A comprehensive Candida albicans Peptide Atlas build enables deep proteome coverage

To provide new and expanded proteome documentation of the opportunistically pathogen Candida albicans, we have developed new protein extraction and analysis routines to provide a new, extended and enhanced version of the C. albicans PeptideAtlas. Two new datasets, resulting from experiments consisting of exhaustive subcellular fractionations and different growing conditions, plus two additional datasets from previous experiments on the surface and the secreted proteomes, have been incorporated to increase the coverage of the proteome. High resolution precursor mass spectrometry (MS) and ion trap tandem MS spectra were analyzed with three different search engines using a database containing allele-specific sequences. This approach, novel for a large-scale C. albicans proteomics project, was combined with the post-processing and filtering implemented in the Trans Proteomic Pipeline consistently used in the PeptideAtlas project and resulted in 49,372 additional peptides (3-fold increase) and 1630 more proteins (1.6-fold increase) identified in the new C. albicans PeptideAtlas with respect to the previous build. A total of 71,310 peptides and 4174 canonical (minimal non-redundant set) proteins (4115 if one protein per pair of alleles is considered) were identified representing 66% of the 6218 proteins in the predicted proteome. This makes the new PeptideAtlas build the most comprehensive C. albicans proteomics resource available and the only large-scale one with detections of individual alleles.This work has been financially supported in part by project BIO2012-31767Ministerio de Economía y Competitividad, Spain, PROPMT (S2010/BMD-2414) from the Comunidad Autónoma de Madrid, REIPI, Spanish Network for the Research in Infectious Diseases (RD12/0015/0004), and PRB2 projects PT13/0001/0004 and PT13/0001/0008 from the ISCIII. VV held a research contract associated to project BIO2012-31767. These results are lined up with the Spanish Initiative on the Human Proteome Project (B/D-HPP). This work was funded in part by the American Recovery and Reinvestment Act (ARRA) funds through National Institutes of Health from the NHGRI grant RC2HG005805, the NIGMS grants R01GM087221 and 2P50GM076547 to the Center for Systems Biology, the National Institute of Biomedical Imaging and Bioengineering grant U54EB020406, the National Science Foundation MRI grant 0923536, and the EU FP7 ‘ProteomeXchange’ grant 260558.Peer Reviewe