Computational identification of potential inhibitory compounds in Indian medicinal and aromatic plant species against major pathogenicity determinants of SARS-CoV-2.

SARS-CoV-2 (COVID-19) viral pandemic has been reported across 223 countries and territories. Globalized vaccination programs alongside administration of repurposed drugs will assumingly confer a stronger and longer individual specific immune protection. However, considering possible recurrence of the disease via new variants, a conveniently deliverable phytopharmaceutical drug might be the best option for COVID-19 treatment. In the current study, the efforts have been made to identify potential leads for inhalation therapy as nasal swabs have been reported to transfer viral load prominently. In that direction, 2363 Essential oil (EOs) compounds from Indian medicinal and aromatic plants were screened through docking analysis and potential candidates were shortlisted that can interfere with viral pathogenicity. The main protease (Mpro) of SARS-CoV-2 interacted closely with jatamansin (JM), 6,7-dehydroferruginol (FG) and beta-sitosterol (BS), while Papain-like Protease (PLpro) with friedelane-3-one (F3O) and lantadene D (LD) independently. Reduced Lantadene A (LAR) exhibited preferable interaction with RNA-dependent-RNA-polymerase (RdRp) whereas Lantadene A (LA) with RdRp and spike-glycoprotein (SG-pro) both target proteins. When compared against highest binding affinity conformations of well-known inhibitors of targets, these prioritized compounds conferred superior or comparable SARS-CoV-2 protein inhibition. Additionally, promising results were noted from pharmacokinetics prediction for all shortlisted compounds. Besides, molecular dynamics simulation for 100 ns in two replicates and binding free energy analysis revealed the stability of complexes with optimum compactness. To the best of our knowledge, the current investigation is a unique initial attempt whereby EO compounds have been computationally screened, irrespective of their known medicinal properties to fight COVID-19 infection.Communicated by Ramaswamy H. Sarma.

Complexity of gene paralogues resolved in biosynthetic pathway of hepatoprotective iridoid glycosides in a medicinal herb, Picrorhiza kurroa through differential NGS transcriptomes.

Picrorhiza kurroa is a medicinal herb with diverse pharmacological applications due to the presence of iridoid glycosides, picroside-I (P-I), and picroside-II (P-II), among others. Any genetic improvement in this medicinal herb can only be undertaken if the biosynthetic pathway genes are correctly identified. Our previous studies have deciphered biosynthetic pathways for P-I and P-II, however, the occurrence of multiple copies of genes has been a stumbling block in their usage. Therefore, a methodological strategy was designed to identify and prioritize paralogues of pathway genes associated with contents of P-I and P-II. We used differential transcriptomes varying for P-I and P-II contents in different tissues of P. kurroa. All transcripts for a particular pathway gene were identified, clustered based on multiple sequence alignment to notify as a representative of the same gene (≥ 99% sequence identity) or a paralogue of the same gene. Further, individual paralogues were tested for their expression level via qRT-PCR in tissue-specific manner. In total 44 paralogues in 14 key genes have been identified out of which 19 gene paralogues showed the highest expression pattern via qRT-PCR. Overall analysis shortlisted 6 gene paralogues, PKHMGR3, PKPAL2, PKDXPS1, PK4CL2, PKG10H2 and PKIS2 that might be playing role in the biosynthesis of P-I and P-II, however, their functional analysis need to be further validated either through gene silencing or over-expression. The usefulness of this approach can be expanded to other non-model plant species for which transcriptome resources have been generated.

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.

Modular Design of Picroside-II Biosynthesis Deciphered through NGS Transcriptomes and Metabolic Intermediates Analysis in Naturally Variant Chemotypes of a Medicinal Herb, Picrorhiza kurroa.

Picroside-II (P-II), an iridoid glycoside, is used as an active ingredient of various commercial herbal formulations available for the treatment of liver ailments. Despite this, the knowledge of P-II biosynthesis remains scarce owing to its negligence in Picrorhiza kurroa shoots which sets constant barrier for function validation experiments. In this study, we utilized natural variation for P-II content in stolon tissues of different P. kurroa accessions and deciphered its metabolic route by integrating metabolomics of intermediates with differential NGS transcriptomes. Upon navigating through high vs. low P-II content accessions (1.3-2.6%), we have established that P-II is biosynthesized via degradation of ferulic acid (FA) to produce vanillic acid (VA) which acts as its immediate biosynthetic precursor. Moreover, the FA treatment in vitro at 150 µM concentration provided further confirmation with 2-fold rise in VA content. Interestingly, the cross-talk between different compartments of P. kurroa, i.e., shoots and stolons, resolved spatial complexity of P-II biosynthesis and consequently speculated the burgeoning necessity to bridge gap between VA and P-II production in P. kurroa shoots. This work thus, offers a forward looking strategy to produce both P-I and P-II in shoot cultures, a step toward providing a sustainable production platform for these medicinal compounds via-à-vis relieving pressure from natural habitat of P. kurroa.

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.

NGS Transcriptomes and Enzyme Inhibitors Unravel Complexity of Picrosides Biosynthesis in Picrorhiza kurroa Royle ex. Benth.

Picrorhiza kurroa is an important medicinal herb valued for iridoid glycosides, Picroside-I (P-I) and Picroside-II (P-II), which have several pharmacological activities. Genetic interventions for developing a picroside production platform would require knowledge on biosynthetic pathway and key control points, which does not exist as of today. The current study reports that geranyl pyrophosphate (GPP) moiety is mainly contributed by the non-mevalonate (MEP) route, which is further modified to P-I and P-II through phenylpropanoid and iridoid pathways, in total consisting of 41 and 35 enzymatic steps, respectively. The role of the MEP pathway was ascertained through enzyme inhibitors fosmidomycin and mevinolin along with importance of other integrating pathways using glyphosate, aminooxy acetic acid (AOA) and actinomycin D, which overall resulted in 17%-92% inhibition of P-I accumulation. Retrieval of gene sequences for enzymatic steps from NGS transcriptomes and their expression analysis vis-à-vis picrosides content in different tissues/organs showed elevated transcripts for twenty genes, which were further shortlisted to seven key genes, ISPD, DXPS, ISPE, PMK, 2HFD, EPSPS and SK, on the basis of expression analysis between high versus low picrosides content strains of P. kurroa so as to eliminate tissue type/ developmental variations in picrosides contents. The higher expression of the majority of the MEP pathway genes (ISPD, DXPS and ISPE), coupled with higher inhibition of DXPR enzyme by fosmidomycin, suggested that the MEP route contributed to the biosynthesis of P-I in P. kurroa. The outcome of the study is expected to be useful in designing a suitable genetic intervention strategy towards enhanced production of picrosides. Possible key genes contributing to picroside biosynthesis have been identified with potential implications in molecular breeding and metabolic engineering of P. kurroa.

Contents of therapeutic metabolites in Swertia chirayita correlate with the expression profiles of multiple genes in corresponding biosynthesis pathways.

Swertia chirayita, an endangered medicinal herb, contains three major secondary metabolites swertiamarin, amarogentin and mangiferin, exhibiting valuable therapeutic traits. No information exists as of today on the biosynthesis of these metabolites in S. chirayita. The current study reports the expression profiling of swertiamarin, amarogentin and mangiferin biosynthesis pathway genes and their correlation with the respective metabolites content in different tissues of S. chirayita. Root tissues of greenhouse grown plants contained the maximum amount of secoiridoids (swertiamarin, 2.8% of fr. wt and amarogentin, 0.1% of fr. wt), whereas maximum accumulation of mangiferin (1.0% of fr. wt) was observed in floral organs. Differential gene expression analysis and their subsequent principal component analysis unveiled ten genes (encoding HMGR, PMK, MVK, ISPD, ISPE, GES, G10H, 8HGO, IS and 7DLGT) of the secoiridoids biosynthesis pathway and five genes (encoding EPSPS, PAL, ADT, CM and CS) of mangiferin biosynthesis with elevated transcript amounts in relation to corresponding metabolite contents. Three genes of the secoiridoids biosynthesis pathway (encoding PMK, ISPD and IS) showed elevated levels (∼57-104 fold increase in roots), and EPSPS of mangiferin biosynthesis showed an about 117 fold increase in transcripts in leaf tissues of the greenhouse grown plants. The study does provide leads on potential candidate genes correlating with the metabolites biosynthesis in S. chirayita as an initiative towards its genetic improvement.

Sex-Biased Temporal Gene Expression in Male and Female Floral Buds of Seabuckthorn (Hippophae rhamnoides).

Seabuckthorn is an economically important dioecious plant in which mechanism of sex determination is unknown. The study was conducted to identify seabuckthorn homologous genes involved in floral development which may have role in sex determination. Forty four putative Genes involved in sex determination (GISD) reported in model plants were shortlisted from literature survey, and twenty nine seabuckthorn homologous sequences were identified from available seabuckthorn genomic resources. Of these, 21 genes were found to differentially express in either male or female flower bud stages. HrCRY2 was significantly expressed in female flower buds only while HrCO had significant expression in male flowers only. Among the three male and female floral development stages (FDS), male stage II had significant expression of most of the GISD. Information on these sex-specific expressed genes will help in elucidating sex determination mechanism in seabuckthorn.

Expression analysis of biosynthetic pathway genes vis-à-vis podophyllotoxin content in Podophyllum hexandrum Royle.

Podophyllum hexandrum Royle is known for its vast medicinal properties, particularly anticancer. It contains higher amount of podophyllotoxin (4.3 %), compared to Podophyllum peltatum (0.025 %) and other plant species; as a result, it has been used worldwide in the preparation of various drugs including anticancer, antimalarial, antiviral, antioxidant, antifungal, and so on. Currently, Etoposide (VP-16-213), Vumon® (Teniposide; VM-26), Etopophos®, Pod-Ben- 25, Condofil, Verrusol, and Warticon are available in the market. Due to highly complex synthesis and low cell culture yields of podophyllotoxin (0.3 %), the supply of raw material cannot be met due to increasing industrial demands. The knowledge on podophyllotoxin biosynthetic pathway vis-à-vis expression status of genes is fragmentary. Quantitative expression analysis of 21 pathway genes has revealed 9 genes, namely SD, PD, PCH, CM, CMT, CAD, CCR, C4H, and ADH, that showed increase in transcript abundance up to 1.4 to 23.05 folds, respectively, vis-à-vis podophyllotoxin content in roots (1.37 %) and rhizomes (3.05 %) of P. hexandrum. In silico analysis of putative cis-regulatory elements in promoter regions of overexpressed genes showed the presence of common Skn-1 motif and MBS elements in CMT, CAD, CCR, C4H, and ADH genes, thereby, suggesting their common regulation. The outcome of the study has resulted in the identification of suitable candidate genes which might be contributing to podophyllotoxin biosynthesis that can act as potential targets for any genetic intervention strategies aimed at its enhanced production.

Common antigens prediction in bacterial bioweapons: a perspective for vaccine design.

Bioweapons (BWs) are a serious threat to mankind and the lack of efficient vaccines against bacterial bioweapons (BBWs) further worsens the situation in face of BW attack. Experts believe that difficulties in detection and ease in dissemination of deadly pathogens make BW a better option for attack compared to nuclear weapons. Molecular biology techniques facilitate the use of genetically modified BBWs thus creating uncertainty on which bacteria will be used for BW attack. In the present work, available resources such as proteomic sequences of BBWs, protective antigenic proteins (PAPs) reported in Protegen database and VaxiJen dataset, and immunogenic epitopes in immune epitope database (IEDB) were used to predict potential broad-specific vaccine candidates against BBWs. Comparison of proteomes sequences of BBWs and their analyses using in-house PERL scripts identified 44 conserved proteins and many of them were known to be immunogenic. Comparison of conserved proteins against PAPs identified six either as PAPs or their homologues with a potential of providing protection against multiple pathogens. Similarly, mapping of conserved proteins against experimentally known IEDB epitopes identified six epitopes which had exact epitope match in four proteins including three from earlier predicted six PAPs. These epitopes were also reported to provide protection against several pathogens. In the backdrop of conserved heat shock GroEL protein from Salmonella enterica providing protection against five diverse bacterial pathogens involved in different diseases, and synthetic proteins produced by combination of epitopes from Mycobacterium tuberculosis and 4 viruses providing protection against both bacterium and viruses, the identified putative immunogenic conserved proteins and immune-protective epitopes can further be explored for their potential as broad-specific vaccine candidates against BBWs.

Jenner-predict server: prediction of protein vaccine candidates (PVCs) in bacteria based on host-pathogen interactions.

BACKGROUND: Subunit vaccines based on recombinant proteins have been effective in preventing infectious diseases and are expected to meet the demands of future vaccine development. Computational approach, especially reverse vaccinology (RV) method has enormous potential for identification of protein vaccine candidates (PVCs) from a proteome. The existing protective antigen prediction software and web servers have low prediction accuracy leading to limited applications for vaccine development. Besides machine learning techniques, those software and web servers have considered only protein's adhesin-likeliness as criterion for identification of PVCs. Several non-adhesin functional classes of proteins involved in host-pathogen interactions and pathogenesis are known to provide protection against bacterial infections. Therefore, knowledge of bacterial pathogenesis has potential to identify PVCs. RESULTS: A web server, Jenner-Predict, has been developed for prediction of PVCs from proteomes of bacterial pathogens. The web server targets host-pathogen interactions and pathogenesis by considering known functional domains from protein classes such as adhesin, virulence, invasin, porin, flagellin, colonization, toxin, choline-binding, penicillin-binding, transferring-binding, fibronectin-binding and solute-binding. It predicts non-cytosolic proteins containing above domains as PVCs. It also provides vaccine potential of PVCs in terms of their possible immunogenicity by comparing with experimentally known IEDB epitopes, absence of autoimmunity and conservation in different strains. Predicted PVCs are prioritized so that only few prospective PVCs could be validated experimentally. The performance of web server was evaluated against known protective antigens from diverse classes of bacteria reported in Protegen database and datasets used for VaxiJen server development. The web server efficiently predicted known vaccine candidates reported from Streptococcus pneumoniae and Escherichia coli proteomes. The Jenner-Predict server outperformed NERVE, Vaxign and VaxiJen methods. It has sensitivity of 0.774 and 0.711 for Protegen and VaxiJen dataset, respectively while specificity of 0.940 has been obtained for the latter dataset. CONCLUSIONS: Better prediction accuracy of Jenner-Predict web server signifies that domains involved in host-pathogen interactions and pathogenesis are better criteria for prediction of PVCs. The web server has successfully predicted maximum known PVCs belonging to different functional classes. Jenner-Predict server is freely accessible at http://117.211.115.67/vaccine/home.html.

EpiCombFlu: exploring known influenza epitopes and their combination to design a universal influenza vaccine.

MOTIVATION: Influenza is responsible for half a million deaths annually, and vaccination is the best preventive measure against this pervasive health problem. Influenza vaccines developed from surveillance data of each season are strain-specific, and therefore, are unable to provide protection against pandemic strains arising from antigenic shift and drift. Seasonal epidemics and occasional pandemics of influenza have created a need for a universal influenza vaccine (UIV). Researchers have shown that a combination of conserved epitopes has the potential to be used as a UIV. RESULT: In the present work, available data on strains, proteins, epitopes and their associated information were used to develop a Web resource, 'EpiCombFlu', which can explore different influenza epitopes and their combinations for conservation among different strains, population coverage and immune response for vaccine design. Forward selection algorithm was implemented in EpiCombFlu to select optimum combination of epitopes that may be expressed and evaluated as potential UIV. AVAILABILITY: The Web resource is freely available at http://117.211.115.67/influenza/home.html. CONTACT: chittaranjan.rout@juit.ac.in SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Chemometric profile of root extracts of Rhodiola imbricata Edgew. with hyphenated gas chromatography mass spectrometric technique.

Rhodiola imbricata Edgew. (Rose root or Arctic root or Golden root or Shrolo), belonging to the family Crassulaceae, is an important food crop and medicinal plant in the Indian trans-Himalayan cold desert. Chemometric profile of the n-hexane, chloroform, dichloroethane, ethyl acetate, methanol, and 60% ethanol root extracts of R. imbricata were performed by hyphenated gas chromatography mass spectrometry (GC/MS) technique. GC/MS analysis was carried out using Thermo Finnigan PolarisQ Ion Trap GC/MS MS system comprising of an AS2000 liquid autosampler. Interpretation on mass spectrum of GC/MS was done using the NIST/EPA/NIH Mass Spectral Database, with NIST MS search program v.2.0g. Chemometric profile of root extracts revealed the presence of 63 phyto-chemotypes, among them, 1-pentacosanol; stigmast-5-en-3-ol, (3ß,24S); 1-teracosanol; 1-henteracontanol; 17-pentatriacontene; 13-tetradecen-1-ol acetate; methyl tri-butyl ammonium chloride; bis(2-ethylhexyl) phthalate; 7,8-dimethylbenzocyclooctene; ethyl linoleate; 3-methoxy-5-methylphenol; hexadecanoic acid; camphor; 1,3-dimethoxybenzene; thujone; 1,3-benzenediol, 5-pentadecyl; benzenemethanol, 3-hydroxy, 5-methoxy; cholest-4-ene-3,6-dione; dodecanoic acid, 3-hydroxy; octadecane, 1-chloro; ethanone, 1-(4-hydroxyphenyl); α-tocopherol; ascaridole; campesterol; 1-dotriacontane; heptadecane, 9-hexyl were found to be present in major amount. Eventually, in the present study we have found phytosterols, terpenoids, fatty acids, fatty acid esters, alkyl halides, phenols, alcohols, ethers, alkanes, and alkenes as the major group of phyto-chemotypes in the different root extracts of R. imbricata. All these compounds identified by GC/MS analysis were further investigated for their biological activities and it was found that they possess a diverse range of positive pharmacological actions. In future, isolation of individual phyto-chemotypes and subjecting them to biological activity will definitely prove fruitful results in designing a novel drug.

AFLP fingerprinting of tartary buckwheat accessions (Fagopyrum tataricum) displaying rutin content variation.

In light of the economic importance of buckwheat as well as existence of enormous accessions of Fagopyrum species in the Himalayan regions of India, the characterization of tartary buckwheat for rutin content variation vis-à-vis DNA fingerprinting was undertaken so as to identify fingerprint profiles unique to high rutin content accessions. Rutin content analysis in mature seeds of 195 accessions of Fagopyrum tataricum showed a wide range of variation (6 µg/mg to 30 µg/mg D.W.) with most of the accessions (81%) containing 10-16 µg/mg of rutin followed by 14% accessions with significantly higher rutin content (17 µg/mg to 30 µg/mg) and 5% accessions with low rutin content (≤10 µg/mg). AFLP fingerprinting of 18 accessions having high (≥17 µg/mg) and low rutin content (≤10 µg/mg) with 19 EcoRI/MseI primer combinations yielded 136 polymorphic fragments out of total 907. The hierarchical and model-based cluster analyses of AFLP data strongly suggested that the 18 populations of F. tataricum were clustered into two separate groups. The high and low rutin content accessions were clustered into two separate groups based on AFLP fingerprinting. The AFLP fingerprints associated with high rutin content accessions of F. tataricum are expected to be useful for evaluation, conservation and genetic improvement of buckwheat.

UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria.

BACKGROUND: Targeting conserved proteins of bacteria through antibacterial medications has resulted in both the development of resistant strains and changes to human health by destroying beneficial microbes which eventually become breeding grounds for the evolution of resistances. Despite the availability of more than 800 genomes sequences, 430 pathways, 4743 enzymes, 9257 metabolic reactions and protein (three-dimensional) 3D structures in bacteria, no pathogen-specific computational drug target identification tool has been developed. METHODS: A web server, UniDrug-Target, which combines bacterial biological information and computational methods to stringently identify pathogen-specific proteins as drug targets, has been designed. Besides predicting pathogen-specific proteins essentiality, chokepoint property, etc., three new algorithms were developed and implemented by using protein sequences, domains, structures, and metabolic reactions for construction of partial metabolic networks (PMNs), determination of conservation in critical residues, and variation analysis of residues forming similar cavities in proteins sequences. First, PMNs are constructed to determine the extent of disturbances in metabolite production by targeting a protein as drug target. Conservation of pathogen-specific protein's critical residues involved in cavity formation and biological function determined at domain-level with low-matching sequences. Last, variation analysis of residues forming similar cavities in proteins sequences from pathogenic versus non-pathogenic bacteria and humans is performed. RESULTS: The server is capable of predicting drug targets for any sequenced pathogenic bacteria having fasta sequences and annotated information. The utility of UniDrug-Target server was demonstrated for Mycobacterium tuberculosis (H37Rv). The UniDrug-Target identified 265 mycobacteria pathogen-specific proteins, including 17 essential proteins which can be potential drug targets. CONCLUSIONS/SIGNIFICANCE: UniDrug-Target is expected to accelerate pathogen-specific drug targets identification which will increase their success and durability as drugs developed against them have less chance to develop resistances and adverse impact on environment. The server is freely available at http://117.211.115.67/UDT/main.html. The standalone application (source codes) is available at http://www.bioinformatics.org/ftp/pub/bioinfojuit/UDT.rar.

Expression of flavonoid biosynthesis genes vis-à-vis rutin content variation in different growth stages of Fagopyrum species.

Buckwheat is one of the field crops with the highest concentration of rutin, an important flavonoid of medicinal value. Two species of buckwheat, Fagopyrum esculentum and Fagopyrum tataricum, are the major sources of rutin. Seeds of latter contain 40-50× higher rutin compared to the former. The physiological and molecular bases of rutin content variation between Fagopyrum species are not known. The current study investigated the differences in rutin content in seeds and in other tissues and growth stages of two Fagopyrum species, and also correlated those differences with the expression of flavonoid pathway genes. The analysis of rutin content dynamics at different growth stages, S1-S9 (from seed germination to mature seed formation) of Fagopyrum species revealed that rutin content was higher during seedling stages of F. tataricum (3.5 to 4.6-fold) compared to F. esculentum and then increased exponentially from stages S3 to S6 (different leaf maturing stages and inflorescence) of F. esculentum, whereas it fluctuated in F. tataricum. The rutin content was highest in the inflorescence stage (S6) of both species, with a relatively higher biosynthesis and accumulation during post-flowering stages of F. tataricum compared to F. esculentum. The expression of flavonoid pathway genes, through qRT-PCR, in different growth stages vis-à-vis rutin content variation showed differential expression for four genes, PAL, CHS, CHI and FLS with the amounts of transcripts relatively higher in F. tataricum compared to F. esculentum, thereby, correlating these genes with the biosynthesis and accumulation of rutin. The expression of PAL was highest, 7.69 and 8.96-fold in Stages 2 (seedling stage) and 9 (fully developed seeds) of F. tataricum compared to F. esculentum, respectively. The expression of the CHS gene correlated with the rutin content because it was highest in the flowers (S6) and fully developed seeds (S9) of both Fagopyrum species, with relatively higher transcript amounts (2.13 and 3.19-fold, respectively) in F. tataricum (IC-329457) compared to F. esculentum (IC-540858). This study provides useful information on molecular and physiological dynamics of rutin biosynthesis and accumulation in Fagopyrum species and the correlation of expression of flavonoid biosynthesis genes with the rutin content can be useful in planning for genetic improvement.