Quantification of biotic stresses on aerial parts of plants using Chlorophyll Fluorescence Imaging and Image Analysis

Image analysis is increasingly used in plant phenotyping. Among the various imaging techniques available for plant phenotyping, Chlorophyll Fluorescence Imaging is particularly su itable for the imaging of biotic and abiotic stresses on the aerial parts of plants. Numerous chlorophyll fluorescence parameters may be measured or calculated, but only some of them may provide useful contrasts for the quantification of a given stress on leaves. In the perspective of high throughput phenotyping of biotic stresses on plants, we developed automated procedures to identify Chlorophyll Fluorescence parameters of interest for the quantification of a given biotic stress on large image datasets. The outputs of the automated procedures enable: - the visualization of the whole dataset, by providing contact sheets for each of the chlorophyll fluorescence parameter tested. - the visualization of basic statistics : radial - plot, box - plot and Mann - Whitney tests based on the mean intensity of each parameters are provided to compare the various treatments performed. - images are clustered based on histograms associated to each images, thereby enabling the clustering of images leaves displaying leaves of si milar phytosanitary status. - the objective quantification of disease incidence on each leaf tested. The quantification can discriminate varois stages of symptom development such as necrotic tissues, wilted and chlorotic tissues, and impacted tissues that do not display any symptoms visible to the eye.

Procédé de dépistage de Xanthomonas axonopodis pv. phaseoli

Screening Xanthomonas axonopodis pathovar phaseoliin a biological sample, comprises detecting a combination (C1) of two genes of the combination AvrBsT/Xac3090, the combination AvrBsT/XopP, and the combination AvrBsT/AvrXccB, where the result of the screening process is positive if the presence of two genes of the combination (C1) is detected in the biological sample. Independent claims are included for: (1) a nucleotide probe or primer used in a method of screening Xanthomonas axonopodis pathovar phaseoli, where the primer or the probe has a length of 12-30 nucleotides and comprising at least 12 consecutive nucleotides from a nucleic acid of the nucleic acid sequence of SEQ ID NOs: 5-12 (e.g. ccatgctgagcacggtcatt (SEQ ID NO: 5), cgccttccagttgctgacat (SEQ ID NO: 6), acgagcccttcccaaactagc (SEQ ID NO: 7), taccaacatcgtacgcttccc (SEQ ID NO: 8), cgtcagtgagtgctcggttg (SEQ ID NO: 9) and tcagagccctggaagcaaga (SEQ ID NO: 10)), and the nucleic acids of complementary sequence; and (2) a kit for detection of Xanthomonas axonopodis pathovar phaseoliin a biological sample, comprising two pairs of primers for amplifying the combination of the two genes (C1) and the nucleotide probe or primer

Recombination-prone bacterial strains form a reservoir from which epidemic clones emerge in agroecosystems

The acquisition of virulence-related genes through horizontal gene transfer can modify the pathogenic profiles of strains and lead to the emergence of new diseases. Xanthomonas arboricola is a bacterial species largely known for the damage it causes to stone and nut fruit trees worldwide. In addition to these host-specific populations called pathovars, many nonpathogenic strains have been identified in this species. Their evolutionary significance in the context of pathogen emergence is unknown. We looked at seven housekeeping genes amplified from 187 pathogenic and nonpathogenic strains isolated from various plants worldwide to analyze population genetics and recombination dynamics. We also examined the dynamics of the gains and losses of genes associated with life history traits (LHTs) during X. arboricola evolution. We discovered that X. arboricola presents an epidemic population structure. Successful pathovars of trees (i.e. pruni, corylina and juglandis) are epidemic clones whose emergence appears to be linked to the acquisition of eight genes coding for Type III effectors. The other strains of this species are part of a recombinant network, within which LHT-associated genes might have been lost. We suggest that nonpathogenic strains, because of their high genetic diversity and propensity for recombination, may promote the emergence of pathogenic strains

Comparative Genomics of Pathogenic and Nonpathogenic Strains of Xanthomonas arboricola Unveil Molecular and Evolutionary Events Linked to Pathoadaptation

The bacterial species Xanthomonas arboricola contains plant pathogenic and nonpathogenic strains. It includes the pathogen X. arboricola pv. juglandis, causing the bacterial blight of Juglans regia. The emergence of a new bacterial disease of J, regia in France called vertical oozing canker (VOC) was previously described and the causal agent was identified as a distinct genetic lineage within the pathovar Symptoms on walnut leaves and fruits are similar to those of a bacterial blight but VOC includes also cankers on trunk and branches. In this work, we used comparative genomics and physiological tests to detect differences between four X. arboricola strains isolated from walnut tree: strain CFBP 2528 causing walnut blight (WB), strain CFBP 7179 causing VOC and two nonpathogenic strains, CFBP 7634 and CFBP 7651, isolated from healthy walnut buds. Whole genome sequence comparisons revealed that pathogenic strains possess a larger and wider range of mobile genetic elements than nonpathogenic strains. One pathogenic strain, CFBP 7179, possessed a specific integrative and conjugative element (ICE) of 95 kb encoding genes involved in copper resistance, transport and regulation. The type three effector repertoire was larger in pathogenic strains than in nonpathogenic strains. Moreover, CFBP 7634 strain lacked the type three secretion system encoding genes. The flagellar system appeared incomplete and nonfunctional in the pathogenic strain CFBP 2528. Differential sets of chemoreceptor and different repertoires of genes coding adhesins were identified between pathogenic and nonpathogenic strains. Besides these differences, some strain-specific differences were also observed. Altogether, this study provides valuable insights to highlight the mechanisms involved in ecology, environment perception, plant adhesion and interaction, leading to the emergence of new strains in a dynamic environment

Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets

Background Image analysis is increasingly used in plant phenotyping. Among the various imaging techniques that can be used in plant phenotyping, chlorophyll fluorescence imaging allows imaging of the impact of biotic or abiotic stresses on leaves. Numerous chlorophyll fluorescence parameters may be measured or calculated, but only a few can produce a contrast in a given condition. Therefore, automated procedures that help screening chlorophyll fluorescence image datasets are needed, especially in the perspective of high-throughput plant phenotyping. Results We developed an automatic procedure aiming at facilitating the identification of chlorophyll fluorescence parameters impacted on leaves by a stress. First, for each chlorophyll fluorescence parameter, the procedure provides an overview of the data by automatically creating contact sheets of images and/or histograms. Such contact sheets enable a fast comparison of the impact on leaves of various treatments, or of the contrast dynamics during the experiments. Second, based on the global intensity of each chlorophyll fluorescence parameter, the procedure automatically produces radial plots and box plots allowing the user to identify chlorophyll fluorescence parameters that discriminate between treatments. Moreover, basic statistical analysis is automatically generated. Third, for each chlorophyll fluorescence parameter the procedure automatically performs a clustering analysis based on the histograms. This analysis clusters images of plants according to their health status. We applied this procedure to monitor the impact of the inoculation of the root parasitic plant Phelipanche ramosa on Arabidopsis thaliana ecotypes Col-0 and Ler. Conclusions Using this automatic procedure, we identified eight chlorophyll fluorescence parameters discriminating between the two ecotypes of A. thaliana, and five impacted by the infection of Arabidopsis thaliana by P. ramosa. More generally, this procedure may help to identify chlorophyll fluorescence parameters impacted by various types of stresses. We implemented this procedure at http://www.phenoplant.org webcite freely accessible to users of the plant phenotyping community