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，即细菌种类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，我们可以检测到演替的模式，然而，关于驱动这些变化的机制，我们还存在一个基本的知识缺口。在驱动演替的三种主要力量（随机、非生物和生物）中，我们对细菌与细菌之间的相互作用等生物力量所知最少。竞争（负相互作用）通过耗尽共享资源、产生有毒化合物或直接杀死而发生。竞争在环境中无处不在，但在宿主相关微生物群落中才刚刚开始研究。与演替相关的合作（积极互动）是通过产生对他人有用的新资源（交叉喂养），但在压力下也可能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有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，分子分类分析和合成生态学来识别和表征细菌-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的细菌。将合成生态学与经验数据和数学模型相结合，将突出我们的合成生物学方法不能完全解释的群落演替方面，需要进一步研究。我们期望首次量化微生物群落演替过程中的生物力量，我们的婴儿肠道微生物组简化模型。揭示这些基本机制将直接有助于微生物生态学领域，因为微生物群落的功能，如生产力，或行为，如在压力下的崩溃，是通过演替决定的。了解微生物群落如何达到最终状态对于解释所有微生物群落的观察结果至关重要，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.