Silver nanoparticles (AgNPs) are believed to be emerging tool against various infectious diseases including multi-drug resistant (MDR) bacteria. In the present study, in vitro synthesis of AgNPs was optimized using 1:50 ratio of macerozyme (25 μg/μl) and 1 mM AgNO3 incubated at 80 °C for 8 h. AgNPs were characterized by UV–Visible spectroscopy, dynamic light scattering (DLS), scanning electron microscopy, energy-dispersive X-ray spectroscopy, transmission electron microscopy (TEM) and X-ray diffraction (XRD). Characterization studies suggest the synthesis of elliptical, stable and crystalline AgNPs with an average size of 38.26 ± 0.4 nm calculated using TEM. The XRD pattern revealed the face-centered-cubic (fcc) form of metallic silver. Good shape integrity and dispersion of AgNPs after 1 year of incubation confirmed their stability. AgNPs were exibited the antimicrobial property against ten pathogenic bacteria, three molds and one yeast. The AgNPs also revealed remarkable antimicrobial activity against three MDR strains i.e. Extended spectrum beta-lactamase positive Escherichia coli, Staphylococcus aureus (MRSA) and Teicoplanin resistant Streptococcus Pneumoniae. The AgNPs coated surgical threads (suture) were revealed the remarkble antibacterial activity against three MDR strains. This is the first report to synthesize antimicrobial elliptical AgNPs using enzymes. The results suggest the possibilities to develop the nanoparticles coated antimicrobial medical fabric to combat against MDR infection.

A taxonomic description of bacteria was deduced from 5.78 Mb metagenomic sequence retrieved from Tulsi Shyam hot spring, India using bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP). Metagenome contained 10,893 16S rDNA sequences that were analyzed by MG-RAST server to generate the comprehensive profile of bacteria. Metagenomic data are available at EBI under EBI Metagenomics database with accession no. ERP009559. Metagenome sequences represented the 98.2% bacteria origin, 1.5% of eukaryotic and 0.3% were unidentified. A total of 16 bacterial phyla demonstrating 97 families and 287 species were revealed in the hot spring metagenome. Most abundant phyla were Firmicutes (65.38%), Proteobacteria (21.21%) and unclassified bacteria (10.69%). Whereas, Peptostreptococcaceae (37.33%), Clostridiaceae (23.36%), and Enterobacteriaceae (16.37%) were highest reported families in metagenome. Ubiquitous species were Clostridium bifermentans (17.47%), Clostridium lituseburense (13.93%) and uncultured bacterium (10.15%). Our data provide new information on hot spring bacteria and shed light on their abundance, diversity, distribution and coexisting organisms.

This is the first report on the metagenomic approach for unveiling the microbial diversity of Lasundra hot spring, Gujarat State, India. High-throughput sequencing of community DNA was performed on an Ion Torrent PGM platform. Metagenome consisted of 606,867 sequences represent 98,567,305 bps size with an average length of 162 bps and 46% G + C content. Metagenome sequence information is available at EBI under EBI Metagenomic database with accession no. ERP009313. MG-RAST assisted community analysis revealed that 99.21% sequences were bacterial origin, 0.43% was fit to eukaryotes and 0.11% belongs to archaea. A total of 29 bacterial, 20 eukaryotic and 4 archaeal phyla were detected. Abundant genera were Bacillus (86.7%), Geobacillus (2.4%), Paenibacillus (1.0%), Clostridium (0.7%) and Listeria (0.5%), that represent 91.52% in metagenome. In functional analysis, Cluster of Orthologous Group (COG) based annotation revealed that 45.4% was metabolism connected and 19.6% falls in poorly characterized group. Subsystem based annotation approach suggests that the 14.0% was carbohydrates, 7.0% was protein metabolism and 3.0% genes for various stress responses together with the versatile presence of commercially useful traits.

Here, we report metagenome from the Tuwa hot spring, India using shotgun sequencing approach. Metagenome consisted of 541,379 sequences with 98.7 Mbps size with 46% G + C content. Metagenomic sequence reads were deposited into the EMBL database under accession number ERP009321. Community analysis presented 99.1% sequences belong to bacteria, 0.3% of eukaryotic origin, 0.2% virus derived and 0.05% from archea. Unclassified and unidentified sequences were 0.4% and 0.07% respectively. A total of 22 bacterial phyla include 90 families and 201 species were observed in the hot spring metagenome. Firmicutes (97.0%), Proteobacteria (1.3%) and Actinobacteria (0.4%) were reported as dominant bacterial phyla. In functional analysis using Cluster of Orthologous Group (COG), 21.5% drops in the poorly characterized group. Using subsystem based annotation, 4.0% genes were assigned for stress responses and 3% genes were fit into the metabolism of aromatic compounds. The hot spring metagenome is very rich with novel sequences affiliated to unclassified and unidentified lineages, suggesting the potential source for novel microbial species and their products.

The development of next-generation sequencing (NGS) platforms spawned an enormous volume of data. This explosion in data has unearthed new scalability challenges for existing bioinformatics tools. The analysis of metagenomic sequences using bioinformatics pipelines is complicated by the substantial complexity of these data. In this article, we review several commonly-used online tools for metagenomics data analysis with respect to their quality and detail of analysis using simulated metagenomics data. There are at least a dozen such software tools presently available in the public domain. Among them, MGRAST, IMG/M, and METAVIR are the most well-known tools according to the number of citations by peer-reviewed scientific media up to mid-2015. Here, we describe 12 online tools with respect to their web link, annotation pipelines, clustering methods, online user support, and availability of data storage. We have also done the rating for each tool to screen more potential and preferential tools and evaluated five best tools using synthetic metagenome. The article comprehensively deals with the contemporary problems and the prospects of metagenomics from a bioinformatics viewpoint.