Proteomics refers to the analysis of the complete complement of proteins expressed in a given set of cells, biological fluids (e.g., plasma, urine, saliva), tissues and organs (e.g., brain slices, liver), or whole organisms. Proteins are extracted from these sources and are digested into peptides using enzymes. Because of the complexity of the peptide mixture, multiple dimensions of liquid chromatographic or other separation techniques are used to separate the peptides. The final liquid chromatography separation is coupled to mass spectrometry analysis, where the intact masses of peptides are measured as well as their corresponding gas-phase fragments. Using sophisticated database searching algorithms, the raw data is searched against species-specific databases to give the identification of proteins present in the mixture.
In order to adequately address problems about aging and disease using proteomics, high-throughput approaches are necessary. This is because investigating changes across many clinical samples, disease stages or aging timepoints, with treatment, or across tissues, etc. can take significant amounts of time. We are working to improve the throughput involved with quantitative proteomics methods with chemical tagging approaches. We have developed an enhanced multiplexing approach that combines precursor isotopic labeling and isobaric tagging (cPILOT) methods and frequently use different types of chemical labeling strategies in our application projects. Currently, we are working to 1) increase sample multiplexing capability for global peptide analysis and 2) develop selective quantitative methods for oxidative post-translational modifications such as 3-nitrotyrosine, protein carbonyls, and cysteine oxidation.
