Rocabert Charles, Knibbe Carole, Consuegra Jessika, Schneider Dominique, Beslon Guillaume
Univ. de Lyon, CNRS, INRIA, INSA-Lyon, UCB Lyon 1, LIRIS UMR5205, Lyon, France.
Univ. Grenoble Alpes, Laboratoire Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble (TIMC-IMAG), Grenoble, France.
PLoS Comput Biol. 2017 Mar 30;13(3):e1005459. doi: 10.1371/journal.pcbi.1005459. eCollection 2017 Mar.
Metabolic cross-feeding interactions between microbial strains are common in nature, and emerge during evolution experiments in the laboratory, even in homogeneous environments providing a single carbon source. In sympatry, when the environment is well-mixed, the reasons why emerging cross-feeding interactions may sometimes become stable and lead to monophyletic genotypic clusters occupying specific niches, named ecotypes, remain unclear. As an alternative to evolution experiments in the laboratory, we developed Evo2Sim, a multi-scale model of in silico experimental evolution, equipped with the whole tool case of experimental setups, competition assays, phylogenetic analysis, and, most importantly, allowing for evolvable ecological interactions. Digital organisms with an evolvable genome structure encoding an evolvable metabolic network evolved for tens of thousands of generations in environments mimicking the dynamics of real controlled environments, including chemostat or batch culture providing a single limiting resource. We show here that the evolution of stable cross-feeding interactions requires seasonal batch conditions. In this case, adaptive diversification events result in two stably co-existing ecotypes, with one feeding on the primary resource and the other on by-products. We show that the regularity of serial transfers is essential for the maintenance of the polymorphism, as it allows for at least two stable seasons and thus two temporal niches. A first season is externally generated by the transfer into fresh medium, while a second one is internally generated by niche construction as the provided nutrient is replaced by secreted by-products derived from bacterial growth. In chemostat conditions, even if cross-feeding interactions emerge, they are not stable on the long-term because fitter mutants eventually invade the whole population. We also show that the long-term evolution of the two stable ecotypes leads to character displacement, at the level of the metabolic network but also of the genome structure. This difference of genome structure between both ecotypes impacts the stability of the cross-feeding interaction, when the population is propagated in chemostat conditions. This study shows the crucial role played by seasonality in temporal niche partitioning and in promoting cross-feeding subgroups into stable ecotypes, a premise to sympatric speciation.
微生物菌株之间的代谢交叉喂养相互作用在自然界中很常见,并且在实验室的进化实验中也会出现,即使是在提供单一碳源的均匀环境中。在同域分布中,当环境充分混合时,新兴的交叉喂养相互作用有时会变得稳定并导致占据特定生态位(称为生态型)的单系基因型簇的原因仍不清楚。作为实验室进化实验的替代方法,我们开发了Evo2Sim,这是一个计算机模拟实验进化的多尺度模型,配备了完整的实验设置、竞争分析、系统发育分析工具,最重要的是,允许进化的生态相互作用。具有可进化基因组结构并编码可进化代谢网络的数字生物体在模拟真实受控环境动态的环境中进化了数万代,包括提供单一限制资源的恒化器或分批培养。我们在此表明,稳定的交叉喂养相互作用的进化需要季节性分批条件。在这种情况下,适应性多样化事件会导致两种稳定共存的生态型,一种以主要资源为食,另一种以副产品为食。我们表明,连续转移的规律性对于维持多态性至关重要,因为它允许至少两个稳定季节,从而形成两个时间生态位。第一个季节是由转移到新鲜培养基中外部产生的,而第二个季节是由生态位构建内部产生的,因为提供的营养被细菌生长分泌的副产品所取代。在恒化器条件下,即使出现交叉喂养相互作用,从长期来看它们也不稳定,因为更适应的突变体最终会侵入整个种群。我们还表明,两种稳定生态型的长期进化会导致特征取代,这不仅体现在代谢网络层面,也体现在基因组结构层面。当种群在恒化器条件下繁殖时,这两种生态型之间基因组结构的差异会影响交叉喂养相互作用的稳定性。这项研究表明了季节性在时间生态位划分以及促进交叉喂养亚群形成稳定生态型方面所起的关键作用,这是同域物种形成的一个前提。