期刊
MSYSTEMS
卷 4, 期 2, 页码 -出版社
AMER SOC MICROBIOLOGY
DOI: 10.1128/mSystems.00263-18
关键词
division of labor; flux balance analysis; genome-scale stoichiometric models; metabolic networks; microbiome; mixed-integer linear programming; resource allocation; synthetic ecology; microbial communities
类别
资金
- Defense Advanced Research Projects Agency [HR0011515303, HR0011-15-C-0091]
- U.S. Department of Energy [DE-SC0004962, DE-SC0012627]
- National Institutes of Health [5R01DE024468, R01GM121950, Sub_P30DK036836_PF]
- National Science Foundation [1457695, NSFOCE-BSF 1635070, DMS-1664644, CNS-1645681, CCF-1527292, IIS-1237022]
- Army Research Office (MURI grant) [W911NF-12-1-0390]
- Office of Naval Research (MURI grant) [N00014-16-1-2832]
- Human Frontiers Science Program [RGP0020/2016]
- Boston University Interdisciplinary Biomedical Research Office
- U.S. Department of Energy (DOE) [DE-SC0012627, DE-SC0004962] Funding Source: U.S. Department of Energy (DOE)
Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A gedanken (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a non-linear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.
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