Abstract

Bacterial metabolism plays a fundamental role in gut microbiota ecology and host–microbiome interactions. Yet the metabolic capabilities of most gut bacteria have remained unknown. Here we report growth characteristics of 96 phylogenetically diverse gut bacterial strains across 4 rich and 15 defined media. The vast majority of strains (76) grow in at least one defined medium, enabling accurate assessment of their biosynthetic capabilities. These do not necessarily match phylogenetic similarity, thus indicating a complex evolution of nutritional preferences. We identify mucin utilizers and species inhibited by amino acids and short-chain fatty acids. Our analysis also uncovers media for in vitro studies wherein growth capacity correlates well with in vivo abundance. Further value of the underlying resource is demonstrated by correcting pathway gaps in available genome-scale metabolic models of gut microorganisms. Together, the media resource and the extracted knowledge on growth abilities widen experimental and computational access to the gut microbiota.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.

    Hooper, L. V., Littman, D. R. & Macpherson, A. J. Interactions between the microbiota and the immune system. Science 336, 1268–1273 (2012).

  2. 2.

    Sharon, G., Sampson, T. R., Geschwind, D. H. & Mazmanian, S. K. The central nervous system and the gut microbiome. Cell 167, 915–932 (2016).

  3. 3.

    Zeevi, D. et al. Personalized nutrition by prediction of glycemic responses. Cell 163, 1079–1095 (2015).

  4. 4.

    Holmes, E., Li, J. V., Marchesi, J. R. & Nicholson, J. K. Gut microbiota composition and activity in relation to host metabolic phenotype and disease risk. Cell Metab. 16, 559–564 (2012).

  5. 5.

    Sonnenburg, J. L. & Bäckhed, F. Diet–microbiota interactions as moderators of human metabolism. Nature 535, 56–64 (2016).

  6. 6.

    Luis, A. S. et al. Dietary pectic glycans are degraded by coordinated enzyme pathways in human colonic Bacteroides. Nat. Microbiol. 3, 210–219 (2017).

  7. 7.

    O’Mahony, S. M., Clarke, G., Borre, Y. E., Dinan, T. G. & Cryan, J. F. Serotonin, tryptophan metabolism and the brain-gut-microbiome axis. Behav. Brain Res. 277, 32–48 (2015).

  8. 8.

    Bäumler, A. J. & Sperandio, V. Interactions between the microbiota and pathogenic bacteria in the gut. Nature 535, 85–93 (2016).

  9. 9.

    Pedersen, H. K. et al. Human gut microbes impact host serum metabolome and insulin sensitivity. Nature 535, 376–381 (2016).

  10. 10.

    Curtis, M. M. et al. The gut commensal Bacteroides thetaiotaomicron exacerbates enteric infection through modification of the metabolic landscape. Cell Host Microbe 16, 759–769 (2014).

  11. 11.

    Neidhardt, F. C., Bloch, P. L. & Smith, D. F. Culture medium for enterobacteria. J. Bacteriol. 119, 736–747 (1974).

  12. 12.

    Goodman, A. L. et al. Identifying genetic determinants needed to establish a human gut symbiont in its habitat. Cell Host Microbe 6, 279–289 (2009).

  13. 13.

    Sebald, M. & Costilow, R. N. Minimal growth requirements for Clostridium perfringens and isolation of auxotrophic mutants. Appl. Microbiol. 29, 1–6 (1975).

  14. 14.

    Lopes, J. N. & Cruz, F. S. Chemically defined media for growing anaerobic bacteria of the genus Veillonella. Antonie Van. Leeuwenhoek 42, 411–420 (1976).

  15. 15.

    Magnúsdóttir, S. et al. Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota. Nat. Biotechnol. 35, 81–89 (2017).

  16. 16.

    Larsbrink, J. et al. A discrete genetic locus confers xyloglucan metabolism in select human gut Bacteroidetes. Nature 506, 498–502 (2014).

  17. 17.

    Ponomarova, O. & Patil, K. R. Metabolic interactions in microbial communities: untangling the Gordian knot. Curr. Opin. Microbiol. 27, 37–44 (2015).

  18. 18.

    Thiele, I. & Palsson, B. Ø. A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat. Protoc. 5, 93–121 (2010).

  19. 19.

    Shoaie, S. et al. Quantifying diet-induced metabolic changes of the human gut microbiome. Cell Metab. 22, 320–331 (2015).

  20. 20.

    Castellarin, M. et al. Fusobacterium nucleatum infection is prevalent in human colorectal carcinoma. Genome Res. 22, 299–306 (2012).

  21. 21.

    Strauss, J. et al. Invasive potential of gut mucosa-derived fusobacterium nucleatum positively correlates with IBD status of the host. Inflamm. Bowel Dis. 17, 1971–1978 (2011).

  22. 22.

    Grass, J. E., Gould, L. H. & Mahon, B. E. Epidemiology of foodborne disease outbreaks caused by Clostridium perfringens, United States, 1998–2010. Foodborne Pathog. Dis. 10, 131–136 (2013).

  23. 23.

    Gardiner, B. J. et al. Clinical and microbiological characteristics of Eggerthella lenta bacteremia. J. Clin. Microbiol. 53, 626–635 (2015).

  24. 24.

    Könönen, E. & Wade, W. G. Actinomyces and related organisms in human infections. Clin. Microbiol. Rev. 28, 419–442 (2015).

  25. 25.

    Goodman, A. L. et al. Extensive personal human gut microbiota culture collections characterized and manipulated in gnotobiotic mice. Proc. Natl Acad. Sci. USA 108, 6252–6257 (2011).

  26. 26.

    Zhang, G., Mills, D. A. & Block, D. E. Development of chemically defined media supporting high-cell-density growth of lactococci, enterococci, and streptococci. Appl. Environ. Microbiol. 75, 1080–1087 (2009).

  27. 27.

    Wegkamp, A., Van Oorschot, W., De Vos, W. M. & Smid, E. J. Characterization of the role of para-aminobenzoic acid biosynthesis in folate production by Lactococcus lactis. Appl. Environ. Microbiol. 73, 2673–2681 (2007).

  28. 28.

    Evans, D. F. et al. Measurement of gastrointestinal pH profiles in normal ambulant human subjects. Gut 29, 1035–1041 (1988).

  29. 29.

    Rettedal, E. A., Gumpert, H. & Sommer, M. O. A. Cultivation-based multiplex phenotyping of human gut microbiota allows targeted recovery of previously uncultured bacteria. Nat. Commun. 5, 4714 (2014).

  30. 30.

    Png, C. W. et al. Mucolytic bacteria with increased prevalence in IBD mucosa augment in vitro utilization of mucin by other bacteria. Am. J. Gastroenterol. 105, 2420–2428 (2010).

  31. 31.

    Klumpp, S., Zhang, Z. & Hwa, T. Growth rate-dependent global effects on gene expression in bacteria. Cell 139, 1366–1375 (2009).

  32. 32.

    Browne, H. P. et al. Culturing of ‘unculturable’ human microbiota reveals novel taxa and extensive sporulation. Nature 533, 543–546 (2016).

  33. 33.

    Ríos-Covián, D. et al. Intestinal short chain fatty acids and their link with diet and human health. Front. Microbiol. 7, 185 (2016).

  34. 34.

    Louis, P., Hold, G. L. & Flint, H. J. The gut microbiota, bacterial metabolites and colorectal cancer. Nat. Rev. Microbiol. 12, 661–672 (2014).

  35. 35.

    Bergeim, O. Toxicity of intestinal volatile fatty acids for yeast and Esch. coli. J. Infect. Dis. 66, 222–234 (1940).

  36. 36.

    Hentges, D. J. Influence of pH on the inhibitory activity of formic and acetic acids for Shigella. J. Bacteriol. 93, 2029–2030 (1967).

  37. 37.

    De Felice, M., Levinthal, M., Iaccarino, M. & Guardiola, J. Growth inhibition as a consequence of antagonism between related amino acids: effect of valine in Escherichia coli K-12. Microbiol. Rev. 43, 42–58 (1979).

  38. 38.

    Tailford, L. E., Crost, E. H., Kavanaugh, D. & Juge, N. Mucin glycan foraging in the human gut microbiome. Front. Genet. https://doi.org/10.3389/fgene.2015.00081 (2015).

  39. 39.

    Ng, K. M. et al. Microbiota-liberated host sugars facilitate post-antibiotic expansion of enteric pathogens. Nature 502, 96–99 (2013).

  40. 40.

    Ponomarova, O. et al. Yeast creates a niche for symbiotic lactic acid bacteria through nitrogen overflow. Cell Syst. 5, 345–357 (2017).

  41. 41.

    Haft, D. H. et al. TIGRFAMs and genome properties in 2013. Nucleic Acids Res. 41, D387–D395 (2013).

  42. 42.

    Lau, J. T. et al. Capturing the diversity of the human gut microbiota through culture-enriched molecular profiling. Genome Med. 8, 72 (2016).

  43. 43.

    Maier, L. et al. Extensive impact of non-antibiotic drugs on human gut bacteria. Nature https://doi.org/10.1038/nature25979 (2018).

  44. 44.

    Duncan, S. H., Hold, G. L., Harmsen, H. J. M., Stewart, C. S. & Flint, H. J. Growth requirements and fermentation products of Fusobacterium prausnitzii, and a proposal to reclassify it as Faecalibacterium prausnitzii gen. nov., comb. nov. Int. J. Syst. Evol. Microbiol. 52, 2141–2146 (2002).

  45. 45.

    Buurman, E. T., Pennock, J., Tempest, D. W., Teixeira de Mattos, M. J. & Neijssel, O. M. Replacement of potassium ions by ammonium ions in different micro-organisms grown in potassium-limited chemostat culture. Arch. Microbiol. 152, 58–63 (1989).

  46. 46.

    Roe, A. J., O’Byrne, C., McLaggan, D. & Booth, I. R. Inhibition of Escherichia coli growth by acetic acid: a problem with methionine biosynthesis and homocysteine toxicity. Microbiology 148, 2215–2222 (2002).

  47. 47.

    Nava, G. M., Friedrichsen, H. J. & Stappenbeck, T. S. Spatial organization of intestinal microbiota in the mouse ascending colon. ISME J. 5, 627–638 (2011).

  48. 48.

    Sonnenburg, J. L. et al. Glycan foraging in vivo by an intestine-adapted bacterial symbiont. Science 307, 1955–1959 (2005).

  49. 49.

    Crost, E. H. et al. Utilisation of mucin glycans by the human gut symbiont Ruminococcus gnavus is strain-dependent. PLoS ONE 8, e76341 (2013).

  50. 50.

    Mende, D. R., Sunagawa, S., Zeller, G. & Bork, P. Accurate and universal delineation of prokaryotic species. Nat. Methods 10, 881–884 (2013).

  51. 51.

    Huttenhower, C. et al. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).

  52. 52.

    Nielsen, H. B. et al. Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes. Nat. Biotechnol. 32, 822–832 (2014).

  53. 53.

    Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing: commentary. Nature 11, 28 (2010).

  54. 54.

    Qin, J. et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490, 55–60 (2012).

  55. 55.

    Chen, I. M. A. et al. IMG/M: Integrated genome and metagenome comparative data analysis system. Nucleic Acids Res. 45, 507–516 (2017).

  56. 56.

    Markowitz, V. M. et al. IMG/M 4 version of the integrated metagenome comparative analysis system. Nucleic Acids Res. 42, 568–573 (2014).

  57. 57.

    Topping, D. L. & Clifton, P. M. Short-chain fatty acids and human colonic function: roles of resistant starch and nonstarch polysaccharides. Physiol. Rev. 81, 1031–1064 (2001).

  58. 58.

    Cook, S. I. & Sellin, J. H. Review article: short chain fatty acids in health and disease. Aliment. Pharmacol. Ther. 12, 499–507 (1998).

  59. 59.

    Massey, L. K., Sokatch, J. R. & Conrad, R. S. Branched-chain amino acid catabolism in bacteria. Bacteriol. Rev. 40, 42–54 (1976).

  60. 60.

    Allison, M. J. Production of branched-chain volatile fatty acids by certain anaerobic bacteria. Appl. Environ. Microbiol. 35, 872–877 (1978).

  61. 61.

    Martens, E. C. et al. Recognition and degradation of plant cell wall polysaccharides by two human gut symbionts. PLoS Biol. 9, e1001221 (2011).

  62. 62.

    Yin, Y. et al. DbCAN: a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 40, 445–451 (2012).

  63. 63.

    Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10–12 (2011).

  64. 64.

    Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).

  65. 65.

    Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).

Download references

Acknowledgements

We thank H. KleinJan and L. Maier for experimental assistance, O. Ponomarova for advice on media design and D. Machado for advice on metabolic modelling. Sequencing was performed at Genecore, EMBL. We thank Dupont Health and Nutrition (formerly Danisco Sweeteners OY, Finland) for providing L. acidophilus NCFM, L. paracasei ATCC SDS275, B. animalis subsp. lactis Bl-04 and BI-07, D. Clarke for Shigella sonnei 53 G and the enteropathogenic Escherichia coli strains CFT073, E2348/69, H10407, HM605 and UTI89, E. Denamur for the Escherichia coli strains ED1a and IAI1, M. Blokesch for the Vibrio cholerae strains A1552 and N16961, H. Andrews-Polymenis for the Salmonella enterica typhimurium strains CDC 6516-60 and LT2 and C. Darby for Yersinia pseudotuberculosis YPIII. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 686070. MT and MP were supported by the EMBL interdisciplinary postdoctoral program.

Author information

Author notes

    • Mihaela Pruteanu

    Present address: Humboldt University Berlin, Berlin, Germany

    • Aleksej Zelezniak

    Present address: Chalmers University of Technology, Gothenburg, Sweden

  1. These authors contributed equally: Melanie Tramontano and Sergej Andrejev.

Affiliations

  1. European Molecular Biology Laboratory, Heidelberg, Germany

    • Melanie Tramontano
    • , Sergej Andrejev
    • , Mihaela Pruteanu
    • , Martina Klünemann
    • , Michael Kuhn
    • , Paula Jouhten
    • , Aleksej Zelezniak
    • , Georg Zeller
    • , Peer Bork
    • , Athanasios Typas
    •  & Kiran Raosaheb Patil
  2. EMBL-EBI, Wellcome Trust Genome Campus, Cambridge, United Kingdom

    • Marco Galardini
  3. Max-Delbrück-Centre for Molecular Medicine, Berlin, Germany

    • Peer Bork
  4. Molecular Medicine Partnership Unit, Heidelberg, Germany

    • Peer Bork
  5. Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany

    • Peer Bork

Authors

  1. Search for Melanie Tramontano in:

  2. Search for Sergej Andrejev in:

  3. Search for Mihaela Pruteanu in:

  4. Search for Martina Klünemann in:

  5. Search for Michael Kuhn in:

  6. Search for Marco Galardini in:

  7. Search for Paula Jouhten in:

  8. Search for Aleksej Zelezniak in:

  9. Search for Georg Zeller in:

  10. Search for Peer Bork in:

  11. Search for Athanasios Typas in:

  12. Search for Kiran Raosaheb Patil in:

Contributions

M.T., P.B., A.T. and K.R.P. conceived the study. M.T., S.A., A.T. and K.R.P. designed the study. M.T., M.P., A.Z. and G.Z. selected gut bacterial strains. M.T. and M.Klünemann performed in vitro experiments. S.A. analysed data. S.A. and P.J. performed metabolic modelling. S.A. and G.Z. compiled figures. M.Kuhn contributed to in vivo abundance analysis. M.G. annotated sequenced genomes. P.B., A.T. and K.R.P. supervised the study. M.T., S.A. and K.R.P. wrote the manuscript. All authors read and commented on the manuscript.

Competing interests

A patent application has been filed based on this work.

Corresponding authors

Correspondence to Peer Bork or Athanasios Typas or Kiran Raosaheb Patil.

Supplementary information

  1. Supplementary Information

    Supplementary Tables 1–9 and Supplementary Figures 1–7.

  2. Life Sciences Reporting Summary

  3. Supplementary Tables

    Supplementary Tables 1–9.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/s41564-018-0123-9

Further reading