Label-free quantitative proteomics in Candida yeast species: technical and biological replicates to assess data reproducibility.
Gaëlle LelandaisThomas DeneckerCamille GarciaNicolas DanilaThibaut LégerJean-Michel CamadroPublished in: BMC research notes (2019)
Three time-courses were performed in each Candida species, and an alkaline pH stress was induced for two of them. Cells were collected 10 and 60 min after stress induction and proteins were extracted. Samples were analysed two times by mass spectrometry. Our final dataset thus comprises label-free quantitative proteomics results for 24 samples (two species, three time-courses, two time points and two runs of mass spectrometry). Statistical procedures were applied to identify proteins with differential abundances between stressed and unstressed situations. Considering that C. glabrata and C. albicans are human pathogens, which face important pH fluctuations during a human host infection, this dataset has a potential value to other researchers in the field.
Keyphrases
- label free
- mass spectrometry
- candida albicans
- endothelial cells
- high resolution
- liquid chromatography
- induced pluripotent stem cells
- high glucose
- pluripotent stem cells
- capillary electrophoresis
- gas chromatography
- genetic diversity
- cell cycle arrest
- machine learning
- diabetic rats
- cell death
- cell proliferation
- big data
- drug induced
- anaerobic digestion
- oxidative stress
- pseudomonas aeruginosa
- human health
- tandem mass spectrometry
- cell wall
- simultaneous determination