Elucidating the mechanisms of protein secretion across the outer membrane by bacterial autotransporters

项目总结/摘要 致病性革兰氏阴性细菌每年造成500多万人死亡。一些 物种也表现出高水平的抗生素耐药性，占世界上12个成员中的9个。 卫生组织的优先病原体清单。革兰氏阴性菌感染通常由所谓的 自身转运蛋白，一类穿过外膜到达细胞外空间的蛋白质， 作为毒力因子，如粘附素、蛋白酶和其它有害因子。自动运输机由一个 转运域，它仍然在膜上，和乘客域，它分泌穿过膜。 膜的另一侧，即使不使用化学能，例如，ATP以这些自动转运者为目标 因为抑制代表了控制感染同时限制抗性发展的有希望的手段。 然而，首先，研究自身转运蛋白的折叠、分泌和表达的分子机制 超越细胞表面的能力是非常需要的。该项目将通过三个具体目标满足这一需要。在 第一个目标，如何乘客域折叠将被表征，回答为什么折叠在体内是有序的 比体外培养快得多第二个目标集中在乘客结构域的分泌， 膜通过一个混合β桶的转运域与BamA，蛋白质负责其 膜插入将确定通过组合桶的路径，以及 外膜在突起上。在第三个目标中，另一类自身转运蛋白，双体分泌， 系统，将被建模，目标是确定它们之间的共性和差异， 班这个项目所使用的主要方法工具是原子尺度的分子动力学（MD） 模拟这些模拟都将在真实的环境中进行，包括一个精确的模型， 不对称革兰氏阴性外膜。还将使用多种创新方法，包括深度 用于对折叠过程进行建模的学习、用于提取动力学信息的马尔可夫状态建模以及粗- 用于观察自发分泌的颗粒布朗动力学。与多个实验室密切合作 实验室将为MD模拟结果提供关键输入和验证。

Project Summary/Abstract Pathogenic Gram-negative bacteria are collectively responsible for over 5 million deaths annually. A number of species also exhibit high levels of antibiotic resistance, comprising nine out of twelve members on the World Health Organization’s list of priority pathogens. Gram-negative bacterial infection is often mediated by so-called autotransporters, a class of proteins that cross the outer membrane to the extracellular space where they act as virulence factors, such as adhesins, proteases, and other harmful agents. Autotransporters consist of a translocator domain, which remains in the membrane, and a passenger domain, which secretes across the membrane to the other side, even without the use chemical energy, e.g., ATP. Targeting these autotransporters for inhibition represents a promising means of controlling infection while limiting the development of resistance. However, first, research into the molecular mechanisms of autotransporter folding, secretion, and expression beyond the cell surface is critically needed. This project will meet that need through three specific aims. In the first aim, how the passenger domain folds will be characterized, answering why folding in vivo is orders of magnitude faster than in vitro. The second aim focuses on the secretion of the passenger domain across the membrane through a hybrid-β-barrel of the translocator domain with BamA, the protein responsible for its membrane insertion. The pathway through the combined barrels will be determined, as well as the influence of the outer membrane on the process. In the third aim, another class of autotransporters, two-partner secretion systems, will be modeled, with a goal of identifying both commonalities and differences between them and other classes. The primary methodological tool to be used for this project is atomic-scale molecular dynamics (MD) simulations. These simulations will all be carried out in realistic environments, including an accurate model of the asymmetric Gram-negative outer membrane. Multiple innovative approaches will also be used, including deep learning for modeling the folding process, Markov state modeling for extracting kinetics information, and coarse- grained Brownian dynamics for observing spontaneous secretion. Close collaboration with multiple experimental labs will provide key inputs to and validation of the MD simulation results.