New Approaches for High-Throughput Identification and Characterization of Protein Complexes Michelle V. Buchanan Oak Ridge National Laboratory NIH Workshop.
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New Approaches for High-Throughput Identification and Characterization of Protein Complexes Michelle V. Buchanan Oak Ridge National Laboratory NIH Workshop on Structural Proteomics of Biological Complexes April 8, 2003
Identification and Characterization of Protein Complexes is one of Four Goals of the GTL Program Goal 1: Identify the molecular machines of life Goal 2: Characterize gene regulatory networks Goal 3: Characterize the functional repertoire of natural microbial communities Goal 4: Develop computational capabilities to advance understanding of complex biological systems and predict their behavior http://DOEGenomesToLife.org/
Center for Molecular & Cellular Systems Goal 1 includes three main steps Identify complement of protein complexes and their components which lay the foundation for GTL Elucidate function and dynamics of complexes— intermediates, nature of interactions, cellular location, kinetics Establish how changes arising from environmental stress, development, etc., affect complex formation and function
Center for Molecular & Cellular Systems Impact of Goal 1 Molecular level understanding of protein complexes and, ultimately, networks Predict/change behavior of organism and community Predict function, biological pathways by homology Discover new functions
Center for Molecular & Cellular Systems New approaches needed for large-scale studies No single analytical tool will provide all required information Integrated computational tools Analyze, compare, predict, share data Quality assessment Guide experimental design and data collection Develop integrated approach to correlate identified complexes with data from gene expression, protein expression, imaging, and other methods Identification and Characterization of Protein Machines
Center for Molecular & Cellular Systems Strategy to Achieve Goal 1 Initiate protein complex identification using affinity separation combined with mass spectrometry and computational tools Evaluate new approaches for high-throughput identification Incorporate additional tools, data to characterize complexes Multiple, controlled sample growth conditions Define conditions for quality assurance
Deputy Directors Steve Wiley (PNNL), Frank Larimer (ORNL) Core Steven Kennel, Thomas Squire High Throughput Complex Processing Mike Ramsey, Karin Rodland Mass Spectrometry Greg Hurst, Richard Smith Molecular and Cellular Imaging Mitch Doktycz, Steve Colson Bioinformatics and Computing Ying Xu, David Dixon Ray Gesteland (U. Utah) mass spectrometry Carol Giometti (ANL) gel electrophoresis Mike Giddings (U. North Carolina) MS, compututation Malin Young (SNL) cross-linking Center for Molecular and Cellular Systems
Center for Molecular & Cellular Systems An Approach for High Throughput Identification of Protein Complexes Combine complex isolation, mass spectrometry and data analysis Bioinformatics Controlled cell growth Cloning, tagging Affinity isolation scFv Cross-linking Separation Mass spectrometry Data analysis, archival Identify genesofinterest Choose I Make scFv Experiments Bioinformatics Cells Grow cells under specific conditions Disrupt & fractionate cells Cell prep Cross-link Isolate Use bait Analyze (Gels) Analyze (LCMS, MS/MS) Isolate III IV Clone & Tag genes In vitro translation Use as bait Data structure Modified Cells Cell Types V II
Center for Molecular & Cellular Systems Choose Gene and Growth Conditions Engineer Tagged Protein Grow Cells Under Specific Conditions Fractionate Cells Pull-down Protein Complex Mass Spec Analysis Bottom- Up Analysis Top- Down Analysis Transfected Cells Data Analysis Whole Protein Spectra Peptide Spectra Native Expression
Center for Molecular & Cellular Systems Heterologous Expression Express & Purify Antigen Select Gene Clone geneMake scFv MS Analysis Pull down Analyze (gel) Antigen with scFv Protein complex
Center for Molecular & Cellular Systems MS for Protein Identification “Top-Down” “Bottom-Up” Protein(s) (gel spot, or complex, or mixture, …) FTMS Intact Molecular Weight digestion Peptide mixture Peptide Mass Map (molecular weights) MS LC-(FT)MS LC-MS-MS AMT’s Partial aa sequence Protein ID DB=database search DB
Center for Molecular & Cellular Systems Microfluidic Devices J.M. Ramsey, et al cells emulsifier waste separation channel (-) high voltage (+) high voltage lysis + injection Note: arrows depict direction of flow.
Center for Molecular & Cellular Systems Molecular and Cellular Imaging Validate the composition of protein complexes Characterize protein complexes in isolation, within cells, and on cell surfaces/interfaces Employ multimodality approaches to molecular imaging—optical probes, molecular recognition force microscopy, afm/optical, (optical) n Determine the location of specific complexes at cellular/subcellular locations Characterize dynamics, binding forces
Center for Molecular & Cellular Systems Other analytical techniques Neutron scattering X-ray scattering Data from high resolution structural techniques others
Center for Molecular & Cellular Systems Computational Tools Support All Aspects of Center sample tracking, work flow monitoring library information management data processing, storage, management, transmission data communication and technical support tools for predicting and validating members of protein complexes, structures, function, etc. Community support sample tracking system library information management system MS, imaging, other analytical tools protein sample preparations Data from Center, other labs, etc. protein complex data depository data storage, management, analysis and transmission
Center for Molecular & Cellular Systems Molec. Tools Sample Prep Data & Models Analysis Test System Resource For High Throughput Complex ID improved affinity reagents automation, fluidics dynamic range, sensitivity crosslinkingsingle cell dynamics, biophysical validation archival data mining interactions, protein networks
Center for Molecular & Cellular Systems New approaches needed for large- scale studies, both analytical and computational Multiple tools required for full characterization Requires multidisciplinary teams— biologists, chemists, computational scientists Identification and Characterization of Protein Machines
Center for Molecular & Cellular Systems Acknowledgements Research sponsored by Office of Biological and Environmental Research, U.S. Department of Energy.