Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast.
Cells react to extracellular perturbations with complex and intertwined responses. Systematic identification of the regulatory mechanisms that control these responses is still a challenge and requires tailored analyses integrating different types of molecular data. Here we acquired time-resolved met...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005297&type=printable |
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| author | Emanuel Gonçalves Zrinka Raguz Nakic Mattia Zampieri Omar Wagih David Ochoa Uwe Sauer Pedro Beltrao Julio Saez-Rodriguez |
| author_facet | Emanuel Gonçalves Zrinka Raguz Nakic Mattia Zampieri Omar Wagih David Ochoa Uwe Sauer Pedro Beltrao Julio Saez-Rodriguez |
| author_sort | Emanuel Gonçalves |
| collection | DOAJ |
| description | Cells react to extracellular perturbations with complex and intertwined responses. Systematic identification of the regulatory mechanisms that control these responses is still a challenge and requires tailored analyses integrating different types of molecular data. Here we acquired time-resolved metabolomics measurements in yeast under salt and pheromone stimulation and developed a machine learning approach to explore regulatory associations between metabolism and signal transduction. Existing phosphoproteomics measurements under the same conditions and kinase-substrate regulatory interactions were used to in silico estimate the enzymatic activity of signalling kinases. Our approach identified informative associations between kinases and metabolic enzymes capable of predicting metabolic changes. We extended our analysis to two studies containing transcriptomics, phosphoproteomics and metabolomics measurements across a comprehensive panel of kinases/phosphatases knockouts and time-resolved perturbations to the nitrogen metabolism. Changes in activity of transcription factors, kinases and phosphatases were estimated in silico and these were capable of building predictive models to infer the metabolic adaptations of previously unseen conditions across different dynamic experiments. Time-resolved experiments were significantly more informative than genetic perturbations to infer metabolic adaptation. This difference may be due to the indirect nature of the associations and of general cellular states that can hinder the identification of causal relationships. This work provides a novel genome-scale integrative analysis to propose putative transcriptional and post-translational regulatory mechanisms of metabolic processes. |
| format | Article |
| id | doaj-art-62347357f83a4e8fbbe4eb7e5b024083 |
| institution | DOAJ |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-62347357f83a4e8fbbe4eb7e5b0240832025-08-20T02:46:00ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582017-01-01131e100529710.1371/journal.pcbi.1005297Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast.Emanuel GonçalvesZrinka Raguz NakicMattia ZampieriOmar WagihDavid OchoaUwe SauerPedro BeltraoJulio Saez-RodriguezCells react to extracellular perturbations with complex and intertwined responses. Systematic identification of the regulatory mechanisms that control these responses is still a challenge and requires tailored analyses integrating different types of molecular data. Here we acquired time-resolved metabolomics measurements in yeast under salt and pheromone stimulation and developed a machine learning approach to explore regulatory associations between metabolism and signal transduction. Existing phosphoproteomics measurements under the same conditions and kinase-substrate regulatory interactions were used to in silico estimate the enzymatic activity of signalling kinases. Our approach identified informative associations between kinases and metabolic enzymes capable of predicting metabolic changes. We extended our analysis to two studies containing transcriptomics, phosphoproteomics and metabolomics measurements across a comprehensive panel of kinases/phosphatases knockouts and time-resolved perturbations to the nitrogen metabolism. Changes in activity of transcription factors, kinases and phosphatases were estimated in silico and these were capable of building predictive models to infer the metabolic adaptations of previously unseen conditions across different dynamic experiments. Time-resolved experiments were significantly more informative than genetic perturbations to infer metabolic adaptation. This difference may be due to the indirect nature of the associations and of general cellular states that can hinder the identification of causal relationships. This work provides a novel genome-scale integrative analysis to propose putative transcriptional and post-translational regulatory mechanisms of metabolic processes.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005297&type=printable |
| spellingShingle | Emanuel Gonçalves Zrinka Raguz Nakic Mattia Zampieri Omar Wagih David Ochoa Uwe Sauer Pedro Beltrao Julio Saez-Rodriguez Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast. PLoS Computational Biology |
| title | Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast. |
| title_full | Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast. |
| title_fullStr | Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast. |
| title_full_unstemmed | Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast. |
| title_short | Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast. |
| title_sort | systematic analysis of transcriptional and post transcriptional regulation of metabolism in yeast |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005297&type=printable |
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