Linked Life Data

16333109

Source:http://linkedlifedata.com/resource/pubmed/id/16333109

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2005-12-7
pubmed:abstractText
Traditional methods for microbial identification require the recognition of differences in morphology, growth, enzymatic activity, and metabolism to define genera and species. Full and partial 16S rRNA gene sequencing methods have emerged as useful tools for identifying phenotypically aberrant microorganisms. We report on three bacterial blood isolates from three different College of American Pathologists-certified laboratories that were referred to ARUP Laboratories for definitive identification. Because phenotypic identification suggested unusual organisms not typically associated with the submitted clinical diagnosis, consultation with the Medical Director was sought and further testing was performed including partial 16S rRNA gene sequencing. All three patients had endocarditis, and conventional methods identified isolates from patients A, B, and C as a Facklamia sp., Eubacterium tenue, and a Bifidobacterium sp. 16S rRNA gene sequencing identified the isolates as Enterococcus faecalis, Cardiobacterium valvarum, and Streptococcus mutans, respectively. We conclude that the initial identifications of these three isolates were erroneous, may have misled clinicians, and potentially impacted patient care. 16S rRNA gene sequencing is a more objective identification tool, unaffected by phenotypic variation or technologist bias, and has the potential to reduce laboratory errors.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0095-1137
pubmed:author
pubmed:issnType
Print
pubmed:volume
43
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
6123-5
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
The role of 16S rRNA gene sequencing in identification of microorganisms misidentified by conventional methods.
pubmed:affiliation
ARUP Laboratories, Inc., 500 Chipeta Way, Salt Lake City, UT 84108, USA. cathy.petti@aruplab.com
pubmed:publicationType
Journal Article