Metabolomics-Driven Mining of Metabolite Resources:Applications and Prospects for Improving Vegetable Crops

Vegetable crops possess a prominent nutri-metabolite pool that not only contributes to the crop performance in the fields, but also offers nutritional security for humans. In the pursuit of identifying, quantifying and functionally characterizing the cellular metabolome pool, biomolecule separation technologies, data acquisition platforms, chemical libraries, bioinformatics tools, databases and visualization techniques have come to play significant role. High-throughput metabolomics unravels structurally diverse nutrition-rich metabolites and their entangled interactions in vegetable plants. It has helped to link identified phytometabolites with unique phenotypic traits, nutri-functional characters, defense mechanisms and crop productivity. In this study, we explore mining diverse metabolites, localizing cellular metabolic pathways, classifying functional biomolecules and establishing linkages between metabolic fluxes and genomic regulations, using comprehensive metabolomics deciphers of the plant’s performance in the environment. We discuss exemplary reports covering the implications of metabolomics, addressing metabolic changes in vegetable plants during crop domestication, stage-dependent growth, fruit development, nutri-metabolic capabilities, climatic impacts, plant-microbe-pest interactions and anthropogenic activities. Efforts leading to identify biomarker metabolites, candidate proteins and the genes responsible for plant health, defense mechanisms and nutri-rich crop produce are documented. With the insights on metabolite-QTL (mQTL) driven genetic architecture, molecular breeding in vegetable crops can be revolutionized for developing better nutritional capabilities, improved tolerance against diseases/pests and enhanced climate resilience in plants

Predicting the next pandemic: VACCELERATE ranking of the World Health Organization's Blueprint for Action to Prevent Epidemics

Introduction: The World Health Organization (WHO)'s Research and Development (R&D) Blueprint for Action to Prevent Epidemics, a plan of action, highlighted several infectious diseases as crucial targets for prevention. These infections were selected based on a thorough assessment of factors such as transmissibility, infectivity, severity, and evolutionary potential. In line with this blueprint, the VACCELERATE Site Network approached infectious disease experts to rank the diseases listed in the WHO R&D Blueprint according to their perceived risk of triggering a pandemic. VACCELERATE is an EU-funded collaborative European network of clinical trial sites, established to respond to emerging pandemics and enhance vaccine development capabilities. Methods: Between February and June 2023, a survey was conducted using an online form to collect data from members of the VACCELERATE Site Network and infectious disease experts worldwide. Participants were asked to rank various pathogens based on their perceived risk of causing a pandemic, including those listed in the WHO R&D Blueprint and additional pathogens. Results: A total of 187 responses were obtained from infectious disease experts representing 57 countries, with Germany, Spain, and Italy providing the highest number of replies. Influenza viruses received the highest rankings among the pathogens, with 79 % of participants including them in their top rankings. Disease X, SARS-CoV-2, SARS-CoV, and Ebola virus were also ranked highly. Hantavirus, Lassa virus, Nipah virus, and henipavirus were among the bottom-ranked pathogens in terms of pandemic potential. Conclusion: Influenza, SARS-CoV, SARS-CoV-2, and Ebola virus were found to be the most concerning pathogens with pandemic potential, characterised by transmissibility through respiratory droplets and a reported history of epidemic or pandemic outbreaks

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Not AvailableIn this paper, exponentiated exponential-geometric distribution is considered. Some new explicit expressions for single and product moment of generalized order statistics based on a random sample drawn from the considered distribution are derived. The results for order statistics and upper records as special cases are obtained. Some new explicit expressions for marginal and joint moment generating functions of generalized order statistics are also derived. By using these relations to obtain the means and variances of order statistics and record values. Finally, we considered two characterization Theorems of this distribution based on the conditional expectation of generalized order statistics.Not Availabl

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Not AvailableBibliographic data contains necessary information about literature to help users to recognize and retrieve that resource. These data are used quantitatively by a “Bibliometrician” for analysis and dissemination purpose but with the increasing rate of literature publication in open access journals such as Nucleic Acids Research (NAR), Springer, Oxford Journals etc., it has become difficult to retrieve structured bibliographic information in desired format. A digital bibliographic database contains necessary and structured information about published literature. Bibliographic records of different articles are scattered and resides on different web pages. This thesis presents the retrieval system for bibliographic data of NAR at a single place. For this purpose, parser agents have been developed which access the web pages of NAR and parse the scattered bibliographic data and finally store it into a local bibliographic database. Based on the bibliographic database, “three-tier architecture” has been utilized to display the bibliographic information in systematized format. Using this system, it would be possible to build the network between different authors and affiliations and also other analytical reports can be generated.Not Availabl

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Not AvailableRNA-Seq has gained immense popularity and emerged as a potential high-throughput platform for identification of differentially expressed (DE) genes. In order to estimate the nature of differential genes, it is important to find statistical distributional property of the data. In the present study we propose a new hybrid model (NBPFCROS) based on parametric and non-parametric statistic for the identification of DE genes. The NBP model based on Compound mixture of Poisson-gamma distribution is used as a parametric statistic and Fold change value derived using fold change rank ordering statistics (FCROS) algorithm is used as non-parametric statistic, we used a gene significance score pi-value by combining expression fold change (f value) and statistical significance (p-value). The performance of NBPFCROS model was compared with NBP, FCROS, edgeR and DESeq2 models using synthetic and real RNA-Seq datasets and it was found that the developed model NBPFCROS is more robust as compared to the other models.Not Availabl

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Not AvailablePigeon pea is avital food legume crop grown in India. Pigeon pea is consumed as green pea, whole grain or split pea. Many studies have been under taken by researchers for the analysis of whole genome sequence of pigeon pea. Also, post transcriptional gene regulation has emerged as an important technology for crop sciences. The discoveries of miRNAs in plants and the growing evidence of their involvement in a variety of functional roles have produced a great deal of excitement in plant biology. Approaches developed for identification of miRNAs are in-vitro, in-silico and combination of both these. This study was undertaken to identify the miRNAs in pigeon pea using computational methods. Eleven miRNAs were identified using this method. This study will help in improved understanding of molecular mechanisms of miRNA and development of novel and more precise techniques for better understanding of post-transcriptional gene silencing in pigeon pea.Not Availabl

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Not AvailableChromohalobacter salexigens, a Gammaproteobacterium belonging to the family Halomonadaceae, shows a broad salinity range for growth. In order to reveal the factors influencing architecture of protein coding genes in C. salexigens, pattern of synonymous codon usage bias has been investigated. Overall codon usage analysis of the microorganism revealed that C and G ending codons are predominantly used in all the genes which are indicative of mutational bias. Multivariate statistical analysis showed that the genes are separated along the first major explanatory axis according to their expression levels and their genomic GC content at the synonymous third positions of the codons. Both NC plot and correspondence analysis on Relative Synonymous Codon Usage (RSCU) indicates that the variation in codon usage among the genes may be due to mutational bias at the DNA level and natural selection acting at the level of mRNA translation. Gene length and the hydrophobicity of the encoded protein also influence the codon usage variation of genes to some extent. A comparison of the relative synonymous codon usage between 10% each of highly and lowly expressed genes determines 23 optimal codons, which are statistically over represented in the former group of genes and may provide useful information for salt-stressed gene prediction and gene-transformation. Furthermore, genes for regulatory functions; mobile and extrachromosomal element functions; and cell envelope are observed to be highly expressed. The study could provide insight into the gene expression response of halophilic bacteria and facilitate establishment of effective strategies to develop salt-tolerant crops of agronomic value.Not Availabl

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Not AvailableHalophilic archaea/bacteria adapt to different salt concentration, namely extreme, moderate and low. These type of adaptations may occur as a result of modification of protein structure and other changes in different cell organelles. Thus proteins may play an important role in the adaptation of halophilic archaea/bacteria to saline conditions. The Halophile protein database (HProtDB) is a systematic attempt to document the biochemical and biophysical properties of proteins from halophilic archaea/bacteria which may be involved in adaptation of these organisms to saline conditions. In this database, various physicochemical properties such as molecular weight, theoretical pI, amino acid composition, atomic composition, estimated half-life, instability index, aliphatic index and grand average of hydropathicity (Gravy) have been listed. These physicochemical properties play an important role in identifying the protein structure, bonding pattern and function of the specific proteins. This database is comprehensive, manually curated, non-redundant catalogue of proteins. The database currently contains 59 897 proteins properties extracted from 21 different strains of halophilic archaea/bacteria. The database can be accessed through link. Database URL: http://webapp.cabgrid.res.in/protein/Not Availabl

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Not AvailableCodon is the basic unit for biological message transmission during synthesis of proteins in an organism. Codon Usage Bias is preferential usage among synonymous codons, in an organisms. This preferential use of a synonymous codon was found not only among species but also occurs among genes within the same genome of a species. This variation of codon usage patterns are controlled by natural processes such as mutation, drift and pressure. In this study, we have used computational as well as statistical techniques for finding codon usage bias and codon context pattern of Salinibacter ruber (extreme halophilic), Chromohalobacter salexigens (moderate halophilic) and Rhizobium etli (nonhalophilic). In addition to this, compositional variation in translated amino acid frequency, effective number of codons and optimal codons were also studied. A plot of ENc versus GC3s suggests that both mutation bias and translational selection contribute to these differences of codon bias. However, mutation bias is the driving force of the synonymous codon usage patterns in halophilic bacteria (Salinibacter ruber and Chromohalobacter salexigens) and translational selection seems to affect codon usage pattern in non-halophilic bacteria (Rhizobium etli). Correspondence analysis of Relative Synonymous Codon Usage revealed different clusters of genes varying in numbers in the bacteria under study. Moreover, codon context pattern was also seen variable in these bacteria. These results clearly indicate the variation in the codon usage pattern in these bacterial genomes.Not Availabl

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Not AvailableCodon is the basic unit for biological message transmission during synthesis of proteins in an organism. Codon Usage Bias is preferential usage among synonymous codons, in an organisms. This preferential use of a synonymous codon was found not only among species but also occurs among genes within the same genome of a species. This variation of codon usage patterns are controlled by natural processes such as mutation, drift and pressure. In this study, we have used computational as well as statistical techniques for finding codon usage bias and codon context pattern of Salinibacter ruber (extreme halophilic), Chromohalobacter salexigens (moderate halophilic) and Rhizobium etli (nonhalophilic). In addition to this, compositional variation in translated amino acid frequency, effective number of codons and optimal codons were also studied. A plot of ENc versus GC3s suggests that both mutation bias and translational selection contribute to these differences of codon bias. However, mutation bias is the driving force of the synonymous codon usage patterns in halophilic bacteria (Salinibacter ruber and Chromohalobacter salexigens) and translational selection seems to affect codon usage pattern in non-halophilic bacteria (Rhizobium etli). Correspondence analysis of Relative Synonymous Codon Usage revealed different clusters of genes varying in numbers in the bacteria under study. Moreover, codon context pattern was also seen variable in these bacteria. These results clearly indicate the variation in the codon usage pattern in these bacterial genomes.Not Availabl