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Plants have developed sophisticated mechanisms to survive in dynamic environments. Plants can communicate via volatile organic compounds (VOCs) to warn neighboring plants of threats. In most cases, VOCs act as positive regulators of plant defense. However, the communication and role of volatiles in response to drought stress are poorly understood. Here, we showed that tea plants release numerous VOCs. Among them, methyl salicylate (MeSA), benzyl alcohol, and phenethyl alcohol markedly increased under drought stress. Interestingly, further experiments revealed that drought-induced MeSA lowered the abscisic acid (ABA) content in neighboring plants by reducing 9-cis-epoxycarotenoid dioxygenase (NCED) gene expression, resulting in inhibition of stomatal closure and ultimately decreasing early drought tolerance in neighboring plants. Exogenous application of ABA reduced the wilting of tea plants caused by MeSA exposure. Exposure of Nicotiana benthamiana to MeSA also led to severe wilting, indicating that the ability of drought-induced MeSA to reduce early drought tolerance in neighboring plants may be conserved in other plant species. Taken together, these results provide evidence that drought-induced volatiles can reduce early drought tolerance in neighboring plants and lay a novel theoretical foundation for optimizing plant density and spacing.
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http://dx.doi.org/10.1038/s41438-021-00704-x | DOI Listing |
J Eval Clin Pract
September 2025
St. Luke's Health System, Boise, Idaho, USA.
Introduction: Voucher-based food as medicine programs have become a common method to help reduce the burden of chronic disease. While recent studies find these programs reduce HbA1c, few of these studies included a comparison group.
Objective: This article evaluates the impact of a clinically based voucher program on HbA1c of diabetic patients.
Ecol Lett
September 2025
State Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.
Symbioses with mycorrhizal fungi and nitrogen-fixing bacteria (NFB) enhance nitrogen (N) acquisition in host plants and may promote N transfer to neighbouring plants through mycorrhizal networks (MN). Nevertheless, the extent and mechanisms of this transfer remain unclear. On the basis of a synthesis of N labeling studies, we show that MN and NFB synergistically enhanced interplant N sharing.
View Article and Find Full Text PDFJ Plant Physiol
September 2025
Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy.
Weeds are one of the major constraints for wheat productivity, causing significant yield losses worldwide. While chemical control is the most used practice to overcome weed damage, its efficacy is challenged by increasing weed resistance to most used herbicides, which is an expanding phenomenon caused by herbicide overuse/misuse. Modern wheat varieties are less able to perceive the presence of weeds than old varieties and are therefore less competitive against them and require chemical control to ensure adequate yields.
View Article and Find Full Text PDFPLoS One
September 2025
Genetics, Biotechnology and Seed Science Unit (GBioS), Laboratory of Plant Production, Physiology and Plant Breeding (PAGEV), School of Plant Sciences, University of Abomey-Calavi, Abomey-Calavi, Republic of Benin.
Mesosphaerum suaveolens (L.) Kuntze is a wild species with many biological activities in medicine. The species can potentially serve as a pesticide in agriculture thanks to its high content of volatile compounds.
View Article and Find Full Text PDFFuture Med Chem
September 2025
College of Mathematics and Computer Science, Dali University, Dali Old City, China.
Aim: Generating molecules with specific chemical properties for target proteins can accelerate the drug development process and open new avenues for developing treatments for diseases with known pathogenic target proteins. However, current approaches to generate molecules with desired properties face several challenges, including prolonged generation time, complexity in learning parameters, and unqualified chemical properties.
Results/methodology: To address these issues, we proposed a structure-aware diffusion model, termed KGMG.