Literature DB >> 23396215

Combining COLD-PCR and high-resolution melt analysis for rapid detection of low-level, rifampin-resistant mutations in Mycobacterium tuberculosis.

Yu Pang1, Guan Liu, Yufeng Wang, Suhua Zheng, Yan-Lin Zhao.   

Abstract

Multidrug-resistant Mycobacterium tuberculosis (M. tuberculosis) remains a serious threat to public health. Mutational analysis of the gene encoding the beta subunit of RNA polymerase (rpoB) is an established and widely used surrogate marker for multidrug-resistant tuberculosis (MDR-TB). The rpoB-based drug-resistant assay requires relatively less time to detect drug resistance in M. tuberculosis, yet it fails to detect low-level mutations in wild-type DNA. Here, we describe a low-level mutation detection method that combines co-amplification at lower denaturation temperature polymerase chain reaction (COLD-PCR) with high-resolution melting (HRM) analysis, aimed at detecting low-level, rifampin-resistant mutations in M. tuberculosis. Compared to conventional polymerase chain reaction (PCR), dilution experiments demonstrated a four- to eightfold improvement in selectivity using COLD-PCR/HRM to detect low-level, rifampin-resistant mutations. The mutation detection limit of conventional PCR/HRM was approximately 20%, whereas COLD-PCR/HRM had a mutation detection limit of 2.5%. Using traditional PCR/HRM and DNA sequencing, we found rpoB mutation in 110 rifampin-resistant isolates. The use of COLD-PCR/HRM allowed us to detect 10 low-level, rifampin-resistant mutations in 16 additional drug-resistant isolates. The sensitivity of COLD-PCR/HRM (95.2%) is significantly higher than that of PCR/HRM (87.3%). Our findings demonstrate that combined use of COLD-PCR with HRM can provide a sensitivity of at least 5% in detecting rpoB-mutated populations in a wild-type background, decreasing the delay in drug-resistant TB diagnosis and leading to faster, cheaper, more efficient, and more personalized antibiotic treatment, especially for low-level drug resistance mutations among the excess wild-type DNA.
Copyright © 2013 Elsevier B.V. All rights reserved.

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Year:  2013        PMID: 23396215     DOI: 10.1016/j.mimet.2013.01.008

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


  7 in total

1.  Comparison of different drug susceptibility test methods to detect rifampin heteroresistance in Mycobacterium tuberculosis.

Authors:  Zhijian Zhang; Yufeng Wang; Yu Pang; Changting Liu
Journal:  Antimicrob Agents Chemother       Date:  2014-07-14       Impact factor: 5.191

2.  Molecular characterization of multidrug-resistant Mycobacterium tuberculosis isolates from China.

Authors:  Li-Li Zhao; Yan Chen; Hai-Can Liu; Qiang Xia; Xiao-Cui Wu; Qing Sun; Xiu-Qin Zhao; Gui-Lian Li; Zhi-Guang Liu; Kang-Lin Wan
Journal:  Antimicrob Agents Chemother       Date:  2014-01-13       Impact factor: 5.191

3.  Automated liquid culture system misses isoniazid heteroresistance in Mycobacterium tuberculosis isolates with mutations in the promoter region of the inhA gene.

Authors:  Z Zhang; J Lu; Y Wang; Y Pang; Y Zhao
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2014-10-26       Impact factor: 3.267

4.  Genomic Analysis of the Evolution of Fluoroquinolone Resistance in Mycobacterium tuberculosis Prior to Tuberculosis Diagnosis.

Authors:  Danfeng Zhang; James E Gomez; Jung-Yien Chien; Nathan Haseley; Christopher A Desjardins; Ashlee M Earl; Po-Ren Hsueh; Deborah T Hung
Journal:  Antimicrob Agents Chemother       Date:  2016-10-21       Impact factor: 5.191

5.  Trainable high resolution melt curve machine learning classifier for large-scale reliable genotyping of sequence variants.

Authors:  Pornpat Athamanolap; Vishwa Parekh; Stephanie I Fraley; Vatsal Agarwal; Dong J Shin; Michael A Jacobs; Tza-Huei Wang; Samuel Yang
Journal:  PLoS One       Date:  2014-10-02       Impact factor: 3.240

6.  High Resolution Melting Curve Analysis for Rapid Detection of Streptomycin and Ethambutol Resistance in Mycobacterium tuberculosis.

Authors:  Faranak Rezaei; Mehri Haeili; Abbasali Imani Fooladi; Mohammad Mehdi Feizabadi
Journal:  Maedica (Bucur)       Date:  2017-12

7.  Dependence of Xpert MTB/RIF Accuracy for Detecting Rifampin Resistance in Bronchoalveolar Lavage Fluid on Bacterial Load: A Retrospective Study in Beijing, China.

Authors:  Lin Qin; Fengmin Huo; Weicong Ren; Yuanyuan Shang; Cong Yao; Xuxia Zhang; Rongmei Liu; Liping Ma; Mengqiu Gao; Yu Pang
Journal:  Infect Drug Resist       Date:  2021-06-28       Impact factor: 4.003

  7 in total

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