Mass spectrometry excels as a powerful technique to identify, quantify, and elucidate chemical substances. It is notable for its accuracy and sensitivity, and as a result, new applications and advances constantly pour forth. Recently launched innovative hardware and software for use in the life sciences were discussed at the “Pittcon” meeting held in Chicago.
“Accuracy of mass spectrometry can be divided into must-have versus nice-to-have situations,” according to John Yates, Ph.D., principal investigator, Scripps Research Institute. Dr. Yates discussed examples of both categories of investigation. For example, in database searching, if the precursor ion mass is known with high accuracy, the speed of the search is increased, resulting in fewer candidate peptides that need to be tracked down. Peptide validation, in which the precursor ion mass accuracy can be used to filter and validate peptide identification is another situation, helpful but not absolutely necessary, for the success of the investigation.
Dr. Yates contrasted these investigations with ones that place a higher demand on the technology. For example, post-translational modifications represent “must-have high mass accuracy” situations in which validation of large mass and dealing with ambiguous and unanticipated post-translational modifications are more exacting. Other high accuracy tasks include quantitative proteomics and peptide mass fingerprinting.
As a case study, Dr. Yates and his coworkers considered arginylation analysis as an example of ambiguous post-translational modifications. Since many different residues and modifications can have similar molecular weights, it is necessary to have accurate measurements in order to avoid confounding one type of sequence modification with another.
According to Dr. Yates, highly accurate data is also of importance in identifying unanticipated and unknown modifications in a database search. These may include chemical modifications introduced during sample preparation, poor quality spectra, the presence of low-abundance peptides, and sequences not in the database. The team took advantage of BlindP™, a database search engine designed to find unanticipated or unknown post-translational modifications. This search engine does not require users to list potential post-translational modifications, but it does require high mass accuracy precursor mass information.
Dr. Yates covered quantitative proteomics as a second example of an area requiring extremely accurate MS data, including a case study of the arginine-to-proline conversion in SILAC (stable isotope labeling with amino acids in cell culture). This method detects differences in protein abundance between samples, and has proven to be useful in quantitative proteomics.
Dr. Yates and his coworkers determined that, despite the power of the SILAC methodology, the ratio of light and heavy peptides can be incorrectly calculated due to the insertion of heavy isotope labels into proline through arginine catabolism. But high-resolution mass spectrometers can distinguish isotopes of converted heavy proline clusters from the heavy arginine clusters.
Finally, Dr. Yates discussed the applications of high-resolution mass spectrometry to peptide identification using a unique mass identifier, accurate mass tag, and peptide mass fingerprinting.