Molecular drug resistance profiles of Mycobacterium tuberculosis from sputum specimens using ion semiconductor sequencing.

来自 PUBMED

作者:

Park JJang WKim MKim YShin SYPark KKim MSShin S

展开

摘要:

The increasing burden of multidrug resistant (MDR)-TB, defined by resistance to rifampin (RFP) and isoniazid (INH), and extensively drug resistant-TB, defined by MDR-TB with additional resistance to fluoroquinolones (FQs) and more than one second-line injectable drug, is a serious impediment to global TB control. We evaluated the feasibility of full-length gene analysis including inhA, katG, rpoB, pncA, rpsL embB, eis, and gyrA using a semiconductor NGS with the Ion AmpliSeq TB panel to directly analyse 34 sputum specimens confirmed by phenotypic DST: INH, RFP, ethambutol (EMB), pyrazinamide (PZA), amikacin, kanamycin, streptomycin (SM), FQs including ofloxacin, moxifloxacin, and levofloxacin. The molecular drug resistance profiles showed "very good" and "substantial" strength of agreement for the phenotypic DST results of RFP and EMB, PZA, SM, FQs resistance with specificities of 96%, and 88%, 97%, 100% and sensitivities of 100%, and 88%, 60%, 67%, respectively. The strength of agreement for the detection of resistance to INH was "substantial", compared between katG mutation and phenotypic INH only. Ion semiconductor NGS could make possible detection of several uncommon or novel amino acid changes in the full coding regions of these eight genes. However, molecular drug resistant profile should be complemented and validated by subsequent phenotypic DST studies at the same time.

收起

展开

DOI:

10.1016/j.mimet.2017.12.003

被引量:

7

年份:

1970

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(176)

参考文献(0)

引证文献(7)

来源期刊

-

影响因子:暂无数据

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读