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Abstract

Accumulating evidence suggests that humans could be considered as holobionts in which the gut microbiota play essential functions. Initial metagenomic studies reported a pattern of shared genes in the gut microbiome of different individuals, leading to the definition of the minimal gut metagenome as the set of microbial genes necessary for homeostasis and present in all healthy individuals. This study analyses the minimal gut metagenome of the most comprehensive dataset available, including individuals from agriculturalist and industrialist societies, also embodying highly diverse ethnic and geographical backgrounds. The outcome, based on metagenomic predictions for community composition data, resulted in a minimal metagenome comprising 3412 genes, mapping to 1856 reactions and 128 metabolic pathways predicted to occur across all individuals. These results were substantiated by the analysis of two additional datasets describing the microbial community compositions of larger Western cohorts, as well as a substantial shotgun metagenomics dataset. Subsequent analyses showed the plausible metabolic complementarity provided by the minimal gut metagenome to the human genome.

Funding
This study was supported by the:
  • Dirección General de Universidades e Investigación (Award PID2019-108797RB-I00)
    • Principle Award Recipient: Daniel Aguirre de Carcer
  • Dirección General de Universidades e Investigación (Award BIO2016-80101-R)
    • Principle Award Recipient: Daniel Aguirre de Carcer
  • This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial License.
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2020-11-03
2024-04-19
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References

  1. Bordenstein SR, Theis KR. Host biology in light of the microbiome: ten principles of holobionts and hologenomes. PLoS Biol 2015; 13:e1002226 [View Article][PubMed]
    [Google Scholar]
  2. Bäckhed F, Ley RE, Sonnenburg JL, Peterson DA, Gordon JI. Host-bacterial mutualism in the human intestine. Science 2005; 307:1915–1920 [View Article][PubMed]
    [Google Scholar]
  3. Gill SR, Pop M, Deboy RT, Eckburg PB, Turnbaugh PJ et al. Metagenomic analysis of the human distal gut microbiome. Science 2006; 312:1355–1359 [View Article][PubMed]
    [Google Scholar]
  4. Falony G, Joossens M, Vieira-Silva S, Wang J, Darzi Y et al. Population-level analysis of gut microbiome variation. Science 2016; 352:560–564 [View Article][PubMed]
    [Google Scholar]
  5. Aguirre de Cárcer D, Cuív PO, Wang T, Kang S, Worthley D et al. Numerical ecology validates a biogeographical distribution and gender-based effect on mucosa-associated bacteria along the human colon. ISME J 2011; 5:801–809 [View Article][PubMed]
    [Google Scholar]
  6. Turnbaugh PJ, Ley RE, Hamady M, Fraser-Liggett CM, Knight R et al. The human microbiome project. Nature 2007; 449:804–810 [View Article][PubMed]
    [Google Scholar]
  7. Zhang J, Guo Z, Xue Z, Sun Z, Zhang M et al. A phylo-functional core of gut microbiota in healthy young Chinese cohorts across lifestyles, geography and ethnicities. ISME J 2015; 9:1979–1990 [View Article][PubMed]
    [Google Scholar]
  8. Aguirre de Cárcer D. The human gut pan-microbiome presents a compositional core formed by discrete phylogenetic units. Sci Rep 2018; 8:14069 [View Article][PubMed]
    [Google Scholar]
  9. Aguirre de Cárcer D. A conceptual framework for the phylogenetically constrained assembly of microbial communities. Microbiome 2019; 7:142 [View Article][PubMed]
    [Google Scholar]
  10. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A et al. A core gut microbiome in obese and lean twins. Nature 2009; 457:480–484 [View Article][PubMed]
    [Google Scholar]
  11. Human Microbiome Project Consortium Structure, function and diversity of the healthy human microbiome. Nature 2012; 486:207–214 [View Article][PubMed]
    [Google Scholar]
  12. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 2010; 464:59–65 [View Article][PubMed]
    [Google Scholar]
  13. Lloyd-Price J, Mahurkar A, Rahnavard G, Crabtree J, Orvis J et al. Strains, functions and dynamics in the expanded human microbiome project. Nature 2017; 550:61–66 [View Article][PubMed]
    [Google Scholar]
  14. Li J, Jia H, Cai X, Zhong H, Feng Q et al. An integrated catalog of reference genes in the human gut microbiome. Nat Biotechnol 2014; 32:834–841 [View Article][PubMed]
    [Google Scholar]
  15. Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG et al. Human gut microbiome viewed across age and geography. Nature 2012; 486:222–227 [View Article][PubMed]
    [Google Scholar]
  16. Goodrich JK, Davenport ER, Beaumont M, Jackson MA, Knight R et al. Genetic determinants of the gut microbiome in UK twins. Cell Host Microbe 2016; 19:731–743 [View Article][PubMed]
    [Google Scholar]
  17. Bradley PH, Pollard KS. Proteobacteria explain significant functional variability in the human gut microbiome. Microbiome 2017; 5:36 [View Article][PubMed]
    [Google Scholar]
  18. Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res 2016; 44:D457–D462 [View Article][PubMed]
    [Google Scholar]
  19. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 2010; 7:335–336 [View Article][PubMed]
    [Google Scholar]
  20. Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010; 26:2460–2461 [View Article][PubMed]
    [Google Scholar]
  21. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 2006; 72:5069–5072 [View Article][PubMed]
    [Google Scholar]
  22. Langille MGI, Zaneveld J, Caporaso JG, McDonald D, Knights D et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol 2013; 31:814–821 [View Article][PubMed]
    [Google Scholar]
  23. Aßhauer KP, Wemheuer B, Daniel R, Meinicke P. Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics 2015; 31:2882–2884 [View Article][PubMed]
    [Google Scholar]
  24. Ye Y, Doak TG. A parsimony approach to biological pathway reconstruction/inference for genomes and metagenomes. PLoS Comput Biol 2009; 5:14 [View Article][PubMed]
    [Google Scholar]
  25. Levy R, Carr R, Kreimer A, Freilich S, Borenstein E. NetCooperate: a network-based tool for inferring host-microbe and microbe-microbe cooperation. BMC Bioinformatics 2015; 16:164 [View Article][PubMed]
    [Google Scholar]
  26. Darzi Y, Letunic I, Bork P, Yamada T. iPath3.0: interactive pathways explorer v3. Nucleic Acids Res 2018; 46:W510–W513 [View Article][PubMed]
    [Google Scholar]
  27. Donohoe DR, Garge N, Zhang X, Sun W, O'Connell TM et al. The microbiome and butyrate regulate energy metabolism and autophagy in the mammalian colon. Cell Metab 2011; 13:517–526 [View Article][PubMed]
    [Google Scholar]
  28. Furusawa Y, Obata Y, Fukuda S, Endo TA, Nakato G et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature 2013; 504:446–450 [View Article][PubMed]
    [Google Scholar]
  29. Letunic I, Yamada T, Kanehisa M, Bork P. iPath: interactive exploration of biochemical pathways and networks. Trends Biochem Sci 2008; 33:101–103 [View Article][PubMed]
    [Google Scholar]
  30. Nayfach S, Shi ZJ, Seshadri R, Pollard KS, Kyrpides NC. New insights from uncultivated genomes of the global human gut microbiome. Nature 2019; 568:505–510 [View Article][PubMed]
    [Google Scholar]
  31. Brito IL, Yilmaz S, Huang K, Xu L, Jupiter SD et al. Mobile genes in the human microbiome are structured from global to individual scales. Nature 2016; 535:435–439 [View Article][PubMed]
    [Google Scholar]
  32. Abu-Ali GS, Mehta RS, Lloyd-Price J, Mallick H, Branck T et al. Metatranscriptome of human faecal microbial communities in a cohort of adult men. Nat Microbiol 2018; 3:356–366 [View Article][PubMed]
    [Google Scholar]
  33. Blaser MJ. The past and future biology of the human microbiome in an age of extinctions. Cell 2018; 172:1173–1177 [View Article][PubMed]
    [Google Scholar]
  34. Moran NA, Sloan DB. The hologenome concept: helpful or hollow?. PLoS Biol 2015; 13:e1002311 [View Article][PubMed]
    [Google Scholar]
  35. Theis KR, Dheilly NM, Klassen JL, Brucker RM, Baines JF et al. Getting the hologenome concept right: an eco-evolutionary framework for hosts and their microbiomes. mSystems 2016; 1:e00028-16 [View Article][PubMed]
    [Google Scholar]
  36. Bier RL, Voss KA, Bernhardt ES. Bacterial community responses to a gradient of alkaline mountaintop mine drainage in Central Appalachian streams. ISME J 2015; 9:1378–1390 [View Article][PubMed]
    [Google Scholar]
  37. Buffie CG, Bucci V, Stein RR, McKenney PT, Ling L et al. Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile . Nature 2015; 517:205–208 [View Article][PubMed]
    [Google Scholar]
  38. Goldford JE, Lu N, Bajić D, Estrela S, Tikhonov M et al. Emergent simplicity in microbial community assembly. Science 2018; 361:469–474 [View Article][PubMed]
    [Google Scholar]
  39. Douglas GM, Beiko RG, Langille MGI. Predicting the functional potential of the microbiome from marker genes using PICRUSt. Methods Mol Biol 2018; 1849:169–177 [View Article][PubMed]
    [Google Scholar]
  40. Douglas GM, Maffei VJ, Zaneveld J, Yurgel SN, Brown JR et al. PICRUSt2: an improved and extensible approach for metagenome inference. bioRxiv 2019; 672295:
    [Google Scholar]
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