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BASIC SCIENCE REVIEW

Characterization of the Gastrointestinal Microbiota in Health and Inflammatory Bowel Disease Peter De Cruz, MD,*,† Lani Prideaux, MD,*,† Josef Wagner, PhD,‡ Siew C. Ng, PhD,§,k Chris McSweeney, PhD,¶ Carl Kirkwood, PhD,‡ Mark Morrison, PhD,¶ and Michael A. Kamm, PhD*,†

Abstract: The enteric bacterial flora play a key role in maintaining health. Inflammatory bowel disease is associated with quantitative and qualitative alterations in the microbiota. Early characterization of the microbiota involved culture-dependent techniques. The advent of metagenomic techniques, however, allows for structural and functional characterization using culture-independent methods. Changes in diversity, together with quantitative alterations in specific bacterial species, have been identified. The functional significance of these changes, and their pathogenic role, remain to be elucidated. (Inflamm Bowel Dis 2012;18:372–390) Key Words: enteric bacterial flora, inflammatory bowel disease, metagenomic, microbiota

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ecent advances in the techniques available to characterize the microbiota and their interaction with the human host have opened up new means of exploring the role of the intestinal microbiota in health and inflammatory bowel disease (IBD). The gut microbiota is a complex ecological environment, with each human harboring up to 100 trillion (1014) bacteria,1,2 10-fold the number of human cells in the same individual. It is estimated that the gut microbiota comprises 40,000 or more different species.3 Microbes comprise 50% of our fecal volume.4 There is strong evidence for the involvement of microbes in the development of IBD. Animal models of inflammation require bacteria.5,6 Antibiotics have therapeutic efficacy in Crohn’s disease (CD),7 pouchitis,8,9 and ulcerative colitis (UC).10 Probiotics have therapeutic efficacy in pouchitis11 and UC.12 Diverting the fecal stream from the inflamed gut induces healing in CD,13,14 while reinfusion of intestinal content into surgically excluded ileum triggers recurrence.15 There is an ongoing debate as to whether changes in the intestinal microbiota precede or follow the development Received for publication March 21, 2011; Accepted March 31, 2011. From the *St Vincent’s Hospital, Melbourne, Australia, †University of Melbourne, Australia, ‡Murdoch Children’s Research Institute, Australia, § Chinese University of Hong Kong, kPrince of Wales Hospital, Hong Kong, ¶ Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia. The first two authors contributed equally to this article. Reprints: Professor Michael A. Kamm, St Vincent’s Hospital, Victoria Parade, Fitzroy 3065, Melbourne, Australia (e-mail: [email protected]). C 2011 Crohn’s & Colitis Foundation of America, Inc. Copyright V DOI 10.1002/ibd.21751 Published online 20 May 2011 in Wiley Online Library (wileyonlinelibrary. com).

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of colitis in IBD. Early work to correlate altered microbiota composition with disease causation has had some success, with changes in the relative densities and spatial distribution of dominant bacterial groups preceding the onset of colitis in interleukin (IL)-10 knockout mice.16 Seventy percent of the gut microbiota have not been cultured by standard, culture-based techniques.17 This has in part given rise to the field of metagenomics, the study of microbiota using culture-independent techniques.18 At the cornerstone of bacterial classification using these techniques is the bacterial 16S ribosomal (r)RNA gene. The 1.5 kbp bacterial 16S rRNA gene, which consists of nine conserved regions and nine variable regions, provides the basis for bacterial classification. This has revolutionized bacterial taxonomy.19 It has now been almost a decade since the completion of the Human Genome Project. Knowledge of the sequences of the 20,000 genes in the human body, however, is not enough to understand the functional and metabolic capabilities of man. This relates, at least in part, to Man’s coevolution with microbiota; Man can be considered a ‘‘supra-organism’’—a composite of human and microbial genes (the microbiome).20,21 This microbiome, estimated to encode 100fold more genes than the human genome,1 is currently being characterized as part of the Human Microbiome Project.21 Characterization of the microbiota has until now been complicated by large person-to-person variation.22 The ‘‘normal’’ human bowel community is still being defined.23

TECHNIQUES FOR BACTERIAL CHARACTERIZATION Traditional culture methods cultivated only 10%– 30% of the gut microbiota.4,17,24 More recently, molecular Inflamm Bowel Dis Volume 18, Number 2, February 2012

Inflamm Bowel Dis Volume 18, Number 2, February 2012

approaches based on 16S rRNA have been employed to detect uncultivable microbiota, using denaturing gradient gel electrophoresis (DGGE),25–27 temporal temperature gradient gel electrophoresis (TTGE),28 temperature gradient gel electrophoresis (TGGE),22 fluorescent in-situ hybridization (FISH),22,29 and terminal restriction fragment length polymorphism (T-RFLP).30–32 These techniques provide information about the predominant microbiota but an incomplete view of microbial composition, only showing the most abundant taxa.33 More recent DNA sequencing technologies and phylogenetic microarray analysis have revolutionized bacterial characterization by increasing sequence sampling depth and throughput, respectively. As with traditional polymerase chain reaction (PCR)-based techniques, the main limitations of these methodologies are sequence-specific PCR amplification differences and biases introduced by DNA extraction.34 Sequencing techniques are used to determine the order of nucleotides in any DNA fragment. Initially, Sanger et al35 described a technique based on chain termination. The more recent technique of next-generation sequencing is based on sequencing by synthesis.36 Compared to Sanger sequencing, next-generation sequencing is higher throughput, less expensive, and reveals less abundant taxa.36 Phylogenetic microarray analysis characterizes the presence and abundance of different species within the bacterial community. It uses species-specific probes to analyze multiple sequences simultaneously. It is high throughput, allows comparison between two groups, and is relatively inexpensive. Its main limitations are that probes are limited to those related to known sequences, and it is not quantitative.33,37 Once a sequence of interest is identified, it can be quantitated using real-time PCR (also called quantitative PCR, qPCR). The method can be used to quantify organisms from the level of species to higher taxonomic groups depending on the specificity of the primer sets being employed. Real-time PCR allows validation of metagenomic data and is fast compared with traditional methods of quantification.38 Through metagenomic approaches the generation of large volumes of bacterial 16S sequence data, of both known and unknown microbes, within our gut is possible. Sequence data are categorized into groups called operational taxonomic units (OTUs), sometimes referred to as ribo-types or phylo-groups. Based on the 16S gene sequence similarity of more than 99% is regarded as a ‘‘strain’’; 97% similarity as a ‘‘species’’; 95% as ‘‘genus’’; more than 90% as ‘‘family’’19; and more than 80% as a phyla.39 Previously unidentified bacteria can often be assigned a classification within the taxonomic tree based on their similarity to previously identified bacteria.

Microbiota in Health and IBD

MICROBIOTA THROUGHOUT LIFE Traditionally it has been thought that a newborn’s gut is sterile at birth.40 Recent observations suggest that infants also receive microorganisms from their mothers during gestation.41 The gut microbiota of infants is initially unstable, highly variable,42 with abrupt shifts in abundance of taxonomic groups that can be linked to illness, dietary change, and antibiotic therapy.43,44 Antibiotic use in children has recently been linked to the development of IBD in later life.45 Other environmental influences on the microbiota include mode of delivery46–49 and breast versus formula feeding.46,47,50–58 In particular, breast feeding and vaginal delivery provide initial colonization of the infant with Lactobacilli and Bifidobacteria.59,60 A recent study has suggested that the fecal microbiota may also be influenced by body mass index, weight, and maternal weight gain during pregnancy.61 This period in the development of the infant microbiota is believed to be crucial in determining subsequent health or disease, such as eczema,41,62–66 asthma,63,67–70 and IBD.45,71 By the age of two an infant’s microbiota is established40 and is thought to remain relatively stable throughout the remainder of life.22,72 Centenarians have an unstable microbiota, raising the possibility of a link to increased disease in the elderly.73 It is currently believed that greater than 90% of all phylotypes within the adult colonic microbiota belong to just two phyla19: the Firmicutes (Gram-positive; mainly Clostridium coccoides and Clostridium leptum subgroups), and Bacteroidetes (Gram-negative), with less abundant phyla including Proteobacteria, Actinobacteria, Fusobacteria, and Verrucmicrobia.17,72

SEARCH FOR A CORE Phylogenetic Core Despite abundant evidence of high individual variation in the human gut microbiota, with the majority of OTUs specific to an individual,22,72,74–78 a ‘‘phylogenetic core,’’ comprising a small number of OTUs, is shared among individuals.79–81 Tap et al found that 66 OTUs (2.1%) were present in more than 50% of 17 fecal samples, with 52 of these 66 OTUs detected in at least 3 of 4 previously published human fecal microbiota data sets.20,72,82,83 However, there appear to be radically different levels of abundance (12– 2000-fold) for these common species among individuals.79 Turnbaugh et al78 challenged the concept of a phylogenetic core in a study using pyrosequencing. While a number of OTUs were shared there was not a single abundant bacterial species (defined as representing more than 0.5% of the population) present in all of the 154 individuals studied. It remains likely that a phylogenetic core does exist. In a follow-up study, Turnbaugh et al81 performed deeper

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pyrosequencing on one monozygotic twin pair, and broader sequencing on 54 twin pairs and their mothers. Of 134 phylotypes identified in all the twin pairs, only 37 were present in more than 50% of the samples. Only one phylotype, Lachnospiraceae, was present in nearly all individuals. The concept that previously inadequate depth of sampling concealed common species which are in low abundance was reinforced by Qin et al,79 who found that a 2–3-fold increase in sequencing depth raised by 25% the number of shared species between two individuals. Recently, Sekelja et al84 confirmed the presence of a phylogenetic core by reanalyzing sequence data using a phylogroup- and tree-independent approach. In particular, two highly prevalent core phylogroups were identified which belong to the clostridial family Lachnospiraceae and are believed to be ancient, abundant, and stable in the human gut.84

Functional Core While the phylogenetic core describes what is commonly present in the gut between individuals, it does not explain the role of these bacteria. An emerging concept is that of a functional core, a ‘‘core microbiome,’’ at a gene expression and organismal lineage level,78 related to the products and effects of the microbiota. There appears to be extensive functional redundancy within an individual’s gut microbiota whereby a number of different organisms, some of which are shared, and some of which differ between individuals, perform similar functions. Qin et al79 recently confirmed the presence of a functional core and extended the size of functional categories by 30%, compared with the previous work of Turnbaugh et al.78 Functional analysis of the microbiota is a rapidly evolving area and refers broadly to community characterization at the level of RNA (metatranscriptomics), protein (metaproteonomics), and metabolites (metabonomics).

HOST-BACTERIAL MUTUALISM Man’s coevolution with microbiota has resulted in a tight, finely balanced relationship, referred to as host-bacterial mutualism.85 The host influences or determines the nature and activity of the microbiota and the microbiota influences or determines aspects of host immunity.17

Host Effects on the Microbiota General Several studies have suggested that host genetics influence the composition of gut microbiota. Mouse studies have demonstrated that the enteric microbiota is transmitted vertically from mother to child.86 Germ-free mice receiving adult human fecal transplants subsequently transmitted their microbial community to their offspring.87

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A study employing culture of enteric bacteria showed that the fecal-associated microbiota (FAM) of monozygotic twins were much more alike than those of dizygotic twins.88 TTGE on fecal samples from children further demonstrated a greater similarity between monozygotic twins than dizygotic twins or unrelated paired controls.89 In contrast, other studies using DGGE90 and pyrosequencing78,91 have shown no difference between monozygotic and dizygotic twins with respect to FAM. Family members were, however, found to have more similar profiles than unrelated individuals.90 Although a study by Willing et al,91 which included CD patients, showed that the effect of disease phenotype was greater than that of host genotype, there was similarity apparent at the genus level, in adult healthy twin pairs who had lived apart for many years. This observation underscores the importance of genes and/or environmental exposure during early childhood in the development of the microbial community.91 Differentiating between the environmental and genetic factors that converge to shape the gut microbiota is a complex task, which was highlighted in a study by Rawls et al92 that used reciprocal mice/zebrafish gut microbiota transplantations to germ-free zebrafish/mice hosts. The microbiota posttransplantation reflected the donor community in terms of the bacterial lineages, but in contrast, microbial community abundances more closely resembling the normal profile of the recipient host. A donor fecal infusion study has been performed in humans; following a healthy donor’s fecal infusion, a durable beneficial change in the patients’ colonic microbiota (using DGGE) was found, which represented that of the healthy donor’s microbiota.93

Specific Genes Related to IBD For the host and microbiota to maintain equilibrium the host requires an immune system that processes microbial antigens, allowing it to shape its resident microbiota into a nonhostile and productive community. The host achieves this control over the microbiota via the immune system. Mutations in a number of genes involved in innate immunity including NOD2, ATG16L1, IRGM, and OCTN1/ 2 have indicated a link between the innate immune response to invasive bacteria and the development of CD.17,94 The key immune mediators involved in the control of the microbiota are Paneth cells, defensins, MyD88 (myeloid differentiation primary response gene 88), Toll-like receptors (TLR), unfolded protein response (UPR), autophagy, and nucleotide-binding oligomerization domain containing 2 (NOD2). Any factors that disrupt these immune-mediated pathways can lead to dysregulation of the microbiota,95 as detailed below. Paneth cells directly sense enteric bacteria and regulate their production of antimicrobial peptides via MyD88-


dependent activation of TLRs, thereby limiting bacterial penetration of host tissue.96 Paneth cell function and antimicrobial activity is regulated by a number of immune pathways and genes including UPR, autophagy, and NOD2.97 The UPR pathway maintains normal epithelial function and therefore homeostasis between the microbiota and immune system and the epithelial interface.98–100 The UPR is activated in response to endoplasmic reticulum (ER) stress and regulates autophagy. Paneth cells, goblets cells, and other highly secretory cells are particularly prone to ER stress and therefore dependent on the UPR pathway to increase the size and protein processing function of the ER.101 Mutations within the UPR, and environmental factors that create disturbances in the UPR, such as microbial products and inflammatory cytokines, have been shown to cause or perpetuate intestinal inflammation.101 Autophagy, a lysosomal process, is triggered by cellular stress including ER stress.97,101 Two variants of the autophagy protein, ATG16L1 and IRGM, have been discovered in association with CD. Paneth cells have defects in granule content and exocytosis, indicating that autophagy also plays an important role in Paneth cell function.102 Other key innate immunity mediators that allow crosstalk between the host and microbiota include pattern recognition receptors such as NOD2 and TLRs.103 NOD2, highly expressed in Paneth cells, enables detection of a wide variety of bacteria by responding to their cell wall peptidoglycan.104 Mutations in NOD2 alter the antimicrobial activity of Paneth cells in the terminal ileum,105 resulting in impaired bacterial surveillance.106,107 The important role of NOD2 in the regulation of commensal microbiota was recently highlighted in a study which showed that in comparison with wildtype mice, NOD2-deficient mice had increased amounts of commensal bacterial in the gut as well as reduced capability to clear newly colonizing bacteria.104 Antimicrobial peptides such as defensins are also key effector molecules in the innate immune systems control of gut microbiota.17 Reduced levels of defensins have been observed in both ileal and colonic CD.97 Reduced defensin production has been associated with NOD2 mutations.108–110

Microbiota Controls Host Immunity Effect on Intestinal Immunity The gut microbiota has an early impact after birth on the development of the host intestinal immune system by generating signals that influence maturation of the gut-associated lymphoid tissue. Gram-negative peptidoglycan is required for maturation of isolated lymphoid follicles in the gut.111 The microbiota also generate signals that promote recruitment of IgA secreting plasma cells and T cells to the gut mucosa and facilitate crosstalk between dendritic cells


(DCs) and gut epithelial cells, thereby regulating the intensity of intestinal B- and T-cell responses.112–114 DCs play an important role in mediating the effect of gut bacteria on the host immune system. DCs sample and respond to luminal microbiota via pattern recognition receptors such as TLRs, and therefore modify the nature of subsequent T-cell responses.115 It has recently been shown that IL-6 production by intestinal DCs is increased in CD and correlates with disease activity and C-reactive protein, and intestinal DC function may be influenced by the composition of the commensal microbiota.116 Commensal microbiota, such as Bacteroides fragilis, express molecules such as polysaccharide A which protect against the proinflammatory effects of potentially pathogenic microbiota by stimulating IL-10-producing CD4þ T cells.117–119 Similarly, the commensal Fecalibacterium prausnitzii has been shown to have antiinflammatory effects due to secreted metabolites which block NF-jB activation and IL-8 production.120 Segmented filamentous bacteria (SFB) have also been shown to regulate the balance between T helper 17 (Th17) and regulatory T cells, contributing to the influence that microbiota composition has on intestinal immunity, tolerance, and susceptibility to IBD.119–121 Recently, a method of identification of bacterial genes involved in regulation of NF-jB signaling in intraepipthelial cells has been developed. This may help identify bacteria that directly affect mucosal immunity and inflammation.122

Effect on Systemic Immunity Dysbiosis, imbalance between beneficial and harmful bacteria, has been proposed to be associated with the development of extraintestinal immune-mediated diseases,114 but the mechanism by which this occurs has been difficult to establish. It has been recently shown that the microbiota are a source of peptidoglycan that systemically primes the innate immune system via recognition by NOD1.123 Other studies have shown that the capsular polysaccharide of B. fragilis is able to restore the Th1/Th2 imbalance in germfree mice.124 Diet has also been shown to affect systemic immunity through altering the gut microbiota, and one mechanism by which this could occur is via short chain fatty acid binding to a chemoattractant receptor.125 Further studies are required to establish the clear link between the gut microbiota and systemic immunity.

APPROACHES TO BACTERIAL CHARACTERIZATION Two broad approaches have been taken to define the role of the microbiota in IBD: the ‘‘global description strategy’’126–128 and the ‘‘candidate microorganism strategy.’’129 The former describes the attempt to characterize the composition of the microbial community and has led to the

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concept of ‘‘dysbiosis.’’ The ‘‘candidate microorganism strategy’’ refers to the identification of single specific microorganisms that are thought to be directly pathogenic, such as Escherichia coli129 or Mycobacterium avium subspecies paratuberculosis (MAP).130 These two approaches are not mutually exclusive.

‘ Global Description Strategy’’ While dysbiosis is defined broadly as a deviation of the microbial community from its normal state, in IBD a number of consistent features have been identified. The FAM of CD28,82,131 and UC127 patients is characterized by the presence of bacteria that do not belong to the usual dominant phylogenetic groups. In the mucosa-associated microbiota (MAM) of CD patients there are increased concentrations of total bacteria,132–137 and total and facultative anaerobes.133,138,139 In the MAM of UC patients there are increased concentrations of total bacteria,133–135,137 total anaerobes,133,140 and aerobes.141 The definition of the nature and diversity of the microbial spectrum is dependent in part on the techniques used to characterize it. Dysbiosis has been characterized by an overall decrease in biodiversity in the MAM and FAM of CD127,131,142–145 and UC143,145–148 compared with controls. However, recent pyrosequencing studies suggest that the FAM of UC patients in remission is similar to that of healthy controls.91 CD appears to be associated with a reduction in the diversity of the phylum Firmicutes, particularly the Clostridium leptum subgroup, in both the FAM82,127,131,142 and MAM.3,145,149 In particular, the species Fecalibacterium prausnitzii, which has antiinflammatory properties,120 is less prevalent in the FAM150,151 and MAM3,152,153 of CD patients, as is the genus Roseburia.91 In UC, Firmicutes, particularly the C. coccoides group, has been shown to be reduced in both FAM127 and MAM.128,145 F. prausnitzii has been shown in a single study to be increased in UC.150 The Ruminococcaceae family appear to be more abundant in the FAM and MAM of healthy subjects, compared with elderly subjects154 and CD,91,155,156 and in females compared with males.157 Some Ruminococcus species also appear to be more abundant in the FAM and MAM of active UC.158,159 The relative abundance of R. gnavus has been found to be increased in ileal CD.91 The pathogenic significance of this microbe is unclear; it has been reported to both produce a bacteriocin with antiinflammatory properties,160 and to have mucolytic properties.161 Using a variety of techniques, increased counts of bacteria, especially E. coli and Enterococci, have been found in the FAM28,156,162 and MAM133,152,155,159,163–165 of both active and inactive CD and UC, compared with healthy controls.

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There are conflicting data regarding the phylum Bacteroidetes. In the FAM and MAM of CD and UC versus controls, Bacteroidetes and its species has been found to be both increased128,131,133,144,145,151,166,167 and decreased.3,136,142,148,155 Increased numbers of Fusobacteria have been found in the FAM140 and MAM158 of active UC compared with inactive UC and controls. In CD Bifidobacteria and Lactobacilli have been found to be decreased in the FAM in both adults28,142,156,168 and children.151 In the MAM of UC patients, Bifidobacteria are decreased,164 whereas Lactobacilli have been found to be decreased in the FAM of patients with active UC.169 Recently, TM7 (a subgroup of Gram-positive uncultivable bacteria), previously implicated in oral inflammation, has been shown to be increased in diversity in active CD (23 phylotypes) compared with active UC (10 phylotypes) and non-IBD controls (12 phylotypes). The TM7 associated with CD and UC was strongly associated with antibiotic resistance compared with controls.170 Swidsinski et al150 suggested that two features could be useful as a ‘‘fingerprint’’ to discriminate between CD and UC: a reduction in the concentration of F. prausnitzii in CD to less than 1 109 per mL, and an increase in leukocytes in UC to >30 leukocytes/104lm2. Recent studies have also demonstrated differences in the relative abundance of the Bifidobacteriaceae, Coriobacteriaceae, and Ruminococcaceae families among individuals with different CD phenotypes.91,144,153 In a study of FAM using DGGE, Joossens et al171 found a ‘‘dysbiosis signature’’ associated with CD, characterized by five bacterial species, namely, a decrease in Dialister invisus, F. prausnitzii, and Bifidobacterium adolescentis, and an increase in R. gnavus and an uncharacterized species of Clostridium cluster XIVa. In the same study, the fecal samples of 84 unaffected first-degree relatives of CD patients were found to have an altered composition of the predominant microbiota compared with controls. No difference was seen when F. prausnitzii was specifically targeted by qPCR.171 Prospective studies are needed to identify if overt disease will develop in some of these relatives over time.

‘ Candidate Microorganism Strategy’’ The two ‘‘candidate organisms’’ that have received the most attention as having a possible specific association with CD are E. coli and MAP.

MAP MAP has long been considered a possible causative agent in CD because of the similarity of Johne’s disease in cattle, caused by MAP, and CD in humans.172


Of two recent meta-analyses and systematic reviews of the association of MAP with CD the first included 28 case-controlled studies of MAP DNA detected by PCR in tissue samples, or antibodies against MAP antigens tested by enzyme-linked immunosorbent assay in serum. MAP was detected more often in patients with CD than in controls and patients with UC.173 The second meta-analysis only included studies of tissue samples using nucleic acidbased techniques, specifically PCR or in situ hybridization. In the analysis of the 47 studies, MAP was detected more frequently among CD patients compared with controls.174 This meta-analysis has been criticized on its exclusion of 13 studies in which MAP was not detected in any patients with CD or in controls.175 In a recent large-scale 16S rRNA gene library study which was not included in either of these two meta-analyses, more than 15,000 small subunit ribosomal RNA genes were analyzed and MAP was not detected in CD patients.3 The influence of IBD medication on MAP should be considered. Methotrexate, 6-mercaptopurine, and 5-aminosalicylic acid have been shown to inhibit MAP growth in vitro.176,177 Kirkwood et al130 investigated pediatric patients not yet treated with any medication and found that MAP was identified more often in mucosal biopsies and peripheral blood mononuclear cells from CD than in nonIBD patients. Difficulties in extraction of MAP DNA may explain the failure and detection in many studies. The effect of antimycobacterial therapy has been the subject of a Cochrane review, which cautiously concluded that antimycobacterial therapy may have a role in maintaining remission in CD, but fell short of recommending therapy.178 The result of the largest randomized controlled trial to date does not support the use of antimycobacterial therapy in CD.179

E. coli Numerous studies have shown increased numbers of mucosa associated E. coli in both CD and UC compared with healthy controls.129,132,133,136,153,163,164,180–182 As a commensal organism within the normal gut microbiota, E. coli plays an important role in maintaining intestinal homeostasis and is not implicated in disease unless there is a breach in the intestinal mucosa barrier. Of the colonic-like microbiota that colonize the neoterminal ileum postresectional surgery for CD, E. coli tend to predominate.180,181 The adherent invasive strain of E. coli (AIEC) has developed virulence factors that allow it to adapt and survive in the postoperative environment.183 AIEC has been found in association with early neoterminal ileal lesions in the postoperative CD setting.165 The ability of AIEC to adhere and invade intestinal cells is mediated by a number of virulence factors including type 1 pili, flagella, and outer membrane porin C.184–188 Moreover, AIEC is able to resist phagocyto-


sis, and survive and replicate extensively in large vacuoles within macrophages without triggering host cell death.189–191 The type 1 pili of AIEC bind to the specific receptor CEACAM-6 expressed in ileal epithelial cells of patients with CD but not healthy controls.192 CEACAM-6 receptors become overexpressed in response to stimulation of ileal epithelial cells by tumor necrosis factor alpha (TNFa), which is released from macrophages that have taken up CD-associated AIEC.193 AIEC therefore causes an amplification loop of colonization and inflammation.190 The early inflammatory response to AIEC among patients with CD carrying CARD15 polymorphisms appears to be disturbed.194

Other Organisms Several other bacteria such as Pseudomonas,195–199 Yersinia,200,201 Listeria,155,202–204 Burkholderia,205 and Helicobacter206–210 have been linked to IBD, but what pathophysiological role, if any, they play remains to be determined. A contribution from viruses211–213 and fungi214–216 has also not been excluded.

MICROBIOTA DIFFERENCES WITHIN AN INDIVIDUAL Fecal-associated Microbiota Versus Mucosa-associated Microbiota The nature and extent of difference between the FAM and MAM remains unclear. Numerous studies using different techniques have tried to evaluate this question. Three studies have found the FAM and MAM to be similar. Van de Waaij et al217 used FISH in nine healthy subjects, Bibiloni et al218 used TGGE on healthy, CD, and UC subjects (15 subjects in total), and Willing et al91 used pyrosequencing on 18 subjects. In contrast, four studies have found a significant difference between the FAM and MAM in healthy subjects using DGGE (10 subjects),25 gene library sequence analysis in (three and nine subjects),72,74 and T-RFLP (16 subjects)219, and in CD and UC patients using TTGE.220 On balance, it appears that the FAM represents a combination of shed mucosal bacteria and a separate nonadherent luminal population,72 and differs from the MAM.

Stability Along the Gastrointestinal (GI) Tract The extent to which the MAM varies along the GI tract has not been resolved. In healthy subjects, MAM has been found to be similar within the colon25,72,221 as well as between the colon and ileum,153,220,222,223 including a recent study using pyrosequencing.91 In contrast, significant differences have been found in a number of studies between the ileum and colon,221,224 and a proximal to distal gradient described between ileum and proximal to distal colon.225,226

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In both CD and UC no significant difference has been identified between the ileum and colon.220,222,223 This observation has been confirmed in CD in a recent study using microarray227 as well as a study which involved pyrosequencing on biopsies of nine twin pairs.91

Inflamed Versus Noninflamed Mucosa There have been a number of studies on the difference between inflamed and noninflamed mucosa in IBD within one patient. No difference has been found in inflamed versus noninflamed tissue in CD and/or UC using DGGE,152,222,228 TGGE,229,230 FISH,230 and clone library analysis.138,149 A microarray study of samples from the same patient showed a similar profile whether from inflamed or noninflamed tissue.227 In contrast, in UC a difference in the bacterial subdominant populations in inflamed versus noninflamed mucosa was found using DGGE, and a decrease in diversity in ‘‘inflamed tissue’’ (CD and UC combined) versus noninflamed tissue using 16S-23S intergenic spacer analysis and T-RFLP.231 Recent deep sequencing of paired biopsies from inflamed and noninflamed mucosa in CD (n = 6) and UC (n = 6) has demonstrated some differences in bacterial community composition, but these differences varied greatly between individuals, as a consequence of which, no bacterial signature was obviously associated with the inflamed gut.145 In summary, current evidence has failed to demonstrate a difference in bacterial composition between inflamed and noninflamed tissue but further deeper phylogenetic analysis is required.

Stability Over Time The temporal stability of the microbiota within one individual has mainly been investigated using fecal samples, with few data analyzing mucosal biopsies over time.147 Using a variety of techniques (but not next generation sequencing), FAM and MAM have been shown to be stable in healthy patients over 1 month,232 2 months,78 6 months,22,90 8 months,233 1 year,146,147,234 and 2 years28; and unstable in CD and/or UC over 6 months,142 1 year,146,147 and 2 years.28 Analyzing mucosal biopsies over time with next generation sequencing will provide important information regarding bacterial stability.

Active Versus Inactive IBD Changes in the microbiota between active and inactive disease has been characterized in two different settings. Within one person, Ott et al147 biopsied the same location over several timepoints (during remission and relapse, defined by criteria using clinical and endoscopic indices) and observed baseline reduction, temporal instability, and decrease of bacterial richness towards relapse.

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Other studies of FAM have grouped subjects into ‘‘active’’ and ‘‘inactive’’ and then compared their microbiota. In CD, using pyrosequencing, no difference has been seen between active CD versus remission.91 In UC, some studies have shown differences in specific bacterial probes between active disease and remission. In one study, Lactobacilli species was found to be present, or increased, during inactive versus active UC.158,169 In a study using T-RFLP, Andoh et al235 found a decrease in the Clostridium family in the FAM of patients with active UC, and inactive/active CD. In contrast, Bacteroides was significantly increased in CD patients.

Changes in Microbiota Following Surgery for CD and UC Postoperative CD A number of studies of the microbiota in IBD have been undertaken in the postoperative setting. These studies have provided insight into the changes in the microbiota among those who develop disease recurrence, compared to those who are in remission, and may reflect the microbiologic changes that contribute to underlying disease and disease progression. The findings in these studies need to be interpreted within context, as the microbiota colonizing the postsurgical niche may be subject to colonization pressure, and may not be the same as the microbiota that contributed to the development of disease initially. The postsurgical milieu is influenced by use of perioperative medications known to induce changes in the microbiota. Despite these limitations, the postoperative setting remains a useful model to study the evolution of IBD. Initial microbiota studies in the postoperative CD setting indicated that the neoterminal ileum is characterized by bacterial colonization following ileocolonic resection.180,181 Subsequent studies have shown that E. coli can be recovered from 65% of chronic lesions (ileal resections) and from 100% of the biopsies of CD neoterminal lesions.129,165 In a study by Sokol et al,120 among the 13 of 21 patients who developed endoscopic recurrence at 6 months postileal resection, endoscopic relapse was consistently associated with a lower proportion of F. prausnitzii isolated at the time of surgery, and a lower proportion of Firmicutes (i.e., C. coccoides and F. prausnitzii) 6 months postsurgery. In another study of 20 patients with CD undergoing ileocolonic resection, LePage et al220 observed Bacteroides colonizing the neoterminal ileum in patients with recurrence, but were only found at the anastomosis in patients in remission.

Pouchitis An etiological role for the microbiota in pouchitis has been proposed by studies indicating that remission of


pouchitis can be induced by antibiotics,9,236 and maintained by probiotics.237 Initial culture based studies have shown that pouch effluent is characterized by the presence of more anaerobes than ileostomy effluent, and that the pouch and fecal microbiota are similar.238–240 However, no trends in specific levels of different bacterial species or the degree of mucosal inflammation were observed. A number of studies have suggested that dysbiosis is implicated in the development of pouchitis, but it is unclear whether this is a predisposing factor or the cause of pouchitis. In a study using 16S rRNA analysis on patients with FAP and UC with and without pouchitis, there appeared to be limited differences in bacterial composition between those with and without pouchitis, suggesting dysbiosis as a predisposing rather than causative factor.241 However, a central role for dysbiosis in pouchitis is more likely and has been supported by two studies, one of which compared the MAM of UC pouch patients with and without active pouchitis, and found UC pouchitis was characterized by persistence of Fusobacter and Enteric species and the absence of specific bacteria such as Streptococcus species.242 The other study analyzed the FAM and MAM of UC patients with and without pouchitis compared with Familial Adenomatous Polyposis pouches and found that UC pouchitis patients had substantially fewer Bacteroidetes and more Clostridia compared to the healthy UC pouch and Familial Adenomatous Polyposis groups.243

FUNCTIONAL ANALYSIS OF THE GUT MICROBIOTA In addition to quantitative changes in the microbiota structure, functional activity of specific members of the gut microbiota is likely to be important in disease states. It is well recognized that many core metabolic functions may be shared between bacteria, promoting stability in metabolic function, and maintaining homeostasis; hydrolysis and fermentation of foods, production of essential cofactors and vitamins, biosynthesis of polyketides, nonribosomal peptides and secondary metabolites, and the processing of xenobiotics. The microbiota also play a role in mucosa barrier function and immune modulation. While the human genome determines some of these roles, other roles such as the metabolism of plant polysaccharides require the gut microbiome.244 However, some bacteria may alter their metabolic and physiological profile in response to various environmental cues, which may arise from the host, dietary components, and/or other microbes. To date, most studies have focused on the bacterial diversity associated with health. However, functional analyses of the microbiota is a rapidly evolving area of investigation, comprising various -‘‘omics’’ technologies that characterize microbial activity at the level of DNA (metagenomics); RNA (metatranscriptomics), protein expression (metaproteonomics), and metab-


olite release and production (metabonomics). In that context, Qin et al79 recently described a gut microbial gene catalog of 3.3 million genes which will help advance the utilization of these ‘‘-omic’’-based technologies in the future.

DNA-based (Metagenomic) Approaches In their analysis of metagenomic data produced from the fecal samples of two unrelated American adults, Gill et al20 found that their microbiomes were particularly rich with genes that code for the metabolism of glycans, amino acids, and xenobiotics; methanogenesis; and biosynthesis of vitamins, compared to the human genome. A later study by Kurokawa et al245 examined the fecal samples of 13 healthy Japanese subjects including adults, weaned children, and unweaned infants and found that the microbiomes of the adults and weaned children were quite similar in terms of their functional characteristics. In contrast, the unweaned infant gut microbiome showed a high interindividual variation. Furthermore, there were CEGs (commonly enriched genes) within the human genome and gut microbiome. In particular, genes involved in carbohydrate metabolism and defense mechanisms were enriched in the metagenomes of all 13 subjects, whereas genes involved in lipid metabolism, flagella biosynthesis, and chemotaxis were underrepresented. The identification of conjugative transposons in the metagenomic data also confirmed the extent to which horizontal gene transfer might play in these microbiomes.245 Tasse et al246 employed a novel multistep functionally based approach to identify clones encoding carbohydrate active enzymes (CAZymes). Upon isolation of 26 clones found to be particularly efficient in the degradation of dietary fiber, pyrosequencing was undertaken enabling a 5-fold increase in the target-gene enrichment compared to random sequencing. Such findings have also led to the consideration of whether there is a ‘‘core microbiome.’’ The studies of Tap et al showed only 66 (2%) of the OTUs encountered in the fecal samples they examined were found in one or more subjects. Interestingly, many of these so-called ‘‘core’’ OTUs were also identified in the other human gut microbiome datasets described above. Qin et al79 have since expanded this ‘‘core’’ to include both functional genes and bacterial ‘‘species.’’ These authors go further to propose that the gut microbiome of each individual is comprised of 160 bacterial ‘‘species’’; but the entire cohort of gut bacterial species probably does not exceed 1150 ‘‘species.’’ Given the advances in DNA sequencing technologies it seems reasonable to suggest that in the near future the microbial genome sequencing projects will produce a ‘‘saturation’’ of metagenomic data for a range of age and ethnic groups, as well as for healthy subjects and subjects suffering from various maladies such as obesity and IBD. In

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other words, the composition of human gut metagenomes are fast approaching the level of characterization that their ‘‘profiling’’ will extend beyond a select number of taxonomic marker genes, and include a much greater depth of functional complexity, including the approaches described below.


metatranscriptomes, suggesting site-specific alterations in gene expression profiles.248 Furthermore, functional gene microarrays have been synthesized using the metagenomic dataset produced by Qin et al79 (2010; Ehrlich, pers. commun.). Accordingly, exciting new results will soon be forthcoming as a result of the successful use of these resources.

Metatranscriptomics: RNA Transcriptomics and metatranscriptomics seek to characterize the gene expression patterns of select microbes, or the entire microbiome, respectively. Rehman et al247 analyzed the transcriptional activity of MAM by comparing 16S rRNA gene and rRNA profiles from biopsies of active IBD patients and healthy subjects. They found that specific bacterial populations were activated in IBD patients, whereas other groups lay dormant. In contrast, among healthy patients, there did not appear to be the same variation in abundance and activity. This confirms that, in disease, it is the microbiota’s functional activity or inactivity that is as important as its presence, abundance, or absence. Our collaborative group has recently undertaken studies to examine how the transcriptomes of Australian isolates of Enterococcus fecium and Bacteroides vulgatus may change in media designed to simulate the colonic environment during health and disease. These bacteria were cultured using anaerobic media supplemented with fecal waters prepared from either healthy persons or IBD patients, as well as media supplemented with additional water or a complex nutrient broth. A preliminary assessment of the transcriptomic responses has been obtained for the E. fecium isolate (Klaassens et al, submitted). Approximately 16% of the RNA-sequence reads were expressed under all four growth conditions, suggesting the genes encode general ‘‘housekeeping’’ functions. However, there was also a similar percentage of RNA-sequence reads that were produced only in response to the bacterium’s exposure to the fecal waters; several of these encode proteins that are presumptive extracellular, membrane-bound proteins. These findings further confirm that the transcriptomes of gut bacteria are dynamic and responsive to components present in the colonic environment. Subtractive enrichment of microbial mRNA from stool or tissue samples, as well as a comprehensive metagenome dataset for interrogation, have been viable constraints on these metatranscriptomics analyses of human gut microbiomes. However, for reasons outlined above, metatranscriptomic studies of the human gut microbiome are now within reach: a recent abstract illustrated a metatranscriptome and metagenome comparison between the luminal and MAM of a single CD patient using pyrosequencing and KEGG (Kyoto Encyclopedia of Genes and Genomes) database analysis.248 Metagenomes of luminal and MAM were more similar to each other than to their respective

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Metaproteomics: Proteins Metaproteomics is the study of the proteome, which refers to the set of all expressed proteins in a cell, tissue, or organism. The proteome is dynamic and subject to changes in health and disease, and reflects the interactions between genes and the environment. The fluctuation of proteins in response to health and disease make them attractive as both diagnostic biomarkers and targets to guide molecular therapeutics.249 The most commonly used technique in metaproteomics is mass spectrometry, which measures the mass-tocharge ratio of charged particles. These charged particles are created from proteins, peptides, or metabolites, which are subsequently separated according to this mass-to-charge ratio. Klaassens et al250 were among the first to examine the metaproteome produced from human fecal samples, and also performed DGGE of the gene encoding 16S rRNA to monitor the bacterial communities from two infants. FAM was found to be relatively simple and predominated by bifidobacteria. Using mass spectrometry, a peptide sequence was discovered in the stool sample which was similar to a bifidobacteria transaldolase.250 It is felt that other functionally active bacteria can be discovered via a similar metaproteomic approaches. Using mass spectrometry-based shotgun proteomics, Verberkmoes et al251 compared the identified proteins in the feces of a healthy monozygotic twin pair to available protein databases, and in so doing, identified the functional activities of the gut microbiota on a large scale. Metaproteomics has not yet been applied to the IBD setting, but it has been employed by Ang et al252 to examine stool samples in pursuit of diagnostic biomarkers for early colorectal cancer diagnosis. Similar to metatranscriptomics, the DNA sequence databases that are being rapidly produced should serve to improve the interrogative potential of proteomic methods, ensuring more of these types of analyses successfully result in the identification of the cognate gene (and microbe[s]) encoding that particular protein.

Metabolomics: Metabolites Metabolomics (also known as metabonomics) refers to the quantification of metabolites present in cells or organisms that participate in the metabolic reactions required for growth and maintenance of normal function. It also includes metabolites ingested from the external environment and the


metabolites of the gut microbiota.253 Metabolomics is a rapidly evolving area and involves the characterization of the true endproducts of biological processes within biological tissues and fluids such as urine, feces, and blood.254,255 Just as genome-wide association studies (GWAS) have found associations between genotype and disease phenotypes,256,257 the metabolome-wide association study (MWAS) has revealed associations of metabolic phenotypes with disease risk.258,259 Metabolic profiling can also be used to determine the impact of diet260–265 and medications.266 Metabolomics utilizes mass spectrometry and nuclear magnetic resonance spectroscopy, which exploits the fine differences in the frequency of subatomic particles within organic compounds that depends on their neighboring atoms to differentiate one compound from another.253 There is increasing research on the use of metabolomics in IBD. Using feces and urine from healthy subjects, Li et al83 were able to link the microbiota composition within feces with the metabolic products in the urine. Other studies were able to form similar correlations from feces of patients with and without IBD.267,268 The modulation of the metabolites in the urine by the gut microbiota has also been proven in animal models.269,270 Williams et al271 applied urinary metabolic profiling to 86 CD patients, 60 UC patients, and 60 healthy controls. Specific metabolite levels were significantly different among the three groups, allowing differentiation according to urinary metabolic profile; importantly, colonic CD could be differentiated from UC. A number of other studies on colonic biopsies have also demonstrated the ability of metabolomics to distinguish CD from UC.272,273 A subgroup analysis in the Williams et al study271 did not reveal any significant variation of the individual diseases by disease location, which is in contrast to Jansson et al,267 who were able to show a difference in the fecal metabolite profiles of ileal versus colonic CD. Regarding disease activity, Jansson et al did not find any influence of disease activity on the metabolic profile; however, other studies have found that the activity of IBD could be distinguished on the basis of altered metabolite levels.255,272 Metabolic profiles of colonic biopsies in IBD has shown that there was little difference between inflamed and noninflamed tissue, but the metabolic profiles differed from that of healthy controls.274 In summary, the rapid development of extensive datasets of the genetic potential resident within various gut microbiomes should soon result in the next wave of highimpact discoveries, which elucidate not only the structural, but also the functional attributes of the gut microbiota that contribute to health and/or disease. Such datasets should support the further establishment of systems biology approaches within select clinical studies, increasing the likelihood of dissecting the roles of the host, diet, and microbiology in gut health and disease.


ENVIRONMENTAL INFLUENCES ON THE GUT MICROBIOTA Geography and Lifestyle A limited number of studies have compared the gut microbiota between subjects from different countries and/or different lifestyles. Within Europe, infants have been studied using molecular techniques on feces, showing that the country of birth plays a greater role in defining the microbiota than delivery mode and feeding method.47 The same study also identified a European geographic gradient where the highest number of differences in the microbiota were in the extreme north and south.47 Adults within Europe were studied by Mueller et al,275 who performed FISH on the feces of 30 subjects across four countries. Results included a 2–3-fold higher level of bifidobacteria in Italians compared to French, Germans, and Swedes. It was concluded on multivariate analysis that the country effects, with respect to phylogenetic groups, may be due to differences in dietary habits. In contrast, Lay et al,276 in a study on the feces of 91 young adults across five countries in central and northern Europe, found no significant correlation between the microbiota and geographic region. A number of groups have attempted to study differences in the gut microbiota between countries of different lifestyle and diet. Using fecal culture, Estonian infants were found to have higher counts of Lactobacilli and Eubacteria, while Swedish infants had higher Clostridia counts.277 There was an increase in lactic acid bacteria, coliforms, and Staphylococci in rural children from Thailand compared with urban children from Singapore.278 No single lifestyle factor was identified to account for these differences. Li et al83 found that their study using DGGE on Chinese gut microbiota differed from previous studies on American gut microbiota at the species level. Recently, using pyrosequencing on fecal samples, De Filippo et al279 found that children from Burkina Faso had significantly different microbiota from children in urban Florence. In the African children there was a higher fecal microbial richness and biodiversity, and a unique abundance of bacteria from the genus Prevotella and Xylanibacter, known to contain a set of bacterial genes for cellulose and xylan hydrolysis. They concluded that that gut microbiota of Burkina Faso children allows maximum energy intake from fibers by coevolving with the polysaccharide-rich diet. The only study to utilize mucosal biopsies, as well as to include subjects with IBD, used TTGE to compare the FAM and MAM of 38 subjects in Mexico and 64 subjects in Canada. There was greater similarity in the microbiota profiles for country of origin than for disease status.218 Differences in microbiota between different countries is likely to relate to a combination of genetic, dietary, and

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other environmental factors. Diet has a major impact on the composition and activity of the gut microbiota.280,281 Changes in gut microbiota, mediated via environmental factors, may contribute to the recent increase in incidence of IBD in developing countries.282

Diet The relationship between the host, diet, and the gut microbiota is complex. The dynamic impact of diet on the microbiota composition and function has been reflected in obesity research. Studies in both mouse models and humans have shown that compared with the lean gut microbiome, the obese gut microbiome is enriched with genes involved in energy extraction from the host diet.78,86,283 The large and abrupt impact of diet on humanized gnotobiotic mice has been demonstrated by Turnbaugh et al,87 who showed that when switching from a low-fat, plant polysaccharide-rich diet to a high-fat/high-sugar diet, the microbiota changed substantially within 1 day, the representation of metabolic pathways in the microbiome changed, and the microbiome gene expression was altered. More recently, glucagon-like peptide 2 (GLP-2), via its effect on gut permeability, has been raised as a potential mechanism by which the microbiota mediate their effect on obesity.284 A key functional contribution of the microbiota is the harvest of otherwise inaccessible nutrients and/or sources of energy from the diet, and the synthesis of vitamins.21 The microbiota metabolize fiber and resistant starch to the short chain fatty acids (SCFAs) butyrate, acetate, and propionate, which serve as a major energy source for colonocytes, and implicated in prevention of colitis and colorectal cancer.285–287 Butyrate also strengthens and maintains mucosal barrier function via production of mucin, antimicrobial peptides, and tight-junction proteins.288 The antiinflammatory property of SCFAs may relate to their binding to a G-protein-coupled receptor (GPR43), leading to downregulation of inflammatory responses.125 Growth in number of butyrate producing bacteria such as Eubacterium rectale and Roseburia species is directly stimulated by dietary carbohydrates.289–292 Carbohydrate substrates inulin and fructo-oligosaccharide also promote growth of ‘‘probiotic’’ bacteria Bifidobacteria and Lactobacilli.293 IBD is associated with reduced numbers of butyrateproducing bacteria (e.g., clostridia groups IV and XIVa of which F. prausnitzii is a member), and accordingly, reduced concentrations of SCFAs.120,294 A lack of the antiinflammatory effects of butyrate could be implicated in the inflammatory cascade involved in IBD and butyrate is already considered to be of therapeutic benefit in IBD.295–297 A class of microbiota, known as sulfate-reducing bacteria (SRB), have been shown to synthesize toxic metabolic products such as hydrogen sulfide,298 which is toxic to

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colonocytes, blocks butyrate utilization, indices cell hyperproliferation, and inhibits phagocytosis and bacterial killing.299 Overgrowth of SRB has been demonstrated in IBD, particularly among UC and pouch patients.300 A high meat-containing diet has been associated with the toxic products of SRB.298,300–304 A diet of low meat, saturated fat, high fiber, and resistant starch, through its effects on the microbiota, may be linked to the low incidence of colorectal cancer in Africa.302,305,306 Diet may impact the composition of the gut microbiota in diverse ways. Genes used by marine microbiota to metabolize carbohydrates in seaweed have been found among the gut microbiome in Japanese but not Americans. Acquisition of these novel genes in the Japanese gut microbiome most likely occurred though ingestion of seaweed and marine microbes, with horizontal gene transfer.307 Case-control studies and epidemiological data have yielded inconsistent results for an association between specific foods and the occurrence of CD and/or UC. None of these studies have clearly linked diet to the gut microbiota and the development of IBD. Foods that have been implicated include meat308 and fats/oils,308–310 sweets/confectionary,308,311–313 and fast food.313 Fatty acids have been suggested to have a protective role,309 as have fiber, fruit, and vegetable from IBD,308,309,314–317 while other studies have been negative.308,318,319 There is emerging evidence in mouse models and humans that iron may have an impact on the intestinal microbiota and immune response to inflammation. Iron has been shown to increase the concentration of iron-dependent E coli, Klebsiella, and Bacteroides species and exacerbate colitis in mouse models.320,321 In a recent study of anemic African children, treatment with iron produced a more pathogenic gut microbiota profile, which was associated with increased gut inflammation (measured by fecal calprotectin).322 In contrast, a recent abstract has shown that iron supplementation reduces inflammatory lesions in experimental colitis in rats.323

CONCLUSION The prospects for discovery within the GI microbiota/microbiome is captivating and rapidly evolving. While traditionally characterization of the microbiota has focused on which bacteria are present, it is becoming clear that analysis of bacterial function is as important to establish the complex relationship between the gut microbiota and its host.

REFERENCES 1. Ley RE, Peterson DA, Gordon JI. Ecological and evolutionary forces shaping microbial diversity in the human intestine. Cell. 2006;124: 837–848. 2. Savage DC. Microbial ecology of the gastrointestinal tract. Annu Rev Microbiol. 1977;31:107–133.


3. Frank DN, St Amand AL, Feldman RA, et al. Molecular-phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases. Proc Natl Acad Sci U S A. 2007;104: 13780–13785. 4. Suau A, Bonnet R, Sutren M, et al. Direct analysis of genes encoding 16S rRNA from complex communities reveals many novel molecular species within the human gut. Appl Environ Microbiol. 1999; 65:4799–4807. 5. Strober W, Fuss IJ, Blumberg RS. The immunology of mucosal models of inflammation. Annu Rev Immunol. 2002;20:495–549. 6. Sellon RK, Tonkonogy S, Schultz M, et al. Resident enteric bacteria are necessary for development of spontaneous colitis and immune system activation in interleukin-10-deficient mice. Infect Immun. 1998;66:5224–5231. 7. Sartor RB. Therapeutic manipulation of the enteric microflora in inflammatory bowel diseases: antibiotics, probiotics, and prebiotics. Gastroenterology. 2004;126:1620–1633. 8. Shen B, Achkar JP, Lashner BA, et al. A randomized clinical trial of ciprofloxacin and metronidazole to treat acute pouchitis. Inflamm Bowel Dis. 2001;7:301–305. 9. Gionchetti P, Rizzello F, Venturi A, et al. Antibiotic combination therapy in patients with chronic, treatment-resistant pouchitis. Aliment Pharmacol Ther. 1999;13:713–718. 10. Ohkusa T, Kato K, Terao S, et al. Newly developed antibiotic combination therapy for ulcerative colitis: a double-blind placebo-controlled multicenter trial. Am J Gastroenterol. 2010;105:1820–1829. 11. Gionchetti P, Rizzello F, Venturi A, et al. Oral bacteriotherapy as maintenance treatment in patients with chronic pouchitis: a doubleblind, placebo-controlled trial. Gastroenterology. 2000;119:305–309. 12. Kruis W, Fric P, Pokrotnieks J, et al. Maintaining remission of ulcerative colitis with the probiotic Escherichia coli Nissle 1917 is as effective as with standard mesalazine. Gut. 2004;53:1617–1623. 13. Rutgeerts P, Goboes K, Peeters M, et al. Effect of faecal stream diversion on recurrence of Crohn’s disease in the neoterminal ileum. Lancet. 1991;338:771–774. 14. Lee E. Split ileostomy in the treatment of Crohn’s disease of the colon. Ann R Coll Surg Engl. 1975;56:94–102. 15. D’Haens GR, Geboes K, Peeters M, et al. Early lesions of recurrent Crohn’s disease caused by infusion of intestinal contents in excluded ileum. Gastroenterology. 1998;114:262–267. 16. Overstreet AMC, Ramer-Tait AE, Atherly TA, et al. W1829 changes in composition of the intestinal microbiota precede onset of colitis in genetically-susceptible (IL-10-/-) mice. Gastroenterology. 2010;138: 748–749. 17. Sokol H, Seksik P. The intestinal microbiota in inflammatory bowel diseases: time to connect with the host. Curr Opin Gastroenterol. 2010;26:327–331. 18. Ley RE, Lozupone CA, Hamady M, et al. Worlds within worlds: evolution of the vertebrate gut microbiota. Nat Rev Microbiol. 2008; 6:776–788. 19. Peterson DA, Frank DN, Pace NR, et al. Metagenomic approaches for defining the pathogenesis of inflammatory bowel diseases. Cell Host Microbe. 2008;3:417–427. 20. Gill SR, Pop M, Deboy RT, et al. Metagenomic analysis of the human distal gut microbiome. Science. 2006;312:1355–1359. 21. Turnbaugh PJ, Ley RE, Hamady M, et al. The human microbiome project. Nature. 2007;449:804–810. 22. Zoetendal EG, Akkermans AD, De Vos WM. Temperature gradient gel electrophoresis analysis of 16S rRNA from human fecal samples reveals stable and host-specific communities of active bacteria. Appl Environ Microbiol. 1998;64:3854–3859. 23. Tannock GW. The search for disease-associated compositional shifts in bowel bacterial communities of humans. Trends Microbiol. 2008; 16:488–495. 24. Tannock GW. Molecular assessment of intestinal microflora. Am J Clin Nutr. 2001;73(Suppl):410S–414S. 25. Zoetendal EG, von Wright A, Vilpponen-Salmela T, et al. Mucosaassociated bacteria in the human gastrointestinal tract are uniformly distributed along the colon and differ from the community recovered from feces. Appl Environ Microbiol. 2002;68:3401–3407.


26. Muyzer G, Smalla K. Application of denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE) in microbial ecology. Antonie Van Leeuwenhoek. 1998;73: 127–141. 27. Tannock GW. The intestinal microflora: potentially fertile ground for microbial physiologists. Adv Microb Physiol. 2000;42:25–46. 28. Seksik P, Rigottier-Gois L, Gramet G, et al. Alterations of the dominant faecal bacterial groups in patients with Crohn’s disease of the colon. Gut. 2003;52:237–242. 29. Franks AH, Harmsen HJ, Raangs GC, et al. Variations of bacterial populations in human feces measured by fluorescent in situ hybridization with group-specific 16S rRNA-targeted oligonucleotide probes. Appl Environ Microbiol. 1998;64:3336–3345. 30. Leser TD, Lindecrona RH, Jensen TK, et al. Changes in bacterial community structure in the colon of pigs fed different experimental diets and after infection with Brachyspira hyodysenteriae. Appl Environ Microbiol. 2000;66:3290–3296. 31. Kaplan CW, Astaire JC, Sanders ME, et al. 16S ribosomal DNA terminal restriction fragment pattern analysis of bacterial communities in feces of rats fed Lactobacillus acidophilus NCFM. Appl Environ Microbiol. 2001;67:1935–1939. 32. Nagashima K, Hisada T, Sato M, et al. Application of new primerenzyme combinations to terminal restriction fragment length polymorphism profiling of bacterial populations in human feces. Appl Environ Microbiol. 2003;69:1251–1262. 33. Zoetendal EG, Collier CT, Koike S, et al. Molecular ecological analysis of the gastrointestinal microbiota: a review. J Nutr. 2004;134: 465–472. 34. Andersson AF, Lindberg M, Jakobsson H, et al. Comparative analysis of human gut microbiota by barcoded pyrosequencing. PLoS ONE. 2008;3:e2836. 35. Sanger F, Nicklen S, Coulson AR. DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci U S A. 1977;74:5463–5467. 36. Ahmadian A, Ehn M, Hober S. Pyrosequencing: history, biochemistry and future. Clin Chim Acta. 2006;363:83–94. 37. El Fantroussi S, Urakawa H, Bernhard AE, et al. Direct profiling of environmental microbial populations by thermal dissociation analysis of native rRNAs hybridized to oligonucleotide microarrays. Appl Environ Microbiol. 2003;69:2377–2382. 38. Wang AM, Doyle MV, Mark DF. Quantitation of mRNA by the polymerase chain reaction. Proc Natl Acad Sci U S A. 1989;86: 9717–9721. 39. Schloss PD, Handelsman J. Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness. Appl Environ Microbiol. 2005;71:1501–1506. 40. Mackie RI, Sghir A, Gaskins HR. Developmental microbial ecology of the neonatal gastrointestinal tract. Am J Clin Nutr. 1999;69: 1035S–1045S. 41. Hong PY, Lee BW, Aw M, et al. Comparative analysis of fecal microbiota in infants with and without eczema. PLoS One. 2010;5: e9964. 42. Cucchiara S, Iebba V, Conte MP, et al. The microbiota in inflammatory bowel disease in different age groups. Dig Dis. 2009;27: 252–258. 43. Koenig JE, Spor A, Scalfone N, et al. Succession of microbial consortia in the developing infant gut microbiome. Proc Natl Acad Sci U S A. 2011;108:4578–4585. 44. Savino F, Roana J, Mandras N, et al. Faecal microbiota in breast-fed infants after antibiotic therapy. Acta Paediatr. 2011;100:75–78. 45. Hviid A, Svanstrom H, Frisch M. Antibiotic use and inflammatory bowel diseases in childhood. Gut. 2011;60:49–54. 46. Penders J, Thijs C, Vink C, et al. Factors influencing the composition of the intestinal microbiota in early infancy. Pediatrics. 2006;118: 511–521. 47. Fallani M, Young D, Scott J, et al. Intestinal microbiota of 6-weekold infants across Europe: geographic influence beyond delivery mode, breast-feeding, and antibiotics. J Pediatr Gastroenterol Nutr. 2010;51:77–84. 48. Dominguez-Bello MG, Costello EK, Contreras M, et al. Delivery mode shapes the acquisition and structure of the initial microbiota

383

De Cruz et al

49.

50.

51. 52. 53.

54. 55. 56. 57.

58. 59.

60.

61.

62. 63. 64. 65.

66. 67. 68. 69.

across multiple body habitats in newborns. Proc Natl Acad Sci U S. A;107:11971–11975. Gronlund MM, Lehtonen OP, Eerola E, et al. Fecal microflora in healthy infants born by different methods of delivery: permanent changes in intestinal flora after cesarean delivery. J Pediatr Gastroenterol Nutr. 1999;28:19–25. Harmsen HJ, Wildeboer-Veloo AC, Raangs GC, et al. Analysis of intestinal flora development in breast-fed and formula-fed infants by using molecular identification and detection methods. J Pediatr Gastroenterol Nutr. 2000;30:61–67. Favier CF, Vaughan EE, De Vos WM, et al. Molecular monitoring of succession of bacterial communities in human neonates. Appl Environ Microbiol. 2002;68:219–226. Hopkins MJ, Macfarlane GT, Furrie E, et al. Characterisation of intestinal bacteria in infant stools using real-time PCR and northern hybridisation analyses. FEMS Microbiol Ecol. 2005;54:77–85. Penders J, Vink C, Driessen C, et al. Quantification of Bifidobacterium spp., Escherichia coli and Clostridium difficile in faecal samples of breast-fed and formula-fed infants by real-time PCR. FEMS Microbiol Lett. 2005;243:141–147. Benno Y, Sawada K, Mitsuoka T. The intestinal microflora of infants: composition of fecal flora in breast-fed and bottle-fed infants. Microbiol Immunol. 1984;28:975–986. Lundequist B, Nord CE, Winberg J. The composition of the faecal microflora in breastfed and bottle fed infants from birth to eight weeks. Acta Paediatr Scand. 1985;74:45–51. Stark PL, Lee A. The microbial ecology of the large bowel of breast-fed and formula-fed infants during the first year of life. J Med Microbiol. 1982;15:189–203. Dore J, Sghir A, Hannequart-Gramet G, et al. Design and evaluation of a 16S rRNA-targeted oligonucleotide probe for specific detection and quantitation of human faecal Bacteroides populations. Syst Appl Microbiol. 1998;21:65–71. Adlerberth I, Carlsson B, de Man P, et al. Intestinal colonization with Enterobacteriaceae in Pakistani and Swedish hospital-delivered infants. Acta Paediatr Scand. 1991;80:602–610. Martin R, Heilig GH, Zoetendal EG, et al. Diversity of the Lactobacillus group in breast milk and vagina of healthy women and potential role in the colonization of the infant gut. J Appl Microbiol. 2007;103:2638–2644. Martin R, Jimenez E, Heilig H, et al. Isolation of bifidobacteria from breast milk and assessment of the bifidobacterial population by PCRdenaturing gradient gel electrophoresis and quantitative real-time PCR. Appl Environ Microbiol. 2009;75:965–969. Collado MC, Isolauri E, Laitinen K, et al. Effect of mother’s weight on infant’s microbiota acquisition, composition, and activity during early infancy: a prospective follow-up study initiated in early pregnancy. Am J Clin Nutr. 2010;92:1023–1030. Wang M, Karlsson C, Olsson C, et al. Reduced diversity in the early fecal microbiota of infants with atopic eczema. J Allergy Clin Immunol. 2008;121:129–134. Penders J, Thijs C, van den Brandt PA, et al. Gut microbiota composition and development of atopic manifestations in infancy: the KOALA Birth Cohort Study. Gut. 2007;56:661–667. Kirjavainen PV, Arvola T, Salminen SJ, et al. Aberrant composition of gut microbiota of allergic infants: a target of bifidobacterial therapy at weaning? Gut. 2002;51:51–55. Gore C, Munro K, Lay C, et al. Bifidobacterium pseudocatenulatum is associated with atopic eczema: a nested case-control study investigating the fecal microbiota of infants. J Allergy Clin Immunol. 2008; 121:135–140. Forno E, Onderdonk AB, McCracken J, et al. Diversity of the gut microbiota and eczema in early life. Clin Mol Allergy. 2008;6:11. Murray CS, Tannock GW, Simon MA, et al. Fecal microbiota in sensitized wheezy and non-sensitized non-wheezy children: a nested case-control study. Clin Exp Allergy. 2005;35:741–745. Kalliomaki M, Isolauri E. Role of intestinal flora in the development of allergy. Curr Opin Allergy Clin Immunol. 2003;3:15–20. Devereux G. The increase in the prevalence of asthma and allergy: food for thought. Nat Rev Immunol. 2006;6:869–874.

384


70. Wang Y, McCusker C. Neonatal exposure with LPS and/or allergen prevents experimental allergic airways disease: development of tolerance using environmental antigens. J Allergy Clin Immunol. 2006; 118:143–151. 71. Probert CS, Brown M. Are there any ethnic groups that are more likely to develop IBD? Inflamm Bowel Dis. 2008;14(suppl 2): S24–25. 72. Eckburg PB, Bik EM, Bernstein CN, et al. Diversity of the human intestinal microbial flora. Science. 2005;308:1635–1638. 73. Biagi E, Nylund L, Candela M, et al. Through ageing, and beyond: gut microbiota and inflammatory status in seniors and centenarians. PLoS One. 2010;5:e10667. 74. Durban A, Abellan JJ, Jimenez-Hernandez N, et al. Assessing gut microbial diversity from feces and rectal mucosa. Microb Ecol. 2011;61:123–133. 75. Vanhoutte T, Huys G, Brandt E, et al. Temporal stability analysis of the microbiota in human feces by denaturing gradient gel electrophoresis using universal and group-specific 16S rRNA gene primers. FEMS Microbiol Ecol. 2004;48:437–446. 76. Maukonen J, Satokari R, Matto J, et al. Prevalence and temporal stability of selected clostridial groups in irritable bowel syndrome in relation to predominant faecal bacteria. J Med Microbiol. 2006;55: 625–633. 77. Booijink CC, El-Aidy S, Rajilic-Stojanovic M, et al. High temporal and inter-individual variation detected in the human ileal microbiota. Environ Microbiol. 2010;12:3213–3217. 78. Turnbaugh PJ, Hamady M, Yatsunenko T, et al. A core gut microbiome in obese and lean twins. Nature. 2009;457:480–484. 79. Qin J, Li R, Raes J, et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature. 2010;464:59–65. 80. Tap J, Mondot S, Levenez F, et al. Towards the human intestinal microbiota phylogenetic core. Environ Microbiol. 2009;11: 2574–2584. 81. Turnbaugh PJ, Quince C, Faith JJ, et al. Organismal, genetic, and transcriptional variation in the deeply sequenced gut microbiomes of identical twins. Proc Natl Acad Sci U S A. 2010;107:7503–7508. 82. Manichanh C, Rigottier-Gois L, Bonnaud E, et al. Reduced diversity of faecal microbiota in Crohn’s disease revealed by a metagenomic approach. Gut. 2006;55:205–211. 83. Li M, Wang B, Zhang M, et al. Symbiotic gut microbes modulate human metabolic phenotypes. Proc Natl Acad Sci U S A. 2008;105: 2117–2122. 84. Sekelja M, Berget I, Naes T, et al. Unveiling an abundant core microbiota in the human adult colon by a phylogroup-independent searching approach. ISME J. 2011;5:519–531. 85. Backhed F, Ley RE, Sonnenburg JL, et al. Host-bacterial mutualism in the human intestine. Science. 2005;307:1915–1920. 86. Ley RE, Backhed F, Turnbaugh P, et al. Obesity alters gut microbial ecology. Proc Natl Acad Sci U S A. 2005;102:11070–11075. 87. Turnbaugh PJ, Ridaura VK, Faith JJ, et al. The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci Transl Med. 2009;1:6ra14. 88. Van de Merwe JP, Stegeman JH, Hazenberg MP. The resident faecal flora is determined by genetic characteristics of the host. Implications for Crohn’s disease? Antonie Van Leeuwenhoek. 1983;49:119–124. 89. Stewart JA, Chadwick VS, Murray A. Investigations into the influence of host genetics on the predominant eubacteria in the faecal microflora of children. J Med Microbiol. 2005;54:1239–12342. 90. Zoetendal EG, Akkermans ADL, Akkermans-van Vliet WM, et al. The host genotype affects the bacterial community in the human gastroinestinal tract. Microb Ecol Health Dis. 2001;13:129–134. 91. Willing B, Dicksved J, Halfvarson J, et al. A pyrosequencing study in twins shows that GI microbial profiles vary with inflammatory bowel disease phenotypes. Gastroenterology. 2010;139:1844–1854. 92. Rawls JF, Mahowald MA, Ley RE, et al. Reciprocal gut microbiota transplants from zebrafish and mice to germ-free recipients reveal host habitat selection. Cell. 2006;127:423–433. 93. Grehan MJ, Borody TJ, Leis SM, et al. Durable alteration of the colonic microbiota by the administration of donor fecal flora. J Clin Gastroenterol. 2010;44:551–561.


94. Frank DN, Robertson CE, Hamm CM, et al. Disease phenotype and genotype are associated with shifts in intestinal-associated microbiota in inflammatory bowel diseases. Inflamm Bowel Dis. 2011;17: 179–184. 95. Fritz T, Niederreiter L, Adolph T, et al. Crohn’s disease: NOD2, autophagy and ER stress converge. Gut. 2011; [Epub ahead of print]. 96. Vaishnava S, Behrendt CL, Ismail AS, et al. Paneth cells directly sense gut commensals and maintain homeostasis at the intestinal host-microbial interface. Proc Natl Acad Sci U S A. 2008;105: 20858–20863. 97. Garrett WS, Gordon JI, Glimcher LH. Homeostasis and inflammation in the intestine. Cell. 2010;140:859–870. 98. Kaser A, Blumberg RS. Endoplasmic reticulum stress in the intestinal epithelium and inflammatory bowel disease. Semin Immunol. 2009;21:156–163. 99. Kaser A, Blumberg RS. Paneth cells and inflammation dance together in Crohn’s disease. Cell Res. 2008;18:1160–1162. 100. Kaser A, Lee AH, Franke A, et al. XBP1 links ER stress to intestinal inflammation and confers genetic risk for human inflammatory bowel disease. Cell. 2008;134:743–756. 101. Kaser A, Martinez-Naves E, Blumberg RS. Endoplasmic reticulum stress: implications for inflammatory bowel disease pathogenesis. Curr Opin Gastroenterol. 2010;26:318–326. 102. Cadwell K, Liu JY, Brown SL, et al. A key role for autophagy and the autophagy gene Atg16l1 in mouse and human intestinal Paneth cells. Nature. 2008;456:259–263. 103. Uronis JM, Muhlbauer M, Herfarth HH, et al. Modulation of the intestinal microbiota alters colitis-associated colorectal cancer susceptibility. PLoS One. 2009;4:e6026. 104. Petnicki-Ocwieja T, Hrncir T, Liu YJ, et al. Nod2 is required for the regulation of commensal microbiota in the intestine. Proc Natl Acad Sci U S A. 2009;106:15813–15818. 105. Cho JH. The genetics and immunopathogenesis of inflammatory bowel disease. Nat Rev Immunol. 2008;8:458–466. 106. Kobayashi KS, Chamaillard M, Ogura Y, et al. Nod2-dependent regulation of innate and adaptive immunity in the intestinal tract. Science. 2005;307:731–734. 107. Begue B, Dumant C, Bambou JC, et al. Microbial induction of CARD15 expression in intestinal epithelial cells via toll-like receptor 5 triggers an antibacterial response loop. J Cell Physiol. 2006;209: 241–252. 108. Wehkamp J, Salzman NH, Porter E, et al. Reduced Paneth cell alpha-defensins in ileal Crohn’s disease. Proc Natl Acad Sci U S A. 2005;102:18129–18134. 109. Simms LA, Doecke JD, Walsh MD, et al. Reduced alpha-defensin expression is associated with inflammation and not NOD2 mutation status in ileal Crohn’s disease. Gut. 2008;57:903–910. 110. Bevins CL, Stange EF, Wehkamp J. Decreased Paneth cell defensin expression in ileal Crohn’s disease is independent of inflammation, but linked to the NOD2 1007fs genotype. Gut. 2009;58:882–883; discussion 3–4. 111. Bouskra D, Brezillon C, Berard M, et al. Lymphoid tissue genesis induced by commensals through NOD1 regulates intestinal homeostasis. Nature. 2008;456:507–510. 112. Hooper LV, Macpherson AJ. Immune adaptations that maintain homeostasis with the intestinal microbiota. Nat Rev Immunol. 2010;10: 159–169. 113. Eberl G, Lochner M. The development of intestinal lymphoid tissues at the interface of self and microbiota. Mucosal Immunol. 2009;2: 478–485. 114. Cerf-Bensussan N, Gaboriau-Routhiau V. The immune system and the gut microbiota: friends or foes? Nat Rev Immunol. 2010;10: 735–744. 115. Stagg AJ, Hart AL, Knight SC, et al. Microbial-gut interactions in health and disease. Interactions between dendritic cells and bacteria in the regulation of intestinal immunity. Best Pract Res Clin Gastroenterol. 2004;18:255–270. 116. Ng SC, Benjamin JL, McCarthy NE, et al. Relationship between human intestinal dendritic cells, gut microbiota, and disease activity in Crohn’s disease. Inflamm Bowel Dis. 2010; [Epub ahead of print].


117. Glocker EO, Kotlarz D, Boztug K, et al. Inflammatory bowel disease and mutations affecting the interleukin-10 receptor. N Engl J Med. 2009;361:2033–2045. 118. Round JL, Mazmanian SK. Inducible Foxp3þ regulatory T-cell development by a commensal bacterium of the intestinal microbiota. Proc Natl Acad Sci U S A. 2010;107:12204–12209. 119. Mazmanian SK, Round JL, Kasper DL. A microbial symbiosis factor prevents intestinal inflammatory disease. Nature. 2008;453:620–625. 120. Sokol H, Pigneur B, Watterlot L, et al. Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc Natl Acad Sci U S A. 2008;105:16731–16736. 121. Ivanov II, Frutos Rde L, Manel N, et al. Specific microbiota direct the differentiation of IL-17-producing T-helper cells in the mucosa of the small intestine. Cell Host Microbe. 2008;4:337–349. 122. Lakhdari O, Cultrone A, Tap J, et al. Functional metagenomics: a high throughput screening method to decipher microbiota-driven NF-kappaB modulation in the human gut. PLoS One. 2010;5. 123. Clarke TB, Davis KM, Lysenko ES, et al. Recognition of peptidoglycan from the microbiota by Nod1 enhances systemic innate immunity. Nat Med. 2010;16:228–231. 124. Mazmanian SK, Liu CH, Tzianabos AO, et al. An immunomodulatory molecule of symbiotic bacteria directs maturation of the host immune system. Cell. 2005;122:107–118. 125. Maslowski KM, Vieira AT, Ng A, et al. Regulation of inflammatory responses by gut microbiota and chemoattractant receptor GPR43. Nature. 2009;461:1282–1286. 126. Sokol H, Lepage P, Seksik P, et al. Molecular comparison of dominant microbiota associated with injured versus healthy mucosa in ulcerative colitis. Gut. 2007;56:152–154. 127. Sokol H, Seksik P, Rigottier-Gois L, et al. Specificities of the fecal microbiota in inflammatory bowel disease. Inflamm Bowel Dis. 2006; 12:106–111. 128. Swidsinski A, Weber J, Loening-Baucke V, et al. Spatial organization and composition of the mucosal flora in patients with inflammatory bowel disease. J Clin Microbiol. 2005;43:3380–3389. 129. Darfeuille-Michaud A, Neut C, Barnich N, et al. Presence of adherent Escherichia coli strains in ileal mucosa of patients with Crohn’s disease. Gastroenterology. 1998;115:1405–1413. 130. Kirkwood CD, Wagner J, Boniface K, et al. Mycobacterium avium subspecies paratuberculosis in children with early-onset Crohn’s disease. Inflamm Bowel Dis. 2009;15:1643–1655. 131. Ruseler-van Embden JG, Both-Patoir HC. Anaerobic gram-negative faecal flora in patients with Crohn’s disease and healthy subjects. Antonie Van Leeuwenhoek. 1983;49:125–132. 132. Martin HM, Campbell BJ, Hart CA, et al. Enhanced Escherichia coli adherence and invasion in Crohn’s disease and colon cancer. Gastroenterology. 2004;127:80–93. 133. Swidsinski A, Ladhoff A, Pernthaler A, et al. Mucosal flora in inflammatory bowel disease. Gastroenterology. 2002;122:44–54. 134. Kleessen B, Kroesen AJ, Buhr HJ, et al. Mucosal and invading bacteria in patients with inflammatory bowel disease compared with controls. Scand J Gastroenterol. 2002;37:1034–1041. 135. Schultsz C, Van Den Berg FM, Ten Kate FW, et al. The intestinal mucus layer from patients with inflammatory bowel disease harbors high numbers of bacteria compared with controls. Gastroenterology. 1999;117:1089–1097. 136. Conte MP, Schippa S, Zamboni I, et al. Gut-associated bacterial microbiota in paediatric patients with inflammatory bowel disease. Gut. 2006;55:1760–1767. 137. Swidsinski A, Loening-Baucke V, Lochs H, et al. Spatial organization of bacterial flora in normal and inflamed intestine: a fluorescence in situ hybridization study in mice. World J Gastroenterol. 2005;11:1131–1140. 138. Prindiville T, Cantrell M, Wilson KH. Ribosomal DNA sequence analysis of mucosa-associated bacteria in Crohn’s disease. Inflamm Bowel Dis. 2004;10:824–833. 139. Gophna U, Charlebois RL, Doolittle WF. Ancient lateral gene transfer in the evolution of Bdellovibrio bacteriovorus. Trends Microbiol. 2006;14:64–69.

385


De Cruz et al

140. Ohkusa T, Sato N, Ogihara T, et al. Fusobacterium varium localized in the colonic mucosa of patients with ulcerative colitis stimulates species-specific antibody. J Gastroenterol Hepatol. 2002;17:849–853. 141. Matsuda H, Fujiyama Y, Andoh A, et al. Characterization of antibody responses against rectal mucosa-associated bacterial flora in patients with ulcerative colitis. J Gastroenterol Hepatol. 2000;15: 61–68. 142. Scanlan PD, Shanahan F, O’Mahony C, et al. Culture-independent analyses of temporal variation of the dominant fecal microbiota and targeted bacterial subgroups in Crohn’s disease. J Clin Microbiol. 2006;44:3980–3988. 143. Ott SJ, Musfeldt M, Wenderoth DF, et al. Reduction in diversity of the colonic mucosa associated bacterial microflora in patients with active inflammatory bowel disease. Gut. 2004;53:685–693. 144. Dicksved J, Halfvarson J, Rosenquist M, et al. Molecular analysis of the gut microbiota of identical twins with Crohn’s disease. ISME J. 2008;2:716–727. 145. Walker AW, Sanderson JD, Churcher C, et al. High-throughput clone library analysis of the mucosa-associated microbiota reveals dysbiosis and differences between inflamed and non-inflamed regions of the intestine in inflammatory bowel disease. BMC Microbiol. 2011;11:7. 146. Martinez C, Antolin M, Santos J, et al. Unstable composition of the fecal microbiota in ulcerative colitis during clinical remission. Am J Gastroenterol. 2008;103:643–648. 147. Ott SJ, Plamondon S, Hart A, et al. Dynamics of the mucosa-associated flora in ulcerative colitis patients during remission and clinical relapse. J Clin Microbiol. 2008;46:3510–3513. 148. Noor SO, Ridgway K, Scovell L, et al. Ulcerative colitis and irritable bowel patients exhibit distinct abnormalities of the gut microbiota. BMC Gastroenterol. 2010;10:134. 149. Gophna U, Sommerfeld K, Gophna S, et al. Differences between tissue-associated intestinal microfloras of patients with Crohn’s disease and ulcerative colitis. J Clin Microbiol. 2006;44:4136–4141. 150. Swidsinski A, Loening-Baucke V, Vaneechoutte M, et al. Active Crohn’s disease and ulcerative colitis can be specifically diagnosed and monitored based on the biostructure of the fecal flora. Inflamm Bowel Dis. 2008;14:147–161. 151. Schwiertz A, Jacobi M, Frick JS, et al. Microbiota in pediatric inflammatory bowel disease. J Pediatr. 2010;157:240–244. 152. Martinez-Medina M, Aldeguer X, Gonzalez-Huix F, et al. Abnormal microbiota composition in the ileocolonic mucosa of Crohn’s disease patients as revealed by polymerase chain reaction-denaturing gradient gel electrophoresis. Inflamm Bowel Dis. 2006;12:1136–1145. 153. Willing B, Halfvarson J, Dicksved J, et al. Twin studies reveal specific imbalances in the mucosa-associated microbiota of patients with ileal Crohn’s disease. Inflamm Bowel Dis. 2009;15:653–660. 154. Hayashi H, Sakamoto M, Kitahara M, et al. Molecular analysis of fecal microbiota in elderly individuals using 16S rDNA library and T-RFLP. Microbiol Immunol. 2003;47:557–570. 155. Kang S, Denman SE, Morrison M, et al. Dysbiosis of fecal microbiota in Crohn’s disease patients as revealed by a custom phylogenetic microarray. Inflamm Bowel Dis. 2010;16:2034–2042. 156. Mondot S, Kang S, Furet JP, et al. Highlighting new phylogenetic specificities of crohn’s disease microbiota. Inflamm Bowel Dis. 2010; 17:185–192. 157. Aguirre De Carcer D, Cuiv PO, Wang T, et al. Application of numerical ecology methods to microarray data reveals obscured patterns in the mucosa associated microbial community of the human colorectum. J Gastroenterol Hepatol. 2009;24:A241. 158. Andoh A, Sakata S, Koizumi Y, et al. Terminal restriction fragment length polymorphism analysis of the diversity of fecal microbiota in patients with ulcerative colitis. Inflamm Bowel Dis. 2007;13:955–962. 159. Christophersen CT, Kang S, McSweeney CS, et al. The gut microflora of individuals with ulcerative colitis (remission or mild) differs from healthy individuals. J Gastroenterol Hepatol. 2009;24:A320. 160. Dabard J, Bridonneau C, Phillipe C, et al. Ruminococcin A, a new lantibiotic produced by a Ruminococcus gnavus strain isolated from human feces. Appl Environ Microbiol. 2001;67:4111–4118. 161. Png CW, Linden SK, Gilshenan KS, et al. Mucolytic bacteria with increased prevalence in IBD mucosa augment in vitro utilization

386

162. 163. 164. 165. 166.

167. 168. 169. 170. 171. 172. 173. 174.

175. 176. 177. 178. 179. 180. 181. 182. 183. 184.

of mucin by other bacteria. Am J Gastroenterol. 2010;105: 2420–2428. Giaffer MH, Holdsworth CD, Duerden BI. Virulence properties of Escherichia coli strains isolated from patients with inflammatory bowel disease. Gut. 1992;33:646–650. Kotlowski R, Bernstein CN, Sepehri S, et al. High prevalence of Escherichia coli belonging to the B2þD phylogenetic group in inflammatory bowel disease. Gut. 2007;56:669–675. Mylonaki M, Rayment NB, Rampton DS, et al. Molecular characterization of rectal mucosa-associated bacterial flora in inflammatory bowel disease. Inflamm Bowel Dis. 2005;11:481–487. Darfeuille-Michaud A, Boudeau J, Bulois P, et al. High prevalence of adherent-invasive Escherichia coli associated with ileal mucosa in Crohn’s disease. Gastroenterology. 2004;127:412–421. Fujita H, Eishi Y, Ishige I, et al. Quantitative analysis of bacterial DNA from Mycobacteria spp., Bacteroides vulgatus, and Escherichia coli in tissue samples from patients with inflammatory bowel diseases. J Gastroenterol. 2002;37:509–516. Mangin I, Bonnet R, Seksik P, et al. Molecular inventory of faecal microflora in patients with Crohn’s disease. FEMS Microbiol Ecol. 2004;50:25–36. Giaffer MH, Holdsworth CD, Duerden BI. The assessment of faecal flora in patients with inflammatory bowel disease by a simplified bacteriological technique. J Med Microbiol. 1991;35:238–243. Bullock NR, Booth JC, Gibson GR. Comparative composition of bacteria in the human intestinal microflora during remission and active ulcerative colitis. Curr Issues Intest Microbiol. 2004;5:59–64. Kuehbacher T, Rehman A, Lepage P, et al. Intestinal TM7 bacterial phylogenies in active inflammatory bowel disease. J Med Microbiol. 2008;57:1569–1576. Joossens M, Huys G, Cnockaert M, et al. Dysbiosis of the faecal microbiota in patients with Crohn’s disease and their unaffected relatives. Gut. 2011;60:631–637. Dalsiel TK. Chronic intestinal enteritis. Br Med J 1913:1068–1070. Feller M, Huwiler K, Stephan R, et al. Mycobacterium avium subspecies paratuberculosis and Crohn’s disease: a systematic review and meta-analysis. Lancet Infect Dis. 2007;7:607–613. Abubakar I, Myhill D, Aliyu SH, et al. Detection of Mycobacterium avium subspecies paratuberculosis from patients with Crohn’s disease using nucleic acid-based techniques: a systematic review and metaanalysis. Inflamm Bowel Dis. 2008;14:401–410. Frank DN. Mycobacterium avium subspecies paratuberculosis and Crohn’s disease. Lancet Infect Dis. 2008;8:345; author reply 346. Greenstein RJ, Su L, Haroutunian V, et al. On the action of methotrexate and 6-mercaptopurine on M. avium subspecies paratuberculosis. PLoS One. 2007;2:e161. Greenstein RJ, Su L, Shahidi A, et al. On the action of 5-amino-salicylic acid and sulfapyridine on M. avium including subspecies paratuberculosis. PLoS One. 2007;2:e516. Borgaonkar M, MacIntosh D, Fardy J, et al. Anti-tuberculous therapy for maintaining remission of Crohn’s disease. Cochrane Database Syst Rev. 2000;CD000299. Selby W, Pavli P, Crotty B, et al. Two-year combination antibiotic therapy with clarithromycin, rifabutin, and clofazimine for Crohn’s disease. Gastroenterology. 2007;132:2313–2319. Lederman E, Neut C, Desreumaux P. Bacterial overgrowth in the neoterminal ileum after ileocolonic resection for Crohn’s disease. Gastroenterology. 1997;112. Neut C, Bulois P, Desreumaux P, et al. Changes in the bacterial flora of the neoterminal ileum after ileocolonic resection for Crohn’s disease. Am J Gastroenterol. 2002;97:939–946. Rolhion N, Darfeuille-Michaud A. Adherent-invasive Escherichia coli in inflammatory bowel disease. Inflamm Bowel Dis. 2007;13: 1277–1283. Kaper JB, Nataro JP, Mobley HL. Pathogenic Escherichia coli. Nat Rev Microbiol. 2004;2:123–140. Boudeau J, Barnich N, Darfeuille-Michaud A. Type 1 pili-mediated adherence of Escherichia coli strain LF82 isolated from Crohn’s disease is involved in bacterial invasion of intestinal epithelial cells. Mol Microbiol. 2001;39:1272–1284.


185. Barnich N, Boudeau J, Claret L, et al. Regulatory and functional cooperation of flagella and type 1 pili in adhesive and invasive abilities of AIEC strain LF82 isolated from a patient with Crohn’s disease. Mol Microbiol. 2003;48:781–794. 186. Claret L, Miquel S, Vieille N, et al. The flagellar sigma factor FliA regulates adhesion and invasion of Crohn disease-associated Escherichia coli via a cyclic dimeric GMP-dependent pathway. J Biol Chem. 2007;282:33275–33283. 187. Rolhion N, Carvalho FA, Darfeuille-Michaud A. OmpC and the sigma(E) regulatory pathway are involved in adhesion and invasion of the Crohn’s disease-associated Escherichia coli strain LF82. Mol Microbiol. 2007;63:1684–1700. 188. Barnich N, Bringer MA, Claret L, et al. Involvement of lipoprotein NlpI in the virulence of adherent invasive Escherichia coli strain LF82 isolated from a patient with Crohn’s disease. Infect Immun. 2004;72:2484–2493. 189. Bringer MA, Rolhion N, Glasser AL, et al. The oxidoreductase DsbA plays a key role in the ability of the Crohn’s disease-associated adherent-invasive Escherichia coli strain LF82 to resist macrophage killing. J Bacteriol. 2007;189:4860–48671. 190. Pineton de Chambrun G, Colombel JF, Poulain D, et al. Pathogenic agents in inflammatory bowel diseases. Curr Opin Gastroenterol. 2008;24:440–447. 191. Lapaquette P, Glasser AL, Huett A, et al. Crohn’s disease-associated adherent-invasive E. coli are selectively favoured by impaired autophagy to replicate intracellularly. Cell Microbiol. 2010;12: 99–113. 192. Barnich N, Carvalho FA, Glasser AL, et al. CEACAM6 acts as a receptor for adherent-invasive E. coli, supporting ileal mucosa colonization in Crohn disease. J Clin Invest. 2007;117:1566–1574. 193. Glasser AL, Boudeau J, Barnich N, et al. Adherent invasive Escherichia coli strains from patients with Crohn’s disease survive and replicate within macrophages without inducing host cell death. Infect Immun. 2001;69:5529–5537. 194. Peeters H, Bogaert S, Laukens D, et al. CARD15 variants determine a disturbed early response of monocytes to adherent-invasive Escherichia coli strain LF82 in Crohn’s disease. Int J Immunogenet. 2007; 34:181–191. 195. Wagner J, Short K, Catto-Smith AG, et al. Identification and characterisation of Pseudomonas 16S ribosomal DNA from ileal biopsies of children with Crohn’s disease. PLoS One. 2008;3:e3578. 196. Parent K, Mitchell P. Cell wall-defective variants of pseudomonaslike (group Va) bacteria in Crohn’s disease. Gastroenterology. 1978; 75:368–372. 197. Sutton CL, Kim J, Yamane A, et al. Identification of a novel bacterial sequence associated with Crohn’s disease. Gastroenterology. 2000;119:23–31. 198. Spivak J, Landers CJ, Vasiliauskas EA, et al. Antibodies to I2 predict clinical response to fecal diversion in Crohn’s disease. Inflamm Bowel Dis. 2006;12:1122–1130. 199. Madi A, Lakhdari O, Blottiere HM, et al. The clinical Pseudomonas fluorescens MFN1032 strain exerts a cytotoxic effect on epithelial intestinal cells and induces Interleukin-8 via the AP-1 signaling pathway. BMC Microbiol. 2010;10:215. 200. Kallinowski F, Wassmer A, Hofmann MA, et al. Prevalence of enteropathogenic bacteria in surgically treated chronic inflammatory bowel disease. Hepatogastroenterology. 1998;45:1552–1558. 201. Lamps LW, Madhusudhan KT, Havens JM, et al. Pathogenic Yersinia DNA is detected in bowel and mesenteric lymph nodes from patients with Crohn’s disease. Am J Surg Pathol. 2003;27:220–227. 202. Huijsdens XW, Linskens RK, Taspinar H, et al. Listeria monocytogenes and inflammatory bowel disease: detection of Listeria species in intestinal mucosal biopsies by real-time PCR. Scand J Gastroenterol. 2003;38:332–333. 203. Chen W, Li D, Paulus B, et al. Detection of Listeria monocytogenes by polymerase chain reaction in intestinal mucosal biopsies from patients with inflammatory bowel disease and controls. J Gastroenterol Hepatol. 2000;15:1145–1150. 204. Brown WR. Listeria: the latest putative pathogenetic microorganism in Crohn’s disease. Gastroenterology. 1995;108:1589–1590.


205. Sim WH, Wagner J, Cameron DJ, et al. Novel Burkholderiales 23S rRNA genes identified in ileal biopsy samples from children: preliminary evidence that a subtype is associated with perianal Crohn’s disease. J Clin Microbiol. 2010;48:1939–1942. 206. Chow J, Mazmanian SK. A pathobiont of the microbiota balances host colonization and intestinal inflammation. Cell Host Microbe. 2010;7:265–276. 207. Man SM, Zhang L, Day AS, et al. Detection of enterohepatic and gastric helicobacter species in fecal specimens of children with Crohn’s disease. Helicobacter. 2008;13:234–238. 208. Oliveira AG, Rocha GA, Rocha AM, et al. Isolation of Helicobacter pylori from the intestinal mucosa of patients with Crohn’s disease. Helicobacter. 2006;11:2–9. 209. Cahill RJ, Foltz CJ, Fox JG, et al. Inflammatory bowel disease: an immunity-mediated condition triggered by bacterial infection with Helicobacter hepaticus. Infect Immun. 1997;65:3126–3131. 210. Laharie D, Asencio C, Asselineau J, et al. Association between entero-hepatic Helicobacter species and Crohn’s disease: a prospective cross-sectional study. Aliment Pharmacol Ther. 2009;30: 283–293. 211. Cadwell K, Patel KK, Maloney NS, et al. Virus-plus-susceptibility gene interaction determines Crohn’s disease gene Atg16L1 phenotypes in intestine. Cell. 2010;141:1135–1145. 212. Peterson DA, Turnbaugh PJ. A microbe-dependent viral key to Crohn’s box. Sci Transl Med. 2010;2:43ps39. 213. Smith MS, Wakefield AJ. Viral association with Crohn’s disease. Ann Med. 1993;25:557–561. 214. Rehaume LM, Jouault T, Chamaillard M. Lessons from the inflammasome: a molecular sentry linking Candida and Crohn’s disease. Trends Immunol. 2010;31:171–175. 215. Standaert-Vitse A, Sendid B, Joossens M, et al. Candida albicans colonization and ASCA in familial Crohn’s disease. Am J Gastroenterol. 2009;104:1745–1753. 216. Ott SJ, Kuhbacher T, Musfeldt M, et al. Fungi and inflammatory bowel diseases: Alterations of composition and diversity. Scand J Gastroenterol. 2008;43:831–841. 217. van der Waaij LA, Harmsen HJ, Madjipour M, et al. Bacterial population analysis of human colon and terminal ileum biopsies with 16S rRNA-based fluorescent probes: commensal bacteria live in suspension and have no direct contact with epithelial cells. Inflamm Bowel Dis. 2005;11:865–871. 218. Bibiloni R, Tandon P, Vargas-Voracka F, et al. Differential clustering of bowel biopsy-associated bacterial profiles of specimens collected in Mexico and Canada: what do these profiles represent? J Med Microbiol. 2008;57:111–117. 219. Ian MC, Temitope OK, Tamar R-K, et al. T2065 Molecular characterization of the fecal and mucosal-associated intestinal microbiota in patients with diarrhea-predominant IBS and healthy subjects. Gastroenterology. 2010;138:S–624. 220. Lepage P, Mondot S, Vasquez N et al, Bacterial Recolonization after Gut Resection for Crohn’s DIsease: Uniformity as an Essential Factor Toward Remission. Gut; 2009:58 (Suppl II) OPO20. 221. Ahmed S, Macfarlane GT, Fite A, et al. Mucosa-associated bacterial diversity in relation to human terminal ileum and colonic biopsy samples. Appl Environ Microbiol. 2007;73:7435–7442. 222. Bibiloni R, Mangold M, Madsen KL, et al. The bacteriology of biopsies differs between newly diagnosed, untreated, Crohn’s disease and ulcerative colitis patients. J Med Microbiol. 2006;55: 1141–1149. 223. Valerio I, Monica Proietti C, Valentina T, et al. T1811 Dominant Intestinal Mucosa-Associated Microbiota in Pediatric Patients With Inflammatory Bowel Disease. Gastroenterology. 2010;138: S583–S584. 224. Hayashi H, Takahashi R, Nishi T, et al. Molecular analysis of jejunal, ileal, caecal and recto-sigmoidal human colonic microbiota using 16S rRNA gene libraries and terminal restriction fragment length polymorphism. J Med Microbiol. 2005;54: 1093–1101. 225. Wang X, Heazlewood SP, Krause DO, et al. Molecular characterization of the microbial species that colonize human ileal and colonic

387

De Cruz et al

226.

227.

228. 229.

230.

231. 232.

233.

234. 235.

236. 237. 238.

239. 240. 241. 242. 243. 244. 245.

mucosa by using 16S rDNA sequence analysis. J Appl Microbiol. 2003;95:508–5020. de Carcer DA, Cuiv PO, Wang T, et al. Numerical ecology validates a biogeographical distribution and gender-based effect on mucosaassociated bacteria along the human colon. ISME J. 2010; [Epub ahead of print]. Seungha K, Arun G, Josef W, et al. T1805 Analysis of the Mucosal Microbiota From Inflammatory Bowel Disease Biopsy Tissues Using a Custom 16s rRNA Based Phylogenetic Microarray. Gastroenterology. 2010;138:S–582. Zhang M, Liu B, Zhang Y, et al. Structural shifts of mucosa-associated lactobacilli and Clostridium leptum subgroup in patients with ulcerative colitis. J Clin Microbiol. 2007;45:496–500. Seksik P, Lepage P, de la Cochetiere MF, et al. Search for localized dysbiosis in Crohn’s disease ulcerations by temporal temperature gradient gel electrophoresis of 16S rRNA. J Clin Microbiol. 2005;43: 4654–4658. Vasquez N, Mangin I, Lepage P, et al. Patchy distribution of mucosal lesions in ileal Crohn’s disease is not linked to differences in the dominant mucosa-associated bacteria: a study using fluorescence in situ hybridization and temporal temperature gradient gel electrophoresis. Inflamm Bowel Dis. 2007;13:684–692. Sepehri S, Kotlowski R, Bernstein CN, et al. Microbial diversity of inflamed and noninflamed gut biopsy tissues in inflammatory bowel disease. Inflamm Bowel Dis. 2007;13:675–683. Rajilic-Stojanovic M, Heilig HG, Molenaar D, et al. Development and application of the human intestinal tract chip, a phylogenetic microarray: analysis of universally conserved phylotypes in the abundant microbiota of young and elderly adults. Environ Microbiol. 2009;11:1736–1751. Matsuki T, Watanabe K, Fujimoto J, et al. Use of 16S rRNA genetargeted group-specific primers for real-time PCR analysis of predominant bacteria in human feces. Appl Environ Microbiol. 2004;70: 7220–7228. Ley RE, Turnbaugh PJ, Klein S, et al. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444:1022–1023. Andoh A, Imaeda H, Aomatsu T, et al. Comparison of the fecal microbiota profiles between ulcerative colitis and Crohn’s disease using terminal restriction fragment length polymorphism analysis. J Gastroenterol. 2011; [Epub ahead of print]. Madden MV, McIntyre AS, Nicholls RJ. Double-blind crossover trial of metronidazole versus placebo in chronic unremitting pouchitis. Dig Dis Sci. 1994;39:1193–1196. Gionchetti P, Rizzello F, Helwig U, et al. Prophylaxis of pouchitis onset with probiotic therapy: a double-blind, placebo-controlled trial. Gastroenterology. 2003;124:1202–1209. Nasmyth DG, Godwin PG, Dixon MF, et al. Ileal ecology after pouch-anal anastomosis or ileostomy. A study of mucosal morphology, fecal bacteriology, fecal volatile fatty acids, and their interrelationship. Gastroenterology. 1989;96:817–824. Smith FM, Coffey JC, Kell MR, et al. A characterization of anaerobic colonization and associated mucosal adaptations in the undiseased ileal pouch. Colorectal Dis. 2005;7:563–570. Loeschke K, Bolkert T, Kiefhaber P, et al. Bacterial overgrowth in ileal reservoirs (Koch pouch): extended functional studies. Hepatogastroenterology. 1980;27:310–316. McLaughlin SD, Walker AW, Churcher C, et al. The bacteriology of pouchitis: a molecular phylogenetic analysis using 16S rRNA gene cloning and sequencing. Ann Surg. 2010;252:90–98. Komanduri S, Gillevet PM, Sikaroodi M, et al. Dysbiosis in pouchitis: evidence of unique microfloral patterns in pouch inflammation. Clin Gastroenterol Hepatol. 2007;5:352–360. Zella GC, Hait EJ, Glavan T, et al. Distinct microbiome in pouchitis compared to healthy pouches in ulcerative colitis and familial adenomatous polyposis. Inflamm Bowel Dis. 2010; [Epub ahead of print]. Tringe SG, Rubin EM. Metagenomics: DNA sequencing of environmental samples. Nat Rev Genet. 2005;6:805–814. Kurokawa K, Itoh T, Kuwahara T, et al. Comparative metagenomics revealed commonly enriched gene sets in human gut microbiomes. DNA Res. 2007;14:169–181.

388


246. Tasse L, Bercovici J, Pizzut-Serin S, et al. Functional metagenomics to mine the human gut microbiome for dietary fiber catabolic enzymes. Genome Res. 2010;20:1605–1612. 247. Rehman A, Lepage P, Nolte A, et al. Transcriptional activity of the dominant gut mucosal microbiota in chronic inflammatory bowel disease patients. J Med Microbiol. 2010;59:1114–1122. 248. Mondot S, Lepage P, Coehlo J, et al. P0904 Functionality of the gut mucosal microbiota: an -omics vision of the Crohn’s disease microbiome. Gut. 2010;59:A289. 249. Kussmann M, Raymond F, Affolter M. OMICS-driven biomarker discovery in nutrition and health. J Biotechnol. 2006;124:758–787. 250. Klaassens ES, de Vos WM, Vaughan EE. Metaproteomics approach to study the functionality of the microbiota in the human infant gastrointestinal tract. Appl Environ Microbiol. 2007;73:1388–1392. 251. Verberkmoes NC, Russell AL, Shah M, et al. Shotgun metaproteomics of the human distal gut microbiota. ISME J. 2009;3: 179–189. 252. Ang CS, Phung J, Nice EC. The discovery and validation of colorectal cancer biomarkers. Biomed Chromatogr. 2011;25:82–99. 253. Horgan RP, Clancy OH, Myers JE, et al. An overview of proteomic and metabolomic technologies and their application to pregnancy research. BJOG. 2009;116:173–181. 254. Nicholson JK, Wilson ID. Opinion: understanding /global/ systems biology: metabonomics and the continuum of metabolism. Nat Rev Drug Discov. 2003;2:668–676. 255. Bjerrum JT, Nielsen OH, Hao F, et al. Metabonomics in ulcerative colitis: diagnostics, biomarker identification, and insight into the pathophysiology. J Proteome Res. 2010;9:954–962. 256. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447:661–678. 257. Sladek R, Rocheleau G, Rung J, et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature. 2007;445: 881–885. 258. Holmes E, Loo RL, Stamler J, et al. Human metabolic phenotype diversity and its association with diet and blood pressure. Nature. 2008;453:396–400. 259. Bictash M, Ebbels TM, Chan Q, et al. Opening up the ‘‘Black Box’’: metabolic phenotyping and metabolome-wide association studies in epidemiology. J Clin Epidemiol. 2010;63:970–979. 260. Slupsky CM, Rankin KN, Wagner J. Investigations of the effects of gender, diurnal variation, and age in human urinary metabolomic profiles. Anal Chem. 2007;79:6995–7004. 261. Psihogios NG, Gazi IF, Elisaf MS. Gender-related and age-related urinalysis of healthy subjects by NMR-based metabonomics. NMR Biomed. 2008;21:195–207. 262. Walsh MC, Brennan L, Malthouse JP. Effect of acute dietary standardization on the urinary, plasma, and salivary metabolomic profiles of healthy humans. Am J Clin Nutr. 2006;84:531–539. 263. Lenz EM, Bright J, Wilson ID. A 1H NMR-based metabonomic study of urine and plasma samples obtained from healthy human subjects. J Pharm Biomed Anal. 2003;33:1103–1115. 264. Varma S, Eskin MN, Bird R, et al. Potential of magnetic resonance spectroscopy in assessing the effect of fatty acids on inflammatory bowel disease in an animal model. Lipids. 2010;45:843–854. 265. Stella C, Beckwith-Hall B, Cloarec O. Susceptibility of human metabolic phenotypes to dietary modulation. J Proteome Res. 2006;5: 2780–2788. 266. Romick-Rosendale LE, Goodpaster AM, Hanwright PJ, et al. NMRbased metabonomics analysis of mouse urine and fecal extracts following oral treatment with the broad-spectrum antibiotic enrofloxacin (Baytril). Magn Reson Chem. 2009;47(suppl 1):S36–46. 267. Jansson J, Willing B, Lucio M, et al. Metabolomics reveals metabolic biomarkers of Crohn’s disease. PLoS One. 2009;4:e6386. 268. Marchesi JR, Holmes E, Khan F, et al. Rapid and noninvasive metabonomic characterization of inflammatory bowel disease. J Proteome Res. 2007;6:546–551. 269. Williams RE, Eyton-Jones HW, Farnworth MJ. Effect of intestinal microflora on the urinary metabolic profile of rats: a 1H-nuclear magnetic resonance spectroscopy study. Xenobiotica. 2002;32: 783–794.


270. Nicholls AW, Mortishire-Smith RJ, Nicholson JK. NMR spectroscopic-based metabonomic studies of urinary metabolite variation in acclimatizing germ-free rats. Chem Res Toxicol. 2003;16:1395–404. 271. Williams HR, Cox IJ, Walker DG, et al. Characterization of inflammatory bowel disease with urinary metabolic profiling. Am J Gastroenterol. 2009;104:1435–1444. 272. Balasubramanian K, Kumar S, Singh RR, et al. Metabolism of the colonic mucosa in patients with inflammatory bowel diseases: an in vitro proton magnetic resonance spectroscopy study. Magn Reson Imaging. 2009;27:79–86. 273. Bezabeh T, Somorjai RL, Smith IC, et al. The use of 1H magnetic resonance spectroscopy in inflammatory bowel diseases: distinguishing ulcerative colitis from Crohn’s disease. Am J Gastroenterol. 2001;96:442–448. 274. Sharma U, Singh RR, Ahuja V, et al. Similarity in the metabolic profile in macroscopically involved and un-involved colonic mucosa in patients with inflammatory bowel disease: an in vitro proton ((1)H) MR spectroscopy study. Magn Reson Imaging. 2010;28: 1022–1029. 275. Mueller S, Saunier K, Hanisch C, et al. Differences in fecal microbiota in different European study populations in relation to age, gender, and country: a cross-sectional study. Appl Environ Microbiol. 2006;72:1027–1033. 276. Lay C, Rigottier-Gois L, Holmstrom K, et al. Colonic microbiota signatures across five northern European countries. Appl Environ Microbiol. 2005;71:4153–4155. 277. Sepp E, Julge K, Vasar M, et al. Intestinal microflora of Estonian and Swedish infants. Acta Paediatr. 1997;86:956–961. 278. Mah KW, Sangsupawanich P, Tunyapanit W, et al. Gut microbiota of children living in rural south Thailand and urban Singapore. Allergol Int. 2008;57:65–71. 279. De Filippo C, Cavalieri D, Di Paola M, et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci U S A. 2010;107: 14691–14696. 280. Flint HJ, Duncan SH, Scott KP, et al. Interactions and competition within the microbial community of the human colon: links between diet and health. Environ Microbiol. 2007;9:1101–1111. 281. Bernstein CN, Shanahan F. Disorders of a modern lifestyle: reconciling the epidemiology of inflammatory bowel diseases. Gut. 2008;57: 1185–1191. 282. Thia KT, Loftus EV Jr, Sandborn WJ, et al. An update on the epidemiology of inflammatory bowel disease in Asia. Am J Gastroenterol. 2008;103:3167–3182. 283. Ley RE. Obesity and the human microbiome. Curr Opin Gastroenterol. 2010;26:5–11. 284. Cani PD, Possemiers S, Van de Wiele T, et al. Changes in gut microbiota control inflammation in obese mice through a mechanism involving GLP-2-driven improvement of gut permeability. Gut. 2009; 58:1091–1103. 285. Nguyen KA, Cao Y, Chen JR, et al., Dietary fiber enhances a tumor suppressor signaling pathway in the gut. Ann Surg. 2006;243: 619–625; discussion 25–27. 286. Roy CC, Kien CL, Bouthillier L, et al. Short-chain fatty acids: ready for prime time? Nutr Clin Pract. 2006;21:351–366. 287. Macfarlane S, Macfarlane GT. Regulation of short-chain fatty acid production. Proc Nutr Soc. 2003;62:67–72. 288. Vanhoutvin SA, Troost FJ, Hamer HM, et al. Butyrate-induced transcriptional changes in human colonic mucosa. PLoS One. 2009;4: e6759. 289. Louis P, Scott KP, Duncan SH, et al. Understanding the effects of diet on bacterial metabolism in the large intestine. J Appl Microbiol. 2007;102:1197–1208. 290. Barcenilla A, Pryde SE, Martin JC, et al. Phylogenetic relationships of butyrate-producing bacteria from the human gut. Appl Environ Microbiol. 2000;66:1654–1661. 291. Hold GL, Schwiertz A, Aminov RI, et al. Oligonucleotide probes that detect quantitatively significant groups of butyrate-producing bacteria in human feces. Appl Environ Microbiol. 2003;69: 4320–4324.


292. Aminov RI, Walker AW, Duncan SH, et al. Molecular diversity, cultivation, and improved detection by fluorescent in situ hybridization of a dominant group of human gut bacteria related to Roseburia spp. or Eubacterium rectale. Appl Environ Microbiol. 2006;72: 6371–6376. 293. Van Loo J. The specificity of the interaction with intestinal bacterial fermentation by prebiotics determines their physiological efficacy. Nutr Res Rev. 2004;17:89–98. 294. Sokol H, Seksik P, Furet JP, et al. Low counts of Faecalibacterium prausnitzii in colitis microbiota. Inflamm Bowel Dis. 2009;15: 1183–1189. 295. Kanauchi O, Suga T, Tochihara M, et al. Treatment of ulcerative colitis by feeding with germinated barley foodstuff: first report of a multicenter open control trial. J Gastroenterol. 2002;37 Suppl 14: 67–72. 296. Breuer RI, Soergel KH, Lashner BA, et al. Short chain fatty acid rectal irrigation for left-sided ulcerative colitis: a randomised, placebo controlled trial. Gut. 1997;40:485–491. 297. Galvez J, Rodriguez-Cabezas ME, Zarzuelo A. Effects of dietary fiber on inflammatory bowel disease. Mol Nutr Food Res. 2005;49: 601–608. 298. Attene-Ramos MS, Wagner ED, Gaskins HR, et al. Hydrogen sulfide induces direct radical-associated DNA damage. Mol Cancer Res. 2007;5:455–459. 299. Gardiner KR, Halliday MI, Barclay GR, et al. Significance of systemic endotoxaemia in inflammatory bowel disease. Gut. 1995;36: 897–901. 300. Roediger WE, Moore J, Babidge W. Colonic sulfide in pathogenesis and treatment of ulcerative colitis. Dig Dis Sci. 1997;42:1571–1579. 301. Sharma S, O’Keefe SJ. Environmental influences on the high mortality from colorectal cancer in African Americans. Postgrad Med J. 2007;83:583–589. 302. O’Keefe SJ. The African way of life and colon cancer risk. Am J Gastroenterol. 2001;96:3220–3221. 303. O’Keefe SJ. Nutrition and colonic health: the critical role of the microbiota. Curr Opin Gastroenterol. 2008;24:51–58. 304. Magee EA, Richardson CJ, Hughes R, et al. Contribution of dietary protein to sulfide production in the large intestine: an in vitro and a controlled feeding study in humans. Am J Clin Nutr. 2000;72: 1488–1494. 305. O’Keefe SJ, Chung D, Mahmoud N, et al. Why do African Americans get more colon cancer than Native Africans? J Nutr. 2007;137: 175S–182S. 306. O’Keefe SJ, Ou J, Aufreiter S, et al. Products of the colonic microbiota mediate the effects of diet on colon cancer risk. J Nutr. 2009; 139:2044–2048. 307. Hehemann JH, Correc G, Barbeyron T, et al. Transfer of carbohydrate-active enzymes from marine bacteria to Japanese gut microbiota. Nature. 2010;464:908–912. 308. Sakamoto N, Kono S, Wakai K, et al. Dietary risk factors for inflammatory bowel disease: a multicenter case-control study in Japan. Inflamm Bowel Dis. 2005;11:154–163. 309. Amre DK, D’Souza S, Morgan K, et al. Imbalances in dietary consumption of fatty acids, vegetables, and fruits are associated with risk for Crohn’s disease in children. Am J Gastroenterol. 2007;102: 2016–2025. 310. Geerling BJ, Dagnelie PC, Badart-Smook A, et al. Diet as a risk factor for the development of ulcerative colitis. Am J Gastroenterol. 2000;95:1008–1013. 311. Jowett SL, Seal CJ, Pearce MS, et al. Influence of dietary factors on the clinical course of ulcerative colitis: a prospective cohort study. Gut. 2004;53:1479–1484. 312. Tragnone A, Valpiani D, Miglio F, et al. Dietary habits as risk factors for inflammatory bowel disease. Eur J Gastroenterol Hepatol. 1995;7:47–51. 313. Persson PG, Ahlbom A, Hellers G. Diet and inflammatory bowel disease: a case-control study. Epidemiology. 1992;3:47–52. 314. Loftus EV Jr. Clinical epidemiology of inflammatory bowel disease: incidence, prevalence, and environmental influences. Gastroenterology. 2004;126:1504–1517.

389

De Cruz et al

315. Gilat T, Hacohen D, Lilos P, et al. Childhood factors in ulcerative colitis and Crohn’s disease. An international cooperative study. Scand J Gastroenterol. 1987;22:1009–1024. 316. Russel MG, Engels LG, Muris JW, et al. Modern life in the epidemiology of inflammatory bowel disease: a case-control study with special emphasis on nutritional factors. Eur J Gastroenterol Hepatol. 1998;10:243–249. 317. Reif S, Klein I, Lubin F, et al. Pre-illness dietary factors in inflammatory bowel disease. Gut. 1997;40:754–760. 318. Halfvarson J, Jess T, Magnuson A, et al. Environmental factors in inflammatory bowel disease: a co-twin control study of a SwedishDanish twin population. Inflamm Bowel Dis. 2006;12:925–933. 319. Baron S, Turck D, Leplat C, et al. Environmental risk factors in paediatric inflammatory bowel diseases: a population based case control study. Gut. 2005;54:357–363.

390


320. Matsuura M, Liu B, Carroll I, et al. Selective alteration of growth and virulence for iron-dependent bacterial species; possible novel mechanisms of detrimental effects of dietary iron on intestinal inflammation. Gastroenterology. 2010;138:S–580. 321. Werner T, Wagner SJ, Martinez I, et al. Depletion of luminal iron alters the gut microbiota and prevents Crohn’s disease-like ileitis. Gut. 2011;60:325–333. 322. Zimmermann MB, Chassard C, Rohner F, et al. The effects of iron fortification on the gut microbiota in African children: a randomized controlled trial in Cote d’Ivoire. Am J Clin Nutr. 2010;92: 1406–1415. 323. Ettreiki C, Trakhna F, Gadonna-Widehem P, et al. P0165 Impact of iron on intestinal microbiota equilibrium, inflammtory and orientation of immune responses during IBD. Gut. 2010;59:A139.