Inferring active metabolic pathways from proteomics and essentiality data
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- dc.contributor.author Montero-Blay, Ariadna, 1994-
- dc.contributor.author Piñero-Lambea, Carlos
- dc.contributor.author Miravet Verde, Samuel, 1992-
- dc.contributor.author Lluch-Senar, Maria 1982-
- dc.contributor.author Serrano Pubull, Luis, 1982-
- dc.date.accessioned 2020-10-14T05:57:15Z
- dc.date.available 2020-10-14T05:57:15Z
- dc.date.issued 2020
- dc.description.abstract Here, we propose an approach to identify active metabolic pathways by integrating gene essentiality analysis and protein abundance. We use two bacterial species (Mycoplasma pneumoniae and Mycoplasma agalactiae) that share a high gene content similarity yet show significant metabolic differences. First, we build detailed metabolic maps of their carbon metabolism, the most striking difference being the absence of two key enzymes for glucose metabolism in M. agalactiae. We then determine carbon sources that allow growth in M. agalactiae, and we introduce glucose-dependent growth to show the functionality of its remaining glycolytic enzymes. By analyzing gene essentiality and performing quantitative proteomics, we can predict the active metabolic pathways connected to carbon metabolism and show significant differences in use and direction of key pathways despite sharing the large majority of genes. Gene essentiality combined with quantitative proteomics and metabolic maps can be used to determine activity and directionality of metabolic pathways.
- dc.description.sponsorship This project was financed by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program, under grant agreement nos. 634942 (MycoSynVac) and 670216 (MYCOCHASSIS). We acknowledge support of the Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Programme / Generalitat de Catalunya.
- dc.format.mimetype application/pdf
- dc.identifier.citation Montero-Blay A, Piñero-Lambea C, Miravet-Verde S, Lluch-Senar M, Serrano L. Inferring active metabolic pathways from proteomics and essentiality data. Cell Rep. 2020; 31(9):107722. DOI: 10.1016/j.celrep.2020.107722
- dc.identifier.doi http://dx.doi.org/10.1016/j.celrep.2020.107722
- dc.identifier.issn 2211-1247
- dc.identifier.uri http://hdl.handle.net/10230/45477
- dc.language.iso eng
- dc.publisher Elsevier
- dc.relation.ispartof Cell Rep. 2020; 31(9):107722
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/634942
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/670216
- dc.rights © 2020 The Author(s). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
- dc.subject.keyword Metabolism
- dc.subject.keyword Bacteria
- dc.subject.keyword Transposon
- dc.subject.keyword Active pathways
- dc.subject.keyword Mycoplasma
- dc.subject.keyword Proteomics
- dc.subject.keyword Essentiality
- dc.title Inferring active metabolic pathways from proteomics and essentiality data
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion