Gold nanoparticles-based biosensor can detect drought stress in tomato by ultrasensitive and specific determination of miRNAs

Transcriptome sequencing and metabolome analysis reveal the molecular mechanism of Salvia miltiorrhiza in response to drought stress

Salvia miltiorrhiza is commonly used as a Chinese herbal medicine to treat different cardiovascular and cerebrovascular illnesses due to its active ingredients. Environmental conditions, especially drought stress, can affect the yield and quality of S. miltiorrhiza. However, moderate drought stress could improve the quality of S. miltiorrhiza without significantly reducing the yield, and the mechanism of this initial drought resistance is still unclear. In our study, transcriptome and metabolome analyses of S. miltiorrhiza under different drought treatment groups (CK, A, B, and C groups) were conducted to reveal the basis for its drought tolerance. We discovered that the leaves of S. miltiorrhiza under different drought treatment groups had no obvious shrinkage, and the malondialdehyde (MDA) contents as well as superoxide dismutase (SOD) and peroxidase (POD) activities dramatically increased, indicating that our drought treatment methods were moderate, and the leaves of S. miltiorrhiza began to initiate drought resistance. The morphology of root tissue had no significant change under different drought treatment groups, and the contents of four tanshinones significantly enhanced. In all, 5213, 6611, and 5241 differentially expressed genes (DEGs) were shared in the A, B, and C groups compared with the CK group, respectively. The results of KEGG and co-expression analysis showed that the DEGs involved in plant-pathogen interactions, the MAPK signaling pathway, phenylpropanoid biosynthesis, flavonoid biosynthesis, and plant hormone signal transduction responded to drought stress and were strongly correlated with tanshinone biosynthesis. Furthermore, the results of metabolism analysis indicated that 67, 72, and 92 differentially accumulated metabolites (DAMs), including fumarate, ferulic acid, xanthohumol, and phytocassanes, which were primarily involved in phenylpropanoid biosynthesis, flavonoid biosynthesis, and diterpenoid biosynthesis pathways, were detected in these groups. These discoveries provide valuable information on the molecular mechanisms by which S. miltiorrhiza responds to drought stress and will facilitate the development of drought-resistant and high-quality S. miltiorrhiza production.

Physical and physiological characteristics, as well as miRNA concentrations, are affected by the storage time of tomatoes

This study aims to investigate the potential of miRNA measurements in indicating tomato quality during transportation and storage. The impact of storage temperature, duration, and mechanical loading on tomato senescence, carotenoid content, total soluble solids, fruit firmness, and relevant miRNA concentrations were examined. Significant two-way or three-way interactions were observed between storage conditions and physical/physiological characteristics (excluding carotenoids). Remarkably, significant three-way interactions were found between storage conditions and miRNA concentrations. Strong correlations were observed between the physiological characteristics of the tomatoes and their miRNA concentrations. These findings suggest that measuring miRNAs could serve as a convenient and portable method for evaluating postharvest fruit quality, reducing reliance on labor-intensive laboratory techniques.

Machine learning provides specific detection of salt and drought stresses in cucumber based on miRNA characteristics

BACKGROUND

Specific detection of the type and severity of plant abiotic stresses helps prevent yield loss by considering timely actions. This study introduces a novel method to detect the type and severity of stress in cucumber plants under salinity and drought conditions. Various features, i.e., morphological (image textural features), physiological/biochemical (relative water content, chlorophyll, catalase activity, anthocyanins, phenol content, and proline), as well as miRNA characteristics (the concentration of miRNA-156a, miRNA-166i, miRNA-399g, and miRNA-477b) were extracted from plant leaves, and machine learning methods were used to predict the type and severity of stress by having these features. Support vector machine (SVM) with parameters optimized by genetic algorithm (GA) and particle swarm optimization (PSO) was used for machine learning.

RESULTS

The coefficient of determination of predicting the stress type and severity in plants under both stresses was 0.61, 0.82, and 0.99 using morphological, physiological/biochemical, and miRNA characteristics, respectively. This reveals machine learning methods optimized by metaheuristic optimization techniques can provide specific detection of salt and drought stresses in cucumber plants based on miRNA characteristics. Among the study miRNAs, miRNA-477b and miRNA-399g had the highest and lowest contribution to salt and drought stresses, respectively.

CONCLUSIONS

Comapred to conventional plant traits, miRNAs are more reliable features for providing us with valuable information about plant abiotic diseases at early stages. Using an electrochemical miRNA biosensor similar to one used in this work to measure the miRNA concentration in plant leaves and using a machine learning algorithm such as SVM enable farmers to detect the salt and drought stress at early stages in cucumber plants with very high accuracy.

Modern analytical and bioanalytical technologies and concepts for smart and precision farming

Unpredictable natural disasters, disease outbreaks, climate change, pollution, and war constantly threaten food crop production. Smart and precision farming encourages using information or data obtained by using advanced technology (sensors, AI, and IoT) to improve decision-making in agriculture and achieve high productivity. For instance, weather prediction, nutrient information, pollutant assessment, and pathogen determination can be made with the help of new analytical and bioanalytical methods, demonstrating the potential for societal impact such as environmental, agricultural, and food science. As a rising technology, biosensors can be a potential tool to promote smart and precision farming in developing and underdeveloped countries. This review emphasizes the role of on-field, in vivo, and wearable biosensors in smart and precision farming, especially those biosensing systems that have proven with suitably complex and analytically challenging samples. The development of various agricultural biosensors in the past five years that fulfill market requirements such as portability, low cost, long-term stability, user-friendliness, rapidity, and on-site monitoring will be reviewed. The challenges and prospects for developing IoT and AI-integrated biosensors to increase crop yield and advance sustainable agriculture will be discussed. Using biosensors in smart and precision farming would ensure food security and revenue for farming communities.

Potential of nanobiosensor in sustainable agriculture: the state-of-art

A rapid surge in world population leads to an increase in worldwide demand for agricultural products. Nanotechnology and its applications in agriculture have appeared as a boon to civilization with enormous potential in transforming conventional farming practices into redefined farming activities. Low-cost portable nanobiosensors are the most effective diagnostic tool for the rapid on-site assessment of plant and soil health including plant biotic and abiotic stress level, nutritional status, presence of hazardous chemicals in soil, etc. to maintain proper farming and crop productivity. Nanobiosensors detect physiological signals and convert them into standardized detectable signals. In order to achieve a reliable sensing analysis, nanoparticles can aid in signal amplification and sensor sensitivity by lowering the detection limit. The high selectivity and sensitivity of nanobiosensors enable early detection and management of targeted abnormalities. This study identifies the types of nanobiosensors according to the target application in agriculture sector.

The role of nanoparticles in plant biochemical, physiological, and molecular responses under drought stress: A review

Drought stress (DS) is a serious challenge for sustaining global crop production and food security. Nanoparticles (NPs) have emerged as an excellent tool to enhance crop production under current rapid climate change and increasing drought intensity. DS negatively affects plant growth, physiological and metabolic processes, and disturbs cellular membranes, nutrient and water uptake, photosynthetic apparatus, and antioxidant activities. The application of NPs protects the membranes, maintains water relationship, and enhances nutrient and water uptake, leading to an appreciable increase in plant growth under DS. NPs protect the photosynthetic apparatus and improve photosynthetic efficiency, accumulation of osmolytes, hormones, and phenolics, antioxidant activities, and gene expression, thus providing better resistance to plants against DS. In this review, we discuss the role of different metal-based NPs to mitigate DS in plants. We also highlighted various research gaps that should be filled in future research studies. This detailed review will be an excellent source of information for future researchers to adopt nanotechnology as an eco-friendly technique to improve drought tolerance.

Regulatory role of microRNAs (miRNAs) in the recent development of abiotic stress tolerance of plants

MicroRNAs (miRNAs) are a distinct groups of single-stranded non-coding, tiny regulatory RNAs approximately 20-24 nucleotides in length. miRNAs negatively influence gene expression at the post-transcriptional level and have evolved considerably in the development of abiotic stress tolerance in a number of model plants and economically important crop species. The present review aims to deliver the information on miRNA-mediated regulation of the expression of major genes or Transcription Factors (TFs), as well as genetic and regulatory pathways. Also, the information on adaptive mechanisms involved in plant abiotic stress responses, prediction, and validation of targets, computational tools, and databases available for plant miRNAs, specifically focus on their exploration for engineering abiotic stress tolerance in plants. The regulatory function of miRNAs in plant growth, development, and abiotic stresses consider in this review, which uses high-throughput sequencing (HTS) technologies to generate large-scale libraries of small RNAs (sRNAs) for conventional screening of known and novel abiotic stress-responsive miRNAs adds complexity to regulatory networks in plants. The discoveries of miRNA-mediated tolerance to multiple abiotic stresses, including salinity, drought, cold, heat stress, nutritional deficiency, UV-radiation, oxidative stress, hypoxia, and heavy metal toxicity, are highlighted and discussed in this review.

Nanoparticles as potential hallmarks of drought stress tolerance in plants

Plants are inevitably exposed to drought stress limiting their growth and causing yield loss, thus inciting food crises across the world. Nanoparticles (NPs) are regarded as effective and promising tools for modulation of crop yield to overcome current and future constraints in sustainable agricultural production by upgrading the plant tolerance mechanism under abiotic stress conditions, including drought. NPs exhibit alleviating effects against drought stress via induction of physiological and biochemical readjustments accompanied by modulation of gene expression involved in drought response/tolerance. NPs ameliorate drought-induced reduction in carbon assimilation via increasing the photosynthetic activity. The improved root growth, upregulation of aquaporins, modification of intracellular water metabolism, accumulation of compatible solutes and ion homeostasis are the major mechanisms used by NPs to mitigate the osmotic stress caused by water deficit. NPs reduce water loss from leaves through stomatal closure due to fostered abscisic acid (ABA) accumulation and ameliorate oxidative stress damage by reducing reactive oxygen species and activating the antioxidant defense system. This review provides an evolutionary foundation regarding drought stress in plant life and summarizes the interactions between NPs and plants under drought. The subsequent impact of NPs on plant development and productivity and recent nanobiotechnological approaches to improve drought stress resilience are presented. On the whole, this review highlights the significance of NPs in dealing with the global problem of water scarcity faced by farmers.

Substrate-Free Untagged Detection of miR393a Using an Ultrasensitive Electrochemical Biosensor

Rapid and sensitive detection of numerous regulatory pathways in growth and development processes and defensive responses in plant-pathogen interactions caused by miRNA has been the current interest of agricultural scientists. Herein, an uncomplicated ultrasensitive electrochemical biosensor was fabricated to detect miR393a, as its detection is of vital importance for plant diseases. A streptavidin-coated screen-printed carbon electrode (SPCE) was fabricated and characterized by scanning electrochemical microscopy, scanning electron microscopy, surface plasmon resonance, and cyclic voltammetry. The two-dimensional (2D) structure and chemical functionality of the streptavidin-coated SPCE render it a superior platform for loading a modified probe via a 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide-N-hydroxysuccinimide linker. This biorecognition platform is capable of efficiently using its excellent conductivity, greater surface area, and effective electrochemical execution due to its synergistic effect between streptavidin and carbon electrodes. The biosensor showed a good linear response (R ² = 0.96) to miR393a concentrations ranging from 100 nM to 100 fM. This streptavidin-based biosensor is highly sensitive to the minimum concentration of miR393a, lowest detection limit, and ultrasensitivity under optimized conditions, i.e., 100 fM, 0.33 fM, and 33.72 μA fM^-1 cm^-2, respectively. In addition, remarkable recoveries could be obtained to confirm the feasibility of this assay in plant disease samples. The fabricated technology could offer a selective, adaptable, and farmer-friendly strategy for the timely detection of miRNA of plant samples.

Effects of fulvic acid on the photosynthetic and physiological characteristics of Paeonia ostii under drought stress

PAEONIA OST II

has become an economically important oil crop in recent years, but its growth is seriously affected by drought stress in dry areas. In this study, the alleviating effect of fulvic acid (FA) on potted P. ostii under natural drought stress was investigated. The natural drought stress adopted in this experiment was mainly characterized by the low soil water content, and the roots of plants cannot absorb enough water to compensate for the consumption of transpiration, which affects the normal physiological activities and causes damage. The results showed that FA treatment significantly increased the leaf water content and antioxidant enzyme activities and decreased reactive oxygen species (ROS) accumulation, the proline (Pro) content, and the relative electrical conductivity (REC). Moreover, FA treatment improved photosynthetic parameters and chlorophyll (Chl) fluorescence parameters, maintained the integrity of chloroplasts and mesophyll cells, and increased the expression level of drought-tolerant genes. These results indicated that FA treatment could induce antioxidant enzymes to eliminate ROS, reduce membrane lipid peroxidation and decrease damage to photosynthesis in P. ostii under drought stress, which would provide a measure for alleviating the damage of P. ostii caused by drought stress.

Machine learning improves our knowledge about miRNA functions towards plant abiotic stresses

During the last two decades, human has increased his knowledge about the role of miRNAs and their target genes in plant stress response. Biotic and abiotic stresses result in simultaneous tissue-specific up/down-regulation of several miRNAs. In this study, for the first time, feature selection algorithms have been used to investigate the contribution of individual plant miRNAs in Arabidopsis thaliana response towards different levels of several abiotic stresses including drought, salinity, cold, and heat. Results of information theory-based feature selection revealed that miRNA-169, miRNA-159, miRNA-396, and miRNA-393 had the highest contributions to plant response towards drought, salinity, cold, and heat, respectively. Furthermore, regression models, i.e., decision tree (DT), support vector machines (SVMs), and Naïve Bayes (NB) were used to predict the plant stress by having the plant miRNAs' concentration. SVM with Gaussian kernel was capable of predicting plant stress (R2 = 0.96) considering miRNA concentrations as input features. Findings of this study prove the performance of machine learning as a promising tool to investigate some aspects of miRNAs' contribution to plant stress responses that have been undiscovered until today.