We investigated the usefulness of a novel DNA fingerprinting technique, AFLP, which is based on the selective amplification of genomic restriction fragments by PCR, to differentiate bacterial strains at the subgeneric level. In total, 147 bacterial strains were subjected to AFLP fingerprinting: 36 strains, including 23 pathovars of and six pathovars of one strain of 90 genotypically characterized strains comprising all 14 hybridization groups currently described in the genus and four strains of each of the genera and Depending on the genus, total genomic DNA of each bacterium was digested with a particular combination of two restriction endonucleases and the resulting fragments were ligated to restriction halfsite-specific adaptors. These adaptors served as primer-binding sites allowing the fragments to be amplified by selective PCR primers that extend beyond the adaptor and restriction site sequences. Following electrophoretic separation on 5% (w/v) polyacrylamide/8.3 M urea, amplified products could be visualized by autoradiography because one of the selective primers was radioactively labelled. The resulting banding patterns, containing approximately 30-50 visualized PCR products in the size range 80-550 bp, were captured by a high-resolution densitoscanner and further processed for computer-assisted analysis to determine band-based similarity coefficients. This study reveals extensive evidence for the applicability of AFLP in bacterial taxonomy through comparison of the newly obtained data with results previously obtained by well-established genotypic and chemotaxonomic methods such as DNA-DNA hybridization and cellular fatty acid analysis. In addition, this study clearly demonstrates the superior discriminative power of AFLP towards the differentiation of highly related bacterial strains that belong to the same species or even biovar (i.e. to characterize strains at the infrasubspecific level), highlighting the potential of this novel fingerprinting method in epidemiological and evolutionary studies.


Article metrics loading...

Loading full text...

Full text loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error