Infection Assay for Xanthomonas campestris pv. campestris in Arabidopsis thaliana Mimicking Natural Entry via Hydathodes

ScAnalyzer: an image processing tool to monitor plant disease symptoms and pathogen spread in Arabidopsis thaliana leaves

BACKGROUND

Plants are known to be infected by a wide range of pathogenic microbes. To study plant diseases caused by microbes, it is imperative to be able to monitor disease symptoms and microbial colonization in a quantitative and objective manner. In contrast to more traditional measures that use manual assignments of disease categories, image processing provides a more accurate and objective quantification of plant disease symptoms. Besides monitoring disease symptoms, computational image processing provides additional information on the spatial localization of pathogenic microbes in different plant tissues.

RESULTS

Here we report on an image analysis tool called ScAnalyzer to monitor disease symptoms and bacterial spread in Arabidopsis thaliana leaves. Thereto, detached leaves are assembled in a grid and scanned, which enables automated separation of individual samples. A pixel color threshold is used to segment healthy (green) from chlorotic (yellow) leaf areas. The spread of luminescence-tagged bacteria is monitored via light-sensitive films, which are processed in a similar manner as the leaf scans. We show that this tool is able to capture previously identified differences in susceptibility of the model plant A. thaliana to the bacterial pathogen Xanthomonas campestris pv. campestris. Moreover, we show that the ScAnalyzer pipeline provides a more detailed assessment of bacterial spread within plant leaves than previously used methods. Finally, by combining the disease symptom values with bacterial spread values from the same leaves, we show that bacterial spread precedes visual disease symptoms.

CONCLUSION

Taken together, we present an automated script to monitor plant disease symptoms and microbial spread in A. thaliana leaves. The freely available software ( https://github.com/MolPlantPathology/ScAnalyzer ) has the potential to standardize the analysis of disease assays between different groups.

Arabidopsis thaliana Early Foliar Proteome Response to Root Exposure to the Rhizobacterium Pseudomonas simiae WCS417

Pseudomonas simiae WCS417 is a plant growth-promoting rhizobacterium that improves plant health and development. In this study, we investigate the early leaf responses of Arabidopsis thaliana to WCS417 exposure and the possible involvement of formate dehydrogenase (FDH) in such responses. In vitro-grown A. thaliana seedlings expressing an FDH::GUS reporter show a significant increase in FDH promoter activity in their roots and shoots after 7 days of indirect exposure (without contact) to WCS417. After root exposure to WCS417, the leaves of FDH::GUS plants grown in the soil also show an increased FDH promoter activity in hydathodes. To elucidate early foliar responses to WCS417 as well as FDH involvement, the roots of A. thaliana wild-type Col and atfdh1-5 knock-out mutant plants grown in soil were exposed to WCS417, and proteins from rosette leaves were subjected to proteomic analysis. The results reveal that chloroplasts, in particular several components of the photosystems PSI and PSII, as well as members of the glutathione S-transferase family, are among the early targets of the metabolic changes induced by WCS417. Taken together, the alterations in the foliar proteome, as observed in the atfdh1-5 mutant, especially after exposure to WCS417 and involving stress-responsive genes, suggest that FDH is a node in the early events triggered by the interactions between A. thaliana and the rhizobacterium WCS417. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

High-throughput screening paradigms in ecotoxicity testing: Emerging prospects and ongoing challenges

The rapidly increasing number of new production chemicals coupled with stringent implementation of global chemical management programs necessities a paradigm shift towards boarder uses of low-cost and high-throughput ecotoxicity testing strategies as well as deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity that can be used in effective risk assessment. The latter will require automated acquisition of biological data, new capabilities for big data analysis as well as computational simulations capable of translating new data into in vivo relevance. However, very few efforts have been so far devoted into the development of automated bioanalytical systems in ecotoxicology. This is in stark contrast to standardized and high-throughput chemical screening and prioritization routines found in modern drug discovery pipelines. As a result, the high-throughput and high-content data acquisition in ecotoxicology is still in its infancy with limited examples focused on cell-free and cell-based assays. In this work we outline recent developments and emerging prospects of high-throughput bioanalytical approaches in ecotoxicology that reach beyond in vitro biotests. We discuss future importance of automated quantitative data acquisition for cell-free, cell-based as well as developments in phytotoxicity and in vivo biotests utilizing small aquatic model organisms. We also discuss recent innovations such as organs-on-a-chip technologies and existing challenges for emerging high-throughput ecotoxicity testing strategies. Lastly, we provide seminal examples of the small number of successful high-throughput implementations that have been employed in prioritization of chemicals and accelerated environmental risk assessment.