Designing Metabolic Division of Labor in Microbial Communities
Designing Metabolic Division of Labor in Microbial Communities
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DOI：
10.1128/msystems.00263-18
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发表时间：
2019-03-01
期刊：
影响因子：
6.4
通讯作者：
Segre, Daniel
中科院分区：
文献类型：
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作者：
Thommes, Meghan;Wang, Taiyao;Segre, Daniel
微生物面临着代谢独立和依赖邻近生物体提供一些必需代谢物之间的权衡。这种冲突策略的平衡影响微生物群落结构和动态，对微生物组研究和合成生态学具有重要意义。研究这种权衡的“gedanken”（思想）实验将涉及监测相互依赖性的增加，因为有机体中允许的代谢反应的数量越来越受到限制。预期反应低于一定数量，任何个体生物体都无法孤立生长，并且会出现交叉喂养伙伴关系和劳动分工。我们使用计算机基因组规模模型实施了这个理想化的实验。特别是，我们使用混合整数线性规划来确定大肠杆菌菌株群落中的权衡解决方案。我们发现的策略揭示了微妙且非直观的代谢分工中存在大量机会，包括例如将三羧酸（TCA）循环分成两个独立的一半。对 1、2 和 3 菌株联合体分工中可能的解决方案的系统计算导致了丰富而复杂的景观。这种景观显示出非线性边界，表明细胞内反应的损失不一定可以通过单一输入的代谢物来补偿。该景观中的不同区域与交换代谢物的特定解决方案和模式相关。我们的方法还预测了该景观中存在一些区域，在这些区域中，独立的细菌是可行的，但会被交叉喂养的细菌击败，从而为劳动分工的兴起提供了可能的激励。 重要性 了解微生物如何组装成群落是生物学中的一个基本开放问题，与人类健康、代谢工程和环境可持续性相关。微生物相互作用的一种可能机制是通过交叉喂养，即小分子的交换。这些代谢交换可能允许不同的微生物专门从事不同的任务并进化出劳动分工。为了系统地探索可能的劳动分工策略空间，我们将先进的优化算法应用于细胞代谢的计算模型。具体来说，我们寻找能够在单个物种无法维持的限制（例如有限数量的反应）下生存的群落。我们发现，预测的联合体以难以手动识别的方式划分代谢途径，可能比个体生物体具有竞争优势。除了帮助了解自然微生物群落的多样性之外，我们的方法还可以帮助设计合成菌群。
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.