Charles Manceau

High throughput quantitative phenotyping of plant resistance using chlorophyll fluorescence image analysis

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.

Morphological and genotypic features of Xanthomonas arboricola pv. juglandis populations from walnut groves in Romagna region, Italy

Seventy-seven Xanthomonas arboricola pv. juglandis isolates, originating from a small region (Romagna, Italy) within 4xa0years, were phenotypically typed, in order to study their population features. Assessment of phenotypes resulted in the identification of three different groups of morphotypes, in the assessment of different virulence on walnut fruitlets, and in the evidence that all isolates were able to grow on Mannitol-glutamate-yeast agar containing 50xa0ppm of copper sulphate. Moreover, several isolates showed to be highly copper resistant in vitro, up to 500xa0ppm. Forty-one isolates, selected considering year/origin of plant material and phenotypic features, were molecularly studied by rep-PCR fingerprinting using BOXA1R primer. These strains showed a clear intra-pathovar variation by the presence of eight different haplotypes. Twenty isolates, representative of different BOX profile, were studied by means of variable number of tandem repeats (VNTR) on the locus TR5b. Such analysis highlighted five different sequence types. Eight polymorphic strains on this flanking region isolated in between 2007 and 20 and one isolated in 2010 were subject to multilocus sequence analysis (MLSA) using atpD, dnaK, efP, fyuA, glnA, gyrB, and rpoD housekeeping genes. A diversity level in Italian isolates was highlighted in the same range as in reference strains from a worldwide origin. Finally, the gene cluster copLAB presence was confirmed for all isolates. In this study, the high phenotype and genotype variability inside Xanthomonas arboricola pv. juglandis, was explained by the different origin of the propagation material. Information provided in this study on an Italian Xanthomonas arboricola pv. juglandis collection allows a better understanding of the walnut bacterial blight epidemiology.

Inferring pathogen dynamics from temporal count data: the emergence of Xylella fastidiosa in France is probably not recent

Summary Unravelling the ecological structure of emerging plant pathogens persisting in multi‐host systems is challenging. In such systems, observations are often heterogeneous with respect to time, space and host species, and may lead to biases of perception. The biased perception of pathogen ecology may be exacerbated by hidden fractions of the whole host population, which may act as infection reservoirs. We designed a mechanistic‐statistical approach to help understand the ecology of emerging pathogens by filtering out some biases of perception. This approach, based on SIR (Susceptible–Infected–Removed) models and a Bayesian framework, disentangles epidemiological and observational processes underlying temporal counting data. We applied our approach to French surveillance data on Xylella fastidiosa, a multi‐host pathogenic bacterium recently discovered in Corsica, France. A model selection led to two diverging scenarios: one scenario without a hidden compartment and an introduction around 2001, and the other with a hidden compartment and an introduction around 1985. Thus, Xylella fastidiosa was probably introduced into Corsica much earlier than its discovery, and its control could be arduous under the hidden compartment scenario. From a methodological perspective, our approach provides insights into the dynamics of emerging plant pathogens and, in particular, the potential existence of infection reservoirs.

Fireblight survey and first characterization of Erwinia amylovora isolates from Algeria.

During field surveys conducted in Spring and Summer 2010-2011, typical fire blight symptoms were observed on twigs and branches of pear (Pyrus communis) and apple (Malus domestica) in Algerian commercial orchards located in the areas of Algiers, Blida, Tipaza and Boumerdes. The disease was observed in 284 orchards, mainly on pear cv. Santa Maria and on apple cvs Royal gala and Golden delicious. Bacterial colonies were isolated on King’s medium B (KB) and the semi-selective medium CCT (cycloheximide, cristal violet and thallium nitrate). Bacterial isolates displayed biochemical patterns typical of Erwinia amylovora and reacted positively in a serological slide agglutination test. Pathogenicity of bacterial isolates was confirmed by inoculating immature pear fruits of cv. Conference. The identity of the isolates was further confirmed by nested-PCR, and rep-PCR. A sequenced DNA fragment (713 bp) of the recA gene (accession No. JN812979) matched with 100% identity all E. amylovora recA DNA sequences available in GeneBank.

From Farms to Markets: Gram-Negative Bacteria Resistant to Third-Generation Cephalosporins in Fruits and Vegetables in a Region of North Africa

The role of food in human exposure to antimicrobial-resistant bacteria is a growing food safety issue. The contribution of fruits and vegetables eaten raw to this exposure is still unclear. The evaluation of contamination levels of fruits, vegetables and the agricultural environment by third-generation cephalosporin (3GC)-resistant Gram-negative bacteria was performed by analyzing 491 samples of fruits and vegetables collected from 5 markets and 7 farms in Bejaia area, north-eastern Mediterranean coast of Algeria. Ninety soil samples and 45 irrigation water samples were also sampled in farms in order to assess them as potential inoculum sources. All samples were investigated at the same time on ceftazidime-containing selective media for 3GC-resistant Gram-negative bacteria detection and on Hektoen media, for Salmonella spp. presence. The bacteria isolated (n = 30) from fruits and vegetables, soil and irrigation water collected in the farms were almost all non-fermenting bacterial species (Stenotrophomonas, Acinetobacter, Pseudomonas, Ochrobactrum) except one strain of Enterobacter cloacae and two strains of Citrobacter murliniae, isolated on one cucumber and two tomato samples in the same farm. Greater diversity in bacterial species and antimicrobial resistance profiles was observed at markets: Enterobacteriaceae (n = 41) were as strongly represented as non-fermenting bacteria (n = 37). Among Enterobacteriaceae, E. cloacae (n = 21), and Klebsiella pneumoniae (n = 13) were the most common isolates. Most of the K. pneumoniae isolates were extended-spectrum beta-lactamase (ESBL) producers (n = 11). No Salmonella spp. was recovered in any sample. This study showed that fruits and vegetables including those which may be eaten up raw constitute a reservoir of 3GC-resistant Gram-negative bacteria and multi-drug resistant-bacteria in general that can be transferred to humans through food. The general public should be informed of this hazard for health in order to encourage good domestic hygiene practices. In addition, further investigation is needed throughout the production chain to enrol professionals in actions to reduce this contamination.

Development of a new technique to detect living cells of Xanthomonas campestris pv. campestris in crucifers seeds: the seed-qPCR

Xanthomonas campestris pv. campestris is a seed-borne bacterium that causes black rot on Brassicaceae. Ensuring seed lot sanitary quality is the most efficient control strategy against bacterial diseases. Currently, the procedures adopted in the control of seed lots are mainly based on microbiological techniques combined with PCR or plant inoculation which is time and money consuming. The aim of this study was to propose a reliable and rapid detection technique of living X. c. pv. campestris in cabbage seeds. We have shown that not all cells of X. campestris is able to grown on rich medium after washing and soaking seeds as no colony of X. campestris was detected on inoculated seeds, whereas plantlets develop symptoms 7–14xa0days after germination. The PCR technique used alone does not address the viability of bacteria in samples. We set up a technique named seed-qPCR for the detection of living X. c. pv. campestris bacterial cells in seed lots. This technique is based on an enrichment of bacterial population associated with infected seeds by seed germination coupled with real-time Taq-man PCR after extraction of the target DNA. It is an inexpensive technique that allow the detection of down to 1 contaminated seed among 10 000 healthy seeds. The seed-qPCR method combines an efficient extraction based on bacterial multiplication on seedlings with a sensitive technique qPCR for the detection of bacteria in seed lots.