Pattern recognition receptors as potential therapeutic targets for developing immunological engineered plants.

There is an urgent need to combat pathogen infestations in crop plants to ensure food security worldwide. To counter this, plants have developed innate immunity mediated by Pattern Recognition Receptors (PRRs) that recognize pathogen-associated molecular patterns (PAMPs) and damage- associated molecular patterns (DAMPs). PRRs activate Pattern-Triggered Immunity (PTI), a defence mechanism involving intricate cell-surface and intracellular receptors. The diverse ligand-binding ectodomains of PRRs, including leucine-rich repeats (LRRs) and lectin domains, facilitate the recognition of MAMPs and DAMPs. Pathogen resistance is mediated by a variety of PTI responses, including membrane depolarization, ROS production, and the induction of defence genes. An integral part of intracellular immunity is the Nucleotide-binding Oligomerization Domain, Leucine-rich Repeat proteins (NLRs) which recognize and respond to effectors in a potent manner. Enhanced understanding of PRRs, their ligands, and downstream signalling pathways has contributed to the identification of potential targets for genetically modified plants. By transferring PRRs across plant species, it is possible to create broad-spectrum resistance, potentially offering innovative solutions for plant protection and global food security. The purpose of this chapter is to provide an update on PRRs involved in disease resistance, clarify the mechanisms by which PRRs recognize ligands to form active receptor complexes and present various applications of PRRs and PTI in disease resistance management for plants.

Recent advances in plant translational genomics for crop improvement.

The growing population, climate change, and limited agricultural resources put enormous pressure on agricultural systems. A plateau in crop yields is occurring and extreme weather events and urbanization threaten the livelihood of farmers. It is imperative that immediate attention is paid to addressing the increasing food demand, ensuring resilience against emerging threats, and meeting the demand for more nutritious, safer food. Under uncertain conditions, it is essential to expand genetic diversity and discover novel crop varieties or variations to develop higher and more stable yields. Genomics plays a significant role in developing abundant and nutrient-dense food crops. An alternative to traditional breeding approach, translational genomics is able to improve breeding programs in a more efficient and precise manner by translating genomic concepts into practical tools. Crop breeding based on genomics offers potential solutions to overcome the limitations of conventional breeding methods, including improved crop varieties that provide more nutritional value and are protected from biotic and abiotic stresses. Genetic markers, such as SNPs and ESTs, contribute to the discovery of QTLs controlling agronomic traits and stress tolerance. In order to meet the growing demand for food, there is a need to incorporate QTLs into breeding programs using marker-assisted selection/breeding and transgenic technologies. This chapter primarily focuses on the recent advances that are made in translational genomics for crop improvement and various omics techniques including transcriptomics, metagenomics, pangenomics, single cell omics etc. Numerous genome editing techniques including CRISPR Cas technology and their applications in crop improvement had been discussed.

Diosgenin biosynthesis investigation in medicinal herb (Tribulus terrestris) by transcriptome analysis.

Next-generation sequencing (NGS) has revolutionized the analysis of specific genes, pathways, and their regulation in various species. Tribulus terrestris L., an annual medicinal herb of Zygophyllaceae family, has gained significant attention due to its diverse medicinal properties, including anti-inflammatory, antimicrobial, and anti-cancer effects. Diosgenin, a steroidal saponin, is the major bioactive compound responsible for the medicinal importance of T. terrestris. However, there is a paucity of information regarding the genes involved in the diosgenin biosynthetic pathway in T. terrestris. To address this gap, this study aimed to identify candidate genes associated with diosgenin biosynthesis through whole transcriptome profiling. A total of ∼7.9 GB of data, comprising 482 million reads, was obtained and assembled into 148,871 unigenes. Subsequently, functional annotations were assigned to 50 % of the unigenes using sequence similarity searches against the NCBI non-redundant (NR), Uniprot, KEGG, Pfam, GO, and COG databases, primarily based on Gene Ontology and KEGG-KAAS pathways. The majority of unigenes associated with the biosynthesis of the steroidal diosgenin backbone exhibited up-regulation in the fruit, leaf, and root tissues, except the SQE gene in root. The differential expression of selected genes was further validated through quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, the study identified 21,026 unigenes related to transcription factors and 15,551 unigenes containing simple sequence repeats (SSR). Notably, di-nucleotide SSR motifs exhibited a high repeat frequency. These findings greatly enhance our understanding of the diosgenin biosynthesis pathway and provide a basis for future research in molecular investigation and metabolic engineering, specifically for boosting diosgenin content.

Genetic circuits in microbial biosensors for heavy metal detection in soil and water.

With the rapid population growth, the world is witnessing an ever-increasing demand for energy and natural resources. Consequently, soil, air, and water are polluted with diverse pollutants, including heavy metals (HM). The detection of heavy metals is necessary to remediate them, which is achieved with biosensors. Initially, these HM were detected using atomic absorption spectroscopy (AAS), emission spectroscopy, mass spectrometry, gas chromatography etc., but these were costly and time consuming which further paved a way for microbe-based biosensors. The development of genetic circuits for microbe-based biosensors has become more popular in recent years for heavy metal detection. In this review, we have especially discussed the various types of genetic circuits such as toggle switches, logic gates, and amplification modules used in these biosensors as they are used to enhance sensitivity and specificity. Genetic circuits also allow for rapid and multiple analyte detection at the same time. The use of microbial biosensors for the detection of HM in the soil as well as the water is also described below. Although with a higher success rate than classical biosensors, these microbial biosensors still have some drawbacks like bioavailability and size of the analyte which are needed to be addressed.

A review on phytochemical and pharmacological facets of tropical ethnomedicinal plants as reformed DPP-IV inhibitors to regulate incretin activity.

Type 2 diabetes mellitus is a metabolic disorder resulting from impaired insulin secretion and resistance. Dipeptidyl peptidase (DPP)-IV is an enzyme known to trigger the catalysis of insulinotropic hormones, further abating the endogenous insulin levels and elevating the glucose levels in blood plasma. In the field of drug development, DPP-IV inhibitors have opened up numerous opportunities for leveraging this target to generate compounds as hypoglycemic agents by regulating incretin activity and subsequently decreasing blood glucose levels. However, the practice of synthetic drugs is an apparent choice but poses a great pharmacovigilance issue due to their incessant undesirable effects. The ideology was set to inventively look upon different ethnomedicinal plants for their anti-diabetic properties to address these issues. To date, myriads of phytochemicals are characterized, eliciting an anti-diabetic response by targeting various enzymes and augmenting glucose homeostasis. Antioxidants have played a crucial role in alleviating the symptoms of diabetes by scavenging free radicals or treating the underlying causes of metabolic disorders and reducing free radical formation. Plant-based DPP-IV inhibitors, including alkaloids, phenolic acid, flavonoids, quercetin, and coumarin, also possess antioxidant capabilities, providing anti-diabetic and antioxidative protection. This review article provides a new gateway for exploring the ability of plant-based DPP-IV inhibitors to withstand oxidative stress under pathological conditions related to diabetes and for reforming the strategic role of ethnomedicinal plants as potent DPP-IV inhibitors through the development of polyherbal formulations and nanophytomedicines to regulate incretin activity.

Upcoming progress of transcriptomics studies on plants: An overview.

Transcriptome sequencing or RNA-Sequencing is a high-resolution, sensitive and high-throughput next-generation sequencing (NGS) approach used to study non-model plants and other organisms. In other words, it is an assembly of RNA transcripts from individual or whole samples of functional and developmental stages. RNA-Seq is a significant technique for identifying gene predictions and mining functional analysis that improves gene ontology understanding mechanisms of biological processes, molecular functions, and cellular components, but there is limited information available on this topic. Transcriptomics research on different types of plants can assist researchers to understand functional genes in better ways and regulatory processes to improve breeding selection and cultivation practices. In recent years, several advancements in RNA-Seq technology have been made for the characterization of the transcriptomes of distinct cell types in biological tissues in an efficient manner. RNA-Seq technologies are briefly introduced and examined in terms of their scientific applications. In a nutshell, it introduces all transcriptome sequencing and analysis techniques, as well as their applications in plant biology research. This review will focus on numerous existing and forthcoming strategies for improving transcriptome sequencing technologies for functional gene mining in various plants using RNA- Seq technology, based on the principles, development, and applications.