Identifying phage-bacteria interactions using a multispecies model

定植动物的微生物群落对动物的健康和发育是不可或缺的，但细节 关于是什么让这些社区发挥作用和稳定，目前还缺乏。噬菌体(感染的病毒 细菌)是动物微生物群中数量占优势的成员，它们影响着许多 这些社区的属性。噬菌体通过捕食来调节细菌群落组成， 在宿主基因组之间转移遗传物质，有益地刺激动物的免疫系统。 然而，我们对噬菌体的了解在很大程度上局限于一组有限的实验室适应菌株和 因此，我们对它们在动物微生物群中的作用缺乏了解。噬菌体可能会影响 通过调节细菌群落的组成和丰度，或通过促进细菌宿主毒力的变化，通过生态过程来控制疾病。 导致微生物组成随时间变化的因素通常很难确定和经验性检验，因为大多数动物微生物群都很复杂，实验上很难解决。我们建议利用一个重要的动物模型系统，蜜蜂(蜜蜂)，来确定生态和进化力量如何塑造动物微生物群。为此，我们概述了两个目标，这将有助于我们 描述这些力量的特征。 目的1：确定噬菌体抗性进化如何依赖于微生物的生长条件。在这一目标中 我们将全面测试可能影响增长速度的不同参数 细菌对噬菌体感染产生抵抗力。我们将仔细测量 细菌和噬菌体一起生长的集合的变化。我们期待确定这些动态是如何受到增长条件的影响的。 目的2：测定微生物相互作用对噬菌体抗性进化动态的影响。在这一目标中 我们扩大了我们的研究范围，将相互作用的细菌物种包括在内。在大多数自然条件下，微生物 在生活中，他们会遇到其他细菌。这些相互作用可能会改变细菌对感染它们的噬菌体的反应和进化抗性。我们的实验将通过共培养细菌并再次测量这些系统中的进化速度来解决这个问题。 在这两个目标中，我们采用了一种综合的方法，利用数学模型，在实验室中培养细菌和噬菌体，并测试它们在蜜蜂肠道中的生长。在这样做的过程中，我们受益于每种方法的优势，并增加了我们结果的严谨性。

The microbial communities colonizing animals are integral to animal health and development but details about what make these communities functional and stable are lacking. Bacteriophages (viruses that infect bacteria) are the numerically dominant members of animal microbiomes and they influence many properties of these communities. Bacteriophages regulate bacterial community composition by predation, transfer genetic material between host genomes, and beneficially stimulate the immune system of animals. However, our knowledge of bacteriophages is largely restricted to a limited set of lab-adapted strains and thus our understanding of their role in animal microbiomes is lacking. Bacteriophages may influence disease through ecological processes by regulating bacterial community composition and abundance or by promoting changes in the virulence of their bacterial hosts. The factors causing microbial composition to change over time are often hard to determine and empirically test because most animal microbiomes are complex and experimental intractable. We propose to utilize an important animal model system, the honey bee (Apis mellifera), to determine how ecological and evolutionary forces shape animal microbiomes. To this end, we outline two Aims that will help us characterize these forces. Aim 1: Determine how phage resistance evolution is dependent on microbial growth conditions. In this aim we will comprehensively test different parameters of growth than are likely to influence how quickly bacteria evolve resistance against bacteriophage infections. We will carefully measure the tempo of change in sets of bacteria and phages growing together. We anticipate identifying how these dynamics are impacted by growth conditions. Aim 2: Measure the impact of microbial interactions on phage resistance evolution dynamics. In this aim we expand our research to include interacting bacterial species. In most natural conditions that microbes live in they will encounter other bacteria. These interactions likely alter how bacteria respond to and evolveresistance against the bacteriophages that infect them. Our experiments will address this by co-culturing bacteria and again measuring the tempo of evolution in these systems. In both aims we adopt an integrative approach that utilizes mathematic modeling, culturing of bacteria and phages in the lab, and testing their growth in the honey bee gut. In doing so, we benefit from the strengths of each approach and increase the rigor of our results.