Suppr超能文献

在恒化器中模拟微生物代谢权衡。

Modeling microbial metabolic trade-offs in a chemostat.

机构信息

Center for Quantitative Biology, Peking University, Beijing, China.

Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.

出版信息

PLoS Comput Biol. 2020 Aug 28;16(8):e1008156. doi: 10.1371/journal.pcbi.1008156. eCollection 2020 Aug.

Abstract

Microbes face intense competition in the natural world, and so need to wisely allocate their resources to multiple functions, in particular to metabolism. Understanding competition among metabolic strategies that are subject to trade-offs is therefore crucial for deeper insight into the competition, cooperation, and community assembly of microorganisms. In this work, we evaluate competing metabolic strategies within an ecological context by considering not only how the environment influences cell growth, but also how microbes shape their chemical environment. Utilizing chemostat-based resource-competition models, we exhibit a set of intuitive and general procedures for assessing metabolic strategies. Using this framework, we are able to relate and unify multiple metabolic models, and to demonstrate how the fitness landscape of strategies becomes intrinsically dynamic due to species-environment feedback. Such dynamic fitness landscapes produce rich behaviors, and prove to be crucial for ecological and evolutionarily stable coexistence in all the models we examined.

摘要

微生物在自然界中面临着激烈的竞争,因此需要明智地将资源分配到多种功能上,特别是代谢功能。因此,了解受权衡影响的代谢策略之间的竞争对于更深入地了解微生物的竞争、合作和群落组装至关重要。在这项工作中,我们通过考虑环境不仅如何影响细胞生长,还考虑微生物如何塑造其化学环境,在生态背景下评估竞争代谢策略。利用基于恒化器的资源竞争模型,我们展示了一组直观且通用的程序来评估代谢策略。使用这个框架,我们能够关联和统一多种代谢模型,并展示由于物种-环境反馈,策略的适应度景观如何变得内在动态。这种动态适应度景观产生了丰富的行为,并被证明对于我们研究的所有模型中的生态和进化稳定共存至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/446d/7482850/5f9e6fdac42e/pcbi.1008156.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验