Knowledge remains limited about how fungal pathogens that colonize living plant cells translocate effector proteins inside host cells to regulate cellular processes and neutralize defense responses. To cause the globally important rice blast disease, specialized invasive hyphae (IH) invade successive living rice (Oryza sativa) cells while enclosed in host-derived extrainvasive hyphal membrane. Using live-cell imaging, we identified a highly localized structure, the biotrophic interfacial complex (BIC), which accumulates fluorescently labeled effectors secreted by IH. In each newly entered rice cell, effectors were first secreted into BICs at the tips of the initially filamentous hyphae in the cell. These tip BICs were left behind beside the first-differentiated bulbous IH cells as the fungus continued to colonize the host cell. Fluorescence recovery after photobleaching experiments showed that the effector protein PWL2 (for prevents pathogenicity toward weeping lovegrass [Eragrostis curvula]) continued to accumulate in BICs after IH were growing elsewhere. PWL2 and BAS1 (for biotrophyassociated secreted protein 1), BIC-localized secreted proteins, were translocated into the rice cytoplasm. By contrast, BAS4, which uniformly outlines the IH, was not translocated into the host cytoplasm. Fluorescent PWL2 and BAS1 proteins that reached the rice cytoplasm moved into uninvaded neighbors, presumably preparing host cells before invasion. We report robust assays for elucidating the molecular mechanisms that underpin effector secretion into BICs, translocation to the rice cytoplasm, and cell-to-cell movement in rice.

BackgroundIn order to select for quantitative plant resistance to pathogens, high throughput approaches that can precisely quantify disease severity are needed. Automation and use of calibrated image analysis should provide more accurate, objective and faster analyses than visual assessments. In contrast to conventional visible imaging, chlorophyll fluorescence imaging is not sensitive to environmental light variations and provides single-channel images prone to a segmentation analysis by simple thresholding approaches. Among the various parameters used in chlorophyll fluorescence imaging, the maximum quantum yield of photosystem II photochemistry (Fv/Fm) is well adapted to phenotyping disease severity. Fv/Fm is an indicator of plant stress that displays a robust contrast between infected and healthy tissues. In the present paper, we aimed at the segmentation of Fv/Fm images to quantify disease severity.ResultsBased on the Fv/Fm values of each pixel of the image, a thresholding approach was developed to delimit diseased areas. A first step consisted in setting up thresholds to reproduce visual observations by trained raters of symptoms caused by Xanthomonas fuscans subsp. fuscans (Xff) CFBP4834-R on Phaseolus vulgaris cv. Flavert. In order to develop a thresholding approach valuable on any cultivars or species, a second step was based on modeling pixel-wise Fv/Fm-distributions as mixtures of Gaussian distributions. Such a modeling may discriminate various stages of the symptom development but over-weights artifacts that can occur on mock-inoculated samples. Therefore, we developed a thresholding approach based on the probability of misclassification of a healthy pixel. Then, a clustering step is performed on the diseased areas to discriminate between various stages of alteration of plant tissues. Notably, the use of chlorophyll fluorescence imaging could detect pre-symptomatic area. The interest of this image analysis procedure for assessing the levels of quantitative resistance is illustrated with the quantitation of disease severity on five commercial varieties of bean inoculated with Xff CFBP4834-R.ConclusionsIn this paper, we describe an image analysis procedure for quantifying the leaf area impacted by the pathogen. In a perspective of high throughput phenotyping, the procedure was automated with the software R downloadable at http://www.r-project.org/. The R script is available at http://lisa.univ-angers.fr/PHENOTIC/telechargements.html.