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Arabian Sea harbours one of the largest oxygen minimal zones (OMZs) among the global oceans wherein biogeochemical cycles are regulated through dominant and complex microbial processes. The present study investigated the bacterial communities at various depths of the Arabian Sea OMZ using high-throughput sequencing of the v3-v4 hyper variable region of 16S rRNA gene. A total of 10 samples which included water samples from 8 different depths and 2 sediment samples were analyzed in this study. About 2.7 million sequences were obtained from all the samples. The sequence analysis revealed high bacterial diversity at deep waters and sediment samples and comparatively less species richness at the core OMZ depths. Number of OTUs ranged from 114 to 14441.Taxonomic assignments of the obtained OTUs showed dominant presence of Proteobacteria, Bacteriodetes, and Chloroflexi across all the samples. The identified OTUs were further affiliated to the phyla Marinimicrobia, Colwellia, Nitrospina, Tepidicaulis, Shewanella, Pseudoalteromonas, Woeseia at various depths along the water column. Correlation with abiotic factors suggested distinct variation in bacterial community composition with change in depth and dissolved oxygen (DO) levels. Predictive functional annotation based on bacterial phylotypes suggested presence of active nitrogen, sulphur, carbon, and methane metabolic cycles along the vertical transect of the studied region. Presence of nitrogen reduction bacterial group below the core OMZ depths may potentially provide insight into the expansion of OMZ region in Arabian Sea. Functional profiling further revealed presence of genes related to xenobiotic degradation in the water and sediment samples indicating a potential hotspot for bio-prospection.

Bay of Bengal (BoB) has immense significance with respect to ecological diversity and natural resources. Studies on microbial profiling and their functional significance at sediment level of BoB remain poorly represented. Herein, we describe the microbial diversity and metabolic potentials of BOB deep-sea sediment samples by subjecting the metagenomes to Nanopore sequencing. Taxonomic diversity ascertained at various levels revealed that bacteria belonging to phylum Proteobacteria predominantly represented in sediment samples NIOT_S7 and NIOT_S9. A comparative study with 16S datasets from similar ecological sites revealed depth as a crucial factor in determining taxonomic diversity. KEGG annotation indicated that bacterial communities possess sequence reads corresponding to carbon dioxide fixation, sulfur, nitrogen metabolism, but at varying levels. Additionally, gene sequences related to bioremediation of dyes, plastics, hydrocarbon, antibiotic resistance, secondary metabolite synthesis and metal resistance from both the samples as studied indicate BoB to represent a highly diverse environmental niche for further exploration.

Efficient methodology for simultaneous extraction of multiple bioactive compounds from microalgae still remains a major challenge. The present study provides a method for the sequential production of three major products: Chlorella Growth Factor (CGF, a nucleotide-peptide complex enriched with vitamins, minerals, and carbohydrates), lipid, and carotenoids from Chlorella vulgaris biomass in an economically feasible manner. After protein-rich CGF was extracted, the spent biomass was found to contain 12% lipid and 3% carotenoids when extracted individually, compared to that of the un-utilized (fresh) biomass (lipid, 14%; carotenoids, 4%). When extracted simultaneously using conventional methods, the yield of lipid from “CGF and carotenoids-extracted biomass,” and carotenoids from “CGF and lipid-extracted biomass” were significantly reduced (50%). However, simultaneous extraction using different solvent mixtures such as hexane:methanol:water and pentane:methanol:water mixture-augmented lipid yield by 38.5% and carotenoids by 14%, and additionally retained chlorophyll and its derivatives. Column chromatographic approach yielded sequential production of lipid (18%), lutein (9%) with better yields as well as without chlorophyll interference. Different geometric isomers of lutein all-E-(trans)-(3R,3′R,6′R)-β,e-carotene-3,3′diol, 9Z(cis)-(3R,3′R,6′R)-β,e-carotene-3,3′diol, and 13Z(cis)-(3R,3′R,6′R)-β,e-carotene-3,3′diol were purified by HPLC and elucidated by CD, UV, NMR, FT-IR, and Mass spectra. In conclusion, the study provides an efficient and economically viable methodology for sequential production of lipid and lutein along with its geometrical isomers without chlorophyll influence and yield loss from the protein-rich CGF-extracted spent biomass of marine microalga, Chlorella vulgaris.

Environmental pollution has emerged to be a major hazard in today's world. Pollutants from varied sources cause harmful effects to the ecosystem. The major pollutants across marine and terrestrial regions are hydrocarbons, plastics, and dyes. Conventional methods for remediation have their own limitations and shortcomings to deal with these environmental pollutants. Bio-based remediation techniques using microbes have gained momentum in the recent past, primarily ascribed to their eco-friendly approach. The role of microbial enzymes in remediating the pollutants are well reported, and further exploration of microbial resources could lead to discovery of novel pollutant degrading enzymes (PDEs). Recent advances in next-generation sequencing technologies and metagenomics have provided the impetus to explore environmental microbes for potentially novel bioremediation enzymes. In this study, a tool, RemeDB, was developed for identifying bioremediation enzymes sequences from metagenomes. RemeDB aims at identifying hydrocarbon, dye, and plastic degrading enzymes from various metagenomic libraries. A sequence database consisting of >30,000 sequences proven to degrade the major pollutants was curated from various literature sources and this constituted the PDEs' database. Programs such as HMMER and RAPSearch were incorporated to scan across large metagenomic sequences libraries to identify PDEs. The tool was tested with metagenome data sets from varied sources and the outputs were validated. RemeDB was efficient to classify and identify the signature patterns of PDEs in the input data sets.

Biocalcification or microbially induced carbonate precipitation (MICP) is gaining attention from the research fraternity, primarily ascribed to their eco-friendly applications. Bacterial strains have been isolated from various sources and their ability to precipitate carbonate has been studied extensively. In spite of the fact that the deep-sea environment is a potential source for bioprospecting, meager reports exist on the isolation of biocalcifying bacterial strains from deep-sea. In this study, a deep-sea sediment sample obtained from off-Barren Island coast in the Andaman Sea was investigated for biocalcifying strains. Based on the urease activity and the ability to produce calcite crystals, the strain NIOTVJ5 was chosen for further investigations. The strain showed a similarity to Bacillus thuringiensis through 16S rRNA sequencing and was shown to possess positive urease, protease, amylase, catalase, and oxidase activities. The isolate was found to be piezotolerant as it was able to survive at 100 bar pressure with significant changes in the spore morphology. The strain was able to produce strong monoxenic biofilms as well. Maximum urease activity was 554.03 U/mL and it precipitated 1.80 g/L of carbonate crystals. Scanning electron microscopy coupled with energy dispersive X-ray spectroscopy confirmed the presence of calcium carbonate. The carbonate polymorph was identified as calcite using X-ray powder diffraction. The impact of biocalcification by NIOTVJ5 on concrete specimens indicated an increase of 30.91% in their compressive strength. This is the first report of a biocalcifying strain from a deep-sea sediment around the Indian subcontinent region. This study indicates the potential of the strain NIOTVJ5, which can be employed for various biotechnological applications.

The present study was aimed at randomly mutating the microalga, Chlorella vulgaris, in order to alter its cellular behaviour towards increased lipid production for efficient biodiesel production from algal biomass. Individual mutants from ultraviolet light (UV-1 (30 s exposure), UV-2 (60 s exposure) and UV-3 (90 s exposure)) and 5'fluorodeoxyuridine (5'FDU-1 (0.25 mM) and 5'FDU-2 (0.50 mM)) exposed cells were identified to explore an alternative method for lipid enhancement. A marginally significant decrease in biomass in the UV mutants; marked increase in the lipid content in UV-2 and 5'FDU-1 mutants; significant increase in saturated fatty acids level, especially in UV-2 mutant; insignificant increase in lipid production when these mutants were subjected to an additional stress of nitrogen starvation and predominantly enhanced level of unsaturated fatty acids in all the strains except UV-2 were noted. Chloroplast ultrastructural alterations and defective biosynthesis of chloroplast specific lipid constituents were observed in the mutants. Modelling of three-dimensional structures of acetyl coA carboxylase (ACCase), omega-6, plastid delta-12 and microsomal delta-12 fatty acid desaturases for the first time and ligand-interaction studies greatly substantiated our findings. A replacement of leucine by a serine residue in the acetyl coA carboxylase gene of UV-2 mutant suggests the reason behind lipid enhancement in UV-2 mutant. Higher activity of ACCase in UV-2 and 5'FDU-1 strongly proves the functional consequences of gene mutation to lipid production. In conclusion, algal mutants exhibited significant impact on biodiesel production through structural alterations in the lipid-metabolizing genes, thereby enhancing lipid production and saturated fatty acid levels.

The present study was undertaken to evaluate the microbial composition of farmed cobia pompano and milkfish, reared in sea-cages by culture-independent methods. This study would serve as a basis for assessing the general health of fish, identifying the dominant bacterial species present in the gut for future probiotic work and in early detection of potential pathogens. High-throughput sequencing of V3-V4 hyper variable regions of 16S rDNA on Illumina MiSeq platform facilitated unravelling of composite bacterial population. Analysis of 1.3 million quality-filtered sequences revealed high microbial diversity. Characteristic marine fish gut microbes: Vibrio and Photobacterium spp. showed prevalence in cobia and pompano whereas Pelomonas and Fusobacterium spp. dominated the gut of milkfish. Pompano hindgut with 10,537 operational taxonomy units (OTUs) exhibited the highest alpha-diversity index followed by cobia (10,435) and milkfish (2799). Additionally unique and shared OTUs in each gut type were identified. Gammaproteobacteria dominated in cobia and pompano while Betaproteobacteria showed prevalence in milkfish. We obtained 96 shared OTUs among the three species though the numbers of reads were highly variable. These differences in microbiota of farmed fish reared in same environment were presumably due to differences in the gut morphology, physiological behavior and host specificity.

Computational tools have extended their reach into different realms of scientific research. Often coupled with molecular dynamics simulation, docking provides comprehensive insight into molecular mechanisms of biological processes. Influence of molecular docking is highly experienced in the field of structure based drug discovery, wherein docking is vital in validating novel lead compounds. The significance of molecular docking is also understood in several environmental and industrial research, in order to untangle the interactions among macromolecules of non-medical interest. Various processes such as bioremediation (REMEDIDOCK), nanomaterial interactions (NANODOCK), nutraceutical interactions (NUTRADOCK), fatty acid biosynthesis (FADOCK), and antifoulers interactions (FOULDOCK) find the application of molecular docking. This chapter emphasizes the involvement of computational techniques in the aforementioned fields to expand our knowledge on macromolecular interacting mechanisms.