EnvironMicrobiol.13(2011)3088 Human Distal Gut Microbiome

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Human distal gut microbiomeemi_2574 3088..3102

Julian R. Marchesi*School of Biosciences, Museum Avenue, CardiffUniversity, Cardiff CF10 3AX, UK.

Summary

The distal gut and its associated microbiota is a newfrontier in the quest to understand human biology andevolution. The renaissance in this field has beenpartly driven by advances in sequencing technologyand also by the application of a variety of omic tech-nologies in a systems biology framework. In the initialstages of understanding what constitutes the gut,culture-independent methods, primarily inventoriesof 16S rRNA genes, have provided a clear view of themain taxonomic groups of Bacteria in the distal gutand we are now moving towards defining the func-tions that reside in the distal gut microbiome. Thisreview will explore recent advances in the area of thedistal gut and the use of a variety of omic approachesto determine what constitutes this fascinating collec-tion of microbes.

Introduction

Gut or intestinal microbiology has undergone a mini-renaissance in the past 10 years. In a comprehensivereview of the role of the gut microbiota in the health of thehost, Sekirov and colleagues (Sekirov et al., 2010)charted the number of publications for the period from1990 to 2009. Their data show that in this period there hasbeen a near fivefold increase in the yearly publicationrate. In fact the overall number they show is an underes-timation, if the ISI Web of Knowledge database is queriedwith similar keywords (Fig. 1), the trend is the same;however, the number of publications, which now includes2010, is nearly twice the figure and currently peaks at1366 for 2010. Several reasons are responsible for thisincreased attention, the recognition that the gut micro-biota plays a central role in host health, as well as thecross-pollination of ideas from microbiologists working in

the varied areas of environmental microbiology. As a dis-cipline environmental microbiology has always been chal-lenged by what has been referred to as the the great platecount anomaly and which describes the disparitybetween what we can grow in the laboratory, on conven-tional microbiology media and what we can directly count(Staley and Konopka, 1985). This challenge has resultedin a dramatic (and some may say it is a swing too far awayfrom culturing) shift away from culturing to developingculture-independent approaches to investigate ecosys-tem function and the role that microbes play (Amann andKuhl, 1998). However, microbiologists working in thehuman body, have been relatively fortunate because asignificant proportion of the microbial community in thesesystems are culturable, a fact that delayed the introduc-tion of culture-independent approaches to analyse thisecosystem. The suite of methods that have been used arevariations on the genomic, transcriptomic, proteomic andmetabolomic methods. The most commonly used are themetagenomic and 16S/18S rRNA gene-based methods todetermine the functions in the microbiome and thespecies present. While metatranscriptomic {Gosalbes,2011 #17381; Bomar, 2011 #17475} and metaproteomic{Verberkmoes, 2009 #15794} {Rooijers, 2011 #17579;Klaassens, 2007 #6600} methods are been implemented,but to a much lesser extent. Using the gut as an example,the two most commonly studied niches are the distal gutand oral cavity, because logistically they are the easiest toaccess. In both instances the proportions of the microbialcommunity that are as yet uncultivated are between 30%and 50% (Wade, 2002; Eckburg et al., 2005; Duncanet al., 2007), which provides researchers with a significantculturable microbial biomass for investigation. When thisfigure is compared with environmental ecosystems suchas the deep biosphere or soil where the culturable fractioncan be between < 0.1% and 1% respectively (Hugenholtzet al., 1998; Fry et al., 2008) it becomes clear howresearchers in these areas needed to create a suite oftools to help in developing a more complete picture ofmicrobial contributions to ecosystem function. The currentburst of interest in the gut ecosystem and how itsmicrobes influence host function/physiology has in someway been driven by microbiologists adopting the tools ofenvironmental microbiologists and implementing them in

Received 13 May 2011; accepted 20 July 2011. *For correspondence.E-mail [email protected]; Tel. (+44) 29208 74188; Fax(+44) 29208 74305.

Environmental Microbiology (2011) 13(12), 30883102 doi:10.1111/j.1462-2920.2011.02574.x

2011 Society for Applied Microbiology and Blackwell Publishing Ltd

a new setting. Without these methods we would not haverealized that the gut microbiota is so diverse betweendifferent individuals, or resilient to perturbations, or thatkey functions in some instances are redundant, whileother they are not. These initial forays into the gut eco-system using culture-independent methods paved theway for developing hypotheses in which the gut micro-biota are drivers of health and disease. Hence in light ofthe numerous reviews on the microbiota of the human gut(524 for 20082010) this review will concentrate on themost recent and significant findings in the literature.

Anatomically, the human gut is divided into six sections,the oral cavity, oesophagus, stomach, small intestine(subdivided into the duodenum, jejunum and ileum), thecolon or distal gut (subdivided into the ascending, trans-verse and descending colons) and rectum (Fig. 2). Whilethe physiological role of the gut is to process and digestthe food we ingest, it also offers a niche for colonization bya variety of microbes. Each niche harbours a specificmicrobial community, which to some extent reflects thedynamics of that compartment. The numbers of microbesin each niche increases as one moves from the stomachto the rectum resulting in one of the most densely popu-lated ecosystems being found in the distal gut or colon,which contains between 10111012 bacteria per gram ofluminal material. Because the distal gut contains one ofthe densest communities known (Whitman et al., 1998)and is very easy to access [up to 55% of a stool sample isbacterial biomass (Cummings and Macfarlane, 1997)] it

has received the majority of the attention. However, thisdoes not mean it is a robust representation of the wholecolon or small intestine; moreover, the mucosal surfacecontains a microbiota that is significantly different to thatfound in a stool sample from the same subject(Momozawa et al., 2011). Data obtained from analysis offaecal material must be considered in light of where thissample comes from and conclusions based on this datamust be tempered appropriately; however, these data stillprovide a very valuable insight into functions and speciespresent in the gut.

The current census of the inhabitants of the distalgut: the early years of the distal gut

Unlike many environmental ecosystems being investi-gated, the establishment of the climax community in thegut is played out time and time again with every birth;moreover, it can very easily be perturbed and involves animmunological dialogue with the system in which itresides. Many of the major ecosystems that are studied,marine, terrestrial, deep-biosphere and atmosphere havebeen colonized for many millions to billions of years.However, in the majority of cases humans are born sterile[cases have been reported in which amniotic fluid sludgecontaining cultured isolates of Mycoplasma hominis,Streptococcus mutans and Aspergillus flavus has beenobserved (Espinoza et al., 2005; Romero et al., 2008)]and immediately upon exit from the mother start to be

Fig. 1. The number of publications retrieved from the ISI Web of Knowledge database (http://apps.isiknowledge.com/), obtained by using thefollowing keywords and Boolean operators: intestinal microbiota OR gut microbiota OR intestinal flora OR gut flora OR intestinalmicroflora OR gut microflora OR gut microbiome OR intestinal microbiome (the addition of the word gut microbiome and intestinalmicrobiome, not used by Sekirov and colleagues, added 92 publications compared with the same search without).

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colonized by microbes. There is a significant interest inunderstanding what drives this colonization process andhow much nature or nurture plays an influencing role.Specifically, because we have a poor understanding ofwhether early life events, which may alter the gut micro-biotas composition, can have ramifications for later lifehealth. The climax community seems to be establishedwithin the first 2 years of life and after the first year, it hasstarted to converge and reflects a generalized adult distalgut community (Palmer et al., 2007). The factors that influ-ence this process are the maternal microbiota(Dominguez-Bello et al., 2010), diet (breast fed vs.formula fed; Favier et al., 2003), mode of delivery (normalvs. caesarean; Biasucci et al., 2010; Dominguez-Bello

et al., 2010), full or preterm gestation (Schwiertz et al.,2003; Morowitz et al., 2011), environmental exposure(Palmer et al., 2007) and clinical interventions [antibiotics(Palmer et al., 2007) or gastrointestinal surgery (Zhanget al., 2009) technically this paper shows the impact ofsurgery on the adult gut)]. This progression has also beenconfirmed when using metagenomic DNA (mgDNA)instead of the 16S rRNA gene. Koenig and co-workers(Koenig et al., 2011) created inventories of the 16S rRNAgene (from 60 infants) and used this information to select12 infants for a sequence based metagenomic analysison the Roche 454 platform. The data they generated wereprocessed using MEGAN (Huson et al., 2007) andMG-RAST (Meyer et al., 2008) to assess the taxonomic

Fig. 2. The anatomy of the gastrointestinal tract, major bacterial phyla and their abundance in each niche. The information for this figure wascompiled from (Eckburg et al., 2005; Bik et al., 2006; OHara and Shanahan, 2006; McConnell et al., 2008; van den Bogert et al., 2011).

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source and functions contained within the mgDNA respec-tively. Using mgDNA the same succession was seen aswith 16S rRNA gene data (Fig. 3) and other groups havealso confirmed that random sequence reads can be usedin lieu of taxonomically relevant genes such as the 16SrRNA gene (Manichanh et al., 2008; Ghosh et al., 2010;Gori et al., 2011). The consensus of opinion from thesestudies seems to be that the trajectory of the colonizationprocess is towards a similar outcome, i.e. a distal gutmicrobiota, which after the age of 2 is stable and colo-nized predominantly by Firmicutes and Bacteroidetes(see below). However, we do lack the information of whichfactors are driving this process, how the colonizationprocess in different ethnic groups proceeds and to whatextent the functions in the gut are established. Hencethere is a clear need to continue to determine the keyevents that influence the establishment of the climaxcommunity.

The adult and ageing distal gut microbiota

One of the most comprehensive early culture-independent analyses (using clone libraries of 16S rRNAgenes and Sanger or first-generation sequencing plat-forms) was carried out on the distal gut by Eckburg andcolleagues (Eckburg et al., 2005). This study revealedthat while there were many bacteria in the gut they wereactually not as diverse as soil or marine ecosystems. In

the majority of mammals the two main phyla present arethe Bacteriodetes and Firmicutes (Ley et al., 2008) and itseems that members of these two phyla contributeapproximately 90% of the species in the distal gut. Thenumber of species estimated to be present in the distalgut is relatively small [compared with soil in which millionsof species are estimated to exist in 10 g (Gans et al.,2005)] and is in the hundreds (Qin et al., 2010), while alarger degree of diversity exists at the strain level, whichmaybe in the thousands (Ley et al., 2006). The impor-tance of the strain diversity may only be significant whenthe functions that the strain carries are non-redundant.For example, there are two hydrogenotrophic groups, themethanogens and sulphate reducing bacteria, which arerepresented by very few species and strains in the distalgut {Scanlan, 2009 #16220} {Dridi, 2009 #17393}. In thisscenario, it would be easy to lose the functions theseorganisms provide, whether health promoting or detrimen-tal remains to be seen, to the host. A further consequenceof this strain diversity is that phylogenetic trees of the guttend to have few branches, which are not deep, but havea large degree of radiance at the ends. However, thiscensus is based on a very small number of samples andto put it into perspective a recent search for single nucle-otide polymorphisms that correlate with adult heightscreened 183 727 individuals to determine statisticallysignificant correlations (Lango Allen et al., 2010); in con-trast, the majority of the studies that have been under-

Fig. 3. Taxonomic distribution ofmetagenomic sequences isolated from infantfaecal DNA [adapted from Koenig et al. (2011)with data kindly provided by Prof Ruth Ley].



taken to determine the composition of the gut microbiotause small cohorts that can be counted in the tens ratherthan thousands. One recent study that has sampled hun-dreds of individuals has shown why we need large cohortsof subjects. While we can take averages of the numbersof species present in the distal gut and conclude that twophyla predominate, if the sample size is increased theproportions of these phyla can tell a very different story. Inthe Eldermet project (http://eldermet.ucc.ie/) being under-taken in University College Cork, Ireland, the investigatorsprofiled the distal gut of 386 > 65 year old individualsusing second-generation 454 pyrosequencing andobtained approximately 40 000 reads per sample andwhich spanned the V4 region of the 16S rRNA gene. Onceagain the composite picture of the distal gut was one inwhich gene sequences from the Bacteriodetes and Firmi-cutes contributed 97% of the overall sequences obtained(57% and 40% respectively; Claesson et al., 2011).However, when the individual profiles were plotted andordered an entirely different picture was obtained (Fig. 4).The distribution of 16S rRNA genes showed that withinthe cohort there was a continuum, at one endBacteroidetes made up nearly 90% of the distal gut micro-biota while at the other Firmicutes made up more than95% of the sequences recovered. This larger study furtherhighlights the necessity to increase the cohort size andmove away from small studies of 23 subjects. The factthat the distal gut microbiota is so variable at the phylumlevel does make one wonder whether it is this variablefurther down the taxonomic levels, for example, at the

genus level? To answer this question, several groupshave been exploring the concept of the core microbiotaand whether there exist a group of species found in alldistal guts regardless of geography, ethnicity, age, genderor diet. While it would be safe to say that there is a coremicrobiota at the phylum level, i.e. all humans possesmembers of the Bacteroidetes and Firmicutes, when wedrill down the taxonomic levels it seems that this conceptbecomes more sketchy and different studies and methodsprovide different answers. Tap and colleagues undertooka de novo analysis of the composition of the distal gutmicrobiota using first-generation sequencing and PCRamplification and cloning of the 16S rRNA gene (Tapet al., 2009). They generated 10 456 16S rRNA genesequences from 17 human faecal DNA samples andanalysed them to determine which sequences wereshared and which were unique. In their conclusions, theystate that on average each individual contains 259 opera-tional taxonomic units (OTUs at the 98% level), but therange was large (159383) and in total 3180 OTUs wereidentified from the total pool of 16S rRNA genesequences. Approximately, 79% of the OTUs were onlyfound in one sample and 21% were found at least twice;however, no OTUs was found in all 17 distal guts. Theyshowed that 66 OTUs were found in 50% of the samplesand proposed that these may in some way constitute acore microbiota. These OTUs belonged to 18 genera andthese were affiliated predominantly with the Firmicutes(57/66). In a study with a similar goal, to determine themembers of the core microbiota of the distal gut, Rajilic-

Fig. 4. Proportions of main bacterial phyla in 386 Eldermet faecal samples, the two main phyla are shown in the figure while the remainingphyla were the Proteobacteria, Actinobacteria, Lentisphaerae and Verrucomicrobia. The inset pie-chart shows the mean values for the phyla(F Firmicutes and B Bacteroidetes) isolated from the distal guts of the elderly individuals, the category others includes the following phyla Proteobacteria, Actinobacteria, Lentisphaerae and Verrucomicrobia (data to construct this figure were kindly supplied by Dr Paul OToole,University College Cork, Ireland and Eldermet principle investigator).

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Stojanovic and co-workers used a DNA array approach todetermine the composition of the distal gut (Rajilic-Stojanovic et al., 2009). While the aims were comparablethe methods are not, even if they both target the samegene 16S rRNA. DNA arrays have the advantage ofbeing more sensitive and are able to detect sequences ina mixture at much lower levels than a random samplingwithout replacement strategy, e.g. analysis of a clonelibrary or second-generation amplicon sequencing (Har-rington et al., 2008; Paliy et al., 2009; Rigsbee et al.,2011). However, they are only as good as the databaseused to design the array probes and any novel sequencesin the samples, which are not represented on the chip, willnot be detected. Bearing this in mind Rajilic-Stojanovicand co-workers used their human intestinal tract chip(HITChip) to profile the distal gut of five young and fiveelderly volunteers. Their HITchip can measure the abun-dance of 1140 unique microbial phylotypes and they con-cluded that there was a common core between all 10individuals, which consisted mainly of probes from threephyla (Actinobacteria, Bacteroidetes and Firmicutes)found in the distal gut and confirms that we possess adistal gut microbiota that is host specific. In addition, theywere also able to show that the young and elderly gutssamples clustered according to the hosts age with all theyoung and elderly samples found in their respectiveclades. In the Eldermet study (Claesson et al., 2011),there was also a significant difference between the elderlyand young distal gut. In the elderly distal gut more thanhalf of the core microbiota (53%) were from theBacteroidetes, from the genera Bacteroides (29%), Alisti-pes (17%) and Parabacteroides (7%), while in theyounger distal gut this figure dropped to between 8% and27%. Furthermore, the core clostridial species were pre-dominantly in the Clostridium cluster IV for the elderlywhereas cluster XIVa was more prevalent in the youngercohort, again highlighting the need for longitudinal studiesrather than snapshots of the distal gut composition. In thestudy conducted by Biagi and co-workers (Biagi et al.,2010), which looked at young (Y), elderly (E) and cente-narians (C) (groups of 20, 22 and 21 and average ages of31, 72.7 and 100.5 respectively) using the HITChip plat-form and quantitative PCR, the trend for a variation in themain groups was also seen (Fig. 5). However, thechanges in the subgroups within the clostridial group werenot the same as found in the Eldermet project, with anincrease in Clostridium cluster XIVa going from Y to E,which decreased in the centenarians. The Clostridiumcluster IV remained the same between all three groups,while between the C and E groups only the Faecalibac-terium prausnitzii was significantly different, between Cand Y groups Bifidobacterium spp. differed and betweenE and Y members of the genus Akkermansia differed. In arecent development to describe the core microbiota of the

distal gut Sekelja and colleagues undertook a post hocanalysis of previously published datasets from pyrose-quencing projects targeting the 16S rRNA genes (Sekeljaet al., 2011). They also changed the approach used, bymoving away from defining taxonomic groups and in theirwords search for a human core microbiota independentof both predefined phylogroup depths and phylogenetictrees. Using an alignment-independent approach, theyanalysed 16S rRNA gene sequences (from eight previousstudies and comprising 1 186 272 partial 16S rRNAsequences from 210 samples) and clustered them usingprincipal component analysis based on their sequencesimilarity [calculated by establishing 5 mer nucleotide fre-quencies in each sequence (Rudi et al., 2006; 2007)].From their analysis they report that there were two micro-biota cores, which were consistently found in all samples.Both cores were affiliated to the Firmicutes and weremembers of the clostridial family Lachnospiraceae.Interestingly they concluded that each core appeared atdefined moments in evolution with core 2 co-evolving withthe radiation of vertebrates and core 1 co-evolved with themammals. These studies enforce the stochastic nature ofsampling the distal gut and the need for more large-scalestudies to minimize confounding factors such as diet,environment and genetic/immunological variability of thehost.

Fig. 5. Relative abundance of phylum/order phylotypes fromcentenarians (C), elderly (E) and young (Y) (adapted from Biagiet al., 2010).



A bacterial-centric view that needs toencompass all the microbiota

To date we still have a limited understanding of whatconstitutes the core microbiota of the distal gut and assuch cannot define its limits. We still need to expand thenumbers of distal guts sampled, the ethnic groups fromwhich we obtain the samples and also the compositionalstability of the core. While the previous studies have allindicated that the concept of a core microbiota is notdead, we have not reached any consensus as to whatspecies should be considered as members of this impor-tant group of bacteria, but we do agree that main phylaare the Bacteroidetes and Firmicutes. Furthermore, theconcept of a core microbiota has not been fully inclusiveand maybe should be renamed the core bacteriota as ithas not considered the micro-eukaryotic and viral compo-nents. Both of these groups of organisms have beenstudied in relation to the distal gut, but in a more limitedfashion. Only a few studies have been undertaken lookingat the human micro-eukaryotic diversity using culture-independent approaches (Ott et al., 2008; Scanlan andMarchesi, 2008) and viral diversity in faecal samples(Breitbart et al., 2003; 2008; Zhang et al., 2005; Reyeset al., 2010). The micro-eukaryotic diversity and numbersis several orders of magnitude lower than the Bacteriaand is skewed towards Candida and Saccharomyces spp.when cultured, but culture-independent approaches using18S rRNA genes shows that Blastocystis spp. are verycommon in the distal gut and yeasts are rarely obtained.In fact, it may be concluded that micro-eukaryotes areonly really significant when there is a dysbiosis in the gut(Goldman and Huffnagle, 2009). For the viral componentthe story is very different with their numbers being at leastan order of magnitude higher than the bacterial numbersin the distal gut. Thus we might need to start to considerthe viral component as drivers of community dynamics assome marine microbiologists do (Suttle, 2007). In fact,Lepage and colleagues (2008) have hypothesized a rolefor distal gut bacteriophage as drivers of dysbiosis in thedistal gut and inflammatory bowel disease. While studieslooking to define the core microbiota have focused ondescribing the Bacteria within the distal gut, there is alsoa significant number of Archaea in this niche. The mostcommon species and 16S rRNA gene sequence isolatedfrom the distal gut come from the Euryarchaeota and inparticular the Methanobacteriaceae family (Scanlan et al.,2008a; Dridi et al., 2009) with Methanobrevibacter smithiiand Methanosphaera stadtmanae the two predominantArchaea found. However, other rarer archaeal sequenceshave been reported that cluster in the Methanosarcinales[a methyl coenzyme reductase subunit A (mcrA)sequence (Scanlan et al., 2008a)], Halobacteriaceae(Oxley et al., 2010) and a putative sixth archaeal order

(Mihajlovski et al., 2008; 2010). However, in all studies todate M. smithii and M. stadtmanae are the two mainArchaea (Dridi et al., 2011) and one would question towhat extent the much rarer species are autochthonousand are actually contaminants from our diet/environment.

The luminal microbiota versus themucosal microbiota

One of the major criticisms of many of the studies on thedistal gut is the reliance on stool or faecal material as thesource of microbial biomass or genomic DNA. While it isquite simple to collect it is clear that faeces do not afforda robust proxy for the gut microbiota as a whole. InEckburg and co-workers 2005 culture-independentanalysis of the distal gut (Eckburg et al., 2005) theyclearly showed that while the microbiota attached to themucosa was similar throughout an individuals large intes-tine it was significantly different to the stool sample fromthe same individual, but whether there is any biologicalsignificance in this difference remains to be shown, as thenumber of luminal bacteria are between 46 orders ofmagnitude less than the mucosally associated bacteria[MAB; Zoetendal (Zoetendal et al., 2002; Ahmed et al.,2007; Walker et al., 2011)]. Using a DNA microarray (Aus-HIT Chip) Aguirre de Carcer and colleagues (de Carceret al., 2011) have shown not only a gender differencebetween the MAB, but also a qualitative change in theMAB composition moving from the caecum to the rectum,via the transverse and sigmoid colon. However, we stillneed larger studies to determine what is considered to bethe prevalent species colonizing the different regions ofthe colon and at what scale the community starts todiverge.

Is there a core microbiome?

Qin and co-workers (Qin et al., 2010) and othersequence-based metagenomic studies have addressedthe issue of whether there is a core microbiome (thecollection of microbial genes) and if so what does it looklike? To date the study of Qin and colleagues is by far thedeepest and largest metagenomic1 sequencing project tobe undertaken; however, two smaller metagenomicstudies do precede it (Kurokawa et al., 2007; Turnbaughet al., 2009). In the most recent study the authors used anIllumina second-generation sequencing platform to gen-erate 0.58 terabases of sequence from 124 volunteers

1The term metagenomics is routinely confused with creatinginventories of 16S rRNA genes to describe bacterial diversity.Metagenomics is the analysis of random genomic fragmentseither by sequencing or functional analysis.

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(approximately 4.5 gigabases per individual with anaverage read-length of 75 bp) and determined that therewere 3.3 million non-redundant genes in the distal gutmetagenome. This figure is in agreement with the previ-ous figure of 9 million genes (Yang et al., 2009) and thatbetween the different gut samples there were 204 056common genes that comprised 38% of an individuals gutmicrobiome. In this project these genes were grouped into6313 clusters of orthologous groups and could be dividedinto house-keeping genes and gut-specific genes. Whenstudying the gut it would be the genes only found in thegut that are of key interest as these may play a role inshaping the relationship between the host and its gutmicrobiota. While the house-keeping genes were part ofthe main metabolic pathways commonly associated withbacteria, for example, amino acid synthesis, nucleic acidprocessing and general secretory processes, the gut-specific genes were identified as being involved in adhe-sion to host proteins or catabolizing globoseriesglycolipids. However, the majority of the clusters oforthologous groups (74.3%) were not defined and this facthighlights a key problem with sequence-based metage-nomic projects, they lack the ability to provide novel func-tions (Table 1). Many of the sequences, when comparedwith the current databases will either return hits to anno-tated functions, hypothetical ORFs or unknowns. In thecase at hand when the supplementary data (tables 10 and11 from Qin et al., 2010) are searched there are noreported hits to genes involved in butyrate synthesis(Louis et al., 2010), bile catabolism (Jones et al., 2008),glucuronidases (Gloux et al., 2011) and functions, whichare not easily classified, but maybe important to the host,for example indole-3-propionic acid synthesis (Wikoffet al., 2009), choline catabolism (Wang et al., 2011) andNF-kB modulators (Lakhdari et al., 2010). However, this isnot a criticism of the study, but rather an observation of thedifficulty of the task and deciding what should be classi-fied as a core function of the microbiome (genes involvedin bile catabolism and butyrate synthesis are present inthe METAHIT datasets, but are not abundant). Trying to

determine which genes are important to the host, whenthey may be at low levels in the microbiome, cannot beachieved by simply sequencing. This fact is furtherenforced by the recent study of Arumugam and col-leagues (Arumugam et al., 2011), which has taken 17metagenomic datasets from previous studies (Gill et al.,2006; Kurokawa et al., 2007; Turnbaugh et al., 2009) aswell as 22 they generated using first-generation Sangersequencing and statistically and phylogenetically analy-sed the information. The major outcome of this analysiswas their conclusion that the distal gut is stratified intothree enterotypes, which are predominantly driven byspecies composition. Enterotype 1 is dominated by thegenus Bacteroides, enterotype 2 is dominated by thegenera Prevotella while in enterotype 3 the genus Rumi-nococcus is the discriminatory genus (Fig. 6; see Sup-porting information for Arumugam et al., 2011 for furtherinformation on genus abundance). Another interestingfinding was that several abundant functions found in thedifferent enterotypes are not associated with abundantgenera, for example, bacterial pilus assembly were asso-ciated with the low-abundance genus Escherichia, whilethe hydrogenotrophic functions, which include acetogen-esis, sulphate reduction and methanogenesis were notdetected using the functional marker approach. The mcrAfunctional gene was only detected in 3 out of the 22European samples, although the methanogens thatharbour this gene is found in > 95% of individuals (Dridiet al., 2009). Dridi and colleagues claim that the low inci-dence of methanogens in previous studies was due to aninappropriate DNA extraction method and PCR target,using their modified approach they improved detectionfrom 19% to 95.7% in the 700 samples studied (Dridiet al., 2009). Which raises the question of how much biasis introduced into these studies by such factors as themethod used to extract the DNA? The method used in theMETAHIT study was one developed to obtain highmolecular weight genomic DNA for creating a metage-nomic library fosmids and uses a gentle extraction pro-tocol that does not involve any mechanical shearing

Table 1. Comparison of the pros and cons of the two metagenomics methods used to study the functions in an ecosystem.

Function-based screen Sequence-based screen

Screen large amounts of DNA Yes with the aid of colony picking andarraying robots

Yes with the use of second-generationsequencing platforms

Provide novelty Yes NoGenomic context Yes Limited and relies on assembly of reads and

assumptions on pan-genomic nature of gut bacteria.Toxic genes No YesExpression issues Yes NoStorage issues Yes physical storage, one fosmid library

can easily take 650, 384 well platesand 1950 if stored in triplicate

No

Computational issues No Yes BLAST searches and data analysis arebecoming bottlenecks in the analysis



(Courtois et al., 2003), hence this may explain why somefunctions/groups are absent. Furthermore, if genesinvolved in hydrogenotrophic processes, which are knownto be important to gut and host function (McNeil, 1984;Waniewski and Martin, 1998; Attene-Ramos et al., 2006;Sahakian et al., 2010), cannot be robustly detected is thedata suspect? The authors concede [functional genes]from these less abundant microbes could barely be iden-tified. However, such studies do provide the wider scien-tific community with an invaluable resource from which wecan derive hypotheses as to what constitute a core micro-biome and these can be tested in either large humancohorts or animal models of the human gut. However, wemay need to invest in even deeper sequencing projects toestablish the limits of how deep we need to probe in orderto find functions that are of importance to the host anddefine the gut ecosystem.

One way to avoid missing functions is to adopt a top-down or reverse genetics strategy to determine the corefunctions in the gut (Nicholson et al., 2005; Martin et al.,2007). The most robust strategy would be to use a meta-bonomic approach either in a targeted fashion or non-targeted, using either mass spectrometry (hyphenated

with chromatographic separation, e.g. UPLC-MS) ornuclear magnetic resonance to identify key metabolitesthat occur in the gut and can only be derived from micro-bial processes (see example in Fig. 7). From thesemetabolites it would be possible to develop a database ofthe core metabonome and work back to microbial genesthat are responsible for synthesizing them. Metabonomicstudies have started to provide an insight into the keymetabolites that are seen constantly in the gut at varyinglevels, for example, the short chain fatty acids (Martinet al., 2009), amines (Wang et al., 2011), amino acids(Wikoff et al., 2009) and bile salts (Martin et al., 2007).From these metabolite signals, we can start to developstrategies to investigate the diversity and expression ofthe microbials genes that are responsible for their synthe-sis. Louis and colleagues investigated the diversity ofbutyrl-CoA : acetate CoA-transfereses (Louis et al., 2010)using a degenerate PCR method and showed that thisgene and its associated function are found in all thesamples studied and shows a large degree of variation.Thus this function would be considered to be a corefunction of the microbiome, because it not only plays arole in the bacterium, but is a significant factor responsible

a

b

Fig. 6. A. Abundance of the main phylogenetic groups contributing to defining the three enterotypes of the distal gut.B. Network analysis showing the interrelationships between the main genera in each enterotype (taken from Arumugam et al., 2011).

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for a key interaction with the host itself. Hence the defini-tion of a core function may need to be revised so we getaway from defining the core microbiome as the functions/genes found in a gut, which include genes found in allbacteria, to one that includes the need to interact with thehost and is undergoing positive selection by the host,either directly or indirectly. Using this definition many func-tions would not be included in the core microbiome andonly those playing a role in both biological compartmentswould be considered. Another such example of a corefunction of the microbiome would be the bile salt hydro-lases (Jones et al., 2008). In the absence of these geneswe can see that rodents have reduced bile acid deconju-gation, produce more bile acids and absorb more choles-terol (Wostmann, 1973; Wilks, 2007). Furthermore, themicrobial re-colonization of a gnotobiotic animal providesevidence of the gut microbiomes ability to modulate bileacid metabolites, which themselves are regulators of lipidabsorption (Claus et al., 2011). These types of integrativeor systems biology studies are bringing together the dif-ferent biological compartments and help to develop abetter understanding of the what aspects of the coremicrobiome are really important in a superorganism.

The mobile microbiome or mobilome

In nearly all the functional and sequence driven humanmetagenomic studies to date, very little regard is paid togenetic elements involved in gene transfer. However, weknow that bacteria are frequently transferring DNA viaphage, plasmids, transposons and other mobile geneticelements (MGEs) (Ochman et al., 2000). One of the most

commonly isolated functions that are found on these ele-ments are genes involved in antibiotic resistance (Wright,2007); however, the methods used to pull out theseMGEs are themselves highly biased. They tend to isolatebacteria showing a chosen function [positive screening orendogenous isolation (Smalla and Sobecky, 2002)], thisapproach limits the range of functions that can bescreened and microbes that can be cultured. Alternativelythe methods only isolate MGEs that can transfer into asuitable host [exogenous isolation (Bale et al., 1988)],which tend to be Gram-negative. Hence the ability toisolate and describe the functions on MGEs is limited bythe current methods available and the fact that manyfunctions are not easily maintained or screened for in asurrogate host (when using functional metagenomics) orreassembled into a whole plasmid in sequence-basedapproaches. Moreover, cryptic ORFs on MGEs may notbe recognized as such if the complete element is notreassembled from the raw data. To this end otherapproaches have been developed to specifically look atunknown function on plasmids and these have beenapplied to the distal gut. The TRACA method (Jones andMarchesi, 2007) uses an in vitro transposition eventcoupled with a plasmid-safe DNAse to tag circular DNA(plasmids and DNA phage) with a selectable marker andan E. coli plasmid origin of replication. This strategy canbe used to capture small plasmids (< 15 kb) from the gutmetagenome and stability maintain them in E. coli withoutthe need for any selection, apart from that which wasintroduced (in this case kanamycin), or transfer to a suit-able recipient. Using this approach, several plasmidshave been isolated from the large intestine of an individual

Fig. 7. Changes in urinary metabolites due to colonization of the gut by microbiota as shown by pattern recognition analysis [principalcomponents (PC) analysis] of partial nuclear magnetic resonance spectroscopic data from gnotobiotic sequential rat urine samples. Sampleswere collected for up to 3 weeks during the gut microbiotal conventionalization process, the mapping position of five different temporal subsetsare shown (T1T5). One animal (triangle marked by an asterisk next to d 21 cluster) completed conventionalization by day 17 (adapted fromNicholson et al., 2005).



and sequenced. Coupling these sequence data with bio-informatic methods, it was possible to use them as a DNAhook to pull out similar sequences from the metagenomicdatasets deposited in the public databases (Jones, 2010;Jones et al., 2010). These studies have started to showthat as with certain gut functions, such as butyrate pro-duction and bile salt deconjugation, there is also a coremobilome in the gut. Two of the plasmids isolated,pTRACA10 and pTRACA22, were found to be enriched inthe metagenomes of the 15 human distal guts (from USA,Europe and Japan), while four others did not showany significant homology to these datasets (BLASTn,> 100 bp fragments, > 80% identity and E-value of 1e-5).However, when the same six plasmids were screenedagainst the METAHIT dataset, all were shown to be rep-resented in these datasets, with pTRACA22, showing asignificant enrichment compared with the other five plas-mids. pTRACA22 is a small 5.9 kb mobilizable plasmidthat most probably originates from Blautia hydro-genotrophica as all nine ORFs show > 98% identity togenes from this draft genome (Jones et al., 2010). Themost notable feature of this plasmid is its RelBE or type IIaddiction module (Van Melderen, 2010) and thesemodules have been implicated in range of host-specificfunctions, for example, modulation of gene expression,formation of persister cells and biofilm dispersal.However, whether this enrichment of these modules isbiologically significant and of relevance to the gut or hoststill needs to be determined, but it does show that even inthe mobilome the gut does show interesting enrichmentsof some genes and more thorough investigation of thisgenetic compartment needs to be undertaken in order toestablish its role in the ecology of this ecosystem.

The distal gut microbiome as a driver of healthand disease

The whole concept of integrating the core microbiome intohost biology and physiology is further extended and chal-lenged by considering it as a driver of disease as well. Ifwe have a core microbiota, evolved to the hosts needs,and if two individuals share common features of this corewill they also share common emergent properties too?Furthermore, if there is a dysbiosis in the gut microbiota,does this lead to the development of gastrointestinal dis-eases? Such concepts have been explored in the contextof the gut microbiota as an environmental factor in func-tional gastrointestinal diseases, for example, inflamma-tory bowel disease (Scanlan et al., 2006; Frank et al.,2007), colorectal cancer (Scanlan et al., 2008b; Sobhaniet al., 2011), irritable bowel syndrome (Kassinen et al.,2007; OMahony et al., 2009) and Clostridium difficile-associated diarrhoea (Khoruts et al., 2010) and morerecently in ex-intestinal diseases such as cardiovascular

disease (Wang et al., 2011), obesity {Turnbaugh, 2008#15541; Ley, 2005 #7445; Backhed, 2004 #501}(however, others have been unable to confirm this obser-vation {Duncan, 2008 #15503} {Fleissner, 2010 #17580}{De La Serre, 2010 #16857} {Zhang, 2009 #15740}{Schwiertz, 2009 #16428}) and psychiatric diseases (Des-bonnet et al., 2008; Rook and Lowry, 2008) {Bercik, 2011#17583}. However, there are several issues that discom-bobulate the idea of the gut microbiota as an environmen-tal factor in these and other diseases. First, many of thestudies look at the gut microbiota after diagnosis of thedisease, hence we are unsure as to whether we areobserving cause or effect. In order to circumvent thisissue, large prospective studies need to be undertaken,which are statistically empowered, in which frequentsamples are taken and appropriately stored for retrospec-tive analysis. Second, we are currently developing corre-lations between a disease state and a snapshot ofmicrobial diversity in the gut or a potential metabolite, weneed to develop stronger causal links and mechanisticmodels that are predictive and can be tested in suitableanimal models. Even with these issues researchers aredeveloping the view that certain functions and the asso-ciated microbes are beneficial to the health of the host.Some of the most commonly seen bacterial metabolites inthe human gut are the SCFA, butyrate, acetate, lactateand propionate {Saric, 2008 #15051}. The two bacterialgroups that are mainly responsible for producing butyrateare the F. prauznitzii and Eubacterium rectale/Roseburiagroups {Louis, 2010 #17389; Louis, 2009 #15805}. Thismetabolite has been implicated in large array of effects inthe intestine that include controlling apoptosis, cytokineproduction, energy for colonocytes and mucus synthesis{Guilloteau, 2010 #17009}. Hence any changes in thesegroups would potentially have an impact on this functionand host physiology. Beyond this ubiquitous function itdoes become an exercise in speculation as to what bac-terial groups are important to host health. In one respectmoving away from trying to define a core microbiome to acore metabonome may aid in defining what we need tostudy and understand in order to maintain a healthy gutand thus a healthy host.

Concluding remarks

The paradigm of the human distal gut microbiome hasshifted in recent years, from one that looked upon it as asource of opportunistic pathogens to one that embraces itas a virtual organ with the ability to influence the healthstatus of the host. Taxonomically, we have establishedthat this system is mainly composed of members of theBacteroidetes and Firmicutes, but we are still struggling todetermine the key functions that are important to themicrobes and the host. The ability to catalogue the genes

3098 J. R. Marchesi


present in the distal gut does not equate to defining thecore microbiome and using a top down approach will helpto determine this feature in more detail. The question ofcohort sizes needs to be addressed and to this end weneed to increase the sample sizes used, in order todevelop a much more complete picture of the functions inthe gut and start to combine sequence and function-based metagenomic studies in order to determine thecore microbiome. In addition, the integration of metabo-nomic data into this model will help to determine the coremicrobiome and establish how it varies both inter- andintra-individually. Once we have created this foundationwe can commence to develop hypothesizes that addresssuch questions as how does variation in the distal gutmicrobiome influence host function or can we modulatethe gut microbiome in order to promote health and shouldwe even try.

Acknowledgements

I wish to acknowledge the help of my colleagues in theEldermet project in University College Cork for sharing theirdata and Professor Ruth Ley for kindly providing me with heredata for Fig. 3.

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EnvironMicrobiol.13(2011)3088 Human Distal Gut Microbiome