Can metabolic tightening and expansion of co-expression network play a role in stress response and tolerance?

Comparative transcriptome profiling reveals distinct regulatory responses of secondary defensive metabolism in Datura species (Solanaceae) under plant development and herbivory-mediated stress

Differential expression of genes is key to mediating developmental and stress-related plant responses. Here, we addressed the regulation of plant metabolic responses to biotic stress and the developmental variation of defense-related genes in four species of the genus Datura with variable patterns of metabolite accumulation and development. We combine transcriptome profiling with phylogenomic techniques to analyze gene expression and coexpression in plants subjected to damage by a specialist folivore insect. We found (1) common overall gene expression in species of similar chemical profiles, (2) species-specific responses of proteins involved in specialized metabolism, characterized by constant levels of gene expression coupled with transcriptional rearrangement, and (3) induction of transcriptional rearrangement of major terpene and tropane alkaloid genes upon herbivory. Our results indicate differential modulation of terpene and tropane metabolism linked to jasmonate signaling and specific transcription factors to regulate developmental variation and stress programs, and suggest plastic adaptive responses to cope with herbivory. The transcriptional profiles of specialized metabolism shown here reveal complex genetic control of plant metabolism and contribute to understanding the molecular basis of adaptations and the physiological variation of significant ecological traits.

Exploring low-dose gamma radiation effects on monoterpene biosynthesis in Thymus vulgaris: insights into plant defense mechanisms

Thymus vulgaris, commonly known as thyme, is a plant renowned for producing monoterpenes. This study aimed to understand the effects of low-dose gamma radiation, specifically in the range of 1-5 Gy, on various traits of Thymus vulgaris, providing context on its importance in agricultural and medicinal applications. The research explored morpho-physiological, biochemical, and gene-expression responses in thyme plants under no gamma- and gamma-ray exposure conditions. The study revealed complex relationships between gamma-ray doses and plant characteristics. In particular, shoot and root lengths initially increased with low doses (1-3 Gy) but decreased at higher doses (5 Gy), suggesting a dose-dependent threshold effect. Similarly, shoot and root fresh weights displayed an initial increase followed by a decline with increasing doses. Biochemical parameters showed dose-dependent responses, with low to moderate doses (1-3 Gy) stimulating enzyme activities and high doses (5 Gy) inhibiting them. Gene expression analysis was focused on the following specific genes: thymol synthase, γ-terpinene synthase, and carvacrol synthase. Low to moderate doses increased the expression of these genes, resulting in increased production of bioactive compounds. However, higher doses had diminished effects or suppressed gene expression. Metabolite analysis demonstrated dose-dependent responses, with moderate doses enhancing secondary metabolite production, while higher doses provided limited benefits. These findings underscore the implications of using gamma radiation to enhance secondary metabolite production in plants and its potential applications in agriculture, medicine, and environmental science. The study emphasizes the potential of gamma radiation as an external stressor to influence plant responses and highlights the importance of understanding such effects in various fields.

Temperature differences between sites lead to altered phenylpropanoid metabolism in a varietal dependent manner

Elevated temperature has already caused a significant loss of wine growing areas and resulted in inferior fruit quality, particularly in arid and semi-arid regions. The existence of broad genetic diversity in V. vinifera is key in adapting viticulture to climate change; however, a lack of understanding on the variability in berry metabolic response to climate change remains a major challenge to build ad-hoc strategies for quality fruit production. In the present study, we examined the impact of a consistent temperature difference between two vineyards on polyphenol metabolism in the berries of 20 red V. vinifera cultivars across three consecutive seasons (2017-2019). The results emphasize a varietal specific response in the content of several phenylpropanoid metabolites; the interaction factor between the variety and the vineyard location was also found significant. Higher seasonal temperatures were coupled with lower flavonol and anthocyanin contents, but such reductions were not related with the level of expression of phenylpropanoid related genes. Hierarchical clustering analyses of the metabolic data revealed varieties with a location specific response, exceptional among them was Tempranillo, suggesting a greater susceptibility to temperature of this cultivar. In conclusion, our results indicate that the extensive genetic capacity of V. vinifera bears a significant potential to withstand temperature increase associated with climate change.

Genome-wide characterization of the common bean kinome: Catalog and insights into expression patterns and genetic organization

The protein kinase (PK) superfamily is one of the largest superfamilies in plants and is the core regulator of cellular signaling. Even considering this substantial importance, the kinome of common bean (Phaseolus vulgaris) has not been profiled yet. Here, we identified and characterised the complete set of kinases of common bean, performing an in-depth investigation with phylogenetic analyses and measurements of gene distribution, structural organization, protein properties, and expression patterns over a large set of RNA-Sequencing data. Being composed of 1,203 PKs distributed across all P. vulgaris chromosomes, this set represents 3.25% of all predicted proteins for the species. These PKs could be classified into 20 groups and 119 subfamilies, with a more pronounced abundance of subfamilies belonging to the receptor-like kinase (RLK)-Pelle group. In addition to provide a vast and rich reservoir of data, our study supplied insights into the compositional similarities between PK subfamilies, their evolutionary divergences, highly variable functional profile, structural diversity, and expression patterns, modeled with coexpression networks for investigating putative interactions associated with stress response.

From Classical to Modern Computational Approaches to Identify Key Genetic Regulatory Components in Plant Biology

The selection of plant genotypes with improved productivity and tolerance to environmental constraints has always been a major concern in plant breeding. Classical approaches based on the generation of variability and selection of better phenotypes from large variant collections have improved their efficacy and processivity due to the implementation of molecular biology techniques, particularly genomics, Next Generation Sequencing and other omics such as proteomics and metabolomics. In this regard, the identification of interesting variants before they develop the phenotype trait of interest with molecular markers has advanced the breeding process of new varieties. Moreover, the correlation of phenotype or biochemical traits with gene expression or protein abundance has boosted the identification of potential new regulators of the traits of interest, using a relatively low number of variants. These important breakthrough technologies, built on top of classical approaches, will be improved in the future by including the spatial variable, allowing the identification of gene(s) involved in key processes at the tissue and cell levels.

Identifying magnetosome-associated genes in the extended CtrA regulon in Magnetospirillum magneticum AMB-1 using a combinational approach

Magnetotactic bacteria (MTB) are worth studying because of magnetosome biomineralization. Magnetosome biogenesis in MTB is controlled by multiple genes known as magnetosome-associated genes. Recent advances in bioinformatics provide a unique opportunity for studying functions of magnetosome-associated genes and networks that they are involved in. Furthermore, various types of bioinformatics analyses can also help identify genes associated with magnetosome biogenesis. To predict novel magnetosome-associated genes in the extended CtrA regulon, we analyzed expression data of Magnetospirillum magneticum AMB-1 in the GSE35625 dataset in NCBI GEO. We identified 10 potential magnetosome-associated genes using a combinational approach of differential expression analysis, Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analysis, protein-protein interaction network analysis and weighted gene co-expression network analysis. Meanwhile, we also discovered and compared two co-expression modules that most known magnetosome-associated genes belong to. Our comparison indicated the importance of energy on regulating co-expression module structures for magnetosome biogenesis. At the last stage of our research, we predicted at least four real magnetosome-associated genes out of 10 potential genes, based on a comparison of evolutionary trees between known and potential magnetosome-associated genes. Because of the discovery of common subtrees that the stressed species are enriched in, we proposed a hypothesis that multiple types of environmental stress can trigger magnetosome evolution in different waters, and therefore its evolution can recur at different times in various locations on earth. Overall, our research provides useful information for identifying new MTB species and understanding magnetosome biogenesis.

Environment-driven shifts in inter-individual variation and phenotypic integration within subnetworks of the mussel transcriptome and proteome

The environment can alter the magnitude of phenotypic variation among individuals, potentially influencing evolutionary trajectories. However, environmental influences on variation are complex and remain understudied. Populations in heterogeneous environments might exhibit more variation, the amount of variation could differ between benign and stressful conditions, and/or variation might manifest in different ways among stages of the gene‐to‐protein expression cascade or among physiological functions. Here, we explore these three issues by quantifying patterns of inter‐individual variation in both transcript and protein expression levels among California mussels, Mytilus californianus Conrad. Mussels were exposed to five ecologically relevant treatments that varied in the mean and interindividual heterogeneity of body temperature. To target a diverse set of physiological functions, we assessed variation within 19 expression subnetworks, including canonical stress‐response pathways and empirically derived coexpression clusters that represent a diffuse set of cellular processes. Variation in expression was particularly pronounced in the treatments with high mean and heterogeneous body temperatures. However, with few exceptions, environment‐dependent shifts of variation in the transcriptome were not reflected in the proteome. A metric of phenotypic integration provided evidence for a greater degree of constraint on relative expression levels (i.e., stronger correlation) within expression subnetworks in benign, homogeneous environments. Our results suggest that environments that are more stressful on average – and which also tend to be more heterogeneous – can relax these expression constraints and reduce phenotypic integration within biochemical subnetworks. Context‐dependent “unmasking” of functional variation may contribute to interindividual differences in physiological phenotype and performance in stressful environments.

Transcriptome-based metabolic profiling of flavonoids in Agave lechuguilla waste biomass

Agave lechuguilla is one of the most abundant species in arid and semiarid regions of Mexico, and is used to extract fiber. However, 85 % of the harvested plant material is discarded. Previous bioprospecting studies of the waste biomass suggest the presence of bioactive compounds, although the extraction process limited metabolite characterization. This work achieved flavonoid profiling of A. lechuguilla in both processed and non-processed leaf tissues using transcriptomic analysis. Functional annotation of the first de novo transcriptome of A. lechuguilla (255.7 Mbp) allowed identifying genes coding for 33 enzymes and 8 transcription factors involved in flavonoid biosynthesis. The flavonoid metabolic pathway was mostly elucidated by HPLC-MS/MS screening of alcoholic extracts. Key genes of flavonoid synthesis were higher expressed in processed leaf tissues than in non-processed leaves, suggesting a high content of flavonoids and glycoside derivatives in the waste biomass. Targeted HPLC-UV-MS analyses confirmed the concentration of isorhamnetin (1251.96 μg), flavanone (291.51 μg), hesperidin (34.23 μg), delphinidin (24.23 μg), quercetin (15.57 μg), kaempferol (13.71 μg), cyanidin (12.32 μg), apigenin (9.70 μg) and catechin (7.91 μg) per gram of dry residue. Transcriptomic and biochemical profiling concur in the potential of lechuguilla by-products with a wide range of applications in agriculture, feed, food, cosmetics, and pharmaceutical industries.

Computational solutions for modeling and controlling plant response to abiotic stresses: a review with focus on iron deficiency

Computational solutions enable plant scientists to model protein-mediated stress responses and characterize novel gene functions that coordinate responses to a variety of abiotic stress conditions. Recently, density functional theory was used to study proteins active sites and elucidate enzyme conversion mechanisms involved in iron deficiency responsive signaling pathways. Computational approaches for protein homology modeling and the kinetic modeling of signaling pathways have also resolved the identity and function in proteins involved in iron deficiency signaling pathways. Significant changes in gene relationships under other stress conditions, such as heat or drought stress, have been recently identified using differential network analysis, suggesting that stress tolerance is achieved through asynchronous control. Moreover, the increasing development and use of statistical modeling and systematic modeling of transcriptomic data have provided significant insight into the gene regulatory mechanisms associated with abiotic stress responses. These types of in silico approaches have facilitated the plant science community's future goals of developing multi-scale models of responses to iron deficiency stress and other abiotic stress conditions.

High-Resolution Magic Angle Spinning (HR-MAS) NMR-Based Fingerprints Determination in the Medicinal Plant Berberis laurina

Berberis laurina (Berberidaceae) is a well-known medicinal plant used in traditional medicine since ancient times; however, it is scarcely studied to a large-scale fingerprint. This work presents a broad-range fingerprints determination through high-resolution magical angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy, a well-established flexible analytical method and one of most powerful "omics" platforms. It had been intended to describe a large range of chemical compositions in all plant parts. Beyond that, HR-MAS NMR allowed the direct investigation of botanical material (leaves, stems, and roots) in their natural, unaltered states, preventing molecular changes. The study revealed 17 metabolites, including caffeic acid, and berberine, a remarkable alkaloid from the genus Berberis L. The metabolic pattern changes of the leaves in the course of time were found to be seasonally dependent, probably due to the variability of seasonal and environmental trends. This metabolites overview is of great importance in understanding plant (bio)chemistry and mediating plant survival and is influenceable by interacting environmental means. Moreover, the study will be helpful in medicinal purposes, health sciences, crop evaluations, and genetic and biotechnological research.