Development of a quantification method for routine analysis of glucosinolates and camalexin in brassicaceous small-sized samples by simultaneous extraction prior to liquid chromatography determination.

Glucosinolates and camalexin are secondary metabolites that, as phytoanticipins and phytoalexins, play a crucial role in plant defence. The present work proposes an improved analytical method for routine analysis and quantification of glucosinolates and camalexin in brassicaceous small-sized samples by using the very specific desulfation process of glucosinolates analysis and the specificity of fluorescence detection for camalexin analysis. The approach is based on a simultaneous ultrasound-assisted extraction followed by a purification on an anion-exchange column. Final analyses are conducted by HPLC-UV-MS for desulfo-glucosinolates and HPLC coupled to a fluorescence detector (HPLC-FLD) for camalexin. The method is linear for glucosinolates (50-3500 µM) and camalexin (0.025-5 µg.mL-1) with an LOD/LOQ of 3.8/12.6 µM and 0.014/0.046 µg.mL-1 respectively. The method demonstrated adequate precision, accuracy and trueness on certified reference rapeseed. A practical application of our approach was conducted on different Brassicaceae genera (Barbarea vulgaris, Brassica nigra, Capsella bursa-pastoris, Cardamine hirsuta, Coincya monensis, Sinapis arvensis, and Sisymbrium officinale) and Arabidopsis thaliana genotypes (Columbia and Wassilewskija). Futhermore, different plant organs (seeds and leaves) were analysed, previously inoculated or not with the pathogenic fungus Alternaria brassicicola.

A Computation Method Based on the Combination of Chlorophyll Fluorescence Parameters to Improve the Discrimination of Visually Similar Phenotypes Induced by Bacterial Virulence Factors.

Phenotyping biotic stresses in plant-pathogen interactions studies is often hindered by phenotypes that can hardly be discriminated by visual assessment. Particularly, single gene mutants in virulence factors could lack visible phenotypes. Chlorophyll fluorescence (CF) imaging is a valuable tool to monitor plant-pathogen interactions. However, while numerous CF parameters can be measured, studies on plant-pathogen interactions often focus on a restricted number of parameters. It could result in limited abilities to discriminate visually similar phenotypes. In this study, we assess the ability of the combination of multiple CF parameters to improve the discrimination of such phenotypes. Such an approach could be of interest for screening and discriminating the impact of bacterial virulence factors without prior knowledge. A computation method was developed, based on the combination of multiple CF parameters, without any parameter selection. It involves histogram Bhattacharyya distance calculations and hierarchical clustering, with a normalization approach to take into account the inter-leaves and intra-phenotypes heterogeneities. To assess the efficiency of the method, two datasets were analyzed the same way. The first dataset featured single gene mutants of a Xanthomonas strain which differed only by their abilities to secrete bacterial virulence proteins. This dataset displayed expected phenotypes at 6 days post-inoculation and was used as ground truth dataset to setup the method. The efficiency of the computation method was demonstrated by the relevant discrimination of phenotypes at 3 days post-inoculation. A second dataset was composed of transient expression (agrotransformation) of Type 3 Effectors. This second dataset displayed phenotypes that cannot be discriminated by visual assessment and no prior knowledge can be made on the respective impact of each Type 3 Effectors on leaf tissues. Using the computation method resulted in clustering the leaf samples according to the Type 3 Effectors, thereby demonstrating an improvement of the discrimination of the visually similar phenotypes. The relevant discrimination of visually similar phenotypes induced by bacterial strains differing only by one virulence factor illustrated the importance of using a combination of CF parameters to monitor plant-pathogen interactions. It opens a perspective for the identification of specific signatures of biotic stresses.

Role of the acquisition of a type 3 secretion system in the emergence of novel pathogenic strains of Xanthomonas.

Cases of emergence of novel plant-pathogenic strains are regularly reported that reduce the yields of crops and trees. However, the molecular mechanisms underlying such emergence are still poorly understood. The acquisition by environmental non-pathogenic strains of novel virulence genes by horizontal gene transfer has been suggested as a driver for the emergence of novel pathogenic strains. In this study, we tested such an hypothesis by transferring a plasmid encoding the type 3 secretion system (T3SS) and four associated type 3 secreted proteins (T3SPs) to the non-pathogenic strains of Xanthomonas CFBP 7698 and CFBP 7700, which lack genes encoding T3SS and any previously known T3SPs. The resulting strains were phenotyped on Nicotiana benthamiana using chlorophyll fluorescence imaging and image analysis. Wild-type, non-pathogenic strains induced a hypersensitive response (HR)-like necrosis, whereas strains complemented with T3SS and T3SPs suppressed this response. Such suppression depends on a functional T3SS. Amongst the T3SPs encoded on the plasmid, Hpa2, Hpa1 and, to a lesser extent, XopF1 collectively participate in suppression. Monitoring of the population sizes in planta showed that the sole acquisition of a functional T3SS by non-pathogenic strains impairs growth inside leaf tissues. These results provide functional evidence that the acquisition via horizontal gene transfer of a T3SS and four T3SPs by environmental non-pathogenic strains is not sufficient to make strains pathogenic. In the absence of a canonical effector, the sole acquisition of a T3SS seems to be counter-selective, and further acquisition of type 3 effectors is probably needed to allow the emergence of novel pathogenic strains.