Harnessing and bioprospecting botanical-based herbal medicines against potential drug targets for COVID-19: a review coupled molecular docking studies.

Since the end of February 2020, the world has come to a standstill due to the virus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). Since then, the global scientific community has explored various remedies and treatments against this virus, including natural products that have always been a choice because of their many benefits. Various known phytochemicals are well documented for their antiviral properties. Research is being carried out to discover new natural plant products or existing ones as a treatment measure for this disease. The three important targets in this regard are-papain like protease (PLpro), spike protein, and 3 chymotrypsin like proteases (3CLpro). Various docking studies are also being elucidated to identify the phytochemicals that modulate crucial proteins of the virus. The paper is simultaneously a comprehensive review that covers recent advances in the domain of the effect of various botanically derived natural products as an alternative treatment approach against Coronavirus Disease 2019 (COVID-19). Furthermore, the docking analyses revealed that rutin (inhibitor of the major protease of SARS-CoV-2), gallocatechin (e.g., interacting with 03 hydrogen bonds with a spike-like protein), lycorine (showing the best binding affinity with amino acids GLN498, THR500 and GLY446 of the spike-like protein), and quercetrin (inhabiting at its residues ASP216, PHE219, and ILE259) are promising inhibitors of SARS­CoV­2.Communicated by Ramaswamy H. Sarma.

The spread of the omicron variant: Identification of knowledge gaps, virus diffusion modelling, and future research needs.

The World Health Organization (WHO) recognised variant B.1.1.529 of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) as a variant of concern, termed "Omicron", on November 26, 2021. Its diffusion was attributed to its several mutations, which allow promoting its ability to diffuse worldwide and its capability in immune evasion. As a consequence, some additional serious threats to public health posed the risk to undermine the global efforts made in the last two years to control the pandemic. In the past, several works were devoted to discussing a possible contribution of air pollution to the SARS-CoV-2 spread. However, to the best of the authors' knowledge, there are still no works dealing with the Omicron variant diffusion mechanisms. This work represents a snapshot of what we know right now, in the frame of an analysis of the Omicron variant spread. The paper proposes the use of a single indicator, commercial trade data, to model the virus spread. It is proposed as a surrogate of the interactions occurring between humans (the virus transmission mechanism due to human-to-human contacts) and could be considered for other diseases. It allows also to explain the unexpected increase in infection cases in China, detected at beginning of 2023. The air quality data are also analyzed to evaluate for the first time the role of air particulate matter (PM) as a carrier of the Omicron variant diffusion. Due to emerging concerns associated with other viruses (such as smallpox-like virus diffusion in Europe and America), the proposed approach seems to be promising to model the virus spreading.

Bioactive Molecules Derived from Plants in Managing Dengue Vector Aedes aegypti (Linn.).

Mosquitoes are the potential vectors of several viral diseases such as filariasis, malaria, dengue, yellow fever, Zika fever and encephalitis in humans as well as other species. Dengue, the most common mosquito-borne disease in humans caused by the dengue virus is transmitted by the vector Ae. aegypti. Fever, chills, nausea and neurological disorders are the frequent symptoms of Zika and dengue. Thanks to various anthropogenic activities such as deforestation, industrialized farming and poor drainage facilities there has been a significant rise in mosquitoes and vector-borne diseases. Control measures such as the destruction of mosquito breeding places, a reduction in global warming, as well as the use of natural and chemical repellents, mainly DEET, picaridin, temephos and IR-3535 have proven to be effective in many instances. Although potent, these chemicals cause swelling, rashes, and eye irritation in adults and children, and are also toxic to the skin and nervous system. Due to their shorter protection period and harmful nature towards non-target organisms, the use of chemical repellents is greatly reduced, and more research and development is taking place in the field of plant-derived repellents, which are found to be selective, biodegradable and harmless to non-target species. Many tribal and rural communities across the world have been using plant-based extracts since ancient times for various traditional and medical purposes, and to ward off mosquitoes and various other insects. In this regard, new species of plants are being identified through ethnobotanical surveys and tested for their repellency against Ae. aegypti. This review aims to provide insight into many such plant extracts, essential oils and their metabolites, which have been tested for their mosquitocidal activity against different life cycle forms of Ae. Aegypti, as well as for their efficacy in controlling mosquitoes.

Current Scenario and Future Prospects of Endophytic Microbes: Promising Candidates for Abiotic and Biotic Stress Management for Agricultural and Environmental Sustainability.

Globally, substantial research into endophytic microbes is being conducted to increase agricultural and environmental sustainability. Endophytic microbes such as bacteria, actinomycetes, and fungi inhabit ubiquitously within the tissues of all plant species without causing any harm or disease. Endophytes form symbiotic relationships with diverse plant species and can regulate numerous host functions, including resistance to abiotic and biotic stresses, growth and development, and stimulating immune systems. Moreover, plant endophytes play a dominant role in nutrient cycling, biodegradation, and bioremediation, and are widely used in many industries. Endophytes have a stronger predisposition for enhancing mineral and metal solubility by cells through the secretion of organic acids with low molecular weight and metal-specific ligands (such as siderophores) that alter soil pH and boost binding activity. Finally, endophytes synthesize various bioactive compounds with high competence that are promising candidates for new drugs, antibiotics, and medicines. Bioprospecting of endophytic novel secondary metabolites has given momentum to sustainable agriculture for combating environmental stresses. Biotechnological interventions with the aid of endophytes played a pivotal role in crop improvement to mitigate biotic and abiotic stress conditions like drought, salinity, xenobiotic compounds, and heavy metals. Identification of putative genes from endophytes conferring resistance and tolerance to crop diseases, apart from those involved in the accumulation and degradation of contaminants, could open new avenues in agricultural research and development. Furthermore, a detailed molecular and biochemical understanding of endophyte entry and colonization strategy in the host would better help in manipulating crop productivity under changing climatic conditions. Therefore, the present review highlights current research trends based on the SCOPUS database, potential biotechnological interventions of endophytic microorganisms in combating environmental stresses influencing crop productivity, future opportunities of endophytes in improving plant stress tolerance, and their contribution to sustainable remediation of hazardous environmental contaminants.

Exploring the potential of CRISPR/Cas genome editing for vegetable crop improvement: An overview of challenges and approaches.

Vegetables provide many nutrients in the form of fiber, vitamins, and minerals, which make them an important part of our diet. Numerous biotic and abiotic stresses can affect crop growth, quality, and yield. Traditional and modern breeding strategies to improve plant traits are slow and resource intensive. Therefore, it is necessary to find new approaches for crop improvement. Clustered regularly interspaced short palindromic repeats/CRISPR associated 9 (CRISPR/Cas9) is a genome editing tool that can be used to modify targeted genes for desirable traits with greater efficiency and accuracy. By using CRISPR/Cas9 editing to precisely mutate key genes, it is possible to rapidly generate new germplasm resources for the promotion of important agronomic traits. This is made possible by the availability of whole genome sequencing data and information on the function of genes responsible for important traits. In addition, CRISPR/Cas9 systems have revolutionized agriculture, making genome editing more versatile. Currently, genome editing of vegetable crops is limited to a few vegetable varieties (tomato, sweet potato, potato, carrot, squash, eggplant, etc.) due to lack of regeneration protocols and sufficient genome sequencing data. In this article, we summarize recent studies on the application of CRISPR/Cas9 in improving vegetable trait development and the potential for future improvement.

Genome-wide identification and development of miniature inverted-repeat transposable elements and intron length polymorphic markers in tea plant (Camellia sinensis).

Marker-assisted breeding and tagging of important quantitative trait loci for beneficial traits are two important strategies for the genetic improvement of plants. However, the scarcity of diverse and informative genetic markers covering the entire tea genome limits our ability to achieve such goals. In the present study, we used a comparative genomic approach to mine the tea genomes of Camellia sinensis var. assamica (CSA) and C. sinensis var. sinensis (CSS) to identify the markers to differentiate tea genotypes. In our study, 43 and 60 Camellia sinensis miniature inverted-repeat transposable element (CsMITE) families were identified in these two sequenced tea genomes, with 23,170 and 37,958 putative CsMITE sequences, respectively. In addition, we identified 4912 non-redundant, Camellia sinensis intron length polymorphic (CsILP) markers, 85.8% of which were shared by both the CSS and CSA genomes. To validate, a subset of randomly chosen 10 CsMITE markers and 15 CsILP markers were tested and found to be polymorphic among the 36 highly diverse tea genotypes. These genome-wide markers, which were identified for the first time in tea plants, will be a valuable resource for genetic diversity analysis as well as marker-assisted breeding of tea genotypes for quality improvement.

On Aethina Erichson of Northeast India (Coleoptera: Nitidulidae: Nitidulinae).

Four species of Aethina [Aethina (Aethina) vicina Grouvelle, 1894, Aethina (Idaethina) orientalis (Nietner, 1856), Aethina (Idaethina) subrugosa (Grouvelle, 1894b) and Aethina (Circopes) subquadrata (Motschulsky, 1858)] have been newly recorded from northeast Indian states. Hitherto, three species, viz., Aethina (Aethina) argus Grouvelle, 1890, Aethina (Aethina) cyaneipennis Grouvelle, 1903 and Aethina (Aethina) inconspicua Nakane, 1967 were known from Northeast India. The specific status of Aethina (Aethina) nigrocastanea Grouvelle, 1903 has been reestablished. Altogether eight species of Aethina are treated in this paper. The paper incorporates redescriptions of the genus, and species of Aethina from Northeast India with a key to these species.

Impact of clinical posting in psychiatry on the attitude towards mental illness in undergraduate final year medical students.

INTRODUCTION: The stigma in psychiatry is pervasive, it is more serious obstacle for treatment initiation. Stigmatization among health professional themselves can result in compromised patient care. The aim of this study is to see the impact of psychiatry clinical posting on the attitude of medical students towards, psychiatry and mental illness. MATERIAL AND METHODS: A total of 30 final year medical students participated to this study. The attitude towards psychiatry (ATP) and the attitude towards mental illness (AMI) questionnaire were administered before and after 15 days clinical posting in psychiatry. RESULT: Medical students had favorable attitude towards psychiatry and mental illness with in a mean score of 108.34 on ATP and on 68.24AMI. There was a significant increase in the mean score of both scales after the psychiatry clinical posting. AMI and ATP for female and for male (AMI - ATP). CONCLUSION: A 15 days clinical posting of final year medical students in psychiatry was associated with an increase in positive attitude towards mental illness and psychiatry among female students but not among male students and posting reduces the stigma among the students also.

Insights into Novel Coronavirus Disease 2019 (COVID-19): Current Understanding, Research, and Therapeutic Updates.

BACKGROUND: Humans can be infected with various coronaviruses that can cause serious illness and death. One such pandemic strain of coronavirus was recently identified in December 2019, and it led to a devastating outbreak in Wuhan city of China. It is caused by severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2). It is highly contagious and causes symptoms such as fever, cough, and shortness of breath. OBJECTIVE: The objective of this review is to highlight the current understanding, research, and therapeutic updates of the novel coronavirus disease 2019 (COVID-19). METHODS: A thorough literature search was conducted for research papers and patents in the context of COVID-19. All the related articles were extracted from various public repositories such as Google Scholar, Pubmed, ScienceDirect (Elsevier), Springer, Web of Science, etc. Results: The present analysis revealed that the key areas of the inventions were vaccines and diagnostic kits apart from developing the treatment of CoV. It was also observed that no specific vaccine treatments were available for the treatment of 2019-nCov; therefore, developing novel chemical or biological drugs and kits for early diagnosis, prevention, and disease management is the primary governing topic among the patented inventions. The present study also indicates potential research opportunities for the future, particularly to combat 2019-nCoV. The current focus of the researches has turned towards developing four potential treatments, including the development of candidate vaccines, development of novel potential drugs, repurposing of existing drugs, and development of convalescent plasma therapy. The PCR based diagnosis is the gold standard for the COVID-19 testing, but it requires resource time, expertise, and high associated cost; hence researchers are also developing different diagnostic methods for the COVID-19. Although vaccines are being developed by various companies and have passed the pre-clinical stages but there still exists no guarantee for these to come into effect. The current treatments that are being used for COVID-19 patients are not well established and have shown limited success. CONCLUSION: The pandemic has challenged the medical, economic, and public health infrastructure across the globe. There is an urgent need to explore all available and possible methods/ approaches to study this disease for drug and vaccine development at the earliest.

Pharmacokinetic and molecular docking studies to design antimalarial compounds targeting Actin I.

OBJECTIVE: Malaria is an ancient disease that still causes more than 200 million of cases 7 with high mortality globally. Identification of new drug targets and development of novel antimalarial drugs with unique mode of action encounter the drug resistance and reduce the mortality by Plasmodium parasites. Actin protein is one of the key proteins in Plasmodium falciparum playing multifarious important roles including transport, cell motility, cell division, and shape determination. This study investigated Actin I as a drug target, in silico screening of diverse molecules through molecular docking was considered. Further, pharmacokinetic parameters of the selected molecules from the docking and interaction studies were planned to propose the lead molecules.b. METHODS: Molecules were selected according to score and protein ligand interaction and selected molecules were subjected for pharmacokinetic studies to investigate important drug parameters. RESULTS: The docked molecules were ranked according to the binding score and good interaction pattern was observed with Actin I within top 20 scoring molecules. The selected molecules also had optimum pharmacokinetic parameters. CONCLUSION: The current study provides a set of hit molecules which can be further explored through in vitro and in vivo experiments for the development of potential drugs against malaria, there by encountering drug resistance and establishing Actin I as an important drug target.

Computational and experimental insight into antituberculosis agent, (E)-benzyl-2-(4-hydroxy-2-methoxybenzylidene) hydrazinecarbodithioate: ADME analysis.

A new Schiff base, (E)-benzyl-2-(4-hydroxy-2-methoxybenzylidene)hydrazinecarbodithioate (compound 1) has been synthesized and experimentally characterized by the IR, UV-Vis, 1H-NMR and mass spectroscopies. The theoretical study of the synthesized compound was evaluated using the density functional theory (DFT) at B3LYP/6-31G+(d,p) basis set. The electronic absorption spectrum of compound 1 was evaluated using time-dependent density functional theory. Besides, in silico studies were done for the prediction of absorption, distribution, metabolism and excretion profiles of compound 1. According to the result, the theoretical data were well fitted with the experimental values. The studied compound has low chemical reactivity and high kinetic stability. In the molecular electrostatic potential map, the negative and positive potential sites were found around electronegative atoms and hydrogen atoms of compound 1, respectively. The 97.75% Lewis and 2.25% non-Lewis structure were present in the studied molecule. The molecular docking results reveal that compound 1 can be used as antituberculosis agent as compare to ethambutol.

A review on current advances in machine learning based diabetes prediction.

Diabetes is a metabolic disorder comprising of high glucose level in blood over a prolonged period in the body as it is not capable of using it properly. The severe complications associated with diabetes include diabetic ketoacidosis, nonketotic hypersmolar coma, cardiovascular disease, stroke, chronic renal failure, retinal damage and foot ulcers. There is a huge increase in the number of patients with diabetes globally and it is considered a major health problem worldwide. Early diagnosis of diabetes is helpful for treatment and reduces the chance of severe complications associated with it. Machine learning algorithms (such as ANN, SVM, Naive Bayes, PLS-DA and deep learning) and data mining techniques are used for detecting interesting patterns for diagnosing and treatment of disease. Current computational methods for diabetes diagnosis have some limitations and are not tested on different datasets or peoples from different countries which limits the practical use of prediction methods. This paper is an effort to summarize the majority of the literature concerned with machine learning and data mining techniques applied for the prediction of diabetes and associated challenges. This report would be helpful for better prediction of disease and improve in understanding the pattern of diabetes. Consequently, the report would be helpful for treatment and reduce risk of other complications of diabetes.

The Role of Advanced Technologies Supplemented with Traditional Methods in Pharmacovigilance Sciences.

BACKGROUND: The immediate automatic systemic monitoring and reporting of adverse drug reactions, improving the efficacy is the utmost need of the medical informatics community. The venturing of advanced digital technologies into the health sector has opened new avenues for rapid monitoring. In recent years, data shared through social media, mobile apps, and other social websites has increased manifolds requiring data mining techniques. OBJECTIVE: The objective of this report is to highlight the role of advanced technologies together with the traditional methods to proactively aid in the early detection of adverse drug reactions concerned with drug safety and pharmacovigilance. METHODS: A thorough search was conducted on papers and patents regarding pharmacovigilance. All articles with respect to the relevant subject were explored and mined from public repositories such as Pubmed, Google Scholar, Springer, ScienceDirect (Elsevier), Web of Science, etc. Results: The European Union's Innovative Medicines Initiative WEB-RADR project has emphasized the development of mobile applications and social media data for reporting adverse effects. Only relevant data has to be captured through the data mining algorithms (DMAs) as it plays an important role in timely prediction of risk with high accuracy using two popular approaches; the frequentist and Bayesian approach. Pharmacovigilance at the pre-marketing stage is useful for the prediction of adverse drug reactions in the early developmental stage of a drug. Later, post-marketing safety reports and clinical data reports are important to be monitored through electronic health records, prescription-event monitoring, spontaneous reporting databases, etc. Conclusion: The advanced technologies supplemented with traditional technologies are the need of the hour for evaluating a product's risk profile and reducing risk in population especially with comorbid conditions and on concomitant medications.

DFT studies on vibrational and electronic spectra, HOMO-LUMO, MEP, HOMA, NBO and molecular docking analysis of benzyl-3-N-(2,4,5-trimethoxyphenylmethylene)hydrazinecarbodithioate.

Benzyl-3-N-(2,4,5-trimethoxyphenylmethylene)hydrazinecarbodithioate (compound 1) is a bidentate and nitrogen-sulfur containing Schiff base, which has been synthesized by the condensation reaction of S-benzylndithiocarbazate and 2,4,5-trimethoxybenzaldehyde. The theoretical calculations of the mentioned compound have been carried out using the more popular density functional theory method, Becke-3-Parameter-Lee-Yang-Parr (B3LYP) in 6-31G+(d,p) basis set. The computational results of the compound were compared with the obtained experimental value. Moreover, the highest occupied molecular orbital, the lowest unoccupied molecular orbital, molecular electrostatic potential, chemical reactivity parameters and natural bond orbital of the optimized structure have been evaluated at the same level of theory. Furthermore, the UV-Vis spectrum of the compound has been carried out for the better understanding of electronic absorption spectra with the help of the time-dependent density functional theory at room temperature. Besides, the molecular docking simulation of the mentioned molecule with target protein was also investigated. In addition, in silico studies were performed to predict absorption, distribution, metabolism, excretion and toxicity profiles of the designed compound. The results indicated that the theoretical data have well correlated with the observed values. The narrow frontier orbital gap indicated that the eventual charge transfer interaction occurs within the studied molecule and showed high chemical reactivity. The global reactivity values showed that the compound is soft molecule, electrophilic species and has strong binding ability with biomolecules. The molecular electrostatic potential structure indicated that the negative and positive potential sites are around electronegative atoms and hydrogen atoms of studied compound, respectively. The natural bond orbital data revealed that the compound contains 97.42% Lewis and 2.58% non-Lewis structure. The intra and inter-molecular charge transfers process occur within the studied compound. The studied compound showed more binding energy (-6.0 kcal/mol) with target protein than hydroxychloroquine (-5.6 kcal/mol). The absorption, distribution, metabolism, excretion and toxicity investigation predicted that the compound has good drug like character.

Comparative transcriptomics uncovers differences in photoautotrophic versus photoheterotrophic modes of nutrition in relation to secondary metabolites biosynthesis in Swertia chirayita.

Swertia chirayita is a high-value medicinal herb exhibiting antidiabetic, hepatoprotective, anticancer, antiediematogenic and antipyretic properties. Scarcity of its plant material has necessitated in vitro production of therapeutic metabolites; however, their yields were low compared to field grown plants. Possible reasons for this could be differences in physiological and biochemical processes between plants grown in photoautotrophic versus photoheterotrophic modes of nutrition. Comparative transcriptomes of S. chirayita were generated to decipher the crucial molecular components associated with the secondary metabolites biosynthesis. Illumina HiSeq sequencing yielded 57,460 and 43,702 transcripts for green house grown (SCFG) and tissue cultured (SCTC) plants, respectively. Biological role analysis (GO and COG assignments) revealed major differences in SCFG and SCTC transcriptomes. KEGG orthology mapped 351 and 341 transcripts onto secondary metabolites biosynthesis pathways for SCFG and SCTC transcriptomes, respectively. Nineteen out of 30 genes from primary metabolism showed higher in silico expression (FPKM) in SCFG versus SCTC, possibly indicating their involvement in regulating the central carbon pool. In silico data were validated by RT-qPCR using a set of 16 genes, wherein 10 genes showed similar expression pattern across both the methods. Comparative transcriptomes identified differentially expressed transcription factors and ABC-type transporters putatively associated with secondary metabolism in S. chirayita. Additionally, functional classification was performed using NCBI Biosystems database. This study identified the molecular components implicated in differential modes of nutrition (photoautotrophic vs. photoheterotrophic) in relation to secondary metabolites production in S. chirayita.

Comparative whole-transcriptome analysis in Podophyllum species identifies key transcription factors contributing to biosynthesis of podophyllotoxin in P. hexandrum.

Podophyllum species (Podophyllum hexandrum Royle and Podophyllum peltatum) are a major source of deriving anticancer drugs from their major chemical constituent, podophyllotoxin. However, information lacks on regulatory components of podophyllotoxin biosynthesis; therefore, different classes of transcription factors were identified through mining transcriptomes of Podophyllum species and validated through qRT-PCR analysis vis-à-vis podophyllotoxin contents in different tissues/organs of Podophyllum hexandrum. A total of 82, 278, 70, and 90 transcripts were identified in shoots and 89, 273, 72, and 91 transcripts in rhizomes of P. hexandrum transcriptome; 70, 268, 48, and 92 transcripts were in shoots and 58, 245, 41, and 85 transcripts in rhizomes of P. peltatum transcriptome corresponding to bZIP, MYB, WRKY, and bHLH families of transcription factors, which have been shown in regulating biosynthesis of secondary metabolites. Two unique transcripts encoding bHLH and MYB/SANT TFs in shoots of P. peltatum (medp_podpe_41091 and medp_podpe_2547) and bZIP and MYB TFs in rhizomes of P. hexandrum (medp_podhe_163581 and medp_podhe_147614) correlated with podophyllotoxin content. Quantification of podophyllotoxin and comparative expression analysis between high (2.51 %) versus low (0.59) podophyllotoxin content accessions revealed 0.04 to ~16-folds increase in transcripts of transcription factors, thereby further supporting the association of identified transcription factors with podophyllotoxin content. bZIP TF showed the highest transcript abundance (19.60-folds) in P. hexandrum rhizomes (2.51 % podophyllotoxin) compared to shoots (0.01 %). In silico analysis of putative promoter regions of pathway genes in other plant species revealed the presence of sequence elements for MYB and WRKY transcription factors, thereby suggesting their role in controlling the production of podophyllotoxin. A repertoire of additional transcription factors has been provided, which can be functionally validated and used in designing a suitable genetic intervention strategy towards enhanced production of podophyllotoxin.

DRPPP: A machine learning based tool for prediction of disease resistance proteins in plants.

Plant disease outbreak is increasing rapidly around the globe and is a major cause for crop loss worldwide. Plants, in turn, have developed diverse defense mechanisms to identify and evade different pathogenic microorganisms. Early identification of plant disease resistance genes (R genes) can be exploited for crop improvement programs. The present prediction methods are either based on sequence similarity/domain-based methods or electronically annotated sequences, which might miss existing unrecognized proteins or low similarity proteins. Therefore, there is an urgent need to devise a novel machine learning technique to address this problem. In the current study, a SVM-based tool was developed for prediction of disease resistance proteins in plants. All known disease resistance (R) proteins (112) were taken as a positive set, whereas manually curated negative dataset consisted of 119 non-R proteins. Feature extraction generated 10,270 features using 16 different methods. The ten-fold cross validation was performed to optimize SVM parameters using radial basis function. The model was derived using libSVM and achieved an overall accuracy of 91.11% on the test dataset. The tool was found to be robust and can be used for high-throughput datasets. The current study provides instant identification of R proteins using machine learning approach, in addition to the similarity or domain prediction methods.

Comparative transcriptome analysis in different tissues of a medicinal herb, Picrorhiza kurroa pinpoints transcription factors regulating picrosides biosynthesis.

Transcriptional regulation of picrosides biosynthesis, the iridoid glycosides of an endangered medicinal herb, Picrorhiza kurroa, is completely unknown. P. kurroa plants obtained from natural habitat accumulate higher picrosides than in-vitro cultured plants, which necessitates identification of transcription factors (TFs) regulating their differential biosynthesis. The current study investigates complete spectrum of different TF classes in P. kurroa transcriptomes and discerns their association with picrosides biosynthesis. Transcriptomes of differential picroside-I content shoots and picroside-II content roots were mined for seven classes of TFs implicated in secondary metabolism regulation in plants. Key TFs were identified through in silico transcript abundance and qPCR analysis was performed to confirm transcript levels of TFs under study in differential content tissues and genotypes. Promoter regions of key picrosides biosynthetic pathway genes were explored to hypothesize which TFs can possibly regulate target genes. A total of 131, 137, 107, 82 and 101 transcripts encoding different TFs families were identified in PKS-25, PKS-15, PKSS, PKR-25 and PKSR transcriptomes, respectively. ERF-18, bHLH-104, NAC-25, 32, 94 and SUF-4 showed elevated expression in roots (up to 37 folds) and shoots (up to 195 folds) of plants obtained from natural habitat, indicating their role as activators of picrosides biosynthesis whereas, elevated expression of WRKY-17, 40, 71 and MYB-4 in low picrosides content conditions suggested their down-regulatory role. In silico analysis of key picrosides biosynthetic pathway gene promoter regions revealed binding domains for ERF-18, NAC-25, WRKY-40 and MYB-4. Identification of candidate TFs contributing towards picrosides biosynthesis is a pre-requisite for designing appropriate metabolic engineering strategies aimed at enhancing picrosides content in vitro and in vivo.

The effect of microwave roasting on the antioxidant properties of the Bangladeshi groundnut cultivar.

BACKGROUND: Groundnut seeds are an important source of bioactive phenolic compounds with noteworthy antioxidant capacity, which may be enhanced by the microwave roasting process. The aim of this work is   to study the changes in antioxidant activity in groundnut seeds during microwave roasting, as a function of roasting time and extract concentration, in order to maximise the phenolic content and antioxidant activity of roasted seeds. METHODS: The study was conducted to evaluate total phenolic content (TPC), total flavonoid content (TFC), and antioxidative activity of methanolic (GME), ethanolic (GEE), and chloroform (GCE) extracts and methanolic extract of oil (GMO) from groundnut seeds exposed to microwaves. The antioxidant activity was investigated using several assays, namely phosphomolybdenum assay, DPPH radical scavenging activity, H2O2 scavenging activity, hydroxyl radical scavenging activity and reducing power. RESULTS: The microwave roasting process significantly increased the TPC, whilst the TFC decreased with roasting time. Antioxidant activity increased with increased roasting time and extract concentration in all extracts. Antioxidant activity increased significantly at lower concentrations; however, the rate of increment decreased gradually as the concentration of the solvent extract increased. Thus, among all the extracts, methanol extracts at all roasting times and extract concentrations appeared to display the highest effectiveness. The various scavenging activities of the samples are ranked in the following order: GME > GEE > GCE > GMO, in both raw and roasted samples. CONCLUSIONS: Both roasting time and extract concentration were found to be critical factors in determining the overall quality of the product. This investigation is important to determine optimum roasting conditions, in order to maximise the anti-oxidative health benefits of the Bangladeshi groundnut cultivar.