An updated genome-scale model forXylella fastidiosasubsp.paucaDe Donno

Abstract

Xylella fastidiosa is a gram-negative phytopathogenic bacterium that caused a significant economic impact around the world. In the last decade, genome-scale metabolic models have become important systems biology tools for studying the metabolic behaviour of different pathogens and driving the discovery of novel drug targets. In this work, a GSM model of X. fastidiosa subsp. pauca De Donno was developed. The model comprises 1164 reactions, 1379 metabolites, and 508 genes. in silico validation of the metabolic model was achieved through the comparison of simulations with available experimental data. Aerobic metabolism was simulated properly and fastidian gum production rates predicted accurately. The GSM model allowed identifying potential drug targets, using a pipeline based on the model's gene essentially analysis.