Imaging with spatio-temporal modelling to characterize the dynamics of plant-pathogen lesions

Leclerc, Melen; Jumel, Stéphane; Hamelin, Frédéric M.; Treilhaud, Rémi; Parisey, Nicolas; Mammeri, Youcef

doi:10.1371/journal.pcbi.1011627

Cited by 2 publications

(1 citation statement)

References 54 publications

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“…NADPH is also crucial for the reactive oxygen species (ROS) metabolic system (in the ascorbate-glutathione pathway), NADPH-dependent thioredoxin reductase, and apoplastic oxidative burst in most plant-pathogen interactions, and it is a key enzyme in carbon metabolism, playing an important role in plant photosynthesis [82,83]. The negative effect of D. pinodes on leaf photosynthesis efficiency was well documented [84] and can be related to the dynamics of plant-pathogen lesions [85,86]. Comparative studies of cultivars more and less resistant to D. pinodes infection revealed common metabolomic responses such as increased contents of sugars (but not sucrose), sugar alcohols, and glycolysis/tricarboxylic acid (TCA) cycle intermediates and changes in amino acid content [87].…”

Section: Changes In Polar Metabolic Profiles Of Pea Seedlings After I...mentioning

confidence: 99%

Antifungal Properties of Bio-AgNPs against D. pinodes and F. avenaceum Infection of Pea (Pisum sativum L.) Seedlings

Stałanowska,

Szablińska-Piernik,

Pszczółkowska

et al. 2024

IJMS

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Ascochyta blight and Fusarium root rot are the most serious fungal diseases of pea, caused by D. pinodes and F. avenaceum, respectively. Due to the lack of fully resistant cultivars, we proposed the use of biologically synthesized silver nanoparticles (bio-AgNPs) as a novel protecting agent. In this study, we evaluated the antifungal properties and effectiveness of bio-AgNPs, in in vitro (poisoned food technique; resazurin assay) and in vivo (seedlings infection) experiments, against D. pinodes and F. avenaceum. Moreover, the effects of diseases on changes in the seedlings’ metabolic profiles were analyzed. The MIC for spores of both fungi was 125 mg/L, and bio-AgNPs at 200 mg/L most effectively inhibited the mycelium growth of D. pinodes and F. avenaceum (by 45 and 26%, respectively, measured on the 14th day of incubation). The treatment of seedlings with bio-AgNPs or fungicides before inoculation prevented the development of infection. Bio-AgNPs at concentrations of 200 mg/L for D. pinodes and 100 mg/L for F. avenaceum effectively inhibited infections’ spread. The comparison of changes in polar metabolites’ profiles revealed disturbances in carbon and nitrogen metabolism in pea seedlings by both pathogenic fungi. The involvement of bio-AgNPs in the mobilization of plant metabolism in response to fungal infection is also discussed.

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Section: Changes In Polar Metabolic Profiles Of Pea Seedlings After I...mentioning

confidence: 99%

Antifungal Properties of Bio-AgNPs against D. pinodes and F. avenaceum Infection of Pea (Pisum sativum L.) Seedlings

Stałanowska,

Szablińska-Piernik,

Pszczółkowska

et al. 2024

IJMS

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SYMPATHIQUE: Image-based tracking of Symptoms and monitoring of Pathogenesis to decompose Quantitative disease resistance in the field

Anderegg,

Zenkl,

Kirchgessner

et al. 2024

Preprint

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Background. Quantitative disease resistance (QR) is a complex, dynamic trait that is most reliably quantified in field-grown crops. Traditional disease assessments offer limited potential to disentangle the contributions of different components to overall QR at critical crop developmental stages. Yet, a better functional understanding of QR could greatly support a more targeted, knowledge-based selection for QR and improve predictions of seasonal epidemics. Image-based approaches together with advanced image processing methodologies recently emerged as valuable tools to standardize relevant disease assessments, increase measurement throughput, and describe diseases along multiple dimensions. Results. We present a simple, affordable, and easy-to-operate imaging set-up and imaging procedure for in-field acquisition of wheat leaf image sequences. The development of Septoria tritici blotch and leaf rusts was monitored over time via robust methods for symptom detection and segmentation, image registration, symptom tracking, and leaf- and symptom characterization. The average accuracy of the co-registration of images in a time series was approximately 5 pixels (~ 0.15 mm). Leaf-level symptom counts as well as individual symptom property measurements revealed stable patterns over time that were generally in excellent agreement with visual impressions. This provided strong evidence for the robustness of the methodology to variability typically inherent in field data. Contrasting patterns in lesion numbers and lesion expansion dynamics were observed across wheat genotypes. The number of separate infection events and average lesion size contributed to different degrees to overall disease intensity, possibly indicating distinct and complementary mechanisms of QR. Conclusions. The proposed methodology enables rapid, non-destructive, and reproducible measurement of several key epidemiological parameters under natural field conditions. Such data can support decomposition and functional understanding of QR as well as the parameterization, fine-tuning, and validation of epidemiological models. Details of pathogenesis can translate into specific symptom phenotypes resolvable using time series of high-resolution RGB images, which may improve biological understanding of plant-pathogen interactions as well as interactions in disease complexes.

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Imaging with spatio-temporal modelling to characterize the dynamics of plant-pathogen lesions

Cited by 2 publications

References 54 publications

Antifungal Properties of Bio-AgNPs against D. pinodes and F. avenaceum Infection of Pea (Pisum sativum L.) Seedlings

Antifungal Properties of Bio-AgNPs against D. pinodes and F. avenaceum Infection of Pea (Pisum sativum L.) Seedlings

SYMPATHIQUE: Image-based tracking of Symptoms and monitoring of Pathogenesis to decompose Quantitative disease resistance in the field

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