Biomedical subjects

D V Raje

Publications and source records attributed to D V Raje.

4 recordsLinked to original sources

PubMed2003

Identification of signature and primers specific to genus Pseudomonas using mismatched patterns of 16S rDNA sequences.

BACKGROUND: Pseudomonas, a soil bacterium, has been observed as a dominant genus that survives in different habitats with wide hostile conditions. We had a basic assumption that the species level variation in 16S rDNA sequences of a bacterial genus is mainly due to substitutions rather than insertion or deletion of bases. Keeping this in view, the aim was to identify a region of 16S rDNA sequence and within that focus on substitution prone stretches indicating species level variation and to derive patterns from these stretches that are specific to the genus. RESULTS: Repeating elements that are highly conserved across different species of Pseudomonas were considered as guiding markers to locate a region within the 16S gene. Four repeating patterns showing more than 80% consistency across fifty different species of Pseudomonas were identified. The sub-sequences between the repeating patterns yielded a continuous region of 495 bases. The sub-sequences after alignment and using Shanon's entropy measure yielded a consensus pattern. A stretch of 24 base positions in this region, showing maximum variations across the sampled sequences was focused for possible genus specific patterns. Nine patterns in this stretch showed nearly 70% specificity to the target genus. These patterns were further used to obtain a signature that is highly specific to Pseudomonas. The signature region was used to design PCR primers, which yielded a PCR product of 150 bp whose specificity was validated through a sample experiment. CONCLUSIONS: The developed approach was successfully applied to genus Pseudomonas. It could be tried in other bacterial genera to obtain respective signature patterns and thereby PCR primers, for their rapid tracking in the environmental samples.

Base Pair Mismatch↗

PubMed2002

Distinguishing features of 16S rDNA gene for five dominating bacterial genus observed in bioremediation.

Defining a microbial community and identifying bacteria, at least at the genus level, is a first step in predicting the behavior of a microbial community in bioremediation. In biological treatment systems, the most dominating groups observed are Pseudomonas, Moraxella, Acinetobactor, Burkholderia, and Alcaligenes. Our interest lies in identifying the distinguishing features of these bacterial groups based on their 16S rDNA sequence data, which could be used further for generating genus-specific probes. Accordingly, 20 sequences representing different species from each genus above were retrieved, which constituted a training set. A 16-dimensional feature vector comprised of transition probabilities of nucleotides was considered and each sampled sequence was expressed in terms of these features. A stepwise feature selection method was used to identify features that are distinct across the species of these five groups. Wilk's lambda selection criterion was used and resulted in a subset with six distinguishing features. The discriminating efficacy of this subset was tested through multiple group discriminant analysis. Two linear composites, as a function of these features, could discriminate the test set of forty-five sequences from these groups with 95% accuracy, thereby ascertaining the relevance of the identified features. The geometric representation of feature correlation in the reduced discriminant space demonstrated the dominance of identified features in specific groups. These features independently or in combination could be used to generate genus-specific patterns to design probes, so as to develop a tracking tool for the selected group of bacteria.

Bacteria↗

PubMed2001

Quantitative structure-activity relationships based on functional and structural characteristics of organic compounds.

In the present quantitative structure-activity relationship (QSAR) modeling, organic compounds, including priority pollutants, have been considered and classified based on their functional and structural characteristics. Five physico-chemical characteristics have been used to develop a QSAR model for Pimephales promelas, by means of multiple regression analysis. Collinearity diagnostics was carried out using two different approaches based on condition index and K correlation index. The outlier analysis was carried out using the variable subsets obtained through both the approaches. An attempt has been made to justify the deletion of outliers in each group referring to their physico-chemical characteristics. The expressions obtained by using both approaches provide almost the same prediction accuracy, however, the latter approach resulted in expressions with reduced number of molecular descriptors. The QSARs obtained through this exercise would certainly assist in designing environment-friendly molecules with lower toxicity.

Animals↗

PubMed2001

An approach to assess level of satisfaction of the residents in relation to SWM system.

The issue of managing solid waste (SW), especially in the major cities, is of growing concern to the municipal organisations in India. The present performance of the system is recognised to be unsatisfactory. This paper delineates an approach to quantify the satisfaction level of the residents as a measure of performance of the system and also presents a case study in a major city. The results show the validity of the approach.

Cities↗