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  Perseus plugin "Metis'' for metabolic-pathway-centered quantitative multi-omics data analysis for static and time-series experimental designs

Hamzeiy, H., Ferretti, D., Robles, M. S., & Cox, J. (2022). Perseus plugin "Metis'' for metabolic-pathway-centered quantitative multi-omics data analysis for static and time-series experimental designs. Cell Reports: Methods, 2(4): 100198. doi:10.1016/j.crmeth.2022.100198.

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 Creators:
Hamzeiy, Hamid1, Author           
Ferretti, Daniela1, Author           
Robles, Maria S.2, Author
Cox, Jürgen1, Author           
Affiliations:
1Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society, ou_2063284              
2external, ou_persistent22              

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Free keywords: GENE-EXPRESSION; CIRCADIAN CONTROL; TRANSCRIPTION; OSCILLATIONSBiochemistry & Molecular Biology; Cell Biology;
 Abstract: We introduce Metis, a new plugin for the Perseus software aimed at analyzing quantitative multi- omics data based on metabolic pathways. Data from different omics types are connected through reactions of a genome-scale metabolic-pathway reconstruction. Metabolite concentrations connect through the reactants, while transcript, protein, and protein post-translational modification (PTM) data are associated through the enzymes catalyzing the reactions. Supported experimental designs include static comparative studies and time-series data. As an example for the latter, we combine circadian mouse liver multi-omics data and study the contribution of cycles of phosphoproteome and metabolome to enzyme activity regulation. Our analysis resulted in 52 pairs of cycling phosphosites and metabolites connected through a reaction. The time lags between phosphorylation and metabolite peak show non-uniform behavior, indicating a major contribution of phosphorylation in the modulation of enzymatic activity.

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Language(s): eng - English
 Dates: 2022-04-252022-04-14
 Publication Status: Issued
 Pages: 15
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Degree: -

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Title: Cell Reports: Methods
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Amsterdam : Elsevier
Pages: - Volume / Issue: 2 (4) Sequence Number: 100198 Start / End Page: - Identifier: Other: ISSN
CoNE: https://pure.mpg.de/cone/journals/resource/2667-2375