Microbial Identification System Identifies Cause of Bacterial Contamination
By LabMedica International staff writers
Posted on 03 Sep 2009
An identification system, which can identify 1,044 species of bacterium, solved a contamination problem in a renal dialysis center.Posted on 03 Sep 2009
Doctors and scientists first tried unsuccessfully to identify the bacterium causing contamination in a renal care center (San Jose, CA, USA) using a standard hospital microbial identification system. The microbial identification systems routinely used by hospitals can only identify about 300 bacterial species.
The investigating team from Stanford University (Palo Alto, CA, USA), then used Biolog's (Hayward, CA, USA) GEN III system and identified the contaminant in the renal care center as a Halomonas bacterium. The GEN III system is an easy system to use as it is built around a single test panel that can identify both Gram-negative and Gram-positive bacteria without a Gram stain. The finding was verified by 16s ribosomal DNA (rDNA) sequencing, a more complicated and costly molecular identification method.
Biolog has microbiology test kits capable of identifying environmental as well as known pathogenic bacteria species infecting humans, animals, and even plants. The bacterial contaminant Halomonas is typically found in high salt environments such as salt ponds. Normally, one would not expect to find this bacterium in a hospital clinic. In this case, the investigators believe that the bacterium was a contaminant of the sodium bicarbonate solutions that are routinely used to prepare dialysis fluid.
"Bacteria are enterprising, and they will get into and thrive in any environment that they can adapt to and grow in,” said Barry Bochner, Ph.D., CEO and CSO at Biolog "This is why it is important for microbiology labs to use identification methods with broader capabilities. It is not reasonable to assume that environmental bacteria will not find ways to cause contamination and infections.”
Biolog is a privately held company that develops new cell analysis tools for solving critical medical laboratory, pharmaceutical, and biotechnological problems.
The findings were published in July 2009 in the journal Medicine.
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Stanford University
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