标题： 相互作用的宿主与微生物组交换：离散相互作用的元群落理论扩展 显示英文标题

标题： Interacting Hosts with Microbiome Exchange: An Extension of Metacommunity Theory for Discrete Interactions

摘要： 微生物组是由环境中相互作用的微生物组成的集合，它们通常显著影响其所占据的环境斑块或宿主。在微生物组模型中，考虑环境内部的局部动态以及不同环境之间的微生物组交换是很重要的。一种将这些及其他跨多个尺度的相互作用纳入考虑的方法是采用元群落理论。元群落模型通常假设在发生局部微生物组动态的环境中，微生物组持续扩散。在这种假设下，每对环境之间的一个参数控制这两个环境之间的扩散率。这种元群落框架非常适合非生物环境斑块，但它无法捕捉到活体宿主微生物组的一个关键方面，即这些宿主通常不会持续相互作用。相反，活体宿主在离散的时间间隔内相互作用。在本文中，我们开发了一个编码这种离散相互作用的建模框架，并使用两个参数分别控制宿主之间的相互作用频率以及每次相互作用时的微生物组交换量。我们在三种参数范围内推导了框架中模型的解析近似，并证明了它们在这些范围内的准确性。我们将这些近似与一个示例模型的数值模拟进行了比较。我们证明，我们的建模框架中的两个参数对于确定微生物组动态都是必要的。动态的关键特征，如宿主间的微生物组收敛，对相互作用频率和强度之间的相互作用非常敏感。 显示英文摘要

摘要： Microbiomes, which are collections of interacting microbes in an environment, often substantially impact the environmental patches or living hosts that they occupy. In microbiome models, it is important to consider both the local dynamics within an environment and exchanges of microbiomes between environments. One way to incorporate these and other interactions across multiple scales is to employ metacommunity theory. Metacommunity models commonly assume continuous microbiome dispersal between the environments in which local microbiome dynamics occur. Under this assumption, a single parameter between each pair of environments controls the dispersal rate between those environments. This metacommunity framework is well-suited to abiotic environmental patches, but it fails to capture an essential aspect of the microbiomes of living hosts, which generally do not interact continuously with each other. Instead, living hosts interact with each other in discrete time intervals. In this paper, we develop a modeling framework that encodes such discrete interactions and uses two parameters to separately control the interaction frequencies between hosts and the amount of microbiome exchange during each interaction. We derive analytical approximations of models in our framework in three parameter regimes and prove that they are accurate in those regimes. We compare these approximations to numerical simulations for an illustrative model. We demonstrate that both parameters in our modeling framework are necessary to determine microbiome dynamics. Key features of the dynamics, such as microbiome convergence across hosts, depend sensitively on the interplay between interaction frequency and strength.