integrative image-based high-throughput phenotyping Dotaz Zobrazit nápovědu
Designing and developing new biostimulants is a crucial process which requires an accurate testing of the product effects on the morpho-physiological traits of plants and a deep understanding of the mechanism of action of selected products. Product screening approaches using omics technologies have been found to be more efficient and cost effective in finding new biostimulant substances. A screening protocol based on the use of high-throughput phenotyping platform for screening new vegetal-derived protein hydrolysates (PHs) for biostimulant activity followed by a metabolomic analysis to elucidate the mechanism of the most active PHs has been applied on tomato crop. Eight PHs (A-G, I) derived from enzymatic hydrolysis of seed proteins of Leguminosae and Brassicaceae species were foliarly sprayed twice during the trial. A non-ionic surfactant Triton X-100 at 0.1% was also added to the solutions before spraying. A control treatment foliarly sprayed with distilled water containing 0.1% Triton X-100 was also included. Untreated and PH-treated tomato plants were monitored regularly using high-throughput non-invasive imaging technologies. The phenotyping approach we used is based on automated integrative analysis of photosynthetic performance, growth analysis, and color index analysis. The digital biomass of the plants sprayed with PH was generally increased. In particular, the relative growth rate and the growth performance were significantly improved by PHs A and I, respectively, compared to the untreated control plants. Kinetic chlorophyll fluorescence imaging did not allow to differentiate the photosynthetic performance of treated and untreated plants. Finally, MS-based untargeted metabolomics analysis was performed in order to characterize the functional mechanisms of selected PHs. The treatment modulated the multi-layer regulation process that involved the ethylene precursor and polyamines and affected the ROS-mediated signaling pathways. Although further investigation is needed to strengthen our findings, metabolomic data suggest that treated plants experienced a metabolic reprogramming following the application of the tested biostimulants. Nonetheless, our experimental data highlight the potential for combined use of high-throughput phenotyping and metabolomics to facilitate the screening of new substances with biostimulant properties and to provide a morpho-physiological and metabolomic gateway to the mechanisms underlying PHs action on plants.
Plant biostimulants which include bioactive substances (humic acids, protein hydrolysates and seaweed extracts) and microorganisms (mycorrhizal fungi and plant growth promoting rhizobacteria of strains belonging to the genera Azospirillum, Azotobacter, and Rhizobium spp.) are gaining prominence in agricultural systems because of their potential for improving nutrient use efficiency, tolerance to abiotic stressors, and crop quality. Highly accurate non-destructive phenotyping techniques have attracted the interest of scientists and the biostimulant industry as an efficient means for elucidating the mode of biostimulant activity. High-throughput phenotyping technologies successfully employed in plant breeding and precision agriculture, could prove extremely useful in unraveling biostimulant-mediated modulation of key quantitative traits and would also facilitate the screening process for development of effective biostimulant products in controlled environments and field conditions. This perspective article provides an innovative discussion on how small, medium, and large high-throughput phenotyping platforms can accelerate efforts for screening numerous biostimulants and understanding their mode of action thanks to pioneering sensor and image-based phenotyping techniques. Potentiality and constraints of small-, medium-, and large-scale screening platforms are also discussed. Finally, the perspective addresses two screening approaches, "lab to field" and "field to lab," used, respectively, by small/medium and large companies for developing novel and effective second generation biostimulant products.
BACKGROUND: Recently emerging approaches to high-throughput plant phenotyping have discovered their importance as tools in unravelling the complex questions of plant growth, development and response to the environment, both in basic and applied science. High-throughput methods have been also used to study plant responses to various types of biotic and abiotic stresses (drought, heat, salinity, nutrient-starving, UV light) but only rarely to cold tolerance. RESULTS: We present here an experimental procedure of integrative high-throughput in-house phenotyping of plant shoots employing automated simultaneous analyses of shoot biomass and photosystem II efficiency to study the cold tolerance of pea (Pisum sativum L.). For this purpose, we developed new software for automatic RGB image analysis, evaluated various parameters of chlorophyll fluorescence obtained from kinetic chlorophyll fluorescence imaging, and performed an experiment in which the growth and photosynthetic activity of two different pea cultivars were followed during cold acclimation. The data obtained from the automated RGB imaging were validated through correlation of pixel based shoot area with measurement of the shoot fresh weight. Further, data obtained from automated chlorophyll fluorescence imaging analysis were compared with chlorophyll fluorescence parameters measured by a non-imaging chlorophyll fluorometer. In both cases, high correlation was obtained, confirming the reliability of the procedure described. CONCLUSIONS: This study of the response of two pea cultivars to cold stress confirmed that our procedure may have important application, not only for selection of cold-sensitive/tolerant varieties of pea, but also for studies of plant cold-response strategies in general. The approach, provides a very broad tool for the morphological and physiological selection of parameters which correspond to shoot growth and the efficiency of photosystem II, and is thus applicable in studies of various plant species and crops.
- Klíčová slova
- Biomass production, Chlorophyll fluorescence imaging, Cold adaptation, Pea (Pisum), Plant phenotyping, RGB digital imaging, Shoot growth,
- Publikační typ
- časopisecké články MeSH
Gap junctional intercellular communication (GJIC) is a vital cellular process required for maintenance of tissue homeostasis. In vitro assessment of GJIC represents valuable phenotypic endpoint that could be effectively utilized as an integral component in modern toxicity testing, drug screening or biomedical in vitro research. However, currently available methods for quantifying GJIC with higher-throughputs typically require specialized equipment, proprietary software and/or genetically engineered cell models. To overcome these limitations, we present here an innovative adaptation of traditional, fluorescence microscopy-based scrape loading-dye transfer (SL-DT) assay, which has been optimized to simultaneously evaluate GJIC, cell density and viability. This multiparametric method was demonstrated to be suitable for various multiwell microplate formats, which facilitates an automatized image acquisition. The assay workflow is further assisted by an open source-based software tools for batch image processing, analysis and evaluation of GJIC, cell density and viability. Our results suggest that this approach provides a simple, fast, versatile and cost effective way for in vitro high-throughput assessment of GJIC and other related phenotypic cellular events, which could be included into in vitro screening and assessment of pharmacologically and toxicologically relevant compounds.
- MeSH
- fluorescenční mikroskopie metody MeSH
- krysa rodu Rattus MeSH
- kultivované buňky MeSH
- mezerový spoj * MeSH
- mezibuněčná komunikace * MeSH
- molekulární zobrazování metody MeSH
- počet buněk * MeSH
- počítačové zpracování obrazu metody MeSH
- viabilita buněk * MeSH
- zvířata MeSH
- Check Tag
- krysa rodu Rattus MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
