Catálogo de publicaciones - revistas

<jats:sec><jats:title>Introduction</jats:title><jats:p>The aim of our study was to examine how silicon regulates water uptake by oilseed rape roots under drought conditions and which components of the antioxidant system take part in alleviating stress-induced ROS generation in the roots.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>The study analyzed mainly the changes in the roots and also some changes in the leaves of oilseed rape plants, including total silicon content, relative water content, osmotic potential, stomatal conductance, abscisic acid level, the accumulation of BnPIP1, BnPIP2-1-7 and BnTIP1 aquaporins, and the activity of antioxidant enzymes.</jats:p></jats:sec><jats:sec><jats:title>Results and discussion</jats:title><jats:p>It was shown that plants growing in well-watered conditions and supplemented with silicon accumulate smaller amounts of this element in the roots and also have higher relative water content in the leaves compared to the control plants. It was demonstrated for the first time that BnTIP1 accumulation in oilseed rape roots is reduced under drought compared to wellwatered plants, and that this effect is intensified in plants supplemented with silicon. In addition, it was shown that silicon supplementation of oilseed rape increases catalase activity in the roots, which correlates with their high metabolic activity under drought and ultimately stimulates their growth. It was shown that silicon improves water balance in oilseed rape plants subjected to drought stress, and that an important role in these processes is played by tonoplast aquaporins. In addition, it was demonstrated that silicon reduces oxidative stress in roots under drought conditions by increasing the activity of catalase.</jats:p></jats:sec>

<jats:sec><jats:title>Introduction</jats:title><jats:p>Phytobiomes have a significant impact on plant health. The microbiome of <jats:italic>Cannabis sativa</jats:italic> is particularly interesting both because of renewed interest in this crop and because it is commercially propagated in two different ways (i.e. clonally and by seed). Angiosperms obtain a founding population of seed-borne endophytes from their seed-bearing parent. This study examines the influence of both seed and soil-derived bacteria on the endospheres of cannabis seedlings of both hemp- and drug-types.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A multi-factorial metagenomic study was conducted with three cannabis genotypes and two soil sources, which were tested both before and after autoclave sterilization. Seedlings were grown on soil, then rinsed and surface-sterilized, and 16S rDNA amplicons from seedling endophytes were sequenced, taxonomically classified, and used to estimate alpha- and beta-diversity in Qiime2. The statistical significance of differences in seedling microbiomes across treatments was tested, and PiCRUST2 was used to infer the functional relevance of these differences.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Soil was found to have a profound effect on the alpha-diversity, beta-diversity, relative abundance, and functional genes of endophytic bacteria in germinating cannabis seedlings. Additionally, there was a significant effect of cannabis genotype on beta diversity, especially when genotypes were grown in sterilized soil. <jats:italic>Gammaproteobacteria</jats:italic> and <jats:italic>Bacilli</jats:italic> were the two most abundant taxa and were found in all genotypes and soil types, including sterilized soil.</jats:p></jats:sec><jats:sec><jats:title>Discussion</jats:title><jats:p>The results indicated that a component of cannabis seedling endosphere microbiomes is seed-derived and conserved across the environments tested. Functional prediction of seedling endophytes using piCRUST suggested a number of important functions of seed-borne endophytes in cannabis including nutrient and amino acid cycling, hormone regulation, and as precursors to antibiotics. This study suggested both seed and soil play a critical role in shaping the microbiome of germinating cannabis seedlings.</jats:p></jats:sec>

<jats:p>Plants are the richest source of specialized metabolites. The specialized metabolites offer a variety of physiological benefits and many adaptive evolutionary advantages and frequently linked to plant defense mechanisms. Medicinal plants are a vital source of nutrition and active pharmaceutical agents. The production of valuable specialized metabolites and bioactive compounds has increased with the improvement of transgenic techniques like gene silencing and gene overexpression. These techniques are beneficial for decreasing production costs and increasing nutritional value. Utilizing biotechnological applications to enhance specialized metabolites in medicinal plants needs characterization and identification of genes within an elucidated pathway. The breakthrough and advancement of CRISPR/Cas-based gene editing in improving the production of specific metabolites in medicinal plants have gained significant importance in contemporary times. This article imparts a comprehensive recapitulation of the latest advancements made in the implementation of CRISPR-gene editing techniques for the purpose of augmenting specific metabolites in medicinal plants. We also provide further insights and perspectives for improving metabolic engineering scenarios in medicinal plants.</jats:p>

<jats:p>The timing of floral budbreak in apple has a significant effect on fruit production and quality. Budbreak occurs as a result of a complex molecular mechanism that relies on accurate integration of external environmental cues, principally temperature. In the pursuit of understanding this mechanism, especially with respect to aiding adaptation to climate change, a QTL at the top of linkage group (LG) 9 has been identified by many studies on budbreak, but the genes underlying it remain elusive. Here, together with a dessert apple core collection of 239 cultivars, we used a targeted capture sequencing approach to increase SNP resolution in apple orthologues of known or suspected <jats:italic>A. thaliana</jats:italic> flowering time-related genes, as well as approximately 200 genes within the LG9 QTL interval. This increased the 275 223 SNP Axiom<jats:sup>®</jats:sup> Apple 480 K array dataset by an additional 40 857 markers. Robust GWAS analyses identified <jats:italic>MdPRX10</jats:italic>, a peroxidase superfamily gene, as a strong candidate that demonstrated a dormancy-related expression pattern and down-regulation in response to chilling. <jats:italic>In-silico</jats:italic> analyses also predicted the residue change resulting from the SNP allele associated with late budbreak could alter protein conformation and likely function. Late budbreak cultivars homozygous for this SNP allele also showed significantly up-regulated expression of <jats:italic>C-REPEAT BINDING FACTOR</jats:italic> (<jats:italic>CBF</jats:italic>) genes, which are involved in cold tolerance and perception, compared to reference cultivars, such as Gala. Taken together, these results indicate a role for <jats:italic>MdPRX10</jats:italic> in budbreak, potentially via redox-mediated signaling and <jats:italic>CBF</jats:italic> gene regulation. Moving forward, this provides a focus for developing our understanding of the effects of temperature on flowering time and how redox processes may influence integration of external cues in dormancy pathways.</jats:p>

<jats:p>Advancements in phenotyping technology have enabled plant science researchers to gather large volumes of information from their experiments, especially those that evaluate multiple genotypes. To fully leverage these complex and often heterogeneous data sets (i.e. those that differ in format and structure), scientists must invest considerable time in data processing, and data management has emerged as a considerable barrier for downstream application. Here, we propose a pipeline to enhance data collection, processing, and management from plant science studies comprising of two newly developed open-source programs. The first, called AgTC, is a series of programming functions that generates comma-separated values file templates to collect data in a standard format using either a lab-based computer or a mobile device. The second series of functions, AgETL, executes steps for an <jats:italic>Extract</jats:italic>-<jats:italic>Transform</jats:italic>-<jats:italic>Load</jats:italic> (ETL) data integration process where data are extracted from heterogeneously formatted files, transformed to meet standard criteria, and loaded into a database. There, data are stored and can be accessed for data analysis-related processes, including dynamic data visualization through web-based tools. Both AgTC and AgETL are flexible for application across plant science experiments without programming knowledge on the part of the domain scientist, and their functions are executed on Jupyter Notebook, a browser-based interactive development environment. Additionally, all parameters are easily customized from central configuration files written in the human-readable YAML format. Using three experiments from research laboratories in university and non-government organization (NGO) settings as test cases, we demonstrate the utility of AgTC and AgETL to streamline critical steps from data collection to analysis in the plant sciences.</jats:p>

<jats:p>Legumes are essential to healthy agroecosystems, with a rich phytochemical content that impacts overall human and animal well-being and environmental sustainability. While these phytochemicals can have both positive and negative effects, legumes have traditionally been bred to produce genotypes with lower levels of certain plant phytochemicals, specifically those commonly termed as ‘antifeedants’ including phenolic compounds, saponins, alkaloids, tannins, and raffinose family oligosaccharides (RFOs). However, when incorporated into a balanced diet, such legume phytochemicals can offer health benefits for both humans and animals. They can positively influence the human gut microbiome by promoting the growth of beneficial bacteria, contributing to gut health, and demonstrating anti-inflammatory and antioxidant properties. Beyond their nutritional value, legume phytochemicals also play a vital role in soil health. The phytochemical containing residues from their shoots and roots usually remain in-field to positively affect soil nutrient status and microbiome diversity, so enhancing soil functions and benefiting performance and yield of following crops. This review explores the role of legume phytochemicals from a ‘one health’ perspective, examining their on soil- and gut-microbial ecology, bridging the gap between human nutrition and agroecological science.</jats:p>

<jats:p><jats:italic>Phellodendron amurense</jats:italic> is the essential source of bisbenzylisoquinoline alkaloids (BIAs), making it a highly valued raw material in traditional Chinese medicine. The plant’s root secondary metabolism is intricately linked to the microbial communities that surround it. However, the root-associated microbiomes of <jats:italic>P. amurense</jats:italic>, as well as the potential correlation between its bioactive compounds and these microbiomes, remain poorly understood. Here, the metabolic profiles of root, rhizosphere, and bulk soils of <jats:italic>P. amurense</jats:italic> revealed the dramatic differences in the relative content of plant-specialized metabolites. A total of 31, 21, and 0 specialized metabolites in <jats:italic>P. amurense</jats:italic> were identified in the root, rhizosphere soil, and bulk soil, respectively, with higher content of the seven major BIAs observed in the rhizosphere compared with that in the bulk soils. The composition of the bulk and rhizosphere microbiomes was noticeably distinct from that of the endospheric microbiome. The phylum Cyanobacteria accounted for over 60% of the root endosphere communities, and the α-diversity in root was the lowest. Targeted seven BIAs, namely, berberine, palmatine, magnocurarine, phellodendrine, jatrorrhizine, tetrahydropalmatine, and magnoflorine, were significantly positively correlated with Nectriaceae and Sphingobacteriaceae. This study has illuminated the intricate interaction networks between <jats:italic>P. amurense</jats:italic> root-associated microorganisms and their key chemical compounds, providing the theoretical foundation for discovering biological fertilizers and laying the groundwork for cultivating high-quality medicinal plants.</jats:p>

<jats:p>Numerous studies have revealed that past geological events and climatic fluctuations had profoundly affected the genetic structure and demographic patterns of species. However, related species with overlapping ranges may have responded to such environmental changes in different ways. In this study, we compared the genetic structure and population dynamics of two typical desert shrubs with overlapping distributions in northern China, <jats:italic>Nitraria tangutorum</jats:italic> and <jats:italic>Nitraria sphaerocarpa</jats:italic>, based on chloroplast DNA (cpDNA) variations and species distribution models. We sequenced two cpDNA fragments (<jats:italic>trn</jats:italic>H-<jats:italic>trn</jats:italic>A and <jats:italic>atp</jats:italic>H-<jats:italic>atp</jats:italic>I) in 633 individuals sampled from 52 natural populations. Twenty-four chlorotypes, including eight rare chlorotypes, were identified, and a single dominant haplotype (H4) widely occurred in the entire geographical ranges of the two species. There were also a few distinctive chlorotypes fixed in different geographical regions. Population structure analyses suggested that the two species had significantly different levels of total genetic diversity and interpopulation differentiation, which was highly likely correlated with the special habitat preferences of the two species. A clear phylogeographic structure was identified to exist among populations of <jats:italic>N. sphaerocarpa</jats:italic>, but not exist for <jats:italic>N. tangutorum</jats:italic>. The neutral tests, together with the distribution of pairwise differences revealed that <jats:italic>N. tangutorum</jats:italic> experienced a sudden demographic expansion, and its expansion approximately occurred between 21 and 7 Kya before present, while a rapid range expansion was not identified for <jats:italic>N. sphaerocarpa</jats:italic>. The ecological niche modeling (ENM) analysis indicated that the potential ranges of two species apparently fluctuated during the past and present periods, with obvious contraction in the Last Glacial Maximum (LGM) and recolonization in the present, respectively, comparing to the Last Interglacial (LIG). These findings suggest that the two species extensively occurred in the Northwest of China before the Quaternary, and the current populations of them originated from a few separated glacial refugia following their habitat fragmentation in the Quarternary. Our results provide new insights on the impact of past geological and climatic fluctuations on the population dynamics of desert plants in northwestern China, and further enforce the hypothesis that there were several independent glacial refugia for these species during the Quaternary glaciations.</jats:p>

<jats:sec><jats:title>Introduction</jats:title><jats:p>Drought detection, spanning from early stress to severe conditions, plays a crucial role in maintaining productivity, facilitating recovery, and preventing plant mortality. While handheld thermal cameras have been widely employed to track changes in leaf water content and stomatal conductance, research on thermal image classification remains limited due mainly to low resolution and blurry images produced by handheld cameras.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>In this study, we introduce a computer vision pipeline to enhance the significance of leaf-level thermal images across 27 distinct cotton genotypes cultivated in a greenhouse under progressive drought conditions. Our approach involved employing a customized software pipeline to process raw thermal images, generating leaf masks, and extracting a range of statistically relevant thermal features (e.g., min and max temperature, median value, quartiles, etc.). These features were then utilized to develop machine learning algorithms capable of assessing leaf hydration status and distinguishing between well-watered (WW) and dry-down (DD) conditions.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Two different classifiers were trained to predict the plant treatment—random forest and multilayer perceptron neural networks—finding 75% and 78% accuracy in the treatment prediction, respectively. Furthermore, we evaluated the predicted versus true labels based on classic physiological indicators of drought in plants, including volumetric soil water content, leaf water potential, and chlorophyll <jats:italic>a</jats:italic> fluorescence, to provide more insights and possible explanations about the classification outputs.</jats:p></jats:sec><jats:sec><jats:title>Discussion</jats:title><jats:p>Interestingly, mislabeled leaves mostly exhibited notable responses in fluorescence, water uptake from the soil, and/or leaf hydration status. Our findings emphasize the potential of AI-assisted thermal image analysis in enhancing the informative value of common heterogeneous datasets for drought detection. This application suggests widening the experimental settings to be used with deep learning models, designing future investigations into the genotypic variation in plant drought response and potential optimization of water management in agricultural settings.</jats:p></jats:sec>

<jats:sec><jats:title>Introduction</jats:title><jats:p><jats:italic>Bromus japonicus</jats:italic> is one of the most notorious agricultural weeds in China. The long-term use of ALS-inhibiting herbicides has led to rapid evolution of herbicide resistance in <jats:italic>B. japonicus</jats:italic>. <jats:italic>B. japonicus</jats:italic> population (BJ-R) surviving mesosulfuron-methyl treatment was collected from wheatland. Here, we aimed to confirm the resistance mechanisms in this putative resistant population.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>The dose-reponse tests were used to test the resistance level of the <jats:italic>B. japonicus</jats:italic> to ALS-inhibiting herbicides. Pretreatment with P450 and GST inhibitors and GST activity assays were used to determine whether P450 or GST was involved in the resistance of the BJ-R population. Sanger sequencing was used to analyse the ALS mutation of the BJ-R population. RT-qPCR was used to confirm the the expression levels of the ALS gene in mesosulfuron-methyl -resistant (BJ-R) and-susceptible (BJ-S) <jats:italic>B. japonicus</jats:italic>. An in vitro ALS activity assay was used to determine the ALS activity of the BJ-R and BJ-S populations. Homology modelling and docking were used to determine the binding energy of the BJ-R and BJ-S populations with ALS-inhibiting herbicides.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p><jats:italic>B. japonicus</jats:italic> population (BJ-R) was confirmed to be 454- and 2.7-fold resistant to the SU herbicides mesosulfuron-methyl and nicosulfuron, and 7.3-, 2.3-, 1.1- and 10.8-fold resistant to the IMI herbicide imazamox, the TP herbicide penoxsulam, the PTB herbicide pyribenzoxim and the SCT herbicide flucarbazone-sodium, respectively, compared with its susceptible counterpart (BJ-S). Neither a P450 inhibitor nor a GST inhibitor could reverse the level of resistance to mesosulfuron-methyl in BJ-R. In addition, no significant differences in GST activity were found between the BJ-R and BJ-S. <jats:italic>ALS</jats:italic> gene sequencing revealed a Pro-197-Thr mutation in BJ-R, and the gene expression had no significant differences between the BJ-R and BJ-S. The ALS activity of BJ-R was 106-fold more tolerant to mesosulfuron-methyl than that of BJ-S. Molecular docking showed that the binding energy of the ALS active site and mesosulfuron-methyl was changed from -6.67 to -4.57 kcal mol<jats:sup>-1</jats:sup> due to the mutation at position 197.</jats:p></jats:sec><jats:sec><jats:title>Discussion</jats:title><jats:p>These results suggested that the Pro-197-Thr mutation was the main reason for the high resistance level of BJ-R to mesosulfuron-methyl. Unlike previous reports of the cross-resistance pattern conferred by this mutation, we firstly documented that the Pro-197-Thr mutation confers broad cross-resistance spectrums to ALS-inhibiting herbicides in <jats:italic>B. japonicus</jats:italic>.</jats:p></jats:sec>