A gzip-based algorithm to identify bacterial families by 16S rRNA.
OBJECTIVE
Microbial family identification of 16S rDNA sequences by applying a strategy based on algorithms for data compression.


RESULTS
Perl scripts were developed to analyse similarities in microbial sequences, based on a gzip data compression technique. For each bacterial family (n=196) a 16S rRNA reference file was constructed to compare new queries looking at compression performance. An online user-friendly bioinformatics tool was built up to attribute a bacterial family to a 16S rRNA sequence. It was successfully applied to recognize different bacterial families, including Legionellaceae, Bacillaceae, Enterobacteriaceae, Acetobacteriaceae and Rhizobiaceae. The percentage of positive identifications is higher than 95% for fragments over 450 bp.


CONCLUSIONS
A new bioinformatics approach has been developed to assign a taxonomic classification to a 16SrDNA sequence. An online tool provides quick and easy sequence attribution. The general principle can be applied to other genes of taxonomic interest.


CONCLUSIONS
Availability of simple bioinformatics tools can support the development of molecular-based analysis and classification of bacteria, especially for environmental or uncultured strains.
Santoni
D
D
Hygiene and Public Health Unit, Department of Health Sciences, IUSM, Rome, Italy.
Romano-Spica
V
V
D000465:Algorithms; D001419:Bacteria / Q000145:classification* / Q000235:genetics; D019295:Computational Biology; D004275:DNA, Ribosomal / Q000737:chemistry*; D012336:RNA, Ribosomal, 16S / Q000235:genetics*; D017422:Sequence Analysis, DNA
D004275:DNA, Ribosomal; D012336:RNA, Ribosomal, 16S