Biotechnology

Background / Purpose: Enzymes can be classified by the kind of chemical reactions they catalyze (e.g. The International Union of Biochemistry and Molecular Biology (IUBMB) enzyme classification). We present a novel method called “EC-BLAST” to search and compare enzymes based on chemical reactions.This robust and efficient tool is based on an in-house algorithm. It computes atom-atom mapping between the reactant(s) and product(s) of a reaction and marks bond changes. A user can search similar enzymes based on the reactions’ substrate specificity, reaction centers and bond changes, or even a combination of these queries. The results are ranked based on a scoring function, highlighting the degree of conserved/variable regions between reactions. This information complements knowledge obtained from protein sequence/structure based studies. The knowledge of annotated reaction centers from the processed reactions can be used to predict the enzymes that can potentially transform or act on a...

Extracting chemical features like Atom-Atom Mapping (AAM), Bond Changes (BCs) and Reaction Centres from biochemical reactions helps us understand the chemical composition of enzymatic reactions. Reaction Decoder is a robust command line tool, which performs this task with high accuracy. It supports standard chemical input/output exchange formats i.e. RXN/SMILES, computes AAM, highlights BCs and creates images of the mapped reaction. This aids in the analysis of metabolic pathways and the ability to perform comparative studies of chemical reactions based on these features. This software is implemented in Java, supported on Windows, Linux and Mac OSX, and freely available at https://github.com/asad/ReactionDecoder CONTACT: : asad@ebi.ac.uk or s9asad@gmail.com.

The indigenous microbial community utilizing aliphatic, aromatic, and polar components from the oily sludge as sole source of carbon and energy was selected from the soil samples of Ankleshwar, India for biosurfactant production. Evaluation of biosurfactant production was done using screening assays such as surface tension reduction, hemolytic activity, emulsification activity, drop-collapse assay, and cell surface hydrophobicity studies. Maximum biosurfactant (6.9 g/l) production was achieved after 5 days of growth from Bacillus subtilis DSVP23 which was identified by 16S RNA technique (NCBI GenBank accession no. EU679368). Composition of biosurfactant showed it to be lipopeptide in nature with 15.2% protein content and 18.0% lipid content. Functional group analysis was also done by using Fourier transform infrared spectroscopy which showed it to be a protein-bound lipid thereby imparting them special properties. Analysis by matrix-assisted laser desorption/ionization time-of-flight mass spectrometric and nuclear magnetic resonance revealed that the major constituents of lipopeptide are leucine and isoleucine. Gas chromatographic analysis data indicated that oily sludge components of chain length C₁₂-C₃₀ and aromatic hydrocarbons were degraded effectively by B. subtilis DSVP23 after 5 days of incubation. These results collectively points toward the importance of B. subtilis DSVP23 as a potential candidate for bioremediation studies.

Three bacterial strains, Bacillus sp. SV9, Acinetobacter sp. SV4 and Pseudomonas sp., SV17 from contaminated soil in Ankleshwar, India were tested for their ability to degrade the complex mixture of petroleum hydrocarbons (such as alkanes, aromatics, resins and ...

Candida species, notably Candida albicans, is the major fungal pathogen in humans. It is a dimorphic fungus capable of causing superficial mucosal infections, as well as systemic infections, in immunocompromised individuals. The factors responsible for its pathogenesis are still not fully understood and increasing resistance to commonly used antifungal agents necessitates the search for new formulations. The inhibitory effect of 30 different plant oils on Candida albicans isolated from clinical samples was evaluated. The antifungal agent fluconazole was used as a positive control. Plant oils were tested at concentrations from 0.03% to 3% (v/v) to determine the minimum inhibitory concentration and minimum fungicidal concentration (MFC) using agar dilution and macro broth dilution assays. Of the 30 plant oils tested, 18 were found to be effective and 12 were ineffective. Based on their MFCs, effective oils were placed into three categories: most effective, moderately effective and least effective. Eucalyptus and peppermint oils were most effective, with MFC values of 0.12% and 0.15% (v/v), respectively. The significant antifungal activity of these oils suggests that they could serve as a source of compounds with therapeutic potential against Candida-related infections.

The current treatment options for Candida albicans biofilm-device related infections are very scarce due to their intrinsic increased tolerance to antimycotics. The aim of this work was to study synergistic action of terpenes (eugenol, menthol and thymol) with fluconazole (FLA) on C. albicans biofilm inhibition. The minimum inhibitory concentration (MIC) assayed using CLSI M27-A3 broth micro-dilution method showed antifungal activity against C. albicans MTCC 227 at a concentration of 0.12 % (v/v) for both thymol and eugenol as compared to 0.25 % (v/v) for menthol. FLA was taken as positive control. The effect of these terpenes on metabolic activity of preformed C. albicans biofilm cells was evaluated using 2,3-bis (2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide (XTT) reduction assay in 96-well polystyrene microtiter plate. Thymol and eugenol were more effective at lower concentrations of > or = 1.0 % (v/v) than menthol. Synergistic studies using checkerboard micr...