Department of Information Engineering and Mathematics, University of Siena Siena, Italy.
Structural Biology and Imaging Department, Life Sciences Division, Lawrence Berkeley National Laboratory Berkeley, CA, USA.
Front Microbiol. 2014 Aug 19;5:407. doi: 10.3389/fmicb.2014.00407. eCollection 2014.
The majority of microorganisms live in complex communities under varying conditions. One pivotal question in evolutionary biology is the emergence of cooperative traits and their sustainment in altered environments or in the presence of free-riders. Co-occurrence patterns in the spatial distribution of biofilms can help define species' identities, and systems biology tools are revealing networks of interacting microorganisms. However, networks of inter-dependencies involving micro-organisms in the planktonic phase may be just as important, with the added complexity that they are not bounded in space. An integrated approach linking imaging, "Omics" and modeling has the potential to enable new hypothesis and working models. In order to understand how cooperation can emerge and be maintained without abilities like memory or recognition we use evolutionary game theory as the natural framework to model cell-cell interactions arising from evolutive decisions. We consider a finite population distributed in a spatial domain (biofilm), and divided into two interacting classes with different traits. This interaction can be weighted by distance, and produces physical connections between two elements allowing them to exchange finite amounts of energy and matter. Available strategies to each individual of one class in the population are the propensities or "willingness" to connect any individual of the other class. Following evolutionary game theory, we propose a mathematical model which explains the patterns of connections which emerge when individuals are able to find connection strategies that asymptotically optimize their fitness. The process explains the formation of a network for efficiently exchanging energy and matter among individuals and thus ensuring their survival in hostile environments.
大多数微生物生活在复杂的环境中,其条件各不相同。进化生物学中的一个关键问题是合作特征的出现及其在环境变化或存在搭便车者的情况下的维持。生物膜空间分布的共现模式有助于定义物种的身份,而系统生物学工具则揭示了相互作用的微生物网络。然而,浮游阶段微生物之间的相互依赖关系网络可能同样重要,而且它们的复杂性在于不受空间限制。将成像、“组学”和建模相结合的综合方法有可能为新的假设和工作模型提供依据。为了了解在没有记忆或识别等能力的情况下合作是如何产生和维持的,我们使用进化博弈论作为自然框架来模拟由进化决策产生的细胞间相互作用。我们考虑一个分布在空间域(生物膜)中的有限种群,并将其分为两个具有不同特征的相互作用类。这种相互作用可以通过距离加权,并且在两个元素之间产生物理连接,允许它们交换有限量的能量和物质。种群中某一类个体的可用策略是与另一类个体中任何个体连接的倾向或“意愿”。根据进化博弈论,我们提出了一个数学模型,该模型解释了当个体能够找到渐近优化其适应性的连接策略时出现的连接模式。这个过程解释了如何在个体之间形成一个网络,以便有效地交换能量和物质,从而确保它们在恶劣环境中的生存。