Novel N-substituted 4-hydrazino piperidine derivative as a dipeptidyl peptidase IV inhibitor

A novel class of N-substituted 4-hydrazino piperidine derivatives were designed, synthesized and evaluated for DPP IV inhibition. The SAR studies on the N-substituted piperidine led to the discovery of compound 22e as a potent DPP IV inhibitor (IC₅₀ 88 nM), which is highly selective over other peptidases. In vivo efficacy indicates that compound 22e stimulates insulin release in response to glucose load and improves glucose tolerance in n5-STZ and Zucker Diabetic Fatty (ZDF) rats.     

Influence of Diet Composition on Cattle Rumen Methanogenesis: A Comparative Metagenomic Analysis in Indian and Exotic Cattle

Comparative metagenomics approach has been used in this study to discriminate colonization of methanogenic population in different breeds of cattle. We compared two Indian cattle breeds (Gir and Kankrej) and two exotic cattle (Holstein and Jersey) breeds. Using a defined dietary plan for selected Indian varieties, the diet dependent shifts in microbial community and abundance of the enzymes associated with methanogenesis were studied. This data has been compared with the available rumen metagenome data from Holstein and Jersey dairy cattle. The abundance of genes for methanogenesis in Holstein and Jersey cattle came from Methanobacteriales order whereas, majority of the enzymes for methanogenesis in Gir and Kankrej cattle came from Methanomicrobiales order. The study suggested that by using slow/less digestible feed, the propionate levels could be controlled in rumen; and in turn, this would also help in further reducing the hydrogenotrophic production of methane. The study proposes that with the designed diet plan the overall methanogenic microbial pool or the individual methanogens could be targeted for development of methane mitigation strategies.     

Preferential interactions of trehalose,L-arginine.HCl and sodium chloride with therapeutically relevant IgG1 monoclonal antibodies

Preferential interactions of weakly interacting formulation excipients govern their effect on the equilibrium and kinetics of several reactions of protein molecules in solution. Using vapor pressure osmometry, we characterized the preferential interactions of commonly used excipients trehalose, L-arginine.HCl and NaCl with three therapeutically-relevant, IgG1 monoclonal antibodies that have similar size and shape, but differ in their surface hydrophobicity and net charge. We further characterized the effect of these excipients on the reversible self-association, aggregation and viscosity behavior of these antibody molecules. We report that trehalose, L-arginine.HCl and NaCl are all excluded from the surface of the three IgG1 monoclonal antibodies, and that the exclusion behavior is linearly related to the excipient molality in the case of trehalose and NaCl, whereas a non-linear behavior is observed for L-arginine.HCl. Interestingly, we find that the magnitude of trehalose exclusion depends upon the nature of the protein surface. Such behavior is not observed in case of NaCl and L-arginine.HCl as they are excluded to the same extent from the surface of all three antibody molecules tested in this study. Analysis of data presented in this study provides further insight into the mechanisms governing excipient-mediated stabilization of mAb formulations.     

Conjugated linoleic acid producing potential of lactobacilli isolated from the rumen of cattle

Lactobacilli isolated from the rumen of cattle were subjected to morphological and biochemical characterizations followed by PCR-based identification. Among isolates, Lactobacillus brevis was found to be the most prevalent species in the rumen. For in vitro conjugated linoleic acid (CLA) production, the two isolates of L. brevis and one each of Lactobacillus viridescens and Lactobacillus lactis were selected. The sunflower oil (i.e., 0.25, 0.5 and 1.0%; a rich source of linoleic acid) was added to skim milk as a substrate for CLA production by isolates at 37 °C/12 h. L. brevis 02 was found to be the most potential CLA producer (10.53 mg CLA/g fat) at 0.25% concentration of sunflower oil followed by L. brevis 01 (8.27 mg CLA/g fat). However, at higher level of sunflower oil (i.e., 1.0%), L. lactis was the highest CLA producer (9.22 mg/g fat) when compared to L. brevis and L. viridescens. The results indicated that L. brevis and/or CLA production was inhibited with increasing concentration of sunflower oil in skim milk. In contrast, L. lactis and L. viridescens could tolerate the increasing concentrations of sunflower oil and produced higher CLA. Overall, L. brevis extends a possibility to be used as a direct-fed microbial for ruminants to increase the CLA content in milk, however, in vivo trials are needed for validation of results obtained.     

4-D single particle tracking of synthetic and proteinaceous microspheres reveals preferential movement of nuclear particles along chromatin – poor tracks

Background  

The dynamics of nuclear organization, nuclear bodies and RNPs in particular has been the focus of many studies. To understand their function, knowledge of their spatial nuclear position and temporal translocation is essential. Typically, such studies generate a wealth of data that require novel methods in image analysis and computational tools to quantitatively track particle movement on the background of moving cells and shape changing nuclei.     

A Metabolomic Approach to Understanding the Metabolic Link between Obesity and Diabetes

Obesity and diabetes arise from an intricate interplay between both genetic and environmental factors. It is well recognized that obesity plays an important role in the development of insulin resistance and diabetes. Yet, the exact mechanism of the connection between obesity and diabetes is still not completely understood. Metabolomics is an analytical approach that aims to detect and quantify small metabolites. Recently, there has been an increased interest in the application of metabolomics to the identification of disease biomarkers, with a number of well-known biomarkers identified. Metabolomics is a potent approach to unravel the intricate relationships between metabolism, obesity and progression to diabetes and, at the same time, has potential as a clinical tool for risk evaluation and monitoring of disease. Moreover, metabolomics applications have revealed alterations in the levels of metabolites related to obesity-associated diabetes. This review focuses on the part that metabolomics has played in elucidating the roles of metabolites in the regulation of systemic metabolism relevant to obesity and diabetes. It also explains the possible metabolic relation and association between the two diseases. The metabolites with altered profiles in individual disorders and those that are specifically and similarly altered in both disorders are classified, categorized and summarized.     

Enhancing Degradation of Low Density Polyethylene Films by Curvularia lunata SG1 Using Particle Swarm Optimization Strategy

Abstract

In the present study, artificial neural network (ANN) modelling coupled with particle swarm optimization (PSO) algorithm was used to optimize the process variables for enhanced low density polyethylene (LDPE) degradation by Curvularia lunata SG1. In the non-linear ANN model, temperature, pH, contact time and agitation were used as input variables and polyethylene bio-degradation as the output variable. Further, on application of PSO to the ANN model, the optimum values of the process parameters were as follows: pH = 7.6, temperature = 37.97 °C, agitation rate = 190.48 rpm and incubation time = 261.95 days. A comparison between the model results and experimental data gave a high correlation coefficient (RANN2=0.999). Significant enhancement of LDPE bio-degradation using C.lunata SG1by about 48 % was achieved under optimum conditions. Thus, the novelty of the work lies in the application of combination of ANN–PSO as optimization strategy to enhance the bio-degradation of LDPE.

Graphical Abstract

Electronic supplementary materialThe online version of this article (doi:10.1007/s12088-015-0522-z) contains supplementary material, which is available to authorized users.     

Femtochemistry in enzyme catalysis: DNA photolyase

Photolyase uses light energy to split UV-induced cyclobutane pyrimidine dimers in damaged DNA. This photoenzyme encompasses a series of elementary dynamical processes during repair function from early photoinitiation by a photoantenna molecule to enhance repair efficiency, to in vitro photoreduction through aromatic residues to reconvert the cofactor to the active form, and to final photorepair to fix damaged DNA. The corresponding series of dynamics include resonance energy transfer, intraprotein electron transfer, and intermolecular electron transfer, bond breaking-making rearrangements and back electron return, respectively. We review here our recent direct studies of these dynamical processes in real time, which showed that all these elementary reactions in the enzyme occur within subnanosecond timescale. Active-site solvation was observed to play a critical role in the continuous modulation of catalytic reactions. As a model system for enzyme catalysis, we isolated the enzyme–substrate complex in the transition-state region and mapped out the entire evolution of unmasked catalytic reactions of DNA repair. These observed synergistic motions in the active site reveal a perfect correlation of structural integrity and dynamical locality to ensure maximum repair efficiency on the ultrafast time scale.