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PXD010529

PXD010529 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleProteomes of yeast kinase knock-outs analysed by SWATH-MS
DescriptionIt proves so far difficult to predict the metabolome, even when genome, transcriptome or proteome of a cell are known. In order to globally map enzyme-metabolite relationships, we systematically quantified enzyme expression and metabolite concentrations in Saccharomyces cerevisiae kinase knock-out strains. Enzymes expression changes did account for a major fraction of all differentially expressed proteins, and were non-redundant, implying that kinases act generally yet specifically in metabolic regulation. Differential enzyme expression was found to affect metabolite concentrations through the redistribution of flux control, resulting in a many-to-many relationship between enzyme abundance and the metabolome. Machine learning successfully mapped these relationships, allowing the precise prediction of metabolite concentrations, as well as identifying regulatory genes. Our study reveals that hierarchical metabolic regulation acts predominantly through adjustment of broad enzyme expression patterns rather than over rate-limiting enzymes, and may account for more than half of metabolic regulation.
HostingRepositoryPRIDE
AnnounceDate2018-09-12
AnnouncementXMLSubmission_2018-09-12_09:28:56.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterVadim Demichev
SpeciesList scientific name: Saccharomyces cerevisiae (Baker's yeast); NCBI TaxID: 4932;
ModificationListiodoacetamide derivatized residue
InstrumentTripleTOF 5600
Dataset History
RevisionDatetimeStatusChangeLog Entry
02018-07-23 02:29:40ID requested
12018-09-12 09:28:57announced
Publication List
Zelezniak A, Vowinckel J, Capuano F, Messner CB, Demichev V, Polowsky N, M, ü, lleder M, Kamrad S, Klaus B, Keller MA, Ralser M, Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts. Cell Syst, 7(3):269-283.e6(2018) [pubmed]
Keyword List
curator keyword: Biological
submitter keyword: High-throughput proteomics, SWATH, yeast, kinase
Contact List
Markus Ralser
contact affiliationThe Francis Crick Institute, Molecular Biology of Metabolism laboratory, London, United Kingdom; Department of Biochemistry and Cambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom; Department of Biochemistry, Charité Universitaetsmedizin Berlin, Berlin, Germany
contact emailmarkus.ralser@crick.ac.uk
lab head
Vadim Demichev
contact affiliationUniversity of Cambridge
contact emailvd286@cam.ac.uk
dataset submitter
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Dataset FTP location
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