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GASTROENTEROLOGY 2007;133:24–33

he Fecal Microbiota of Irritable Bowel Syndrome Patients Differsignificantly From That of Healthy Subjects

NNA KASSINEN,* LOTTA KROGIUS-KURIKKA,* HARRI MÄKIVUOKKO,‡ TEEMU RINTTILÄ,* LARS PAULIN,§

UKKA CORANDER,� ERJA MALINEN,* JUHA APAJALAHTI,‡ and AIRI PALVA*

Department of Basic Veterinary Sciences, Division of Microbiology and Epidemiology, §Institute of Biotechnology, and �Department of Mathematics and Statistics,

niversity of Helsinki, Helsinki, Finland; and ‡Danisco Innovation, Kantvik, Finland

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ackground & Aims: Irritable bowel syndromeIBS) is a significant gastrointestinal disorder withnknown etiology. The symptoms can greatlyeaken patients’ quality of life and account forotable economical costs for society. Contributionf the gastrointestinal microbiota in IBS has beenuggested. Our objective was to characterize puta-ive differences in gastrointestinal microbiota be-ween patients with IBS and control subjects. Theseifferences could potentially have a causal relation-hip with the syndrome. Methods: Microbial ge-omes from fecal samples of 24 patients with IBSnd 23 controls were collected, pooled in a group-ise manner, and fractionated according to theiruanine cytosine content. Selected fractions werenalyzed by extensive high-throughput 16S ribo-omal RNA gene cloning and sequencing of 3753lones. Some of the revealed phylogenetic differ-nces were further confirmed by quantitative poly-erase chain reaction assays on individual sam-

les. Results: The coverage of the clone libraries ofBS subtypes and control subjects differed signifi-antly (P < .0253). The samples were also distin-uishable by the Bayesian analysis of bacterial pop-lation structure. Moreover, significant (P < .05)ifferences between the clone libraries were found

n several bacterial genera, which could be verifiedy quantitative polymerase chain reaction assays ofhylotypes belonging to the genera Coprococcus, Col-

insella, and Coprobacillus. Conclusions: The studyhowed that fecal microbiota is significantly alteredn IBS. Further studies on molecular mechanismsnderlying these alterations are needed to elucidate

he exact role of intestinal bacteria in IBS.

rritable bowel syndrome (IBS) is a common functionalgastrointestinal (GI) disorder with a worldwide preva-

ence of 10%–20%.1 Although IBS does not predisposeatients to severe illness, it can have significant effects on

heir well-being and need for medical consultation. The

ymptoms of IBS vary with affected individuals and in-lude abdominal pain or discomfort, irregular bowelovements, flatulence, and constipation or diarrhea. Pa-

ients with IBS can be grouped into 3 subtypes accordingo their bowel habit.1,2 These are diarrhea predominantIBS-D), constipation predominant (IBS-C), and mixedubtype (IBS-M), which refers to patients with symptomsf both diarrhea and constipation. The etiology of IBS isoorly understood. Miscellaneous causes, including physi-logic features such as altered GI motility and visceralypersensitivity, psychological stress and disturbances, low-rade inflammation, and bacterial gastroenteritis, have beenssociated with IBS.3

The microbiota of the human GI tract constitutes aomplex ecosystem that is involved in the health andhysiologic functions of the host. Alterations of the nor-al GI microbiota have been shown to take place as a

esult of antibiotic therapies4 and the use of probiotics,5

n connection with various dietary strategies,6 and withbesity.7,8 Moreover, bacteria belonging to the normalicrobiota seem also to be capable of causing disease in

ome individuals and may have a role in certain disor-ers, such as inflammatory bowel disease,9 –11 aller-ies,12,13 and IBS.14 –17 Conventional culture-based meth-ds provide an incomplete and biased picture of theiodiversity of intestinal microbiota, because the major-

ty of the GI tract bacterial species cannot be cultivated.18

o overcome these drawbacks, culture-independent mo-ecular methods have been introduced. These methodsre mainly based on ribosomal RNA (rRNA) genes thateflect the natural evolutionary relationships among dif-erent organisms. The microbial composition of humanntestinal microbiota has been studied, for example, by

Abbreviations used in this paper: bp, base pairs; G�C, guanine plusytosine; %G�C, percent guanine plus cytosine; IBS, irritable bowelyndrome; IBS-C, constipation-predominant irritable bowel syndrome;BS-D, diarrhea-predominant irritable bowel syndrome; IBS-M, mixed-ype irritable bowel syndrome; OTU, operational taxonomic unit; PCR,olymerase chain reaction; qPCR, quantitative real-time polymerasehain reaction; RDP II, Ribosomal Database Project II; rRNA, ribosomalNA.

© 2007 by the AGA Institute0016-5085/07/$32.00

doi:10.1053/j.gastro.2007.04.005

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July 2007 FECAL MICROBIOTA IN IBS 25

equencing the 16S rRNA genes of clones obtained bymplification with polymerase chain reaction (PCR) fromecal DNA preparations.19 However, multitemplate PCRmplification causes a bias in favor of dominant and lowuanine-plus-cytosine (G�C) content bacteria.20 Frac-ionating the DNA preparations according to the sample�C percentage (%G�C) has been shown to allow less

bundant species as well as sequences with high G�Contents to be amplified by PCR when studying environ-ental bacterial samples.21 Fractionation according to

he %G�C content thus enriches considerably the diver-ity of sequences obtained by cloning and sequencing.

In this study, we applied the %G�C profiling andxtensive 16S rRNA gene cloning and sequencing toompare the fecal microbiota of patients with IBS withhat of control subjects using pooled samples to over-ome individual variation not originating from the sub-ects’ IBS status. The combination of these 2 methods,pplied for the first time for studying human gut micro-iota, showed exceptionally high resolution and allowedvery detailed analysis of the bacterial populations. With

his extensive molecular characterization, significant dif-erences between the GI microbiota of symptomaticallyategorized patients with IBS and age- and sex-matchedolunteers devoid of GI disturbances were revealed bothn the microbial community structures (%G�C profiling)s well as on genus-level bacterial composition (cloningnd sequencing). The detected divergences in the bacte-ial phylotypes could be verified from fecal DNA prepa-ations of individual subjects already with a small pri-

ary set of quantitative real-time PCR (qPCR) assayssing primers designed specifically for the phylogeneticifferences found.

Materials and MethodsIn this study, we characterized the GI microbiota

n the fecal samples of 24 patients with IBS and 23 sex-

able 1. Characteristics of Patients With IBS and Controls

Variable Patients With IBS Controls

ge (y), mean (range) 47.3 (21–65) 45.2 (26–64)ex (F/M) 19/5 16/7redominant bowel

habit, n (%)Diarrhea 10 (42)Constipation 8 (33)Mixed type 6 (25)

xclusion criteriaPregnancyLactationOrganic GI diseaseSevere systematic

diseaseMajor or complicated

abdominal surgerySevere endometriosis

GI symptomsOngoing antibiotic

treatment� All exclusion

criteria of thepatients withIBS

wDementia

nd age-matched control individuals. These samples werereviously analyzed by qPCR with a set of primers tar-eting selected known GI bacterial groups.22

The patients with IBS were recruited by experiencedhysicians (Table 1). The patients fulfilled the Rome IIriteria for IBS,23 except for 3 subjects who reportedlightly less than 12 weeks of abdominal pain during thereceding year. All patients with IBS had undergonelinical investigation and endoscopy or barium enema ofhe GI tract less than 1 year before being recruited. Theatients were classified as having IBS-C, IBS-D, or IBS-My a questionnaire following the Rome II subgroupingriteria,2 which have been recognized as valid also in theome III criteria.1 The participants gave their written

nformed consent and were permitted to withdraw fromhe study at any time. For the IBS patients, the studyrotocol had the approval of the Human Ethics Com-ittee at the Joint Authority for the Hospital District ofelsinki and Uusimaa. Healthy control subjects devoid

f GI symptoms were recruited to form an age- andex-matched control group for the patients with IBSTable 1). Intestinal disturbances (including lactose in-olerance and celiac disease) and ongoing antibiotic treat-

ents were considered exclusion criteria for the controlroup.

A total of 24 patients with IBS classified as IBS-D (n �0), IBS-C (n � 8), or IBS-M (n � 6) and 23 volunteerontrol subjects donated fecal samples. Bacterial genomicNA was extracted as described by Apajalahti et al.24 TheNA preparations were subsequently pooled (IBS-D,

BS-C, IBS-M, and control), centrifuged in a cesium chlo-ide/bisbenzimidazole gradient, and divided into frac-ions within 5% intervals according to their G�C con-ent.25 The %G�C fractions displaying the most variationetween pooled DNA specimens were selected for furthernalysis (fraction 7 [%G�C, 25–30], fraction 10 [%G�C,0 – 45], and fraction 13 [%G�C, 55– 60]) (Figure 1). Totudy whether the differences observed in the %G�Crofiles were significant, the divergent fractions were sub-

ected to cloning and sequencing of the 16S rRNA gene.The selected fractions of 4 pooled samples were cloned

nd sequenced with a high-throughput protocol. Theloning was performed with the Qiagen PCR Cloninglus Kit (Qiagen, Hilden, Germany) by using indepen-ently 2 universal 16S rRNA gene PCR primer pairs. Therst primer pair corresponded to the Escherichia coli 16SRNA gene in the positions 8 –27 base pairs (bp) and492–1512 bp,18,26 and the second primer pair corre-ponded to the Escherichia coli 16S rRNA gene in theositions 7–27 bp and 1522–1541 bp.27 A PCR protocolf minimum amount of cycles (20 cycles for fraction 7nd 27 cycles for fractions 10 and 13) was applied forach fraction to avoid biases in favor of abundant tem-lates. The 2 amplicons were mixed in a 1:1 molecularatio before cloning, and a library of nearly 14,000 clones

as constructed. From each fraction, the 5= end of the

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26 KASSINEN ET AL GASTROENTEROLOGY Vol. 133, No. 1

6S rRNA gene was sequenced from 384 clones with theequencing primer corresponding to the E coli 16S rRNAene position 536 –518 bp.28 The BigDye terminator cycleequencing kit (Applied Biosystems, Foster City, CA) andn ABI 3700 Capillary DNA Sequencer (GMI, Ramsey,N) were used to analyze the products.All sequences were checked manually with the Staden

rogram package.29 Putative chimeras were eliminatedrom sequences aligned with ClustalW.30 The number ofperational taxonomic units (OTUs) was determinedith DOTUR.31 Each sequence was checked against theMBL Nucleotide Sequence Database with Fasta homol-gy search program at http://www.ebi.ac.uk/fasta33/ucleotide.html.32 Sequences with �95% similarity toxisting entries in the EMBL Nucleotide Sequence Data-ases of prokaryotes and environmental samples wereonsidered novel. These were further sequenced to nearlyull-length 16S rRNA gene using the vector primers T7nd SP6 (Qiagen PCR Cloning plus Kit) and primersorresponding to the E coli 16S rRNA gene in the posi-

able 2. Real-Time PCR Primers for Selected Sequence Grou

Target species/group Control sequenceSequence

length Tm

catenulatum/Bpseudocatenulatum

AM277149 275 68 5=-A

cocleatum 88% AM276544 104 60 5=-Aaerofaciens AM276107 260 67 5=-Ceutactus 97% AM275825 97 63 5=-Afarciminis AM275648 127 63 5=-Agasseri AM275470 160 63 5=-Atorques 91% AM276558 119 62 5=-Ttorques 94% AM275522 137 65 5=-Abovis AM276559 150 60 5=-T

niversal B longum DSM 20219 466 50 5=-T

OTE. Percentages in the names of target species refer to the seque

igure 1. %G�C profiles of intestinal microbial genomic DNA samplesrom IBS subtypes and control subjects. These included from left toight the fractions 7, 10, and 13, consisting of bacterial genomes with

G�C of 25–30, 40–45, and 55–60, respectively.

ptimized annealing temperatures used in each assay.

ions 908 –928 bp and 1073–1053 bp.28 After the supple-entary sequencing, they were reanalyzed with the Fasta

nd Ribosomal Database Project II (RDP II) Classifierool (http://rdp.cme.msu.edu/classifier/classifier.jsp)33 tossign them into phyla.

The statistical comparisons of the individual cloneibraries representing the 3 different IBS symptom sub-ypes and the control were performed with 3 individual

ethods revealing different aspects: the �-LIBSHUFFrogram,34 BAPS 4.1 program for Bayesian analysis ofenetic population structure,35 and the RDP II Libraryompare Tool (http://rdp.cme.msu.edu/comparison/

omp.jsp).33 The �-LIBSHUFF analysis generates the ho-ologous and heterologous coverage curves from the

6S rRNA clone libraries and thus analyzes the differ-nces in the libraries based on Good’s formula of cover-ge.36 In the Bayesian analysis, we used the unsupervisedequence classification option of BAPS 4.1 to discoveromogeneous subgroups in the investigated microbiota.he resulting groups within each fraction were furthernalyzed using multidimensional scaling based on theverage relative sequence dissimilarity to discover whetherhere are systematic differences in the sample compositionetween the control and the symptom subtypes.37 Further-ore, the RDP II Library Compare Tool33 was used to

est whether the corresponding sequence libraries di-erged from each other at the genus level. The compari-ons were run with a bootstrapping confidence thresholdf 95%. The Library Compare Tool uses naive BayesianRNA classifier to assign sequences in the 16S rRNA geneibraries under comparison to taxa and subsequently es-imates the significance of the observed differences.33

rom the output, the genus-level results were selected.For phylogenetic comparison of gene libraries, all se-

uences were aligned using the ARB program designedor 16S rRNA gene sequence database handling and datanalysis.38 For some of the sections of the tree, whereutative deviation could be seen between the pooledamples, qPCR primers were designed. The primers and

Forward primer Reverse primer

CTCGCATGGGGTGTC-3= 5=-CCGAAGGCTTGCTCCCGAT-3=

ATAAGTAACCTGGCRTC-3= 5=-CGTAGCACTTTTCATATAGAGTT-3=ACGGGAGGGGAT-3= 5=-CTTCTGCAGGTACAGTCTTGA-3=TGCTCCGGCYGATTTA-3= 5=-CGGTTTTACCAGTCGTTTCCAA-3=TCAGAYCTTGGTGAG-3= 5=-AAGCTACGATCATGTGAAAGTA-3=GTGCTTGCACCAGA-3= 5=-CAGAACCATCTTTTAAACTCTAGA-3=AACTGATCTTCTTCGGA-3= 5=-CGGTATTAGCAGTCATTTCTG-3=TCGGAGGAAGAGGACA-3= 5=-ACACTACACCATGCGGTCCT-3=TTGCTAAAGTTGGAA-3= 5=-ATCTACTAGTGAAGCAATTGCT-3=CGGGAGGCAGCAGT-3= 5=-GGACTACCAGGGTATCTAATCCTGTT-3=

homology with nearest cultured bacterial species. Tm values refer to

ps

CTC

ATACCCGGCTTGATTTTGGCTTATCTTAGCCCTA

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July 2007 FECAL MICROBIOTA IN IBS 27

heir optimal annealing temperatures are shown in Table 2.he qPCR primers corresponded to phylotypes belonging

o a particular species or resembling the given species bydenoted percentage: Ruminococcus torques, 91%; Clostrid-

um cocleatum, 88%; Coprococcus eutactus, 97%; Ruminococcusorques, 94%; Collinsella aerofaciens; Bifidobacterium catenula-um; Lactobacillus farciminis; Lactobacillus gasseri; Streptococ-us bovis; and to all eubacteria with universal primers.39

uantitative PCR was performed with an iCycler iQ ap-aratus (Bio-Rad, Hercules, CA) using SYBR Green Ietection chemistry according to Malinen et al.22 A set of2 control samples and 24 IBS patient samples consistingf 10 IBS-D, 8 IBS-C, and 6 IBS-M subtypes were ana-

yzed. All qPCR reactions were performed using triplicatearallel samples. For statistical analysis of the results, theontrol samples were compared with the IBS patientamples using the Mann–Whitney test.

The obtained sequences were deposited to the EMBLucleotide Sequence Database under the accession num-

ers AM275396 –AM279148.

Results%G�C ProfilingGenomic bacterial DNA from fecal samples was

ubjected to a %G�C profile analysis in which the ge-omes become differentiated according to their %G�Content. In this community-level analysis, considerableifferences were detected among the 4 pooled samples ofBS-D, IBS-C, IBS-M, and healthy control subjects in 3istinct %G�C fractions (fraction 7 [%G�C, 25–30], frac-ion 10 [%G�C, 40 – 45], and fraction 13 [%G�C, 55– 60])Figure 1). The %G�C profile is a culture-independentut rather robust and coarse characterization of the totalacterial community structure; thus, observed differencesay be caused by number of bacterial species of %G�C

ontent corresponding to the fraction in question. There-ore, these 3 fraction groups were directed to high-hroughput DNA cloning and sequencing analyses.

Cloning and SequencingFrom 14,000 clones in the 16S rRNA gene library

onstructed, 4,608 sequences, encompassing approxi-ately 450 bp from the 5= end of the 16S rRNA gene,ere gathered. After excluding sequences of weak qualityr chimeric structure, the success rate of sequencing waspproximately 81%. According to Good’s formula,36 theoverage of clone libraries ranged from 80% to 93%. Table 3llustrates the number of sequences acquired and theumber of OTUs these sequences represent when a sim-

larity criterion of 98% was used. A total of 79 novelhylotypes were detected, after which the correspondinglones were further sequenced to obtain the almost com-lete 16S rRNA gene sequence. After a subsequent Fastaearch, 53 phylotypes, representing altogether 98 sequences,

emained previously uncharacterized novel ones (Table 4). a

Statistical Analyses of Sequence LibrariesAll sequence analyses were performed by comparing

ndividual libraries of the 3 IBS subtypes and controls withach other within the fractions. Applying �-LIBSHUFF, theoverage of individual libraries was significantly differentn each sample, except for the control and IBS-D librariesn fraction 10 and the IBS-C and IBS-M libraries inraction 13 (Table 5).

According to the Bayesian analysis of population struc-ure, all samples, except for the control and IBS-M sam-les in %G�C fraction 7, could be clearly distinguishedrom one another (Figure 2). However, in fraction 13, theBS-D and IBS-M samples were somewhat closer to eachther as compared with the other pairwise distances. Inddition, the bacterial composition of the homogeneousubgroups identified by the unsupervised classification

ethod varied extensively between the control group andymptom subtypes, except for the control and IBS-Mamples in fraction 7 (data not shown).

Multiple statistically significant differences were de-ected on genus level with the RDP II Library Compareool (Table 6). A considerable abundance of Lactobacillus

n fraction 7 and a high number of Collinsella sequences inraction 13 distinguished the control sample from thether samples. Indeed, lactobacilli seemed to be almostotally extinct in all libraries derived from patients withBS, while the amounts of Collinsella sequences were

inute in IBS-C and IBS-D libraries. IBS-M was charac-erized especially by Bacteroides and Allisonella sequences;BS-C contained abundantly ruminococci, whereas nu-

erous streptococcal sequences were included in the IBS-Dibrary. Bifidobacterium clones were profusely present in allraction 13 samples, the least amount being discovered inhe IBS-D library. In addition, several other genera from thehyla Firmicutes, Actinobacteria, Proteobacteria, Bacteroidetes,

able 3. Number of Sequences and OTUs in Each CloneLibrary

Sample Sequences OTUs

Fraction 7Control 319 91IBS-M 324 108IBS-C 291 63IBS-D 342 70

Fraction 10Control 346 119IBS-M 327 100IBS-C 323 90IBS-D 318 78

Fraction 13Control 311 45IBS-M 289 61IBS-C 291 70IBS-D 272 50

OTE. DOTUR was used for the calculation of OTUs with 98% similar-ty criteria.

nd Fusobacteria were detected (data not shown).

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28 KASSINEN ET AL GASTROENTEROLOGY Vol. 133, No. 1

qPCRTo perform a preliminary quantitative analysis

ith the individual samples included in the %G�C pools,set of 9 phylotype-specific qPCR assays was designed on

he basis of some of the differences seen in the phyloge-etic analysis of the clone libraries (Table 2). In addition,

able 4. Novel Near Full-Length 16S rRNA Sequences in All S

Phylum Accession no. Sample Similarity (%) Clos

ctinobacteria AM275775 Control 88.554 Airmicutes AM275415 Control 89.624 Dctinobacteria AM275737 Control 90.283 Dirmicutes AM275764 Control 90.606 Dacteroidetes AM275765 Control 90.817 Airmicutes AM275604 Control 91.764 Airmicutes AM275757 Control 92.158 Actinobacteria AM276076 Control 92.765 Actinobacteria AM276120 Control 93.653 Aacteroidetes AM275718 Control 93.681 Airmicutes AM275741 Control 93.907 Airmicutes AM275589 Control 94.146 Airmicutes AM275546 Control 94.206 Aacteroidetes AM277971 IBS-M 88.749 Airmicutes AM277985 IBS-M 88.814 Airmicutes AM277955 IBS-M 89.759 Airmicutes AM277680 IBS-M 89.966 Airmicutes AM277963 IBS-M 90.976 Airmicutes AM277633 IBS-M 91.557 Dirmicutes AM277333 IBS-M 90.867 Dirmicutes AM277516 IBS-M 91.585 Airmicutes AM277667 IBS-M 91.866 Dctinobacteria AM277970 IBS-M 91.948 Dirmicutes AM277638 IBS-M 92.498 Dirmicutes AM277966 IBS-M 92.545 Airmicutes AM277375 IBS-M 93.122 Airmicutes AM277324 IBS-M 93.666 Airmicutes AM277369 IBS-M 94.265 Airmicutes AM277526 IBS-M 94.651 Airmicutes AM277551 IBS-M 94.655 Dirmicutes AM277455 IBS-M 94.973 Mctinobacteria AM277978 IBS-M 94.976 Airmicutes AM278539 IBS-C 88.979 Dirmicutes AM278620 IBS-C 89.913 Actinobacteria AM278923 IBS-C 90.220 Dirmicutes AM278277 IBS-C 90.349 Airmicutes AM278246 IBS-C 92.241 Airmicutes AM278250 IBS-C 92.271 Dirmicutes AM278918 IBS-C 92.666 Airmicutes AM278926 IBS-C 94.029 Airmicutes AM278590 IBS-C 94.278 Airmicutes AM278916 IBS-C 94.292 Dirmicutes AM278254 IBS-C 94.391 Airmicutes AM278259 IBS-C 94.448 Xirmicutes AM278900 IBS-C 94.582 Actinobacteria AM277063 IBS-D 91.348 Airmicutes AM276746 IBS-D 91.404 Airmicutes AM276386 IBS-D 91.638 Airmicutes AM276409 IBS-D 92.127 Airmicutes AM277070 IBS-D 93.329 Airmicutes AM276744 IBS-D 94.248 Xroteobacteria AM277069 IBS-D 94.463 Airmicutes AM276768 IBS-D 94.719 D

universal eubacterial PCR assay was used to ascertain C

hat DNA could be amplified from each sample with aational efficiency (Figure 3). In this assay, the amplifica-ion of 16S rRNA genes among samples derived from theatients with IBS showed slightly more deviation thanhose from the control subjects. From the 9 assays de-igned on a phylogenetic basis, 3 (Collinsella aerofaciens,

les With �95% Similarity to Any EMBL Sequence

eighbor Description Source

023 Uncultured bacteria Human vagina685 Uncultured bacteria Cow rumen921 Uncultured bacteria Wild gorilla feces628 Uncultured bacteria Reindeer rumen

236 Uncultured bacteria Mouse feces867 Uncultured bacteria Anaerobic digester775 Uncultured bacteria Cow rumen686 Slackia faecicanis Type strain375 Eggerthella lenta Type strain797 Uncultured bacteria Human cecum845 Uncultured bacteria Hudson river sediment666 Uncultured bacteria Swine intestine219 Coprobacillus catenaformis Type strain623 Uncultured bacteria Cow rumen461 Uncultured bacteria Zebra GI tract991 Catabacter hongkongensis Type strain334 Uncultured bacteria Hindgut of larva334 Uncultured bacteria Gazella GI tract247 Uncultured bacteria Turkey cecum306 Uncultured bacteria Turkey cecum528 Uncultured bacteria Swine GI tract610 Uncultured bacteria Piglet GI tract921 Uncultured bacteria Wild gorilla feces277 Uncultured bacteria Turkey cecum641 Uncultured bacteria Cow rumen592 Uncultured bacteria Siwhaho sediment070 Uncultured bacteria Cow rumen687 Uncultured bacteria Cow rumen125 Uncultured bacteria Human colon660 Uncultured bacteria Reindeer rumen2 Clostridium innocuum Type strain

789 Bifidobacterium sp Human feces632 Uncultured bacteria Reindeer rumen126 Uncultured bacteria Cow rumen921 Uncultured bacteria Wild gorilla feces742 Uncultured bacteria Cow rumen019 Uncultured bacteria Zophobas mori GI tract232 Uncultured bacteria Turkey cecum755 Uncultured bacteria Cow rumen832 Uncultured bacteria Swine intestine709 Uncultured bacteria Swine intestine157 Uncultured bacteria Turkey cecum577 Uncultured bacteria Human feces9 Ruminococcus bromii Type strain476 Uncultured bacteria Zebra GI tract874 Uncultured bacteria Termite GI tract469 Dialister nvisus Human oral cavity321 Butyrate-producing bacterium Human feces231 Ruminococcus sp Rat cecum458 Uncultured bacteria Zebra GI tract9 Ruminococcus bromii Type strain891 Enterobacter ludwigii Human urine681 Uncultured bacteria Piglet GI tract

amp

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lostridium cocleatum–related and Coprococcus eutactus–re-

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July 2007 FECAL MICROBIOTA IN IBS 29

ated phylotype assays) showed statistically significantifferences (P � .05) between the 22 control subject and4 IBS patient samples tested (Figure 3). In addition, 2

Ruminococcus torques 94% related and Bifidobacteriumatenulatum) assays revealed some differences (P � .09)Figure 3). Results from the qPCR assays designed forctinobacterial targets Collinsella aerofaciens and Bifidobac-erium catenulatum were of special interest because theseere also in accordance with the RDP II Library Compareool Analysis (Table 6). A single control sample was

hown to underlie the Lactobacillus farciminis–related phy-otype, while all other samples remained negative inPCR (data not shown).

DiscussionThe GI microbiota consists of 1014 bacterial cells,

hich exceeds approximately 10 times the number ofomatic and germ cells in the human body.40 These

icrobes serve as a barrier against pathogens and areital for development of the host immune system. Inddition, the microbial metabolism has both beneficialnd disadvantageous effects on the host’s well-being.owever, the effects of GI microbiota still remain unex-lored in many ways. In this study, we applied sophisti-ated molecular tools for evaluation of the potentialmportance of GI microbiota in IBS. We used the com-ination of 2 methods that have not previously been usedogether in general surveys of human GI microbiota butave proven powerful in comparative studies with othernimals41 and specific bifidobacterial surveys in hu-ans.42 At first, bacterial genomic DNA samples wereG�C profiled to reveal the differences in a scale cover-

ng the entire microbial population.24 This enabled fo-using on the distinct %G�C fractions, where differencesetween the IBS subtypes and controls could be observedFigure 1). Subsequently, from the selected %G�C frac-ions of the analyzed samples, the bacterial 16S rRNAenes were cloned and partially sequenced to obtain moreetailed information of the composition of microbial

able 5. �-LIBSHUFF Comparison Results

�-LIBSHUFFcomparisons Fraction 7 Fraction 10 Fraction 13

(X-Y) XY YX XY YX XY YX

ontrol vs IBS-C .0000 .0000 .0000 .0228 .0000 .0000ontrol vs IBS-D .0000 .0000 .0000 .0326 .0000 .0000ontrol vs IBS-M .0000 .0018 .0000 .0000 .0000 .0002

BS-C vs IBS-D .0000 .0000 .0000 .0176 .0000 .0000BS-C vs IBS-M .0000 .0000 .0008 .0000 .0526 .0093BS-D vs IBS-M .0000 .0000 .0003 .0000 .0000 .0000

OTE. The critical P value for the confidence interval of 95% is .0253. The-LIBSHUFF comparison estimates whether sequence library X is included inequence library Y and vice versa. Thus, significant P values for both com-arisons YX and XY indicate that the gene libraries differ from each other.

opulations. Furthermore, some of the suggested phylo- si

igure 2. Results of the Bayesian population structure analysis on samplesrom fraction (A) 7, (B) 10, and (C) 13. Each dot represents an identified homo-eneous subgroup of bacterial sequences, which is projected into a 2-dimen-ional space using multidimensional scaling of average relative sequence dis-imilarities between the subgroups. In the presence of systematic differencesetween the subgroup compositions for the controls and the IBS symptomubtypes, thedotsappearaswidelyseparatedgroups.Thecoloringusedhere

s as follows: control, black; IBS-D, red; IBS-C, green; IBS-M, blue.

go

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30 KASSINEN ET AL GASTROENTEROLOGY Vol. 133, No. 1

enetic differences could be confirmed by qPCR analysisf individual samples from each test subject.

The %G�C fractionation allowed the enrichment ofare sequences, which otherwise would be covered by

ore abundant ones. Out of the 3753 high-quality se-uences, 53 OTUs corresponding to 98 sequences re-ained novel, with �95% identity to other publicly avail-

ble sequences (Table 4). The majority of the novel OTUsetected were included in phyla Firmicutes (75%) andctinobacteria (15%). Corresponding abundances for Fir-icutes and Actinobacteria within the whole sequence dataere 70% and 2%, respectively. Indeed, the amount ofctinobacteria detected, including Bifidobacterium and Col-

insella (Table 6), was considerably higher in comparisonith a sequencing study by Eckburg et al,43 in which only2 actinobacterial sequences were detected from 11,831acterial 16S rRNA gene sequences. In our study, theost obvious explanation for the abundance of Actinobac-

eria was the use of %G�C profiling before cloning andequencing, which diminished biases against high %G�Cpecies during the amplification steps in the procedure.

Molecular studies based on analysis of the 16S se-uence data have revealed that only 9 bacterial divisionsre represented in the human GI microbiota; indeed, thenormous microbial diversity present in the intestine isue to a lower-level variation that is reflected by theultitude of closely related species or strains revealed by

equencing approaches.44 In this respect, analysis of guticrobiota of patients with IBS did not provide any

able 6. Number of Partial 16S rRNA Sequences Classifiedto Different Taxa by the RDP II Library CompareTool Analysis

Genus Control IBS-M IBS-C IBS-D

raction 7Butyrivibrio 8–9 9 2 0Dorea 2 3 9–10 3–4Lactobacillus 30 0 0 0Lactococcus 0 0 16 0Roseburia 7–8 1 11 5–6Ruminococcus 12 56 61 22–23Streptococcus 3 7 2 33

raction 10Allisonella 3 21–22 2 4Bacteroides 10–11 51–53 13 5Eubacterium 8 1 2–4 0–1Lactobacillus 0 6 0 0Roseburia 19 23–25 34–36 11–12Ruminococcus 8–10 4–5 18 2–6Streptococcus 2 14 5 3

raction 13Bifidobacterium 129 119 137 81Collinsella 116 68 4 17

OTE. The taxa shown here are such that a statistically significantifference (P � .05) was found at least between 1 pairwise compar-

son of the 4 groups. Slight variation in the assignment of sequenceso taxa is expected due to bootstrapping.

ajor exceptions. Sequence data derived from one library t

id not contain any higher taxonomic groups that wouldave been totally missing in the remaining clone libraries.he sequences representing potentially novel species werell included merely in 4 phyla: Firmicutes, Bacteroidetes,ctinobacteria, and Proteobacteria (Table 4). It has been

uggested, however, that lower-level consistency of the GIicrobiota accompanied by other factors (eg, stress, nu-

rition, genetic background of the host) could promotedverse effects toward the host.44

Variation in the GI microbiota of individual healthyubjects has been observed.45 In our study, however, these of pooled samples of several individuals in each studyroup may have diminished some of this variation and

ncreased the reliability of the results in revealing commonutative differences between the IBS and control groups.e compared the sequence data with the �-LIBSHUFF

rogram, the Bayesian analysis of population structureBAPS 4.1), and the RDP II Library Compare Tool, all ofhich indicated the presence of significant divergences be-

ween control samples and various IBS subtypes (Figure 2nd Tables 5 and 6).

In the �-LIBSHUFF analysis, the variation observedetween clone libraries diverged in some cases from whatas anticipated on the basis of the %G�C profiling

esults. This is not unexpected, because the %G�C pro-ling differentiates samples by the amount of genomicNA and the �-LIBSHUFF analysis is based on 16S rRNA

ene libraries representing species diversity. Inversely, it isossible that some differences between the samples re-ained unnoticed and could be revealed by additional

equencing of the yet uncharacterized %G�C fractions.In the multidimensional scaling plot (Figure 2), clear

eparation of the distinct homogeneous sequence groupsdentified by the Bayesian methods reflects the overallarge differences in the sample composition between theontrol subjects and the symptom subtypes. While theontrol and the IBS subtypes share some basic bacterialomposition, the differences are sufficiently substantialo make a distinction between them (with the exceptionf 2 cases). Our scaling technique is similar to that usedy Eckburg et al43 to reveal differences in the intestinalicrobiota among healthy subjects.It is also worth pointing out that the control libraries

ere derived from fecal samples of 23 subjects, whereashe other libraries were built from samples of only 6 –10eople (Table 1). Therefore, considering the natural vari-tion between individual GI microbiota, it would seemeasonable to expect a maximum variety of sequences inach of the control libraries just by chance. However,mong the fraction 13 libraries, composed of clones de-ived from high-GC organisms, the control library seemso display the least diversity in the amount of OTUsTable 3). This is also reflected in the RDP II Libraryompare Tool results (Table 6), where most (79%) of the

ontrol library sequences are classified in genera Bifidobac-

erium and Collinsella. While Bifidobacterium sequences are

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ell represented in all fraction 13 libraries, the numbersf Collinsella appear low in IBS-C and IBS-D libraries. Inomparison with the control library, a substantialmount of sequences thus actually diverge in IBS fromhat is normal.Recently, the presence of phylum-level alterations in

he fecal microbiota of obese people was suggested by6S ribosomal DNA sequencing.8 A decrease in Bacte-oidetes and a corresponding increase in Firmicutes werehown to be associated with a higher body mass index,hile successful losing of weight gradually increased the

elative amount of Bacteroidetes and decreased the countsf Firmicutes sequences.8 The pools of metabolically activeicrobial genes present in the GI tract of lean and obese

eople were also shown to be different, indicating thatissimilar microbial compositions indeed result in al-ered functions of the GI microbiota.46 In our study,lterations of the GI normal microbiota between healthyubjects and patients with IBS were included particularlyn the phyla Firmicutes and Actinobacteria. Although a

igure 3. qPCR results of fecal samples from 24 patients with IBS ando 10416S ribosomal RNA gene copies except for the universal qPCR asBS-M, triangle.

ubstantial group of subjects was covered by the sequenc- e

ng approach, qPCR analysis was applied to provide aore steadfast answer whether the observed differencesere valid in the level of individual samples. In thehylum Firmicutes, the real-time PCR assays for Coprococ-

us eutactus– and Clostridium cocleatum–related sequencesevealed differences between the patients with IBS andealthy control subjects, while the other assays for mem-ers of Firmicutes remained statistically nonsignificantFigure 3).

It should be further noted that the phylum Firmicutesncompasses the majority of the species diversity presentn the GI tract, and a major part of the interestinghylotypes still remains to be analyzed with qPCR tests.n the phylum Actinobacteria, qPCR analysis revealed sig-ificant differences in the counts of C aerofaciens. Thisacterium was found in 96% of all tested control samples,erived from subjects devoid of gastrointestinal distur-ances, and its prevalence is thus well in accordance witharlier reports for this organism.47 In contrast, the preva-ence of C aerofaciens among patients with IBS was consid-

ntrol subjects. For visualization, detection limits of the assays were setSymbols are as follows: Control, tick; IBS-C, open circle; IBS-D, cross;

22 cosay.

rably lower. GI actinobacteria are members of 3 distinct

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32 KASSINEN ET AL GASTROENTEROLOGY Vol. 133, No. 1

rders: Actinomycetales, Bifidobacteriales, and Coriobacteriales.hile some bacterial strains are considered health bene-

ting (probiotic) in both Actinomycetales (eg, Propionibac-erium freudenreichii sp Shermanii) and Bifidobacteriales (eg,ifidobacterium animalis sp lactis Bb-12), the order Coriobac-

eriales may have received too little attention in regard toealth issues. However, an abundance of C aerofaciens

formerly Eubacterium aerofaciens) in the fecal microbiotaas been associated with a low risk of colon cancer.48 To

urther support the observed statistical differences foundFigure 3), we used the same set of qPCR assays to studynother independent group of patients with IBS (n � 29),nd indeed, highly similar results with the same statisticallyignificant differences were obtained (data not shown).

Previous studies suggest that the GI fermentation pat-erns, reflecting the microbial metabolism in the colon,re changed in IBS15 and that there are quantitativelterations in the GI microbiota of patients with IBS.14,17

he importance of the GI bacteria on IBS is also reflectedy intervention studies in which ingestion of probioticacteria has been shown to result in alleviation of theymptoms.49 –51 The findings of our study further supporthe role of GI microbes in IBS. The fecal samples analyzedere have previously been characterized with a limited num-er of qPCR assays22 as well as with conventional plating52

nd denaturing gradient gel electrophoresis.53 The 20PCR assays, detecting known dominant groups of the

ntestinal bacteria as well as species previously associatedith IBS, revealed certain differences between the IBS

ubtypes.22 On the other hand, utilizing a narrow set ofulture-based techniques no major differences were ob-erved, whereas with denaturing gradient gel electro-horesis the GI microbiota of patients with IBS wasound to be temporally more unstable than that of theontrol subjects.52,53 Some contradicting results obtainedn these earlier studies are probably due to the limitationsn the resolution power of the methods used for GI

icrobiota analyses. Instead, the results obtained withhe high-resolution methods applied in our study pro-ide a substantially more comprehensive view of theiversity and alterations of this complex ecosystem.In conclusion, we applied a highly detailed analysis

ombining 2 methods to resolve the average compositionf GI microbiota involved in each IBS subtype and aore profound view with qPCR concerning some differ-

nces observed in the sequencing part of the study. Theesults presented here give evidence that the GI microbiotas indeed significantly altered in IBS and that the microbialomposition varies with the main symptoms of the patients.his striking observation emphasizes that additional re-

earch on the host GI microbiota interactions in IBS iseeded. In the future, our extensive 16S rRNA gene data-ase will serve as a valuable tool for development of new,igh-throughput methods for further characterization and

iagnostics of the GI microbiota in IBS.

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Received September 8, 2006. Accepted March 29, 2007.Address requests for reprints to: Airi Palva, PhD, Department of

asic Veterinary Sciences, Division of Microbiology and Epidemiology,O Box 66, 00014 University of Helsinki, Finland. e-mail: airi.palva@elsinki.fi; fax: (358) 9 191 57033.The authors have no conflicts of interest to disclose.T.R. and J.A.’s current affiliation is Alimetrics Ltd, Helsinki, Finland.Supported by the Finnish Funding Agency for Technology and

nnovation (Tekes), Finnish Graduate School of Applied Bio-ciences.The authors thank Sinikka Ahonen for excellent technical assistance

nd Kyösti Kurikka, MSc, for assistance in the statistical analysis andraphical presentation of the qPCR results. The authors also thank Drsaria Saarela and Jaana Mättö and Kajsa Kajander, MSc for recruiting

he study subjects.