The ultimate goal of proteomics is determination of the functions of genes from analysis of the proteome and its response to perturbations. Inferences about gene and pathway function can be obtained using a broad range of proteomics technologies, from classical protein expression profiling to yeast two-hybrid methodologies and high-throughput analysis of protein complexes. One of the most useful conceptual approaches in proteomics is to elucidate pathways and identify control points in those pathways. This can be achieved by combining data from current and emerging proteomics technologies to establish functional linkages between proteins, for example, by determining direct interactions, genetic interactions, and coordinate expression profiles. This proposal describes technologies that allow improvements in proteome mapping, methods to query changes in signal transduction, identification of protein interactions, and improved algorithms and computational tools for analyzing proteomics data. Altogether, they represent an integrated approach to identifying and building maps of cell pathways. Specific new technology areas addressed include: phosphoproteomics, high-throughput isolation of protein complexes, high-throughput yeast two-hybrid technologies, virtual 2D gels, protein microarrays, and collision-induced-dissociation of proteins. Mechanisms are proposed to provide dissemination of results, provide training opportunities, and ensure that technology development is responsive to the needs of investigators. One of the strengths of this proposal is its potential to leverage the substantial investment in proteomics infrastructure made by the State of Michigan and to extend the benefits of this investment to investigators outside Michigan.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR018627-04
Application #
7118617
Study Section
Special Emphasis Panel (ZRG1-BECM (40))
Program Officer
Sheeley, Douglas
Project Start
2003-09-30
Project End
2008-07-31
Budget Start
2006-08-01
Budget End
2007-07-31
Support Year
4
Fiscal Year
2006
Total Cost
$2,336,405
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biochemistry
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Hagen, Susan E; Liu, Kun; Jin, Yafei et al. (2018) Synthesis of CID-cleavable protein crosslinking agents containing quaternary amines for structural mass spectrometry. Org Biomol Chem 16:8245-8248
Zhang, Chunchao; Gao, Shan; Molascon, Anthony J et al. (2014) Quantitative proteomics reveals histone modifications in crosstalk with H3 lysine 27 methylation. Mol Cell Proteomics 13:749-59
Pai, Dave A; Kaplan, Craig D; Kweon, Hye Kyong et al. (2014) RNAs nonspecifically inhibit RNA polymerase II by preventing binding to the DNA template. RNA 20:644-55
Zhang, Chunchao; Gao, Shan; Molascon, Anthony J et al. (2014) Bioinformatic and proteomic analysis of bulk histones reveals PTM crosstalk and chromatin features. J Proteome Res 13:3330-7
Johnson, Cole; Kweon, Hye Kyong; Sheidy, Daniel et al. (2014) The yeast Sks1p kinase signaling network regulates pseudohyphal growth and glucose response. PLoS Genet 10:e1004183
Zhang, Yan; Kweon, Hye Kyong; Shively, Christian et al. (2013) Towards systematic discovery of signaling networks in budding yeast filamentous growth stress response using interventional phosphorylation data. PLoS Comput Biol 9:e1003077
Simon, E S; Papoulias, P G; Andrews, P C (2013) Selective collision-induced fragmentation of ortho-hydroxybenzyl-aminated lysyl-containing tryptic peptides. Rapid Commun Mass Spectrom 27:1619-30
Zhang, Chunchao; Molascon, Anthony J; Gao, Shan et al. (2013) Quantitative proteomics reveals that the specific methyltransferases Txr1p and Ezl2p differentially affect the mono-, di- and trimethylation states of histone H3 lysine 27 (H3K27). Mol Cell Proteomics 12:1678-88
Gao, Shan; Xiong, Jie; Zhang, Chunchao et al. (2013) Impaired replication elongation in Tetrahymena mutants deficient in histone H3 Lys 27 monomethylation. Genes Dev 27:1662-79
Zhang, Chunchao; Liu, Yifan; Andrews, Philip C (2013) Quantification of histone modifications using ยน?N metabolic labeling. Methods 61:236-43

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