Assistant Professor Sophie Arbefeville

Lab Medicine & Pathology
Medical School
Twin Cities
Project Title: 
Bacterial and Fungal Identification by RNA Genes Sequencing

One of the essential roles of the Clinical Microbiology Laboratory is to provide rapid and accurate identification of bacteria and fungi isolated from patient specimens. The conventional methods used in the clinical laboratory to identify organisms rely on phenotypic characteristics such as microscopic morphology and Gram reaction, growth requirements and rate, colony morphology, and biochemical characteristics. However, some organisms are slow-growing, fastidious, or express biochemical characteristics that do not adequately fit into the pattern of a known genus or species. To identify such an isolate, a laboratory may need to resort to long incubation times, rarely used media, or methods that are not routinely available in most laboratories. Advances in the development of genetic methods provide the clinical microbiology laboratory with additional tools for bacterial identification that supplement conventional phenotypic testing. Of these new methods of identification, the most widely used are the rRNA genes sequencing for the identification of bacteria and fungi.

The 16S rRNA gene (about 1,500 base pairs long) is universal in all bacteria, highly conserved within living organisms of the same genus and species, but with enough variation between species of the same genus to be used to identify bacteria to the genus and species level. It has been demonstrated that the sequence information obtained from the initial 500 base pair of the 5’ region of the 16S rRNA gene often contains sufficient sequence variations to differentiate bacteria at the genus level and usually at the species level.

These researchers are in the process of evaluating the accuracy of multiple public databases to correctly give the identification of bacteria and fungi using the RNA genes.

Project Investigators

Assistant Professor Sophie Arbefeville
Christine Henzler
Todd Knutson
 
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