A Model and Image Based Investigation of X. fastidiosa Within Host Dynamics

Photosynthesis relies on the transport of water and sugars from roots to leaves facilitated by two key tissues: xylem and phloem. Blockages in the xylem/phloem, either by structures formed by the pathogen itself or those formed by the plant as a defence mechanism, disrupt the soil-plant-atmosphere continuum and cause many vascular plant disease symptoms. Xylella fastidiosa (X. fastidiosa) is a bacterium that colonises internal plant vascular networks causing pathogenic effects on several commercially important crops, including those associated with the olive quick decline syndrome causing devastating olive decline in Apulia, Southern Italy. Despite a growing research effort since the recent detection of X. fastidiosa in Europe, the exact processes leading to X. fastidiosa disease symptoms are not fully understood due to difficulties in observing internal plant structures.

Our goal is to utilise models to elucidate fundamental processes that lead to olive quick decline syndrome. We are developing a mathematical model describing within-host biofilm development that predicts water-stresses that ultimately inhibit plant functionality. Our approach is centred on the assumption that the biofilm structure is determined by the arrangement of extracellular polysaccharide (EPS) molecules, and as such, our model contains a polymer-physical description of X. fastidiosa biofilm formation dynamics. We used our model, requiring minimal empirical assumptions, to replicate biofilm aggregation observed by microfluidics. We have also produced X-ray Computed Tomography (XCT) images of vascular networks in both resistant and susceptible olive cultivars. We are using these images to test whether susceptibility is correlated with morphological differences that might influence fluid flow through the plant. This work improves the understanding of possible cultivar resistance mechanisms to aid informed breeding and orchard management, and model simulations will provide insights for understanding xylem blockages and their relation to observed symptom severity.