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Feng L, He W, Song Z, Zhao B, Teng C, Liu E, Zhu H, Pei S, Liu L, Song Y, Zheng Y, Liu X, Zhao Y, Ou X. Drug-Resistant Profiles and Genetic Diversity of Mycobacterium Tuberculosis Revealed by Whole-Genome Sequencing in Hinggan League of Inner Mongolia, China. Infect Drug Resist 2024; 17:3089-3100. [PMID: 39050828 PMCID: PMC11268717 DOI: 10.2147/idr.s466197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 07/02/2024] [Indexed: 07/27/2024] Open
Abstract
Background Tuberculosis remains a major public health concern in China, with varying prevalence and drug resistance profiles across regions. This study explores the genetic diversity and drug-resistant profiles of MTB strains in Hinggan League, a high TB burden in Inner Mongolia, China. Methods This population-based retrospective study, encompassing all culture-positive TB cases from Jun. 2021 to Jun. 2023 in Hinggan League. Drug resistant profiles and genetic diversity of MTB strains were assessed using phenotypic drug susceptibility testing and whole-genome sequencing. Risk factors associated with drug resistance were analyzed using univariate and multivariate logistic regression models. Results A total of 211 MTB strains were recovered successfully and included into final analysis. Lineage 2.2.1 (88.6%, 187/211) was the dominant sub-lineage, followed by lineage 4.5 (7.1%, 15/211) and lineage 4.4 (4.3%, 9/211). MTB strains exhibited the highest resistance rates to isoniazid (16.1%, 34/211), followed by rifampicin (10.0, 21/211). In addition, the MTB strains also showed relatively high rates of resistance against new and repurposed anti-TB drugs, with resistant rates of 2.4% (5/211) to delamanid and 1.9% (4/211) to bedaquiline. Overall, 25.6% (54/211) of MTB strains were DR-TB, and 14 MTB strains met the definition of MDR-TB, including 7 strains of simple-MDR-TB, 5 of pre-XDR-TB, and 2 of XDR-TB. Genetic analysis revealed that the dominant mutations of isoniazid-, rifampin-, ethambutol-, levofloxacin-/moxifloxacin-, and ethionamide- resistance were katG_Ser315Thr(46.4%), rpoB_Ser450Leu (47.4%), embB_Met306Val (25.0%), gyrA_Asp94Ala (40.0%), and fabG1_c15t (42.9%), respectively. Previously treated patients (AOR = 2.015, 95% CI: 1.052-4.210) and male patients (AOR = 3.858, 95% CI: 1.416-10.511) were identified as independent risk factors associated with DR-TB. Conclusion Our study offers crucial insights into the genetic diversity and drug-resistant profiles of TB strains circulating in Hinggan League. These findings are valuable for DR-TB surveillance and for guiding treatment regimens and public health interventions in the region.
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Affiliation(s)
- Liping Feng
- Department of Microbiology, Hinggan League Center for Disease Control and Prevention, Ulanhot, 137499, People’s Republic of China
| | - Wencong He
- Department of Clinical Laboratory, Beijing Tongren Hospital, Capital Medical University, Beijing, 100176, People’s Republic of China
| | - Zexuan Song
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Bing Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Chong Teng
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Eryong Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Hanfang Zhu
- Department of Microbiology, Hinggan League Center for Disease Control and Prevention, Ulanhot, 137499, People’s Republic of China
| | - Shaojun Pei
- School of Public Health, Peking University, Beijing, 100191, People’s Republic of China
| | - Lina Liu
- Blood Transfusion Department, Hinggan League People’s Hospital, Ulanhot, 137400, People’s Republic of China
| | - Yuanyuan Song
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Yang Zheng
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Xiangyi Liu
- Department of Clinical Laboratory, Beijing Tongren Hospital, Capital Medical University, Beijing, 100176, People’s Republic of China
| | - Yanlin Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Xichao Ou
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
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Zhu Y, Feng Z, Xu Y, Luo S, Zhang R, Shi X, Wu X, Zhang H. Rapid detection of Mycobacterium tuberculosis based on cyp141 via real-time fluorescence loop-mediated isothermal amplification (cyp141-RealAmp). Front Cell Infect Microbiol 2024; 14:1349063. [PMID: 38938885 PMCID: PMC11208306 DOI: 10.3389/fcimb.2024.1349063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 05/06/2024] [Indexed: 06/29/2024] Open
Abstract
Background The rapid detection of Mycobacterium tuberculosis (MTB) is essential for controlling tuberculosis. Methods We designed a portable thermocycler-based real-time fluorescence loop-mediated isothermal amplification assay (cyp141-RealAmp) using six oligonucleotide primers derived from cyp141 to detect MTB. A combined number of 213 sputum samples (169 obtained from clinically diagnosed cases of pulmonary TB and 44 from a control group without tuberculosis) underwent Acid-fast bacillus (AFB) smear, culture, Xpert MTB/RIF assays, and cyp141-RealAmp assay. Results By targeting MTB cyp141, this technique could detect as low as 10 copies/reaction within 30 min, and it was successfully rejected by other mycobacteria and other bacterial species tested. Of the 169 patients, there was no statistical difference between the detection rate of cyp141-RealAmp (92.90%, 95% CI: 89.03-96.07) and that of Xpert MTB/RIF (94.67%, 95% CI: 91.28-98.06) (P > 0.05), but both were statistically higher than that of culture (65.68%, 95% CI: 58.52-72.84) (P< 0.05) and AFB (57.40%, 95% CI: 49.94-64.86) (P< 0.05). Both cyp141-RealAmp and Xpert MTB/RIF had a specificity of 100%. Furthermore, a high concordance between cyp141-RealAmp and Xpert MTB/RIF was found (Kappa = 0.89). Conclusion The cyp141-RealAmp assay was shown to be effective, responsive, and accurate in this study. This method offers a prospective strategy for the speedy and precise detection of MTB.
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Affiliation(s)
- Yinyin Zhu
- Department of Microbial Testing, Nanjing Center for Disease Control and Prevention Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
- School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zi Feng
- Department of Microbial Testing, Nanjing Center for Disease Control and Prevention Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
- School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yinfang Xu
- Department of Infectious Diseases, the Affiliated Zhongda Hospital of Southeast University, Nanjing, Jiangsu, China
| | - Sha Luo
- The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Ruixian Zhang
- The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Xudong Shi
- The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Xuping Wu
- The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Hongying Zhang
- Department of Microbial Testing, Nanjing Center for Disease Control and Prevention Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
- School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
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He G, Zheng Q, Wu J, Wu L, Geng Z, Jiang G, Huang H, Jiang X, Yu X. Discordant results between Xpert MTB/RIF assay and Bactec MGIT 960 culture system regarding the detection of rifampin-resistant Mycobacterium tuberculosis isolates in Wenzhou, China. Microbiol Spectr 2024; 12:e0385923. [PMID: 38738892 PMCID: PMC11237732 DOI: 10.1128/spectrum.03859-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 04/08/2024] [Indexed: 05/14/2024] Open
Abstract
This study aimed to assess the possible causes of discordant results between Xpert MTB/RIF (Xpert) and Bactec MGIT 960 Culture System (MGIT960) regarding rifampicin (RIF) susceptibility in Mycobacterium tuberculosis. Patients with previous RIF-resistant tuberculosis who were admitted to Wenzhou Central Hospital from January 2020 to December 2022 were enrolled. The isolates obtained from these patients were subjected to RIF susceptibility tests using Xpert and MGIT960, and the minimum inhibitory concentration (MIC) of RIF was determined by the MYCOTB MIC plate test. Additionally, molecular docking and molecular dynamics (MD) simulations were performed to evaluate the binding efficacy of rpoB and RIF based on rpoB mutations detected in the isolates with discordant RIF susceptibility results. A total of 28 isolates with discordant RIF susceptibility test results were detected, 15 of them were RIF susceptible with MICs ≤ 0.5 µg/mL. Twelve out of 15 isolates contained borderline RIF resistance-associated mutations [L430P (n = 6), H445N (n = 6)], 1 isolate had D435Y and Q429H double mutation, and the remaining 2 isolates had a silent (Q432Q) mutation. Compared with the affinity of RIF toward the wild type (WT) (-45.83 kcal/mol) by MD, its affinity toward L452P (-55.52 kcal/mol), D435Y (-47.39 kcal/mol), L430P (approximately -69.72 kcal/mol), H445N (-49.53 kcal/mol), and Q429H (-55.67 kcal/mol) increased. Borderline RIF resistance-associated mutations were the main cause for the discordant RIF susceptibility results between Xpert and MGIT960, and the mechanisms of the resistance need further investigated.IMPORTANCEThis study is aimed at assessing discordant results between Xpert MTB/RIF (Xpert) assay and Bactec MGIT 960 Culture System (MGIT960) regarding the detection of rifampicin (RIF)-resistant Mycobacterium tuberculosis isolates in Wenzhou, China. The discordant results of RIF between these two assays were mainly caused by borderline RIF resistance-associated mutations, subsequently by silent mutations of rpoB. Borderline RIF resistance- associated mutations detected in our study were demonstrated to not be affected by the affinity of rpoB and RIF by molecular dynamics, and the mechanism of resistance was needed to be clarified. For the discordant results of RIF by Xpert and MGIT960 that occurred, rpoB DNA sequencing was recommended to investigate its association with resistance to RIF.
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Affiliation(s)
- Guiqing He
- Department of Infectious Diseases, Wenzhou Central Hospital, The Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University, Wenzhou, China
- Laboratory of Infectious Diseases, Wenzhou Central Hospital, The Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University, Wenzhou, China
| | - Qingyong Zheng
- Laboratory of Infectious Diseases, Wenzhou Central Hospital, The Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University, Wenzhou, China
| | - Jing Wu
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-Resistant Tuberculosis, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Lianpeng Wu
- Department of Clinical Laboratory Medicine, Wenzhou Central Hospital, The Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University, Wenzhou, China
| | - Zhi Geng
- Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| | - Guanglu Jiang
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-Resistant Tuberculosis, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Hairong Huang
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-Resistant Tuberculosis, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Xiangao Jiang
- Department of Infectious Diseases, Wenzhou Central Hospital, The Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University, Wenzhou, China
| | - Xia Yu
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-Resistant Tuberculosis, Beijing Chest Hospital, Capital Medical University, Beijing, China
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Sanchini A, Lanni A, Giannoni F, Mustazzolu A. Exploring diagnostic methods for drug-resistant tuberculosis: A comprehensive overview. Tuberculosis (Edinb) 2024; 148:102522. [PMID: 38850839 DOI: 10.1016/j.tube.2024.102522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/14/2024] [Accepted: 05/30/2024] [Indexed: 06/10/2024]
Abstract
Despite available global efforts and funding, Tuberculosis (TB) continues to affect a considerable number of patients worldwide. Policy makers and stakeholders set clear goals to reduce TB incidence and mortality, but the emergence of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) complicate the reach of these goals. Drug-resistance TB needs to be diagnosed rapidly and accurately to effectively treat patients, prevent the transmission of MDR-TB, minimise mortality, reduce treatment costs and avoid unnecessary hospitalisations. In this narrative review, we provide a comprehensive overview of laboratory methods for detecting drug resistance in MTB, focusing on phenotypic, molecular and other drug susceptibility testing (DST) techniques. We found a large variety of methods used, with the BACTEC MGIT 960 being the most common phenotypic DST and the Xpert MTB/RIF being the most common molecular DST. We emphasise the importance of integrating phenotypic and molecular DST to address issues like resistance to new drugs, heteroresistance, mixed infections and low-level resistance mutations. Notably, most of the analysed studies adhered to the outdated definition of XDR-TB and did not consider the pre-XDR definition, thus posing challenges in aligning diagnostic methods with the current landscape of TB resistance.
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Affiliation(s)
| | - Alessio Lanni
- Department of Infectious Diseases, Istituto Superiore di Sanità, 00161, Rome, Italy.
| | - Federico Giannoni
- Department of Infectious Diseases, Istituto Superiore di Sanità, 00161, Rome, Italy.
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Song Z, He W, Cao X, Ma A, He P, Zhao B, Wang S, Liu C, Zhao Y. The Recent Transmission and Associated Risk Factor of Mycobacterium tuberculosis in Golmud City, China. Infect Drug Resist 2024; 17:417-425. [PMID: 38318210 PMCID: PMC10840525 DOI: 10.2147/idr.s437026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 12/05/2023] [Indexed: 02/07/2024] Open
Abstract
Background Tuberculosis (TB) remains a severe public health problem globally, and it is essential to comprehend the transmission pattern to control tuberculosis. Herein, we evaluated the drug-resistant characteristics, recent transmission, and associated risk factors of TB in Golmud, Qinghai, China. Methods In this study, we performed a population-based study of patients diagnosed with TB in Golmud from 2013 to 2018. Drug-susceptibility testing and whole-genome sequencing were performed on 133 Mycobacterium tuberculosis strains. The genomic clustering rate was calculated to evaluate the level of recent transmission. Risk factors were identified by logistic regression analysis. Results Our results showed that 46.97% (62/132) of strains were phylogenetically clustered and formed into 23 transmission clusters, suggesting a high recent transmission of TB in the area. 12.78% (17/133) strains were multidrug-resistant/rifampicin tuberculosis (MDR/RR-TB), with a high drug-resistant burden. Based on drug resistance gene analysis, we found 23 strains belonging to genotype MDR/RR-TB, where some strains may have borderline mutations. Among these strains, 65.2% (15/23) were found within putative transmission clusters. Additionally, risk factor analysis showed that recent transmission of TB happened more in patients with Tibetan nationality or older age. Conclusion Overall our study indicates that the recent transmissions of MTB strains, especially genotypic MDR/RR strains, drive the tuberculosis epidemic in Golmud, which could contribute to developing effective TB prevention and control strategies.
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Affiliation(s)
- Zexuan Song
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Wencong He
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Xiaolong Cao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Aijing Ma
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Ping He
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Bing Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Shengfen Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Chunfa Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
- Animal Science and Technology College, Beijing University of Agriculture, Huilongguan, Changping, Beijing, 102206, People’s Republic of China
| | - Yanlin Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
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Ou X, Song Z, Zhao B, Pei S, Teng C, Zheng H, He W, Xing R, Wang Y, Wang S, Xia H, Zhou Y, He P, Zhao Y. Diagnostic efficacy of an optimized nucleotide MALDI-TOF-MS assay for anti-tuberculosis drug resistance detection. Eur J Clin Microbiol Infect Dis 2024; 43:105-114. [PMID: 37980301 DOI: 10.1007/s10096-023-04700-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 11/01/2023] [Indexed: 11/20/2023]
Abstract
PURPOSE We aimed at evaluating the diagnostic efficacy of a nucleotide matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) assay to detect drug resistance of Mycobacterium tuberculosis. METHODS Overall, 263 M. tuberculosis clinical isolates were selected to evaluate the performance of nucleic MALDI-TOF-MS for rifampin (RIF), isoniazid (INH), ethambutol (EMB), moxifloxacin (MXF), streptomycin (SM), and pyrazinamide (PZA) resistance detection. The results for RIF, INH, EMB, and MXF were compared with phenotypic microbroth dilution drug susceptibility testing (DST) and whole-genome sequencing (WGS), and the results for SM and PZA were compared with those obtained by WGS. RESULTS Using DST as the gold standard, the sensitivity, specificity, and kappa values of the MALDI-TOF-MS assay for the detection of resistance were 98.2%, 98.7%, and 0.97 for RIF; 92.8%, 99%, and 0.90 for INH; 82.4%, 98.0%, and 0.82 for EMB; and 92.6%, 99.5%, and 0.94 for MXF, respectively. Compared with WGS as the reference standard, the sensitivity, specificity, and kappa values of the MALDI-TOF-MS assay for the detection of resistance were 97.4%, 100.0%, and 0.98 for RIF; 98.7%, 92.9%, and 0.92 for INH; 96.3%, 100.0%, and 0.98 for EMB; 98.1%, 100.0%, and 0.99 for MXF; 98.0%, 100.0%, and 0.98 for SM; and 50.0%, 100.0%, and 0.65 for PZA. CONCLUSION The nucleotide MALDI-TOF-MS assay yielded highly consistent results compared to DST and WGS, suggesting that it is a promising tool for the rapid detection of sensitivity to RIF, INH, EMB, and MXF.
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Affiliation(s)
- Xichao Ou
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Zexuan Song
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Bing Zhao
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Shaojun Pei
- School of Public Health, Peking University, Beijing, 100191, China
| | - Chong Teng
- Department of Tuberculosis, Beijing Dongcheng District Center for Disease Control, Beijing, 100050, China
| | - Huiwen Zheng
- Laboratory of Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Children's Hospital, Capital Medical University, Beijing, 100045, China
| | - Wencong He
- Clinical Laboratory, Beijing Tong Ren Hospital, Capital Medical University, Beijing, 100730, China
| | - Ruida Xing
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Yiting Wang
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Shengfen Wang
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Hui Xia
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Yang Zhou
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Ping He
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Yanlin Zhao
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, No. 155 Chang Bai Road, Changping District, Beijing, 102206, People's Republic of China.
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Li K, Hu Q, Liu J, Liu S, He Y. Effects of sputum bacillary load and age on GeneXpert and traditional methods in pulmonary tuberculosis: a 4-year retrospective comparative study. BMC Infect Dis 2023; 23:831. [PMID: 38012541 PMCID: PMC10680317 DOI: 10.1186/s12879-023-08832-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 11/18/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND The purpose of this study was to evaluate the diagnostic value of the GeneXpert® MTB/RIF (Xpert®), Auramine O staining method, and Lowenstein-Jensen medium for bacteriologically confirmed pulmonary tuberculosis and explore the effects of the sputum bacillary load (SBL) and qRT‒PCR threshold cycle (Ct) value on the detection methods. METHODS We retrospectively analysed the results in the Department of Infectious Disease for 49 months. The χ2 test was used to compare the performances of each method, receiver operating characteristic curve analysis was used to determine the optimal cut-off values, and the factors associated with a false-negative result from Xpert® were analysed by logistic regression. RESULTS Simultaneous analysis of 980 sputum specimens showed that the positive detection rate of Xpert® did not increase with increasing SBL, and there were differences between the three when SBL ≤ 1 + (all P < 0.05). There was a good negative correlation between the Ct value and the SBL (P < 0.0001). Age was an independent risk factor for false-negative Xpert® results (P = 0.029), and when Ct < 16, the diagnostic sensitivity and specificity were both 100.00%. The optimal cut-off Ct values for resegmentation based on the drug resistance classification were < 18.6, 18.6-34.1, and > 34.1 cycles. CONCLUSIONS Xpert® was not affected by SBL but it was by age, and it is more advantageous when SBL ≤ 1 + . The results regarding rifampicin resistance were reliable, and the novel Ct segmentation was a practical and more clinically meaningful classification method for diagnosing rifampicin resistance. These findings will help improve physicians' ability to accurately diagnose TB.
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Affiliation(s)
- Kui Li
- Department of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West YantaRoad, Xi'an, Shaanxi Province, 710061, China
- Department of Infectious Diseases, Ankang Central Hospital, 85 South Jinzhou Road, Ankang, Shaanxi Province, 725000, China
| | - Qianqian Hu
- Laboratory of Molecular Pathology and Tuberculosis Diseases, Ankang Central Hospital, 85 South Jinzhou Road, Ankang, Shaanxi Province, 725000, China
| | - Jun Liu
- Laboratory of Molecular Pathology and Tuberculosis Diseases, Ankang Central Hospital, 85 South Jinzhou Road, Ankang, Shaanxi Province, 725000, China
| | - Siyi Liu
- Department of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West YantaRoad, Xi'an, Shaanxi Province, 710061, China
| | - Yingli He
- Department of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West YantaRoad, Xi'an, Shaanxi Province, 710061, China.
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Karuniawati A, Burhan E, Koendhori EB, Sari D, Haryanto B, Nuryastuti T, Gayatri AAAY, Bahrun U, Kusumawati RL, Sugiyono RI, Susanto NH, Diana A, Kosasih H, Naysilla AM, Lokida D, Neal A, Siddiqui S, Lau CY, Karyana M. Performance of Xpert MTB/RIF and sputum microscopy compared to sputum culture for diagnosis of tuberculosis in seven hospitals in Indonesia. Front Med (Lausanne) 2023; 9:909198. [PMID: 36743681 PMCID: PMC9896521 DOI: 10.3389/fmed.2022.909198] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 12/07/2022] [Indexed: 01/21/2023] Open
Abstract
Introduction Tuberculosis (TB) is a major public health concern in Indonesia, where the incidence was 301 cases per 100,000 inhabitants in 2020 and the prevalence of multi-drug resistant (MDR) TB is increasing. Diagnostic testing approaches vary across Indonesia due to resource limitations. Acid-fast bacilli (AFB) smear is widely used, though Xpert MTB/RIF has been the preferred assay for detecting TB and rifampicin resistance since 2012 due to higher sensitivity and ability to rapidly identify rifampicin resistance. However, <1,000 Xpert instruments were available in Indonesia as of 2020 and the Xpert supply chain has suffered interruptions. Methods We compared the performance of Xpert MTB/RIF and AFB smear to facilitate optimization of TB case identification. We analyzed baseline data from a cohort study of adults with pulmonary TB conducted at seven hospitals across Indonesia. We evaluated sensitivity and specificity of AFB smear and Xpert MTB/RIF using Mycobacterium tuberculosis (Mtb) culture as the gold standard, factors associated with assay results, and consistency of Xpert MTB/RIF with drug susceptibility test (DST) in detecting rifampicin resistance. Results Sensitivity of AFB smear was significantly lower than Xpert MTB/RIF (86.2 vs. 97.4%, p-value <0.001), but specificity was significantly better (86.7 vs. 73.3%, p-value <0.001). Performance varied by hospital. Positivity rate for AFB smear and Mtb culture was higher in subjects with pulmonary cavities and in morning sputum samples. Consistency of Xpert MTB/RIF with DST was lower in those with rifampicin- sensitive TB by DST. Discussion Additional evaluation using sputa from primary and secondary Indonesian health centers will increase the generalizability of the assessment of AFB smear and Xpert MTB/RIF performance, and better inform health policy. Clinical trial registration [https://clinicaltrials.gov/], identifier [NCT027 58236].
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Affiliation(s)
- Anis Karuniawati
- Department of Microbiology, Faculty of Medicine, Universitas Indonesia, Dr. Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Erlina Burhan
- Department of Pulmonary and Respiratory Medicine, Faculty of Medicine, Universitas Indonesia, Persahabatan Hospital, Jakarta, Indonesia
| | - Eko Budi Koendhori
- Department of Medical Microbiology, Faculty of Medicine, Universitas Airlangga, Dr. Soetomo Hospital, Surabaya, Indonesia
| | - Desvita Sari
- Department of Microbiology, Faculty of Medicine, Universitas Diponegoro, Dr. Kariadi Hospital, Semarang, Indonesia
| | - Budi Haryanto
- Microbiology Unit, Persahabatan Hospital, Jakarta, Indonesia
| | - Titik Nuryastuti
- Department of Microbiology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - A. A. A. Yuli Gayatri
- Department of Internal Medicine, Faculty of Medicine, Universitas Udayana, Prof. IGNG. Ngoerah General Hospital, Bali, Indonesia
| | - Uleng Bahrun
- Department of Clinical Pathology, Faculty of Medicine, University of Hasanuddin, Dr. Wahidin Sudirohusodo Hospital, Makassar, Indonesia
| | - R. Lia Kusumawati
- Department of Microbiology, Faculty of Medicine, Universitas Sumatera Utara, H. Adam Malik General Hospital, Medan, Indonesia
| | - Retna Indah Sugiyono
- Indonesia Research Partnership on Infectious Disease (INA-RESPOND), Jakarta, Indonesia
| | - Nugroho Harry Susanto
- Indonesia Research Partnership on Infectious Disease (INA-RESPOND), Jakarta, Indonesia
| | - Aly Diana
- Indonesia Research Partnership on Infectious Disease (INA-RESPOND), Jakarta, Indonesia,Department of Public Health, Faculty of Medicine, Universitas Padjadjaran, Sumedang, Indonesia
| | - Herman Kosasih
- Indonesia Research Partnership on Infectious Disease (INA-RESPOND), Jakarta, Indonesia,*Correspondence: Herman Kosasih,
| | | | - Dewi Lokida
- Department of Clinical Pathology, Tangerang District Hospital, Tangerang, Indonesia
| | - Aaron Neal
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Sophia Siddiqui
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Chuen-Yen Lau
- HIV Dynamics and Replication Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Muhammad Karyana
- National Institute of Health Research and Development, Ministry of Health, Republic of Indonesia, Jakarta, Indonesia
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Ou X, Zhang Z, Zhao B, Song Z, Wang S, He W, Pei S, Liu D, Xing R, Xia H, Zhao Y. Evaluation Study of xMAP TIER Assay on a Microsphere-Based Platform for Detecting First-Line Anti-Tuberculosis Drug Resistance. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph192417068. [PMID: 36554951 PMCID: PMC9779588 DOI: 10.3390/ijerph192417068] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 12/15/2022] [Accepted: 12/16/2022] [Indexed: 05/09/2023]
Abstract
Early diagnosis of drug susceptibility for tuberculosis (TB) patients could guide the timely initiation of effective treatment. We evaluated a novel multiplex xMAP TIER (Tuberculosis-Isoniazid-Ethambutol-Rifampicin) assay based on the Luminex xMAP system to detect first-line anti-tuberculous drug resistance. Deoxyribonucleic acid samples from 353 Mycobacterium tuberculosis clinical isolates were amplified by multiplex polymerase chain reaction, followed by hybridization and analysis through the xMAP system. Compared with the broth microdilution method, the sensitivity and specificity of the xMAP TIER assay for detecting resistance was 94.9% (95%CI, 90.0-99.8%) and 98.9% (95%CI, 97.7-100.0%) for rifampicin; 89.1% (95%CI, 83.9-94.3%) and 100.0% (95%CI, 100.0-100.0%) for isoniazid; 82.1% (95% CI, 68.0-96.3%) and 99.7% (95% CI, 99.0-100.0%) for ethambutol. With DNA sequencing as the reference standard, the sensitivity and specificity of xMAP TIER for detecting resistance were 95.0% (95% CI, 90.2-99.8%) and 99.6% (95% CI, 98.9-100.0%) for rifampicin; 96.9% (95% CI, 93.8-99.9%) and 100.0% (95% CI, 100.0-100.0%) for isoniazid; 86.1% (95% CI, 74.8-97.4%) and 100.0% (95% CI, 100.0-100.0%) for ethambutol. The results achieved showed that the xMAP TIER assay had good performance for detecting first-line anti-tuberculosis drug resistance, and it has the potential to diagnose drug-resistant tuberculosis more accurately due to the addition of more optimal design primers and probes on open architecture xMAP system.
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Affiliation(s)
- Xichao Ou
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Zhiguo Zhang
- Tuberculosis Dispensary of Changping District, Beijing 102202, China
| | - Bing Zhao
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Zexuan Song
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Shengfen Wang
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Wencong He
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Shaojun Pei
- School of Public Health, Peking University, Beijing 100191, China
| | - Dongxin Liu
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Ruida Xing
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Hui Xia
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Yanlin Zhao
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
- Correspondence:
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