Thermal asymmetric interlaced polymerase chain reaction (TAIL-PCR) is a powerful technique for amplifying genomic regions flanking Tnt1-retortransposon insertions in plants. Here, we present a TAIL-PCR protocol for amplifying Tnt1-flanking genomic sequences in chickpea using Tnt1-transformed hairy roots as the starting material. The amplified products can be cloned and sequenced for the precise mapping of Tnt1-integration sites in the chickpea genome. This method enables the functional characterization of chickpea genes governing root-specific traits and can be easily adapted for flanking sequence tag recovery in chickpea Tnt1-mutant populations.

Protoplasts serve as a powerful system to study various plant physiological processes and to understand crucial signaling pathways within the plant system. The isolation of Arabidopsis protoplasts is a well-established technique and being utilized for wide range of assays. The method described herein includes the precise cutting of Arabidopsis leaves using extraction buffer containing cellulase and macerozyme. Further we present a polyethylene glycol [PEG]-mediated protoplast transformation method. Here, we have elucidated the methodology for isolation of protoplast for the AtSWEET-mediated sucrose uptake assay in control, and Pseudomonas syringe pv tomato DC3000 (Pst DC3000) treated leaves by utilizing GC/MS analysis. Our approach includes certain modifications to the previously published protoplast isolation technique, streamlining the process and providing a more accessible alternative to the highly specialized Xenopus oocyte uptake assay.

Abiotic and biotic stresses remain major constraints affecting plant growth, development, and crop productivity worldwide. Understanding plant responses to these stresses, both individually and in combination, is therefore essential for developing resilient crop systems and ensuring sustainable agricultural production. This special issue, comprising 32 articles including both review and research papers, highlights recent advances in plant stress biology and provides insights into the mechanisms underlying plant adaptation to diverse environmental challenges. A major focus of the issue is on heat stress tolerance and its interaction with other stresses such as drought, particularly during critical developmental stages in crops such as rice and wheat. Several contributions examine physiological, molecular, and genomic mechanisms associated with stress tolerance, including studies on HSP100 proteins and thermotolerance, drought tolerance in indigenous finger millet, salinity responses in rice and chickpea, and alternative splicing events under salt stress. The issue also includes investigations into plant responses to combined abiotic and biotic stresses, such as heat and aphid stress in wheat, as well as research on plant defense mechanisms against pathogens, including the induction of defense enzymes against mango anthracnose and metabolite-mediated resistance to cucumber downy mildew. In addition, several articles explore beneficial plant–microbe interactions, such as cyanobacterial root microbiomes and microbial consortia that enhance drought tolerance. Advances in genomics and transcriptomics are highlighted through genome-wide analyses of stress-responsive gene families and endophyte-mediated transcriptomic regulation. The issue further covers methodological developments, that integrate artificial intelligence and machine learning with multi-omics data for plant stress research. Collectively, the articles presented in this special issue provide valuable insights into plant stress responses and offer potential strategies for improving crop resilience under changing environmental conditions.

Optimizing the conditions for the overexpression and purification of membrane proteins for functional and structural studies is a complex and tedious process, which demands considerable time and effort. Membranes are made up of phospholipid bilayer embedded with proteins, cholesterol, and carbohydrates. While cholesterol regulates the fluidity, proteins and carbohydrates provide functionality to the membranes. Membrane proteins are responsible for transport, signaling, adhesion, and catalysis and have membrane spanning domains that tether them to the lipid bilayer. Due to the hydrophobic nature of these membrane spanning domains, isolation, and biochemical analysis becomes challenging. For an extended period, researchers have refined techniques to achieve the highest purity in plasma membrane vesicle preparations derived from crude plant extracts. While, conventional detergent-based isolation methods can solubilize both globular and membrane proteins, an enrichment step is necessary to remove cytosolic or aggregated contaminants. The current protocol outlines a method for membrane purification utilizing ultracentrifugation and detergents, which facilitates the isolation of membrane proteins in their native conformational state.

Premise:Plants are frequently exposed to combinations of abiotic and biotic stresses that pose a greater threat to yield and productivity than individual stresses. However, knowledge of the impact of many stress combinations in numerous plants is limited due to the lack of experimental data, which could take decades to generate. To overcome this limitation, we utilized existing literature data from various plant species and stress combinations to derive biological inferences, thereby gaining a comprehensive understanding of plant responses through a computational tool. Methods:Public databases were used to gather literature on the impact of various abiotic and biotic stress combinations. Then, a composite artificial neural network (ANN)-based multi-target classification and regression deep learning model was developed using machine learning algorithms. Results:The model predicted the impact of stress interactions in plants, including the morphological parameters affected and percentage changes in those parameters, with an overall accuracy of 76.33%. Predicted reductions in yield were validated in rice under combined drought and heat stress. Discussion:The ANN-based model developed in this study is a valuable resource for plant researchers seeking to understand the impact of stress combinations. The tool can make use of multivariate and complex combined stress datasets.

As climate change continues to impact crop yields, developing strategies to enhance plant tolerance to biotic stress has become increasingly important. This requires a thorough evaluation of the tools and methodologies used to manipulate and study biotic stress tolerance. It is crucial to comprehensively understand both conventional and modern techniques, as well as their effectiveness in addressing the specific needs of the crop under study. Detecting diseases at the early stages of plant development can prevent significant losses in large-scale cultivations. Two broad approaches commonly used to mitigate biotic stresses are eliminating causative agents such as fungi, bacteria, nematodes, viruses, or pests, and imparting resistance to the plant. Although there are similarities in the tools and techniques used to address different biotic stresses, each scenario requires dedicated case studies. It is also essential to stay up to date with the latest developments in plant biotechnology to incorporate a cross-disciplinary approach in conducting and validating experiments. This chapter provides an overview of methods covered in this book ranging from molecular breeding to nondestructive techniques that help achieve the goal of safeguarding plant health.

Antifungal agents provide both preventive and curative effects by protecting plant surfaces and eliminating existing infections within plant tissues. Evaluating their impact against phytopathogenic fungi is critical for sustainable agriculture. Macrophomina phaseolina is a highly destructive soil-borne pathogen with a broad host range, causing charcoal rot and related diseases that result in severe yield losses in crops such as soybean, sorghum, maize, and legumes. Several methods are employed to assess the in vitro antifungal efficacy of various substances, including broth microdilution, disk diffusion, gradient screening, and agar-based screening. However, these conventional techniques are generally slower, more labor-intensive, and limited by reproducibility issues. The adoption of microplate reader-based antifungal efficacy testing has enhanced efficiency and scalability, enabling high-throughput evaluation of multiple antifungal agents across a range of concentrations while providing a streamlined platform for preliminary screening. This chapter presents a convenient and cost-effective protocol for assessing the activity of antifungal agents against fungi that produce microsclerotia, with emphasis on standardization and quality control measures. The antifungal efficacy testing and cell death assay are employed to determine inhibitory concentrations via spectrophotometry and to quantify hyphal death through fluorescence microscopy, respectively. In addition, detailed procedures for inoculum preparation, antifungal agent dilution, incubation conditions, and statistical analysis are described.

Pyrroline-5 carboxylic acid (P5C) is an intermediary metabolite formed during proline synthesis and catabolism. Proline catabolism in two steps occurs in mitochondria where proline dehydrogenase (ProDH) catabolizes proline into P5C, and finally, pyrroline-5 carboxylate dehydrogenase catabolizes P5C into glutamate. Estimating mitochondrial P5C is essential to know how the metabolism of P5C in mitochondria via proline catabolism genes is responsible for causing disease and defense reaction in the case of Pseudomonas syringae-Arabidopsis interaction. There is no protocol available in the literature to estimate mitochondrial P5C due to which its role is masked and not properly deciphered. Here, we describe the protocol for estimating mitochondrial P5C from Arabidopsis leaves infected with bacterial pathogen P. syringae. Mitochondria was isolated from Arabidopsis leaf samples by percoll gradient centrifugation method. Mitochondrial amino acids and their derivatives were extracted in 80% methanol and without derivatization directly used for LC-MS analysis with standard labeled amino acids acting as internal control. P5C was detected as the daughter ion of the parent ion proline and quantified from the internally labeled proline standard.

Chickpea (Cicer arietinum L.), confronts substantial challenges from the emerging pathogenic fungus Macrophomina phaseolina (Tassi) Goid, causing dry root rot (DRR) disease. Chickpea plants severely affected by combined DRR and drought stress. Currently sick plot and sick pot method are utilized for germplasm screening to identify tolerant genotypes. These methods are time-consuming; therefore, we propose a novel methodology for the rapid screening of chickpea under combined DRR and osmotic stress conditions. This chapter introduces an adept high-throughput phenotyping methodology, conducted within controlled laboratory conditions, aiming to investigate the interaction between osmotic stress and DRR disease in chickpea crops. The methodology employs an innovative pouch technique for screening combined stress, providing a streamlined temporal investigation process and precise control over stress parameters. The incorporation of polyethylene glycol (PEG) enables the simultaneous imposition of osmotic stress alongside pathogen infection, making the methodology versatile for studying combined stress scenarios. This approach fills a gap in concurrent stress imposition techniques, enhancing germplasm screening by identifying genotypes with varying susceptibility and resistance levels. Thus, we suggest use of high-throughput phenotyping in combination genome-wide association study (GWAS) can take combined stress resistance breeding in chickpea at next level to combat food security and climate change.

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Dry Root Rot (DRR), caused by the soil-borne fungal pathogen Macrophomina phaseolina, is an emerging threat to global chickpea production. Screening large chickpea germplasm collections, mutant populations, and transgenic lines for DRR resistance remains challenging due to manual disease scoring, which is subjective, labor-intensive and often prone to rating bias. To address this, our laboratory has previously developed RootRotAI 2.0, a set of deep learning models developed using TensorFlow to support automated detection and assessment of DRR from images of chickpea collected under laboratory conditions. In the current study, we focus on the high-throughput deployment of these models by developing a mobile application, RootRotAI 2.2, and, a web application, RootRotAI 2.1, to facilitate a user-friendly interface and broader accessibility. These applications allow users to upload or capture images to automatically diagnose and assess DRR severity. RootRotAI 2.2 and 2.1 integrate two transformer-based multitask deep learning models now optimized and deployed via TensorFlow Lite for efficient on-device inference. These tools can be accessed via https://github.com/scipdatabase/RootRotAI and mobile app is available in play store. The application supports three imaging modalities, a handheld camera, a root scanner, and a light microscope each with modality-specific backgrounds. These tools offer a real-time assessment capabilities through an offline mobile mode and a high-capacity platform for large-scale data analysis via the online web application. While image-based disease detection tools are common, RootRotAI serves as a novel and key digital resource for the identification of DRR in chickpea, ultimately facilitating crop improvement programs and contributes to sustainable agriculture.

Macrophomina phaseolina is a fungus that causes dry root rot disease and considerable yield loss worldwide. Fungi exhibit various ways of absorbing nutrients through their plasma membrane, such as free or facilitated diffusion, diffusion channels, or active transport. Glucose, as a preferred carbon source, activates the plasma membrane H+-ATPase, resulting in the release of protons. Consequently, the protons, along with the organic acid metabolites released into the extracellular environment, acidify the cell surroundings. This decrease in pH cues the fungus to shift from saprotrophic to necrotrophic growth, facilitating host invasion. Sustainable dry root rot disease management often relies on the employment of antifungal agents from various biological sources. Despite the discovery of numerous antifungal agents, only a limited number have been evaluated for their efficacy against this phytopathogenic fungus. This scarcity of testing is primarily due to the limitations of existing methods, which often lack standardisation and reproducibility. This chapter introduces a rapid and sensitive method to assess the antifungal activity of various agents against M. phaseolina. By measuring extracellular pH changes after treatment in the presence of a nutrient source, we can determine the inhibitory concentrations of these agents and evaluate their potential for controlling fungal pathogenicity in plants.

Dry root rot (DRR) disease is a major threat to chickpea production across the world. This disease is caused by a soil-borne necrotrophic fungal pathogen, Macrophomina phaseolina. The use of disease-resistant varieties paves the way to conquer the disease spread. Though chickpea germplasm with rich genetic diversity is available around the world, its response to DRR is still unexplored. In turn, this demands screening and identification of resistant genotypes for crop protection against the disease. Here we describe an improved blotting paper technique for the large-scale screening of chickpea genotypes for DRR resistance. The method is quick, cost-effective, less labour-intensive, and thus optimized for high-throughput screening and can be efficiently used to screen a large number of chickpea genotypes for resistance against DRR.

Jasmonates (JAs) are a group of oxylipin-derived phytohormones involved in various biotic and abiotic stress responses and regulate plant development. JAs are perceived by receptor proteins called coronatine insensitive (COI). These JA receptors encode F-box proteins that form the SCFCOI ubiquitin ligase complex (comprising Skp, Cullin, and F-box) and activate JA signaling by promoting the degradation of the transcriptional repressor JAZ (JA associated ZIM domain containing) proteins via the 26S proteasomal pathway. However, JA signaling is not well understood in chickpea, a vital legume. In this study, we identified two potential chickpea JA receptors, named CaCOI1 and CaCOI2, and characterized CaCOI2 as a functional JA receptor. Subcellular localization experiments revealed that CaCOI2 is localized outside the nucleus but moves into the nucleus upon JA perception to activate signaling. Using domain-swapping experiments between CaCOI1 and CaCOI2, we demonstrated that the leucine-rich repeat region of the receptors, which interacts with bioactive JA such as JA-Isoleucine, also plays a crucial role in controlling the subcellular localization of CaCOI proteins. Our findings identify a functional JA receptor in chickpea and reveal new aspects of JA signaling and perception, which may also be relevant to other plants.

Dry root rot (DRR) of chickpea is caused by the broad-range necrotrophic fungus Macrophomina phaseolina. Chickpea germplasm does not provide durable resistance to DRR, which is particularly devastating under drought. Even moderately resistant chickpea varieties become susceptible under combined stress. We hypothesized that nonhost resistance (NHR) is durable even under combined stress. Using the blotter paper assay and stereomicroscopic observations, we identified the asterid weed Parthenium hysterophorus as a potential nonhost of M. phaseolina among 82 potential nonhosts. Epidermal necrotic lesions were prevented in P. hysterophorus. In planta fungal load was 0.195 and 0.007 ng/ng total DNA in chickpea and P. hysterophorus, respectively. M. phaseolina could not colonize the P. hysterophorus root while up to 6 cortical cell layers were colonized in chickpea. Further, NHR was durable under combined stress. Dual RNA sequencing revealed that M. phaseolina actively attempted to infect the nonhost and activated specific genes in the xenobiotics degradation pathway. P. hysterophorus also showed an active defense response with1958 and 2294 differentially expressed genes at 2 and 4 DAI, respectively, with 363 upregulated at both time points. Differential expression of cell wall synthesis, phytohormone signaling, and other defense response pathways likely contributes to NHR. Few genes in the phenylpropanoid biosynthesis pathways in P. hysterophorus were also upregulated, possibly because these metabolites are linked to the distinct changes in the fungus during nonhost infection. We therefore conclude that P. hysterophorus exhibits post-invasive NHR to M. phaseolina and that general defense, phytohormone signaling and secondary metabolic pathways contribute to NHR.

Understanding the complex challenges that plants face from multiple stresses is key to developing climate-ready crops. We highlight the significance of the Stress Combinations and their Interactions in Plants database (SCIPdb) for studying the impact of stress combinations on plants and the importance of aligning thematic research programs to create crops aligned with achieving sustainable development goals.

Combined stresses are a common occurrence in agricultural fields. There is a pressing need for empirical understanding of the plant responses and find ways to develop stress tolerant plants and stress management strategies to tackle combined stresses in the field conditions. Here a comprehensive overview of the current understating and recent research on combined stress interactions in plants are presented. Here we comprehend the findings from various studies focusing on different aspects of combined stress, including abiotic-abiotic, abiotic-biotic, and biotic-biotic stress interactions. In general, the studies discussed here highlight the escalating impact of climate change on plants, emphasizing the need for a deeper understanding of plant responses to concurrent abiotic and biotic stresses. Key findings from the articles published in this issue, include the adverse effects of combined drought and high-temperature stress on crop growth and yield, the exacerbation of pathogen impacts under abiotic stresses, and the potential for melatonin and salicylic acid to mitigate stress-induced damage. Additionally, use of model systems for quicker understanding of combined stress responses and development of methods and technologies which can be extrapolated to crop plants are discussed. Overall, findings from the articles from this special issue underscore the complexity of combined stress interactions in plants and highlight the importance of interdisciplinary research efforts to address the challenges posed by climate change and ensure global food security.

The reactive oxygen species (ROS) including superoxide (O2−), hydrogen peroxide (H2O2), and singlet oxygen (O2−), are the main molecules produced in excessive amounts under stress conditions, leading to cellular damage in plants. These ROS molecules should be effectively removed to impart stress tolerance. Enzymatic scavengers like superoxide dismutase, catalase, and peroxidases plays a significant role in scavenging ROS molecules. However, the functional validation of such genes cloned from hardy crops are very much limited. The present research demonstrates the synergistic effect of co-expressing multiple antioxidant genes encoding copper-zinc superoxide dismutase (Cu/Zn-SOD) and ascorbate peroxidase cloned from hardy crop Pennisetum glaucum to improve single and combined abiotic stress tolerance and also corroborates Chlamydomonas as a valuable model system for functional validation of multi genes, especially for understanding combined stress responses due to its rapid transformation process and molecular similarity to higher plants.

Alternaria blight is a devastating disease that causes significant crop losses in oilseed Brassicas every year. Adoption of conventional breeding to generate disease-resistant varieties has so far been unsuccessful due to the lack of suitable resistant source germplasms of cultivated Brassica spp. A thorough understanding of the molecular basis of resistance, as well as the identification of defense-related genes involved in resistance responses in closely related wild germplasms, would substantially aid in disease management. In the current study, a comparative transcriptome profiling was performed using Illumina based RNA-seq to detect differentially expressed genes (DEGs) specifically modulated in response to Alternaria brassicicola infection in resistant Sinapis alba, a close relative of Brassicas, and the highly susceptible Brassica rapa. The analysis revealed that, at 48 hpi (hours post inoculation), 3396 genes were upregulated and 23239 were downregulated, whereas at 72 hpi, 4023 genes were upregulated and 21116 were downregulated. Furthermore, a large number of defense response genes were detected to be specifically regulated as a result of Alternaria infection. The transcriptome data was validated using qPCR-based expression profiling for selected defense-related DEGs, that revealed significantly higher fold change in gene expression in S. alba when compared to B. rapa. Expression of most of the selected genes was elevated across all the time points under study with significantly higher expression towards the later time point of 72 hpi in the resistant germplasm. S. alba activates a stronger defense response reaction against the disease by deploying an array of genes and transcription factors involved in a wide range of biological processes such as pathogen recognition, signal transduction, cell wall modification, antioxidation, transcription regulation, etc. Overall, the study provides new insights on resistance of S. alba against A. brassicicola, which will aid in devising strategies for breeding resistant varieties of oilseed Brassica.

Drought dynamically influences the interactions between plants and pathogens, thereby affecting disease outbreaks. Understanding the intricate mechanistic aspects of the multiscale interactions among plants, pathogens, and the environment-known as the disease triangle-is paramount for enhancing the climate resilience of crop plants. In this review, we systematically compile and comprehensively analyse current knowledge on the influence of drought on the severity of plant diseases. We emphasise that studying these stresses in isolation is not sufficient to predict how plants respond to combined stress from both drought and pathogens. The impact of drought and pathogens on plants is complex and multifaceted, encompassing the activation of antagonistic signalling cascades in response to stress factors. The nature, intensity, and temporality of drought and pathogen stress occurrence significantly influence the outcome of diseases. We delineate the drought-sensitive nodes of plant immunity and highlight the emerging points of crosstalk between drought and defence signalling under combined stress. The limited mechanistic understanding of these interactions is acknowledged as a key research gap in this area. The information synthesised herein will be crucial for crafting strategies for the accurate prediction and mitigation of future crop disease risks, particularly in the context of a changing climate.