Long Chengyi, Deng Jie, Nguyen Jen, Liu Yang-Yu, Alm Eric J, Solé Ricard, Saavedra Serguei
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.
Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139.
Proc Natl Acad Sci U S A. 2024 Feb 6;121(6):e2312521121. doi: 10.1073/pnas.2312521121. Epub 2024 Jan 29.
Microbial systems appear to exhibit a relatively high switching capacity of moving back and forth among few dominant communities (taxon memberships). While this switching behavior has been mainly attributed to random environmental factors, it remains unclear the extent to which internal community dynamics affect the switching capacity of microbial systems. Here, we integrate ecological theory and empirical data to demonstrate that structured community transitions increase the dependency of future communities on the current taxon membership, enhancing the switching capacity of microbial systems. Following a structuralist approach, we propose that each community is feasible within a unique domain in environmental parameter space. Then, structured transitions between any two communities can happen with probability proportional to the size of their feasibility domains and inversely proportional to their distance in environmental parameter space-which can be treated as a special case of the gravity model. We detect two broad classes of systems with structured transitions: one class where switching capacity is high across a wide range of community sizes and another class where switching capacity is high only inside a narrow size range. We corroborate our theory using temporal data of gut and oral microbiota (belonging to class 1) as well as vaginal and ocean microbiota (belonging to class 2). These results reveal that the topology of feasibility domains in environmental parameter space is a relevant property to understand the changing behavior of microbial systems. This knowledge can be potentially used to understand the relevant community size at which internal dynamics can be operating in microbial systems.
微生物系统似乎表现出相对较高的转换能力,能够在少数几个优势群落(分类单元成员)之间来回切换。虽然这种切换行为主要归因于随机环境因素,但尚不清楚群落内部动态在多大程度上影响微生物系统的转换能力。在这里,我们整合了生态学理论和实证数据,以证明结构化的群落转变会增加未来群落对当前分类单元成员的依赖性,从而增强微生物系统的转换能力。遵循结构主义方法,我们提出每个群落在环境参数空间的唯一域内是可行的。然后,任意两个群落之间的结构化转变发生的概率与它们可行域的大小成正比,与它们在环境参数空间中的距离成反比——这可以被视为引力模型的一个特例。我们检测到两类具有结构化转变的系统:一类是在广泛的群落大小范围内转换能力都很高,另一类是仅在狭窄的大小范围内转换能力很高。我们使用肠道和口腔微生物群(属于第1类)以及阴道和海洋微生物群(属于第2类)的时间数据来证实我们的理论。这些结果表明,环境参数空间中可行域的拓扑结构是理解微生物系统变化行为的一个相关属性。这些知识可能有助于理解微生物系统中内部动态可能起作用的相关群落大小。