Probiotic Bifidobacterium longum alters gut luminal metabolism through modification of the gut microbial community

Hirosuke Sugahara, Toshitaka Odamaki, Shinji Fukuda, Tamotsu Kato, Jin-zhong Xiao, Fumiaki Abe, Jun Kikuchi, Hiroshi Ohno, Hirosuke Sugahara, Toshitaka Odamaki, Shinji Fukuda, Tamotsu Kato, Jin-zhong Xiao, Fumiaki Abe, Jun Kikuchi, Hiroshi Ohno

Abstract

Probiotics are well known as health-promoting agents that modulate intestinal microbiota. However, the molecular mechanisms underlying this effect remain unclear. Using gnotobiotic mice harboring 15 strains of predominant human gut-derived microbiota (HGM), we investigated the effects of Bifidobacterium longum BB536 (BB536-HGM) supplementation on the gut luminal metabolism. Nuclear magnetic resonance (NMR)-based metabolomics showed significantly increased fecal levels of pimelate, a precursor of biotin, and butyrate in the BB536-HGM group. In addition, the bioassay revealed significantly elevated fecal levels of biotin in the BB536-HGM group. Metatranscriptomic analysis of fecal microbiota followed by an in vitro bioassay indicated that the elevated biotin level was due to an alteration in metabolism related to biotin synthesis by Bacteroides caccae in this mouse model. Furthermore, the proportion of Eubacterium rectale, a butyrate producer, was significantly higher in the BB536-HGM group than in the group without B. longum BB536 supplementation. Our findings help to elucidate the molecular basis underlying the effect of B. longum BB536 on the gut luminal metabolism through its interactions with the microbial community.

Conflict of interest statement

H.S., T.O., J.-z.X. and F.A. are employees of Morinaga Milk Industry Co., Ltd.

Figures

Figure 1. Experimental design of the mouse…
Figure 1. Experimental design of the mouse study.
Germ-free mice were inoculated with a single gavage of 15 species of a predominant human gut-derived microbiota cocktail at day -14 and were administered PBS containing Bifidobacterium longum BB536 or nothing (n = 6) every day for 14 days. Fecal samples were collected on days 0 and 13.
Figure 2. Water-soluble metabolic profiling in fecal…
Figure 2. Water-soluble metabolic profiling in fecal samples of the human gut-derived microbiota (HGM) mice.
(a) Principal component analysis (PCA) of fecal 1D 1H-NMR spectroscopy profiles. The contributions of PC1, PC2 and PC3 were 63.7%, 20.1% and 6.3%, respectively. (b) Fecal pimelate, butyrate and acetate levels at day 13. All compounds were calculated and identified using 1H-13C HSQC 2D-NMR measurements (n = 6). Boxes denote the interquartile range between the first and third quartiles, and the line within denotes the median. P-values were calculated using Mann–Whitney U test. *P < 0.05; **P < 0.01. (c) Biotin concentrations in fecal samples at day 13. Data are shown as the mean ± SD (n = 6). P-values were calculated using Student’s t-test. *P < 0.05. (d) Correlation analysis based on Spearman’s rank correlation coefficient between fecal pimelate and biotin levels. Fecal pimelate and biotin levels are shown as open symbols, and the line indicates a simple regression model.
Figure 3. Metabolite levels in germ-free and…
Figure 3. Metabolite levels in germ-free and Bifidobacterium longum mono-associated mice.
(a) Fecal pimelate, butyrate and acetate levels measured by 2D-NMR. The levels were based on the normalized intensities calculated from 1H-13C HSQC 2D-NMR measurements (n = 5). Boxes denote the interquartile range between the first and third quartiles, and lines within the boxes denote the median. P-values were calculated using the Mann–Whitney U test. (b) Acetate concentration in fecal samples measured by enzyme method. Data are shown as the mean ± SD (n = 5). P-values were calculated using Student’s t-test. **P < 0.01. (c) Biotin concentration in fecal samples after treatment. Data are shown as the mean ± SD (n = 5). P-values were calculated using Student’s t-test. *P < 0.05.
Figure 4. Distribution of bacterial transcripts in…
Figure 4. Distribution of bacterial transcripts in fecal samples of the human gut-derived microbiota (HGM) mice.
Boxes denote the interquartile range between the first and third quartiles, and the line within denotes the median. P-values were calculated using the Mann–Whitney U test. *P 

Figure 5. Predicted contribution to biotin production…

Figure 5. Predicted contribution to biotin production in gut microbiota.

( a ) Components of…

Figure 5. Predicted contribution to biotin production in gut microbiota.
(a) Components of pathways from pimelate to biotin. The black arrow indicates the step with a significant difference between the two groups. (b) Gene expression with a significant difference between the two groups. RPKM-normalized reads are shown as boxes that denote the interquartile range between the first and third quartiles, and the line within denotes the median (n = 6). P-values were calculated using the Mann–Whitney U test. *P < 0.05. (c) In vitro assay of biotin synthesis. Each strain was cultivated for 16 h in GAM broth with or without pimelate (10 mg/ml). Data are shown as the mean ± SD (n = 3). P-values were calculated using Student’s t-test. **P < 0.01.

Figure 6. Proposed effect of Bifidobacterium longum…

Figure 6. Proposed effect of Bifidobacterium longum BB536 on the gut luminal metabolism mediated by…

Figure 6. Proposed effect of Bifidobacterium longum BB536 on the gut luminal metabolism mediated by interaction with the human gut-derived microbiota (HGM) community.
Figure 5. Predicted contribution to biotin production…
Figure 5. Predicted contribution to biotin production in gut microbiota.
(a) Components of pathways from pimelate to biotin. The black arrow indicates the step with a significant difference between the two groups. (b) Gene expression with a significant difference between the two groups. RPKM-normalized reads are shown as boxes that denote the interquartile range between the first and third quartiles, and the line within denotes the median (n = 6). P-values were calculated using the Mann–Whitney U test. *P < 0.05. (c) In vitro assay of biotin synthesis. Each strain was cultivated for 16 h in GAM broth with or without pimelate (10 mg/ml). Data are shown as the mean ± SD (n = 3). P-values were calculated using Student’s t-test. **P < 0.01.
Figure 6. Proposed effect of Bifidobacterium longum…
Figure 6. Proposed effect of Bifidobacterium longum BB536 on the gut luminal metabolism mediated by interaction with the human gut-derived microbiota (HGM) community.

References

    1. Sanders M. E. et al.. An update on the use and investigation of probiotics in health and disease. Gut 62, 787–96 (2013).
    1. Tabbers M. M., de Milliano I., Roseboom M. G. & Benninga M. A. Is Bifidobacterium breve effective in the treatment of childhood constipation? Results from a pilot study. Nutr. J. 10, 19 (2011).
    1. Yang Y.-X. et al.. Effect of a fermented milk containing Bifidobacterium lactis DN-173010 on Chinese constipated women. World J. Gastroenterol. 14, 6237–43 (2008).
    1. Tian C. et al.. Top-down phenomics of Arabidopsis thaliana: metabolic profiling by one- and two-dimensional nuclear magnetic resonance spectroscopy and transcriptome analysis of albino mutants. J. Biol. Chem. 282, 18532–41 (2007).
    1. Fukuda S. et al.. Evaluation and characterization of bacterial metabolic dynamics with a novel profiling technique, real-time metabolotyping. PLoS One 4, e4893 (2009).
    1. Yatsunenko T. et al.. Human gut microbiome viewed across age and geography. Nature 486, 222–7 (2012).
    1. Xiong X. et al.. Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing. PLoS One 7, e36009 (2012).
    1. Yi P. & Li L. The germfree murine animal: an important animal model for research on the relationship between gut microbiota and the host. Vet. Microbiol. 157, 1–7 (2012).
    1. Fukuda S. et al.. Bifidobacteria can protect from enteropathogenic infection through production of acetate. Nature 469, 543–7 (2011).
    1. McNulty N. P. et al.. The impact of a consortium of fermented milk strains on the gut microbiome of gnotobiotic mice and monozygotic twins. Sci. Transl. Med. 3, 106ra106 (2011).
    1. Xiao J. et al.. Clinical efficacy of probiotic Bifidobacterium longum for the treatment of symptoms of Japanese cedar pollen allergy in subjects evaluated in an environmental exposure unit. Allergol. Int. 56, 67–75 (2007).
    1. Odamaki T. et al.. Effect of the oral intake of yogurt containing Bifidobacterium longum BB536 on the cell numbers of enterotoxigenic Bacteroides fragilis in microbiota. Anaerobe 18, 14–8 (2012).
    1. Namba K., Yaeshima T., Ishibashi N., Hayasawa H. & Yamazaki S. Inhibitory effects of Bifidobacterium longum on enterohemorrhagic Escherichia coli O157:H7. Biosci. microflora 22, 85–91
    1. Yaeshima T. et al.. Effect of yogurt containing Bifidobacterium longum BB536 on the intestinal environment, fecal characteristics and defecation frequency: a comparison with standard yogurt. Biosci. Microflora 16, 73–77 (1997).
    1. Ogata T. et al.. Effect of Bifidobacterium longum BB536 administration on the intestinal environment, defecation frequency and fecal characteristics of human volunteers. Biosci. Microflora 16, 53–58 (1997).
    1. Ploux O., Soularue P., Marquet A., Gloeckler R. & Lemoine Y. Investigation of the first step of biotin biosynthesis in Bacillus sphaericus. Purification and characterization of the pimeloyl-CoA synthase, and uptake of pimelate. Biochem. J. 287 (Pt 3, 685–90 (1992).
    1. Kanehisa M. & Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2000).
    1. Cryle M. J. Selectivity in a barren landscape: the P450(BioI)-ACP complex. Biochem. Soc. Trans. 38, 934–9 (2010).
    1. Cryle M. J. & Schlichting I. Structural insights from a P450 Carrier Protein complex reveal how specificity is achieved in the P450(BioI) ACP complex. Proc. Natl. Acad. Sci. USA 105, 15696–701 (2008).
    1. Zhang W.-W., Yang M.-M., Li H. & Wang D. Construction of recombinant Bacillus subtilis strains for efficient pimelic acid synthesis. Electron. J. Biotechnol. 14 (2011). 10.2225/vol14-issue6-fulltext-1.
    1. Cryle M. J. & De Voss J. J. Carbon-carbon bond cleavage by cytochrome p450(BioI)(CYP107H1). Chem. Commun. (Camb). 86–7 (2004). 10.1039/b311652b.
    1. Clemente J. C., Ursell L. K., Parfrey L. W. & Knight R. The impact of the gut microbiota on human health: an integrative view. Cell 148, 1258–70 (2012).
    1. Koropatkin N. M., Cameron E. A. & Martens E. C. How glycan metabolism shapes the human gut microbiota. Nat. Rev. Microbiol. 10, 323–35 (2012).
    1. Hill M. J. Intestinal flora and endogenous vitamin synthesis. Eur. J. Cancer Prev. 6 Suppl 1, S43–5 (1997).
    1. Said H. M. & Mohammed Z. M. Intestinal absorption of water-soluble vitamins: an update. Curr. Opin. Gastroenterol. 22, 140–6 (2006).
    1. Arumugam M. et al.. Enterotypes of the human gut microbiome. Nature 473, 174–80 (2011).
    1. Lin S., Hanson R. E. & Cronan J. E. Biotin synthesis begins by hijacking the fatty acid synthetic pathway. Nat. Chem. Biol. 6, 682–8 (2010).
    1. Rodionov D. A., Mironov A. A. & Gelfand M. S. Conservation of the biotin regulon and the BirA regulatory signal in Eubacteria and Archaea. Genome Res. 12, 1507–16 (2002).
    1. Mahowald M. A. et al.. Characterizing a model human gut microbiota composed of members of its two dominant bacterial phyla. Proc. Natl. Acad. Sci. USA 106, 5859–64 (2009).
    1. De Vuyst L. & Leroy F. Cross-feeding between bifidobacteria and butyrate-producing colon bacteria explains bifdobacterial competitiveness, butyrate production, and gas production. Int. J. Food Microbiol. 149, 73–80 (2011).
    1. Falony G., Vlachou A., Verbrugghe K. & De Vuyst L. Cross-feeding between Bifidobacterium longum BB536 and acetate-converting, butyrate-producing colon bacteria during growth on oligofructose. Appl. Environ. Microbiol. 72, 7835–41 (2006).
    1. Kondo J. et al.. Modulatory effects of Bifidobacterium longum BB536 on defecation in elderly patients receiving enteral feeding. World J. Gastroenterol. 19, 2162–70 (2013).
    1. Kato T. et al.. Multiple omics uncovers host-gut microbial mutualism during prebiotic fructooligosaccharide supplementation. DNA Res. 21, 469–80 (2014).
    1. Veiga P. et al.. Changes of the human gut microbiome induced by a fermented milk product. Sci. Rep. 4, 6328 (2014).
    1. Furusawa Y. et al.. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature 504, 446–50 (2013).
    1. Sone H. et al.. Biotin enhances glucose-stimulated insulin secretion in the isolated perfused pancreas of the rat. J. Nutr. Biochem. 10, 237–43 (1999).
    1. Báez-Saldaña A., Díaz G., Espinoza B. & Ortega E. Biotin deficiency induces changes in subpopulations of spleen lymphocytes in mice. Am. J. Clin. Nutr. 67, 431–7 (1998).
    1. Sekiyama Y., Chikayama E. & Kikuchi J. Profiling polar and semipolar plant metabolites throughout extraction processes using a combined solution-state and high-resolution magic angle spinning NMR approach. Anal. Chem. 82, 1643–52 (2010).
    1. Kikuchi J., Shinozaki K. & Hirayama T. Stable isotope labeling of Arabidopsis thaliana for an NMR-based metabolomics approach. Plant Cell Physiol. 45, 1099–104 (2004).
    1. Wang T. et al.. Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis. BMC Bioinformatics 10, 83 (2009).
    1. Lewis I. A., Schommer S. C. & Markley J. L. rNMR: open source software for identifying and quantifying metabolites in NMR spectra. Magn. Reson. Chem. 47 Suppl 1, S123–6 (2009).
    1. Akiyama K. et al.. PRIMe: a Web site that assembles tools for metabolomics and transcriptomics. In Silico Biol. 8, 339–45 (2008).
    1. Chikayama E. et al.. Statistical indices for simultaneous large-scale metabolite detections for a single NMR spectrum. Anal. Chem. 82, 1653–8 (2010).
    1. Taniguchi A., Nagai Y. & Watanabe T. Study on teratogenicity of biotin deficiency in mice at midgestation. Trace Nutr Res 24, 145–152 (2007).
    1. Ishiguro K., Ando T., Maeda O., Watanabe O. & Goto H. Suppressive action of acetate on interleukin-8 production via tubulin-α acetylation. Immunol. Cell Biol. 92, 624–30 (2014).
    1. Odamaki T. et al.. Fluctuation of fecal microbiota in individuals with Japanese cedar pollinosis during the pollen season and influence of probiotic intake. J. Investig. Allergol. Clin. Immunol. 17, 92–100 (2007).
    1. Fadrosh D. W. et al.. An improved dual-indexing approach for multiplexed 16S rRNA gene sequencing on the Illumina MiSeq platform. Microbiome 2, 6 (2014).
    1. Aronesty E. Comparison of Sequencing Utility Programs. Open Bioinforma. J. 7, 1–8 (2013).
    1. Edgar R. C., Haas B. J., Clemente J. C., Quince C. & Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).
    1. Caporaso J. G. et al.. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–6 (2010).
    1. Kuczynski J. et al.. Using QIIME to analyze 16S rRNA gene sequences from microbial communities. Curr. Protoc. Microbiol. Chapter 1, Unit 1E.5. (2012).
    1. Marco M. L. et al.. Lifestyle of Lactobacillus plantarum in the mouse caecum. Environ. Microbiol. 11, 2747–57 (2009).
    1. McClure R. et al.. Computational analysis of bacterial RNA-Seq data. Nucleic Acids Res. 41, e140 (2013).
    1. Mortazavi A., Williams B. A., McCue K., Schaeffer L. & Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods 5, 621–8 (2008).
    1. Markowitz V. M. et al.. IMG/M: the integrated metagenome data management and comparative analysis system. Nucleic Acids Res. 40, D123–9 (2012).

Source: PubMed

3
Předplatit