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High Throughput Proteomics

The PNNL proteome measurement strategy consists of two approaches that in combination allow higher-throughput measurements well suited to a number of applications. The first approach is the more conventional, involving capillary LC-MS/MS measurements of trypsin-digested proteomes to provide "shotgun" protein identification. We have refined the approach to provide greater depth of coverage, while also generating an effective reference map or "lookup table" of peptides identified from extensive automated LC(/LC)-MS/MS analyses for the specific sample type (generally a microbe cultured under one or more conditions in the initial applications). The second approach involves the capability for high-throughput LC-MS studies that use these peptide markers in subsequent studies to identify peptides/proteins on the basis of their characteristic accurate masses and LC separation elution times.

FTICR Mass Spectrometer

Automated Sample Processing

Developments in this area are associated with automated processing for consistent, high-throughput manipulation of very small samples (less than or equal to 1 µg), emphasizing methods for isolating protein complexes. Technologies in development include:

  • High-throughput methods for rapid generation of single-chain antibodies for isolation and validation of specific protein complexes.
  • Methods based on automated sample processing of proteome samples and affinity-isolated protein complexes to enable much more effective characterization.

Methods, Instrumentation, and Techniques for Proteome Analyses

We are addressing the need to improve the dynamic range, sensitivity, and quality and reproducibility of proteomic analyses. Advancements enable high-precision proteome measurements as well as global absolute abundance measurements. Technologies in development include:

Advanced MS instrumentation
  • Improved separation methods to increase the comprehensiveness and throughput of proteome analyses and to address the complexity of mammalian proteomes.
  • Sub-attomole sensitivity, a dynamic range of more than six orders of magnitude, and high-throughput broad proteome analyses based on Fourier transform ion cyclotron resonance (FTICR) mass spectrometry, using the accurate mass and time (AMT) tag approach introduced by PNNL.
  • Improved methods for both relative quantitation (e.g., using stable-isotope labeling methods) and absolute quantitation of protein abundance with statistical measures of quality for each analysis.
  • Sensitive, high-throughput data-directed MS/MS to identify targeted proteins based on relative (e.g., using stable-isotope labeling) or absolute abundance changes.
  • An extension of the AMT tag concept to allow broad proteome studies at the intact protein level using capillary isoelectric-focusing FTICR mass spectrometry, and the capability to combine information from peptide-level analyses to improve identification and quantification of protein modifications.

Tools and Methods for Data Analysis

Data analysis

Developments in the related and equally important area of data quality include an approach that will provide a comprehensive statistical evaluation of proteomic data quality that provides a firm foundation for subsequent use of these data. Technologies in development include:

  • Approaches and software tools to aid quantitation, validation, and statistical evaluation of proteome analyses.
  • New approaches using separations information (e.g., liquid chromatography elution times) to improve protein identifications.
  • Development of software tools for integrating peptide-level and intact protein-level analyses and improved characterization of modified proteins.
  • Methods for the analysis and interpretation of proteomic data in conjunction with transcriptome-level expression microarray data.
  • Development of an integrated computational infrastructure that enables researchers to access and use large, heterogeneous data sets and analysis tools.
  • Integration of bioinformatic tools to aid interpretation, the extraction of biological understanding, and the development of hypotheses from proteomic analyses.

BER-PNNL Proteomics