The role of bacterial interactions in succession of microbial communities in anaerobic environments

微生物存在于通过动态过程形成的复杂群落中。演替，即细菌物种数量和丰度随时间的变化，调节了所产生的群落的许多方面，如物种丰富度和多样性。通过DNA测序，我们可以检测到继承的模式，但对于驱动这些变化的机制存在根本的知识差距。在驱动演替的三种主要力量（随机、非生物和生物）中，我们对细菌-细菌相互作用等生物力量知之甚少。竞争（负面相互作用）通过消耗共享资源、生产有毒化合物或直接杀死而发生。竞争在环境中普遍存在，但在宿主相关的微生物群落中才开始研究。与继承相关的合作（积极的相互作用）是通过生产对他人有用的新资源（交叉喂养），但在压力下也可以包括抗生素等分子的解毒。只有一小部分细菌相互作用是合作的，然而，它们对微生物群落和演替产生了不成比例的强烈影响。我的研究项目旨在确定细菌如何通过竞争和合作相互作用，以及这些相互作用对微生物群落演替的影响。我们将通过体外培养，分子分类学分析和合成生态学来鉴定和表征细菌-细菌相互作用。我们将通过收集有关体外微生物群落的经验数据来确定微生物群落中有影响力的细菌。合成生态学与经验数据和数学建模的结合将突出群落演替的方面，我们的合成生物学方法不能完全解释，需要进一步研究。我们希望通过我们简化的婴儿肠道微生物组模型，首次量化微生物群落演替过程中的生物力量。揭示这些基本机制将直接有助于微生物生态学领域，因为微生物群落功能，如生产力，或行为，如压力下的崩溃，是通过演替决定的。了解微生物群落如何达到其最终状态对于解释微生物群落的所有观察结果至关重要，并将有利于保护生物学、生物多样性和生物技术领域的研究。

Microorganisms exist in complex communities that are formed through dynamic processes. Succession, the change in the number and abundance of bacterial species over time, regulates many aspects of the resulting community, such as species richness and diversity. With DNA sequencing we can detect the patterns of succession, yet there is a fundamental knowledge gap about the mechanisms that drive these changes. Of the three main forces that drive succession (random, abiotic and biotic), we know the least about biotic forces such as bacteria-bacteria interactions. Competition (negative interactions) occurs through the depletion of shared resources, production of toxic compounds or direct killing. Competition is ubiquitous in the environment but has only begun to be studied in host-associated microbial communities. Cooperation (positive interactions) relevant to succession is through the production of a new resource useful to others (cross-feeding) but under stress can also include the detoxification of molecules like antibiotics. Only a fraction of bacterial interactions are cooperative, however, they have a disproportionately strong impact on microbial communities and succession. My research program aims to determine how bacteria interact with one another, through competition and cooperation, and the impact of these interactions on succession of microbial communities. We will identify and characterize bacteria-bacteria interactions with in vitro culture, molecular taxonomic profiling and synthetic ecology. We will identify influential bacteria within microbial community assembly by collecting empirical data about microbial communities in vitro. The combination of synthetic ecology with empirical data and mathematical modeling will highlight the aspects of community succession that are not fully explained by our synthetic biology approach requiring further study. We expect to quantify, for the first time, the biotic forces during microbial community succession with our simplified model of the gut microbiome from infants. Uncovering these basic mechanisms will contribute directly to the field of microbial ecology since microbial community function, such as productivity, or behavior, such as collapse under stress, are determined through succession. An understanding of how communities get to their final state is essential to the interpretation of all observations of microbial communities and will benefit research within the areas of conservation biology, biodiversity and biotechnology.