Author
STENDER, HENRIK - BOSTON PROBES, INC. | |
Kurtzman, Cletus | |
HYLDIG-NIELSEN, JENS - BOSTON PROBES, INC. | |
SORENSEN, DITTE - BOSTON PROBES, INC. | |
BROOMER, ADAM - BOSTON PROBES, INC. | |
OLIVEIRA, KENNETH - BOSTON PROBES, INC. | |
PERRY-0'KEEFE, HEATHER - BOSTON PROBES, INC. | |
SAGE, ANDREW - MILLIPORE CORPORATION | |
YOUNG, BARBARA - MILLIPORE CORPORATION | |
COULL, JAMES - BOSTON PROBES, INC. |
Submitted to: Applied and Environmental Microbiology
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 11/7/2000 Publication Date: N/A Citation: N/A Interpretive Summary: Wine spoilage in the U.S. causes annual losses in the millions of dollars. One of the primary spoilage organisms is a yeast in the genus Brettanomyces. This yeast has been difficult to detect and identify until it reaches overwhelming numbers in the wine. Early detection of this microorganism is shown to be easily done using a chemically tagged bit of genetic material (fluorescence labeled species-specific peptide nucleic acid probe) that is specific for the spoilage yeast. The simplicity of the detection procedure will allow its widespread application, which will save the wine industry considerable economic loss. Further, the same technology can be applied to detection of other spoilage microorganisms leading to increased consumer safety. Technical Abstract: A new fluorescence in situ hybridization (FISH) method using peptide nucleic acid (PNA) probes for identification of Brettanomyces is described. The test is based on fluorescein-labeled PNA probes targeting a species-specific sequence of ribosomal RNA (rRNA) of Dekkera bruxellensis. The probes are applied to smears of colonies, and results are interpreted by fluorescence microscopy. Based on the results from testing 127 different yeast strains, including 78 Brettanomyces isolates from wine, this study shows that the spoilage organism Brettanomyces belongs to the species Dekkera bruxellensis and that this new method is able to identify Brettanomyces (Dekkera bruxellensis) with 100 percent sensitivity and 100 percent specificity. |