Exploring Xylella fastidiosas metabolic traits using a GSM model of the phytopathogenic bacterium
| Autor: | Oliveira, Alexandre Rafael Machado, Cunha, Emanuel Rodrigues, Silva, Miguel, Faria, Cristiana Silva, Dias, Oscar |
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| Přispěvatelé: | Universidade do Minho |
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
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| Popis: | The model presented in this work can be found in BioModels [26] with the identifier MODEL2205020002. To access the model: – Visit https://www.ebi.ac.uk/biomodels/login/auth. – Log in with the username reviewerForMODEL2205020002 and password DEMPB4. – Access https://www.ebi.ac.uk/biomodels/MODEL2205020002 to view the model. First Online: 20 October 2022 Xylella fastidiosa is a gram-negative phytopathogenic bacterium able to infect over 500 plant species, with devastating consequences for agricultural and forest-based economies. In the last decade, genome-scale metabolic (GSM) models have become important systems biology tools for studying the metabolic behaviour of different organisms. In this work, a GSM model of X. fastidiosa subsp. pauca De Donno is presented, comprising 1164 reactions, 1379 metabolites, and 508 genes. The model was validated by comparing in silico simulations with available experimental data. The GSM model allowed identifying potential drug targets using a pipeline based on a gene essentiality analysis of the model. This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit. A. Oliveira (DFA/BD/10205/2020), E. Cunha (DFA/BD/8076/2020) hold a doctoral fellowship provided by the FCT. Oscar Dias acknowledge FCT for the Assistant Research contract obtained under CEEC Individual 2018. info:eu-repo/semantics/publishedVersion |
| Databáze: | OpenAIRE |
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