Publicação
Genome-scale metabolic modelling of the pathogen Xylella fastidiosa
| Resumo: | Xylella fastidiosa is a phytopathogenic bacteria that causes disease in hundreds of differ ent plant species. Increased reports of plants infected by these xylem-limited bacteria are alarming as this pathogen continues to attack crops of relevant economic power such as citrus, grapes, olives and almonds, with considerable economical losses for the producers. The current employed strategy to contain this epidemic is radical in action as it destroys the infected plant and surrounding area. For this reason, it became urgent to develop new ways to eliminate these bacteria with therapeutics that are more pathogen oriented. Genome-Scale Metabolic (GSM) models contain genomic and metabolic information of a given organism and can be used to discover new potential drug targets. Thus, a GSM model of X. fastidiosa may unveil new ways to control these bacteria. In this work, we developed a high-quality GSM model for X. fastidiosa subsp. pauca De Donno, using the user-friendly software Metabolic Models Reconstruction Using Genome Scale Information (merlin). This strain was chosen for its importance in the national econ omy, as it causes Olive Quick Decline Syndrome. The reconstructed model of X. fastidiosa comprises a set of 1280 reactions and 524 genes. The genome of X. fastidiosa subsp. pauca De Donno was functionally annotated in order to identify the metabolic potential of the phytopathogenic organism. Metabolic functions identified in the genome were used to assemble the initial draft metabolic network. Manual curation procedures were made in order to correctly represent organism’s capabilities and biomass related reactions, based on literature and experimental data, were added to model. The reconstructed model was then validated using experimental data, regarding the aerobic metabolism, carbon flux pattern, carbon usage, amino acid auxotrophies and growth in several media developed for X. fastidiosa. In silico simulations revealed interesting metabolic properties of X. fastidiosa. The usage of carbon through the Entner-Doudoroff pathway seems to be a way of generating redox potential for defensive mechanism against the host plant. An absence of auxotrophies and the presence of catabolic routes for amino acids shows the metabolic and adaptive potential of the organism, as expected since it grows on nutrient-limited environments. This reconstructed model can be used to explore the metabolism and provide information for potential drug targets for the agricultural-destructive phytopathogen X. fastidiosa. |
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| Autores principais: | Silva, Miguel Ângelo Fernandes da |
| Assunto: | Xylella fastidiosa subsp. pauca De Donno Phytopathogen Systems biology Genome-scale metabolic model |
| Ano: | 2019 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | Xylella fastidiosa is a phytopathogenic bacteria that causes disease in hundreds of differ ent plant species. Increased reports of plants infected by these xylem-limited bacteria are alarming as this pathogen continues to attack crops of relevant economic power such as citrus, grapes, olives and almonds, with considerable economical losses for the producers. The current employed strategy to contain this epidemic is radical in action as it destroys the infected plant and surrounding area. For this reason, it became urgent to develop new ways to eliminate these bacteria with therapeutics that are more pathogen oriented. Genome-Scale Metabolic (GSM) models contain genomic and metabolic information of a given organism and can be used to discover new potential drug targets. Thus, a GSM model of X. fastidiosa may unveil new ways to control these bacteria. In this work, we developed a high-quality GSM model for X. fastidiosa subsp. pauca De Donno, using the user-friendly software Metabolic Models Reconstruction Using Genome Scale Information (merlin). This strain was chosen for its importance in the national econ omy, as it causes Olive Quick Decline Syndrome. The reconstructed model of X. fastidiosa comprises a set of 1280 reactions and 524 genes. The genome of X. fastidiosa subsp. pauca De Donno was functionally annotated in order to identify the metabolic potential of the phytopathogenic organism. Metabolic functions identified in the genome were used to assemble the initial draft metabolic network. Manual curation procedures were made in order to correctly represent organism’s capabilities and biomass related reactions, based on literature and experimental data, were added to model. The reconstructed model was then validated using experimental data, regarding the aerobic metabolism, carbon flux pattern, carbon usage, amino acid auxotrophies and growth in several media developed for X. fastidiosa. In silico simulations revealed interesting metabolic properties of X. fastidiosa. The usage of carbon through the Entner-Doudoroff pathway seems to be a way of generating redox potential for defensive mechanism against the host plant. An absence of auxotrophies and the presence of catabolic routes for amino acids shows the metabolic and adaptive potential of the organism, as expected since it grows on nutrient-limited environments. This reconstructed model can be used to explore the metabolism and provide information for potential drug targets for the agricultural-destructive phytopathogen X. fastidiosa. |
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