Absolute Proteome and Phosphoproteome Dynamics during the Cell Cycle of Schizosaccharomyces pombe (Fission Yeast)

To quantify cell cycle-dependent fluctuations on a proteome-wide scale, we performed integrative analysis of the proteome and phosphoproteome during the four major phases of the cell cycle in Schizosaccharomyces pombe. In highly synchronized cells, we identified 3753 proteins and 3682 phosphorylatio...

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Published inMolecular & cellular proteomics Vol. 13; no. 8; pp. 1925 - 1936
Main Authors Carpy, Alejandro, Krug, Karsten, Graf, Sabine, Koch, André, Popic, Sasa, Hauf, Silke, Macek, Boris
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.08.2014
The American Society for Biochemistry and Molecular Biology
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Summary:To quantify cell cycle-dependent fluctuations on a proteome-wide scale, we performed integrative analysis of the proteome and phosphoproteome during the four major phases of the cell cycle in Schizosaccharomyces pombe. In highly synchronized cells, we identified 3753 proteins and 3682 phosphorylation events and relatively quantified 65% of the data across all phases. Quantitative changes during the cell cycle were infrequent and weak in the proteome but prominent in the phosphoproteome. Protein phosphorylation peaked in mitosis, where the median phosphorylation site occupancy was 44%, about 2-fold higher than in other phases. We measured copy numbers of 3178 proteins, which together with phosphorylation site stoichiometry enabled us to estimate the absolute amount of protein-bound phosphate, as well as its change across the cell cycle. Our results indicate that 23% of the average intracellular ATP is utilized by protein kinases to phosphorylate their substrates to drive regulatory processes during cell division. Accordingly, we observe that phosphate transporters and phosphate-metabolizing enzymes are phosphorylated and therefore likely to be regulated in mitosis.
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These authors contributed equally to the manuscript.
Present address: Dept. of Biological Sciences, Virginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg, VA 24061, Tel.: 540 231 7318; E-mail: silke.hauf@vt.edu.
ISSN:1535-9476
1535-9484
DOI:10.1074/mcp.M113.035824