Shotgun proteome analysis based on multidimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS) provides a powerful tool for global characterization of proteomes. We use shotgun analyses on a standardized platform to compare proteome differences corresponding to disease phenotypes, molecular characteristics (e.g., mutations) and responses to stimuli (e.g., drugs, toxicants). We have developed standardized workflows for shotgun proteomics to ensure the consistency of results and improve our ability to make meaningful comparisons.
We first digest tissue or biofluid specimens to tryptic peptides and then fractionate peptides by basic reverse phase HPLC (bRPLC). The peptides concatenated bRPLC fractions are then analyzed by reverse phase liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). The objective of the analysis is to generate a collection of MS/MS spectra from as many of the peptides in the sample as possible. Each MS/MS spectrum encodes the sequence of a peptide; these sequences are determined by searching the spectra against a database of sequences corresponding to all known human proteins. The resulting collection of identified peptide sequences is then assembled into an inventory of proteins that can account for the identified peptides.
Because the likelihood of collecting an MS/MS spectrum of a peptide increases with the amount of the peptide in a sample, the numbers of MS/MS spectra that map to each protein provide a number proportional to the amount of each protein in the sample.
Comparisons of the MS/MS datasets and spectral count data for tissue specimens (e.g., normal vs. cancer) thus identifies features of proteomes that distinguish one tissue type from another. This approach compares favorably to isotope-labeling approaches (SILAC, iTRAQ), but avoids the expense of labeling reagents and the requirement for paired (or multiplexed) sample comparisons to a reference standard. Each sample dataset stands on its own and can be directly compared to other datasets collected in different studies. We have applied this shotgun analysis platform to cells, tissues, biofluids and archival formalin-fixed, paraffin-embedded (FFPE) tissues. These shotgun analyses can detect phenotype-specific differences in proteomes (e.g., cancer vs. normal), as well as differences due to single gene mutation events. Combination of shotgun proteomics with new bioinformatics tools also identifies variant peptide sequences associated with cancer-related mutations.
Representative references from our work and collaborations
Slebos, R. J., Brock, J. W., Winters, N. F., Stuart, S. R., Martinez, M. A., Li, M., Chambers, M. C., Zimmerman, L. J., Ham, A. J., Tabb, D. L., and Liebler, D. C. (2008) Evaluation of strong cation exchange versus isoelectric focusing of peptides for multidimensional liquid chromatography-tandem mass spectrometry. J. Proteome Res., 7, 5286-5294. PubMed
Sprung, R. W., Jr., Brock, J. W., Tanksley, J. P., Li, M., Washington, M. K., Slebos, R. J., and Liebler, D. C. (2009) Equivalence of protein inventories obtained from formalin-fixed paraffin-embedded and frozen tissue in multidimensional liquid chromatography-tandem mass spectrometry shotgun proteomic analysis. Mol Cell Proteomics, 8, 1988-1998. PubMed
Halvey, P. J., Zhang, B., Coffey, R., Liebler, D. C., and Slebos, R. J. (2011) Proteomic Consequences of a Single Gene Mutation in a Colorectal Cancer Model. J. Proteome Res., 11, 1184-1195. PubMed
Li, J., Su, Z., Ma, Z. Q., Slebos, R. J., Halvey, P., Tabb, D. L., Liebler, D. C., Pao, W., and Zhang, B. (2011) A bioinformatics workflow for variant peptide detection in shotgun proteomics. Mol Cell Proteomics, 10, M110 006536. PubMed
Wang, X., Slebos, R. J., Wang, D., Halvey, P. J., Tabb, D. L., Liebler, D. C., and Zhang, B. (2011) Protein identification using customized protein sequence databases derived from RNA-Seq data. J. Proteome Res., 11, 1009-1017. PubMed