The identification of genes important in pseudomonas syringae pv. phaseolicola plant colonisation using in vitro screening of transposon libraries

The bacterial plant pathogen Pseudomonas syringae pv. phaseolicola (Pph) colonises the surface of common bean plants before moving into the interior of plant tissue, via wounds and stomata. In the intercellular spaces the pathogen proliferates in the apoplastic fluid and forms microcolonies (biofilms) around plant cells. If the pathogen can suppress the plant’s natural resistance response, it will cause halo blight disease. The process of resistance suppression is fairly well understood, but the mechanisms used by the pathogen in colonisation are less clear. We hypothesised that we could apply in vitro genetic screens to look for changes in motility, colony formation, and adhesion, which are proxies for infection, microcolony formation and cell adhesion. We made transposon (Tn) mutant libraries of Pph strains 1448A and 1302A and found 106/1920 mutants exhibited alterations in colony morphology, motility and biofilm formation. Identification of the insertion point of the Tn identified within the genome highlighted, as expected, a number of altered motility mutants bearing mutations in genes encoding various parts of the flagellum. Genes involved in nutrient biosynthesis, membrane associated proteins, and a number of conserved hypothetical protein (CHP) genes were also identified. A mutation of one CHP gene caused a positive increase in in planta bacterial growth. This rapid and inexpensive screening method allows the discovery of genes important for in vitro traits that can be correlated to roles in the plant interaction

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.