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Liu Z, Li X, Xiong H, Zhou Q, Yi H, Wu K, Zhou Z, Lu Y, Zhu Y, Zhou L, Zhang M, Gao J, Gao J, Chen S, Wang X, Wang W. Genomic and spatial analysis reveal the transmission dynamics of tuberculosis in areas with high incidence of Zhejiang, China: A prospective cohort study. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2024; 121:105603. [PMID: 38723983 DOI: 10.1016/j.meegid.2024.105603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 03/28/2024] [Accepted: 05/05/2024] [Indexed: 05/14/2024]
Abstract
In the mountainous, rural regions of eastern China, tuberculosis (TB) remains a formidable challenge; however, the long-term molecular epidemiological surveillance in these regions is limited. This study aimed to investigate molecular and spatial epidemiology of TB in two mountainous, rural counties of Zhejiang Province, China, from 2015 to 2021, to elucidate the recent transmission and drug-resistance profiles. The predominant Lineage 2 (L2) Beijing family accounted for 80.1% of total 532 sequenced Mycobacterium tuberculosis (Mtb) strains, showing consistent prevalence over seven years. Gene mutations associated with drug resistance were identified in 19.4% (103/532) of strains, including 47 rifampicin or isoniazid-resistant strains, eight multi-drug-resistant (MDR) strains, and five pre-extensively drug-resistant (pre-XDR) strains. Genomic clustering revealed 53 distinct clusters with an overall transmission clustering rate of 23.9% (127/532). Patients with a history of retreatment and those infected with L2 strains had a higher risk of recent transmission. Spatial and epidemiological analysis unveiled significant transmission hotspots, especially in densely populated urban areas, involving various public places such as medical institutions, farmlands, markets, and cardrooms. The study emphasizes the pivotal role of Beijing strains and urban-based TB transmission in the western mountainous regions in Zhejiang, highlighting the urgent requirement for specific interventions to mitigate the impact of TB in these unique communities.
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Affiliation(s)
- Zhengwei Liu
- The Institute of TB Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
| | - Xiangchen Li
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, Zhejiang 310020, China
| | - Haiyan Xiong
- School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Qingrong Zhou
- Center for Disease Control and Prevention of Jiangshan City, Zhejiang 324100, China
| | - Huaiming Yi
- Center for Disease Control and Prevention of Changshan County, Zhejiang 324200, China
| | - Kunyang Wu
- The Institute of TB Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
| | - Zonglei Zhou
- School of Public Health, Fudan University, Shanghai 200032, China
| | - Yewei Lu
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, Zhejiang 310020, China
| | - Yelei Zhu
- The Institute of TB Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
| | - Lin Zhou
- The Institute of TB Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
| | - Mingwu Zhang
- The Institute of TB Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
| | - Junshun Gao
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, Zhejiang 310020, China
| | - Junli Gao
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, Zhejiang 310020, China
| | - Songhua Chen
- The Institute of TB Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China.
| | - Xiaomeng Wang
- The Institute of TB Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China.
| | - Weibing Wang
- School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China.
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Deng L, Wang Q, Liu H, Jiang Y, Xu M, Xiang Y, Yang T, Yang S, Yan D, Li M, Zhao L, Zhao X, Wan K, He G, Mijiti X, Li G. Identification of positively selected genes in Mycobacterium tuberculosis from southern Xinjiang Uygur autonomous region of China. Front Microbiol 2024; 15:1290227. [PMID: 38686109 PMCID: PMC11056549 DOI: 10.3389/fmicb.2024.1290227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 03/28/2024] [Indexed: 05/02/2024] Open
Abstract
Background Tuberculosis (TB), mainly caused by Mycobacterium tuberculosis (Mtb), remains a serious public health problem. Increasing evidence supports that selective evolution is an important force affecting genomic determinants of Mtb phenotypes. It is necessary to further understand the Mtb selective evolution and identify the positively selected genes that probably drive the phenotype of Mtb. Methods This study mainly focused on the positive selection of 807 Mtb strains from Southern Xinjiang of China using whole genome sequencing (WGS). PAML software was used for identifying the genes and sites under positive selection in 807 Mtb strains. Results Lineage 2 (62.70%) strains were the dominant strains in this area, followed by lineage 3 (19.45%) and lineage 4 (17.84%) strains. There were 239 codons in 47 genes under positive selection, and the genes were majorly associated with the functions of transcription, defense mechanisms, and cell wall/membrane/envelope biogenesis. There were 28 codons (43 mutations) in eight genes (gyrA, rpoB, rpoC, katG, pncA, embB, gid, and cut1) under positive selection in multi-drug resistance (MDR) strains but not in drug-susceptible (DS) strains, in which 27 mutations were drug-resistant loci, 9 mutations were non-drug-resistant loci but were in drug-resistant genes, 2 mutations were compensatory mutations, and 5 mutations were in unknown drug-resistant gene of cut1. There was a codon in Rv0336 under positive selection in L3 strains but not in L2 and L4 strains. The epitopes of T and B cells were both hyper-conserved, particularly in the T-cell epitopes. Conclusion This study revealed the ongoing selective evolution of Mtb. We found some special genes and sites under positive selection which may contribute to the advantage of MDR and L3 strains. It is necessary to further study these mutations to understand their impact on phenotypes for providing more useful information to develop new TB interventions.
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Affiliation(s)
- Lele Deng
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Quan Wang
- Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Haican Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yi Jiang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Miao Xu
- Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Yu Xiang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, University of South China, Hengyang, China
| | - Ting Yang
- Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Shuliu Yang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, University of South China, Hengyang, China
| | - Di Yan
- Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Machao Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lili Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiuqin Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Kanglin Wan
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Guangxue He
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaokaiti Mijiti
- Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Guilian Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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Shankaregowda R, Allegretti YH, Sumana MN, Rao MR, Raphael E, Mahesh PA, Riley LW. Whole-Genome Sequencing of Mycobacterium tuberculosis Isolates from Diabetic and Non-Diabetic Patients with Pulmonary Tuberculosis. Microorganisms 2023; 11:1881. [PMID: 37630441 PMCID: PMC10457832 DOI: 10.3390/microorganisms11081881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 07/08/2023] [Accepted: 07/14/2023] [Indexed: 08/27/2023] Open
Abstract
The association of tuberculosis and type 2 diabetes mellitus has been a recognized re-emerging challenge in management of the convergence of the two epidemics. Though much of the literature has studied this association, there is less knowledge in the field of genetic diversities that might occur in strains infecting tuberculosis patients with and without diabetes. Our study focused on determining the extent of diversity of genotypes of Mycobacterium tuberculosis in both these categories of patients. We subjected 55 M. tuberculosis isolates from patients diagnosed with pulmonary TB with and without type 2 diabetes mellitus to whole-genome sequencing on Illumina Hi Seq platform. The most common lineage identified was lineage 1, the Indo-Oceanic lineage (n = 22%), followed by lineage 4, the Euro-American lineage (n = 18, 33%); lineage 3, the East-African Indian lineage (n = 13, 24%); and lineage 2, the East-Asian lineage (n = 1, 2%). There were no significant differences in the distribution of lineages in both diabetics and non-diabetics in the South Indian population, and further studies involving computational analysis and comparative transcriptomics are needed to provide deeper insights.
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Affiliation(s)
- Ranjitha Shankaregowda
- School of Public Health, Division of Infectious Diseases and Vaccinology, University of California, Berkeley, CA 94720, USA; (R.S.); (L.W.R.)
- Department of Microbiology, JSS Medical College and Hospital, JSS AHER, Mysore 570015, India; (M.N.S.); (M.R.R.)
| | - Yuan Hu Allegretti
- School of Public Health, Division of Epidemiology, University of California, Berkeley, CA 94720, USA;
| | | | - Morubagal Raghavendra Rao
- Department of Microbiology, JSS Medical College and Hospital, JSS AHER, Mysore 570015, India; (M.N.S.); (M.R.R.)
| | - Eva Raphael
- Division of Epidemiology and Biostatistics, School of Medicine, University of California, San Fransico, CA 94143, USA;
| | - Padukudru Anand Mahesh
- Department of Respiratory Medicine, JSS Medical College and Hospital, JSS AHER, Mysore 570015, India
| | - Lee W. Riley
- School of Public Health, Division of Infectious Diseases and Vaccinology, University of California, Berkeley, CA 94720, USA; (R.S.); (L.W.R.)
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Zhou Z, Yi H, Zhou Q, Wang L, Zhu Y, Wang W, Liu Z, Xiong H. Evolution and epidemic success of Mycobacterium tuberculosis in eastern China: evidence from a prospective study. BMC Genomics 2023; 24:241. [PMID: 37147590 PMCID: PMC10161668 DOI: 10.1186/s12864-023-09312-6] [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: 01/10/2023] [Accepted: 04/14/2023] [Indexed: 05/07/2023] Open
Abstract
BACKGROUND Lineage distribution of Mycobacterium tuberculosis (Mtb) isolates is strongly associated with geographically distinct human populations, and its transmission can be further impacted by the bacterial genome. However, the epidemic success of Mtb isolates at an individual level was unknown in eastern China. Knowledge regarding the emergence and transmission of Mtb isolates as well as relevant factors may offer a new solution to curb the spread of the disease. Thus, this study aims to reveal the evolution and epidemic success of Mtb isolates in eastern China. RESULTS Of initial 1040 isolates, 997 were retained after removing duplicates and those with insufficient sequencing depth. Of the final samples, 733 (73.52%) were from Zhejiang Province, and 264 (26.48%) were from Shanghai City. Lineage 2 and lineage 4 accounted for 80.44% and 19.56%, with common ancestors dating around 7017 years ago and 6882 years ago, respectively. Sub-lineage L2.2 (80.34%) contributed the majority of total isolates, followed by L4.4 (8.93%) and L4.5 (8.43%). Additionally, 51 (5.12%) isolates were identified to be multidrug-resistant (MDR), of which 21 (29.17%) were pre-extensively drug-resistant (pre-XDR). One clade harboring katG S315T mutation may date back to 65 years ago and subsequently acquired mutations conferring resistance to another five antibiotic drugs. The prevalence of compensatory mutation was the highest in pre-XDR isolates (76.19%), followed by MDR isolates (47.06%) and other drug-resistant isolates (20.60%). Time-scaled haplotypic density analyses suggested comparable success indices between lineage 2 and lineage 4 (P = 0.306), and drug resistance did not significantly promote the transmission of Mtb isolates (P = 0.340). But for pre-XDR isolates, we found a higher success index in those with compensatory mutations (P = 0.025). Mutations under positive selection were found in genes associated with resistance to second-line injectables (whiB6) and drug tolerance (prpR) in both lineage 2 and lineage 4. CONCLUSIONS Our study demonstrates the population expansion of lineage 2 and lineage 4 in eastern China, with comparable transmission capacity, while accumulation of resistance mutations does not necessarily facilitate the success of Mtb isolates. Compensatory mutations usually accompany drug resistance and significantly contribute to the epidemiological transmission of pre-XDR strains. Prospective molecular surveillance is required to further monitor the emergence and spread of pre-XDR/XDR strains in eastern China.
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Affiliation(s)
- Zonglei Zhou
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Huaiming Yi
- Center for Disease Control and Prevention of Changshan County, 324200, Zhejiang, China
| | - Qingrong Zhou
- Center for Disease Control and Prevention of Jiangshan City, 324100, Zhejiang, China
| | - Luqi Wang
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Yue Zhu
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Weibing Wang
- School of Public Health, Fudan University, Shanghai, 200032, China.
- Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, 200032, China.
| | - Zhengwe Liu
- Institute of Tuberculosis Control, Zhejiang Provincial Center for Disease Control and Prevention, 310051, Zhejiang, China.
| | - Haiyan Xiong
- School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, 200032, China
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Wu B, Zhu W, Wang Y, Wang Q, Zhou L, Liu Z, Bi L, Barun M, Kreiswirth BN, Chen L, Chen S, Wang X, Wang W. Correction to: Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations. Cell Biosci 2021; 11:184. [PMID: 34674759 PMCID: PMC8532268 DOI: 10.1186/s13578-021-00692-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/24/2021] [Indexed: 11/10/2022] Open
Affiliation(s)
- Beibei Wu
- Zhejiang Center for Disease Control and Prevention, Institute of Tuberculosis Control, 3399 Binsheng Road, Binjiang District, Hangzhou, 310051, Zhejiang, China
| | - Wenlong Zhu
- Department of Epidemiology, School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China
| | - Yue Wang
- Department of Epidemiology, School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China
| | - Qi Wang
- Department of Epidemiology, School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China
| | - Lin Zhou
- Zhejiang Center for Disease Control and Prevention, Institute of Tuberculosis Control, 3399 Binsheng Road, Binjiang District, Hangzhou, 310051, Zhejiang, China
| | - Zhengwei Liu
- Zhejiang Center for Disease Control and Prevention, Institute of Tuberculosis Control, 3399 Binsheng Road, Binjiang District, Hangzhou, 310051, Zhejiang, China
| | - Lijun Bi
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Mathema Barun
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA
| | - Barry N Kreiswirth
- Hackensack-Meridian Health Center for Discovery and Innovation, Nutley, NJ, 07110, USA
| | - Liang Chen
- Hackensack-Meridian Health Center for Discovery and Innovation, Nutley, NJ, 07110, USA
| | - Songhua Chen
- Zhejiang Center for Disease Control and Prevention, Institute of Tuberculosis Control, 3399 Binsheng Road, Binjiang District, Hangzhou, 310051, Zhejiang, China
| | - Xiaomeng Wang
- Zhejiang Center for Disease Control and Prevention, Institute of Tuberculosis Control, 3399 Binsheng Road, Binjiang District, Hangzhou, 310051, Zhejiang, China.
| | - Weibing Wang
- Department of Epidemiology, School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China. .,Department of Epidemiology, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China.
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