The overall goal of this project is to characterize the composition and dynamics of the proteome of Escherichia coli using quantitative mass spectrometry, and to use those data to inform a coarse-grained proteome flux model that describes the physiological behavior of the bacterium in response to nutrient limitations. Bacteria experience a wide variety of environments, and are subject to both nutrient deprivation and unfavorable environments for growth. The synthesis of cellular proteins is the most energetically expensive aspect of cellular growth, and the synthesis of proteins in response to the environment is tightly controlled. We have observed that the proteome partitions itself into sectors that respond in concert in a linear way in response to limitations for carbon, amino acids, and antibiotic stress. The linear response as a function of growth rate can be captured in a coarse-grained proteome sector model that has a very small number of parameters. A major goal of this project is to extend this model to other limitations and stresses, including phosphorus, sulfur, oxygen, and iron limitation, and osmotic and pH stress. We have also performed pulse labeling experiments that reveal significant turnover of the proteome even under very slow protein synthesis conditions, and a second major goal is to extend the coarse-grained model to include the energetic cost of protein degradation. A third major goal will be to compare proteome changes during nutrient shifts to current theories for the dynamics of growth rate changes. This project is a comprehensive approach to characterize the macroeconomics of protein synthesis and proteome composition in bacteria that will serve as the basis for quantitative models of bacterial physiology under a wide variety of conditions. Understanding bacterial physiology is an important aspect of understanding how bacteria respond in the adverse context of infections or in their beneficial context as part of the microbiome.

Public Health Relevance

The goal of this project is to quantitatively characterize the amounts of all proteins, the proteome, in the bacterium Escherichia coli, under a wide variety of growth-limiting conditions that can be encountered in the environment. These data will be analyzed using simple economic theory that models the increased costs of protein synthesis in response to limitations. These data will provide a systems level understanding of bacterial physiology that will be helpful in understanding how bacteria respond to environmental stresses, such as those encountered during infections.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM118850-04
Application #
9688227
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Gaillard, Shawn R
Project Start
2016-06-13
Project End
2020-06-30
Budget Start
2019-04-01
Budget End
2020-06-30
Support Year
4
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Scripps Research Institute
Department
Type
DUNS #
781613492
City
La Jolla
State
CA
Country
United States
Zip Code
92037
Dai, Xiongfeng; Zhu, Manlu; Warren, Mya et al. (2018) Slowdown of Translational Elongation in Escherichia coli under Hyperosmotic Stress. MBio 9:
Basan, Markus; Hui, Sheng; Williamson, James R (2017) ArcA overexpression induces fermentation and results in enhanced growth rates of E. coli. Sci Rep 7:11866
Erickson, David W; Schink, Severin J; Patsalo, Vadim et al. (2017) A global resource allocation strategy governs growth transition kinetics of Escherichia coli. Nature 551:119-123
Dai, Xiongfeng; Zhu, Manlu; Warren, Mya et al. (2016) Reduction of translating ribosomes enables Escherichia coli to maintain elongation rates during slow growth. Nat Microbiol 2:16231