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

限氧和缓慢生长条件下细菌蛋白质组组成的定量

• 批准号: 10426100
• 负责人: Mohammad Farshad Abdollah Nia
• 金额: $ 6.98万
• 依托单位: SCRIPPS RESEARCH INSTITUTE, THE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-15 至 2023-06-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10426100
• 关键词: Aerobic; Anaerobic Bacteria; Antibiotics; Bacteria; Bacterial Infections; Bacterial Physiology; Biology; Carbon; Cell Respiration; Cell physiology; Cells; Collaborations; Communicable Diseases; Complex; Cost efficiency; Data; Dependence; Development; Disease; Doctor of Philosophy; Environment; Escherichia coli; Exhibits; Face; Fermentation; Food Supply; Future; Generations; Goals; Grain; Growth; Habitats; Health; Intestines; Kinetics; Laboratories; Learning; Mass Spectrum Analysis; Measurement; Measures; Metabolism; Microbial Biofilms; Modeling; Nitrogen; Nutrient; Outcome; Outcomes Research; Oxygen; Performance; Physiological; Production; Proteins; Proteome; Proteomics; RNA Interference; Reporting; Research; Resource Allocation; Ribosomes; Stimulus; Stress; Systems Biology; Techniques; Testing; Therapeutic; Time; Training; Work; base; cell growth; cost; experience; experimental study; innovation; insight; interest; pathogenic Escherichia coli; response

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.

穆罕默德·法沙德·阿卜杜拉·尼亚博士 限氧和缓慢生长条件下细菌蛋白质组组成的定量 项目概要： 在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 和氧气可用性，并受到各种其他挑战，例如 pH、渗透压和抗生素 这些条件限制了细菌的生长速度，并且细胞必须承受大量的压力。 为了适应和维持竞争性生长而发生的生理变化是系统生物学的中心目标。 了解细胞生理学如何响应此类环境刺激进行调节。 蛋白质组的测量可以对细胞的生理状态进行全面的估计 我们使用质谱法对大肠杆菌进行全蛋白质组测量。 了解细菌细胞如何在限制条件下保持最佳生长。 检查了在完全有氧条件下碳、氮和抗生素诱导的核糖体限制。 证明大肠杆菌蛋白质组分为粗粒度部分，每个部分的总质量 丰度与增长率呈现正或负线性关系，这导致了粗粒度。 该模型揭示了细胞蛋白质组经济中资源分配的基本原理。 目前的粗粒度蛋白质组部门模型没有在微氧条件下和在 生长速度缓慢（> 2 小时倍增时间），这是肠道和细菌内与疾病相关的条件 我们最近开发了在受控厌氧和条件下培养大肠杆菌的技术能力。 我们捕捉到了恒化器中微氧条件下生长速度较慢的情况。 新陈代谢代替有氧发酵呼吸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以及新蛋白质组的出现 对氧气供应的反应类型尚未研究的依赖氧气的部门 该提案的首要目标是。 表征微需氧和厌氧条件下已知的蛋白质组部分，并比较 具有有氧结果的模型参数的第二个目标是确定新的氧气依赖部分和 我们的初步数据表明，通过扩展的建模方法来表征它们对氧气的反应。 新的依赖氧的部分表现出对氧气的高度非线性响应，因此是一个动力学版本 需要开发粗粒度模型，通过这些研究，我们将扩展预测和分析。 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- 该培训将与斯克里普斯研究中心的威廉姆森实验室合作进行。 加州大学圣地亚哥分校的 Hwa 实验室培训将增强申请人在定量细菌方面的经验。 生理学、质谱和生物学实验室技术。