Molecular modeling and analysis of human and plant endo-β-N-acetyl- glucosaminidases for mutations effects on function

Endo- β-N-acetylgucosaminidases (ENGases) are the enzymes that catalyze both hydrolysis and transglycosylation reactions. It is of interest to study ENGases because of their ability to synthesize glycopeptides. Homology models of Human, Arabidopsis thaliana and Sorghum ENGases were developed and their active sites marked based on information available from Arthrobacter protophormiae (PDB ID: 3FHQ) ENGase. Further, these models were docked with the natural substrate GlcNAc-Asn and the inhibitor Man₃GlcNAc-thiazoline. The catalytic triad of Asn, Glu and Tyr (N171, E173 and Y205 of bacteria) were found to be conserved across the phyla. The crucial Y299F mutation showing 3 times higher transglycosylation activity than in wild type Endo-A is known. The hydrolytic activity remained unchanged in bacteria, while the transglycosylation activity increased. This Y to F change is found to be naturally evolved and should be attributing higher transglycosylation rates in human and Arabidopsis thaliana ENGases. Ligand interactions Ligplots revealed the interaction of amino acids with hydrophobic side chains and polar uncharged side chain amino acids. Thus, structure based molecular model-ligand interactions provide insights into the catalytic mechanism of ENGases and assist in the rational engineering of ENGases.     

Comparative effects of a highly specific protein kinase C inhibitor, calphostin C and calmodulin inhibitors on angiotensin-stimulated aldosterone secretion

We have examined the relative roles of the calcium-calmodulin system and protein kinase C in angiotensin-mediated aldosterone secretion. We used a highly specific protein kinase C inhibitor, calphostin C and two well-accepted calmodulin inhibitors, W-7 and calmidazolium. Although both types of inhibitors affected angiotensin-induced aldosterone secretion, as judged by the inhibitory doses of these compounds, angiotensin-evoked aldosterone secretion was more sensitive to calmodulin inhibition than protein kinase C inhibition. Manipulation of intracellular calcium by dantrolene and thapsigargin also modified aldosterone secretion significantly.     

Two-stage microbial community experimental design

Microbial community samples can be efficiently surveyed in high throughput by sequencing markers such as the 16S ribosomal RNA gene. Often, a collection of samples is then selected for subsequent metagenomic, metabolomic or other follow-up. Two-stage study design has long been used in ecology but has not yet been studied in-depth for high-throughput microbial community investigations. To avoid ad hoc sample selection, we developed and validated several purposive sample selection methods for two-stage studies (that is, biological criteria) targeting differing types of microbial communities. These methods select follow-up samples from large community surveys, with criteria including samples typical of the initially surveyed population, targeting specific microbial clades or rare species, maximizing diversity, representing extreme or deviant communities, or identifying communities distinct or discriminating among environment or host phenotypes. The accuracies of each sampling technique and their influences on the characteristics of the resulting selected microbial community were evaluated using both simulated and experimental data. Specifically, all criteria were able to identify samples whose properties were accurately retained in 318 paired 16S amplicon and whole-community metagenomic (follow-up) samples from the Human Microbiome Project. Some selection criteria resulted in follow-up samples that were strongly non-representative of the original survey population; diversity maximization particularly undersampled community configurations. Only selection of intentionally representative samples minimized differences in the selected sample set from the original microbial survey. An implementation is provided as the microPITA (Microbiomes: Picking Interesting Taxa for Analysis) software for two-stage study design of microbial communities.