A comprehensive Candida albicans PeptideAtlas 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.
Departamento de Microbiología II, Universidad Complutense Madrid (UCM), Spain; Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain.
Vital
V
Vialas
Institute for Systems Biology, 401, Terry Ave North, Seattle, WA 98109, USA.
Zhi
Z
Sun
Departamento de Microbiología II, Universidad Complutense Madrid (UCM), Spain; Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain.
Jose A
JA
Reales-Calderón
Unidad de Proteómica, Universidad Complutense de Madrid-Parque Científico de Madrid (UCM-PCM), Spain.
María L
ML
Hernáez
CSIC/UAB Proteomics Laboratory, IIBB-CSIC, IDIBAPS, Barcelona, Spain.
Vanessa
V
Casas
CSIC/UAB Proteomics Laboratory, IIBB-CSIC, IDIBAPS, Barcelona, Spain.
Montserrat
M
Carrascal
CSIC/UAB Proteomics Laboratory, IIBB-CSIC, IDIBAPS, Barcelona, Spain.
Joaquín
J
Abián
Departamento de Microbiología II, Universidad Complutense Madrid (UCM), Spain; Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain.
Lucía
L
Monteoliva
Institute for Systems Biology, 401, Terry Ave North, Seattle, WA 98109, USA.
Eric W
EW
Deutsch
Institute for Systems Biology, 401, Terry Ave North, Seattle, WA 98109, USA.
Robert L
RL
Moritz
Departamento de Microbiología II, Universidad Complutense Madrid (UCM), Spain; Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain; Corresponding author at: Departamento de Microbiología II, Universidad Complutense Madrid (UCM), Facultad de Farmacia, Plaza Ramón y Cajal s/n, 28040, Madrid, Spain. Electronic address: conchagil@ucm.es.
Concha
C
Gil
D000595:Amino Acid Sequence; D001426:Bacterial Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism*; D002176:Candida albicans / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D030562:Databases, Protein; D020869:Gene Expression Profiling / Q000379:methods; D008969:Molecular Sequence Data; D020543:Proteome / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D020539:Sequence Analysis, Protein / Q000379:methods*; D021241:Spectrometry, Mass, Electrospray Ionization / Q000379:methods*; D013347:Subcellular Fractions / Q000737:chemistry / Q000378:metabolism
D001426:Bacterial Proteins; D020543:Proteome
Candida albicans; Mass spectrometry; PeptideAtlas; Peptides; Proteome; Proteotypic