Analysis of the unexplored features of rrs (16S rDNA) of the Genus Clostridium

<p>Abstract</p> <p>Background</p> <p>Bacterial taxonomy and phylogeny based on <it>rrs </it>(16S rDNA) sequencing is being vigorously pursued. In fact, it has been stated that novel biological findings are driven by comparison and integration of massive data sets. In spite of a large reservoir of <it>rrs </it>sequencing data of 1,237,963 entries, this analysis invariably needs supplementation with other genes. The need is to divide the genetic variability within a taxa or genus at their <it>rrs </it>phylogenetic boundaries and to discover those fundamental features, which will enable the bacteria to naturally fall within them. Within the large bacterial community, <it>Clostridium </it>represents a large genus of around 110 species of significant biotechnological and medical importance. Certain <it>Clostridium </it>strains produce some of the deadliest toxins, which cause heavy economic losses. We have targeted this genus because of its high genetic diversity, which does not allow accurate typing with the available molecular methods.</p> <p>Results</p> <p>Seven hundred sixty five <it>rrs </it>sequences (> 1200 nucleotides, nts) belonging to 110 <it>Clostridium </it>species were analyzed. On the basis of 404 <it>rrs </it>sequences belonging to 15 <it>Clostridium </it>species, we have developed species specific: (i) phylogenetic framework, (ii) signatures (30 nts) and (iii) <it>in silico </it>restriction enzyme (14 Type II REs) digestion patterns. These tools allowed: (i) species level identification of 95 <it>Clostridium </it>sp. which are presently classified up to genus level, (ii) identification of 84 novel <it>Clostridium </it>spp. and (iii) potential reduction in the number of <it>Clostridium </it>species represented by small populations.</p> <p>Conclusions</p> <p>This integrated approach is quite sensitive and can be easily extended as a molecular tool for diagnostic and taxonomic identification of any microbe of importance to food industries and health services. Since rapid and correct identification allows quicker diagnosis and consequently treatment as well, it is likely to lead to reduction in economic losses and mortality rates.</p