Editorial: Exploring complex biosphere molecular signaling networks: plant-microbes symbiosis at microscopic to macroscopic levels

Abstract

Plants have evolved to live on earth using basic chemicals, such as, CO2, water, and minerals in air and soil. This knowledge helped human beings develop industrial agriculture to build and maintain civilizations, to domesticate animals, and to meet the food demands of growing population. However, crop production engineering using chemical fertilizers/pesticides, overexploitation of soil resources disregarding subtle balances in the ecosystem, and climate change have created a crisis (Timmis and Ramos, 2021). Our realization that soil is a highly interconnected ecosystem with interspecies chemical exchange through, for instance, symbiosis, has opened avenues for developing sustainable agricultural practices protecting the environment (Zipfel and Oldroyd, 2017). Moreover, the quality of the agricultural produces depends heavily on the biotic and abiotic environmental factors plants experience in the environment. The environmental factors that affect crops need to be assessed scientifically and documented, rather than relying on sensory perception to assess nutritional quality of the produces. Further, fundamental investigations should also be conducted to better understand the symbiosis between microbes and plants from a molecular perspective. Studies in the recent past have revealed several molecular aspects of soil microbe entry into legume plants' root system, subsequent nodulation of root, and effective nitrogen fixation. Discovery of nod factor (e.g., oligosaccharide derivative produced by S. meliloti) revealed the molecular mechanism of microbe entrapment in root hairs.Subsequent studies revealed the role of symbiosis entry receptors (e.g., LYK3), hence the corresponding genes, in the effective infection process. Similarly, phosphate levels in the environment and Ca 2+ spiking are essential for the causing appropriate changes in the root hair phenotype and for infection to proceed beyond the microbe entrapment in root hairs (Gilroy and Jones, 2000;Parry, 2018;Bono et al., 2020;de Bruijn, 2020bde Bruijn, , 2020a. Next generation smart analytical tools are also being developed for automated diagnosis of plants by measuring specific molecular species (e.g., volatile organic compounds (VOC), plant metabolites, etc.) (Lew et al., 2020). Accessible and affordable robots, controlled by scientific data-driven artificial intelligence modules, are being developed for specific applications in agriculture.Various plant developmental stages -seed germination to fruit ripening -produce distinct chemicals (e.g., ethylene). At several instances, chemical profile changes can be correlated with pathogen infection much before real symptoms starts to appear. For instance, tomato leaves infected with three different pathogens showed accurately identifiable VOC profiles before visible symptoms appeared (Li et al., 2019). Handheld and smartphone-based spectrometers along with spectral matching applications through mathematical routines find unique applications in agricultural fields (Samuel et al., 2021) abiotic stresses, such as, nitrogen deficiency (ND) and drought, and biotic stresses, such as, aphid infestation and viral infections, affects common wheat. Changes in lutein, chlorophyll, pheophytin, and beta-carotene were estimated with high-pressure liquid chromatography (HPLC). Aphid infestation was found to be the most detrimental among the stresses investigated. Raman spectral data collected directly from wheat leaves with a handheld spectrometer indicated similar reduction in carotenoid band intensity suggesting possible field applications of the technique.Equally important is estimating chemical composition of nutritionally and medically important molecules in plant produces. If spectral signatures corresponding to a molecule of interest is known, then a spectrometer can be calibrated (e.g., with HPLC, for instance) and predictive models (e.g., partial least square methods, machine learning modules) can be built, which will then allow s