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Int J Syst Evol Microbiol 55 (2005), 1171-1179; DOI  10.1099/ijs.0.63452-0
© 2005 International Union of Microbiological Societies

Application of a recN sequence similarity analysis to the identification of species within the bacterial genus Geobacillus

Daniel R. Zeigler

Bacillus Genetic Stock Center, Department of Biochemistry, The Ohio State University, Columbus, OH 43210, USA

Correspondence
Daniel R. Zeigler
zeigler.1{at}osu.edu

Full-length recN and 16S rRNA gene sequences were determined for a collection of 68 strains from the thermophilic Gram-positive genus Geobacillus, members of which have been isolated from geographically and ecologically diverse locations. Phylogenetic treeing methods clustered the isolates into nine sequence similarity groups, regardless of which gene was used for analysis. Several of these groups corresponded unambiguously to known Geobacillus species, whereas others contained two or more type strains from species with validly published names, highlighting a need for a re-assessment of the taxonomy for this genus. For taxonomic analysis of bacteria related at a genus, species or subspecies level, recN sequence comparisons had a resolving power nearly an order or magnitude greater than 16S rRNA gene comparisons. Mutational saturation rendered recN comparisons much less powerful than 16S rRNA gene comparisons for analysis of higher taxa, however. Analysis of recN sequences should prove a powerful tool for assigning strains to species within Geobacillus, and perhaps within other genera as well.


Published online ahead of print on 7 January 2005 as DOI 10.1099/ijs.0.63452-0.

The GenBank/EMBL/DDBJ accession number for the 16S rRNA gene sequences described in this study are AY297092 and AY608927–AY608993, inclusive; those for the recN sequences are AY434725 and AY608994–AY609060, inclusive.

A table giving details for the bacterial strains used in this study and a figure showing the locations of primers used for the recN sequencing project are available as supplementary material in IJSEM Online.




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