Candida auris proteomic data
Description
Candida auris has emerged as a serious worldwide threat by causing opportunistic infections that are frequently resistant to conventional antifungal medication. To date, there is little information about the differentially expressed genes when this fungus is treated with conventional antifungals or in other stress conditions. We treated C. auris for 24h with caspofungin to evaluate global cellular responses.
Files
Steps to reproduce
Peptides of each sample were separated by online reversed-phase nanoscale capillary liquid chromatography and analyzed by electrospray mass spectrometry in tandem (ESI-MS/MS). The experiments were performed in the mass spectrometry facility RPT02H of Carlos Chagas Institute (Fiocruz, Parana) with a nanoLC-1D plus (Eksigent) coupled to LTQ Orbitrap XL ETD (Thermo Scientific) mass spectrometer. Chromatographic separation of the peptide mixtures was carried out on an analytical silica column of 15 cm, 75-micron ID and with a 3 µM diameter C18 particles (Dr. Maisch), flow rate of 250 nL/min of mobile phase (ACN, 0.1% formic acid, 5% DMSO) with a linear gradient from 5 to 40% ACN in 180 min. Peptides were ionized by nano-electrospray (voltage 2.7 kV) and injected into the MS. Full-scan MS spectra (at 300.0–1800.0 m/z range) were acquired on an Orbitrap analyzer with a resolution of R = 60,000. The 10 most intense peaks were fragmented by CID and analyzed in the Ion trap. A dynamic exclusion list of 90 sec was applied and the “lock mass” option was enabled (m/z = 401.922718). The LC-MS/MS data were matched against the C. auris strain B8441 database from UniProt Knowledgebase (downloaded on November 11, 2020, containing 5,409 sequences) using MaxQuant software version 1.6.17.0. Among the search parameters were specified a tolerance of 0.5 Da for MS/MS, and 20 ppm for MS first search and 4.5 ppm for MS main search. Quantification was done by the LFQ method. Cysteine carbamidomenthylation were set as fixed modification, methionine oxidation and N-terminal acetylation were set as variable modification. The tables generated by Max Quant were analyzed with Perseus software version 1.6.14.0. A false discovery rate (FDR) of 1% was applied for both peptide and protein identification. The contaminants and reverse sequences were removed. The LFQ intensity was converted to log2(x) scale and ANOVA multiple-sample test was performed to determine differentially expressed proteins using p-Value ≤ 0.05 and Fold Change > 2 as cut off. The files are available in RAW format.