16S rRNA gene sequencing versus the API 20 NE system and the VITEK 2 ID-GNB card for identification of nonfermenting gram-negative bacteria in the clinical laboratory

16S rRNA gene sequencing versus the API 20 NE system and the VITEK 2 ID-GNB card for identification of nonfermenting gram-negative bacteria in the clinical laboratory
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DOI:
10.1128/jcm.44.4.1359-1366.2006
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发表时间:
2006-04-01
影响因子:
9.4
通讯作者:
Böttger, EC
Böttger, EC
中科院分区:
医学2区
文献类型:
--
作者:
Bosshard, PP;Zbinden, R;Böttger, EC

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在26个月的时间里,我们以前瞻性的方式评估了16S rRNA基因测序在微生物实验室中作为鉴定非发酵革兰氏阴性杆菌(非铜绿假单胞菌)临床相关分离株的方法。该研究旨在比较表型和分子鉴定。分子分析结果与两种市售鉴定系统(API 20 NE, VITEK 2荧光卡;bioMerieux, Marcy l'Etoile,法国)进行比较。通过16S rRNA基因序列分析,92%的分离株属于种水平,8%属于属水平。应用API 20ne分析,54%的分离株可划分为种,7%划分为属,39%的分离株在任何分类水平上都无法区分。VITEK 2的相应数字分别为53%,1%和46%。分别有15%和43%的分离物对应于API 20 NE和VITEK 2数据库中未包含的物种。我们认为16S rRNA基因测序是鉴定临床相关非发酵革兰氏阴性杆菌的有效手段。根据我们的经验,我们提出了一种在诊断实验室正确识别非发酵革兰氏阴性杆菌的算法。
Over a period of 26 months, we have evaluated in a prospective fashion the use of 16S rRNA gene sequencing as a means of identifying clinically relevant isolates of nonfermenting gram-negative bacilli (non-Pseudomonas aeruginosa) in the microbiology laboratory. The study was designed to compare phenotypic with molecular identification. Results of molecular analyses were compared with two commercially available identification systems (API 20 NE, VITEK 2 fluorescent card; bioMerieux, Marcy l'Etoile, France). By 16S rRNA gene sequence analyses, 92% of the isolates were assigned to species level and 8% to genus level. Using API 20 NE, 54% of the isolates were assigned to species and 7% to genus level, and 39% of the isolates could not be discriminated at any taxonomic level. The respective numbers for VITEK 2 were 53%, 1%, and 46%, respectively. Fifteen percent and 43% of the isolates corresponded to species not included in the API 20 NE and VITEK 2 databases, respectively. We conclude that 16S rRNA gene sequencing is an effective means for the identification of clinically relevant nonfermenting gram-negative bacilli. Based on our experience, we propose an algorithm for proper identification of nonfermenting gram-negative bacilli in the diagnostic laboratory.