title: Emergence of microbial networks as response to hostile environments.
abstract: 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.
authors.affiliation: Department of Information Engineering and Mathematics, University of Siena Siena, Italy.
authors.forename: Dario
authors.initials: D
authors.lastname: Madeo
authors.affiliation: Structural Biology and Imaging Department, Life Sciences Division, Lawrence Berkeley National Laboratory Berkeley, CA, USA.
authors.forename: Luis R
authors.initials: LR
authors.lastname: Comolli
authors.affiliation: Department of Information Engineering and Mathematics, University of Siena Siena, Italy.
authors.forename: Chiara
authors.initials: C
authors.lastname: Mocenni
keywords: bacterial social networks; evolutionary games; evolutive decisions; graph theory; hostile environmental conditions; microbial communities