Protein abundance levels are controlled through regulatory processes that govern protein synthesis and degradation. Although translational control is now a widely appreciated mechanism for regulating gene expression and proteome remodeling, a systems-level relationship between translational regulation and cellular physiology remains largely unexplored. The overarching objective of this project is to discover the mechanisms that lead to alterations in proteome flux and predict their responses to dynamic changes in the environment. This objective will be pursued through three aims. First, we will investigate how the availability of key components of the translational apparatus, such as ribosomes, tRNAs and initiation factors, are balanced with the transcriptome and proteome composition depending on a specific static carbon source. This will allow us to develop detailed mathematical models that link global translation, transcription and cell physiology. The predictions of the models can be tested by artificially perturbing the transcription-translation balance. Second, we will study the global feedback mechanisms by which the cell adapts its translational capacity to shifts in the carbon source experimentally, while in parallel extending our mathematical models to integrate the regulatory mechanisms linking carbon source and growth rate with a systems-view of the translation system. We will investigate, using experiments and mathematical models, how differences in the adaptation time of the various components of the translational machinery, proteome and mRNA composition to a fluctuating carbon source affect the cell's translational capacity, and hence, how the cell's global feedback mechanisms respond to dynamic and stochastic changes in the carbon source. Finally, we will build a quantitative mathematical model of proteome flux using a combination of quantitative proteomics and mathematical modeling. We will quantify key parameters of proteome flux including protein translation rate, protein degradation rate, mRNA abundance, and protein abundance. This will be done in both rapidly cycling cells and non-dividing neurons to determine how proteome flux is re-wired in post-mitotic cells. We will use serum starvation as a means to limit nutrients and measure alterations in proteome flux upon nutrient withdrawal and replenishment. We will also investigate dynamics in proteome flux upon mTOR inhibition as a pharmacological means to mimic nutrient deprivation. This will allow for deterministic modeling of how proteome resource allocation is altered, in two divergent cell types, upon nutrient limitation.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center (P50)
Project #
5P50GM085764-09
Application #
9520171
Study Section
Special Emphasis Panel (ZGM1)
Project Start
2010-09-18
Project End
Budget Start
2018-06-01
Budget End
2019-05-31
Support Year
9
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Type
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Antonova-Koch, Yevgeniya; Meister, Stephan; Abraham, Matthew et al. (2018) Open-source discovery of chemical leads for next-generation chemoprotective antimalarials. Science 362:
Zarrinpar, Amir; Chaix, Amandine; Xu, Zhenjiang Z et al. (2018) Antibiotic-induced microbiome depletion alters metabolic homeostasis by affecting gut signaling and colonic metabolism. Nat Commun 9:2872
Cowell, Annie N; Istvan, Eva S; Lukens, Amanda K et al. (2018) Mapping the malaria parasite druggable genome by using in vitro evolution and chemogenomics. Science 359:191-199
Hoeksema, Marten A; Glass, Christopher K (2018) Nature and nurture of tissue-specific macrophage phenotypes. Atherosclerosis :
Preissl, Sebastian; Fang, Rongxin; Huang, Hui et al. (2018) Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation. Nat Neurosci 21:432-439
Cowell, Annie N; Valdivia, Hugo O; Bishop, Danett K et al. (2018) Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing. Genome Med 10:52
Link, Verena M; Duttke, Sascha H; Chun, Hyun B et al. (2018) Analysis of Genetically Diverse Macrophages Reveals Local and Domain-wide Mechanisms that Control Transcription Factor Binding and Function. Cell 173:1796-1809.e17
Zhang, Wei; Ma, Jianzhu; Ideker, Trey (2018) Classifying tumors by supervised network propagation. Bioinformatics 34:i484-i493
Xiong, Liyang; Cooper, Robert; Tsimring, Lev S (2018) Coexistence and Pattern Formation in Bacterial Mixtures with Contact-Dependent Killing. Biophys J 114:1741-1750
Cooper, Robert; Tsimring, Lev; Hasty, Jeff (2018) Microfluidics-Based Analysis of Contact-dependent Bacterial Interactions. Bio Protoc 8:

Showing the most recent 10 out of 207 publications