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Diversity of Streptomyces spp. in Eastern Himalayan region – computational RNomics approach to phylogeny

Isolation and characterization of actinomycetes from soil samples from altitudinal gradient of North-East India were investigated for computational RNomics based phylogeny. A total of 52 diverse isolates of Streptomyces from the soil samples were isolated on four different media and from these 6 iso...

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Detalles Bibliográficos
Autores principales: Bhattacharjee, Kaushik, Banerjee, Subhro, Joshi, Santa Ram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398779/
https://www.ncbi.nlm.nih.gov/pubmed/22829729
http://dx.doi.org/10.6026/97320630008548
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author Bhattacharjee, Kaushik
Banerjee, Subhro
Joshi, Santa Ram
author_facet Bhattacharjee, Kaushik
Banerjee, Subhro
Joshi, Santa Ram
author_sort Bhattacharjee, Kaushik
collection PubMed
description Isolation and characterization of actinomycetes from soil samples from altitudinal gradient of North-East India were investigated for computational RNomics based phylogeny. A total of 52 diverse isolates of Streptomyces from the soil samples were isolated on four different media and from these 6 isolates were selected on the basis of cultural characteristics, microscopic and biochemical studies. Sequencing of 16S rDNA of the selected isolates identified them to belong to six different species of Streptomyces. The molecular morphometric and physico-kinetic analysis of 16S rRNA sequences were performed to predict the diversity of the genus. The computational RNomics study revealed the significance of the structural RNA based phylogenetic analysis in a relatively diverse group of Streptomyces.
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spelling pubmed-33987792012-07-24 Diversity of Streptomyces spp. in Eastern Himalayan region – computational RNomics approach to phylogeny Bhattacharjee, Kaushik Banerjee, Subhro Joshi, Santa Ram Bioinformation Hypothesis Isolation and characterization of actinomycetes from soil samples from altitudinal gradient of North-East India were investigated for computational RNomics based phylogeny. A total of 52 diverse isolates of Streptomyces from the soil samples were isolated on four different media and from these 6 isolates were selected on the basis of cultural characteristics, microscopic and biochemical studies. Sequencing of 16S rDNA of the selected isolates identified them to belong to six different species of Streptomyces. The molecular morphometric and physico-kinetic analysis of 16S rRNA sequences were performed to predict the diversity of the genus. The computational RNomics study revealed the significance of the structural RNA based phylogenetic analysis in a relatively diverse group of Streptomyces. Biomedical Informatics 2012-06-28 /pmc/articles/PMC3398779/ /pubmed/22829729 http://dx.doi.org/10.6026/97320630008548 Text en © 2012 Biomedical Informatics This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.
spellingShingle Hypothesis
Bhattacharjee, Kaushik
Banerjee, Subhro
Joshi, Santa Ram
Diversity of Streptomyces spp. in Eastern Himalayan region – computational RNomics approach to phylogeny
title Diversity of Streptomyces spp. in Eastern Himalayan region – computational RNomics approach to phylogeny
title_full Diversity of Streptomyces spp. in Eastern Himalayan region – computational RNomics approach to phylogeny
title_fullStr Diversity of Streptomyces spp. in Eastern Himalayan region – computational RNomics approach to phylogeny
title_full_unstemmed Diversity of Streptomyces spp. in Eastern Himalayan region – computational RNomics approach to phylogeny
title_short Diversity of Streptomyces spp. in Eastern Himalayan region – computational RNomics approach to phylogeny
title_sort diversity of streptomyces spp. in eastern himalayan region – computational rnomics approach to phylogeny
topic Hypothesis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398779/
https://www.ncbi.nlm.nih.gov/pubmed/22829729
http://dx.doi.org/10.6026/97320630008548
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