Sandeep K. Kushwaha

Protein interaction network analysis--approach for potential drug target identification in Mycobacterium tuberculosis.

In host-parasite diseases like tuberculosis, non-homologous proteins (enzymes) as drug target are first preference. Most potent drug target can be identified among large number of non-homologous protein through protein interaction network analysis. In this study, the entire promising dimension has been explored for identification of potential drug target. A comparative metabolic pathway analysis of the host Homo sapiens and the pathogen M. tuberculosis H37Rv has been performed with three level of analysis. In first level, the unique metabolic pathways of M. tuberculosis have been identified through its comparative study with H. sapiens and identification of non-homologous proteins has been done through BLAST similarity search. In second level, choke-point analysis has been performed with identified non-homologous proteins of metabolic pathways. In third level, two type of analysis have been performed through protein interaction network. First analysis has been done to find out the most potential metabolic functional associations among all identified choke point proteins whereas second analysis has been performed to find out the functional association of high metabolic interacting proteins to pathogenesis causing proteins. Most interactive metabolic proteins which have highest number of functional association with pathogenesis causing proteins have been considered as potential drug target. A list of 18 potential drug targets has been proposed which are various stages of progress at the TBSGC and proposed drug targets are also studied for other pathogenic strains. As a case study, we have built a homology model of identified drug targets histidinol-phosphate aminotransferase (HisC1) using MODELLER software and various information have been generated through molecular dynamics which will be useful in wetlab structure determination. The generated model could be further explored for insilico docking studies with suitable inhibitors.

Potato tuber expression of Arabidopsis WRINKLED1 increase triacylglycerol and membrane lipids while affecting central carbohydrate metabolism

Summary Tuber and root crops virtually exclusively accumulate storage products in the form of carbohydrates. An exception is yellow nutsedge (Cyperus esculentus) in which tubers have the capacity to store starch and triacylglycerols (TAG) in roughly equal amounts. This suggests that a tuber crop can efficiently handle accumulation of energy dense oil. From a nutritional as well as economic aspect, it would be of interest to utilize the high yield capacity of tuber or root crops for oil accumulation similar to yellow nutsedge. The transcription factor WRINKLED1 from Arabidopsis thaliana, which in seed embryos induce fatty acid synthesis, has been shown to be a major factor for oil accumulation. WRINKLED1 was expressed in potato (Solanum tuberosum) tubers to explore whether this factor could impact tuber metabolism. This study shows that a WRINKLED1 transcription factor could induce triacylglycerol accumulation in tubers of transformed potato plants grown in field (up to 12 nmol TAG/mg dry weight, 1% of dry weight) together with a large increase in polar membrane lipids. The changes in metabolism further affected starch accumulation and composition concomitant with massive increases in sugar content.

Food Waste to Energy: An Overview of Sustainable Approaches for Food Waste Management and Nutrient Recycling

Food wastage and its accumulation are becoming a critical problem around the globe due to continuous increase of the world population. The exponential growth in food waste is imposing serious threats to our society like environmental pollution, health risk, and scarcity of dumping land. There is an urgent need to take appropriate measures to reduce food waste burden by adopting standard management practices. Currently, various kinds of approaches are investigated in waste food processing and management for societal benefits and applications. Anaerobic digestion approach has appeared as one of the most ecofriendly and promising solutions for food wastes management, energy, and nutrient production, which can contribute to worlds ever-increasing energy requirements. Here, we have briefly described and explored the different aspects of anaerobic biodegrading approaches for food waste, effects of cosubstrates, effect of environmental factors, contribution of microbial population, and available computational resources for food waste management researches.

Captured metagenomics: large-scale targeting of genes based on 'sequence capture' reveals functional diversity in soils.

Microbial enzyme diversity is a key to understand many ecosystem processes. Whole metagenome sequencing (WMG) obtains information on functional genes, but it is costly and inefficient due to large amount of sequencing that is required. In this study, we have applied a captured metagenomics technique for functional genes in soil microorganisms, as an alternative to WMG. Large-scale targeting of functional genes, coding for enzymes related to organic matter degradation, was applied to two agricultural soil communities through captured metagenomics. Captured metagenomics uses custom-designed, hybridization-based oligonucleotide probes that enrich functional genes of interest in metagenomic libraries where only probe-bound DNA fragments are sequenced. The captured metagenomes were highly enriched with targeted genes while maintaining their target diversity and their taxonomic distribution correlated well with the traditional ribosomal sequencing. The captured metagenomes were highly enriched with genes related to organic matter degradation; at least five times more than similar, publicly available soil WMG projects. This target enrichment technique also preserves the functional representation of the soils, thereby facilitating comparative metagenomics projects. Here, we present the first study that applies the captured metagenomics approach in large scale, and this novel method allows deep investigations of central ecosystem processes by studying functional gene abundances.

MetCap: a bioinformatics probe design pipeline for large-scale targeted metagenomics

Massive sequencing of genes from different environments has evolved metagenomics as central to enhancing the understanding of the wide diversity of micro-organisms and their roles in driving ecological processes. Reduced cost and high throughput sequencing has made large-scale projects achievable to a wider group of researchers, though complete metagenome sequencing is still a daunting task in terms of sequencing as well as the downstream bioinformatics analyses. Alternative approaches such as targeted amplicon sequencing requires custom PCR primer generation, and is not scalable to thousands of genes or gene families. In this study, we are presenting a web-based tool called MetCap that circumvents the limitations of amplicon sequencing of multiple genes by designing probes that are suitable for large-scale targeted metagenomics sequencing studies. MetCap provides a novel approach to target thousands of genes and genomic regions that could be used in targeted metagenomics studies. Automatic analysis of user-defined sequences is performed, and probes specifically designed for metagenome studies are generated. To illustrate the advantage of a targeted metagenome approach, we have generated more than 300,000 probes that match more than 400,000 publicly available sequences related to carbon degradation, and used these probes for target sequencing in a soil metagenome study. The results show high enrichment of target genes and a successful capturing of the majority of gene families. MetCap is freely available to users from: http://soilecology.biol.lu.se/metcap/ . MetCap is facilitating probe-based target enrichment as an easy and efficient alternative tool compared to complex primer-based enrichment for large-scale investigations of metagenomes. Our results have shown efficient large-scale target enrichment through MetCap-designed probes for a soil metagenome. The web service is suitable for any targeted metagenomics project that aims to study several genes simultaneously. The novel bioinformatics approach taken by the web service will enable researchers in microbial ecology to tap into the vast diversity of microbial communities using targeted metagenomics as a cost-effective alternative to whole metagenome sequencing.

Multi-layer Perceptron Architecture for Tertiary Structure Prediction of Helical Content of Proteins from Peptide Sequences

The purpose of the present study is to deduce the novel method for tertiary structure prediction of various important unpredicted proteins i.e. metabolic, regulatory, signalling etc. due unavailability of template structure. Multi-layer perception architecture has been developed to predict the tertiary structure (Phi/Psi) of helical content of proteins. A novel codification scheme has been devised for data processing (I/O). The proposed system has been tested with different number of neural networks, training set sizes and training epochs. The overall successful prediction of residues for tertiary structure prediction (Phi/Psi) of helical content of protein has been reported according to window size as 15(51.4% / 57.8%), 17(57% / 64%), 19(52.2% / 54.2%), 21(52% / 57.4%). This study demonstrated the possibility of implementing fast and efficient structure prediction using neural network.

Draft Genome Sequence of the Mycoparasitic Oomycete Pythium periplocum Strain CBS 532.74

ABSTRACT The oomycete Pythium periplocum is an aggressive mycoparasite of a number of plant pathogenic fungi and oomycetes and therefore has potential as a biological control agent. Here, we report the first draft genome sequence of P. periplocum, which comprises 35.89 Mb. It contains 1,043 scaffolds and 14,399 predicted protein-coding genes.

NBSPred: a support vector machine-based high-throughput pipeline for plant resistance protein NBSLRR prediction.

UNLABELLED The nucleotide binding site leucine-rich repeats (NBSLRRs) belong to one of the largest known families of disease resistance genes that encode resistance proteins (R-protein) against the pathogens of plants. Various defence mechanisms have explained the regulation of plant immunity, but still, we have limited understanding about plant defence against different pathogens. Identification of R-proteins and proteins having R-protein-like features across the genome, transcriptome and proteome would be highly useful to develop the global understanding of plant defence mechanisms, but it is laborious and time-consuming task. Therefore, we have developed a support vector machine-based high-throughput pipeline called NBSPred to differentiate NBSLRR and NBSLRR-like protein from Non-NBSLRR proteins from genome, transcriptome and protein sequences. The pipeline was tested and validated with input sequences from three dicot and two monocot plants including Arabidopsis thaliana, Boechera stricta, Brachypodium distachyon Solanum lycopersicum and Zea mays. AVAILABILITY AND IMPLEMENTATION The NBSPred pipeline is available at http://soilecology.biol.lu.se/nbs/ SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online. CONTACT sandeep.kushwaha@biol.lu.se.

Draft genome of the oomycete pathogen Phytophthora cactorum strain LV007 isolated from European beech (Fagus sylvatica)

Phytophthora cactorum is a broad host range phytopathogenic oomycete. P. cactorum strain LV007 was isolated from a diseased European Beech (Fagus sylvatica) in Malmö, Sweden in 2016. The draft genome of P. cactorum strain LV007 is 67.81 Mb. It contains 15,567 contigs and 21,876 predicted protein-coding genes. As reported for other phytopathogenic Phytophthora species, cytoplasmic effector proteins including RxLR and CRN families were identified. The genome sequence has been deposited at DDBJ/ENA/GenBank under the accession NBIJ00000000. The version described in this paper is version NBIJ01000000.

Draft Genome Sequence of the Mycoparasitic Oomycete Pythium oligandrum Strain CBS 530.74

ABSTRACT The oomycete Pythium oligandrum is a mycoparasite and licenced biological control agent. Here, we report the draft genome sequence of P. oligandrum strain CBS 530.74, which is 36.80 Mb. It contains 341 scaffolds and 11,647 predicted protein-coding genes. As reported for plant-pathogenic Pythium species, RXLR-type effector sequences are absent.