Gitanjali Yadav

NRPS-PKS: a knowledge-based resource for analysis of NRPS/PKS megasynthases

NRPS-PKS is web-based software for analysing large multi-enzymatic, multi-domain megasynthases that are involved in the biosynthesis of pharmaceutically important natural products such as cyclosporin, rifamycin and erythromycin. NRPS-PKS has been developed based on a comprehensive analysis of the sequence and structural features of several experimentally characterized biosynthetic gene clusters. The results of these analyses have been organized as four integrated searchable databases for elucidating domain organization and substrate specificity of nonribosomal peptide synthetases and three types of polyketide synthases. These databases work as the backend of NRPS-PKS and provide the knowledge base for predicting domain organization and substrate specificity of uncharacterized NRPS/PKS clusters. Benchmarking on a large set of biosynthetic gene clusters has demonstrated that, apart from correct identification of NRPS and PKS domains, NRPS-PKS can also predict specificities of adenylation and acyltransferase domains with reasonably high accuracy. These features of NRPS-PKS make it a valuable resource for identification of natural products biosynthesized by NRPS/PKS gene clusters found in newly sequenced genomes. The training and test sets of gene clusters included in NRPS-PKS correlate information on 307 open reading frames, 2223 functional protein domains, 68 starter/extender precursors and their specific recognition motifs, and also the chemical structure of 101 natural products from four different families. NRPS-PKS is a unique resource which provides a user-friendly interface for correlating chemical structures of natural products with the domains and modules in the corresponding nonribosomal peptide synthetases or polyketide synthases. It also provides guidelines for domain/module swapping as well as site-directed mutagenesis experiments to engineer biosynthesis of novel natural products. NRPS-PKS can be accessed at http://www.nii.res.in/nrps-pks.html.

A draft genome sequence of the pulse crop chickpea (Cicer arietinum L.).

Cicer arietinum L. (chickpea) is the third most important food legume crop. We have generated the draft sequence of a desi-type chickpea genome using next-generation sequencing platforms, bacterial artificial chromosome end sequences and a genetic map. The 520-Mb assembly covers 70% of the predicted 740-Mb genome length, and more than 80% of the gene space. Genome analysis predicts the presence of 27,571 genes and 210 Mb as repeat elements. The gene expression analysis performed using 274 million RNA-Seq reads identified several tissue-specific and stress-responsive genes. Although segmental duplicated blocks are observed, the chickpea genome does not exhibit any indication of recent whole-genome duplication. Nucleotide diversity analysis provides an assessment of a narrow genetic base within the chickpea cultivars. We have developed a resource for genetic markers by comparing the genome sequences of one wild and three cultivated chickpea genotypes. The draft genome sequence is expected to facilitate genetic enhancement and breeding to develop improved chickpea varieties.

Computational Approach for Prediction of Domain Organization and Substrate Specificity of Modular Polyketide Synthases

Modular polyketide synthases (PKSs) are large multi-enzymatic, multi-domain megasynthases, which are involved in the biosynthesis of a class of pharmaceutically important natural products, namely polyketides. These enzymes harbor a set of repetitive active sites termed modules and the domains present in each module dictate the chemical moiety that would add to a growing polyketide chain. This modular logic of biosynthesis has been exploited with reasonable success to produce several novel compounds by genetic manipulation. However, for harnessing their vast potential of combinatorial biosynthesis, it is essential to develop knowledge based in silico approaches for correlating the sequence and domain organization of PKSs to their polyketide products. In this work, we have carried out extensive sequence analysis of experimentally characterized PKS clusters to develop an automated computational protocol for unambiguous identification of various PKS domains in a polypeptide sequence. A structure based approach has been used to identify the putative active site residues of acyltransferase (AT) domains, which control the specificities for various starter and extender units during polyketide biosynthesis. On the basis of the analysis of the active site residues and molecular modelling of substrates in the active site of representative AT domains, we have identified a crucial residue that is likely to play a major role in discriminating between malonate and methylmalonate during selection of extender groups by this domain. Structural modelling has also explained the experimentally observed chiral preference of AT domain in substrate selection. This computational protocol has been used to predict the domain organization and substrate specificity for PKS clusters from various microbial genomes. The results of our analysis as well as the computational tools for prediction of domain organization and substrate specificity have been organized in the form of a searchable computerized database (PKSDB). PKSDB would serve as a valuable tool for identification of polyketide products biosynthesized by uncharacterized PKS clusters. This database can also provide guidelines for rational design of experiments to engineer novel polyketides.

Gene Discovery and Tissue-Specific Transcriptome Analysis in Chickpea with Massively Parallel Pyrosequencing and Web Resource Development

Chickpea (Cicer arietinum) is an important food legume crop but lags in the availability of genomic resources. In this study, we have generated about 2 million high-quality sequences of average length of 372 bp using pyrosequencing technology. The optimization of de novo assembly clearly indicated that hybrid assembly of long-read and short-read primary assemblies gave better results. The hybrid assembly generated a set of 34,760 transcripts with an average length of 1,020 bp representing about 4.8% (35.5 Mb) of the total chickpea genome. We identified more than 4,000 simple sequence repeats, which can be developed as functional molecular markers in chickpea. Putative function and Gene Ontology terms were assigned to at least 73.2% and 71.0% of chickpea transcripts, respectively. We have also identified several chickpea transcripts that showed tissue-specific expression and validated the results using real-time polymerase chain reaction analysis. Based on sequence comparison with other species within the plant kingdom, we identified two sets of lineage-specific genes, including those conserved in the Fabaceae family (legume specific) and those lacking significant similarity with any non chickpea species (chickpea specific). Finally, we have developed a Web resource, Chickpea Transcriptome Database, which provides public access to the data and results reported in this study. The strategy for optimization of de novo assembly presented here may further facilitate the transcriptome sequencing and characterization in other organisms. Most importantly, the data and results reported in this study will help to accelerate research in various areas of genomics and implementing breeding programs in chickpea.

SBSPKS: structure based sequence analysis of polyketide synthases

Polyketide synthases (PKSs) catalyze biosynthesis of a diverse family of pharmaceutically important secondary metabolites. Bioinformatics analysis of sequence and structural features of PKS proteins plays a crucial role in discovery of new natural products by genome mining, as well as in design of novel secondary metabolites by biosynthetic engineering. The availability of the crystal structures of various PKS catalytic and docking domains, and mammalian fatty acid synthase module prompted us to develop SBSPKS software which consists of three major components. Model_3D_PKS can be used for modeling, visualization and analysis of 3D structure of individual PKS catalytic domains, dimeric structures for complete PKS modules and prediction of substrate specificity. Dock_Dom_Anal identifies the key interacting residue pairs in inter-subunit interfaces based on alignment of inter-polypeptide linker sequences to the docking domain structure. In case of modular PKS with multiple open reading frames (ORFs), it can predict the cognate order of substrate channeling based on combinatorial evaluation of all possible interface contacts. NRPS–PKS provides user friendly tools for identifying various catalytic domains in the sequence of a Type I PKS protein and comparing them with experimentally characterized PKS/NRPS clusters cataloged in the backend databases of SBSPKS. SBSPKS is available at http://www.nii.ac.in/sbspks.html.

SEARCHPKS: a program for detection and analysis of polyketide synthase domains

SEARCHPKS is a software for detection and analysis of polyketide synthase (PKS) domains in a polypeptide sequence. Modular polyketide synthases are unusually large multi-enzymatic multi-domain megasynthases, which are involved in the biosynthesis of pharmaceutically important natural products using an assembly-line mechanism. This program facilitates easy identification of various PKS domains and modules from a given polypeptide sequence. In addition, it also predicts the specificity of the potential acyltransferase domains for various starter and extender precursor units. SEARCHPKS is a user-friendly tool for correlating polyketide chemical structures with the organization of domains and modules in the corresponding modular polyketide synthases. This program also allows the user to extensively analyze and assess the sequence homology of various polyketide synthase domains, thus providing guidelines for carrying out domain and module swapping experiments. SEARCHPKS can also aid in identification of polyketide products made by PKS clusters found in newly sequenced genomes. The computational approach used in SEARCHPKS is based on a comprehensive analysis of various characterized clusters of modular polyketide synthases compiled in PKSDB, a database of modular polyketide synthases. SEARCHPKS can be accessed at http://www.nii.res.in/searchpks.html.

High-Throughput SNP Discovery and Genotyping for Constructing a Saturated Linkage Map of Chickpea (Cicer arietinum L.)

The present study reports the large-scale discovery of genome-wide single-nucleotide polymorphisms (SNPs) in chickpea, identified mainly through the next generation sequencing of two genotypes, i.e. Cicer arietinum ICC4958 and its wild progenitor C. reticulatum PI489777, parents of an inter-specific reference mapping population of chickpea. Development and validation of a high-throughput SNP genotyping assay based on Illuminas GoldenGate Genotyping Technology and its application in building a high-resolution genetic linkage map of chickpea is described for the first time. In this study, 1022 SNPs were identified, of which 768 high-confidence SNPs were selected for designing the custom Oligo Pool All (CpOPA-I) for genotyping. Of these, 697 SNPs could be successfully used for genotyping, demonstrating a high success rate of 90.75%. Genotyping data of the 697 SNPs were compiled along with those of 368 co-dominant markers mapped in an earlier study, and a saturated genetic linkage map of chickpea was constructed. One thousand and sixty-three markers were mapped onto eight linkage groups spanning 1808.7 cM (centiMorgans) with an average inter-marker distance of 1.70 cM, thereby representing one of the most advanced maps of chickpea. The map was used for the synteny analysis of chickpea, which revealed a higher degree of synteny with the phylogenetically close Medicago than with soybean. The first set of validated SNPs and map resources developed in this study will not only facilitate QTL mapping, genome-wide association analysis and comparative mapping in legumes but also help anchor scaffolds arising out of the whole-genome sequencing of chickpea.

A new family of type III polyketide synthases in Mycobacterium tuberculosis.

The Mycobacterium tuberculosis genome has revealed a remarkable array of polyketide synthases (PKSs); however, no polyketide product has been isolated thus far. Most of the PKS genes have been implicated in the biosynthesis of complex lipids. We report here the characterization of two novel type III PKSs from M. tuberculosis that are involved in the biosynthesis of long-chain α-pyrones. Measurement of steady-state kinetic parameters demonstrated that the catalytic efficiency of PKS18 protein was severalfold higher for long-chain acyl-coenzyme A substrates as compared with the small-chain precursors. The specificity of PKS18 and PKS11 proteins toward long-chain aliphatic acyl-coenzyme A (C12 to C20) substrates is unprecedented in the chalcone synthase (CHS) family of condensing enzymes. Based on comparative modeling studies, we propose that these proteins might have evolved by fusing the catalytic machinery of CHS and β-ketoacyl synthases, the two evolutionarily related members with conserved thiolase fold. The mechanistic and structural importance of several active site residues, as predicted by our structural model, was investigated by performing site-directed mutagenesis. The functional identification of diverse catalytic activity in mycobacterial type III PKSs provide a fascinating example of metabolite divergence in CHS-like proteins.

Towards Prediction of Metabolic Products of Polyketide Synthases: An In Silico Analysis

Sequence data arising from an increasing number of partial and complete genome projects is revealing the presence of the polyketide synthase (PKS) family of genes not only in microbes and fungi but also in plants and other eukaryotes. PKSs are huge multifunctional megasynthases that use a variety of biosynthetic paradigms to generate enormously diverse arrays of polyketide products that posses several pharmaceutically important properties. The remarkable conservation of these gene clusters across organisms offers abundant scope for obtaining novel insights into PKS biosynthetic code by computational analysis. We have carried out a comprehensive in silico analysis of modular and iterative gene clusters to test whether chemical structures of the secondary metabolites can be predicted from PKS protein sequences. Here, we report the success of our method and demonstrate the feasibility of deciphering the putative metabolic products of uncharacterized PKS clusters found in newly sequenced genomes. Profile Hidden Markov Model analysis has revealed distinct sequence features that can distinguish modular PKS proteins from their iterative counterparts. For iterative PKS proteins, structural models of iterative ketosynthase (KS) domains have revealed novel correlations between the size of the polyketide products and volume of the active site pocket. Furthermore, we have identified key residues in the substrate binding pocket that control the number of chain extensions in iterative PKSs. For modular PKS proteins, we describe for the first time an automated method based on crucial intermolecular contacts that can distinguish the correct biosynthetic order of substrate channeling from a large number of non-cognate combinatorial possibilities. Taken together, our in silico analysis provides valuable clues for formulating rules for predicting polyketide products of iterative as well as modular PKS clusters. These results have promising potential for discovery of novel natural products by genome mining and rational design of novel natural products.

An advanced draft genome assembly of a desi type chickpea (Cicer arietinum L.)

Chickpea (Cicer arietinum L.) is an important pulse legume crop. We previously reported a draft genome assembly of the desi chickpea cultivar ICC 4958. Here we report an advanced version of the ICC 4958 genome assembly (version 2.0) generated using additional sequence data and an improved genetic map. This resulted in 2.7-fold increase in the length of the pseudomolecules and substantial reduction of sequence gaps. The genome assembly covered more than 94% of the estimated gene space and predicted the presence of 30,257 protein-coding genes including 2230 and 133 genes encoding potential transcription factors (TF) and resistance gene homologs, respectively. Gene expression analysis identified several TF and chickpea-specific genes with tissue-specific expression and displayed functional diversification of the paralogous genes. Pairwise comparison of pseudomolecules in the desi (ICC 4958) and the earlier reported kabuli (CDC Frontier) chickpea assemblies showed an extensive local collinearity with incongruity in the placement of large sequence blocks along the linkage groups, apparently due to use of different genetic maps. Single nucleotide polymorphism (SNP)-based mining of intra-specific polymorphism identified more than four thousand SNPs differentiating a desi group and a kabuli group of chickpea genotypes.