The tempo and mode of evolutionary dynamics in wild bacterial communities

所有物种都与数以百计的其他物种生活在不同的群体中。环境科学的一个关键挑战是足够详细地了解复杂的生态系统，以预测它们将如何应对多变的环境。这是困难的，因为整个生态系统的反应取决于所有组成物种的特征和它们之间的相互作用。关键的是，物种的特征不仅是恒定的，而且会随着时间的推移而演变。此外，特征进化的方式在丰度和分布上与生态变化相互作用。因此，对不同社区的进化进行核算，对于在与政策相关的时间范围内管理自然系统至关重要。这个项目将在细菌中解决这个问题。细菌生活在异常多样化的群落中，支撑着人类赖以生存的许多过程，如营养循环、分解、废物处理和人类营养。我们知道，在实验室里，当它们暴露在强大的选择压力下，如抗生素时，它们会在几天、几周和几个月的时间里快速进化。然而，由于在如此多样化的系统中跟踪进化的挑战，野生细菌群落中典型的进化速度和驱动因素在很大程度上仍不清楚。我们将利用基因组测序、实验室分析的机器人处理和操纵性实验的最新进展来记录野生细菌群落的进化。我们的系统包括生活在由山毛榉树根形成的短暂水池中的细菌，这些水池被称为树洞。我们之前已经在实验室为这些群落开发了实验进化，并在野外调查了多样性--在这里，我们将整合这些方法，并量化野生树洞的进化动态。我们将比较正常情况下的对照树洞和因pH升高而受到干扰的树洞，这些树洞的pH值高于通过石灰处理实现的自然范围。我们将从元基因组和目标基因组测序数据中量化生态和遗传变化在一系列时间尺度(周、月到一年)上的节奏，并估计决定进化率的关键参数，如世代时间、有效种群规模和正选择频率-目前在野生细菌中未知。这项工作将开发适用于未来其他系统的新方法，包括细菌和真核生物。为了表征进化模式，我们将使用时移分析来测试细菌群落是持续共同进化(根据红女王进化范式的建议)，还是主要适应非生物条件的变化(根据Court Jester范式的建议)，或者以进化平衡的方式共存(根据静态范式的建议)。对局部共同适应的进一步测试将确定社区是否在斑块内局部共同进化。这一方法将涉及在机器人系统上运行50,000多个增长分析，我们已经在早期的研究中试验过这种方法，以证明其可行性。为了进一步确定扩散对群落动力学的重要性，我们将在实验室对瓶子中的整个群落进行实验，比较定期从区域池中接收细菌流入的瓶子与初始接种后没有流入的封闭瓶子之间的反应。结合起来，这些结果将揭示局部动态与扩散、生物条件与非生物条件在设定野生细菌进化模式方面的相对重要性。我们在细菌进化动力学的节奏和模式方面的发现将为未来在广泛应用中对微生物系统的预测和管理提供关键数据。

All species live in diverse assemblages with many hundreds of other species. A key challenge for environmental science is to understand complex ecosystems in enough detail to predict how they will respond to fluctuating environments. This is difficult because whole-ecosystem responses depend on traits of all constituent species and interactions among them. Critically, species traits are not just constant but evolve over time. Moreover, the way that traits evolve interacts with ecological changes in abundance and distribution. Accounting for evolution in diverse communities is therefore vital for managing natural systems over policy-relevant timescales. This project will tackle this problem in bacteria. Bacteria live in exceptionally diverse communities and underpin many processes that human populations depend upon, such as nutrient cycling, decomposition, waste treatment and human nutrition. We know that they evolve rapidly over days, weeks and months in the laboratory and when exposed to strong selection pressures, such as antibiotics. The typical speed and drivers of evolution in wild bacterial communities remains largely unknown, however, due to challenges in tracking evolution in such diverse systems. We will take advantage of recent advances in genome sequencing, robot handling of laboratory assays, and manipulative experiments to document evolution in wild bacterial communities. Our system comprises the bacteria living in ephemeral pools formed by the roots of beech trees, called tree-holes. We have previously developed experimental evolution for these communities in the laboratory and surveyed diversity in the field - here, we will integrate these approaches and quantify evolutionary dynamics in wild tree-holes. We will compare control tree-holes in normal conditions with tree-holes perturbed by an increase in pH above the natural range implemented by liming. We will quantify the tempo of ecological and genetic changes over a hierarchy of time-scales (weeks, months, to a year) from metagenome and targeted genome sequencing data and estimate key parameters that determine evolutionary rates such as generation times, effective population size, and the frequency of positive selection - currently unknown in wild bacteria. The work will develop new methodology applicable to other systems in future, including both bacteria and eukaryotes.To characterise the mode of evolution, we will use time-shift assays to test whether the bacterial communities are continually coevolving (as proposed by the Red Queen paradigm of evolution) or primarily adapting to changes in abiotic conditions (as proposed by the Court Jester paradigm) or coexist at an evolutionary equilibrium (as proposed by a Static paradigm). Further tests for local co-adaptation will determine whether communities coevolve locally within patches. This approach will involve running over 50,000 growth assays on robotic systems, an approach we have trialled in earlier studies to demonstrate feasibility here. To determine the importance of dispersal for community dynamics further, in tandem we will run experiments with whole communities in bottles in the laboratory, comparing responses between bottles that regularly receive an influx of bacteria from a regional pool and closed bottles that do not after initial inoculation. In combination, the results will reveal the relative importance of local dynamics versus dispersal, and biotic versus abiotic conditions, in setting the mode of evolution in wild bacteria. Our findings on tempo and mode of bacterial evolutionary dynamics will provide key data for future prediction and management of microbial systems across a wide range of applications.