Literature DB >> 12543919

Granulicatella adiacens and Abiotrophia defectiva bacteraemia characterized by 16S rRNA gene sequencing.

Patrick Chiu-Yat Woo1, Ami Mei-Yuk Fung1, Susanna Kar-Pui Lau1, Benedict Yin-Leung Chan1, Siu-Kau Chiu1, Jade Lee-Lee Teng1, Tak-Lun Que1, Raymond Wai-Hung Yung1, Kwok-Yung Yuen1.   

Abstract

Traditionally, the identification, epidemiology and spectrum of clinical diseases caused by Granulicatella adiacens and Abiotrophia defectiva are dependent upon their phenotypic characterization. During a 6-year period (July 1995-June 2001), seven and two alpha-haemolytic streptococci were identified as G. adiacens and A. defectiva, respectively, by 16S rRNA gene sequencing. Three patients with haematological malignancies and neutropenic fever had primary bacteraemia. Three patients with valvular problems or congenital heart disease had infective endocarditis. A patient with ischemic heart disease and cerebrovascular accident had infected aortic atheroma with dissection. A patient with recurrent pyogenic cholangitis had acute cholangitis and a patient with polypoid cystitis and benign prostatic hypertrophy had acute prostatitis. Four of the nine patients died, including all three with G. adiacens infective endocarditis or infected atheroma. For the seven G. adiacens isolates, the API 20 STREP system successfully identified one and five isolates as G. adiacens with >95 % and 80-90 % confidence, respectively, whereas the Vitek System (GPI) and ATB Expression system (ID32 STREP) successfully identified none and one isolate as G. adiacens. Of the two A. defectiva isolates, none of the three systems successfully identified either of them as A. defectiva. 16S rRNA gene sequencing is the technique of choice for identifying G. adiacens and A. defectiva, and early surgical intervention should be considered when G. adiacens endocarditis is diagnosed.

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Year:  2003        PMID: 12543919     DOI: 10.1099/jmm.0.04950-0

Source DB:  PubMed          Journal:  J Med Microbiol        ISSN: 0022-2615            Impact factor:   2.472


  33 in total

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