Análisis computacional de redes metabólicas e interacción proteína-proteína en relaciones planta patógeno: dilucidando su complejidad mediante métodos computacionales (2021)
Due to the technological revolution in the last decades, science has also passed through impressive changes. Specially in areas like interactomics, where algorithms and methodologies are required to analyze the result data. Plant-pathogen interaction is a perfect area for such objective. The possible applications in this field extend from improvements in agribusiness to ecology and conservation. This study proposes the use of many computational tools for studying the interaction between Xanthomonas phaseoli pv. manihotis (Xpm) and Manihot esculenta known traditionally as casaba, yuca or mandioca, in order to understand the phenomena that comprises plant pathogen interaction. It is hypothesized that bacterial effectors interact with specific metabolic networks and that many of them are recurrent targets. Metabolic interactions networks were constructed based on identified protein-protein interactions. The principal metabolic hubs affected by effectors were carbohydrate metabolism, amino acids, energetic and signal transduction systems. Multiple alignment showed consensus sequences between many interacting proteins with high coverage for effectors XopN, XopL, XopQ, XopC2. Most of the affected enzymes were hydrolases and transferases. The contact surface for myoinositol phosphate synthase with effector XopN is in congruence with the respective alignment. Results show that bacterial effectors affect specially the catabolic pathways of the plant. This is coherent with pathogenic processes, as this is a fundamental component in the execution of immune response and nutrient production, beneficial for bacteria.