New approaches for high throughput identification and characterization of protein complexes
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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.

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New approaches for high throughput identification and characterization of protein complexes

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

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/


Goal 1 includes three main steps

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


Impact of goal 1

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


Identification and characterization of protein machines

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


Strategy to achieve goal 1

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


New approaches for high throughput identification and characterization of protein complexes

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


An approach for high throughput identification of protein complexes

I

Choose

Identify genes

of

interest

Cell Types

Clone & Tag genes

Cells

Modified Cells

In vitro translation

II

Grow cells under

specific conditions

III

Disrupt & fractionate cells

Make

scFv

Cell prep

Cross

-

link

Use bait

Use as bait

Isolate

Isolate

Isolate

V

Experiments

IV

Analyze

Analyze

Data structure

(Gels)

(LCMS, MS/MS)

Bioinformatics

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


Native expression

Mass Spec Analysis

Bottom-Up Analysis

Top-Down Analysis

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


Heterologous expression

Select Gene

Clone gene

Make scFv

Analyze (gel)

Pull down

Heterologous Expression

Antigen with scFv

Express & Purify

Protein complex

Antigen

MS

Analysis


Ms for protein identification

“Bottom-Up”

“Top-Down”

Protein

ID

Peptide Mass Map

(molecular weights)

Partial aa

sequence

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

AMT’s

DB

DB=database search


Microfluidic devices

(-) high voltage

emulsifier

waste

cells

lysis + injection

separation

channel

(+) high voltage

Microfluidic Devices

J.M. Ramsey, et al

Note: arrows depict direction of flow.


Molecular and cellular imaging

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,

    bindingforces


Other analytical techniques

Other analytical techniques

  • Neutron scattering

  • X-ray scattering

  • Data from high resolution structural techniques

  • others


Computational tools support all aspects of center

protein sample

preparations

Data from Center,

other labs, etc.

protein complex

data depository

MS, imaging, other

analytical tools

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


New approaches for high throughput identification and characterization of protein complexes

dynamics,

biophysical

validation

archival

data mining

crosslinking

single cell

Molec.

Tools

Sample

Prep

Analysis

Data &

Models

Test

System

Resource

For High

Throughput

Complex

ID

improved

affinity

reagents

dynamic

range,

sensitivity

automation,

fluidics

interactions,

protein

networks


New approaches for high throughput identification and characterization of protein complexes

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 teams—biologists, chemists, computational scientists


Acknowledgements

Acknowledgements

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


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