Sayak Ganguli

SECONDARY STRUCTURAL ANALYSIS OF MICRORNA AND THEIR PRECURSORS IN PLANTS

It has been a general belief over a long period of time that RNA molecules were essential molecules involved only in the process of protein synthesis as carriers of genetic. However recent studies have shown that most of the cells RNAome do not encode proteins. The role and diversity of these numerous non-coding RNAs has not been elucidated till date. The most unique of this plethora of non coding molecules are a class of small RNA molecules of ~ 21 nucleotides in length which has been reported by many workers to be involved in many of the cell process such as controls, defense and development. Short interfering RNAs (siRNA) and Micro RNA (miRNA) represent the two most abundant class of the non coding RNA cascade and both of them are key players in the process of RNA Interference. The current work focuses on the identification and development of secondary structures of available plant microRNA sequences and establishment of a relation between the formation of secondary structures and their free energy values.

Antagomirbase: A putative antagomir database

The accurate prediction of a comprehensive set of messenger putative antagomirs against microRNAs (miRNAs) remains an open problem. In particular, a set of putative antagomirs against human miRNA is predicted in this current version of database. We have developed Antagomir database, based on putative antagomirs-miRNA heterodimers. In this work, the human miRNA dataset was used as template to design putative antagomirs, using GC content and secondary structures as parameters. The algorithm used predicted the free energy of unbound antagomirs. Although in its infancy the development of antagomirs, that can target cell specific genes or families of genes, may pave the way forward for the generation of a new class of therapeutics, to treat complex inflammatory diseases. Future versions need to incorporate further sequences from other mammalian homologues for designing of antagomirs for aid in research. Availability The database is available for free at http://bioinfopresidencycollegekolkata.edu.in/antagomirs.html

Targeting pseudoknots in H5N1 hemagglutinin using designed aptamers

Influenza A virus subtype H5N1 is highly contagious among birds, causing high mortality among domestic poultry. The viral genome is contained on eight single RNA strands of which HA encode the antigenic glycoprotein called hemagglutinin. Hemagglutinin found on the surface of the influenza viruses and is responsible for binding the virus to the cell that is being infected. Among the most prevalent RNA structures the pseudoknot motif represents an important piece of RNA architecture, as it provides a means for a single RNA strand to fold upon itself to produce a globular structure capable of performing important biological functions. In this analysis we have identified the pseudoknot motifs in the hemagglutinin gene of HPAI A (H5N1) Asian strains. Specific aptamers have been designed against these pseudoknots. These in-silico aptamers can be used to hinder the ability of pseudoknots to facilitate ribosomal frameshifting. This may ultimately lead to reduce the coding efficiency of the HA that encodes hemagglutinin and might be used as molecular medicine for H5N1.

Molecular modeling of DICER and identification of phosphorylation sites

RNA interference (RNAi) is a post-transcriptional process initiated by double-stranded RNA molecules that degrade a complementary target RNA. In the first step, long double-stranded RNA molecules are chopped into shorter duplexes by an endonuclease dubbed DICER. This work focused on the identification of phosphorylation sites in DICER and proceeded towards comparative modeling. The domain of unknown function in DICER showed homology with the chromatin remodeling protein domains. This suggests that DICER may also perform chromatin remodeling. The Ramachandran analysis revealed that the models had 96% residues in the permissible regions and could be used for future ligand binding studies.

Screening and Identification of putative long non coding RNAs from transcriptome data of a high yielding blackgram (Vigna mungo), Cv. T9

Blackgram (Vigna mungo) is one of primary legumes cultivated throughout India, Cv.T9 being one of its common high yielding cultivar. This article reports RNA sequencing data and a pipeline for prediction of novel long non-coding RNAs from the sequenced data. The raw data generated during sequencing are available at Sequence Read Archive (SRA) of NCBI with accession number- SRX1558530

Metagenome analysis of the root endophytic microbial community of Indian rice (O. sativa L.)

This study reports the root endophytic microbial community profile in rice (Oryza sativa L.), the largest food crop of Asia, using 16S rRNA gene amplicon sequencing. Metagenome of OS01 and OS04 consisted of 11,17,900 sequences with 300 Mbp size and average 55.6% G + C content. Data of this study are available at NCBI Bioproject (PRJNA360379). The taxonomic analysis of 843 OTUs showed that the sequences belonged to four major phyla revealing dominance of Proteobacteria, Firmicutes, Cyanobacteria and Actinobacteria. Results reveal the dominance of Bacillus as major endophytic genera in rice roots, probably playing a key role in Nitrogen fixation.

Analyses of MYMIV-induced transcriptome in Vigna mungo as revealed by next generation sequencing.

Mungbean Yellow Mosaic Virus (MYMIV) is the viral pathogen that causes yellow mosaic disease to a number of legumes including Vigna mungo. VM84 is a recombinant inbred line resistant to MYMIV, developed in our laboratory through introgression of resistance trait from V. mungo line VM-1. Here we present the quality control passed transcriptome data of mock inoculated (control) and MYMIV-infected VM84, those have already been submitted in Sequence Read Archive (SRX1032950, SRX1082731) of NCBI. QC reports of FASTQ files generated by ‘SeqQC V2.2’ bioinformatics tool.

The Silent Assassins: Informatics of Plant Viral Silencing Suppressors

The arms race continues – silencing suppressors have emerged as the silent weapon of counter defense against the indigenous plant RNA silencing machinery. Several reports have identified their presence and in higher plants, these proteins are involved in the inhibition of RNA silencing, which reduces the defense of plants against the pathogen, as well as play important roles for regulation of gene expression during growth and development. These viral silencing suppressors interfere with the various steps of the RNA silencing pathways either by binding to double-stranded RNA or by interfering with the effector proteins and altering their conformation. The informatics challenge lies in the elucidation and unraveling of the diverse structures of these proteins and in understanding and conceptualizing the structure paradigm of these proteins. The basic methods of informatics such as molecular modeling and dynamic simulations would be effective tools for the design and implementation of the above mandates, but advanced techniques such as SVM classification, network analyses, and a systems level approach including phylogenetic analyses should provide a robust framework for such elucidations. This chapter provides a brief overview of the viral silencing suppressors that have been identified so far and provides insights on how they have been studied in the wet lab. Apart from this it focuses on the possibilities of the bioinformatics analyses of the viral silencing suppressors with specific case studies and conceptualizes a future framework for application-oriented use of these silent assassins.

Intelligent Access to Sequence and Structure Databases (IASSD) − an interface for accessing information from major web databases

With the advent of age of big data and advances in high throughput technology accessing data has become one of the most important step in the entire knowledge discovery process. Most users are not able to decipher the query result that is obtained when non specific keywords or a combination of keywords are used. Intelligent access to sequence and structure databases (IASSD) is a desktop application for windows operating system. It is written in Java and utilizes the web service description language (wsdl) files and Jar files of E-utilities of various databases such as National Centre for Biotechnology Information (NCBI) and Protein Data Bank (PDB). Apart from that IASSD allows the user to view protein structure using a JMOL application which supports conditional editing. Availability The Jar file is freely available through e-mail from the corresponding author.

INHIBITING H5N1 HAEMAGGLUTININ WITH SMALL MOLECULE LIGANDS

Mutations in the avian influenza virus can create new pathogenic strains, which can cause future pandemics. Targeting the surface haemagglutinin can inhibit viral fusion and consequent entry. The effects of 27 single and double point mutations on the properties of the H5 haemagglutinin were studied. These mutations were then introduced individually in the PDB file of the H5, to generate mutants. 13 herbal and non-herbal lead inhibitors of H5 were screened and docked with the wild type and mutant haemagglutinins to obtain a comparative docking profile. The nature of the interactions of the inhibitors were analysed, and the binding residues determined. The latter further revealed that certain mutations in HA might be affecting inhibitor binding. Keywords: H5N1 inhibitors, effect of H5 mutations,