Dataset Information

Ultra-deep human phosphoproteome reveals different regulatory nature of Tyr and Ser/Thr-based signaling

ABSTRACT: Regulatory protein phosphorylation controls nearly every normal and pathophysiological signaling system in eukaryotic cells. Despite great advances in mass spectrometry based-proteomics, the total number, localization and site-specific stoichiometry of this post-translational modification (PTM) are unknown. Here we develop stringent experimental and computational workflow, capable of mapping more than 50,000 distinct phosphorylated peptides in a single human cancer cell line. Label-free quantitation determined very high stoichiometries in mitosis or growth factor signaling and more than three-quarters of cellular proteins were detected as phosphoproteins. The proportion of phospho-Tyr drastically decreases as coverage of the phosphoproteome increases, whereas Ser/Thr sites only saturate for technical reasons. Tyrosine phosphorylation is maintained at especially low stoichiometric levels in the absence of specific signaling events. Unexpectedly, it is statistically enriched on higher abundance proteins and this correlates with the substrate Km values of tyrosine kinases. Our data suggests that P-Tyr should be considered a functionally separate PTM of eukaryotic proteomes.

REANALYSED by: PAe005240PAe005289PAe005278PAe005272PAe005270PAe005264PAe005300

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Mario Oroshi

LAB HEAD: Matthias Mann

PROVIDER: PXD000612 | Pride | 2014-08-06

REPOSITORIES: Pride

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			Action	DRS
	20111219_EXQ5_KiSh_SA_LabelFree_HeLa_Proteome_Control_rep1_pH11.raw	Raw
	20111219_EXQ5_KiSh_SA_LabelFree_HeLa_Proteome_Control_rep1_pH3.raw	Raw
	20111219_EXQ5_KiSh_SA_LabelFree_HeLa_Proteome_Control_rep1_pH4.raw	Raw
	20111219_EXQ5_KiSh_SA_LabelFree_HeLa_Proteome_Control_rep1_pH5.raw	Raw
	20111219_EXQ5_KiSh_SA_LabelFree_HeLa_Proteome_Control_rep1_pH6.raw	Raw

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Ultradeep human phosphoproteome reveals a distinct regulatory nature of Tyr and Ser/Thr-based signaling.

Sharma Kirti K D'Souza Rochelle C J RC Tyanova Stefka S Schaab Christoph C Wiśniewski Jacek R JR Cox Jürgen J Mann Matthias M

Cell reports 20140821 5

Regulatory protein phosphorylation controls normal and pathophysiological signaling in eukaryotic cells. Despite great advances in mass-spectrometry-based proteomics, the extent, localization, and site-specific stoichiometry of this posttranslational modification (PTM) are unknown. Here, we develop a stringent experimental and computational workflow, capable of mapping more than 50,000 distinct phosphorylated peptides in a single human cancer cell line. We detected more than three-quarters of ce ...[more]

PMID: 25159151

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Project description:We have previously reported that tyrosol (TYR), one of the main phenols in extra virgin olive oil (EVOO), promotes lifespan extension in the nematode Caenorhabditis elegans, also inducing a stronger resistance to thermal and oxidative stress in this animal model. Although the influence of several longevity-related genes in these effects has been reported by our group, we decided to perform a whole genome DNA-microarray approach in order to identify other genes and molecular pathways further involved in TYR effects on C. elegans longevity. Microarray analysis identified 208 differentially expressed genes (206 overexpressed and 2 underexpressed) when comparing TYR-treated nematodes with non-treated controls. Many of these genes seem linked to processes such as regulation of growth, transcription, reproduction, lipid metabolism and body morphogenesis. Data obtained by microarray was validated by qRT-PCR analysis of selected genes. Our results confirm that several important cellular mechanisms related to longevity are influenced by TYR treatment in this animal model. Moreover, we detected an interesting overlap between the expression pattern elicited by TYR and those induced by other dietary polyphenols known to extend lifespan in C. elegans, such as quercetin and tannic acid. C. elegans were maintained on Nematode Growth Medium (NGM) and E. coli OP50 as described [21]. For microarray experiments, fer15(b26) nematodes were synchronized by hypochlorite treatment and raised at 25°C on NGM plates containing either 250 μM TYR (n=3) or vehicle (control; n=3). At the fourth day of adulthood, nematodes were collected from the plates in M9 buffer, washed 3 times and pelleted by centrifugation for RNA isolation. After centrifugation, worms were resuspended in 350 μl of RLT/BME buffer, flash frozen in liquid nitrogen and thawed at 37 °C three times for disruption and total RNA was extracted using the RNeasy Mini Kit (Qiagen) following the manufacturer recommended protocol. Final volume of isolated RNA was 50 μl per biological sample. RNA quality was analyzed with the 2100 Bioanalyzer (Agilent Technologies) using the RNA 6000 nano kit. All RNA samples were of sufficient quality for gene array analysis with RIN>7. A total amount of 50 ng of RNA was used as the template for cDNA synthesis and in vitro transcription to synthesized biotin-modified aRNA using the GeneChip® 3’ IVT Express Kit (Affymetrix, 901228). aRNA was purified from unincorporated nucleotides and other reaction components using the RNeasy Mini Kit (Qiagen). A total of 15 µg of biotin-labeled aRNA was fragmented following the instructions described in the Affymetrix manual (P/N 702646 Rev.8) and hybridized to C. elegans GeneChip® Genome Arrays (Affymetrix, 900383). They were processed and scanned using Affymetrix instrumentation and with hybridization, washing and scanning parameters provided by the manufacturer. Computational and statistical analyses were carried out using the R software (http://www.r-project.org/) and the appropriate Bioconductor packages (http://www.bioconductor.org/) run under R. In order to remove all the possible sources of variation of a non-biological origin between arrays, densitometry values between arrays were normalized using the RMA (robust multiarray) normalization function implemented in the Bioconductor affylmGUI. Statistically significant differences between groups were identified using the rank product non-parametric test implemented in the Bioconductor Rank-Prod package. Those genes showing a corrected (FDR) p-value < 0.05 were selected as significant.