Evolutionary dynamics of diverse bacterial communities in nature

了解物种如何适应新的环境是进化生物学中最大的挑战之一。然而，实验研究和理论几乎完全集中在包含最多几个物种的简化系统上。如果物种在自然群落中的相互作用从根本上改变了进化的结果，那么就有必要在整个群落的背景下研究适应过程，并了解适应对群落结构和功能的影响。我们以前使用的细菌物种的简单社区，以表明，当挑战一个新的环境，几个物种的混合物的进化动力学与作为单一物种的增长有很大的不同。此外，随着时间的推移，资源的使用和物种的相互作用不断演变，导致整个群落的功能发生变化（以呼吸率衡量）。然而，这些实验仍然集中在相对较少的物种上。我们对简化实验室研究的结果如何应用于自然群落的动态知之甚少。在拟议的项目中，我们将通过跟踪物种适应来应对这一挑战，同时它们嵌入在不同的自然群落中。我们将利用一种新的方法，在实验室围隔生态系统和自然栖息地中“笼住”细菌，这样我们就可以跟踪在不同群落中生长的单一焦点物种。广泛用于复杂细菌群落描述性研究的技术--包括用于跟踪组成变化的下一代测序条形码和用于测量潜在物种相互作用的化学资源使用变化的核磁共振光谱--将应用于实验操作的群落。在实验室实验中，我们将研究多样性如何影响焦点物种适应其物理环境的变化，即酸化。我们预测，多样性应限制组件物种的适应。我们还将量化一组23个焦点物种之间的相互作用如何演变时，暴露于一系列不同的背景社区从天然树洞隔离。我们预测，多样性应该限制物种之间的积极相互作用的演变（我们在早期的实验中观察到的只有几个物种的社区）。在野外实验中，我们将使用我们的实验“笼子”，通过在不同的树洞之间移植分离株，来确定细菌是否适应当地的物理条件和在自己的树洞中发现的生物群落。我们还将把“笼中”细菌放置更长的时间，并测量它们是否适应以提高它们在新环境中生长的能力。最后，在实验室和现场，我们将测试在早期的目标中发现的进化模式是否会导致整个社区的生态系统水平功能的变化。我们之前对简化社区的研究发现，物种适应彼此存在的方式导致它们以更高的速度集体使用可用资源。然而，我们预测，自然群落的非凡多样性可能会确保足够的社区水平的功能，而不管进化历史如何。总体而言，该项目将有助于了解不同社区的相互作用如何影响组成物种的进化，相互作用本身如何演变，以及这些变化如何影响生态系统功能的基本知识。这项工作将为预测微生物群落的动态提供直接的知识，以及适用于其他无法以这种方式进行实验研究的群落的见解。例如，我们的研究结果将产生关于植物和动物群落如何应对环境扰动的假设。

Understanding how species adapt to novel environments is among the greatest challenges in evolutionary biology. However, experimental studies and theories have focused almost exclusively on simplified systems containing at most a few species. If species interactions in natural communities fundamentally alter evolutionary outcomes, then there is a need to study the adaptive process within the context of entire communities, and to understand the consequences of adaptation for community structure and functioning. We previously used simple communities of bacteria species to show that, when challenged with a novel environment, the evolutionary dynamics of mixtures of a few species differ substantially from those grown as single species. Furthermore, resource use and species interactions evolved over time and led to a change in the functioning of the entire community (measured as the respiration rate). However, these experiments still focused on relatively few species. Very little is known of how the findings of simplified laboratory studies apply to the dynamics of natural communities.In the proposed project, we will meet this challenge by tracking species adaptation while they are embedded within diverse natural communities. We will make use of a novel method of 'caging' bacteria in both laboratory mesocosms and natural habitats so that we can track a single focal species growing within a diverse community. Techniques widely used for descriptive studies of complex bacterial communities - including next-generation sequencing barcodes to track changes in composition and nuclear magnetic resonance spectroscopy to measure changes in chemical resource use underlying species interactions - will be applied to the experimentally manipulated communities. In laboratory experiments, we will investigate how diversity affects the adaptation of focal species to changes in their physical environment, namely acidification. We predict that diversity should constrain adaptation of component species. We will also quantify how interactions among a set of 23 focal species evolve when exposed to a range of different background communities isolated from natural tree-holes. We predict that diversity should constrain the evolution of positive interactions among species (which we observed in earlier experiments with communities of just a few species). In field experiments, we will use our experimental 'cages' to determine whether bacteria are adapted to the local physical conditions and biological communities found in their own tree-hole, by transplanting isolates between different tree-holes. We will also leave 'caged' bacteria for longer periods and measure whether they adapt to improve their ability to grow in novel environments. Finally, in both the laboratory and the field, we will test whether the patterns of evolution uncovered in the earlier objectives lead to changes in the ecosystem-level functioning of the entire community. Our previous work with simplified communities found that the way in which species adapt to each other's presence leads to them collectively using available resources at an improved rate. We predict, however, that the extraordinary diversity of natural communities might ensure adequate community-level functioning irrespective of evolutionary history. Overall, the project will contribute fundamental knowledge to understanding how interactions in diverse communities influence the evolution of component species, how interactions themselves evolve, and how these changes impact on ecosystem functioning. The work will provide direct knowledge for predicting dynamics of microbial communities, as well as insights applicable to other communities that cannot be studied in this way experimentally. For example, our findings will generate hypotheses for how plant and animal communities might evolve in response to perturbation of their environments.