Abstract
Biostimulants show potentials as sustainable strategies for improved crop development and stress resilience. However, the cellular and molecular mechanisms, in particular the signaling and regulatory events, governing the agronomically observed positive effects of biostimulants on plants remain enigmatic, thus hampering novel formulation and exploration of biostimulants. Metabolomics offers opportunities to elucidate metabolic and regulatory processes that define biostimulant-induced changes in the plant’s biochemistry and physiology, thus contributing to decode the modes of action of biostimulants. Here, we describe an application of metabolomics to elucidate biostimulant effects on crop plants. Using the case study of a humic substance (HS)-based biostimulant applied on maize plants, under normal and nutrient-starved stress conditions, this chapter proposes key methodological guidance and considerations of computational metabolomics approach to investigate metabolic and regulatory reconfiguration and networks underlying biostimulant-induced physiological changes in plants. Computational metabolome mining tools, in the Global Natural Products Social Molecular Networking (GNPS) ecosystem, are highlighted as well as metabolic pathway and network analysis for biological interpretation of the data.
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Acknowledgments
Shimadzu South Africa Ltd. are gratefully thanked for the support with access to the LCMS-8050 system. Omnia Group Ltd., the South African Cultivar and Technology Agency (SACTA), and the South Africa National Research Foundation (NRF) are duly acknowledged for scholarships to Lerato Nephali and Kgalaletso Othibeng.
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Othibeng, K., Nephali, L., Tugizimana, F. (2023). Computational Metabolomics to Elucidate Molecular Signaling and Regulatory Mechanisms Associated with Biostimulant-Mediated Growth Promotion and Abiotic Stress Tolerance in Crop Plants. In: Couée, I. (eds) Plant Abiotic Stress Signaling. Methods in Molecular Biology, vol 2642. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3044-0_9
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DOI: https://doi.org/10.1007/978-1-0716-3044-0_9
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