An isobutyronitrile-induced bienzymatic system of Alcaligenes sp. MTCC 10674 and its application in the synthesis of α-hydroxyisobutyric acid

Alcaligenes sp. MTCC 10674 was isolated as acetone cyanohydrin hydrolyzing bacterium from soil of orchid gardens of Himachal Pradesh. Acetone cyanohydrin hydrolyzing activity of this organism comprised nitrile hydratase and amidase activities. It exhibited higher substrate specificity towards aliphatic hydroxynitrile (acetone cyanohydrin) in comparison to arylaliphatic hydroxynitrile. Isobutyronitrile (40 mM) acted as a carbon source as well as inducer for growth of Alcaligenes sp. MTCC 10674 and expression of acetone cyanohydrin hydrolyzing activity. Optimization of culture condition using response surface methodology increased acetone cyanohydrin hydrolyzing activity by 1.3-fold, while inducer mediation approach increased the activity by 1.2-fold. The half life of this enzyme was 25 h at 15 °C. V _max and K _m value for acetone cyanohydrin hydrolyzing enzyme was 0.71 μmol mg^?1 min^?1 and 14.3 mM, when acetone cyanohydrin was used as substrate. Acetone cyanohydrin hydrolyzing enzyme encountered product inhibition and IC50 and K _i value were calculated to be 28 and 10.2 mM, respectively, when product α-hydroxyisobutyric acid was added in the reaction. Under optimized reaction conditions at 40 ml fed batch scale, 3 mg dcw ml ^? resting cells of Alcaligenes sp. MTCC 10674 fully converted 0.33 M acetone cyanohydrin into α-hydroxyisobutyric acid (1.02 g) in 6 h 40 min. The characterization of acetone cyanohydrins hydrolyzing activity revealed that it comprises bienzymatic nitrile hydrolyzing system, i.e. nitrile hydratase and amidase for the production of α-hydroxyisobutyric acid from acetone cyanohydrin and maximum 70 % yield is being reported for the first time.     

The Prebiotic Provenance of Semi-Aqueous Solvents

Origins of Life and Evolution of Biospheres - The numerous and varied roles of phosphorylated organic molecules in biochemistry suggest they may have been important to the origin of life. The...     

Computationally guided identification of Akt-3, a serine/threonine kinase inhibitors: Insights from homology modelling,structure-based screening,molecular dynamics and quantum mechanical calculations

Abstract

Chemical entities targeting kinase signalling pathways serve as a potential strategy to combat malignancies. Protein Kinase B or Akt is a validated target for various malignancies and Akt3 remains the least explored isoform among all its isoforms. Initially, homology modelling technique was used for generating protein structure and further validation was performed using molecular dynamics simulation and Ramachandran plot. The validated protein structure was then subjected for active site analysis which led to identification of active site residues based on metrics provided by site score. The important residues in binding site were identified as Thr81, Asp271 and Asp289 for binding energetics and inhibition. Subsequently, virtual screening methodologies were used for identification of novel hits for inhibition of Protein Kinase B or Akt3. This led to the identification of two hits, i.e. thiophene derivative and thieno-pyridine derivative which were selected on the basis of their binding affinity and drug likeliness. These identified hits were subjected for molecular dynamics simulations, quantum mechanical and synthetic accessibility studies. The role of crucial residues in binding site stood validated as suggested by molecular dynamics simulations studies.

Communicated by Ramaswamy H. Sarma     

One size does not fit all: On how Markov model order dictates performance of genomic sequence analyses

The structural simplicity and ability to capture serial correlations make Markov models a popular modeling choice in several genomic analyses, such as identification of motifs, genes and regulatory elements. A critical, yet relatively unexplored, issue is the determination of the order of the Markov model. Most biological applications use a predetermined order for all data sets indiscriminately. Here, we show the vast variation in the performance of such applications with the order. To identify the ‘optimal’ order, we investigated two model selection criteria: Akaike information criterion and Bayesian information criterion (BIC). The BIC optimal order delivers the best performance for mammalian phylogeny reconstruction and motif discovery. Importantly, this order is different from orders typically used by many tools, suggesting that a simple additional step determining this order can significantly improve results. Further, we describe a novel classification approach based on BIC optimal Markov models to predict functionality of tissue-specific promoters. Our classifier discriminates between promoters active across 12 different tissues with remarkable accuracy, yielding 3 times the precision expected by chance. Application to the metagenomics problem of identifying the taxum from a short DNA fragment yields accuracies at least as high as the more complex mainstream methodologies, while retaining conceptual and computational simplicity.     

ParA encoded on chromosome II of Deinococcus radiodurans binds to nucleoid and inhibits cell division in Escherichia coli

Bacterial genome segregation and cell division has been studied mostly in bacteria harbouring single circular chromosome and low-copy plasmids. Deinococcus radiodurans, a radiation-resistant bacterium, harbours multipartite genome system. Chromosome I encodes majority of the functions required for normal growth while other replicons encode mostly the proteins involved in secondary functions. Here, we report the characterization of putative P-loop ATPase (ParA2) encoded on chromosome II of D. radiodurans. Recombinant ParA2 was found to be a DNA-binding ATPase. E. coli cells expressing ParA2 showed cell division inhibition and mislocalization of FtsZ-YFP and those expressing ParA2-CFP showed multiple CFP foci formation on the nucleoid. Although, in trans expression of ParA2 failed to complement SlmA loss per se, it could induce unequal cell division in slmAminCDE double mutant. These results suggested that ParA2 is a nucleoid-binding protein, which could inhibits cell division in E. coli by affecting the correct localization of FtsZ and thereby cytokinesis. Helping slmAminCDE mutant to produce minicells, a phenotype associated with mutations in the ‘Min’ proteins, further indicated the possibility of ParA2 regulating cell division by bringing nucleoid compaction at the vicinity of septum growth.     

β-defensin-3 negatively regulates TLR4–HMGB1 axis mediated HLA-G expression in IL-1β treated glioma cells

The non-classical HLA class I antigen HLA-G contributes to immune escape mechanisms in glioblastoma multiforme (GBM). We have previously shown that IL-1β–HIF-1α axis connects inflammatory and oncogenic pathways in GBM. In this study, we investigated the role of IL-1β induced inflammation in regulating HLA-G expression. IL-1β increased HLA-G and Toll like receptor 4 (TLR4) expression in a HIF-1α dependent manner. Inhibition of TLR4 signaling abrogated IL-1β induced HLA-G. IL-1β increased HMGB1 expression and its interaction with TLR4. Inhibition of HMGB1 inhibited TLR4 and vice versa suggesting the existence of HMGB1–TLR4 axis in glioma cells. Interestingly, HMGB1 inhibition prevented IL-1β induced HLA-G expression. Elevated levels of HMGB1 and β-defensin 3 were observed in GBM tumors. Importantly, β-defensin-3 prevented IL-1β induced HLA-G, TLR4, HMGB1 expression and release of pro-inflammatory mediators. Our studies indicate that β-defensin-3 abrogates IL-1β induced HLA-G expression by negatively affecting key molecules associated with its regulation.