLR pathways

Within the MyD88-dependent pathway, MyD88 facilitates the activation of the IRAK-TRAF6

complex and subsequent activation of the Iκκ complex. In the MyD88-independent pathway, the

adaptor protein TRIF facilitates the recruitment of signaling mediators. Figure adapted from

Akira and Takeda, 2004; Takeuchi and Akira, 2010.

[49]

[50]

Inflammatory responses

The activation of NF-κB and IRF-3 initiate pro-inflammatory responses by upregulating genes

that encode pro-inflammatory cytokines, chemokines, type 1 interferons, antimicrobial proteins

and other inflammatory mediators, some of which are listed in Table 1.5 along with their effects

on the host (Takeuchi and Akira, 2010).

Cytokines and chemokines

Cytokines are secreted extracellular proteins that trigger local inflammation by promoting

vascular permeability, recruiting immune cells, inducing acute-phase response proteins and

regulating cell death in inflamed tissues (Takeuchi and Akira, 2010). Within the plethora of

cytokines expressed are a small group of molecules known as chemokines, which are specialized

chemo-attractant cytokines that facilitate the recruitment of immune cells. Common examples of

cytokines include TNF-α and the interleukin-1 (IL-1) superfamily of cytokines such as IL-1α, IL-

1β and IL-18 (Sims and Smith, 2010), while examples of chemokines includes the C-X-C

chemokine ligand family such as CXCL8 (IL-8) in humans (MIP-2 in mice), and the C-C

chemokine ligand (CCL) family such as CCL2, CCL5 and CCL8. Cytokines and chemokines can

be secreted by a number of non-professional immune cells such as epithelial cells. To attain their

desired functions, secreted cytokines and chemokines bind to their designated receptors (listed in

Table 1.5).

[51]

Table 1.5: Innate immune cytokines and chemokines

Immune functions Cytokine families Cytokine members

Adaptive immunity

(proliferation and

activation of

macrophages, T cells, B

cells and NK cells)

Common γ chain receptor

ligands IL-2, IL-4, IL-7, IL-9, IL-15, IL-21

Common β chain (CD131)

receptor ligands IL-3, IL-5, GM-CSF

Shared IL-2β chain (CD122) IL-2, IL-15

Shared receptors IL-13 (IL-13R–IL-4R complex)

TSLP (TSLPR–IL-7R complex)

Pro-inflammatory

signaling

(activation of

phagocytes, chemotaxis,

and phagocytosis;

induction of cytokines)

(IFN: anti-viral

capacities, macrophage

activation)

IL-1

IL-1α, IL-1β, IL-1ra, IL-18, IL-33,

IL-36α, IL-36β, IL-36γ, IL-36Ra,

IL-37 and IL-1Hy2

IL-6 IL-6, IL-11, IL-31, CNTF, CT-1,

LIF, OPN, OSM

TNFα TNFα, TNFβ, BAFF, APRIL

IL-17 IL-17A-F, IL-25 (IL-17E)

Type I IFN IFNα, IFNβ, IFNω, IFNκ, Limitin

Type II IFN IFNγ

Type III IFN IFNλ1 (IL-29), IFNλ2 (IL-28A),

IFNλ3 (IL-28B)

Anti-inflammatory

signaling

(inhibition of cytokine

production; anti-

inflammatory)

IL-12 IL-12, IL-23, IL-27, IL-35

IL-10 IL-10, IL-19, IL-20, IL-22, IL-24,

IL-26, IL-28, IL-29

Immune functions Chemokine families Chemokine members

Recruitment of immune

cells, T-cells,

macrophages,

neutrophils

CC chemokine/receptor family CCL1-28

C chemokine/receptor family XCL1-2

CXC chemokine/receptor

family CXCL1-17

CX3C chemokine/receptor

family CX3CL1

*Table adapted from: Turner D. Turner et al. Cytokines and chemokines: at the crossroads of cell signaling and

inflammatory disease. Biochim Biophys Acta. 2014; 1843(11): 2563-2582.

[52]

Other TLR-regulatory molecules

In addition to TLR signaling, expression of cytokines and chemokines is also regulated by other

mediators such as phosphatidylinositol-3-kinase (PI3K), protein kinase B (AKT) and protein

kinase C (PKC). My PhD thesis incorporates the activity of PKC in TJ regulation whose role will

be discussed further below.

PKC refers to a family of serine or threonine kinases with at least 15 isoforms (Mochly-Rosen et

al., 2012). Depending on activation conditions, the PKC isoforms can be subdivided into 3

families. The conventional isoforms PKC-α, -βI, -βII and γ are activated by calcium,

diacylglycerol and phosphatidylserine; the novel isoforms, PKC-δ, -ε, -η and -θ are calcium-

independent but require diacylglycerol and phosphatidylserine; and the atypical isoforms, PKC-

ζ and λ/ι require only phosphatidylserine (Newton, 2003).

Two isoforms that play a significant role in TLR signaling and are highly expressed in intestinal

tissues are the PKC isoforms α and δ (Loegering and Lennartz, 2011). Early studies using

chemical inhibitors demonstrated their direct roles in TLR-induced cytokine secretion.

Macrophages and neutrophils exposed to the PKC inhibitor Gö6976, which specifically blocks α

and β isoforms, have reduced NF-κB activation and decreased secretion of TNF-α and IL-1β

following TLR stimulation (Asehnoune et al., 2005; Foey and Brennan, 2004). Likewise,

immune cells derived from PKC-α-/-

mice have reduced activation of MAPK and NF-κB

signaling pathways and their associated cytokines following TLR activation (Langlet et al.,

2010). Similarly, down-regulation of PKCδ or inhibition of its activity using the PKCδ-specific

inhibitor Rottlerin significantly dampens the activation of NF-κB and MAPK pathways by TLR

ligands (Bhatt et al., 2010).

[53]

1.6.3 Innate immunity in health and disease

The host innate immune system provides multiple mechanisms to prtect the host. Defects in any

facet of these mechanisms can render the host susceptible to infection and disease pathogenesis.

Disruption in TJ assembly and function results in intestinal barrier breakdown, which is a key

process in the pathogenesis of several human diseases including inflammatory bowel diseases

(IBD), celiac disease (CD) and necrotizing enterocolitis (NEC) (Odenwald and Turner, 2016). In

IBD, for instance, increased intestinal permeability due in part to the higher expression of pore-

forming TJ claudin-2 (Zeissig et al., 2007) and lower expression of occludin (Heller et al., 2005)

correlates with lower rates of clinical remission (Wyatt et al., 1993). Mutations in genes

encoding TJs are also linked to a wide range of hereditary human diseases (Table 1.6).

Select bacterial pathogens, such as Clostridium perfringens, hijack specific claudin members to

breakdown the integrity of the epithelial barrier (Saitoh et al., 2015). This breakdown of claudins

opens the unrestricted pathway for luminal contents so that intact large proteins and bacterial

cells and metabolites can translocate into the submucosa to initiate further damage.

This sequence of events in epithelial barrier breakdown can be modeled using in vitro systems by

co-culturing an enteric pathogen with intestinal epithelial cell lines on Transwell® inserts (Figure

1.9). These inserts are made of a semi-permeable polystyrene membrane that forms an inner

well, which is completely submersed into an outer well. Confluent epithelial cell monolayers can

be grown on Transwell® inserts and juxtaposed between the inner and outer wells to form apical

and basolateral environments. The human intestinal epithelial cells I used in experiments

described in this thesis are the Caco-2Bbe1 colonic adenocarcinoma cells - a subclone of the

Caco-2 cells with brush border expression on the apical surface of epithelia. To induce barrier

[54]

defects in vitro, enteric pathogens, pro-inflammatory mediators and chemical reagents can be

administered into the apical environment to simulate the luminal exposure of bacteria and their

toxins on the intestinal lining. Within my thesis, the enteric pathogen selected for use was the

non-invasive enterohemorrhagic Escherichia coli (EHEC) serotype O157:H7. EHEC O157:H7 is

a Shiga-toxin-producing E. coli (STEC) responsible for sporadic cases and outbreaks of bloody

diarrhea and, in the most severely affected cases, causes hemolytic-uremic syndrome.

EHEC O157:H7 expresses a number of virulence factors that directly alter the F-actin

cytoskeleton and disrupt TJ barrier function, including Map, EspG and EspF (Ugalde-Silva et al.,

2016). EspG, for instance, contains structural motifs that allow tethering onto the host F-actin

cytoskeleton. This interaction disrupts the microtubule network and alters the integrity of TJ

proteins claudin-1, ZO-1/ZO-2 and occludins (Glotfelty et al., 2014). These effects results in a

decrease in the transepithelial electrical resistance (TER), which is measured by inserting

chopstick electrodes into the inner and outer wells of Transwells®.

[55]

Table 1.6: TJs linked to hereditary diseases and infectious agents

TJ

her

edit

ary d

isea

se

TJ proteins Human diseases

Claudin 1 Neonatal icthyosis, sclerosing cholangitis

Claudin 5 Velo-cardial-facial syndrome

Claudin 14 Non-syndromic deafness

Claudin 16 Familial hypomagnesemia, hypercalciuria, nephrocalcinosis

Claudin 19 Familial hypomagnesemia, hypercalciuria, nephrocalcinosis,

visual impairments

ZO-2 Familial hyper