The genomic revolution has been empowered by technologies that have determined a vast pool of genetic information. While nucleic acids encode this information, it is the proteins that act on it. Proteins are incredibly diverse in their abundance & their properties, making them highly versatile for the dynamic tasks at hand but at the same time exceptionally difficult to analyze. It is for these reasons that the proteomic revolution still lags behind the genomic revolution. Indeed, the comprehensive analysis of the dynamic properties of proteins in cells is still largely beyond current capabilities. Here, we seek to revolutionize proteomics by synergistically combining improvements in established techniques with new approaches. We will overcome major bottlenecks in 3 key areas of proteomics technology. First, we will reform the production stage for generating intact macromolecular complexes, so that we will be able to freeze a tagged macromolecular complex in place, within moments of visualizing its position in the cell, & then isolate it together with all its components & neighbors. Second, we will optimize the analysis of each complex such that its macromolecular composition, structure, & dynamics will be quantified & analyzed. Third, we will develop software to integrate our data & represent in unprecedented detail the actions of the macromolecular players in many dynamic subcellular assemblies. We will seek to make these techniques rapid, robust & routine by beta testing them in 4 experimental systems. These systems focus on aspects of the genetic information pathway, because (i) this is core to eukaryotes, & (ii) it will allow us to develop techniques to analyze the interactions of all 3 information-carrying biological macromolecules (DMA, RNA & proteins). First, we will walk along great stretches of chromatin, determining the normal flux of structural proteins & regulatory factors that together comprise dynamic segments of the genome. Second, we will follow the course of RNA after transcription, as it is processed, packaged & exported from the nucleus; we will enumerate the proteins that dance attendance on each kind of RNA molecule during its maturation. Finally, we will expose how 2 pathogenic human viruses, HIV & CMV, subvert their host's genetic information pathway & supplant it with their own. By creating a National Center for Dynamic Interactome Research, we will be coupling an established mass spectrometry resource, cell biology laboratories, a systems biology resource, & a computational biology center. As part of the larger NIH roadmap, the center's aim will be to create new & useful tools to elucidate the dynamics of macromolecular interactions. In summary, the present proposal seeks the support to advance our methods into totally new areas, & to spread these methods amongst the biomedical community. The Center will enable the community to assemble the kinds of detailed, dynamic representations of the interactions in the cell that will help elucidate the principles underlying all cellular processes, thus bridging the gaps between functional genomics, proteomics, & systems biology.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
3U54RR022220-04S1
Application #
7678658
Study Section
Special Emphasis Panel (ZRG1-BST-D (55))
Program Officer
Sheeley, Douglas
Project Start
2005-09-30
Project End
2009-07-31
Budget Start
2008-08-01
Budget End
2009-07-31
Support Year
4
Fiscal Year
2008
Total Cost
$253,361
Indirect Cost
Name
Rockefeller University
Department
Biology
Type
Other Domestic Higher Education
DUNS #
071037113
City
New York
State
NY
Country
United States
Zip Code
10065
Herricks, Thurston; Mast, Fred D; Li, Song et al. (2017) ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth. J Vis Exp :
Upla, Paula; Kim, Seung Joong; Sampathkumar, Parthasarathy et al. (2017) Molecular Architecture of the Major Membrane Ring Component of the Nuclear Pore Complex. Structure 25:434-445
Hayama, Ryo; Rout, Michael P; Fernandez-Martinez, Javier (2017) The nuclear pore complex core scaffold and permeability barrier: variations of a common theme. Curr Opin Cell Biol 46:110-118
Herricks, Thurston; Dilworth, David J; Mast, Fred D et al. (2017) One-Cell Doubling Evaluation by Living Arrays of Yeast, ODELAY! G3 (Bethesda) 7:279-288
Fernandez-Martinez, Javier; Kim, Seung Joong; Shi, Yi et al. (2016) Structure and Function of the Nuclear Pore Complex Cytoplasmic mRNA Export Platform. Cell 167:1215-1228.e25
Cimermancic, Peter; Weinkam, Patrick; Rettenmaier, T Justin et al. (2016) CryptoSite: Expanding the Druggable Proteome by Characterization and Prediction of Cryptic Binding Sites. J Mol Biol 428:709-719
Molnar, Kathleen S; Bonomi, Massimiliano; Pellarin, Riccardo et al. (2014) Cys-scanning disulfide crosslinking and bayesian modeling probe the transmembrane signaling mechanism of the histidine kinase, PhoQ. Structure 22:1239-1251
Bonomi, Massimiliano; Pellarin, Riccardo; Kim, Seung Joong et al. (2014) Determining protein complex structures based on a Bayesian model of in vivo Förster resonance energy transfer (FRET) data. Mol Cell Proteomics 13:2812-23
Carpp, Lindsay N; Rogers, Richard S; Moritz, Robert L et al. (2014) Quantitative proteomic analysis of host-virus interactions reveals a role for Golgi brefeldin A resistance factor 1 (GBF1) in dengue infection. Mol Cell Proteomics 13:2836-54
Zhong, Yu; Morris, Deanna H; Jin, Lin et al. (2014) Nrbf2 protein suppresses autophagy by modulating Atg14L protein-containing Beclin 1-Vps34 complex architecture and reducing intracellular phosphatidylinositol-3 phosphate levels. J Biol Chem 289:26021-37

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