Structured community transitions explain the switching capacity of microbial systems.
Structured community transitions explain the switching capacity of microbial systems.
复制标题
结构化群落转变解释了微生物系统的转换能力。
DOI：
10.1073/pnas.2312521121
复制
发表时间：
2024
影响因子：
11.1
通讯作者：
Saavedra,Serguei
中科院分区：
文献类型：
--
作者：
Long,Chengyi;Deng,Jie;Nguyen,Jen;Liu,Yang-Yu;Alm,EricJ;Solé,Ricard;Saavedra,Serguei
微生物系统似乎表现出在少数优势群落(分类群成员)之间来回移动的相对较高的切换能力。虽然这种切换行为主要归因于随机环境因素，但仍不清楚内部群落动态对微生物系统切换能力的影响程度。在这里，我们结合生态学理论和经验数据来证明，结构化的群落过渡增加了未来群落对当前分类单元成员的依赖，增强了微生物系统的转换能力。遵循结构主义的方法，我们认为每个群落在环境参数空间中的唯一域内是可行的。然后，任意两个群落之间的结构转换可以发生，其概率与其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--这可以被视为重力模型的特例。我们检测到两大类具有结构化转换的系统：一类交换容量在广泛的社区规模范围内高，另一类交换容量仅在狭窄的大小范围内高。我们使用肠道和口腔微生物区系(属于第一类)以及阴道和海洋微生物区系(属于第二类)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是理解微生物系统变化行为的一个相关性质。这一知识可能被用来理解微生物系统中内部动态可能运行的相关群落规模。
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.