New Approaches for High-Throughput Identification and Characterization of Protein Complexes

1
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

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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/
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Goal 1 includes three main steps

• Identify complement of protein complexes and
  their components

• 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

which lay the foundation for GTL
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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

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Identification and Characterization of Protein
Machines

• 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

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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

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Center for Molecular and Cellular Systems

• 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

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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

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Native Expression
Choose Gene and Growth Conditions
Data Analysis
Peptide Spectra
Pull-down Protein Complex
Engineer Tagged Protein
Whole Protein Spectra
Transfected Cells
Grow Cells Under Specific Conditions
Fractionate Cells
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Heterologous Expression
Antigen with scFv
Express Purify
Protein complex
Antigen
MS Analysis
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MS for Protein Identification
Protein(s) (gel spot, or complex,
or mixture, )
FTMS
Intact Molecular Weight
DB
digestion
DB
MS
Peptide mixture
DB
LC-MS-MS
LC-(FT)MS
AMTs
DB
DBdatabase search
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Microfluidic Devices
J.M. Ramsey, et al
Note arrows depict direction of flow.
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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
  imagingoptical probes, molecular recognition
  force
• microscopy, afm/optical, (optical)n
• Determine the location of specific complexes at
  cellular/subcellular
• locations
• Characterize dynamics,
• binding forces

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Other analytical techniques

• Neutron scattering
• X-ray scattering
• Data from high resolution structural techniques
• others

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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
data storage, management, analysis and
transmission
sample tracking system
library information management system
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dynamics, biophysical
validation archival data mining
crosslinking
single cell
Molec. Tools
Sample Prep
Data Models
Analysis
Test System
Resource For High Throughput Complex ID
improved affinity reagents
dynamic range, sensitivity
automation, fluidics
interactions, protein networks
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Identification and Characterization of Protein
Machines

• New approaches needed for large-scale studies,
  both analytical and computational
• Multiple tools required for full characterization
• Requires multidisciplinary teamsbiologists,
  chemists, computational scientists

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Acknowledgements

• Research sponsored by Office of Biological and
  Environmental Research, U.S. Department of Energy.