Proteomics and genomics projects have yielded a detailed inventory of proteins in a cell. However, little is known about how these proteins are spatially and temporally arranged within the cell. Such knowledge is essential to understanding how proteins contribute to the structure and function of a living cell. Just as words must be assembled into sentences, paragraphs, and chapters to make sense, vital cellular functions are performed by structured assemblies (or complexes) of proteins rather than individual molecules. Often, these complexes comprise tens or hundreds of proteins. This proposal describes a set of computational methods that will exploit and integrate several kinds of emerging experimental data to uncover the structure and dynamics of protein complexes, toward the ultimate goal of achieving a mechanistic understanding of the cell. In particular, we will characterize proteome organization on three levels through the following projects. (1) We will develop an efficient computational method to determine the structure of individual protein complexes by simultaneously fitting multiple components to cryo-electron microscopy maps. (2) We will develop advanced pattern mining methods to discover and localize unknown protein complexes in whole-cell cryoelectron tomograms - a prerequisite towards comprehensive visual proteomics. (3) We will develop simulation methods to study the systems dynamics of protein interaction networks on biologically relevant time scales and within realistic cellular environments. With these tools, we are poised to model the spatial and temporal organizations of proteome. We will freely provide software packages and source code for all methods to the scientific community.

Public Health Relevance

(Public Health Relevance) Detailed knowledge concerning the spatial and temporal organization of the proteome is essential to understanding how proteins perform their functions in a cell. Proteins need to appear in exactly in the right places at exactly the right times in order to accomplish their roles. Any discrepancies may lead to diseases. In fact, many diseases are known to be caused by malfunctions in proteins or protein interactions. Our proposed methods will significantly contribute to knowledge in this area, so are highly relevant to public health.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM096089-02
Application #
8337795
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Wehrle, Janna P
Project Start
2011-09-30
Project End
2016-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
2
Fiscal Year
2012
Total Cost
$310,688
Indirect Cost
$92,416
Name
University of Southern California
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
Singla, Jitin; McClary, Kyle M; White, Kate L et al. (2018) Opportunities and Challenges in Building a Spatiotemporal Multi-scale Model of the Human Pancreatic ? Cell. Cell 173:11-19
Joseph, Agnel Praveen; Polles, Guido; Alber, Frank et al. (2017) Integrative modelling of cellular assemblies. Curr Opin Struct Biol 46:102-109
Frazier, Zachary; Xu, Min; Alber, Frank (2017) TomoMiner and TomoMinerCloud: A Software Platform for Large-Scale Subtomogram Structural Analysis. Structure 25:951-961.e2
Pei, Long; Xu, Min; Frazier, Zachary et al. (2016) Simulating cryo electron tomograms of crowded cell cytoplasm for assessment of automated particle picking. BMC Bioinformatics 17:405
Tjong, Harianto; Li, Wenyuan; Kalhor, Reza et al. (2016) Population-based 3D genome structure analysis reveals driving forces in spatial genome organization. Proc Natl Acad Sci U S A 113:E1663-72
Pandurangan, Arun Prasad; Vasishtan, Daven; Alber, Frank et al. (2015) ?-TEMPy: Simultaneous Fitting of Components in 3D-EM Maps of Their Assembly Using a Genetic Algorithm. Structure 23:2365-2376
Xu, Min; Alber, Frank (2013) Automated target segmentation and real space fast alignment methods for high-throughput classification and averaging of crowded cryo-electron subtomograms. Bioinformatics 29:i274-82
Thalassinos, Konstantinos; Pandurangan, Arun Prasad; Xu, Min et al. (2013) Conformational States of macromolecular assemblies explored by integrative structure calculation. Structure 21:1500-8
Xu, Min; Alber, Frank (2012) High precision alignment of cryo-electron subtomograms through gradient-based parallel optimization. BMC Syst Biol 6 Suppl 1:S18
Zhou, Xianghong Jasmine; Alber, Frank (2012) Zooming in on genome organization. Nat Methods 9:961-3

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