Characterization of the response to abiotic stresses of high ascorbate Arabidopsis lines using phenomic approaches

• Published in: Plant physiology and biochemistry Vol. 151; pp. 500 - 515
• Main Authors: Acosta-Gamboa, Lucia M., Suxing, Liu, Jarrod W, Creameans, Zachary C, Campbell, Raquel, Torres, Jessica P, Yactayo-Chang, Argelia, Lorence
• Format: Journal Article
• Language: English
• Published: France Elsevier Masson SAS 01-06-2020
• Subjects: Ascorbic acid; High throughput phenotyping; Imaging analysis; Myo-inositol oxygenase; Phenomics; Plant metabolic engineering; Plant metabolic engineering; Myo-inositol oxygenase; Ascorbic acid; Phenomics; Imaging analysis; High throughput phenotyping
• ISSN: 0981-9428; 1873-2690
• DOI: 10.1016/j.plaphy.2020.03.038

L-Ascorbic acid (AsA, vitamin C) is a key antioxidant and enzyme cofactor in plants. Ascorbate controls cell division, affects cell expansion, and plays an important role in modulating plant senescence. It protects plants against reactive oxygen species that are produced in response to abiotic and biotic stresses. Manual phenotyping indicated that Arabidopsis lines over-expressing enzymes in the myo-inositol pathway have elevated AsA, accumulate more biomass of both aerial and root tissues and are tolerant to abiotic stresses including salt, cold, heat, and environmental pollutants. However, manual phenotyping is time consuming, low throughput, subjective, and limited to the resolution of the human eye. In contrast, high throughput phenotyping technologies are accurate, non-destructive, and more sensitive, allowing the detection of subtle phenotypes. Therefore, we used a phenomics platform to phenotype our high AsA Arabidopsis lines with visible, fluorescence, and near infrared cameras. Based on this approach, high AsA lines grew faster, accumulated more biomass, and displayed healthier chlorophyll fluorescence and water content profiles than controls. By studying abiotic stress in a high throughout fashion using optimized protocols, we have also shown that these high AsA lines are tolerant to salt and water limitation stresses. In addition, we developed open source algorithms to analyze images and by comparing results obtained with a widely used commercial software against our algorithms, here we show that our method achieved good accuracy for all phenotypic parameters of interest including projected leaf area, rosette diameter (caliper length), compactness, and color classification.
•Novel open source algorithms to analyze digital plant images.•Optimized protocols to assess salt and water limitation tolerance in Arabidopsis.•First report of myo-inositol oxygenase over-expression leading to drought tolerance in Arabidopsis.