Diversity of Culturable Actinobacteria Producing Protease Inhibitors Isolated from the Intertidal Zones of Maharashtra, India.

Phylogenetic diversity of culturable actinobacteria isolated from the intertidal regions of west coast of Maharashtra, India was studied using 16S rRNA gene sequencing. Total of 140 actinobacterial isolates were obtained, which belonged to 14 genera, 10 families and 65 putative species with Streptomyces being the most dominant (63%) genus followed by Nocardiopsis and Micromonospora. Isolates were screened for production of extracellular protease inhibitors (PI) against three pure proteases viz. chymotrypsin, trypsin, subtilisin and a crude extracellular protease from Pseudomonas aeruginosa. Eighty percent of the isolates showed PI activity against at least one of the four proteases, majority of these belonged to genus Streptomyces. Actinobacterial diversity from two sites Ade (17° 52' N, 73° 04' E) and Harnai (17° 48' N, 73° 05' E) with varying anthropological pressure showed that more putative species diversity was obtained from site with lower human intervention i.e. Ade (Shannon's H 3.45) than from Harnai (Shannon's H 2.83), a site with more human intervention. However, in Ade, percentage of isolates not showing PI activity against any of the proteases was close to 21% and that in Harnai was close to 9%. In other words, percentage of PI producers was lower at a site with lesser human intervention.

Phylogenetic diversity and activity screening of cultivable Actinobacteria isolated from marine sponges and associated environments from the western coast of India.

The phylogenetic diversity of cultivable actinobacteria isolated from sponges (Haliclona spp.) and associated intertidal zone environments along the northern parts of the western coast of India were studied using 16S rRNA gene sequences. A subset of randomly selected actinobacterial cultures were screened for three activities, namely predatory behaviour, antibacterial activity and enzyme inhibition. We recovered 237 isolates from the phylum Actinobacteria belonging to 19 families and 28 genera, which could be attributed to 95 putative species using maximum-likelihood partition and 100 putative species using Bayesian partition in Poisson tree processes. Although the trends in the discovery of actinobacterial genera isolated from sponges were consistent with previous studies from different study areas, we provide the first report of nine actinobacterial species from sponges. We observed widespread non-obligate epibiotic predatory behaviour in eight actinobacterial genera and we provide the first report of predatory activity in Brevibacterium , Glutamicibacter , Micromonospora , Nocardiopsis , Rhodococcus and Rothia . Sponge-associated actinobacteria showed significantly more predatory behaviour than environmental isolates. While antibacterial activity by actinobacterial isolates mainly affected Gram-positive target bacteria with little or no effect on Gram-negative bacteria, predation targeted both Gram-positive and Gram-negative prey with equal propensity. Actinobacterial isolates from both sponges and associated environments produced inhibitors of serine proteases and angiotensin-converting enzyme. Predatory behaviour was strongly associated with inhibition of trypsin and chymotrypsin. Our study suggests that the sponges and associated environments of the western coast of India are rich in actinobacterial diversity, with widespread predatory activity, antibacterial activity and production of enzyme inhibitors. Understanding the diversity and associations among various actinobacterial activities - with each other and the source of isolation - can provide new insights into marine microbial ecology and provide opportunities to isolate novel therapeutic agents.

Inferring causal pathways among three or more variables from steady-state correlations in a homeostatic system.

Cross-sectional correlations between two variables have limited implications for causality. We examine here whether it is possible to make causal inferences from steady-state data in a homeostatic system with three or more inter-correlated variables. Every putative pathway between three variables makes a set of differential predictions that can be tested with steady state data. For example, among 3 variables, A, B and C, the coefficient of determination, [Formula: see text] is predicted by the product of [Formula: see text] and [Formula: see text] for some pathways, but not for others. Residuals from a regression line are independent of residuals from another regression for some pathways, but positively or negatively correlated for certain other pathways. Different pathways therefore have different prediction signatures, which can be used to accept or reject plausible pathways using appropriate null hypotheses. The type 2 error reduces with sample size but the nature of this relationship is different for different predictions. We apply these principles to test the classical pathway leading to a hyperinsulinemic normoglycemic insulin-resistant, or pre-diabetic, state using four different sets of epidemiological data. Currently, a set of indices called HOMA-IR and HOMA-ß are used to represent insulin resistance and glucose-stimulated insulin response by ß cells respectively. Our analysis shows that if we assume the HOMA indices to be faithful indicators, the classical pathway must in turn be rejected. In effect, among the populations sampled, the classical pathway and faithfulness of the HOMA indices cannot be simultaneously true. The principles and example shows that it is possible to infer causal pathways from cross sectional correlational data on three or more correlated variables.