Quantitation of Bacterial Proteome Composition under Oxygen-limiting and Slow Growth Conditions

穆罕默德·法沙德·阿卜杜拉·尼亚，博士。 限氧慢速生长条件下细菌蛋白质组组成的定量研究 项目总结： 在它们的自然栖息地和传染病中，细菌细胞不断面临营养供应的限制。 和氧气的可获得性，并受到各种其他挑战，如pH，渗透和抗生素 压力。这些条件限制了细菌的生长速度，细胞必须经历大量的 为了适应和保持竞争性生长而发生的生理变化。这是系统生物学的中心目标。 以了解细胞生理学是如何对这种环境刺激作出反应的。量化 对蛋白质组的测量可以对细胞的生理状态进行全面的评估 感兴趣的条件。我们使用质谱仪在大肠杆菌中进行全蛋白质组测量 了解细菌细胞如何在有限的条件下保持最佳生长。我们实验室以前的工作 检查了完全好氧条件下碳、氮和抗生素诱导的核糖体限制。确实是 证明了大肠杆菌蛋白质组划分成粗粒度的扇区，每个扇区的总质量 丰度与增长率呈正或负的线性关系。这导致了粗粒度的 揭示了细胞蛋白质组经济中资源分配的基本原理的模型。然而， 目前的粗粒蛋白质组扇区模型不能在微氧条件下和在 生长缓慢(2小时倍增时间)，这是肠道和细菌内与疾病相关的状况 生物膜。我们最近开发了在受控厌氧条件下培养大肠杆菌的技术能力 恒化器中的微氧条件，可获得较慢的生长速度。我们假设，使用 发酵代谢而不是有氧呼吸将需要对大肠杆菌进行广泛的改造 蛋白质组，导致已知蛋白质组部分的不同特征，并出现新的 氧气依赖部门，对氧气供应的反应类型未被研究。这项提议的第一个目的是 在微氧和厌氧条件下对已知的蛋白质组区段进行表征，并比较 模型参数和有氧结果。第二个目标是确定新的氧气依赖部门和 用一种扩展的建模方法描述它们对氧气的反应。我们的初步数据表明 新的氧依赖扇区对氧表现出高度的非线性响应，因此是动力学版本的 需要开发粗粒度模型。通过这些研究，我们将扩大预测和 粗粒度蛋白质组模型的适用范围，以更好地了解疾病中的细菌生理学- 相关设置。这项培训将在斯克里普斯研究中心的威廉姆森实验室与 加州大学圣地亚哥分校的HWA实验室。培训将增强申请者在定量细菌方面的经验 生理学、质谱学和生物实验室技术。

Mohammed Farshad Abdollah Nia, Ph.D. Quantitation of Bacterial Proteome Composition under Oxygen-limiting and Slow Growth Conditions Project Summary: In their natural habitat and in infectious diseases, bacterial cells continually face limitations in nutrient supply and oxygen availability and are subject to a variety of other challenges such as pH, osmotic, and antibiotic stress. These conditions limit how fast the bacteria can grow, and the cells must undergo substantial physiological changes in order to adapt and maintain competitive growth. It is a central aim of systems biology to understand how cell physiology is modulated in response to such environmental stimuli. Quantitative measurements of the proteome can yield comprehensive estimates of the physiological state of the cell under the conditions of interest. We use mass spectrometry for whole-proteome measurements in Escherichia coli to learn how bacterial cells can maintain optimal growth under limiting conditions. Previous work from our lab examined carbon, nitrogen, and antibiotic-induced ribosome limitations under fully aerobic conditions. It was demonstrated that the E. coli proteome partitions into coarse-grained sectors, with each sector’s total mass abundance exhibiting positive or negative linear relations with the growth rate. This led to a coarse-grained model that revealed basic principles of resource allocation in proteome economy of the cell. However, the current coarse-grained proteome sector model was not characterized under microaerobic conditions and at slow growth rates (> 2 h doubling time) which are the disease-relevant conditions in the gut and within bacterial biofilms. We have recently developed technical capabilities to culture E. coli under controlled anaerobic and microaerobic conditions in chemostat with access to slower growth rates. We hypothesize that the use of fermentation metabolism instead of aerobic respiration will require extensive remodeling of the E. coli proteome, resulting in a different characterization of the known proteome sectors and the emergence of new oxygen-dependent sectors with unstudied types of response to oxygen supply. The first aim of this proposal is to characterize the known proteome sectors under microaerobic and anerobic conditions and to compare the model parameters with aerobic results. The second aim is to identify new oxygen-dependent sectors and characterize their response to oxygen with an extended modelling approach. Our preliminary data suggest that the new oxygen-dependent sectors exhibit highly nonlinear response to oxygen, thus a kinetic version of the coarse-grained model needs to be developed. Through these studies, we will expand the predictive and applicable scope of coarse-grained proteome models to better understand bacterial physiology in a disease- relevant setting. This training will take place in the Williamson lab at Scripps Research in collaboration with the Hwa lab at UC San Diego. The training will enhance the applicant’s experience in quantitative bacterial physiology, mass spectrometry, and biology laboratory techniques.