4.7 Article

Evaluation of Fluoromycobacteriophages for Detecting Drug Resistance in Mycobacterium tuberculosis

期刊

JOURNAL OF CLINICAL MICROBIOLOGY
卷 49, 期 5, 页码 1838-1842

出版社

AMER SOC MICROBIOLOGY
DOI: 10.1128/JCM.02476-10

关键词

-

资金

  1. FONACIT (Fondo Nacional de Ciencia, Tecnologia y Innovacion) [G-2005000393, 20010001851]
  2. Helmerich & Paine de Venezuela, C. A., through LOCTI (Ley Organcia de Ciencia, Tecnologia y Innovacion)
  3. HHMI

向作者/读者索取更多资源

We tested a new method for detecting drug-resistant strains of Mycobacterium tuberculosis that uses a TM4 mycobacteriophage phAE87::hsp60-EGFP (EGFP-phage) engineered to contain the gene encoding enhanced green fluorescent protein (EGFP). After promising results in preliminary studies, the EGFP-phage was used to detect isoniazid (INH), rifampin (RIF), and streptomycin (STR) resistance in 155 strains of M. tuberculosis, and the results were compared to the resazurin microplate technique, with the proportion method serving as the reference standard. The resazurin technique yielded sensitivities of 94% for INH and RIF and 98% for STR and specificities of 97% for INH, 95% for RIF, and 98% for STR. The sensitivity of EGFP-phage was 94% for all three antibiotics, with specificities of 90% for INH, 93% for RIF, and 95% for STR. The EGFP-phage results were available in 2 days for RIF and STR and in 3 days for INH, with an estimated cost of similar to 2$ to test the three antibiotics. Using a more stringent criterion for resistance improved the specificity of the EGFP-phage for INH and RIF without affecting the sensitivity. In preliminary studies, the EGFP-phage could also effectively detect resistance to the fluoroquinolones. The EGFP-phage method has the potential to be a valuable rapid and economic screen for detecting drug-resistant tuberculosis if the procedure can be simplified, if it can be adapted to clinical material, and if its sensitivity can be improved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据