A gene-targeted approach to investigate the intestinal butyrate-producing bacterialcommunity
Microbiome volume 1, Article number: 8 (2013)
Butyrate, which is produced by the human microbiome, is essential for awell-functioning colon. Bacteria that produce butyrate are phylogeneticallydiverse, which hinders their accurate detection based on conventional phylogeneticmarkers. As a result, reliable information on this important bacterial group isoften lacking in microbiome research.
In this study we describe a gene-targeted approach for 454 pyrotag sequencing andquantitative polymerase chain reaction for the final genes in the two primarybacterial butyrate synthesis pathways, butyryl-CoA:acetate CoA-transferase(but) and butyrate kinase (buk). We monitored theestablishment and early succession of butyrate-producing communities in fourpatients with ulcerative colitis who underwent a colectomy with ileal pouch analanastomosis and compared it with three control samples from healthy colons. Allpatients established an abundant butyrate-producing community (approximately 5% to26% of the total community) in the pouch within the 2-month study, but patternswere distinctive among individuals. Only one patient harbored a community profilesimilar to the healthy controls, in which there was a predominance of butgenes that are similar to reference genes from Acidaminococcus sp.,Eubacterium sp., Faecalibacterium prausnitzii andRoseburia sp., and an almost complete absence of buk genes.Two patients were greatly enriched in buk genes similar to those ofClostridium butyricum and C. perfringens, whereas a fourthpatient displayed abundant communities containing both genes. Most butyrateproducers identified in previous studies were detected and the general patterns oftaxa found were supported by 16S rRNA gene pyrotag analysis, but thegene-targeted approach provided more detail about the potential butyrate-producingmembers of the community.
The presented approach provides quantitative and genotypic insights intobutyrate-producing communities and facilitates a more specific functionalcharacterization of the intestinal microbiome. Furthermore, our analysis refinesbut and buk reference annotations found in centraldatabases.
The relationship between a healthy functioning gut microbiome and overall humanwell-being is firmly established. Recently, large-scale projects in this field, namelythe Human Microbiome Project and the Metagenomics of the Human Intestinal Tractframework program, have been launched, with the goal of developing a holisticunderstanding of the composition and functional properties of intestinal bacteria andtheir effects on the human host. Numerous host-microbiome interactions have beenreported and microbial-derived metabolites such as vitamins or short chain fatty acidshave been of specific interest in many studies (see [1, 2]). Among these, butyrate is consideredas one of the most important metabolites as it serves as the major energy source ofcolonocytes; has anti-inflammatory properties; and regulates gene expression,differentiation and apoptosis in host cells .
Much of the information on the diversity of butyrate-producing bacteria has depended onculture-independent methods, however recent cultivation efforts for some of these strictanaerobes have been successful . The existingisolates within this functional group are phylogenetically diverse, with the two mostabundant groups related to Eubacterium spp. and Roseburia spp.(Clostridium cluster XIVa) and Faecalibacterium prausnitzii (Clostridiumcluster IV) . However, both clusters includeadditional non-butyrate-producing species. As such, 16S rRNA gene-targetedanalysis often cannot distinguish the butyrate-producing from the non-producingcommunity in a sample . Furthermore, it isincreasingly recognized that horizontal gene transfer, which uncouples bacterialfunction from phylogeny, plays an important role in shaping the human microbiome. The shortcomings of relying only ontraditional 16S rRNA gene-based phylogenetic analysis for functional inferencesare now recognized in many other fields of microbial ecology. To resolve this,functional gene-targeted sequencing has emerged as the method of choice to investigatemicrobial functionality independent of phylogeny. This method has been used in severalstudies examining the nitrogen cycle ,degradation of xenobiotic compounds  andantibiotic resistance of gut bacteria .These studies have demonstrated the value of obtaining a detailed insight into specificmicrobial processes.
In the human gut, butyrate is produced through two main pathways, thebutyryl-CoA:acetate CoA-transferase pathway (but) and the butyrate kinase(buk), and previous studies on colonic isolates of healthy individuals haveillustrated that the but pathway predominates . Consequently, Louis and Flint  developed a semi-quantitative PCR protocol targeting aselection of but sequences and used the same primers to construct clonelibraries from fecal samples that revealed high gene diversity, including severalunknown operational taxonomic units (based on a 98% DNA similarity ).
In this study, we present a novel approach that targets a broad range of butand buk genes based on both 454 pyrotag sequencing in combination with theRibosomal Database Project’s (RDP) functional gene pipeline  and on quantitative PCR targeting selected groups ofbutyrate producers. The presented methods were applied on luminal samples from patientswith ulcerative colitis (UC) who underwent a colectomy followed by ileal pouch analanastomosis (IPAA) as described in the accompanying paper by Young etal.. In this procedure, theentire colon is resected, the terminal ileum is fashioned into a pouch and connected tothe anal canal, and intestinal flow is re-established. Previous data indicate thatapproximately half of patients will develop pouchitis within 1 year, aninflammatory condition similar to UC .Because of the clinical similarity between pouchitis and UC, it is thought that studyingthe development of pouchitis can be used to reveal the etiology of UC. Several studiesreported dysbiosis of the intestinal microbiome in patients with UC [16, 17]. However, it is unclearwhether the observed microbiome changes are the cause or the consequence of UC. Thesedifficulties make pouchitis an ideal model system as it allows for the clinicalobservation of individuals from “time zero”, when fecal flow is initiatedthrough the newly established, disease-free pouch. In this study, we specificallymonitored the initial establishment (first 2 months) of butyrate-producingmicrobial communities in four patients after IPAA and compared the results with healthycontrols.
Processing of samples
In this study, four patients with a history of UC undergoing total abdominalcolectomy with IPAA were identified from the outpatient and inpatient practices ofgastroenterologists and colorectal surgeons at the University of Chicago MedicalCenter between 2010 and 2011. All four patients had a confirmed diagnosis of UC basedon endoscopy and pathology findings, were scheduled for a total proctocolectomy withIPAA, and were willing and able to participate in the study. Exclusion criteriaincluded pregnancy or inability to give informed consent. All patients gave writteninformed consent before screening. The Institutional Review Board of the Universityof Chicago Medical Center approved this study protocol. For each patient, one samplewas collected prior to ileostomy takedown (except for patient 200) and an additionalthree samples were collected over a period of 2 months after connection of thepouch to the anal canal (Table 1). None of the patientsreceived antibiotic treatment during the period of this study. All samples wereobtained from stool aspirates. Sterile saline was injected to liquefy the stool andcontents were sampled using the suction port of the colonoscope. Bulk DNA wasextracted using the UltraClean Mega Soil DNA Isolation Kit (MO BIO Laboratories,Inc., Carlsbad, CA, USA) according to the manufacturer’s protocol. Healthycolon samples were obtained from the recto-sigmoid section of the colon without priorbowel preparation to ensure that the microbiota was not altered by this procedure.For additional details on sample collection and storage, see .
Primers, amplicon generation and 454 pyrotag sequencing
Primers were designed based on the Fungene database for the butyryl-CoA:acetateCoA-transferase (but) and butyrate kinase (buk) genes(Table 2 - for more details see Additional file1: Figures S1 and S2 and Tables S1 and S2). Threebarcoded forward and three reverse primers with fused adaptors for the Lib-A system(454 Life Sciences, Branford, CT, USA) were designed for each gene. The aim was toobtain broad coverage without exceeding a degeneracy of 100. For PCR, each forwardprimer (0.4 μM final concentration) was used separately in triplicatesamples and was mixed with all three corresponding reverse primers(0.16 μM final concentration each), except for but_1F, where each reverseprimer was used in a separate reaction. Because of the low target concentrations inmany samples, sufficient amplification was often difficult. Therefore, extracted DNAwas subjected to whole genome amplification (WGA; illustra GenomiPhi V2 DNAAmplification Kit, GE Healthcare, Little Chalfont, UK) to increase templateconcentration. A total of 150 ng of WGA template was used for each PCR reactionusing the GoTaq Flexi system (Promega, Madison, WI, USA; total volume of 12.5μL). Because primers do not perfectly match all desired targets (Additional file1: Tables S1 and S2), PCR stringency was low for bothgenes with an annealing temperature of 54°C and high MgCl2concentrations of 3 mM. Furthermore, higher cycle numbers (35×) were usedto increase yield. Thermocycling was done as follows: 2 min at 95°C;45 s at 95°C, 45 s at 54°C, 45 s at 72°C (×35);10 min at 72°C. PCR products were pooled for each forward primer(triplicate reactions), gel-extracted (QIAquick Gel Extraction Kit; Qiagen, Valencia,CA, USA) and purified (QIAquick Gel Purification Kit; Qiagen). Several bands werevisible on gels (especially for but) and only the target bands locatedaround 425 (but) and 500 (buk) were excised. Nonspecific binding ofprimers was reduced with increased target concentrations. A re-conditioning step ofpurified product was essential to avoid short reads during sequencing. Each samplewas re-amplified (0.2 ng of generated amplicons as template, 60°Cannealing temperature, 15 cycles, total volume of 50 μL) using theAccuPrime PCR system (Life Technologies, Grand Island, NY, USA) with primers(0.4 μM final concentration) targeting whole adaptor sequences. PCRproducts were gel-extracted and purified again. Sequencing was performed with a 454Junior System according to the manufacturer (454 Life Sciences). For each run, eightsamples (four from each gene) were mixed at equal concentrations. We are aware thatthe protocol used, including WGA followed by a high cycle number PCR and a finalre-amplification step, may have introduced bias. However, comparing all obtainedresults derived from different methods suggested that the procedure did not alter themain trends (see main text).
Quantitative real time PCR
Primers designed for quantitative PCR (qPCR; Table 2)targeting the but/buk genes were based on the Fungene database andwere specific to all desired target genes with at least two mismatches in one or bothprimers for other non-target but/buk genes. BLAST analysisillustrated no significant matches to other unrelated sequences. The 16SrRNA gene primers (Rrec2 and Fprau) targeting butyrate producers aredescribed in Ramirez-Farias et al.. Total 16S rRNA gene community qPCR primers werebased on Leigh et al..Additionally, primers for the 16S rRNA genes of C. butyricum weredesigned based on the RDP database. Specific amplification of targets was verifiedfor all primers using the following pure cultures (amplification efficiency pernanogram of pure culture is given in brackets): Bacillus licheniformis ATCC14580, Bacteroidetes thetaiotaomicron E50, C. acetobutylicum ATCC824 (2.65 × 105), C. difficile ATCC 630, C.perfringens ATCC 13124 (4.88 × 105),Eubacterium hallii DSM(Z) 3353, E. rectale DSM(Z) 17629(4.06 × 105), Faecalibacterium prausnitziiDSM(Z) 17677 (5.53 × 105), Roseburiaintestinalis DSM(Z) 14610 (1.80 × 105) and R.inulinivorans DSM(Z) 16841 (4.73 × 105). Strainswere purchased either from ATCC or DSM(Z) (as indicated in name). B.licheniformis and B. thetaiotaomicron E50 were provided byDaniel Clemens. For the primers targeting Acidaminococcus (butgene) and C. butyricum, (16S rRNA gene), instead of a pure culture,a patient sample containing many target bacteria (based on all methods presentedhere) served as a positive control.
Amplification was performed with the SYBR Green Master Mix (Life Technologies) with10 ng template DNA per reaction (total volume of 15 μL; no WGA except forthe healthy control samples) in 384-well plates (ABI Prism 7900 HT, LifeTechnologies). Annealing temperatures and final primer concentrations were asfollows: G_buk (64°C; 0.83 μM), Cbuty (66°C;0.67 μM), FPR/Fprau (60°C; 0.83 μM), G_Acida (67°C;0.83 μM), G_Fprsn (70°C; 0.83 μM), G_Ros/Eub (62°C;0.83 μM; G_Ros_R and G_Eub_R were mixed together at equal finalconcentrations of 0.42 μM), Rrec/Erec (60°C; 0.83 μM; thetwo forward primers were mixed together at equal final concentrations of0.42 μM) and total 16S (60°C; 0.67 μM). Thermocycling wasdone as follows; 2 min at 50°C; 10 min at 95°C; 45 s at95°C; 45 s at individual annealing temperature; and 45 s at72°C (for total 16S rRNA, elongation at 72°C was omitted)(×40). Analysis was performed in duplicate samples. Genomic DNA of R.inulinivorans, F. prausnitzii and C. perfringens (forfunctional gene qPCRs) and cloned amplified products (for 16S qPCRs and G_Acida; TOPOcloning kit, Life Technologies) at concentrations of 102 to 107copies (10-fold dilutions) were used for standard curves to determine targetconcentrations. Genomic DNA of Desulfotomaculum acetoxidans DSM 771 with 1016S rRNA gene copy numbers was used for the standard curve(103 to 108) for total 16S rRNA genequantification. The detection limit was set as 102 target sequences forall primers and results are expressed as a percentage of the total bacterialcommunity based on total 16S rRNA gene qPCR. For 16S rRNA gene copynumber normalizations of specific 16S rRNA targets see below (comparingfunctional gene results to 16S pyrotag data). Because but/buk targetsequences are present as a single copy per genome, qPCR results of functional geneswere multiplied by five to account for multiple 16S rRNA gene copies (fiveon average) of the intestinal bacterial flora).
Raw reads matching barcodes (106,708 for but and 84,222 for buk)were processed using the RDP pyro-sequencing pipeline , where 87% but and 94% buk sequencespassed quality filtering. Subsequently, sequences were subjected to RDP FrameBot forframeshift corrections and closest match assignments. To develop a reference sequenceset for FrameBot, we took the corresponding gene sequence sets from the Fungenedatabase, developed through (Hidden Markov Model) HMM searches of the National Centerfor Biotechnology Information protein database, and removed partial sequences withless than 93% coverage (that is, last filled model position - first filled modelposition/model length) to the full gene length HMM model, giving 452 but and422 buk reference sequences. For buk, 97% reads that passed theinitial process passed FrameBot with minimum 30% identity to the closest match and125 amino acids in length. On average, 1.6 frameshifts were corrected per sequenceand 58% of the sequences contained at least one frameshift. For but, 59%reads that passed the initial process passed FrameBot with minimum 30% identity and100 amino acids in length. The majority of non-passing sequences were identified ashuman origin. On average, 0.6 frameshifts were corrected per sequence, 30% of thesequences contained at least one frameshift. Sequences can be accessed atSRA062948.
Ordination and diversity analysis
For each gene, the frameshift-corrected protein sequences were aligned using HMMER3and clustered using RDP mcClust with the complete-linkage algorithm. Only ampliconswith an identity of ≥70% to the closest matches in the reference (97% ofbut and 93% of buk sequences) were used for additionalphylogenetic tree and ordination analysis, as we were not confident that more distantmatches were bona fide but or buk. Additional filtering wasperformed based on neighbor joining tree analysis of reference sequences (see Resultsand Additional file 1). The remaining sequences were binnedaccording to closest match assignments with reference sequences showing less than 2%dissimilarity merged (based on Figures 1 and 2). Results of both genes were combined and the entire butyratecommunity of each sample was used for ordination analysis. The nonmetricmultidimensional scaling based on Chao corrected Jaccard index distance was performedusing the vegan package in the R environment . Both patients and time points were grouped for analysis.Diversity analysis (Shannon index) was calculated using the Biodiversity Rpackage.
Comparing functional gene results to 16S pyrotag data
For library generation of 16S rRNA gene analysis and pyro-sequencing see Young etal.. For the first healthycontrol, no data on luminal aspirate were available and shown results are based on acolon biopsy sample of the same individual. Data were analyzed for known butyrateproducers in the human colon at the genus level (based on  and obtained but/buk gene sequences) except forClostridia, where species discrimination was applied. All results werenormalized to five 16S rRNA gene copy numbers, which represented the averagefor Firmicutes and Bacteroidetes, the two most abundant phyla in the gut. Averagecopy number of each genus was derived from rrnDB  and the Integrated Microbial Genome database . A list of taxa searched as well as individual16S rRNA gene copy numbers is presented in Additional file 1: Table S3.
Investigating butgene diversity
Several short chain fatty acid (SCFA) transferases have been characterized thatexhibit broad substrate specificities and show remarkable sequence similarities. Consequently, existingannotations in public databases are often unreliable and misleading. In ourestablished Fungene database, many known but sequences are wrongly annotated(due to GenBank’s annotation) and SCFA transferases similar to butsuch as 4-hydroxybutyrate CoA transferases (4hbt) are present. A neighborjoining tree of all sequences from Fungene’s butyryl-CoA:acetateCoA-transferase (but) database (>93% coverage to model; to ensure onlyfull-length sequences were considered) was constructed where all functionallyverified but genes cluster together and apart from 4hbt genes(Additional file 1: Figure S1). Primers were designed tospecifically target those but sequences. However, it is still likely thatSCFA transferases related to but are amplified as well. In order toquality filter our obtained but sequences (in addition to the processingpipeline presented in the Methods section), only sequences located withinthe cluster identified in Additional file 1: Figure S1 wereregarded as likely real but, whereas the remaining amplicons (<1%)matching 16 references outside the cluster were excluded from further analysis. Wedetected a broad diversity of but genes in our samples and they were linkedto almost all described but carrying species (Figure 1A). Four closest FrameBot matches were assigned to 75% of all obtainedsequences, namely R. intestinalis L1-82, R. inulinivorans A2-194,Acidaminococcus sp. D21 and E. rectale ATCC 33656. To verify theclosest match assignments all amplicons were mapped on a tree together withfull-length reference sequences using Pplacer (; Additional file 1: Figure S3). Weobserved minimal deep branching; nearly all amplicons diverged in the terminalbranches to the reference sequences, and the numbers assigned correlated well withthe FrameBot closest match assignments. An exception was Clostridium sp.SS3/4 where many more amplicons than expected, that FrameBot had originally assignedto C. symbiosum and Clostridium sp. M62/1, mapped to that referencesequence. The discrepancies were most likely due to the different underlyingassignment methods used by FrameBot and Pplacer. The former comparesblossum62-corrected pairwise distances, whereas the latter is based on maximumlikelihood criteria. Conservation analysis of but showed a remarkablysimilar pattern between the reference and amplicon sequences, and severalwell-conserved amino acid sites (>95% conservation in both groups) were identified(Figure 1B).
Investigating bukgene diversity
A considerable diversity of buk sequences that included sequences similar tothe majority of previously described butyrate producers were detected in our samples(Figure 2A). The Fungene database contains manysequences assigned to species not reported to produce butyrate, such as members ofthe phylum Bacteroidetes. Many of our amplicons closely matched sequencesoriginating in Bacteroides and the established tree clusters them togetherwith known butyrate producers and apart from acetate kinase, a closely related gene(Figure 2A; a neighbor joining tree of all Fungenesequences (93% cut-off) is shown in Additional file 1:Figure S2). Therefore, we included those sequences for analysis. Three quarters ofall obtained buk amplicon sequences were assigned to four closest FrameBotmatches; Bacteroides sp. D2, Bacteroides sp. 3_2_5, C.butyricum 5521 and C. perfringens. The resultant tree including themapped amplicon sequences confirmed closest match assignments (Additional file1: Figure S4). Sequence analysis revealed lesssimilarity among buk genes than observed for but and fewerconserved amino acids could be detected (Figure 2B versusFigure 1B).
Ordination and diversity analysis of obtained data
Nonmetric multidimensional scaling analysis of the total butyrate-producing community(but and buk genes together) revealed a unique community patternfor individual patients, which all clustered distinct from the healthy controlsamples (Figure 3). However, the successional trend wasdifferent for all patients (Additional file 1: Figure S8).Diversity calculations also did not reveal a consistent successional pattern. WhereasShannon diversity increased for patients 200 and 206, no change was detected for 207,and 210 demonstrated a decrease over time (Figure 4). Atthe fourth visit, all communities analyzed displayed a comparable diversity value,which was similar to that of the healthy control samples.
Quantitative analysis of but/bukgenes
Functional gene pyro-sequencing only allows for relative abundance measurements ineach sample. Hence, we developed a complementary qPCR approach. Clear patternsemerged from qPCR of the buk and but genes. Whereas no target genescould be detected in the luminal aspirate before ileostomy takedown (visit 1; nosample was available for patient 200), abundant butyrate-producing communities becameestablished in all patients over time (Figure 5). Theobserved community profiles were distinct between patients. Patients 206 and 207 wereenriched in buk genes (up to 19.9% of the total community), whereasbut was almost absent. Patient 210 was unique in the development of acommunity similar to the healthy controls, harboring but genes most closelyrelated to both F. prausnitzii and Roseburia sp./E.rectale. Additionally, this patient exhibited abundant but-carryingAcidaminococcus sp. communities, which were absent in the healthy controlsamples. At visits three and four, 15.5% and 26% of patient 210’s totalmicrobial community exhibited but genes, which was within the broad rangefor the control samples with 4.4%, 2.6% and 74.1%, respectively. In patient 200, weinitially detected only buk genes, but a considerable but-genecommunity linked to Roseburia sp./E. rectale was established overtime as well.
Investigating the butyrate-producing community based on 16S rRNAgeneanalysis
We retrieved the major known butyrate-producing taxa from literature  and from the but and buk data andused this information to screen for those taxa in the total 16S 454 pyrotag analysispresented in the accompanying paper .Results are displayed in Figure 6A. Additionally, qPCRtargeting specific butyrate producers was performed (Figure 6C). 16S rRNA gene analysis supported the functional gene resultsin that similar overall patterns were detected by the two different techniques.Communities linked to buk were dominated by sequences similar to those ofC. butyricum and C. perfringens, whereas sequences similar toAcidaminococcus sp., F. prausnitzii and Roseburia sp.comprised the majority of but-associated bacteria in both methods(Figures 5 and 6, Additionalfile 1: Figures S3 and S4). Nevertheless, severaldifferences between 16S rRNA gene and functional gene analysis wereobserved. Only a minute fraction from 16S rRNA gene pyrotag data wasidentified as Eubacterium sp., whereas many but sequences wereassigned to strains of E. hallii and E. rectale. Other studies thatutilized fluorescence in-situ hybridization and clone libraries reportedhigh concentrations of those strains in the healthy colonic microbial flora[4, 25], whichsuggests that 16S rRNA gene-based analysis could not reliably discriminatethem from other taxa. Furthermore, Subdoligranulum sp., which contain onebutyrate-producing isolate, S. variabile ( has the gene buk), were not detected in thefunctional gene data. But if this genus is considered to be butyrate-producing, thenthe 16S rRNA gene analysis suggests a considerable abundance of bukgenes in healthy control samples. Similarly, many more 16S rRNA genesequences were assigned to Acidaminococcus sp., Anaerostipes sp.,Coprococcus sp. and Peptoniphilus sp. in certain samplescompared with the results obtained from the functional gene analysis. These findingssupport earlier reports that butyrate synthesis is often not a homogenous feature ofall members of a genus [4, 5] and strengthens the application of higher taxonomic resolutiontechniques to adequately assess the butyrate-producing potential of bacterialcommunities. Species resolution is also crucial for the functionally diverse genusClostridia. Several butyrate-producing members such asClostridium sp. SS2/1, Clostridium sp. M62/1, C.acetobutylicum, C. carboxidivorans and C. symbiosum were matched tonumerous functional gene sequences, but could not be detected in the 16SrRNA gene data.
In this study we show that functional gene-targeted analysis of the intestinal bacterialbutyrate-producing community can overcome limitations imposed by relying solely on16S rRNA gene targeted investigations. A combination of 454 pyrotagsequencing with qPCR analysis was essential to resolve the full differences amongsamples. Pyro-sequencing provided specific community profiles at great depth, whereasqPCR enabled the absolute quantification of genes. Ordination analysis based on pyrotagdata revealed individual community patterns for each patient distinct from those of thehealthy controls (Figure 3); however, only qPCR coulddemonstrate that overall gene concentrations differed over several orders of magnitude(Figure 5). Notably, the presented protocol for amplicongeneration enabled amplification of genes for all samples, although actual abundance ofindividual targets was often below qPCR thresholds.
An abundant butyrate-producing community is essential for a well-functioning colon. Butyrate is also the preferredenergy generating substrate for the pouch epithelium and it is believed that supplydeficiencies could initiate or promote development of pouchitis . The pouch was aerobic before ileostomy takedown and onlybecame anoxic after it was connected to the anal canal, which limits oxygen influx andpromotes the establishment of anaerobes. Anoxic/oxic ratios of cultivars steadilyincreased over time after ileostomy takedown in all investigated patients . In this study, we could demonstrate that theseenvironmental changes were accompanied by the development of butyrate-producingcommunities at abundances similar to healthy participants of other studies and to the healthy controls of thisstudy. However, only patient 210 displayed a community pattern comparable to healthycontrol samples, which was also the case in the companion global 16S rRNA communityanalysis . Patients 206 and 207 exhibitedabnormal communities with buk genes predominating and only very few detectablebut genes. Patient 200 displayed an ‘in-between’ communityharboring both genes. Currently, the buk pathway is not considered to beimportant for butyrate production in healthy individuals , a finding further supported by this study. Whether thehighly abundant buk-containing communities in patients 206 and 207 cancompensate for low concentration of but is unclear. Unfortunately, no SCFA dataare available to address this question. Enzyme assays on 17 butyrate-producing isolatesdemonstrated considerably higher activities for but than forbuk, suggesting that thebut pathway yields more butyrate in comparison to synthesis viabuk. Interestingly, patient 210 is the only individual who did not showonset of inflammation 25 months post ileostomy takedown, whereas patients 200(8 months), 206 (16 months) and 207 (17 months) all developedpouchitis. Although the patient number is low in this study, it does suggest that theinitial establishment of a ‘healthy type’ butyrate-producing community isimportant to maintain a well-functioning pouch and to prevent the development ofdisease. The specific question of how butyrate production affects the development ofdisease will be addressed in a follow-up study where community profiles of patientsundergoing IPAA will be monitored until the onset of inflammation and compared withthose derived from asymptomatic individuals.
Our approach directly targets the genes coding for butyrate-synthesizing enzymes. We didobserve some discrepancies between phylogeny and predicted function, which wasespecially true for the obtained buk gene sequences assigned to members of thegenus Bacteroides. Bacteroides are currently not considered butyrate producersand several culture-based investigations point out their inability to synthesizebutyrate (for examples, see [29, 30]). This also applies to many other sequences presented inAdditional file 1: Figure S2. Interestingly, some earlystudies from the 1980s indicated butyrate production by closely related bacteria, namelycertain Porphyromonas (former Bacteroides) strains [31, 32]. However, additionalstudies specifically investigating butyrate synthesis including moreBacteroides strains (and other candidates) under several differentphysiological conditions are needed to address this issue. Furthermore, even for knownbutyrate-synthesizing bacteria, gene detection does not automatically imply productionof butyrate. Gene expression and a functioning pathway are determined by environmentalconditions, with oxygen concentration as likely the most important factor . Most butyrate producers are considered to be strictanaerobes with their growth and function strongly coupled. However, it has been recentlyshown that certain butyrate producers, namely F. prausnitzii, can also growunder microaerophilic conditions using extracellular oxygen as the final electronacceptor . Butyrate production by thisbacterium was still detected under these conditions but at a reduced rate.
The presented protocols provide a new approach to more specifically resolve thebutyrate-producing community. We could clearly demonstrate that butyrate producers wereestablished at high abundance (approximately 5% to 26% of total bacterial community) inthe pouch of all patients undergoing an IPAA within the first 2 months afterileostomy takedown. Community profiles were distinctive among patients. Most important,one individual harbored a community profile similar to the healthy controls withbut genes predominating and an almost complete absence of bukgenes, whereas the other three patients had other variants. Only the former patientremained healthy 25 months later. 16S rRNA gene analysis showed similaroverall patterns as the functional gene-targeted approach, but only the latter couldreveal specific details on butyrate-producing taxa that were essential to assess theentire butyrogenic potential of the microbial communities analyzed. Furthermore, ouranalysis refines but and buk reference annotations found in centraldatabases. In the near future, these methods will be complemented by metagenomic toolsthat will provide full-length gene sequences without prior amplification and willfacilitate the investigation of not only individual genes of interest but also completesynthesis pathways.
Basic Local Alignment Search Tool
Hidden Markov Model
Ileal pouch analanastomosis
Polymerase chain reaction
Quantitative polymerase chainreaction
Ribosomal Database Project
Short chain fatty acid
Whole genome amplification
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Financial support was provided by NIH Human Microbiome Project Demonstration Project(UH3 DK083993) and the University of Chicago Digestive Disease Research Core Center(P30DK42086). Special thanks to Charles Falkiewicz, Jiarong Gao, Stephanie LaHaye,Craig McMullen, Derek St. Louis and Andrew Worden for technical assistance, and toChristopher Radek for his support during sequencing. The authors acknowledge DanielClemens for providing several strains.
The authors declare that they have no competing interests.
All authors contributed in the organization and design of experiments as well as datainterpretation and manuscript preparation. VBY, MLS, EBC, GBH, TMS and JMT developed thestudy. MV, CRP, QW, JRC and JMT wrote the paper. CRP and MV designed the primers. MVcoordinated the laboratory work. QW, JRC and MV did sequence analysis and carried outthe statistical analysis. LR, EBC and DAA provided the samples. MLS and HGM provided the16S rRNA sequence data. All authors read and approved the final version of themanuscript.
Electronic supplementary material
Additional file 1: Table S1: All sequences from the green highlighted section presented in Figure S1are shown (as they appear in the tree). Sequences with knownbutyryl-CoA:acetate CoA-transferase (but) activity  are shown in bold. Coverage of primers fromthis study (BUT_F/BUT_R) and of those presented in reference  (Ref_F/Ref_R) is shown, where number ofmismatches (MM) per target sequence (based on RDP’s ProbeMatch) isindicated as a color code. BUT_F/BUT_R: green – 0-1 MM, yellow – 2MM (results are merged from all 3 forward and reverse primers, respectively);Ref_F: green – 0-4 MM, yellow – 5 MM; Ref_R green - 0-2 MM, yellow– 3MM (categorization is based on primer description and testing from). Sequences marked as redare predicted to not amplify. Table S2. All sequences from the greenhighlighted section presented in Figure S2 are shown (as they appear inthe tree). Sequences with known butyrate kinase (buk) activity are shown in bold. Coverageof primers from this study (BUK_F/BUK_R) is shown, where number of mismatches(MM) per target sequence (based on RDP’s ProbeMatch) is indicated as acolor code. Green – 0-1 MM, yellow – 2 MM (results are merged fromall 3 forward and reverse primers, respectively). Sequences marked as red arepredicted to not amplify. Table S3. Butyrate-producing candidates (basedon  and additional taxa wherebut/buk genes were detected in this study) searched for in theobtained 16S rRNA gene data and their corresponding gene copy numbersbased on rrnDB (http://rrndb.mmg.msu.edu) and IMG (http://img.jgi.doe.gov).Figure S1. A neighbor joining tree of all sequences fromFungene’s butyryl-CoA:acetate CoA-transferase (but) database(>93% coverage to model; to ensure only full length sequences were considered).All but reference sequences with known function  group together in the section highlightedin green and apart from 4-hydroxybutyrate:butyryl CoA transferases(4hbt, highlighted in red). Several reference sequences from eachgroup are indicated as stars (for but see Table S1,4hbd: Clostridium klyuveri (153955632), C. tetani(28210230), Anaerostipes caccae (76096774) and C.aminobutyricum (188032706)). All sequences in the green section areconsidered probable but sequences in this study. For details aboutprimer coverage see Table S1. Figure S2. A neighbor-joining tree of allsequences from Fungene’s butyrate kinase (buk) database (>93%coverage to model; to ensure only full length sequences were considered).Eighty-eight percent of sequences are annotated as butyrate kinase and mostsequences cluster apart from acetate kinase, a closely related gene(highlighted in red; two sequences with known acetate kinase function fromBacillus subtilis (405134) and Escherichia coli K-12(67462089) were added to the tree (indicated as a star)). Only a few sequenceshave been verified biochemically as butyrate kinases (, indicated as stars) and all clustered together inone group (highlighted in green). Primers were designed to target most of thesequences in the green block as well as many targets outside this group. Fordetails see Table S2. Figure S3. A maximum likelihood tree of FrameBotreference sequences for butyryl-CoA:acetate CoA-transferase (but)using PhyML . Each ampliconsequence was placed onto this fixed reference tree using Pplacer  under maximum likelihood criteria. Theheight of each branch is proportional to the number of amplicons diverging fromthe tree along the branch. Bootstrap values are indicated. Figure S4. Amaximum likelihood tree of FrameBot reference sequences for butyrate kinase(buk) using PhyML .Each amplicon sequence was placed onto this fixed reference tree using Pplacer under maximum likelihoodcriteria. The height of each branch is proportional to the number of ampliconsdiverging from the tree along the branch. Bootstrap values are indicated.Figure S5. Pyrosequencing results of amplifiedbutyryl-CoA:acetate-CoA transferase (but) sequences. Results are shownas percentage (log10) of total reads per sample. Figure S6.Pyrosequencing results of amplified butyrate kinase (buk) sequences.Results are shown as percentage (log10) of total reads per sample. FigureS7. Shepard plot of the nonmetric multidimensional scaling (NMDS)analysis shown in Figure 3. Figure S8. Nonmetric multidimensionalscaling (NMDS) analysis of the total butyrate producing community -butyryl-CoA:acetate-CoA transferase (but) and butyrate kinase(buk) genes together - based on visits is shown. Ellipses representthe 95% confidence interval on standard errors of means. (PDF 1009 KB)
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Vital, M., Penton, C.R., Wang, Q. et al. A gene-targeted approach to investigate the intestinal butyrate-producing bacterialcommunity. Microbiome 1, 8 (2013). https://doi.org/10.1186/2049-2618-1-8