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
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