DBCOVP: A database of coronavirus virulent glycoproteins.

Since the emergence of SARS-CoV-1 (2002), novel coronaviruses have emerged periodically like the MERS- CoV (2012) and now, the SARS-CoV-2 outbreak which has posed a global threat to public health. Although, this is the third zoonotic coronavirus breakout within the last two decades, there are only a few platforms that provide information about coronavirus genomes. None of them is specific for the virulence glycoproteins and complete sequence-structural features of these virulence factors across the betacoronavirus family including SARS-CoV-2 strains are lacking. Against this backdrop, we present DBCOVP (http://covp.immt.res.in/), the first manually-curated, web-based resource to provide extensive information on the complete repertoire of structural virulent glycoproteins from coronavirus genomes belonging to betacoronavirus genera. The database provides various sequence-structural properties in which users can browse and analyze information in different ways. Furthermore, many conserved T-cell and B-cell epitopes predicted for each protein are present that may perform a significant role in eliciting the humoral and cellular immune response. The tertiary structure of the epitopes together with the docked epitope-HLA binding-complex is made available to facilitate further analysis. DBCOVP presents an easy-to-use interface with in-built tools for similarity search, cross-genome comparison, phylogenetic, and multiple sequence alignment. DBCOVP will certainly be an important resource for experimental biologists engaged in coronavirus research studies and will aid in vaccine development.

dEMBF v2.0: An Updated Database of Enzymes for Microalgal Biofuel Feedstock.

In light of increasing algal genomics data and knowledge of biosynthetic pathways responsible for biofuel production, an integrated resource for easy access to all information is essential to improve our understanding of algal lipid metabolism. Against this backdrop, dEMBF v2.0, a significantly updated and improved version of our database of microalgae lipid biosynthetic enzymes for biofuel production, has been developed. dEMBF v2.0 now contains a comprehensive annotation of 2018 sequences encoding 35 enzymes, an increase of over 7-fold as compared with the first version. Other improved features include an increase in species coverage to 32 algal genomes, analysis of additional metabolic pathways, expanded annotation thoroughly detailing sequence and structural features, including enzyme-ligand interactions, and integration of supporting experimental evidence to demonstrate the role of enzymes in increasing lipid content. Along with a complete redesign of the interface, the updated database provides several inbuilt tools and user-friendly functionalities for more interactive and dynamic visualization of data.

dEMBF: A Comprehensive Database of Enzymes of Microalgal Biofuel Feedstock.

Microalgae have attracted wide attention as one of the most versatile renewable feedstocks for production of biofuel. To develop genetically engineered high lipid yielding algal strains, a thorough understanding of the lipid biosynthetic pathway and the underpinning enzymes is essential. In this work, we have systematically mined the genomes of fifteen diverse algal species belonging to Chlorophyta, Heterokontophyta, Rhodophyta, and Haptophyta, to identify and annotate the putative enzymes of lipid metabolic pathway. Consequently, we have also developed a database, dEMBF (Database of Enzymes of Microalgal Biofuel Feedstock), which catalogues the complete list of identified enzymes along with their computed annotation details including length, hydrophobicity, amino acid composition, subcellular location, gene ontology, KEGG pathway, orthologous group, Pfam domain, intron-exon organization, transmembrane topology, and secondary/tertiary structural data. Furthermore, to facilitate functional and evolutionary study of these enzymes, a collection of built-in applications for BLAST search, motif identification, sequence and phylogenetic analysis have been seamlessly integrated into the database. dEMBF is the first database that brings together all enzymes responsible for lipid synthesis from available algal genomes, and provides an integrative platform for enzyme inquiry and analysis. This database will be extremely useful for algal biofuel research. It can be accessed at http://bbprof.immt.res.in/embf.

Genome-wide identification and evolutionary analysis of algal LPAT genes involved in TAG biosynthesis using bioinformatic approaches.

Lysophosphatidyl acyltransferase (LPAT) is one of the major triacylglycerol synthesis enzymes, controlling the metabolic flow of lysophosphatidic acid to phosphatidic acid. Experimental studies in Arabidopsis have shown that LPAT activity is exhibited primarily by three distinct isoforms, namely the plastid-located LPAT1, the endoplasmic reticulum-located LPAT2, and the soluble isoform of LPAT (solLPAT). In this study, 24 putative genes representing all LPAT isoforms were identified from the analysis of 11 complete genomes including green algae, red algae, diatoms and higher plants. We observed LPAT1 and solLPAT genes to be ubiquitously present in nearly all genomes examined, whereas LPAT2 genes to have evolved more recently in the plant lineage. Phylogenetic analysis indicated that LPAT1, LPAT2 and solLPAT have convergently evolved through separate evolutionary paths and belong to three different gene families, which was further evidenced by their wide divergence at gene structure and sequence level. The genome distribution supports the hypothesis that each gene encoding a LPAT is not duplicated. Mapping of exon-intron structure of LPAT genes to the domain structure of proteins across different algal and plant species indicates that exon shuffling plays no role in the evolution of LPAT genes. Besides the previously defined motifs, several conserved consensus sequences were discovered which could be useful to distinguish different LPAT isoforms. Taken together, this study will enable the generation of experimental approximations to better understand the functional role of algal LPAT in lipid accumulation.

Agrigenomics for microalgal biofuel production: an overview of various bioinformatics resources and recent studies to link OMICS to bioenergy and bioeconomy.

Microalgal biofuels offer great promise in contributing to the growing global demand for alternative sources of renewable energy. However, to make algae-based fuels cost competitive with petroleum, lipid production capabilities of microalgae need to improve substantially. Recent progress in algal genomics, in conjunction with other "omic" approaches, has accelerated the ability to identify metabolic pathways and genes that are potential targets in the development of genetically engineered microalgal strains with optimum lipid content. In this review, we summarize the current bioeconomic status of global biofuel feedstocks with particular reference to the role of "omics" in optimizing sustainable biofuel production. We also provide an overview of the various databases and bioinformatics resources available to gain a more complete understanding of lipid metabolism across algal species, along with the recent contributions of "omic" approaches in the metabolic pathway studies for microalgal biofuel production.

Phylogenomic study of lipid genes involved in microalgal biofuel production-candidate gene mining and metabolic pathway analyses.

Optimizing microalgal biofuel production using metabolic engineering tools requires an in-depth understanding of the structure-function relationship of genes involved in lipid biosynthetic pathway. In the present study, genome-wide identification and characterization of 398 putative genes involved in lipid biosynthesis in Arabidopsis thaliana Chlamydomonas reinhardtii, Volvox carteri, Ostreococcus lucimarinus, Ostreococcus tauri and Cyanidioschyzon merolae was undertaken on the basis of their conserved motif/domain organization and phylogenetic profile. The results indicated that the core lipid metabolic pathways in all the species are carried out by a comparable number of orthologous proteins. Although the fundamental gene organizations were observed to be invariantly conserved between microalgae and Arabidopsis genome, with increased order of genome complexity there seems to be an association with more number of genes involved in triacylglycerol (TAG) biosynthesis and catabolism. Further, phylogenomic analysis of the genes provided insights into the molecular evolution of lipid biosynthetic pathway in microalgae and confirm the close evolutionary proximity between the Streptophyte and Chlorophyte lineages. Together, these studies will improve our understanding of the global lipid metabolic pathway and contribute to the engineering of regulatory networks of algal strains for higher accumulation of oil.