MTM 2: Combining structural informatics and crosslinking mass spectrometry to predict the key protein-protein interactions shaping symbiotic microbial communities

动物体内和体内的微生物群落在生物学中发挥着深远的作用，影响宿主的行为、营养状况和弹性。微生物群落的大部分行为是由微生物的蛋白质和宿主之间的相互作用驱动的。这些相互作用被微生物用来附着、攻击或与周围的其他细胞交流。由于微生物群落极其复杂，已证明很难确定定义和稳定一个群落或影响其他群落成员的一组蛋白质-蛋白质相互作用。了解这些相互作用的机制对于设计或操纵微生物群落至关重要，例如，通过鼓励有益微生物的存在或驱逐有问题的微生物。该项目将结合生物信息学和生物化学方法，揭示蛋白质-蛋白质相互作用如何建立和维持微生物群落的规则。该项目将以两种著名的益生菌(“好”细菌)与人体肠道模型的相互作用为目标。开发的方法也将适用于广泛的其他微生物群落，包括涉及哺乳动物的微生物群落(应用于农业和医药)和涉及非生物表面的微生物群落(应用于食品加工和基础设施维护)。其他更广泛的影响包括在博物馆的外联活动和对下一代科学家进行微生物组研究的培训。该项目将开发一种计算和实验相结合的方法，以确定宿主-微生物蛋白质-蛋白质相互作用(PPI)的身份和功能影响，这些微生物群落生长在上皮细胞培养物和人类有机体内的合成微生物群落中。这些研究将集中在著名的益生菌菌株E.coliNissle和乳杆菌鼠李糖GG的定植上。使用高度可控的还原系统来研究PPI在微生物群落更广泛的行为中的作用，将使研究人员能够开发、测试和基准实验和计算工具，以确定重要的PPI并检查其功能影响。该项目将以开发先进的计算管道为基础，以实现对PPI网络结构和功能的大规模高质量预测。同时，对于目标有机物-微生物群落，研究人员将利用最近发展的交联质谱方法在实验上检查体内PPI的情况，并进行转座子文库图谱实验，以确定对宿主定植或微生物-微生物竞争有重要贡献的微生物基因。随后将使用小鼠粪便提取物和/或在肠道微生物群中发挥重要作用的厌氧菌来鉴定多物种群落中的PPI。本文提出的研究将通过列举推动细菌宿主定植的关键跨王国蛋白质-蛋白质相互作用(包括识别具有重要功能的相互作用)，以及通过开发和完善用于高通量预测生物间蛋白质-蛋白质相互作用及其功能重要性的计算框架，来促进我们的知识库和技术能力。这里开发的方法将是通用的，允许快速列举复杂微生物群落中的关键宿主-微生物和微生物-微生物PPI。该项目由了解生命规则：微生物组理论和机制计划资助，作为NSF十大想法和生物科学理事会新兴前沿部门的一部分进行管理。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Microbial communities on and inside of animals play profound roles in biology, affecting the behavior, nutritional status, and resilience of the host. Much of the behavior of microbial communities is driven by interactions between proteins of microbes and the host. These interactions are used by microbes to adhere to, attack, or communicate with other cells in their surroundings. Because microbial communities are tremendously complex, it has proven difficult to determine the set of protein-protein interactions that define and stabilize a community or affect other community members. Understanding the mechanics of those interactions is essential to engineer or manipulate microbial communities, e.g., by encouraging the presence of beneficial microbes or driving out those that are problematic. This project will unravel the rules governing how protein-protein interactions establish and maintain microbial communities using a combination of bioinformatics and biochemical approaches. The project will target the interaction of two well-known probiotic (‘good’) bacteria with models of the human intestine. The developed methods will also be applicable to a wide range of other microbial communities, both those involving mammals (with applications to agriculture and medicine) and those involving non-living surfaces (with applications to food processing and infrastructure maintenance). Other broader impacts include outreach activities at a museum and training of the next generation scientists in microbiome research.This project will develop a combination of computational and experimental approaches to determine the identities and functional implications of host-microbe protein-protein interactions (PPIs), in the context of synthetic microbial communities grown on epithelial cell cultures and in human organoids. The studies will focus on colonization by the well-known probiotic strains E. coli Nissle and Lactobacillus rhamnosus GG. The use of a highly controllable, reductionist system to study the roles of PPIs in the broader behavior of microbial communities will permit the investigators to develop, test, and benchmark experimental and computational tools to identify important PPIs and examine their functional implications. The project will be anchored by the development of advanced computational pipelines to enable large-scale high-quality prediction of the structure and function of PPI networks. In parallel, for the target organoid-microbe communities, the researchers will make use of recently developed crosslinking mass spectrometry methods to experimentally examine the landscape of PPIs in vivo, and transposon library profiling experiments to identify the microbial genes that contribute substantially to host colonization or microbe-microbe competition. This will be followed by the identification of PPIs in multi-species communities using mouse fecal extracts and/or anaerobes that play an important role in the gut microbiome. The research proposed here will contribute to our knowledge base and technical capabilities both through the enumeration of key trans-kingdom protein-protein interactions driving bacterial host colonization (including identification of the interactions that are functionally important), and through the development and refinement of a computational framework for high throughput prediction of inter-organism protein-protein interactions and their functional importance. The methods developed here will be generalizable to permit rapid enumeration of key host-microbe and microbe-microbe PPIs in complex microbial communities.This project is funded by the Understanding the Rules of Life: Microbiome Theory and Mechanisms Program, administered as part of NSF's Ten Big Ideas and the Division of Emerging Frontiers in the Directorate for Biological Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.