PNNL

Abstract

We have developed a hybrid method for identifying peptides from global proteomics studies that significantly increases sensitivity and specificity in matching peptides to tandem mass spectra using database searches. The method increased the number of spectra that can be assigned to a peptide in a global proteomics study by 57-147% at an estimated false discovery rate of 5%, with clear room for even greater improvements. The approach combines the general utility of using consensus model spectra typical of database search methods1-3 with the accuracy of the intensity information contained in spectral libraries4-6. This hybrid approach is made possible by recent developments that elucidated the statistical framework common to both data analysis and statistical thermodynamics, resulting in a chemically inspired approach to incorporating fragment intensity information into both database searches and spectral library searches. We applied this approach to proteomics analysis of Synechococcus sp. PCC 7002, a cyanobacterium that is a model organism for studies of photosynthetic carbon fixation and biofuels development. The increased specificity and sensitivity of this approach allowed us to identify many more peptides involved in the processes important for photoautotrophic growth.