Search for: All records

Abstract Phosphorylation of the penultimate residue, threonine (pen-Thr), of plasma membrane (PM) H+-ATPase is essential for its activation and blue light (BL)-induced stomatal opening. However, the regulatory mechanism of action of PM H+-ATPase pen-Thr phosphorylation is not completely understood. Here, we performed screening using a protein kinase inhibitor library and found that tyrphostin AG126 inhibited phosphorylation of PM H+-ATPase pen-Thr in guard cells in response to light and fungal toxin fusicoccin (FC), in addition to inhibition of light- and FC-induced stomatal opening. Analysis of the structure–activity relationship using AG126 derivatives revealed the hydroxyl group at the C-5 position of the compound to be essential for its activity. We further characterized one AG126 derivative, AGD-1, which effectively suppressed BL-induced stomatal opening with a half-inhibitory concentration of 2.0 μM. AGD-1 inhibited PM H+-ATPase pen-Thr phosphorylation in guard cells in response to BL and FC. In addition, AGD-1 suppressed FC-induced PM H+-ATPase pen-Thr phosphorylation in mesophyll cell protoplasts, implying that the effect of AGD-1 is not specific to guard cells. Furthermore, to improve the permeability of AGD-1, we synthesized acetylated AGD-1 (AcAGD-1), which was found to suppress BL- and FC-induced stomatal opening. AcAGD-1 suppressed light-induced PM H+-ATPase pen-Thr phosphorylation, but not Thr881 phosphorylation, in leaf discs, which is important for guard cell PM H+-ATPase activation in addition to pen-Thr phosphorylation. This study identified a novel stomatal opening inhibitor capable of specifically inhibiting PM H+-ATPase pen-Thr phosphorylation. 

Abstract Plant metabolomes are structurally diverse. One of the most popular techniques for sampling this diversity is liquid chromatography–mass spectrometry (LC‐MS), which typically detects thousands of peaks from single organ extracts, many representing true metabolites. These peaks are usually annotated using in‐house retention time or spectral libraries, in silico fragmentation libraries, and increasingly through computational techniques such as machine learning. Despite these advances, over 85% of LC‐MS peaks remain unidentified, posing a major challenge for data analysis and biological interpretation. This bottleneck limits our ability to fully understand the diversity, functions, and evolution of plant metabolites. In this review, we first summarize current approaches for metabolite identification, highlighting their challenges and limitations. We further focus on alternative strategies that bypass the need for metabolite identification, allowing researchers to interpret global metabolic patterns and pinpoint key metabolite signals. These methods include molecular networking, distance‐based approaches, information theory–based metrics, and discriminant analysis. Additionally, we explore their practical applications in plant science and highlight a set of useful tools to support researchers in analyzing complex plant metabolomics data. By adopting these approaches, researchers can enhance their ability to uncover new insights into plant metabolism. 

Abstract Diketopiperazines (DKPs) are chemically and functionally diverse cyclic dipeptides associated primarily with microbes. Few DKPs have been reported from plants and animals; the best characterized is cyclo(His-Pro), found in the mammalian central nervous system, where it arises from the proteolytic cleavage of a thyrotropin-releasing tripeptide hormone. Herein, we report the identification of cyclo(His-Pro) in Arabidopsis (Arabidopsis thaliana), where its levels increase upon abiotic stress conditions, including high salt, heat, and cold. To screen for potential protein targets, we used isothermal shift assays, which examine changes in protein-melting stability upon ligand binding. Among the identified proteins, we focused on the glycolytic enzyme, cytosolic glyceraldehyde-3-phosphate dehydrogenase (GAPC1). Binding between the GAPC1 protein and cyclo(His-Pro) was validated using nano-differential scanning fluorimetry and microscale thermophoresis, and we could further demonstrate that cyclo(His-Pro) inhibits GAPC1 activity with an IC50 of ∼200 μm. This inhibition was conserved in human GAPDH. Inhibition of glyceraldehyde-3-phosphate dehydrogenase activity has previously been reported to reroute carbon from glycolysis toward the pentose phosphate pathway. Accordingly, cyclo(His-Pro) supplementation augmented NADPH levels, increasing the NADPH/NADP+ ratio. Phenotypic screening revealed that plants supplemented with cyclo(His-Pro) were more tolerant to high-salt stress, as manifested by higher biomass, which we show is dependent on GAPC1/2. Our work reports the identification and functional characterization of cyclo(His-Pro) as a modulator of glyceraldehyde-3-phosphate dehydrogenase in plants. 

Abstract Global crop production faces increasing threats from the rise in frequency, duration, and intensity of drought and heat stress events due to climate change. Most staple food crops, including wheat, rice, soybean, and corn that provide over half of the world’s caloric intake, are not well adapted to withstand heat or drought. Efforts to breed or engineer stress-tolerant crops have had limited success due to the complexity of tolerance mechanisms and the variability of agricultural environments. Effective solutions require a shift towards fundamental research that incorporates realistic agricultural settings and focuses on practical outcomes for farmers. This review explores the genetic and environmental factors affecting heat and drought tolerance in major crops, examines the physiological and molecular mechanisms underlying these stress responses, and evaluates the limitations of current breeding programs and models. It also discusses emerging technologies and approaches that could enhance crop resilience, such as synthetic biology, advanced breeding techniques, and high-throughput phenotyping. Finally, this review emphasizes the need for interdisciplinary research and collaboration with stakeholders to translate fundamental research into practical agricultural solutions. 

Abstract To thrive in extreme conditions, organisms have evolved a diverse arsenal of adaptations that confer resilience. These species, their traits, and the mechanisms underlying them comprise a valuable resource that can be mined for numerous conceptual insights and applied objectives. One of the most dramatic adaptations to water limitation is desiccation tolerance. Understanding the mechanisms underlying desiccation tolerance has important potential implications for medicine, biotechnology, agriculture, and conservation. However, progress has been hindered by a lack of standardization across sub-disciplines, complicating the integration of data and slowing the translation of basic discoveries into practical applications. Here, we synthesize current knowledge on desiccation tolerance across evolutionary, ecological, physiological, and cellular scales to provide a roadmap for advancing desiccation tolerance research. We also address critical gaps and technical roadblocks, highlighting the need for standardized experimental practices, improved taxonomic sampling, and the development of new tools for studying biology in a dry state. We hope that this perspective can serve as a roadmap to accelerating research breakthroughs and unlocking the potential of desiccation tolerance to address global challenges related to climate change, food security, and health. 

ABSTRACT For most species, transcriptome data are much more readily available than genome data. Without a reference genome, gene calling is cumbersome and inaccurate because of the high degree of redundancy in de novo transcriptome assemblies. To simplify and increase the accuracy of de novo transcriptome assembly in the absence of a reference genome, we developed UnigeneFinder. Combining several clustering methods, UnigeneFinder substantially reduces the redundancy typical of raw transcriptome assemblies. This pipeline offers an effective solution to the problem of inflated transcript numbers, achieving a closer representation of the actual underlying genome. UnigeneFinder performs comparably or better, compared with existing tools, on plant species with varying genome complexities. UnigeneFinder is the only available transcriptome redundancy solution that fully automates the generation of primary transcript, coding region, and protein sequences, analogous to those available for high‐quality reference genomes. These features, coupled with the pipeline’s cross‐platform implementation, focus on automation, and an accessible, user‐friendly interface, make UnigeneFinder a useful tool for many downstream sequence‐based analyses in nonmodel organisms lacking a reference genome, including differential gene expression analysis, accurate ortholog identification, functional enrichments, and evolutionary analyses. UnigeneFinder also runs efficiently both on high‐performance computing (HPC) systems and personal computers, further reducing barriers to use. 

Abstract The Plant Metabolic Network (PMN) is a free online database of plant metabolism available at https://plantcyc.org. The latest release, PMN 16, provides metabolic databases representing >1200 metabolic pathways, 1.3 million enzymes, >8000 metabolites, >10 000 reactions and >15 000 citations for 155 plant and green algal genomes, as well as a pan-plant reference database called PlantCyc. This release contains 29 additional genomes compared with PMN 15, including species listed by the African Orphan Crop Consortium and nonflowering plant species. Furthermore, 52 new enzymes with experimentally supported function information have been included in this release. The single-species databases contain a combination of experimental information from the literature and computationally predicted information obtained through PMN’s database generation pipeline for a single species, while PlantCyc contains only experimental information but for any species within Viridiplantae. PMN is a comprehensive resource for querying, visualizing, analyzing and interpreting omics data with metabolic knowledge. It also serves as a useful and interactive tool for teaching plant metabolism.