Dataset Information

ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics.

ABSTRACT: The ability of plants to sense and orient their root growth towards gravity is studied in many laboratories. It is known that manual analysis of image data is subjected to human bias. Several semi-automated tools are available for analysing images from flatbed scanners, but there is no solution to automatically measure root bending angle over time for vertical-stage microscopy images. To address these problems, we developed ACORBA, which is an automated software that can measure root bending angle over time from vertical-stage microscope and flatbed scanner images. ACORBA also has a semi-automated mode for camera or stereomicroscope images. It represents a flexible approach based on both traditional image processing and deep machine learning segmentation to measure root angle progression over time. As the software is automated, it limits human interactions and is reproducible. ACORBA will support the plant biologist community by reducing labour and increasing reproducibility of image analysis of root gravitropism.

SUBMITTER: Serre NBC

PROVIDER: S-EPMC10095971 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

ACORBA: Automated workflow to measure <i>Arabidopsis thaliana</i> root tip angle dynamics.

Serre Nelson B C NBC Fendrych Matyáš M

Quantitative plant biology 20220524

The ability of plants to sense and orient their root growth towards gravity is studied in many laboratories. It is known that manual analysis of image data is subjected to human bias. Several semi-automated tools are available for analysing images from flatbed scanners, but there is no solution to automatically measure root bending angle over time for vertical-stage microscopy images. To address these problems, we developed ACORBA, which is an automated software that can measure root bending ang ...[more]

PMID: 37077987

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Project description:BackgroundOomycetes are a group of filamentous microorganisms that includes both animal and plant pathogens and causes major agricultural losses. Phytophthora species can infect most crops and plants from natural ecosystems. Despite their tremendous economic and ecologic importance, few effective methods exist for limiting the damage caused by these species. New solutions are required, and their development will require improvements in our understanding of the molecular events governing infection by these pathogens. In this study, we characterized the genetic program activated during penetration of the plant by the soil-borne pathogen Phytophthora parasitica.ResultsUsing all the P. parasitica sequences available in public databases, we generated a custom oligo-array and performed a transcriptomic analysis of the early events of Arabidopsis thaliana infection. We characterized biological stages, ranging from the appressorium-mediated penetration of the pathogen into the roots to the occurrence of first dead cells in the plant. We identified a series of sequences that were transiently modulated during host penetration. Surprisingly, we observed an overall down regulation of genes encoding proteins involved in lipid and sugar metabolism, and an upregulation of functions controlling the transport of amino acids. We also showed that different groups of genes were expressed by P. parasitica during host penetration and the subsequent necrotrophic phase. Differential expression patterns were particularly marked for cell wall-degrading enzymes and other proteins involved in pathogenicity, including RXLR effectors. By transforming P. parasitica with a transcriptional fusion with GFP, we showed that an RXLR-ecoding gene was expressed in the appressorium and infectious hyphae during infection of the first plant cell.ConclusionWe have characterized the genetic program activated during the initial invasion of plant cells by P. parasitica. We showed that a specific set of proteins, including effectors, was mobilized for penetration and to facilitate infection. Our detection of the expression of an RXLR encoding gene by the appressorium and infection hyphae highlights a role of this structure in the manipulation of the host cells.

Dataset Information

ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics.

Publications

ACORBA: Automated workflow to measure <i>Arabidopsis thaliana</i> root tip angle dynamics.

Similar Datasets

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