Emergent simplicity in microbial community assembly

Abstract

Published in final edited form as: Science. 2018 August 03; 361(6401): 469–474. doi:10.1126/science.aat1168.A major unresolved question in microbiome research is whether the complex taxonomic architectures observed in surveys of natural communities can be explained and predicted by fundamental, quantitative principles. Bridging theory and experiment is hampered by the multiplicity of ecological processes that simultaneously affect community assembly in natural ecosystems. We addressed this challenge by monitoring the assembly of hundreds of soil- and plant-derived microbiomes in well-controlled minimal synthetic media. Both the community-level function and the coarse-grained taxonomy of the resulting communities are highly predictable and governed by nutrient availability, despite substantial species variability. By generalizing classical ecological models to include widespread nonspecific cross-feeding, we show that these features are all emergent properties of the assembly of large microbial communities, explaining their ubiquity in natural microbiomes.The funding for this work partly results from a Scialog Program sponsored jointly by the Research Corporation, for Science Advancement and. the Gordon and Betty Moore Foundation through grants to Yale University and Boston University by the Research Corporation and by the Simons Foundation. This work was also supported by a young; investigator award from the Human Frontier Science Program to A.S. (RGY0077/2016) and by NIH NIGMS grant 1R35GM119461 and a Simons Investigator as in the Mathematical Modeling of Living Systems (MMLS) to P.M.; D.S. and J.E.G. additionally acknowledge funding from the Defense Advanced Research Projects Agency (purchase request no. HR0011515303, contract no.. HR0011-15-0-0091), the U.S. Department of Energy (DE-SC0012627), the NIH (T32GM100842, 5R01DE024468, R01GM121950, and Sub_P30DK036836_P&F), the National Science Foundation (1457695), the Human Frontier Science Program (RGP0020/2016) and the Boston University Interdisciplinary Biomedical Research Office. (Research Corporation, for Science Advancement; Gordon and Betty Moore Foundation; Boston University by the Research Corporation; Simons Foundation.; RGY0077/2016 - uman Frontier Science Program; 1R35GM119461 - NIH NIGMS grant; Simons Investigator as in the Mathematical Modeling of Living Systems (MMLS); HR0011515303 - Defense Advanced Research Projects Agency; HR0011-15-0-0091 - Defense Advanced Research Projects Agency; T32GM100842 - NIH; 5R01DE024468 - NIH; R01GM121950 - NIH; ub_P30DK036836 - NIH; 1457695 - National Science Foundation; RGP0020/2016 - Human Frontier Science Program; Boston University Interdisciplinary Biomedical Research Office)Accepted manuscrip