Dataset Information

Improved MS-based proteomics by the reduction of isotopic composition in vivo

ABSTRACT: Reducing the isotopic composition of proteins in vivo improves in-depth, high resolution MS-based quantitative proteomics. We used U-[12C]-glucose as the metabolic precursor of all amino acids in yeast. This substantially increased the peptide monoisotopic ion intensity in bottom-up analyses, greatly improving identification scores and protein sequence coverage, and making it possible to address the dynamics of protein turnover at the proteome scale.

INSTRUMENT(S): Orbitrap Fusion ETD

ORGANISM(S): Candida Albicans (yeast)

TISSUE(S): Diploid Cell

SUBMITTER: Thibaut Léger

LAB HEAD: Jean-Michel Camadro

PROVIDER: PXD005364 | Pride | 2017-08-24

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	All-identifications.pdResult	Other
	All-identifications.pep.xml	Pepxml
	All-identifications.xlsx	Xlsx
	Calbicans_AllelesA22_spe.fasta	Fasta
	Control-120min_R1.raw	Raw

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Publications

A Simple Light Isotope Metabolic Labeling (SLIM-labeling) Strategy: A Powerful Tool to Address the Dynamics of Proteome Variations In Vivo.

Léger Thibaut T Garcia Camille C Collomb Laetitia L Camadro Jean-Michel JM

Molecular & cellular proteomics : MCP 20170818 11

Many quantitative proteomics strategies rely on in vivo metabolic incorporation of amino acids with modified stable isotope profiles into proteins. These methods give rise to multiple ions for each peptide, with possible distortion of the isotopolog distribution, making the overall analytical process complex. We validated an alternative strategy, simple light isotope metabolic labeling (SLIM-labeling), which alleviates many of these problems. SLIM-labeling is based on the in vivo r ...[more]

PMID: 28821603

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Project description:Recent studies have shown that the transcriptional landscape of the pleiomorphic fungus Candida albicans is highly dependent upon growth conditions. Here using a dual RNA-seq approach we identified 299 C. albicans and 72 Streptococcus gordonii genes that were either up- or down-regulated specifically as a result of co-culturing these human oral cavity microorganisms. Seventy five C. albicans genes involved in responses to chemical stimuli, regulation, homeostasis, protein modification and cell cycle were statistically (P ≤0.05) upregulated, while 36 genes mainly involved in transport and translation were down-regulated. Upregulation of filamentation-associated TEC1 and FGR42 genes, and of ALS1 adhesin gene, concurred with previous evidence that the C. albicans yeast to hypha transition is promoted by S. gordonii. Increased expression of genes required for arginine biosynthesis in C. albicans was potentially indicative of a novel oxidative stress response. The transcriptional response of S. gordonii to C. albicans was less dramatic, with only eight S. gordonii genes significantly (P ≤0.05) up-regulated ≥ twofold (glpK, rplO, celB, rplN, rplB, rpsE, ciaR, and gat). The expression patterns suggest that signals from S. gordonii cause a positive filamentation response in C. albicans, while S. gordonii appears to be transcriptionally less influenced by C. albicans. Five Samples; Sample 1 - Candida albicans cells grown in hypha inducing conditions for two hours; Sample 2 - Candida albicans cells grown in hypha-inducing conditions for two hours before co-culture with Streptococcus gordonii cells for one hour in a 2:1 rato; Sample 3 - Candida albicans cells grown in hypha-inducing conditions for two hours before culture in Streptococcus gordonii media for one hour; Sample 4 - Candida albicans cells grown in hypha inducing conditions for two hours, filtered to remove Candida albicans cells and media added to Streptococcus gordonii cells for one hour; Sample 5 - Streptococcus gordonii cells alone for one hour. All samples extracted and sequenced in biological triplicate using Illumina HiSeq2500. Samples 1, 2 and 3 aligned to the reference genome for Candida albicans and Samples 2, 4 and 5 aligned to the reference genome for Streptococcus gordonii.

Dataset Information

Improved MS-based proteomics by the reduction of isotopic composition in vivo

Dataset's files

Publications

A Simple Light Isotope Metabolic Labeling (SLIM-labeling) Strategy: A Powerful Tool to Address the Dynamics of Proteome Variations <i>In Vivo</i>.

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