Dataset Information

Label-free quantitative proteomics in Candida yeast species: technical and biological replicates to asses data reproducibility

ABSTRACT: Objective Label-free quantitative proteomics has emerged as a powerful strategy to obtain high quality quantitative measures of the proteome with only a very small quantity of total protein extract. Because our research projects were requiring the application of bottom-up shotgun Mass Spectrometry proteomics in the pathogenic yeasts Candida glabrata and Candida albicans, we performed preliminary experiments to i) obtained a precise list of all the proteins for which measures of abundance could be obtain and ii) assess the reproducibility of the results arising respectively from biological and technical replicates. Data description C. glabrata and C. albicans cells were grown in minimal liquid medium. Three independent time-courses were performed simultaneously, in each species, and an alkaline pH stress was induced for two of them. Cells were collected 10 and 60 minutes after stress induction and proteins were extracted. They were analysed and quantified two time 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.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Candida Glabrata (yeast) (torulopsis Glabrata) Candida Albicans (yeast)

SUBMITTER: Thibaut LEGER

LAB HEAD: Pr. Gaëlle Lelandais

PROVIDER: PXD014125 | Pride | 2019-07-08

REPOSITORIES: Pride

ACCESS DATA

Similar Datasets

Project description:The differentiation of cells into distinct cell types, each of which is heritable for many generations, underlies many biological phenomena. White and opaque cells of the fungal pathogen Candida albicans are two such heritable cell types, each thought to be adapted to unique niches within their human host. To systematically investigate the differences between the two cell types, we performed strand-specific massively-parallel sequencing of RNA from C. albicans white and opaque cells. Combining the resulting data from both cell types, we first substantially re-annotated the C. albicans transcriptome, finding 1443 novel coding and non-coding transcriptionally active regions. Using the new annotation, we compared differences in transcript abundance between the two cell types with the genomic regions bound by the master regulator of the white-opaque switch (Wor1). We found that the revised transcriptional landscape considerably alters our understanding of the circuit governing differentiation. In particular, we can now resolve the poor concordance between binding of the master regulator and the differential expression of adjacent genes, a discrepancy observed in many other studies of cell differentiation. More than one third of the Wor1-bound differentially-expressed transcripts were previously unannotated, which explains the formerly puzzling presence of Wor1 at these positions along the genome. Indeed, many of these newly identified Wor1-regulated genes are non-coding and transcribed antisense to coding transcripts. We also found that 5' and 3' untranslated regions (UTRs) of mRNAs in the circuit are unusually long and that 5' UTRs often differ in length between white and opaque cells. These observations suggest that the use of alternative promoters is widespread in the circuit and that important regulatory information is carried in the long UTRs. Further analysis revealed that the revised Wor1 circuit bears several striking similarities to the Oct4 circuit that specifies the pluripotency of mammalian embryonic stem cells. Additional characteristics shared with the Oct4 circuit suggest a set of general hallmarks characteristic of heritable differentiation states in eukaryotes. RNA-Seq was applied to Candida albicans white and opaque cells to identify novel transcripts and UTRs that are differentially regulated between the two cell types. Two biological replicates each of white and opaque cell cultures. One of the white cell RNA samples was split just after isolation to allow a comparison of the poly(A)-selection and ribo-depletion sample preparation strategies.

Dataset Information

Label-free quantitative proteomics in Candida yeast species: technical and biological replicates to asses data reproducibility

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure