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Li M, Zhang Y, Wu Z, Jiang Y, Sun R, Yang J, Li J, Lin H, Zhang R, Jiang Q, Wang L, Wu X, Yu F, Yuan J, Yang C, Shen X. Transmission of fluoroquinolones resistance among multidrug-resistant tuberculosis in Shanghai, China: a retrospective population-based genomic epidemiology study. Emerg Microbes Infect 2024; 13:2302837. [PMID: 38205528 PMCID: PMC10810664 DOI: 10.1080/22221751.2024.2302837] [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: 08/21/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
Fluoroquinolones (FQ) are essential for the treatment of multidrug-resistant tuberculosis (MDR-TB). The FQ resistance (FQ-R) rate in MDR-TB in China and its risk factors remain poorly understood. We conducted a retrospective, population-based genomic epidemiology study of MDR-TB patients in Shanghai, China, from 2009 to 2018. A genomic cluster was defined as strains with genetic distances ≤ 12 single nucleotide polymorphisms. The transmitted FQ-R was defined as the same FQ resistance-conferring mutations shared by ≥ 2 strains in a genomic cluster. We used multivariable logistic regression analysis to identify the risk factors for drug resistance. Among the total 850 MDR-TB patients included in the study, 72.8% (619/850) were male, the median age was 39 (interquartile range 28, 55) years, 52.7% (448/850) were migrants, and 34.5% (293/850) were previously treated patients. Most of the MDR-TB strains belong to the Beijing lineage (91.7%, 779/850). Overall, the genotypic resistance rate of FQ was 34.7% (295/850), and 47.1% (139/295) FQ-R patients were in genomic clusters, of which 98 (33.2%, 98/295) were presumed as transmitted FQ-R. Patients with treatment-naïve (aOR = 1.84; 95% CI: 1.09, 3.16), diagnosed in a district-level hospital (aOR = 2.69; 95% CI: 1.56, 4.75), and streptomycin resistance (aOR = 3.69; 95% CI: 1.65, 9.42) were significantly associated with the transmission of FQ-R. In summary, the prevalence of FQ-R among MDR-TB patients was high in Shanghai, and at least one-third were transmitted. Enforced interventions including surveillance of FQ drug susceptibility testing and screening among MDR-TB before initiation of treatment were urgently needed.
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Affiliation(s)
- Minjuan Li
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Guangdong, People’s Republic of China
| | - Yangyi Zhang
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, People’s Republic of China
- Shanghai Institutes of Preventive Medicine, Shanghai, People’s Republic of China
- Department of Epidemiology, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, Shanghai, People’s Republic of China
| | - Zheyuan Wu
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, People’s Republic of China
- Shanghai Institutes of Preventive Medicine, Shanghai, People’s Republic of China
| | - Yuan Jiang
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, People’s Republic of China
- Shanghai Institutes of Preventive Medicine, Shanghai, People’s Republic of China
| | - Ruoyao Sun
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Guangdong, People’s Republic of China
| | - Jinghui Yang
- Department of Clinical Laboratory, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, People’s Republic of China
| | - Jing Li
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, People’s Republic of China
- Shanghai Institutes of Preventive Medicine, Shanghai, People’s Republic of China
| | - Honghua Lin
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Guangdong, People’s Republic of China
| | - Rui Zhang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Guangdong, People’s Republic of China
| | - Qi Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, People’s Republic of China
| | - Lili Wang
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, People’s Republic of China
- Shanghai Institutes of Preventive Medicine, Shanghai, People’s Republic of China
| | - Xiaocui Wu
- Department of Clinical Laboratory, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, People’s Republic of China
| | - Fangyou Yu
- Department of Clinical Laboratory, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, People’s Republic of China
| | - Jianhui Yuan
- Nanshan District Center for Disease Control and Prevention, Shenzhen, People’s Republic of China
| | - Chongguang Yang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Guangdong, People’s Republic of China
- Nanshan District Center for Disease Control and Prevention, Shenzhen, People’s Republic of China
| | - Xin Shen
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, People’s Republic of China
- Shanghai Institutes of Preventive Medicine, Shanghai, People’s Republic of China
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Teng C, Li L, Su D, Li H, Zhao B, Xia H, Teng H, Song Y, Zheng Y, Cao X, Zheng H, Zhao Y, Ou X. Evaluation of genetic correlation with fluoroquinolones resistance in rifampicin-resistant Mycobacterium tuberculosis isolates. Heliyon 2024; 10:e31959. [PMID: 38868072 PMCID: PMC11167346 DOI: 10.1016/j.heliyon.2024.e31959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 05/24/2024] [Accepted: 05/24/2024] [Indexed: 06/14/2024] Open
Abstract
Objective To detect levofloxacin (LFX) and moxifloxacin (MFX) resistance among rifampicin-resistant tuberculosis (RR-TB) isolates, and predict the resistance level based on specific mutations in gyrA and gyrB genes. Methods A total of 686 RR-TB isolates were collected from Chinese Drug Resistance Surveillance Program from 2013 to 2020. The minimum inhibitory concentrations (MICs) of 12 anti-TB drugs were acquired using the broth microdilution method, followed by whole genome sequencing (WGS) analysis. Results Among the 686 RR isolates, the most prevalent resistance was to isoniazid (80.5 %) and ethambutol (28.4 %), followed by LFX (26.1 %) and MFX (21.9 %). The resistance rate of LFX (26.1%-99.4 %) was higher than that of MFX (21.9%-83.3 %) across various drug resistance patterns. Of the 180 fluoroquinolones (FQs) resistant isolates, 168 (93.3 %) had mutations in quinolone-resistant determining regions (QRDRs) with 21 mutation types, and Asp94Gly (32.7 %, 55/168) was the predominant mutation. Isolates with mutations in Asp94Asn and Asp94Gly were associated with high levels of resistance to LFX and MFX. Using broth microdilution method as gold standard, the sensitivities of WGS for LFX and MFX were 93.3 % and 98.0 %, and the specificities were 98.6 % and 95.0 %, respectively. Conclusion The resistance rate of LFX was higher than that of MFX among various drug resistance patterns in RR-TB isolates. The gyrA Asp94Gly was the predominant mutation type underlying FQs resistance. However, no significant difference was observed between mutation patterns in gyrA gene and resistance level of FQs.
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Affiliation(s)
- Chong Teng
- Department of Tuberculosis, Beijing Dongcheng District Center for Disease Control and Prevention, Beijing, 100050, China
- 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, Beijing, 102206, China
- Chinese Field Epidemiology Training Program, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Ling Li
- Department of Clinical Laboratory, Ya'an People's Hospital, Sichuan, 625000, China
| | - Dan Su
- Department of Pathology, Capital Medical University Affiliated Beijing Chest Hospital, Beijing, 101149, China
| | - Hui Li
- Department of Tuberculosis, Beijing Dongcheng District Center for Disease Control and Prevention, Beijing, 100050, 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, Beijing, 102206, China
| | - Hui Xia
- 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, Beijing, 102206, China
| | - Hui Teng
- Centre of Health Management, Hunan Prevention and Treatment Institute for Occupational Diseases, Hunan, 410007, China
| | - Yuanyuan 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, Beijing, 102206, China
| | - Yang Zheng
- 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, Beijing, 102206, 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, Beijing, 102206, China
| | - Huiwen Zheng
- Laboratory of Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, National Center for Children's Health, Beijing, 100045, 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, Beijing, 102206, China
| | - Xichao Ou
- 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, Beijing, 102206, China
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Zhao B, Zheng H, Timm J, Song Z, Pei S, Xing R, Guo Y, Ma L, Li F, Li Q, Li Y, Huang L, Teng C, Wang N, Gupta A, Juneja S, Huang F, Zhao Y, Ou X. Prevalence and genetic basis of Mycobacterium tuberculosis resistance to pretomanid in China. Ann Clin Microbiol Antimicrob 2024; 23:40. [PMID: 38702782 PMCID: PMC11069242 DOI: 10.1186/s12941-024-00697-0] [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: 10/16/2023] [Accepted: 04/20/2024] [Indexed: 05/06/2024] Open
Abstract
BACKGROUND Pretomanid is a key component of new regimens for the treatment of drug-resistant tuberculosis (TB) which are being rolled out globally. However, there is limited information on the prevalence of pre-existing resistance to the drug. METHODS To investigate pretomanid resistance rates in China and its underlying genetic basis, as well as to generate additional minimum inhibitory concentration (MIC) data for epidemiological cutoff (ECOFF)/breakpoint setting, we performed MIC determinations in the Mycobacterial Growth Indicator Tube™ (MGIT) system, followed by WGS analysis, on 475 Mycobacterium tuberculosis (MTB) isolated from Chinese TB patients between 2013 and 2020. RESULTS We observed a pretomanid MIC distribution with a 99% ECOFF equal to 0.5 mg/L. Of the 15 isolates with MIC values > 0.5 mg/L, one (MIC = 1 mg/L) was identified as MTB lineage 1 (L1), a genotype previously reported to be intrinsically less susceptible to pretomanid, two were borderline resistant (MIC = 2-4 mg/L) and the remaining 12 isolates were highly resistant (MIC ≥ 16 mg/L) to the drug. Five resistant isolates did not harbor mutations in the known pretomanid resistant genes. CONCLUSIONS Our results further support a breakpoint of 0.5 mg/L for a non-L1 MTB population, which is characteristic of China. Further, our data point to an unexpected high (14/475, 3%) pre-existing pretomanid resistance rate in the country, as well as to the existence of yet-to-be-discovered pretomanid resistance genes.
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Affiliation(s)
- 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, Beijing, 102206, China
| | - Huiwen Zheng
- Laboratory of Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Children's Hospital, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, Beijing Pediatric Research Institute, Capital Medical University, National Center for Children's Health, Beijing, 100045, China
| | | | - 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, Beijing, 102206, China
| | - Shaojun Pei
- School of Public Health, Peking University, Beijing, 100191, China
| | - Ruida Xing
- 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, Beijing, 102206, China
| | - Yajie Guo
- Laboratory of Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Children's Hospital, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, Beijing Pediatric Research Institute, Capital Medical University, National Center for Children's Health, Beijing, 100045, China
| | - Ling Ma
- Institute of Tuberculosis Prevention and Control, Gansu Provincial Center for Disease Control and Prevention, Lanzhou, 730020, China
| | - Feina Li
- Laboratory of Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Children's Hospital, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, Beijing Pediatric Research Institute, Capital Medical University, National Center for Children's Health, Beijing, 100045, China
| | - Qing Li
- Institute of Tuberculosis Prevention and Control, Gansu Provincial Center for Disease Control and Prevention, Lanzhou, 730020, China
| | - Yan Li
- Department of Tuberculosis Control, Chengde Center of Disease Prevention and Control, Chengde, 067000, China
| | - Lin Huang
- Department of Tuberculosis Control, Chengde Center of Disease Prevention and Control, Chengde, 067000, China
| | - Chong Teng
- 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, Beijing, 102206, China
| | - Ni 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, Beijing, 102206, China
| | | | | | - Fei Huang
- 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, Beijing, 102206, 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, Beijing, 102206, China.
| | - Xichao Ou
- 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, Beijing, 102206, China.
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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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Wang Z, Tang Z, Heidari H, Molaeipour L, Ghanavati R, Kazemian H, Koohsar F, Kouhsari E. Global status of phenotypic pyrazinamide resistance in Mycobacterium tuberculosis clinical isolates: an updated systematic review and meta-analysis. J Chemother 2023; 35:583-595. [PMID: 37211822 DOI: 10.1080/1120009x.2023.2214473] [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: 01/19/2023] [Revised: 05/01/2023] [Accepted: 05/11/2023] [Indexed: 05/23/2023]
Abstract
Pyrazinamide (PZA) is an essential first-line tuberculosis drug for its unique mechanism of action active against multidrug-resistant-TB (MDR-TB). Thus, the aim of updated meta-analysis was to estimate the PZA weighted pooled resistance (WPR) rate in M. tuberculosis isolates based on publication date and WHO regions. We systematically searched the related reports in PubMed, Scopus, and Embase (from January 2015 to July 2022). Statistical analyses were performed using STATA software. The 115 final reports in the analysis investigated phenotypic PZA resistance data. The WPR of PZA was 57% (95% CI 48-65%) in MDR-TB cases. According to the WHO regions, the higher WPRs of PZA were reported in the Western Pacific (32%; 95% CI 18-46%), South East Asian region (37%; 95% CI 31-43%), and the Eastern Mediterranean (78%; 95% CI 54-95%) among any-TB patients, high risk of MDR-TB patients, and MDR-TB patients, respectively. A negligible increase in the rate of PZA resistance were showed in MDR-TB cases (55% to 58%). The rate of PZA resistance has been rising in recent years among MDR-TB cases, underlines the essential for both standard and novel drug regimens development.
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Affiliation(s)
- Zheming Wang
- Department of Pharmacy, Shaoxing People's Hospital, Shaoxing, China
| | - Zhihua Tang
- Department of Pharmacy, Shaoxing People's Hospital, Shaoxing, China
| | - Hamid Heidari
- Department of Microbiology, Faculty of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Leila Molaeipour
- Department of Epidemiology, School of Public Health, University of Medical Sciences, Tehran, Iran
| | | | - Hossein Kazemian
- Clinical Microbiology Research Center, Ilam University of Medical Sciences, Ilam, Iran
| | - Faramarz Koohsar
- Laboratory Sciences Research Center, Golestan University of Medical Sciences, Gorgan, Iran
| | - Ebrahim Kouhsari
- Laboratory Sciences Research Center, Golestan University of Medical Sciences, Gorgan, Iran
- Department of Laboratory Sciences, Faculty of Paramedicine, Golestan University of Medical Sciences, Gorgan, Iran
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7
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Song Z, Liu C, He W, Pei S, Liu D, Cao X, Wang Y, He P, Zhao B, Ou X, Xia H, Wang S, Zhao Y. Insight into the drug-resistant characteristics and genetic diversity of multidrug-resistant Mycobacterium tuberculosis in China. Microbiol Spectr 2023; 11:e0132423. [PMID: 37732780 PMCID: PMC10581218 DOI: 10.1128/spectrum.01324-23] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 07/16/2023] [Indexed: 09/22/2023] Open
Abstract
Multidrug-resistant tuberculosis (MDR-TB) has a severe impact on public health. To investigate the drug-resistant profile, compensatory mutations and genetic variations among MDR-TB isolates, a total of 546 MDR-TB isolates from China underwent drug-susceptibility testing and whole genome sequencing for further analysis. The results showed that our isolates have a high rate of fluoroquinolone resistance (45.60%, 249/546) and a low proportion of conferring resistance to bedaquiline, clofazimine, linezolid, and delamanid. The majority of MDR-TB isolates (77.66%, 424/546) belong to Lineage 2.2.1, followed by Lineage 4.5 (6.41%, 35/546), and the Lineage 2 isolates have a strong association with pre-XDR/XDR-TB (P < 0.05) in our study. Epidemic success analysis using time-scaled haplotypic density (THD) showed that clustered isolates outperformed non-clustered isolates. Compensatory mutations happened in rpoA, rpoC, and non-RRDR of rpoB genes, which were found more frequently in clusters and were associated with the increase of THD index, suggesting that increased bacterial fitness was associated with MDR-TB transmission. In addition, the variants in resistance associated genes in MDR isolates are mainly focused on single nucleotide polymorphism mutations, and only a few genes have indel variants, such as katG, ethA. We also found some genes underwent indel variation correlated with the lineage and sub-lineage of isolates, suggesting the selective evolution of different lineage isolates. Thus, this analysis of the characterization and genetic diversity of MDR isolates would be helpful in developing effective strategies for treatment regimens and tailoring public interventions. IMPORTANCE Multidrug-resistant tuberculosis (MDR-TB) is a serious obstacle to tuberculosis prevention and control in China. This study provides insight into the drug-resistant characteristics of MDR combined with phenotypic drug-susceptibility testing and whole genome sequencing. The compensatory mutations and epidemic success analysis were analyzed by time-scaled haplotypic density (THD) method, suggesting clustered isolates and compensatory mutations are associated with MDR-TB transmission. In addition, the insertion and deletion variants happened in some genes, which are associated with the lineage and sub-lineage of isolates, such as the mpt64 gene. This study offered a valuable reference and increased understanding of MDR-TB in China, which could be crucial for achieving the objective of precision medicine in the prevention and treatment of MDR-TB.
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Affiliation(s)
- Zexuan Song
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Chunfa Liu
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wencong He
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shaojun Pei
- School of Public Health, Peking University, Beijing, China
| | - Dongxin Liu
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaolong Cao
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yiting Wang
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ping He
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Bing Zhao
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xichao Ou
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hui Xia
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shengfen Wang
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yanlin Zhao
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
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Wang J, Yu C, Xu Y, Chen Z, Qiu W, Chen S, Pei H, Zhong Y. Analysis of Drug-Resistance Characteristics and Genetic Diversity of Multidrug-Resistant Tuberculosis Based on Whole-Genome Sequencing on the Hainan Island, China. Infect Drug Resist 2023; 16:5783-5798. [PMID: 37692467 PMCID: PMC10487742 DOI: 10.2147/idr.s423955] [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: 06/22/2023] [Accepted: 08/22/2023] [Indexed: 09/12/2023] Open
Abstract
Purpose Given the high burden of Tuberculosis (TB) in China, the prevalence of multidrug-resistant tuberculosis (MDR-TB) is significant. Whole-genome sequencing (WGS) of Mycobacterium tuberculosis (MTB) enables the identification of lineages, drug-resistant mutations, and transmission patterns, offering valuable insights for TB control, clinical diagnosis, and treatment. Methods We collected 202 MDR-MTB strains from 3519 suspected pulmonary TB patients treated at The Second Affiliated Hospital of Hainan Medical University between July 2019 and June 2021. Proportional drug-susceptibility testing was performed using 8 common anti-tuberculosis drugs. Subsequently, the genotypic drug resistance and genetic characteristics were analyzed by the WGS. Results Lineages are identified by TB-profiler revealed 202 MDR-MTB strains, showcasing three predominant lineages, with lineage 2 being the most prevalent. Close genomic relatedness analysis and evidence of MTB transmission led to the formation of 15 clusters comprising 42 isolates, resulting in a clustering rate of 20.8%. Novelty, lineage 2.1 (non-Beijing) accounted for 27.2% of the MDR-MTB strains, which is rare in China and Neighboring countries. Regarding first-line anti-TB drugs, genes associated with rifampicin resistance, primarily the rpoB gene, were detected in 200 strains (99.0%). Genes conferring resistance to isoniazid, ethambutol, and streptomycin were identified in 191 (94.5%), 125 (61.9%), and 100 (49.5%) strains, respectively. Among the second-line drugs, 97 (48.0%) strains exhibited genes encoding resistance to fluoroquinolones. Comparing the results to phenotypic drug susceptibility-based testing, the sensitivity of WGS for detecting resistance to each of the six drugs (rifampicin, isoniazid, ethambutol, ofloxacin, kanamycin, capreomycin) was 90% or higher. With the exception of ethambutol, the specificity of WGS prediction for the remaining drugs exceeded 88%. Conclusion Our study provides crucial insights into genetic mutation types, genetic diversity, and transmission of MDR-MTB on Hainan Island, serving as a significant reference for MDR-MTB surveillance and clinical decision-making.
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Affiliation(s)
- Jieying Wang
- Department of Clinical Laboratory, The Second Affiliated Hospital of Hainan Medical University, Haikou, 570216, People’s Republic of China
| | - Chunchun Yu
- Department of Clinical Laboratory, The Second Affiliated Hospital of Hainan Medical University, Haikou, 570216, People’s Republic of China
| | - Yuni Xu
- Department of Clinical Laboratory, The Second Affiliated Hospital of Hainan Medical University, Haikou, 570216, People’s Republic of China
| | - Zhuolin Chen
- Department of Clinical Laboratory, The Second Affiliated Hospital of Hainan Medical University, Haikou, 570216, People’s Republic of China
| | - Wenhua Qiu
- Department of Clinical Laboratory, The Second Affiliated Hospital of Hainan Medical University, Haikou, 570216, People’s Republic of China
| | - Shaowen Chen
- Department of Clinical Laboratory, The Second Affiliated Hospital of Hainan Medical University, Haikou, 570216, People’s Republic of China
| | - Hua Pei
- Department of Clinical Laboratory, The Second Affiliated Hospital of Hainan Medical University, Haikou, 570216, People’s Republic of China
| | - Yeteng Zhong
- Department of Clinical Laboratory, The Second Affiliated Hospital of Hainan Medical University, Haikou, 570216, People’s Republic of China
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Liang D, Song Z, Liang X, Qin H, Huang L, Ye J, Lan R, Luo D, Zhao Y, Lin M. Whole Genomic Analysis Revealed High Genetic Diversity and Drug-Resistant Characteristics of Mycobacterium tuberculosis in Guangxi, China. Infect Drug Resist 2023; 16:5021-5031. [PMID: 37554542 PMCID: PMC10405913 DOI: 10.2147/idr.s410828] [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: 03/27/2023] [Accepted: 06/21/2023] [Indexed: 08/10/2023] Open
Abstract
Background Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a major public health issue in China. Nevertheless, the prevalence and drug resistance characteristics of isolates vary in different regions and provinces. In this study, we investigated the population structure, transmission dynamics and drug-resistant profiles of Mtb in Guangxi, located on the border of China. Methods From February 2016 to April 2017, 462 clinical M. tuberculosis isolates were selected from 5 locations in Guangxi. Drug-susceptibility testing was performed using 6 common anti-tuberculosis drugs. The genotypic drug resistance and transmission dynamics were analyzed by the whole genome sequence. Results Our data showed that the Mtb in Guangxi has high genetic diversity including Lineage 1 to Lineage 4, and mostly belong to Lineage 2 and Lineage 4. Novelty, 9.6% of Lineage 2 isolates were proto-Beijing genotype (L2.1), which is rare in China. About 12.6% of isolates were phylogenetically clustered and formed into 28 transmission clusters. We observed that the isolates with the high resistant rate of isoniazid (INH, 21.2%), followed by rifampicin (RIF, 13.2%), and 6.7%, 12.1%, 6.7% and 1.9% isolates were resistant to ethambutol (EMB), streptomycin (SM), ofloxacin (OFL) and kanamycin (KAN), respectively. Among these, 6.5% and 3.3% of isolates belong to MDR-TB and Pre-XDR, respectively, with a high drug-resistant burden. Genetic analysis identified the most frequently encountered mutations of INH, RIF, EMB, SM, OFL and KAN were katG_Ser315Thr (62.2%), rpoB_Ser450Leu (42.6%), embB_Met306Vol (45.2%), rpsL_Lys43Arg (53.6%), gyrA_Asp94Gly (29.0%) and rrs_A1401G (66.7%), respectively. Additionally, we discovered that isolates from border cities are more likely to be drug-resistant than isolates from non-border cities. Conclusion Our findings provide a deep analysis of the genomic population characteristics and drug-resistant of M. tuberculosis in Guangxi, which could contribute to developing effective TB prevention and control strategies.
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Affiliation(s)
- Dabin Liang
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi, People’s Republic of China
| | - Zexuan Song
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Xiaoyan Liang
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi, People’s Republic of China
| | - Huifang Qin
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi, People’s Republic of China
| | - Liwen Huang
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi, People’s Republic of China
| | - Jing Ye
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi, People’s Republic of China
| | - Rushu Lan
- Department of Clinical Laboratory, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, People’s Republic of China
| | - Dan Luo
- School of Public Health and Management, Guangxi University of Chinese Medicine, Nanning, Guangxi, People’s Republic of China
| | - Yanlin Zhao
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Mei Lin
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi, People’s Republic of China
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Cao B, Mijiti X, Deng LL, Wang Q, Yu JJ, Anwaierjiang A, Qian C, Li M, Fang DA, Jiang Y, Zhao LL, Zhao X, Wan K, Liu H, Li G, Yuan X. Genetic Characterization Conferred Co-Resistance to Isoniazid and Ethionamide in Mycobacterium tuberculosis Isolates from Southern Xinjiang, China. Infect Drug Resist 2023; 16:3117-3135. [PMID: 37228658 PMCID: PMC10204763 DOI: 10.2147/idr.s407525] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 05/02/2023] [Indexed: 05/27/2023] Open
Abstract
Background Ethionamide (ETH), a structural analogue of isoniazid (INH), is used for treating multidrug-resistant tuberculosis (MDR-TB). Due to the common target InhA, INH and ETH showed cross-resistance in M. tuberculosis. This study aimed to explore the INH and ETH resistant profiles and genetic mutations conferring independent INH- or ETH-resistance and INH-ETH cross-resistance in M. tuberculosis circulating in south of Xinjiang, China. Methods From Sep 2017 to Dec 2018, 312 isolates were included using drug susceptibility testing (DST), spoligotyping, and whole genome sequencing (WGS) to analyze the resistance characteristics for INH and/or ETH. Results Among the 312 isolates, 185 (58.3%) and 127 (40.7%) belonged to the Beijing family and non-Beijing family, respectively; 90 (28.9%) were INH-resistant (INHR) with mutation rates of 74.4% in katG, 13.3% in inhA and its promoter, 11.1% in ahpC and its upstream region, 2.2% in ndh, 0.0% in mshA, whilst 34 (10.9%) were ETH-resistant (ETHR) with mutation rates of 38.2% in ethA, 26.2% in inhA and its promoter, and 5.9% in ndh, 0.0% in ethR or mshA; and 25 (8.0%) were INH-ETH co-resistant (INHRETHR) with mutation rates of 40.0% in inhA and its promoter, and 8% in ndh. katG mutants tended to display high-level resistant to INH; and more inhA and its promoter mutants showed low-level of INH and ETH resistance. The optimal gene combinations by WGS for the prediction of INHR, ETHR, and INHRETHR were, respectively, katG+inhA and its promoter (sensitivity: 81.11%, specificity: 90.54%), ethA+inhA and its promoter+ndh (sensitivity: 61.76%, specificity: 76.62%), and inhA and its promoter+ndh (sensitivity: 48.00%, specificity: 97.65%). Conclusion This study revealed the high diversity of genetic mutations conferring INH and/or ETH resistance among M. tuberculosis isolates, which would facilitate the study on INHR and/or ETHR mechanisms and provide clues for choosing ETH for MDR treatment and molecular DST methods in south of Xinjiang, China.
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Affiliation(s)
- Bin Cao
- School of Public Health, University of South China, Hengyang, 421001, People’s Republic of China
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Xiaokaiti Mijiti
- The Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, 830000, People’s Republic of China
| | - Le-Le Deng
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Quan Wang
- The Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, 830000, People’s Republic of China
| | - Jin-Jie Yu
- School of Public Health, University of South China, Hengyang, 421001, People’s Republic of China
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | | | - Chengyu Qian
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
- Wenzhou Key Laboratory of Sanitary Microbiology, Key Laboratory of Laboratory Medicine, Ministry of Education, China, School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, 325035, People’s Republic of China
| | - Machao Li
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Dan-Ang Fang
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
- Wenzhou Key Laboratory of Sanitary Microbiology, Key Laboratory of Laboratory Medicine, Ministry of Education, China, School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, 325035, People’s Republic of China
| | - Yi Jiang
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Li-Li Zhao
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Xiuqin Zhao
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Kanglin Wan
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Haican Liu
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Guilian Li
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Xiuqin Yuan
- School of Public Health, University of South China, Hengyang, 421001, People’s Republic of China
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Ji L, Tao FX, Yu YF, Liu JH, Yu FH, Bai CL, Wan ZY, Yang XB, Ma J, Zhou P, Niu Z, Zhou P, Xiang H, Chen M, Xiang Z, Zhang FQ, Jiang Q, Liu XJ. Whole-genome sequencing to characterize the genetic structure and transmission risk of Mycobacterium tuberculosis in Yichang city of China. Front Public Health 2023; 10:1047965. [PMID: 36699912 PMCID: PMC9868839 DOI: 10.3389/fpubh.2022.1047965] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 12/19/2022] [Indexed: 01/11/2023] Open
Abstract
Objective The burden of both general and drug-resistant tuberculosis in rural areas is higher than that in urban areas in China. To characterize the genetic structure and transmission risk of Mycobacterium tuberculosis in rural China, we used whole genome sequencing to analyze clinical strains collected from patients in two counties of Yichang for three consecutive years. Methods From 2018 to 2020, sputum samples were collected for cultures from patients with suspected tuberculosis in Yidu and Zigui county, and DNA was extracted from the positive strains for genome sequencing. The online SAM-TB platform was used to identify the genotypes and drug resistance-related mutations of each strain, establish a phylogenetic tree, and calculated the genetic distances between pairwise strains. Twelve single nucleotide polymorphisms (SNPs) were used as thresholds to identify transmission clusters. The risk of related factors was estimated by univariable and multivariable logistic regression. Results A total of 161 out of the collected 231 positive strains were enrolled for analysis, excluding non-tuberculous mycobacterium and duplicate strains from the same patient. These strains belonged to Lineage 2 (92, 57.1%) and Lineage 4 (69, 42.9%), respectively. A total of 49 (30.4%) strains were detected with known drug resistance-related mutations, including 6 (3.7%) multidrug-resistant-TB (MDR-TB) strains and 11 (6.8%) RIF-resistant INH-susceptible TB (Rr-TB) strains. Six of the MDR/Rr-TB (35.3%) were also resistant to fluoroquinolones, which made them pre-extensively drug-resistant TB (pre-XDR-TB). There were another seven strains with mono-resistance to fluoroquinolones and one strain with resistance to both INH and fluoroquinolones, making the overall rate of fluoroquinolones resistance 8.7% (14/161). A total of 50 strains (31.1%) were identified as transmission clusters. Patients under 45 years old (adjusted odds ratio 3.46 [95% confidential intervals 1.28-9.35]), treatment-naive patients (6.14 [1.39-27.07]) and patients infected by lineage 4 strains (2.22 [1.00-4.91]) had a higher risk of transmission. Conclusion The drug resistance of tuberculosis in rural China, especially to the second-line drug fluoroquinolones, is relatively serious. The standardized treatment for patients and the clinical use of fluoroquinolones warrant attention. At the same time, the recent transmission risk of tuberculosis is high, and rapid diagnosis and treatment management at the primary care needs to be strengthened.
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Affiliation(s)
- Lv Ji
- Institute of Public Health Inspection, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Feng-Xi Tao
- School of Public Health, Wuhan University, Wuhan, Hubei, China
| | - Yun-Fang Yu
- Institute of Public Health Inspection, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Jian-Hua Liu
- Institute of Infectious Disease Prevention and Control, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Feng-Hua Yu
- Institute of Public Health Inspection, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Chun-Lin Bai
- Institute of Public Health Inspection, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Zheng-Yang Wan
- Institute of Public Health Inspection, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Xiao-Bo Yang
- Institute of Public Health Inspection, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Jing Ma
- Institute of Public Health Inspection, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Pan Zhou
- Institute of Public Health Inspection, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Zhao Niu
- Institute of Public Health Inspection, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Ping Zhou
- Institute of Infectious Disease Prevention and Control, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China
| | - Hong Xiang
- Institute of Infectious Disease Prevention and Control, Yidu Center for Disease Control and Prevention, Yidu, Hubei, China
| | - Ming Chen
- Clinical Laboratory, Yidu First People's Hospital, Yidu, Hubei, China
| | - Zhou Xiang
- Institute of Infectious Disease Prevention and Control, Zigui Center for Disease Control and Prevention, Zigui, Hubei, China
| | - Fang-Qiong Zhang
- Clinical Laboratory, Zigui County People's Hospital, Zigui, Hubei, China
| | - Qi Jiang
- School of Public Health, Wuhan University, Wuhan, Hubei, China,*Correspondence: Qi Jiang ✉
| | - Xiao-Jun Liu
- Institute of Public Health Inspection, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China,Institute of Infectious Disease Prevention and Control, Yichang Center for Disease Control and Prevention, Yichang, Hubei, China,Xiao-Jun Liu ✉
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12
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He W, Tan Y, Song Z, Liu B, Wang Y, He P, Xia H, Huang F, Liu C, Zheng H, Pei S, Liu D, Ma A, Cao X, Zhao B, Ou X, Wang S, Zhao Y. Endogenous relapse and exogenous reinfection in recurrent pulmonary tuberculosis: A retrospective study revealed by whole genome sequencing. Front Microbiol 2023; 14:1115295. [PMID: 36876077 PMCID: PMC9981662 DOI: 10.3389/fmicb.2023.1115295] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 02/02/2023] [Indexed: 02/19/2023] Open
Abstract
Background Tuberculosis may reoccur due to reinfection or relapse after initially successful treatment. Distinguishing the cause of TB recurrence is crucial to guide TB control and treatment. This study aimed to investigate the source of TB recurrence and risk factors related to relapse in Hunan province, a high TB burden region in southern China. Methods A population-based retrospective study was conducted on all culture-positive TB cases in Hunan province, China from 2013 to 2020. Phenotypic drug susceptibility testing and whole-genome sequencing were used to detect drug resistance and distinguish between relapse and reinfection. Pearson chi-square test and Fisher exact test were applied to compare differences in categorical variables between relapse and reinfection. The Kaplan-Meier curve was generated in R studio (4.0.4) to describe and compare the time to recurrence between different groups. p < 0.05 was considered statistically significant. Results Of 36 recurrent events, 27 (75.0%, 27/36) paired isolates were caused by relapse, and reinfection accounted for 25.0% (9/36) of recurrent cases. No significant difference in characteristics was observed between relapse and reinfection (all p > 0.05). In addition, TB relapse occurs earlier in patients of Tu ethnicity compared to patients of Han ethnicity (p < 0.0001), whereas no significant differences in the time interval to relapse were noted in other groups. Moreover, 83.3% (30/36) of TB recurrence occurred within 3 years. Overall, these recurrent TB isolates were predominantly pan-susceptible strains (71.0%, 49/69), followed by DR-TB (17.4%, 12/69) and MDR-TB (11.6%, 8/69), with mutations mainly in codon 450 of the rpoB gene and codon 315 of the katG gene. 11.1% (3/27) of relapse cases had acquired new resistance during treatment, with fluoroquinolone resistance occurring most frequently (7.4%, 2/27), both with mutations in codon 94 of gyrA. Conclusion Endogenous relapse is the main mechanism leading to TB recurrences in Hunan province. Given that TB recurrences can occur more than 4 years after treatment completion, it is necessary to extend the post-treatment follow-up period to achieve better management of TB patients. Moreover, the relatively high frequency of fluoroquinolone resistance in the second episode of relapse suggests that fluoroquinolones should be used with caution when treating TB cases with relapse, preferably guided by DST results.
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Affiliation(s)
- Wencong He
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yunhong Tan
- Hunan Provincial Chest Hospital, Tuberculosis Control Institution of Hunan Province, Changsha, Hunan, China
| | - Zexuan Song
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Binbin Liu
- Hunan Provincial Chest Hospital, Tuberculosis Control Institution of Hunan Province, Changsha, Hunan, China
| | - Yiting Wang
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ping He
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hui Xia
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Fei Huang
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Chunfa Liu
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Huiwen Zheng
- Laboratory of Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Shaojun Pei
- School of Public Health, Peking University, Beijing, China
| | - Dongxin Liu
- Shenzhen Third People's Hospital, Shenzhen, China
| | - Aijing Ma
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaolong Cao
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Bing Zhao
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xichao Ou
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shengfen Wang
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yanlin Zhao
- National Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing, China
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Yin C, Mijiti X, Liu H, Wang Q, Cao B, Anwaierjiang A, Li M, Liu M, Jiang Y, Xu M, Wan K, Zhao X, Li G, Xiao H. Molecular Epidemiology of Clinical Mycobacterium tuberculosis Isolates from Southern Xinjiang, China Using Spoligotyping and 15-Locus MIRU-VNTR Typing. Infect Drug Resist 2023; 16:1313-1326. [PMID: 36919034 PMCID: PMC10008323 DOI: 10.2147/idr.s393192] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 02/21/2023] [Indexed: 03/11/2023] Open
Abstract
Background In the last decades, the molecular epidemiological investigation of Mycobacterium tuberculosis has significantly increased our understanding of tuberculosis epidemiology. However, few such studies have been done in southern Xinjiang, China. We aimed to clarify the molecular epidemic characteristics and their association with drug resistance in the M. tuberculosis isolates circulating in this area. Methods A total of 347 isolates obtained from southern Xinjiang, China between Sep, 2017 and Sep, 2019 were included to characterize using a 15-locus MIRU-VNTR (VNTR-15China) typing and spoligotyping, and test for drug susceptibility profiles. Then the lineages and clustering of the isolates were analyzed, as well as their association with drug resistance. Results Spoligotyping results showed that 60 spoligotype international types (SITs) containing 35 predefined SITs and 25 Orphan or New patterns, and 12 definite genotypes were found, and the top three prevalent genotypes were Beijing genotype (207, 59.7%), followed by CAS1-Delhi (46, 13.6%), and Ural-2 (30, 8.6%). The prevalence of Beijing genotype infection in the younger age group (≤30) was more frequent than the two older groups (30~59 and ≥60 years old, both P values <0.05). The Beijing genotype showed significantly higher prevalence of resistance to isoniazid, rifampicin, ethambutol, multi-drug or at least one drug than the non-Beijing genotype (All P values ≤0.05). The estimated proportion of tuberculosis cases due to transmission was 18.4% according to the cluster rate acquired by VNTR-15China typing, and the Beijing genotype was the risk factor for the clustering (OR 9.15, 95% CI: 4.18-20.05). Conclusion Our data demonstrated that the Beijing genotype is the dominant lineage, associated with drug resistance, and was more likely to infect young people and contributed to tuberculosis transmission in southern Xinjiang, China. These findings will contribute to a better understanding of tuberculosis epidemiology in this area.
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Affiliation(s)
- Chunjie Yin
- School of Public Health, Xinjiang Medical University, Urumqi, People's Republic of China
| | - Xiaokaiti Mijiti
- The Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China
| | - Haican Liu
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Quan Wang
- The Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China
| | - Bin Cao
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.,School of Public Health, University of South China, Hengyang, People's Republic of China
| | | | - Machao Li
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Mengwen Liu
- School of Public Health, Xinjiang Medical University, Urumqi, People's Republic of China
| | - Yi Jiang
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Miao Xu
- The Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China
| | - Kanglin Wan
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Xiuqin Zhao
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Guilian Li
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Hui Xiao
- School of Public Health, Xinjiang Medical University, Urumqi, People's Republic of China
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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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Jantarabenjakul W, Supradish Na Ayudhya P, Suntarattiwong P, Thepnarong N, Rotcheewaphan S, Udomsantisuk N, Moonwong J, Kosulvit P, Tawan M, Sudjaritruk T, Puthanakit T. Temporal trend of drug-resistant tuberculosis among Thai children during 2006-2021. IJID REGIONS 2022; 5:79-85. [PMID: 36238580 PMCID: PMC9550601 DOI: 10.1016/j.ijregi.2022.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/13/2022] [Accepted: 09/14/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND The prevalence of drug-resistant tuberculosis (DR-TB) in adults has stabilized in the past decade. Our study aimed to describe the prevalence of DR-TB in Thai children between 2006 and 2021. MATERIALS AND METHODS Children younger than 15 years old who had culture-confirmed Mycobacterium tuberculosis complex (MTB), positive PCR-MTB, or positive Xpert MTB/RIF were included in this cohort. Drug susceptibility testing (DST) was performed using phenotypic and/or genotypic methods. The prevalence of DR-TB was compared using the chi-square test. RESULTS Among 163 confirmed TB cases (44% as pulmonary TB, 27% as extrapulmonary TB, and 29% with both), the median age (IQR) was 12.2 (7.3-14.2) years. DST was performed in 139 cases (85%), revealing prevalences of all DR-TB, isoniazid-resistant TB (Hr-TB), and rifampicin monoresistant/multidrug-resistant TB (Rr/MDR-TB) of 21.6% (95% CI 14.7-28.4), 10.8% (95% CI 5.6-16.0%), and 2.9% (95% CI 0.1-5.7%), respectively. The DR-TB rates did not differ significantly between 2006-2013, 2014-2018, and 2019-2021 (p > 0.05). Two pre-extensively DR-TB (pre-XDR) cases with fluoroquinolone resistance were detected after 2014. CONCLUSION The prevalence of DR-TB in Thai children was stable. However, one-tenth of DR-TB cases confirmed with DST were Hr-TB, which required adjustment of the treatment regimen. The pre-XDR cases should be closely monitored.
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Affiliation(s)
- Watsamon Jantarabenjakul
- Department of Pediatrics, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
- Center of Excellence for Pediatric Infectious Diseases and Vaccines, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | | | | | - Nattawan Thepnarong
- Center of Excellence for Pediatric Infectious Diseases and Vaccines, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | | | - Nibondh Udomsantisuk
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Juthamanee Moonwong
- Center of Excellence for Pediatric Infectious Diseases and Vaccines, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | | | - Monta Tawan
- Center of Excellence for Pediatric Infectious Diseases and Vaccines, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Tavitiya Sudjaritruk
- Department of Pediatrics, Faculty of Medicine, Chiangmai University, Chiangmai, Thailand
- Clinical and Molecular Epidemiology of Emerging and Re-emerging Infectious Diseases Research Cluster, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Thanyawee Puthanakit
- Department of Pediatrics, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
- Center of Excellence for Pediatric Infectious Diseases and Vaccines, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
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Transmission and Drug Resistance Genotype of Multidrug-Resistant or Rifampicin-Resistant Mycobacterium tuberculosis in Chongqing, China. Microbiol Spectr 2022; 10:e0240521. [PMID: 36214695 PMCID: PMC9604020 DOI: 10.1128/spectrum.02405-21] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Multidrug-resistant or rifampicin-resistant tuberculosis (MDR/RR-TB) is a global barrier for the Stop TB plan. To identify risk factors for treatment outcome and cluster transmission of MDR/RR-TB, whole-genome sequencing (WGS) data of isolates from patients of the Chongqing Tuberculosis Control Institute were used for phylogenetic classifications, resistance predictions, and cluster analysis. A total of 223 MDR/RR-TB cases were recorded between 1 January 2018 and 31 December 2020. Elderly patients and those with lung cavitation are at increased risk of death due to MDR/RR-TB. A total of 187 MDR/RR strains were obtained from WGS data; 152 were classified as lineage 2 strains. Eighty (42.8%) strains differing by a distance of 12 or fewer single nucleotide polymorphisms were classified as 20 genomic clusters, indicating recent transmission. Patients infected with lineage 2 strains or those with occupations listed as "other" are significantly associated with a transmission cluster of MDR/RR-TB. Analysis of resistant mutations against first-line tuberculosis drugs found that 76 (95.0%) of all 80 strains had the same mutations within each cluster. A total of 55.0% (44 of 80) of the MDR/RR-TB strains accumulated additional drug resistance mutations along the transmission chain, especially against fluoroquinolones (63.6% [28 of 44]). Recent transmission of MDR/RR strains is driving the MDR/RR-TB epidemics, leading to the accumulation of more serious resistance along the transmission chains. IMPORTANCE The drug resistance molecular characteristics of MDR/RR-TB were elucidated by genome-wide analysis, and risk factors for death by MDR/RR-TB were identified in combination with patient information. Cluster characteristics of MDR/RR-TB in the region were analyzed by genome-wide analysis, and risk factors for cluster transmission (recent transmission) were analyzed. These analyses provide reference for the prevention and treatment of MDR/RR-TB in Chongqing.
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Xu Z, Liu H, Liu Y, Tang Y, Tan Y, Hu P, Zhang C, Yang C, Wan K, Wang Q. Whole-Genome Sequencing and Epidemiological Investigation of Tuberculosis Outbreaks in High Schools in Hunan, China. Infect Drug Resist 2022; 15:5149-5160. [PMID: 36082241 PMCID: PMC9448353 DOI: 10.2147/idr.s371772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/25/2022] [Indexed: 12/03/2022] Open
Abstract
Background Tuberculosis (TB) seriously threatens individual and public health. Recently, TB outbreaks in schools have been reported more frequently in China and have attracted widespread attention. We reported three TB outbreaks in high schools in Hunan Province, China. Methods When a tuberculosis patient was reported in a school, we carried out field epidemiological investigations, including tuberculin skin testing (TST), chest X-ray (CXR) and laboratory test for all close contacts, and whole-genome sequencing (WGS) analyses to understand the transmission patterns, the causes and the risk factors for the outbreaks, thereby providing a foundation for the control of TB epidemics in schools. Results A total of 49 students with TB patients were identified in the three schools where TB outbreaks occurred, including nine patients in School A, 14 patients in School B, and 26 patients in School C. In Schools A, B and C, the putative attack rates in the classes of the index case were 13.8% (8/58), 7.6% (5/66), and 40.4% (21/52), while the putative attack rates of expanding screening in the school were 0.3% (1/361), 0.2% (9/3955), and 0.2% (5/2080), respectively. Thirteen patients had patient delay, with a median delay interval of 69 days (IQR 30.5–113 days). Twelve patients had a healthcare diagnostic delay with a median delay interval of 32 days (IQR 24–82 days). Phylogenetic analysis of culture-positive patients revealed that most of them shared a small genetic distance (≤12 SNPs), with three separate genetic clusters (including one MDR-TB genomic cluster), indicating the recent transmission of Mycobacterium tuberculosis strains. Conclusion This combination of field investigation and WGS analysis revealed the transmission of three TB outbreaks in schools. Reinforced implementation is needed to improve timely case finding and reduce diagnosis delay in routine TB control in the school population.
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Affiliation(s)
- Zuhui Xu
- Xiangya School of Public Health, Central South University, Changsha, 410078, People’s Republic of China
- Tuberculosis Control Institute of Hunan Province, Changsha, 410013, People’s Republic of China
| | - Haican Liu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Yanping Liu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518000, People’s Republic of China
| | - Yi Tang
- Tuberculosis Control Institute of Hunan Province, Changsha, 410013, People’s Republic of China
| | - Yunhong Tan
- Tuberculosis Control Institute of Hunan Province, Changsha, 410013, People’s Republic of China
| | - Peilei Hu
- Tuberculosis Control Institute of Hunan Province, Changsha, 410013, People’s Republic of China
| | - Chuanfang Zhang
- Tuberculosis Control Institute of Hunan Province, Changsha, 410013, People’s Republic of China
| | - Chongguang Yang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518000, People’s Republic of China
| | - Kanglin Wan
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
- Kanglin Wan, State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 155 of Changbai Road, Changping District, Beijing, 102206, People’s Republic of China, Tel +86 13910065264, Email
| | - Qiaozhi Wang
- Tuberculosis Control Institute of Hunan Province, Changsha, 410013, People’s Republic of China
- Correspondence: Qiaozhi Wang, Department of Institute office, Tuberculosis Control Institute of Hunan Province, No. 519 of Xianjiahu Road, Changsha, 410013, People’s Republic of China, Tel/fax +86073188809748, Email
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Differential Impact of the rpoB Mutant on Rifampin and Rifabutin Resistance Signatures of Mycobacterium tuberculosis Is Revealed Using a Whole-Genome Sequencing Assay. Microbiol Spectr 2022; 10:e0075422. [PMID: 35924839 PMCID: PMC9430608 DOI: 10.1128/spectrum.00754-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
Drug resistance in Mycobacterium tuberculosis (MTB) has long been a serious health issue worldwide. Most drug-resistant MTB isolates were identified due to treatment failure or in clinical examinations 3~6 months postinfection. In this study, we propose a whole-genome sequencing (WGS) pipeline via the Nanopore MinION platform to facilitate the efficacy of phenotypic identification of clinical isolates. We used the Nanopore MinION platform to perform WGS of clinical MTB isolates, including susceptible (n = 30) and rifampin- (RIF) or rifabutin (RFB)-resistant isolates (n = 20) according to results of a susceptibility test. Nonsynonymous variants within the rpoB gene associated with RIF resistance were identified using the WGS analytical pipeline. In total, 131 variants within the rpoB gene in RIF-resistant isolates were identified. The presence of the emergent Asp531Gly or His445Gln was first identified to be associated with the rifampin and rifabutin resistance signatures of clinical isolates. The results of the minimum inhibitory concentration (MIC) test further indicated that the Ser450Leu or the mutant within the rifampin resistance-determining region (RRDR)-associated rifabutin-resistant signature was diminished in the presence of novel mutants, including Phe669Val, Leu206Ile, or Met148Leu, identified in this study. IMPORTANCE Current approaches to diagnose drug-resistant MTB are time-consuming, consequently leading to inefficient intervention or further disease transmission. In this study, we curated lists of coding variants associated with differential rifampin and rifabutin resistant signatures using a single molecule real-time (SMRT) sequencing platform with a shorter hands-on time. Accordingly, the emerging WGS pipeline constitutes a potential platform for efficacious and accurate diagnosis of drug-resistant MTB isolates.
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