Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, Laboratory of Gastrointestinal Microbiology, Nanjing Agricultural University, Nanjing, JiangsuProvince, China
Bromochloromethane (BCM), an inhibitor of methanogenesis, has been used in animal production. However, little is knownabout its impact on the intestinal microbiota and metabolic patterns. The present study aimed to investigate the effect of BCMon the colonic bacterial community and metabolism by establishing a Wistar rat model. Twenty male Wistar rats were randomlydivided into two groups (control and treated with BCM) and raised for 6 weeks. Bacterial fermentation products in the cecumwere determined, and colonic methanogens and sulfate-reducing bacteria (SRB) were quantified. The colonic microbiota wasanalyzed by pyrosequencing of the 16S rRNA genes, and metabolites were profiled by gas chromatography and mass spectrome-try. The results showed that BCM did not affect body weight and feed intake, but it did significantly change the intestinal meta-bolic profiles. Cecal protein fermentation was enhanced by BCM, as methylamine, putrescine, phenylethylamine, tyramine, andskatole were significantly increased. Colonic fatty acid and carbohydrate concentrations were significantly decreased, indicatingthe perturbation of lipid and carbohydrate metabolism by BCM. BCM treatment decreased the abundance of methanogen popu-lations, while SRB were increased in the colon. BCM did not affect the total colonic bacterial counts but significantly altered thebacterial community composition by decreasing the abundance of actinobacteria, acidobacteria, and proteobacteria. The resultsdemonstrated that BCM treatment significantly altered the microbiotic and metabolite profiles in the intestines, which may pro-vide further information on the use of BCM in animal production.
Bromochloromethane (BCM) (CH2BrCl, CAS no. 74-97-5) isan analog of dihalogenated methane. Unintentional con-
sumption of this unregulated halomethane as a by-product of dis-infection in drinking water is one of the major sources for BCMexposure (1, 2) and has been linked to an increased risk of stomachcancer in Finland (3). Long-term exposure to BCM may causehepato- and nephrotoxicity in humans. Budnik et al. (4) reviewed542 publications between 1990 and 2011 and found 91 publica-tions referring to the toxicity of halomethanes on lungs, skin, liver,muscle, spleen, kidneys, and the central nervous system. Althoughthe gastrointestinal tract (GIT) comes in direct contact with in-gested BCM, very few studies have focused on the influence ofBCM on the GIT, let alone on the intestinal microbiota.
BCM can be used as an antimethanogenic compound to de-crease methane production. BCM supplementation at 0.3 g/100kg of body weight (BW) significantly decreased methane produc-tion and methanogen abundance in Japanese goats (5), lactatingdairy goats (6), steers (7), and Sprague-Dawley (SD) rats (8). BCMinhibits methanogenesis by reacting with cobalamin (9). Cobala-min-dependent enzymes, including cobalamin-dependent methi-onine synthase (10), methylmalonyl-coenzyme A (CoA) mutase,and glutamate mutase, contribute to the bacterial metabolism un-der physiological conditions. The altered cobalamin due to BCMpotentially affects the intestinal microenvironment. Methanogensand sulfate-reducing bacteria (SRB) are competitive for hydrogenin the GIT (11, 12). Several studies on ruminants have proven thatthe competition between methanogens and SRB will influence thecomposition and activities of other bacteria (13). Our previousresearch showed that BCM administration had no effect on theoverall diversity of bacteria in feces in the SD rat by the use ofdenaturing gradient gel electrophoresis (DGGE) (8). DGGE candetect only the predominant microbial groups (14) and has lim-ited resolution when analyzing highly diverse environments, like
the GIT (15). Thus, it is likely that some bacteria, especially thosewith low abundance but which functionally are important, such asSRB, may not be well detected by the DGGE method. Thus, inorder to evaluate the impact of BCM on the bacterial communityin the gut, it is vital to reveal the structural composition of themicrobiome and especially to uncover those usually undetectablebut functionally important bacterial groups.
The GIT is not only the home for thousands of microorgan-isms, but it also functions in host-microbiota metabolic interac-tions, nutrition absorption, immunological regulation, and themaintenance of gut homeostasis (16–18). The interaction betweenthe host and its resident microbiota results in the mutually bene-ficial environment that contributes to gut health (17). This con-tribution consists of host-microbe metabolic flux, exemplified bythe production of short-chain fatty acids (SCFA) (17), amino ac-ids (19), lipids (17), and polyamines (19). Thus, variation in thegut microbiota might lead to changes in intestinal and host sys-temic metabolism. However, previously published papers onBCM influencing the gut metabolism have focused on energy andadipose deposition (20). To the best of our knowledge, no studies
Received 30 September 2015 Accepted 9 November 2015
Accepted manuscript posted online 13 November 2015
Citation Yang Y-X, Mu C-L, Luo Z, Zhu W-Y. 2016. Bromochloromethane, a methaneanalogue, affects the microbiota and metabolic profiles of the rat gastrointestinaltract. Appl Environ Microbiol 82:778–787. doi:10.1128/AEM.03174-15.
have reported the impact of BCM on the other metabolic pro-cesses in the GIT, let alone the host whole-body metabolism.
Therefore, we hypothesized that oral supplementation of BCMin a monogastric animal with the level per body weight equivalentto that used with ruminants would affect the intestinal microbiotaand its metabolic profile. To test this hypothesis, the present studyintegrated colonic microbiome and metabolomics, coupled withan analysis of bacterial fermentation products to investigate thechange in bacterial community and host metabolites in the Wistarrat model. This may provide fundamental information towardour awareness of the impact of BCM ingestion on GIT bacterialcomposition and metabolism and on animal production.
MATERIALS AND METHODSAnimals and diets. The experiment was conducted in compliance withthe Chinese regulations concerning the protection of experimental ani-mals, according to the protocol approved by the ethics committee of Nan-jing Agricultural University, Nanjing, China.
Adult male Wistar specific-pathogen-free (SPF) rats (n � 20), weigh-ing 200 to 220 g, were housed in stainless steel wire cages on a 12-h reverselight/dark cycle (7:00 a.m. to 7:00 p.m.). The rats were acclimated to theenvironment for the first week with a standard rodent diet (Table 1). Afteracclimatization, the rats were randomly allocated to 2 groups of 10 ratseach (control and BCM group). All rats were given free access to water andfed the standard diet ad libitum for 6 weeks. For the BCM group, liquidBCM (CAS no. 74-97-5, 99.5% purity; Aladdin, Shanghai, China) wasadded to the drinking water, according to their drinking volume, to makethe final concentration 0.3 mg/100 g of BW. The rats were weighed every2 days. Food residues were recorded daily. At 42 days, each rat was anes-thetized between 8:00 a.m. and 11:00 a.m. with diethyl ether. Plasma wascollected from the jugular vein before dissection and collection of theluminal contents of the colon and cecum. Colonic tissue samples werecollected and immediately snap-frozen in liquid nitrogen.
Chemical analytical procedures. The measurement of blood totalprotein, globulin, albumin, glucose, triglyceride, total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein choles-terol (LDL-C), urea, creatinine, and uric acid was conducted by the enzy-matic colorimetric method using an AU2700 autoanalyzer (Olympus,Tokyo, Japan). Plasma concentrations of insulin, glucagon, T3, T4, gas-trin, and growth hormone were determined using a radioimmunoassaykit with 125I as a tracer (North Institute of Biological Technology, Beijing,China). The radioactivity of 125I-labeled hormone was measured using anSN-6105 radioimmunoassay gamma counter (Shanghai Hesuo RihuanPhotoelectric Instruments, Shanghai, China). Cecal SCFA content wasmeasured by gas chromatography (GC), as described previously (21).
Analysis of amino acid-derived metabolites. The free ammonia con-centration of cecal contents was determined by the phenol-hypochloritemethod, as described previously (22). Cecal biogenic amines (23) andphenolic and indolic compounds (24) were determined by high-perfor-mance liquid chromatography (HPLC), as described previously. Sulfideconcentration was determined by the methylene blue method, accordingto Siegel (25).
Gas chromatography and mass spectrometry analysis. The coloncontents were weighed and diluted with double-distilled water (1:3 [wt/vol]), and 300 �l of methanol was added to a 100-�l aliquot of superna-tant. After incubation for 1 min, 100 �l of supernatant was transferred toa gas chromatography (GC) vial and evaporated using an SPD2010-230SpeedVac concentrator (Thermo Savant, Holbrook, NY, USA). The driedextract was methoxylated and trimethylsilylated prior to analysis withGC-mass spectrometry (GC-MS), as described previously (26). The me-tabolites in the gut contents were analyzed using GC-MS (QP2010 Ultra/SE; Shimadzu, Kyoto, Japan). The masses between m/z 50 and 800 wereacquired from 7 to 20 min, with a scan speed of 2,500 Hz and event time of0.30 s. The metabolites were identified in comparison with the databaseNIST and Wiley. Peak areas were normalized to an internal standardbefore further analysis. Partial least-squares discriminant analysis (PLS-DA) was calculated using the SIMCA-P 13.0 software (Umetrics, Umeå,Sweden).
Quantification of methanogens and SRB. Total bacterial DNA wasextracted with 300 mg colonic digesta using the bead-beating and phenol-chloroform extraction methods, as previously described (27). A real-timePCR assay was performed on an ABI 7300 detection system (AppliedBiosystems) with ROX reference dye and SYBR fluorescence dye (TaKaRaBiotechnology, Dalian, China). The sequences of the selected targets andprimers are listed in Table 2.
Pyrosequencing of colonic bacterial 16S rRNA. Universal primers(5=-TACGGRAGGCAGCAG-3= and 5=-AGGGTATCTAATCCT-3=) tar-geting the V3–V4 region of the colonic microbial 16S rRNA gene werechosen for the amplification and subsequent pyrosequencing of the PCRproducts. After purification with the Agencourt AMPure XP system(Beckman Coulter, USA), the PCR amplicons from different sampleswere barcoded, pooled to construct the sequencing library, and sequencedon a 454 GS FLX Titanium platform at the Chinese National HumanGenome Center (Shanghai, China).
Bioinformatics analysis. Raw sequence data generated from pyrose-quencing were processed in the mothur version 1.36 software package(28). All sequences of �200 bp, having one or more ambiguous bases, orcontaining a homopolymer length of �8 bp were removed from the dataset. Unique sequences were normalized to contain an equal number ofsequences in the two groups before the sequences were presumptivelyidentified and aligned against a database of high-quality 16S rRNA bacte-rial sequences derived from the bacterial Silva database (Silva version 108[https://www.arb-silva.de/documentation/release-108/]). Using the aver-age neighbor algorithm with a cutoff of 97% identity, these sequenceswere clustered into operational taxonomic units (OTUs). Representativesequences from each OTU were taxonomically classified with a confi-dence level of 90% using the RDP classifier (http://rdp.cme.msu.edu/).Alpha diversity was conducted within mothur, namely, Chao1, ACE,
TABLE 1 Composition and nutrient concentrations of the experimentaldiets
Shannon, Simpson, and Good’s coverage indices. Significant and uniqueOTUs in each group were picked using a linear discriminant algorithm(LDA) effect size (i.e., LDA score, �2) (29).
Analysis of bacterial cooccurrence pattern. The bacterial cooccur-rence network was constructed as described previously (30). All possibleSpearman correlations were calculated between OTUs with more thanfive sequences. A Spearman correlation coefficient of | r | of �0.9 and a Pvalue of �0.001 were considered to represent a valid cooccurrence event.The nodes in the reconstructed network represent the OTUs at 97% iden-tity, whereas the edges correspond to a strong and significant correlationbetween nodes. The networks were visualized with Gephi (31).
Statistical analysis. Body weight, feed intake, plasma biochemical pa-rameters (metabolites and hormones), SCFA, amino acid-derived metab-olites, and quantitative real-time PCR data were analyzed using the Stu-dent t test corrected with the false-discovery rate (FDR). Bacterialabundance at the phylum level was analyzed by the Mann-Whitney test.FDR correction was also used to verify the discriminant metabolites cho-sen by Wilcoxon-Mann-Whitney P values. The data were expressed as themean � standard error of the mean (SEM). A P value of �0.05 wasconsidered statistically significant.
Nucleotide sequence accession numbers. All qualified sequenceshave been deposited in GenBank under accession numbers KM366802 toKM368234.
RESULTSEffects of BCM treatment on growth performance and biochem-ical parameters. Body weight at day 42 tended to increase afterBCM supplementation (P � 0.07) (Fig. 1A), but feed intake wasnot affected. BCM supplementation changed body compositionand significantly increased spleen weight (see Table S1 in the sup-plemental material). No differences were observed for liver weightor mesenteric adipose pads. The plasma concentrations of glu-cose, triglyceride, amino acids, and uric acid were measured toreflect the systemic change in carbohydrate, lipid, protein, andpurine metabolism with BCM treatment. Concentrations of glu-cose and uric acid in the blood were significantly decreased (P �0.05; see Table S1), while triglyceride levels were slightly decreasedin the BCM group compared to those of the control group (P �0.079; see Table S1) (Fig. 1B).
Effects of BCM treatment on cecal SCFA and amino acid fer-mentation products. As shown in Fig. 1C, BCM intervention sig-nificantly increased the concentrations of butyrate and isovalerate(P � 0.05) and slightly increased the isobutyrate level (P � 0.079),but it did not affect the concentrations of acetate, propionate, andvalerate in the cecum. For biogenic amines, the concentrations ofcecal methylamine, phenylethylamine, putrescine, and tyraminewere significantly increased in the BCM group compared to thosein the control group (P � 0.05, Fig. 2A). For phenolic and indolic
compounds, skatole concentration was significantly increased(P � 0.05, Fig. 2B), and indole concentration was slightly in-creased after BCM supplementation (P � 0.082). There was nosignificant difference in cecal free ammonia concentrations be-tween the two groups. Cecal sulfide production was significantlyincreased in BCM-treated rats compared to that in the controls(P � 0.023, Fig. 2C).
Effect of BCM treatment on colonic metabolite profile. GC-MS-based metabolomics profiles of the colon content are pre-sented in Fig. S1 in the supplemental material. Fifty metaboliteswere detected in the colonic content from adult rats. A heatmapanalysis based on the Z-value-normalized peak area indicated thatthe relative concentrations of colonic metabolites decreased in theBCM treatment group, especially for amino acids, carbohydrates,and fatty acid-related compounds. The PLS-DA model also pro-vided good discrimination between the control and BCM groups(see Fig. S2 in the supplemental material). Nine metabolites withan FDR threshold of �0.05 were identified (Table 3). Glucose-6-phosphate, oleic acid, and proline levels were decreased 5.91-fold,5.31-fold, and 3.69-fold in the BCM group compared to those inthe control group. The levels of taurine, hexadecanoic acid, serine,and gluconic acid decreased by half in the BCM group comparedto those in the control group. The stearic acid, pyroglutamic acid,glutamic acid, and ornithine levels were 1.5-fold lower in the BCMgroup than in the control group. The affected metabolites weremostly involved in bile acid metabolism (taurine), amino acidmetabolism (proline, pyroglutamic acid, glutamic acid, and orni-thine), fatty acid biosynthesis (hexadecanoic acid and stearicacid), and glycolysis/gluconeogenesis (glucose-6-phosphate andgluconic acid).
Effect of BCM supplementation on methanogen and SRBpopulations. Quantitative real-time PCR analysis showed thatmethyl coenzyme-M reductase (mcrA) gene copies of the meth-anogens were significantly reduced (P � 0.040; Fig. 1D), while thedissimilatory sulfite reductase �-subunit (dsrA) gene copies of theSRB were increased in the colonic content of the BCM groupcompared to those in the control group (P � 0.028; Fig. 1D).However, there was no significant difference in total bacteria (asinferred from 16S rRNA gene copy numbers) in the colonic con-tent between the BCM and control groups.
Effect of BCM treatment on colonic bacterial communitystructure revealed by pyrosequencing. The total number of se-quences and OTUs, coverage, bacterial richness, and diversity at agenetic distance of 3% in each colonic sample under differenttreatments are presented in Table 4. Across all 20 samples, an
TABLE 2 Primers used for quantification of methanogens, SRB, and total bacteria
Target Primer direction Sequence Reference
Methanogen 32mcrA Forward TTCGGTGGATCDCARAGRGC
Reverse GBARGTCGWAWCCGTAGAATCC
SRB 63dsrA Forward CCAACATGCACGGYTCCA
Reverse CGTCGAACTTGAACTTGAACTTGTAG
Total bacteria Forward CGGTGAATACGTTCYCGG 64Reverse GGWTACCTTGTTACGACTT
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average of 8,431 and 7,088 quality sequences from the control andBCM groups, respectively, were classified as bacteria (Table 4).Species richness was increased in the BCM group compared tothat in the control group, as reflected by the ACE index with sta-tistical differences (P � 0.040; Table 4). Unweighted UniFracanalysis revealed a significant difference between the BCM andcontrol groups (UniFrac score, 0.955; P � 0.001).
Pyrosequencing data showed that bacteria belonging to thephyla Firmicutes and Bacteroidetes were the most dominating phy-lotypes in the control and BCM-supplemented rats (Fig. 3A). Nosignificant changes in the abundance of bacteria belonging to thephyla Bacteroidetes, Firmicutes, and Proteobacteria were observedbetween the control and BCM groups, whereas BCM supplemen-tation significantly reduced the abundance of bacteria belonging
to the phyla Actinobacteria and Acidobacteria. The taxa that weresignificantly different between the BCM and control groups areshown in Fig. 3. LDA analyses also confirmed that the abundanceof Acidobacteria and Actinobacteria at the phylum level was signif-icantly decreased in the BCM group compared to those in thecontrols (Fig. 3B). Although no significant difference was ob-served for the abundance of Proteobacteria at the phylum level,bacteria from five different taxa (Oceanospirillales, Novosphingo-bium, Sutterella, Halomonas, and Halomonadaceae) within theProteobacteria were significantly decreased after BCM supplemen-tation, with most of them detected in the control group only(Fig. 3B).
Cooccurrence patterns of bacteria. The cooccurrence pat-terns of colonic bacteria in the control and BCM groups are shown
FIG 1 (A) Body weight and feed intake of rats fed control or BCM-supplemented diet. (B) Plasma glucose, triglyceride, and uric acid concentrations for rats fedcontrol or BCM-supplemented diet. (C) Concentration of SCFA in the cecum of control and BCM groups. (D) Number of copies of colonic total bacteria(measured as 16S gene copies), mcrA gene, and dsrA gene. The values are expressed as the means � SEM, with 10 rats per group.
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in Fig. 4. Two distinct networks were generated using the OTUsfrom the control or BCM group, respectively. The cooccurrencenetwork consisted of 359 nodes and 1,169 edges for the controlgroup and 370 nodes and 1,622 edges for the BCM group. Theaverage degree and diameter were 6.51 and 16 in the control group
and 8.77 and 22 in the BCM group. Although the modularities ofthe two networks are similar, bacteria belonging to the phyla Ac-tinobacteria and Proteobacteria, and some from the phylum Bac-teroidetes, tended to cluster together and form a major moduleafter BCM ingestion. This module consisted of very diverse bac-
FIG 2 (A to C) Cecal concentrations of the amino acid fermentation products biogenic amines (A), phenolic and indolic compounds (B), and sulfide (C). (D)Amino acid concentrations in blood. The values are expressed as the means � SEM, with 10 rats per group, *, P � 0.05; **, P � 0.01.
TABLE 3 Significantly altered metabolites in colon of BCM-supplemented rats
Metabolite Biological rolea Metabolic pathway P FCb FDRc VIPd
Glutamic acid Amino acid-derived metabolite Nitrogen metabolism 0.023 0.65 0.026 1.03Ornithine Amino acid-derived metabolite Arginine and proline metabolism 0.028 0.65 0.032 1.07Proline Amino acid-derived metabolite Arginine and proline metabolism 0.016 0.27 0.017 1.07Pyroglutamic acid Amino acid-derived metabolite Glutathione metabolism 0.020 0.71 0.022 1.03Taurine Amino acid-derived metabolite Primary bile acid biosynthesis 0.003 0.43 0.003 1.60Glucose-6-phosphate Carbohydrate Glycolysis and gluconeogenesis 0.014 0.17 0.014 1.17Hexadecanoic acid LCFA Fatty acid biosynthesis 0.005 0.44 0.005 1.74Oleic acid LCFA Fatty acid biosynthesis 0.031 0.19 0.037 1.81Stearic acid LCFA Fatty acid biosynthesis 0.014 0.66 0.015 1.40a LCFA, long-chain fatty acids.b FC, fold change. Fold change was calculated as BCM versus control. A value of �1.0 indicates a lower concentration in the BCM group relative to that in the control group.c FDR, false-discovery rate.d Variable importance in the projection (VIP) value was obtained from the PLS-DA model.
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terial taxa, with 6 Actinobacteria, 4 Bacteroidetes, 11 Firmicutes,and 11 Proteobacteria (see Table S2 in the supplemental material).The nearest neighbor of each OTU in this module is shown inTable S2.
DISCUSSION
BCM has been widely used in ruminants, including cattle (7, 32)and goats (6, 33), because it can effectively inhibit methanogenesiswhile having no adverse effect on growth performance. As a result,the impact of BCM on archaeal composition has widely been in-vestigated (6, 7, 32, 33). However, there is a paucity of informationon the bacterial community and its metabolic pattern after BCMexposure. Given that the GIT is an internal organ with direct con-tact with BCM ingestion, we hypothesized that this level of BCMingestion might exert influence on the intestinal microbial com-munity and metabolic profile. Our results showed, similar to find-ings in previous studies (6–8), that body weight and feed intake ofrats were not influenced by BCM supplementation. Moreover,our hypothesis was supported, as the present study also demon-strated that colonic macronutrients, such as amino acids, carbo-hydrates, and long-chain fatty acids, were significantly decreased,suggesting that the intestinal metabolic profiles were influencedafter BCM administration.
Furthermore, results from colonic metabolomics showed thatcarbohydrates, such as glucose, fructose, glucuronic, and gluconicacid, were decreased after BCM exposure for 6 weeks, indicating
TABLE 4 Summary statistic of pyrosequencing 16S rRNA of colonicsamples
a Means are from statistical models based on 10 replicas in each group.
FIG 3 (A) Significantly changed colonic bacteria in BCM-supplemented rats, as revealed by LDA analysis. An LDA score of �2 was considered significant. P,phylum; O, order; F, family; G, genus. (B) Colonic microbiome composition profiles at the phylum level in control and BCM-supplemented rats, as revealed by16S rRNA sequencing. The values are expressed as the means � SEM, with 10 rats per group.
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that carbohydrate metabolism was disturbed at the local level (Ta-ble 3). Glucose-6-phosphate is the intermediate of the glycolysisprocess in most host cells and bacteria. Decreasing the concentra-tion of colonic glucose-6-phosphate (Table 3) might suggest theinhibition of host glucose metabolism and bacterial glycolysis byBCM. Long-chain fatty acids (LCFA), such as stearic acid, oleicacid, hexadecanoic acid, and linoleic acid, were also decreased inthe colon of BCM rats compared to that in rats in the controlgroup (Table 3). It was possible that the oxidation of LCFA wasupregulated and thus the source for intracellular lipid biosynthesisincreased by BCM. Although no direct evidence for colonic nutri-ents contributing to the decrease in plasma triglycerides was ob-tained, the underlying linkage between the parallel decrease incolonic fatty acids and plasma triglycerides may arise from thenutrient transport by mesenteric vessels. A novel finding of thecurrent study was the increase in amino acids in the blood andthe decrease in amino acids in the colon (Fig. 2D; see also Fig. S1 inthe supplemental material), which indicated that BCM adminis-tration might stimulate the amino acid absorption, leading tofewer amino acids in the large intestine. Russell and Martin (34)reported that the inhibition of methanogenesis would reduceamino acid deamination. Nagase and Matsuo (35) also revealedthat since methanogen acted as a hydrogen acceptor, the inhibi-tion of methanogenesis by BCM would also inhibit amino aciddegradation. The current study results are similar to previous re-sults that amino acids were seldom catabolized after methanogeninhibition by BCM (35). Meanwhile, amino acid absorption andfermentation by bacteria were enhanced (Fig. 1C and 2A and B).
In the present study, the abundance of cecal methanogens, asrepresented by the number of mcrA gene copies, decreased afterBCM treatment for 6 weeks (Fig. 1D), which was in accordancewith previous studies that BCM can reduce the abundance of fecalmethanogens in rats (8) and ruminal methanogens in cattle (32).SRB, like methanogens, are another group of hydrogenotrophicbacteria. However, it was believed that sulfate reduction and
methanogenesis competed against each other (36). In the currentstudy, the abundance of SRB increased and methanogen abun-dance decreased after BCM treatment (Fig. 1D). SRB are closelyassociated with various bowel diseases, such as ulcerative colitis,irritable bowel syndrome, and inflammatory bowel disease (37–39). Furthermore, the increase in SRB was coupled with an eleva-tion in sulfide concentration in the feces of BCM rats (Fig. 2C).Sulfide can be produced by the reduction of inorganic sulfurthrough the sulfate-reducing process. The significant increase inSRB confirmed that the sulfate-reducing process was enhanced.The fermentation of sulfur-containing amino acids (SAA), such ascysteine and methionine, might also release sulfide (40). Researchhas shown that the fermentation of dietary SAA is the majorsource of fecal sulfide concentration (41). Thus, the significantincrease in cecal sulfide concentration suggests that amino acidfermentation was enhanced. Previous researchers have shown thatthe increase in hydrogen sulfide can disrupt the gut epithelial tis-sues and induce DNA damage, and it can even increase the sensi-tivity of the GIT to virus infection (42, 43). Moreover, the reactionof BCM with sulfide compounds may yield a product of greatertoxicological significance than hydrogen sulfide (44), which canbe detrimental to the GIT.
In the large intestine, undigested protein and other nitroge-nous compounds were mainly fermented by bacteria with the pro-duction of branched-chain fatty acids (BCFA), amines, and am-monia (45). In the present study, the decrease in colonic aminoacids (Table 3), together with the elevation in cecal biogenic aminelevels (Fig. 2A), suggested that bacterial decarboxylation of aminoacids was stimulated after BCM administration. Methylamine canbe released during glycine decarboxylation and the degradation ofsarcosine, N,N-methylarginine, adrenaline, choline, and creatine(46–48), which also indicated the enhanced amino acid decarbox-ylation. Polyamines, such as putrescine, have been shown to exertgenotoxic effects on the host and might serve as potential tumormarkers (17). High level of amines, especially histamine, tryptam-
FIG 4 Network of cooccurring OTUs based on correlation analysis in control and BCM groups. A connection stands for a strong (absolute Spearman’scorrelation, �0.9) and significant (P � 0.001) correlation. The size of each node is proportional to the number of connections.
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ine, �-phenylethylamine, and tyramine, might be toxic to guthealth (49). BCFA produced from branched-chain amino aciddeamination and microbial fermentation are regarded as indica-tors of protein fermentation by the large-intestinal bacteria (50).In the present study, the increasing isovalerate and isobutyrateconcentrations in the cecum (Fig. 1C) suggested that the BCM caninduce incomplete degradation of amino acids in the colon, espe-cially leucine and valine. Indolic and phenolic compounds pro-duced from the aromatic amino acids by microorganisms are re-garded as genotoxic, mutagenic, and carcinogenic substances.High levels of indole and skatole in the colon of the BCM-fed rat(Fig. 2B) indicated that bacterial fermentation of tryptophan, ty-rosine, and phenylalanine was increased.
In the present study, the pyrosequencing analysis confirmedthat BCM treatment changed the colonic bacterial composition,even though the abundance of total bacteria was not affected (Fig.1D). The increase in diversity and the richness index (Table 4)suggest that BCM might affect the community composition ofcolonic bacteria. Bacteria belonging to the phyla Actinobacteriaand Acidobacteria were inhibited by BCM (Fig. 3). Recent studiesrevealed that the [Fe]- and [FeFe]-hydrogenase gene, which en-codes the enzyme involved in hydrogen production, had beenfound in soil bacteria belonging to the phyla Acidobacteria andActinobacteria (51, 52). This finding indicated that acidobacteriaand actinobacteria might also be potential hydrogen donors in theGIT. The cumulative hydrogen level might cause the feedbackinhibition of actinobacteria and acidobacteria.
BCM administration also decreased the abundance of manybacteria belonging to the Alphaproteobacteria, Betaproteobacteria,and Gammaproteobacteria (Fig. 3). Gammaproteobacteria and al-phaproteobacteria exhibited slight methanotrophic affinity. It hasbeen shown that they can oxidize at least 0.3% of the methane fluxin the artificial rumen fluid (53, 54). Thus, it was reasonable thatthe abundance of methane-oxidizing proteobacteria would de-crease in the BCM group. The abundance of Acetivibrio in theBCM group was significantly increased compared to that in thecontrol group. Studies have found that most members of the Ace-tivibrio genus are anaerobic carbohydrate-fermenting bacteria, in-cluding A. cellulolyticus and A. cellulosolvens (55–57). The increasein Acetivibrio might be involved in the decrease in glucose concen-tration and carbohydrate metabolism (Fig. 3). Bacteria belongingto the Actinobacteria were significantly decreased in the BCMgroup. Research found out that bacteria within the Actinobacteria,such as those from the genera Streptomyces and Propionibacte-rium, can synthesize cobalamin-dependent enzymes, includingmethylmalonyl-CoA mutase and glutamate mutase (58), whichwere essential for the methionine biosynthesis. BCM can reactwith reduced cobalamin, thereby decreasing methionine synthe-sis. Since methionine is critical to bacterial DNA synthesis, BCMmight decrease the bacterial abundance through the inhibition ofmethionine synthesis.
Network analysis of taxon cooccurrence patterns has beendemonstrated to provide further insight into the structure of com-plex microbial communities (30). The current study revealed theobvious interdependence of the colonic bacteria in rats by BCM.After BCM administration, the correlation module emerged thatDesulfovibrio intestinalis (Deltaproteobacteria), Blautia faecis, andDorea formicigenerans (Clostridia), Pseudomonas geniculata andPseudomonas putida (Gammaproteobacteria), Streptococcus ther-mophilus and Lactobacillus sp. (Bacilli), and the Actinobacteria
were closely correlated in rats in the BCM group (Fig. 4; see alsoTable S2 in the supplemental material). B. faecis and D. formicigen-erans have been reported as potential hydrogen producers (59,60), while D. intestinalis has been reported as a hydrogen con-sumer. Other bacteria, like P. geniculata, can also produce hydro-gen sulfide (61), while P. putida is effective in hydrogen sulfideremoval (62). There were several members of the Actinobacteria,including Bifidobacterium animalis, Collinsella intestinalis, andOlsenella profusa, involved in this modularity class. Although it isnot known whether these enteral actinobacterial species producedor utilized hydrogen, the strong correlation between the hydro-gen-consuming SRB and hydrogen-producing B. faecis and D. for-micigenerans suggested that BCM may influence the metabolismin the large intestine through hydrogen utilization.
BCM supplementation did not affect the feed intake and bodyweight of the rats but significantly altered the gut microbiota andgut metabolism. Colonic bacteria, such as actinobacteria, acido-bacteria, and many proteobacteria, were decreased, but the levelsof SRB were increased after BCM supplementation. Intestinal me-tabolism was disturbed by BCM, as evidenced by the decrease inamino acids, BCFA, and carbohydrates in the colon. Amino acidabsorption and fermentation were enhanced, which increased po-tentially detrimental compounds. These findings may providefurther information for the use of BCM in animal production.
ACKNOWLEDGMENTS
We thank Roderick Mackie from the University of Illinois at Urbana-Champaign and Andre Wright from the University of Arizona for theirsuggestions and critical reading during revision.
FUNDING INFORMATIONNational Key Basic Research Program of China provided funding to Wei-yun Zhu under grant number 2013CB127300. National Natural ScienceFoundation of China (NSFC) provided funding to Weiyun Zhu undergrant number 31430082. Natural Science Foundation of Jiangsu Provinceprovided funding to Weiyun Zhu under grant number BK20130058.
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