Exploring Xylella fastidiosas metabolic traits using a GSM model of the phytopathogenic bacterium

Abstract

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.