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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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Yin J, Yan G, Qin L, Zhu C, Fan J, Li Y, Jia J, Wu Z, Jiang H, Khan MT, Wu J, Chu N, Takiff HE, Gao Q, Qin S, Liu Q, Li W. Genomic investigation of bone tuberculosis highlighted the role of subclinical pulmonary tuberculosis in transmission. Tuberculosis (Edinb) 2024; 148:102534. [PMID: 38909563 DOI: 10.1016/j.tube.2024.102534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 06/09/2024] [Accepted: 06/13/2024] [Indexed: 06/25/2024]
Abstract
BACKGROUND Extrapulmonary tuberculosis (EPTB) without symptomatic pulmonary involvement has been thought to be non-transmissible, but EPTB with asymptomatic pulmonary tuberculosis (PTB) could transmit tuberculosis (TB). Genomic investigation of Mycobacterium tuberculosis (Mtb) isolates from EPTB may provide insight into its epidemiological role in TB transmission. METHODS Between January 2017 and May 2020, 107 Mtb isolates were obtained from surgical drainage of bone TB patients at the Beijing Chest Hospital, and 218 Mtb strains were isolated from PTB cases. These 325 Mtb isolates were whole-genome sequenced to reconstruct a phylogenetic tree, identify transmission clusters, and infer transmission links using a Bayesian approach. Possible subclinical PTB in the bone TB patients was investigated with chest imaging by two independent experts. RESULTS Among 107 bone TB patients, 10 were in genomic clusters (≤12 SNPs). Phylogenetic analysis suggested that three bone TB patients transmitted the infection to secondary cases, supported by epidemiological investigations. Pulmonary imaging of 44 bone TB patients revealed that 79.5 % (35/44) had radiological abnormalities suggestive of subclinical PTB. CONCLUSIONS This study provides genomic evidence that bone TB patients without clinically diagnosed PTB can be sources of TB transmission, underscoring the importance of screening for subclinical, transmissible PTB among EPTB cases.
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Affiliation(s)
- Jinfeng Yin
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Guangxuan Yan
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Liyi Qin
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Chendi Zhu
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Jun Fan
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Yuwei Li
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Junnan Jia
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Zhaojun Wu
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Hui Jiang
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Muhammad Tahir Khan
- Institute of Molecular Biology and Biotechnology (IMBB), the University of Lahore, Lahore, Pakistan
| | - Jiangdong Wu
- Key Laboratory of Xinjiang Endemic and Ethnic Diseases Cooperated by Education Ministry with Xinjiang Province, Shihezi University, Shihezi, China
| | - Naihui Chu
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Howard E Takiff
- Instituto Venezolano de Investigaciones Cientificas, Caracas, Venezuela
| | - Qian Gao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Sciences, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
| | - Shibing Qin
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.
| | - Qingyun Liu
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Department of Microbiology and Immunology, UNC-Chapel Hill School of Medicine, Chapel Hill, NC, 27599, USA.
| | - Weimin Li
- Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China; Beijing Key Laboratory for Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
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3
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Fang WW, Kong XL, Yang JY, Tao NN, Li YM, Wang TT, Li YY, Han QL, Zhang YZ, Hu JJ, Li HC, Liu Y. PE/PPE mutations in the transmission of Mycobacterium tuberculosis in China revealed by whole genome sequencing. BMC Microbiol 2024; 24:206. [PMID: 38858614 PMCID: PMC11163795 DOI: 10.1186/s12866-024-03352-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: 11/08/2023] [Accepted: 05/26/2024] [Indexed: 06/12/2024] Open
Abstract
OBJECTIVE This study aims to examine the impact of PE/PPE gene mutations on the transmission of Mycobacterium tuberculosis (M. tuberculosis) in China. METHODS We collected the whole genome sequencing (WGS) data of 3202 M. tuberculosis isolates in China from 2007 to 2018 and investigated the clustering of strains from different lineages. To evaluate the potential role of PE/PPE gene mutations in the dissemination of the pathogen, we employed homoplastic analysis to detect homoplastic single nucleotide polymorphisms (SNPs) within these gene regions. Subsequently, logistic regression analysis was conducted to analyze the statistical association. RESULTS Based on nationwide M. tuberculosis WGS data, it has been observed that the majority of the M. tuberculosis burden in China is caused by lineage 2 strains, followed by lineage 4. Lineage 2 exhibited a higher number of transmission clusters, totaling 446 clusters, of which 77 were cross-regional clusters. Conversely, there were only 52 transmission clusters in lineage 4, of which 9 were cross-regional clusters. In the analysis of lineage 2 isolates, regression results showed that 4 specific gene mutations, PE4 (position 190,394; c.46G > A), PE_PGRS10 (839,194; c.744 A > G), PE16 (1,607,005; c.620T > G) and PE_PGRS44 (2,921,883; c.333 C > A), were significantly associated with the transmission of M. tuberculosis. Mutations of PE_PGRS10 (839,334; c.884 A > G), PE_PGRS11 (847,613; c.1455G > C), PE_PGRS47 (3,054,724; c.811 A > G) and PPE66 (4,189,930; c.303G > C) exhibited significant associations with the cross-regional clusters. A total of 13 mutation positions showed a positive correlation with clustering size, indicating a positive association. For lineage 4 strains, no mutations were found to enhance transmission, but 2 mutation sites were identified as risk factors for cross-regional clusters. These included PE_PGRS4 (338,100; c.974 A > G) and PPE13 (976,897; c.1307 A > C). CONCLUSION Our results indicate that some PE/PPE gene mutations can increase the risk of M. tuberculosis transmission, which might provide a basis for controlling the spread of tuberculosis.
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Affiliation(s)
- Wei-Wei Fang
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China
- Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China
| | - Xiang-Long Kong
- Shandong Artificial Intelligence Institute, Qilu University of Technology & Shandong Academy of Sciences, Jinan, Shandong, PR China
| | - Jie-Yu Yang
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China
- Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China
| | - Ning-Ning Tao
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China
| | - Ya-Meng Li
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, PR China
| | - Ting-Ting Wang
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China
| | - Ying-Ying Li
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, PR China
| | - Qi-Lin Han
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China
- Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China
| | - Yu-Zhen Zhang
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China
- Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China
| | - Jin-Jiang Hu
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China
- Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China
| | - Huai-Chen Li
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China
| | - Yao Liu
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, 250021, PR China.
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Stanley S, Spaulding CN, Liu Q, Chase MR, Ha DTM, Thai PVK, Lan NH, Thu DDA, Quang NL, Brown J, Hicks ND, Wang X, Marin M, Howard NC, Vickers AJ, Karpinski WM, Chao MC, Farhat MR, Caws M, Dunstan SJ, Thuong NTT, Fortune SM. Identification of bacterial determinants of tuberculosis infection and treatment outcomes: a phenogenomic analysis of clinical strains. THE LANCET. MICROBE 2024; 5:e570-e580. [PMID: 38734030 DOI: 10.1016/s2666-5247(24)00022-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 12/23/2023] [Accepted: 01/16/2024] [Indexed: 05/13/2024]
Abstract
BACKGROUND Bacterial diversity could contribute to the diversity of tuberculosis infection and treatment outcomes observed clinically, but the biological basis of this association is poorly understood. The aim of this study was to identify associations between phenogenomic variation in Mycobacterium tuberculosis and tuberculosis clinical features. METHODS We developed a high-throughput platform to define phenotype-genotype relationships in M tuberculosis clinical isolates, which we tested on a set of 158 drug-sensitive M tuberculosis strains sampled from a large tuberculosis clinical study in Ho Chi Minh City, Viet Nam. We tagged the strains with unique genetic barcodes in multiplicate, allowing us to pool the strains for in-vitro competitive fitness assays across 16 host-relevant antibiotic and metabolic conditions. Relative fitness was quantified by deep sequencing, enumerating output barcode read counts relative to input normalised values. We performed a genome-wide association study to identify phylogenetically linked and monogenic mutations associated with the in-vitro fitness phenotypes. These genetic determinants were further associated with relevant clinical outcomes (cavitary disease and treatment failure) by calculating odds ratios (ORs) with binomial logistic regressions. We also assessed the population-level transmission of strains associated with cavitary disease and treatment failure using terminal branch length analysis of the phylogenetic data. FINDINGS M tuberculosis clinical strains had diverse growth characteristics in host-like metabolic and drug conditions. These fitness phenotypes were highly heritable, and we identified monogenic and phylogenetically linked variants associated with the fitness phenotypes. These data enabled us to define two genetic features that were associated with clinical outcomes. First, mutations in Rv1339, a phosphodiesterase, which were associated with slow growth in glycerol, were further associated with treatment failure (OR 5·34, 95% CI 1·21-23·58, p=0·027). Second, we identified a phenotypically distinct slow-growing subclade of lineage 1 strains (L1.1.1.1) that was associated with cavitary disease (OR 2·49, 1·11-5·59, p=0·027) and treatment failure (OR 4·76, 1·53-14·78, p=0·0069), and which had shorter terminal branch lengths on the phylogenetic tree, suggesting increased transmission. INTERPRETATION Slow growth under various antibiotic and metabolic conditions served as in-vitro intermediate phenotypes underlying the association between M tuberculosis monogenic and phylogenetically linked mutations and outcomes such as cavitary disease, treatment failure, and transmission potential. These data suggest that M tuberculosis growth regulation is an adaptive advantage for bacterial success in human populations, at least in some circumstances. These data further suggest markers for the underlying bacterial processes that contribute to these clinical outcomes. FUNDING National Health and Medical Research Council/A∗STAR, National Institutes of Allergy and Infectious Diseases, National Institute of Child Health and Human Development, and the Wellcome Trust Fellowship in Public Health and Tropical Medicine.
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Affiliation(s)
- Sydney Stanley
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Caitlin N Spaulding
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Qingyun Liu
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Michael R Chase
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | | | | | | | - Do Dang Anh Thu
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Viet Nam
| | - Nguyen Le Quang
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Viet Nam
| | - Jessica Brown
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Nathan D Hicks
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Xin Wang
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Maximillian Marin
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Nicole C Howard
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Andrew J Vickers
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Wiktor M Karpinski
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Michael C Chao
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Maha R Farhat
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Maxine Caws
- Liverpool School of Tropical Medicine, Liverpool, UK; Birat Nepal Medical Trust, Kathmandu, Nepal
| | - Sarah J Dunstan
- Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, VIC, Australia
| | - Nguyen Thuy Thuong Thuong
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Viet Nam; Nuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
| | - Sarah M Fortune
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Boston, MA, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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5
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Dixit A, Ektefaie Y, Kagal A, Freschi L, Karyakarte R, Lokhande R, Groschel M, Tornheim JA, Gupte N, Pradhan NN, Paradkar MS, Deshmukh S, Kadam D, Schito M, Engelthaler DM, Gupta A, Golub J, Mave V, Farhat M. Drug resistance and epidemiological success of modern Mycobacterium tuberculosis lineages in western India. J Infect Dis 2024:jiae240. [PMID: 38819323 DOI: 10.1093/infdis/jiae240] [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: 08/11/2023] [Revised: 04/24/2024] [Accepted: 05/03/2024] [Indexed: 06/01/2024] Open
Abstract
BACKGROUND Transmission is contributing to the slow decline of tuberculosis (TB) incidence globally. Drivers of TB transmission in India, the country estimated to carry a quarter of the World's burden, are not well studied. We conducted a genomic epidemiology study to compare epidemiological success, host factors and drug resistance (DR) among the four major Mycobacterium tuberculosis (Mtb) lineages (L1-4) circulating in Pune, India. METHODS We performed whole-genome sequencing (WGS) of Mtb sputum culture-positive isolates from participants in two prospective cohort studies and predicted genotypic susceptibility using a validated random forest model. We used maximum likelihood estimation to build phylogenies. We compared lineage specific phylogenetic and time-scaled metrics to assess epidemiological success. RESULTS Of the 642 isolates that underwent WGS, 612 met sequence quality criteria. Most isolates belonged to L3 (44.6%). The majority (61.1%) of multidrug-resistant isolates belonged to L2 (P < 0.001). In molecular dating, L2 demonstrated a higher rate and more recent resistance acquisition. We measured higher clustering, and time-scaled haplotypic density (THD) for L4 and L2 compared to L3 and/or L1 suggesting higher epidemiological success. L4 demonstrated higher THD and clustering (OR 5.1 (95% CI 2.3-12.3) in multivariate models controlling for host factors and DR. CONCLUSION L2 shows a higher frequency of DR and both L2 and L4 demonstrate evidence of higher epidemiological success than L3 or L1 in the study setting. Our findings highlight the need for contact tracing around TB cases, and heightened surveillance of TB DR in India.
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Affiliation(s)
- Avika Dixit
- Division of Infectious Diseases, Boston Children's Hospital, Boston MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston MA, USA
| | - Yasha Ektefaie
- Department of Biomedical Informatics, Harvard Medical School, Boston MA, USA
| | - Anju Kagal
- Byramjee-Jeejeebhoy Government Medical College, Pune, India
| | - Luca Freschi
- Department of Biomedical Informatics, Harvard Medical School, Boston MA, USA
| | | | - Rahul Lokhande
- Byramjee-Jeejeebhoy Government Medical College, Pune, India
| | - Matthias Groschel
- Department of Biomedical Informatics, Harvard Medical School, Boston MA, USA
| | - Jeffrey A Tornheim
- Center for Clinical Global Health Education, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Center for Tuberculosis Research, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nikhil Gupte
- Center for Clinical Global Health Education, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins India, Pune, India
| | - Neeta N Pradhan
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins India, Pune, India
| | - Mandar S Paradkar
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins India, Pune, India
| | - Sona Deshmukh
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins India, Pune, India
| | - Dileep Kadam
- Byramjee-Jeejeebhoy Government Medical College, Pune, India
| | | | | | - Amita Gupta
- Center for Clinical Global Health Education, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of International Health, Johns Hopkins Bloomberg School of Public Heath, Baltimore, MD, USA
| | - Jonathan Golub
- Center for Tuberculosis Research, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Vidya Mave
- Center for Clinical Global Health Education, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins India, Pune, India
| | - Maha Farhat
- Department of Biomedical Informatics, Harvard Medical School, Boston MA, USA
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA
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6
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Atavliyeva S, Auganova D, Tarlykov P. Genetic diversity, evolution and drug resistance of Mycobacterium tuberculosis lineage 2. Front Microbiol 2024; 15:1384791. [PMID: 38827149 PMCID: PMC11140050 DOI: 10.3389/fmicb.2024.1384791] [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: 02/12/2024] [Accepted: 05/01/2024] [Indexed: 06/04/2024] Open
Abstract
Mycobacterium tuberculosis causes a chronic infectious disease called tuberculosis. Phylogenetic lineage 2 (L2) of M. tuberculosis, also known as the East Asian lineage, is associated with high virulence, increased transmissibility, and the spread of multidrug-resistant strains. This review article examines the genomic characteristics of the M. tuberculosis genome and M. tuberculosis lineage 2, such as the unique insertion sequence and spoligotype patterns, as well as MIRU-VNTR typing, and SNP-based barcoding. The review describes the geographical distribution of lineage 2 and its history of origin. In addition, the article discusses recent studies on drug resistance and compensatory mechanisms of M. tuberculosis lineage 2 and its impact on the pathogen's transmissibility and virulence. This review article discusses the importance of establishing a unified classification for lineage 2 to ensure consistency in terminology and criteria across different studies and settings.
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Affiliation(s)
- Sabina Atavliyeva
- Genomics and Proteomics Core Facility, National Center for Biotechnology, Astana, Kazakhstan
| | | | - Pavel Tarlykov
- Genomics and Proteomics Core Facility, National Center for Biotechnology, Astana, Kazakhstan
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7
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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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8
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Lan Y, Crudu V, Ciobanu N, Codreanu A, Chitwood MH, Sobkowiak B, Warren JL, Cohen T. Identifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model. EBioMedicine 2024; 102:105085. [PMID: 38531172 PMCID: PMC10987885 DOI: 10.1016/j.ebiom.2024.105085] [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: 01/12/2024] [Revised: 03/08/2024] [Accepted: 03/11/2024] [Indexed: 03/28/2024] Open
Abstract
BACKGROUND Multidrug resistant tuberculosis (MDR-TB) represents a major public health concern in the Republic of Moldova, with an estimated 31% of new and 56% of previously treated TB cases having MDR disease in 2022. A recent genomic epidemiology study of incident TB occurring in 2018 and 2019 found that 92% of MDR-TB was the result of transmission. The MDR phenotype was concentrated among two M. tuberculosis (Mtb) lineages: L2.2.1 (Beijing) and L4.2.1 (Ural). METHODS We developed and applied a hierarchical Bayesian multinominal logistic regression model to Mtb genomic, spatial, and epidemiological data collected from all individuals with diagnosed TB in Moldova in 2018 and 2019 to identify locations in which specific Mtb strains are being transmitted. We then used a logistic regression model to estimate locality-level factors associated with local transmission. FINDINGS We found differences in the spatial distribution and degree of local concentration of disease due to specific strains of Beijing and Ural lineage Mtb. Foci of transmission for four strains of Beijing lineage Mtb, predominantly of the MDR-TB phenotype, were located in several regions, but largely concentrated in Transnistria. In contrast, transmission of Ural lineage Mtb had less marked patterns of spatial aggregation, with a single strain (also of the MDR phenotype) spatially clustered in southern Transnistria. We found a 30% (95% credible interval 2%-80%) increase in odds of a locality being a transmission cluster for each increase of 100 persons per square kilometer, while higher local tuberculosis incidence and poverty were not associated with a locality being a transmission focus. INTERPRETATION Our results identified localities where specific Mtb transmission networks were concentrated and quantified the association between locality-level factors and focal transmission. This analysis revealed Transnistria as the primary area where specific Mtb strains (predominantly of the MDR-TB phenotype) were locally transmitted and suggests that targeted intensified case finding in this region may be an attractive policy option. FUNDING Funding for this work was provided by the National Institute of Allergy and Infectious Diseases at the US National Institutes of Health.
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Affiliation(s)
- Yu Lan
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Valeriu Crudu
- Phthisiopneumology Institute, Chisinau, Republic of Moldova
| | - Nelly Ciobanu
- Phthisiopneumology Institute, Chisinau, Republic of Moldova
| | | | - Melanie H Chitwood
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Benjamin Sobkowiak
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Joshua L Warren
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
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9
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Li Y, Li Y, Wang T, Li Y, Tao N, Kong X, Zhang Y, Han Q, Liu Y, Li H. Multidrug-resistant Mycobacterium tuberculosis transmission in Shandong, China. Medicine (Baltimore) 2024; 103:e37617. [PMID: 38518003 PMCID: PMC10956945 DOI: 10.1097/md.0000000000037617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 02/23/2024] [Indexed: 03/24/2024] Open
Abstract
Multidrug-resistant tuberculosis (MDR-TB) has imposed a significant economic and health burden worldwide, notably in China. Using whole genome sequence, we sought to understand the mutation and transmission of MDR-TB in Shandong. A retrospective study of patients diagnosed with pulmonary tuberculosis in Shandong from 2009 to 2018 was conducted. To explore transmission patterns, we performed whole genome sequencing on MDR-TB isolates, identified genomic clusters, and assessed the drug resistance of TB isolates. Our study analyzed 167 isolates of MDR-TB, finding that 100 were clustered. The predominant lineage among MDR-TB isolates was lineage 2, specifically with a notable 88.6% belonging to lineage 2.2.1. Lineage 4 constituted a smaller proportion, accounting for 4.2% of the isolates. We discovered that Shandong has a significant clustering percentage for MDR-TB, with Jining having the highest percentage among all Shandong cities. The clustering percentages of MDR-TB, pre-extensively drug-resistant tuberculosis, and extensively drug-resistant tuberculosis were 59.9%, 66.0%, and 71.4%, respectively, and the clustering percentages increased with the expansion of the anti-TB spectrum. Isolates from genomic clusters 1 and 3 belonged to lineage 2.2.1 and showed signs of cross-regional transmission. The distribution of rrs A1401G and katG S315T mutations in lineage 2.2.1 and 2.2.2 strains differed significantly (P < .05). MDR-TB isolates with rpoB I480V, embA-12C > T, and rrs A1401G mutations showed a higher likelihood of clustering (P < .05). Our findings indicate a significant problem of local transmission of MDR-TB in Shandong, China. Beijing lineage isolates and some drug-resistant mutations account for the MDR-TB transmission in Shandong.
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Affiliation(s)
- Yingying Li
- Department of Chinese Medicine Integrated with Western Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yifan Li
- Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Shandong First Medical University, Jinan, China
| | - Tingting Wang
- Department of Chinese Medicine Integrated with Western Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yameng Li
- Department of Chinese Medicine Integrated with Western Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Ningning Tao
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Xianglong Kong
- Shandong Artificial Intelligence Institute Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, China
| | - Yuzhen Zhang
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Qilin Han
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Yao Liu
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Huaichen Li
- Department of Chinese Medicine Integrated with Western Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
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10
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Rukmana A, Gozali C, Erlina L. Mycobacterium tuberculosis Lineage Distribution Using Whole-Genome Sequencing and Bedaquiline, Clofazimine, and Linezolid Phenotypic Profiles among Rifampicin-Resistant Isolates from West Java, Indonesia. Int J Microbiol 2024; 2024:2037961. [PMID: 38469390 PMCID: PMC10927343 DOI: 10.1155/2024/2037961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 02/03/2024] [Accepted: 02/22/2024] [Indexed: 03/13/2024] Open
Abstract
Tuberculosis (TB) is caused by Mycobacterium tuberculosis infection. Indonesia is ranked second in the world for TB cases. New anti-TB drugs from groups A and B, such as bedaquiline, clofazimine, and linezolid, have been shown to be effective in curing drug resistance in TB patients, and Indonesia is already using these drugs to treat patients. However, studies comparing the TB strain types with anti-TB resistance profiles are still relevant to understanding the prevalent strains in the country and their phenotypic characteristics. This study aimed to determine the association between the TB lineage distribution using whole-genome sequencing and bedaquiline, clofazimine, and linezolid phenotypic profile resistance among M. tuberculosisrifampicin-resistant isolates from West Java. M. tuberculosis isolates stock of the Department of Microbiology, Faculty of Medicine, Universitas Indonesia, was tested against bedaquiline, clofazimine, and linezolid using a mycobacteria growth indicator tube liquid culture. All isolates were tested for M. tuberculosis and rifampicin resistance using Xpert MTB/RIF. The DNA genome of M. tuberculosis was freshly extracted from a Löwenstein-Jensen medium culture and then sequenced. The isolates showed phenotypically resistance to bedaquiline, clofazimine, and linezolid at 5%, 0%, and 0%, respectively. We identified gene mutations on phenotypically bedaquiline-resistant strains (2/3), and other mutations also found in phenotypically drug-sensitive strains. Mykrobe analysis showed that most (88.33%) of the isolates could be classified as rifampicin-resistant TB. Using Mykrobe and TB-Profiler to determine the lineage distribution, the isolates were found to belong to lineage 4 (Euro-American; 48.33%), lineage 2 (East Asian/Beijing; 46.67%), and lineage 1 (Indo-Oceanic; 5%). This work underlines the requirement to increase the representation of genotype-phenotype TB data while also highlighting the importance and efficacy of WGS in predicting medication resistance and inferring disease transmission.
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Affiliation(s)
- Andriansjah Rukmana
- Department of Microbiology, Faculty of Medicine, Universitas Indonesia, Jakarta 10320, Indonesia
| | - Cynthia Gozali
- Master Programme of Biomedical Sciences, Faculty of Medicine, Universitas Indonesia, Jakarta 10430, Indonesia
| | - Linda Erlina
- Department of Medical Chemistry, Faculty of Medicine, Universitas Indonesia, Jakarta 10430, Indonesia
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11
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Li YF, Yang Y, Kong XL, Song WM, Li YM, Li YY, Fang WW, Yang JY, Men D, Yu CB, Yang GR, Han WG, Liu WY, Yan K, Li HC, Liu Y. Transmission dynamics and phylogeography of Mycobacterium tuberculosis in China based on whole-genome phylogenetic analysis. Int J Infect Dis 2024; 140:124-131. [PMID: 37863309 DOI: 10.1016/j.ijid.2023.10.015] [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: 05/12/2023] [Revised: 09/30/2023] [Accepted: 10/16/2023] [Indexed: 10/22/2023] Open
Abstract
OBJECTIVES This study aimed to describe the lineage-specific transmissibility and epidemiological migration of Mycobacterium tuberculosis in China. METHODS We curated a large set of whole-genome sequences from 3204 M. tuberculosis isolates, including thousands of newly sequenced genomes, and applied a series of metrics to compare the transmissibility of M. tuberculosis strains between lineages and sublineages. The countrywide transmission patterns of major lineages were explored. RESULTS We found that lineage 2 (L2) was the most prevalent lineage in China (85.7%), with the major sublineage 2.2.1 (80.9%), followed by lineage 4 (L4) (13.8%), which comprises major sublineages 4.2 (1.5%), 4.4 (6.2%) and 4.5 (5.8%). We showed evidence for frequent cross-regional spread and large cluster formation of L2.2.1 strains, whereas L4 strains were relatively geographically restricted in China. Next, we applied a series of genomic indices to evaluate M. tuberculosis strain transmissibility and uncovered higher transmissibility of L2.2.1 compared with the L2.2.2 and L4 sublineages. Phylogeographic analysis showed that southern, eastern, and northern China were highly connected regions for countrywide L2.2.1 strain spread. CONCLUSIONS The present study provides insights into the different transmission and migration patterns of the major M. tuberculosis lineages in China and highlights that transmissible L2.2.1 is a threat to tuberculosis control.
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Affiliation(s)
- Yi-Fan Li
- Department of Respiratory and Critical Care Medicine, the Third Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, PR China
| | - Yang Yang
- Institute of Nutrition and Health, School of Public Health, Qingdao University, Qingdao, PR China
| | - Xiang-Long Kong
- Xiang-long Kong, Shandong Artificial Intelligence Institute Qilu University of Technology & Shandong Academy of Sciences, Jinan, Shandong, PR China
| | - Wan-Mei Song
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, PR China
| | - Ya-Meng Li
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, PR China; Shandong University of Traditional Chinese Medicine, Jinan, Shandong, PR China
| | - Ying-Ying Li
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, PR China; Shandong University of Traditional Chinese Medicine, Jinan, Shandong, PR China
| | - Wei-Wei Fang
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, PR China
| | - Jie-Yu Yang
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, PR China
| | - Dan Men
- College of Geography and Environmental Science, Northwest Normal University, No. 967 Anning East Road, Lanzhou, Gansu Province, China
| | - Chun-Bao Yu
- Center for Integrative and Translational Medicine, Shandong Public Health Clinical Center, Jinan, Shandong, PR China
| | - Guo-Ru Yang
- Department of Respiratory and Critical Care Medicine, Weifang Respiratory Disease Hospital & Weifang No. 2 People's Hospital, Weifang, Shandong, PR China
| | - Wen-Ge Han
- Department of Respiratory and Critical Care Medicine, Weifang Respiratory Disease Hospital & Weifang No. 2 People's Hospital, Weifang, Shandong, PR China
| | - Wen-Yu Liu
- Department of Respiratory and Critical Care Medicine, Weifang Respiratory Disease Hospital & Weifang No. 2 People's Hospital, Weifang, Shandong, PR China
| | - Kun Yan
- Department of Respiratory and Critical Care Medicine, Weifang Respiratory Disease Hospital & Weifang No. 2 People's Hospital, Weifang, Shandong, PR China
| | - Huai-Chen Li
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, PR China
| | - Yao Liu
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, PR China.
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12
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Saini A, Dadwal R, Yadav R, Kanaujia R, Aggarwal AN, Arora A, Sethi S. Whole genome sequencing for the prediction of resistant tuberculosis strains from northern India. Indian J Med Microbiol 2024; 48:100537. [PMID: 38350525 DOI: 10.1016/j.ijmmb.2024.100537] [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: 10/04/2023] [Revised: 12/07/2023] [Accepted: 02/09/2024] [Indexed: 02/15/2024]
Abstract
PURPOSE Tuberculosis is an important public health problem among infectious diseases. The problem becomes more concerning with the emergence of MDR-TB and pre-XDR-TB. Whole genome sequencing (WGS) detection of resistance has recently gained popularity as it has advantages over other commercial techniques. METHODS We performed in-house WGS followed by detailed analysis by an in-house pipeline to identify the resistance markers. This was accompanied by Phenotypic DST, and Sanger sequencing on all the 12 XDR, 06 pre-XDR, and 06 susceptible M. tb isolates. These results were collated with online M. tb WGS pipelines (TB profiler, PhyResSE, Mykrobe predictor) for comparative analysis. RESULTS Following our in-house analysis, we observed 64 non-synonymous SNPs, fifteen synonymous SNPs, and five INDELs in 25 drug resistance-associated genes/intergenic regions (IGRs) in M. tb isolates. Sensitivity for detecting XDR is 33%, 58%, 83%, and 83%, respectively, using Mykrobe predictor, PhyResSE, TB-profiler, and in-house pipeline for WGS analysis, respectively. TB-profiler detected a rare mutation H70R in the gyrA gene in one pre-XDR isolate. Lineage 2.2.1 East-Asian (Beijing sublineage type) predominated (60%) in WGS data analysis of the XDR isolates. CONCLUSIONS Our findings suggest that in-house analysis of WGS data and TB-profiler sensitivity was better for the detection of second-line resistance as compared to other automated tested tools. Frequent upgradation of newer mutations associated with resistance needs to be updated, as it potentiates tailored treatment for patients.
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Affiliation(s)
| | | | | | | | | | - Amit Arora
- Dept. of Medical Microbiology, PGIMER, India.
| | - Sunil Sethi
- Dept. of Medical Microbiology, PGIMER, India.
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13
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Stanley S, Wang X, Liu Q, Kwon YY, Frey AM, Hicks ND, Vickers AJ, Hui S, Fortune SM. Ongoing evolution of the Mycobacterium tuberculosis lactate dehydrogenase reveals the pleiotropic effects of bacterial adaption to host pressure. PLoS Pathog 2024; 20:e1012050. [PMID: 38422159 DOI: 10.1371/journal.ppat.1012050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 03/12/2024] [Accepted: 02/13/2024] [Indexed: 03/02/2024] Open
Abstract
The bacterial determinants that facilitate Mycobacterium tuberculosis (Mtb) adaptation to the human host environment are poorly characterized. We have sought to decipher the pressures facing the bacterium in vivo by assessing Mtb genes that are under positive selection in clinical isolates. One of the strongest targets of selection in the Mtb genome is lldD2, which encodes a quinone-dependent L-lactate dehydrogenase (LldD2) that catalyzes the oxidation of lactate to pyruvate. Lactate accumulation is a salient feature of the intracellular environment during infection and lldD2 is essential for Mtb growth in macrophages. We determined the extent of lldD2 variation across a set of global clinical isolates and defined how prevalent mutations modulate Mtb fitness. We show the stepwise nature of lldD2 evolution that occurs as a result of ongoing lldD2 selection in the background of ancestral lineage-defining mutations and demonstrate that the genetic evolution of lldD2 additively augments Mtb growth in lactate. Using quinone-dependent antibiotic susceptibility as a functional reporter, we also find that the evolved lldD2 mutations functionally increase the quinone-dependent activity of LldD2. Using 13C-lactate metabolic flux tracing, we find that lldD2 is necessary for robust incorporation of lactate into central carbon metabolism. In the absence of lldD2, label preferentially accumulates in dihydroxyacetone phosphate (DHAP) and glyceraldehyde-3-phosphate (G3P) and is associated with a discernible growth defect, providing experimental evidence for accrued lactate toxicity via the deleterious buildup of sugar phosphates. The evolved lldD2 variants increase lactate incorporation to pyruvate while altering triose phosphate flux, suggesting both an anaplerotic and detoxification benefit to lldD2 evolution. We further show that the mycobacterial cell is transcriptionally sensitive to the changes associated with altered lldD2 activity which affect the expression of genes involved in cell wall lipid metabolism and the ESX- 1 virulence system. Together, these data illustrate a multifunctional role of LldD2 that provides context for the selective advantage of lldD2 mutations in adapting to host stress.
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Affiliation(s)
- Sydney Stanley
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Xin Wang
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Qingyun Liu
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Young Yon Kwon
- Department of Molecular Metabolism, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Abigail M Frey
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Nathan D Hicks
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Andrew J Vickers
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Sheng Hui
- Department of Molecular Metabolism, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Sarah M Fortune
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, Massachusetts, United States of America
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
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14
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Wang TT, Hu YL, Li YF, Kong XL, Li YM, Sun PY, Wang DX, Li YY, Zhang YZ, Han QL, Zhu XH, An QQ, Liu LL, Liu Y, Li HC. Polyketide synthases mutation in tuberculosis transmission revealed by whole genomic sequence, China, 2011-2019. Front Genet 2024; 14:1217255. [PMID: 38259610 PMCID: PMC10800454 DOI: 10.3389/fgene.2023.1217255] [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: 05/20/2023] [Accepted: 11/30/2023] [Indexed: 01/24/2024] Open
Abstract
Introduction: Tuberculosis (TB) is an infectious disease caused by a bacterium called Mycobacterium tuberculosis (Mtb). Previous studies have primarily focused on the transmissibility of multidrug-resistant (MDR) or extensively drug-resistant (XDR) Mtb. However, variations in virulence across Mtb lineages may also account for differences in transmissibility. In Mtb, polyketide synthase (PKS) genes encode large multifunctional proteins which have been shown to be major mycobacterial virulence factors. Therefore, this study aimed to identify the role of PKS mutations in TB transmission and assess its risk and characteristics. Methods: Whole genome sequences (WGSs) data from 3,204 Mtb isolates was collected from 2011 to 2019 in China. Whole genome single nucleotide polymorphism (SNP) profiles were used for phylogenetic tree analysis. Putative transmission clusters (≤10 SNPs) were identified. To identify the role of PKS mutations in TB transmission, we compared SNPs in the PKS gene region between "clustered isolates" and "non-clustered isolates" in different lineages. Results: Cluster-associated mutations in ppsA, pks12, and pks13 were identified among different lineage isolates. They were statistically significant among clustered strains, indicating that they may enhance the transmissibility of Mtb. Conclusion: Overall, this study provides new insights into the function of PKS and its localization in M. tuberculosis. The study found that ppsA, pks12, and pks13 may contribute to disease progression and higher transmission of certain strains. We also discussed the prospective use of mutant ppsA, pks12, and pks13 genes as drug targets.
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Affiliation(s)
- Ting-Ting Wang
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yuan-Long Hu
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yi-Fan Li
- Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Shandong First Medical University (Affiliated Hospital of Shandong Academy of Medical Sciences), Jinan, China
| | - Xiang-Long Kong
- Shandong Artificial Intelligence Institute Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Ya-Meng Li
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | | | - Da-Xing Wang
- People’s Hospital of Huaiyin Jinan, Jinan, China
| | - Ying-Ying Li
- Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yu-Zhen Zhang
- Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Qi-Lin Han
- Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Xue-Han Zhu
- Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Qi-Qi An
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to 11 Shandong University, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Li-Li Liu
- People’s Hospital of Huaiyin Jinan, Jinan, China
| | - Yao Liu
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to 11 Shandong University, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Huai-Chen Li
- Shandong University of Traditional Chinese Medicine, Jinan, China
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to 11 Shandong University, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
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15
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Abstract
The greatest challenge in drug discovery remains the high rate of attrition across the different phases of the process, which cost the industry billions of dollars every year. While all phases remain crucial to ensure pharmaceutical-level safety, quality, and efficacy of the end product, streamlining these efforts toward compounds with success potential is pivotal for a more efficient and cost-effective process. The use of artificial intelligence (AI) within the pharmaceutical industry aims at just this, and has applications in preclinical screening for biological activity, optimization of pharmacokinetic properties for improved drug formulation, early toxicity prediction which reduces attrition, and pre-emptively screening for genetic changes in the biological target to improve therapeutic longevity. Here, we present a series of in silico tools that address these applications in small molecule development and describe how they can be embedded within the current pharmaceutical development pipeline.
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Affiliation(s)
- Adam Serghini
- School of Chemistry and Molecular Biosciences, University of Queensland, St Lucia, QLD, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Stephanie Portelli
- School of Chemistry and Molecular Biosciences, University of Queensland, St Lucia, QLD, Australia.
| | - David B Ascher
- School of Chemistry and Molecular Biosciences, University of Queensland, St Lucia, QLD, Australia.
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
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16
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Du DH, Geskus RB, Zhao Y, Codecasa LR, Cirillo DM, van Crevel R, Pascapurnama DN, Chaidir L, Niemann S, Diel R, Omar SV, Grandjean L, Rokadiya S, Ortitz AT, Lân NH, Hà ĐTM, Smith EG, Robinson E, Dedicoat M, Nhat LTH, Thwaites GE, Van LH, Thuong NTT, Walker TM. The effect of M. tuberculosis lineage on clinical phenotype. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0001788. [PMID: 38117783 PMCID: PMC10732390 DOI: 10.1371/journal.pgph.0001788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 11/17/2023] [Indexed: 12/22/2023]
Abstract
Six lineages of Mycobacterium tuberculosis sensu stricto (which excludes M. africanum) are described. Single-country or small observational data suggest differences in clinical phenotype between lineages. We present strain lineage and clinical phenotype data from 12,246 patients from 3 low-incidence and 5 high-incidence countries. We used multivariable logistic regression to explore the effect of lineage on site of disease and on cavities on chest radiography, given pulmonary TB; multivariable multinomial logistic regression to investigate types of extra-pulmonary TB, given lineage; and accelerated failure time and Cox proportional-hazards models to explore the effect of lineage on time to smear and culture-conversion. Mediation analyses quantified the direct effects of lineage on outcomes. Pulmonary disease was more likely among patients with lineage(L) 2, L3 or L4, than L1 (adjusted odds ratio (aOR) 1.79, (95% confidence interval 1.49-2.15), p<0.001; aOR = 1.40(1.09-1.79), p = 0.007; aOR = 2.04(1.65-2.53), p<0.001, respectively). Among patients with pulmonary TB, those with L1 had greater risk of cavities on chest radiography versus those with L2 (aOR = 0.69(0.57-0.83), p<0.001) and L4 strains (aOR = 0.73(0.59-0.90), p = 0.002). L1 strains were more likely to cause osteomyelitis among patients with extra-pulmonary TB, versus L2-4 (p = 0.033, p = 0.008 and p = 0.049 respectively). Patients with L1 strains showed shorter time-to-sputum smear conversion than for L2. Causal mediation analysis showed the effect of lineage in each case was largely direct. The pattern of clinical phenotypes seen with L1 strains differed from modern lineages (L2-4). This has implications for clinical management and could influence clinical trial selection strategies.
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Affiliation(s)
- Duc Hong Du
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Ronald B. Geskus
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | | | - Luigi Ruffo Codecasa
- Regional TB Reference Centre/ Istituto Villa Marelli- ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
| | | | - Reinout van Crevel
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Lidya Chaidir
- Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Sumedang, West Java, Indonesia
| | - Stefan Niemann
- Research Center Borstel, Borstel, Germany
- German Center for Infection Research, Partner Site Hamburg-Lübeck-Borstel-Riems, Germany
| | - Roland Diel
- University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
- Lung Clinic Grosshansdorf, Airway Disease Center North (ARCN), German Center for Lung Research (DZL), Grosshansdorf, Germany
| | | | | | - Sakib Rokadiya
- University College London Hospital, London, United Kingdom
| | | | | | | | - E. Grace Smith
- TB Unit and National Mycobacterial Reference Service, UK Health Security Agency, Birmingham, United Kingdom
| | - Esther Robinson
- TB Unit and National Mycobacterial Reference Service, UK Health Security Agency, Birmingham, United Kingdom
| | - Martin Dedicoat
- TB Unit and National Mycobacterial Reference Service, UK Health Security Agency, Birmingham, United Kingdom
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
| | | | - Guy E. Thwaites
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Le Hong Van
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Nguyen Thuy Thuong Thuong
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Timothy M. Walker
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
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Silcocks M, Chang X, Thuong Thuong NT, Qin Y, Minh Ha DT, Khac Thai PV, Vijay S, Anh Thu DD, Ngoc Ha VT, Ngoc Nhung H, Huu Lan N, Quynh Nhu NT, Edwards D, Nath A, Pham K, Duc Bang N, Hong Chau TT, Thwaites G, Heemskerk AD, Chuen Khor C, Teo YY, Inouye M, Ong RTH, Caws M, Holt KE, Dunstan SJ. Evolution and transmission of antibiotic resistance is driven by Beijing lineage Mycobacterium tuberculosis in Vietnam. Microbiol Spectr 2023; 11:e0256223. [PMID: 37971428 PMCID: PMC10714959 DOI: 10.1128/spectrum.02562-23] [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: 06/21/2023] [Accepted: 10/12/2023] [Indexed: 11/19/2023] Open
Abstract
IMPORTANCE Drug-resistant tuberculosis (TB) infection is a growing and potent concern, and combating it will be necessary to achieve the WHO's goal of a 95% reduction in TB deaths by 2035. While prior studies have explored the evolution and spread of drug resistance, we still lack a clear understanding of the fitness costs (if any) imposed by resistance-conferring mutations and the role that Mtb genetic lineage plays in determining the likelihood of resistance evolution. This study offers insight into these questions by assessing the dynamics of resistance evolution in a high-burden Southeast Asian setting with a diverse lineage composition. It demonstrates that there are clear lineage-specific differences in the dynamics of resistance acquisition and transmission and shows that different lineages evolve resistance via characteristic mutational pathways.
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Affiliation(s)
- Matthew Silcocks
- Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria, Australia
| | - Xuling Chang
- Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria, Australia
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, , Singapore
- Khoo Teck Puat–National University Children’s Medical Institute, National University Health System, Singapore
| | - Nguyen Thuy Thuong Thuong
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, District 5, Ho Chi Minh City, Vietnam
- Nuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, United Kingdom
| | - Youwen Qin
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- School of BioSciences, The University of Melbourne, Melbourne, Victoria, Australia
| | - Dang Thi Minh Ha
- Pham Ngoc Thach Hospital for TB and Lung Disease, District 5, Ho Chi Minh City, Vietnam
| | - Phan Vuong Khac Thai
- Pham Ngoc Thach Hospital for TB and Lung Disease, District 5, Ho Chi Minh City, Vietnam
| | - Srinivasan Vijay
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, District 5, Ho Chi Minh City, Vietnam
- Nuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, United Kingdom
- Theoretical Microbial Ecology, Friedrich Schiller University Jena, Jena, Germany
| | - Do Dang Anh Thu
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, District 5, Ho Chi Minh City, Vietnam
| | - Vu Thi Ngoc Ha
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, District 5, Ho Chi Minh City, Vietnam
| | - Hoang Ngoc Nhung
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, District 5, Ho Chi Minh City, Vietnam
| | - Nguyen Huu Lan
- Pham Ngoc Thach Hospital for TB and Lung Disease, District 5, Ho Chi Minh City, Vietnam
| | - Nguyen Thi Quynh Nhu
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, District 5, Ho Chi Minh City, Vietnam
| | - David Edwards
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Artika Nath
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Kym Pham
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Nguyen Duc Bang
- Pham Ngoc Thach Hospital for TB and Lung Disease, District 5, Ho Chi Minh City, Vietnam
| | - Tran Thi Hong Chau
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, District 5, Ho Chi Minh City, Vietnam
- Hospital for Tropical Diseases, District 5, Ho Chi Minh City, Vietnam
| | - Guy Thwaites
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, District 5, Ho Chi Minh City, Vietnam
- Nuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, United Kingdom
| | - A. Dorothee Heemskerk
- Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centre, Amsterdam, Netherlands
| | | | - Yik Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Public Health and Primary Care, Cambridge Baker Systems Genomics Initiative, University of Cambridge, Cambridge, United Kingdom
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Maxine Caws
- Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- Birat Nepal Medical Trust, Kathmandu, Nepal
| | - Kathryn E. Holt
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Department of Infection Biology, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Sarah J. Dunstan
- Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria, Australia
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Silcocks M, Dunstan SJ. Parallel signatures of Mycobacterium tuberculosis and human Y-chromosome phylogeography support the Two Layer model of East Asian population history. Commun Biol 2023; 6:1037. [PMID: 37833496 PMCID: PMC10575886 DOI: 10.1038/s42003-023-05388-8] [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: 07/21/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023] Open
Abstract
The Two Layer hypothesis is fast becoming the favoured narrative describing East Asian population history. Under this model, hunter-gatherer groups who initially peopled East Asia via a route south of the Himalayas were assimilated by agriculturalist migrants who arrived via a northern route across Eurasia. A lack of ancient samples from tropical East Asia limits the resolution of this model. We consider insight afforded by patterns of variation within the human pathogen Mycobacterium tuberculosis (Mtb) by analysing its phylogeographic signatures jointly with the human Y-chromosome. We demonstrate the Y-chromosome lineages enriched in the traditionally hunter-gatherer groups associated with East Asia's first layer of peopling to display deep roots, low long-term effective population size, and diversity patterns consistent with a southern entry route. These characteristics mirror those of the evolutionarily ancient Mtb lineage 1. The remaining East Asian Y-chromosome lineage is almost entirely absent from traditionally hunter-gatherer groups and displays spatial and temporal characteristics which are incompatible with a southern entry route, and which link it to the development of agriculture in modern-day China. These characteristics mirror those of the evolutionarily modern Mtb lineage 2. This model paves the way for novel host-pathogen coevolutionary research hypotheses in East Asia.
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Affiliation(s)
- Matthew Silcocks
- Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, VIC, Australia.
| | - Sarah J Dunstan
- Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, VIC, Australia
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Stanley S, Wang X, Liu Q, Kwon YY, Frey AM, Hicks ND, Vickers AJ, Hui S, Fortune SM. Ongoing evolution of the Mycobacterium tuberculosis lactate dehydrogenase reveals the pleiotropic effects of bacterial adaption to host pressure. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.09.561592. [PMID: 37873410 PMCID: PMC10592758 DOI: 10.1101/2023.10.09.561592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The bacterial determinants that facilitate Mycobacterium tuberculosis (Mtb) adaptation to the human host environment are poorly characterized. We have sought to decipher the pressures facing the bacterium in vivo by assessing Mtb genes that are under positive selection in clinical isolates. One of the strongest targets of selection in the Mtb genome is lldD2 , which encodes a quinone-dependent L-lactate dehydrogenase (LldD2) that catalyzes the oxidation of lactate to pyruvate. Lactate accumulation is a salient feature of the intracellular environment during infection and lldD2 is essential for Mtb growth in macrophages. We determined the extent of lldD2 variation across a set of global clinical isolates and defined how prevalent mutations modulates Mtb fitness. We show the stepwise nature of lldD2 evolution that occurs as a result of ongoing lldD2 selection in the background of ancestral lineage defining mutations and demonstrate that the genetic evolution of lldD2 additively augments Mtb growth in lactate. Using quinone-dependent antibiotic susceptibility as a functional reporter, we also find that the evolved lldD2 mutations functionally increase the quinone-dependent activity of LldD2. Using 13 C-lactate metabolic flux tracing, we find that lldD2 is necessary for robust incorporation of lactate into central carbon metabolism. In the absence of lldD2 , label preferentially accumulates in methylglyoxal precursors dihydroxyacetone phosphate (DHAP) and glyceraldehyde-3-phosphate (G3P) and is associated with a discernible growth defect, providing experimental evidence for accumulated lactate toxicity via a methylglyoxal pathway that has been proposed previously. The evolved lldD2 variants increase lactate incorporation to pyruvate but also alter flux in the methylglyoxal pathway, suggesting both an anaplerotic and detoxification benefit to lldD2 evolution. We further show that the mycobacterial cell is transcriptionally sensitive to the changes associated with altered lldD2 activity which affect the expression of genes involved in cell wall lipid metabolism and the ESX-1 virulence system. Together, these data illustrate a multifunctional role of LldD2 that provide context for the selective advantage of lldD2 mutations in adapting to host stress.
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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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Berry SB, Espich S, Thuong NTT, Chang X, Dorajoo R, Khor CC, Heng CK, Yuan JM, Fox D, Anaya-Sanchez A, Tenney L, Chang CJ, Kotov DI, Vance RE, Dunstan SJ, Darwin KH, Stanley SA. Disruption of Aldehyde Dehydrogenase 2 protects against bacterial infection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.24.554661. [PMID: 37662190 PMCID: PMC10473740 DOI: 10.1101/2023.08.24.554661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The ALDH2*2 (rs671) allele is one of the most common genetic mutations in humans, yet the positive evolutionary selective pressure to maintain this mutation is unknown, despite its association with adverse health outcomes. ALDH2 is responsible for the detoxification of metabolically produced aldehydes, including lipid-peroxidation end products derived from inflammation. Here, we demonstrate that host-derived aldehydes 4-hydroxynonenal (4HNE), malondialdehyde (MDA), and formaldehyde (FA), all of which are metabolized by ALDH2, are directly toxic to the bacterial pathogens Mycobacterium tuberculosis and Francisella tularensis at physiological levels. We find that Aldh2 expression in macrophages is decreased upon immune stimulation, and that bone marrow-derived macrophages from Aldh2 -/- mice contain elevated aldehydes relative to wild-type mice. Macrophages deficient for Aldh2 exhibited enhanced control of Francisella infection. Finally , mice lacking Aldh2 demonstrated increased resistance to pulmonary infection by M. tuberculosis , including in a hypersusceptible model of tuberculosis, and were also resistant to Francisella infection. We hypothesize that the absence of ALDH2 contributes to the host's ability to control infection by pathogens such as M. tuberculosis and F. tularensis , and that host-derived aldehydes act as antimicrobial factors during intracellular bacterial infections. One sentence summary Aldehydes produced by host cells contribute to the control of bacterial infections.
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22
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Zhu C, Yang T, Yin J, Jiang H, Takiff HE, Gao Q, Liu Q, Li W. The Global Success of Mycobacterium tuberculosis Modern Beijing Family Is Driven by a Few Recently Emerged Strains. Microbiol Spectr 2023; 11:e0333922. [PMID: 37272796 PMCID: PMC10434187 DOI: 10.1128/spectrum.03339-22] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 05/23/2023] [Indexed: 06/06/2023] Open
Abstract
Strains of the Mycobacterium tuberculosis complex (MTBC) Beijing family aroused concern because they were often found in clusters and appeared to be exceptionally transmissible. However, it was later found that strains of the Beijing family were heterogeneous, and the transmission advantage was restricted to sublineage L2.3 or modern Beijing. In this study, we analyzed the previously published genome sequences of 7,896 L2.3 strains from 51 different countries. Using BEAST software to approximate the temporal emergence of L2.3, our calculations suggest that L2.3 initially emerged in northern East Asia during the early 15th century and subsequently diverged into six phylogenetic clades, identified as L2.3.1 through L2.3.6. Using terminal branch length and genomic clustering as proxies for transmissibility, we found that the six clades displayed distinct population dynamics, with the three recently emerged clades (L2.3.4 to L2.3.6) exhibiting significantly higher transmissibility than the older three clades (L2.3.1 to L2.3.3). Of the Beijing family strains isolated outside East Asia, 83.1% belonged to the clades L2.3.4 to L2.3.6, which were also associated with more cross-border transmission. This work reveals the heterogeneity in sublineage L2.3 and demonstrates that the global success of Beijing family strains is driven by the three recently emerged L2.3 clades. IMPORTANCE The recent population dynamics of the global tuberculosis epidemic are heavily shaped by Mycobacterium tuberculosis complex (MTBC) strains with enhanced transmissibility. The infamous Beijing family strain stands out because it has rapidly spread throughout the world. Identifying the strains responsible for the global expansion and tracing their evolution should help to understand the nature of high transmissibility and develop effective strategies to control transmission. In this study, we found that the L2.3 sublineage diversified into six phylogenetic clades (L2.3.1 to L2.3.6) with various transmission characteristics. Clades L2.3.4 to L2.3.6 exhibited significantly higher transmissibility than clades L2.3.1 to L2.3.3, which helps explain why more than 80% of Beijing family strains collected outside East Asia belong to these three clades. We conclude that the global success of L2.3 was not caused by the entire L2.3 sublineage but rather was due to the rapid expansion of L2.3.4 to L2.3.6. Tracking the transmission of L2.3.4 to L2.3.6 strains can help to formulate targeted TB prevention and control.
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Affiliation(s)
- Chendi Zhu
- Beijing Chest Hospital, Capital Medical University, Beijing, China
- Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | | | - Jinfeng Yin
- Beijing Chest Hospital, Capital Medical University, Beijing, China
- Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Hui Jiang
- Beijing Chest Hospital, Capital Medical University, Beijing, China
- Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Howard E. Takiff
- Instituto Venezolano de Investigaciones Científicas, Instituto Venezolano de Investigaciones Científicas, Caracas, Venezuela
| | - Qian Gao
- Key Laboratory of Medical Molecular Virology (Ministry of Education/National Health Commission/Chinese Academy of Medical Sciences), School of Basic Medical Sciences, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
| | - Qingyun Liu
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Weimin Li
- Beijing Chest Hospital, Capital Medical University, Beijing, China
- Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 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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Vargas R, Luna MJ, Freschi L, Marin M, Froom R, Murphy KC, Campbell EA, Ioerger TR, Sassetti CM, Farhat MR. Phase variation as a major mechanism of adaptation in Mycobacterium tuberculosis complex. Proc Natl Acad Sci U S A 2023; 120:e2301394120. [PMID: 37399390 PMCID: PMC10334774 DOI: 10.1073/pnas.2301394120] [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: 02/05/2023] [Accepted: 05/03/2023] [Indexed: 07/05/2023] Open
Abstract
Phase variation induced by insertions and deletions (INDELs) in genomic homopolymeric tracts (HT) can silence and regulate genes in pathogenic bacteria, but this process is not characterized in MTBC (Mycobacterium tuberculosis complex) adaptation. We leverage 31,428 diverse clinical isolates to identify genomic regions including phase-variants under positive selection. Of 87,651 INDEL events that emerge repeatedly across the phylogeny, 12.4% are phase-variants within HTs (0.02% of the genome by length). We estimated the in-vitro frameshift rate in a neutral HT at 100× the neutral substitution rate at [Formula: see text] frameshifts/HT/year. Using neutral evolution simulations, we identified 4,098 substitutions and 45 phase-variants to be putatively adaptive to MTBC (P < 0.002). We experimentally confirm that a putatively adaptive phase-variant alters the expression of espA, a critical mediator of ESX-1-dependent virulence. Our evidence supports the hypothesis that phase variation in the ESX-1 system of MTBC can act as a toggle between antigenicity and survival in the host.
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Affiliation(s)
- Roger Vargas
- Center for Computational Biomedicine, Harvard Medical School, Boston, MA02115
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA02115
| | - Michael J. Luna
- Department of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School, Worcester, MA01655
| | - Luca Freschi
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA02115
| | - Maximillian Marin
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA02115
| | - Ruby Froom
- Laboratory of Molecular Biophysics, The Rockefeller University, New York, NY10065
- Laboratory of Host-Pathogen Biology, The Rockefeller University, New York, NY10065
| | - Kenan C. Murphy
- Department of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School, Worcester, MA01655
| | | | - Thomas R. Ioerger
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX77843
| | - Christopher M. Sassetti
- Department of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School, Worcester, MA01655
| | - Maha Reda Farhat
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA02115
- Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA02114
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Dekhil N, Mardassi H. Genomic changes underpinning the emergence of a successful Mycobacterium tuberculosis Latin American and Mediterranean clonal complex. Front Microbiol 2023; 14:1159994. [PMID: 37425998 PMCID: PMC10325029 DOI: 10.3389/fmicb.2023.1159994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 05/26/2023] [Indexed: 07/11/2023] Open
Abstract
Introduction The Latin American and Mediterranean sublineage (L4.3/LAM) is the most common generalist sublineage of Mycobacterium tuberculosis lineage 4 (L4), yet certain L4.3/LAM genotypes appear to be confined to particular geographic regions. This is typically the case of a L4.3/LAM clonal complex (CC), TUN4.3_CC1, which is the most preponderant in Tunisia (61.5% of L4.3/LAM). Methods Here, we used whole-genome sequencing data of 346 globally distributed L4 clinical strains, including 278 L4.3/LAM isolates, to reconstruct the evolutionary history of TUN4.3_CC1 and delineate critical genomic changes underpinning its success. Results and Discussion Phylogenomic coupled to phylogeographic analyses indicated that TUN4.3_CC1 has evolved locally, being confined mainly to North Africa. Maximum likelihood analyses using the site and branch-site models of the PAML package disclosed strong evidence of positive selection in the gene category "cell wall and cell processes" of TUN4.3_CC1. Collectively, the data indicate that TUN4.3_CC1 has inherited several mutations, which could have potentially contributed to its evolutionary success. Of particular interest are amino acid replacements at the esxK and eccC2 genes of the ESX/Type VII secretion system, which were found to be specific to TUN4.3_CC1, being common to almost all isolates. Because of its homoplastic nature, the esxK mutation could potentially have endowed TUN4.3_CC1 with a selective advantage. Moreover, we noticed the occurrence of additional, previously described homoplasic nonsense mutations in ponA1 and Rv0197. The mutation in the latter gene, a putative oxido-reductase, has previously been shown to be correlated with enhanced transmissibility in vivo. In sum, our findings unveiled several features underpinning the success of a locally evolved L4.3/LAM clonal complex, lending further support to the critical role of genes encoded by the ESX/type VII secretion system.
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Lin Y, Du Y, Shen H, Guo Y, Wang T, Lai K, Zhang D, Zheng G, Wu G, Lei Y, Liu J. Transmission of Mycobacterium tuberculosis in schools: a molecular epidemiological study using whole-genome sequencing in Guangzhou, China. Front Public Health 2023; 11:1156930. [PMID: 37250072 PMCID: PMC10219607 DOI: 10.3389/fpubh.2023.1156930] [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: 02/02/2023] [Accepted: 04/18/2023] [Indexed: 05/31/2023] Open
Abstract
Background China is a country with a high burden of tuberculosis (TB). TB outbreaks are frequent in schools. Thus, understanding the transmission patterns is crucial for controlling TB. Method In this genomic epidemiological study, the conventional epidemiological survey data combined with whole-genome sequencing was used to assess the genotypic distribution and transmission characteristics of Mycobacterium tuberculosis strains isolated from patients with TB attending schools during 2015 to 2019 in Guangzhou, China. Result The TB incidence was mainly concentrated in regular secondary schools and technical and vocational schools. The incidence of drug resistance among the students was 16.30% (22/135). The phylogenetic tree showed that 79.26% (107/135) and 20.74% (28/135) of the strains belonged to lineage 2 (Beijing genotype) and lineage 4 (Euro-American genotype), respectively. Among the 135 isolates, five clusters with genomic distance within 12 single nucleotide polymorphisms were identified; these clusters included 10 strains, accounting for an overall clustering rate of 7.4% (10/135), which showed a much lower transmission index. The distance between the home or school address and the interval time of symptom onset or diagnosis indicated that campus dissemination and community dissemination may be existed both, and community dissemination is the main. Conclusion and recommendation TB cases in Guangzhou schools were mainly disseminated and predominantly originated from community transmission. Accordingly, surveillance needs to be strengthened to stop the spread of TB in schools.
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Affiliation(s)
- Ying Lin
- Department of Tuberculosis Control, Guangzhou Chest Hospital, Guangzhou, China
| | - Yuhua Du
- Department of Tuberculosis Control, Guangzhou Chest Hospital, Guangzhou, China
| | - Hongcheng Shen
- Department of Preventive Health Care, Guangzhou Chest Hospital, Guangzhou, China
| | - Yangfeng Guo
- Guangzhou Primary and Secondary School Health and Health Promotion Center, Guangzhou, China
| | - Ting Wang
- Department of Tuberculosis Control, Guangzhou Chest Hospital, Guangzhou, China
| | - Keng Lai
- Department of Tuberculosis Control, Guangzhou Chest Hospital, Guangzhou, China
| | - Danni Zhang
- Academy of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Guangmin Zheng
- Academy of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Guifeng Wu
- Department of Tuberculosis Control, Guangzhou Chest Hospital, Guangzhou, China
| | - Yu Lei
- Department of Tuberculosis Control, Guangzhou Chest Hospital, Guangzhou, China
| | - Jianxiong Liu
- Department of Tuberculosis Control, Guangzhou Chest Hospital, Guangzhou, China
- State Key Laboratory of Respiratory Disease, Guangzhou, China
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Stanley S, Spaulding CN, Liu Q, Chase MR, Ha DTM, Thai PVK, Lan NH, Thu DDA, Quang NL, Brown J, Hicks ND, Wang X, Marin M, Howard NC, Vickers AJ, Karpinski WM, Chao MC, Farhat MR, Caws M, Dunstan SJ, Thuong NTT, Fortune SM. High-throughput phenogenotyping of Mycobacteria tuberculosis clinical strains reveals bacterial determinants of treatment outcomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.09.536166. [PMID: 37090677 PMCID: PMC10120664 DOI: 10.1101/2023.04.09.536166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Background Combatting the tuberculosis (TB) epidemic caused by Mycobacterium tuberculosis ( Mtb ) necessitates a better understanding of the factors contributing to patient clinical outcomes and transmission. While host and environmental factors have been evaluated, the impact of Mtb genetic background and phenotypic diversity is underexplored. Previous work has made associations between Mtb genetic lineages and some clinical and epidemiological features, but the bacterial traits underlying these connections are largely unknown. Methods We developed a high-throughput functional genomics platform for defining genotype-phenotype relationships across a panel of Mtb clinical isolates. These phenotypic fitness profiles function as intermediate traits which can be linked to Mtb genetic variants and associated with clinical and epidemiological outcomes. We applied this approach to a collection of 158 Mtb strains from a study of Mtb transmission in Ho Chi Minh City, Vietnam. Mtb strains were genetically tagged in multiplicate, which allowed us to pool the strains and assess in vitro competitive fitness using deep sequencing across a set of 14 host-relevant antibiotic and metabolic conditions. Phylogenetic and monogenic associations with these intermediate traits were identified and then associated with clinical outcomes. Findings Mtb clinical strains have a broad range of growth and drug response dynamics that can be clustered by their phylogenetic relationships. We identified novel monogenic associations with Mtb fitness in various metabolic and antibiotic conditions. Among these, we find that mutations in Rv1339 , a phosphodiesterase, which were identified through their association with slow growth in glycerol, are further associated with treatment failure. We also identify a previously uncharacterized subclade of Lineage 1 strains (L1.1.1.1) that is phenotypically distinguished by slow growth under most antibiotic and metabolic stress conditions in vitro . This clade is associated with cavitary disease, treatment failure, and demonstrates increased transmission potential. Interpretation High-throughput phenogenotyping of Mtb clinical strains enabled bacterial intermediate trait identification that can provide a mechanistic link between Mtb genetic variation and patient clinical outcomes. Mtb strains associated with cavitary disease, treatment failure, and transmission potential display intermediate phenotypes distinguished by slow growth under various antibiotic and metabolic conditions. These data suggest that Mtb growth regulation is an adaptive advantage for host bacterial success in human populations, in at least some circumstances. These data further suggest markers for the underlying bacterial processes that govern these clinical outcomes. Funding National Institutes of Allergy and Infectious Diseases: P01 AI132130 (SS, SMF); P01 AI143575 (XW, SMF); U19 AI142793 (QL, SMF); 5T32AI132120-03 (SS); 5T32AI132120-04 (SS); 5T32AI049928-17 (SS) Wellcome Trust Fellowship in Public Health and Tropical Medicine: 097124/Z/11/Z (NTTT) National Health and Medical Research Council (NHMRC)/A*STAR joint call: APP1056689 (SJD) The funding sources had no involvement in study methodology, data collection, analysis, and interpretation nor in the writing or submission of the manuscript. Research in context Evidence before this study: We used different combinations of the words mycobacterium tuberculosis, tuberculosis, clinical strains, intermediate phenotypes, genetic barcoding, phenogenomics, cavitary disease, treatment failure, and transmission to search the PubMed database for all studies published up until January 20 th , 2022. We only considered English language publications, which biases our search. Previous work linking Mtb determinants to clinical or epidemiological data has made associations between bacterial lineage, or less frequently, genetic polymorphisms to in vitro or in vivo models of pathogenesis, transmission, and clinical outcomes such as cavitary disease, treatment failure, delayed culture conversion, and severity. Many of these studies focus on the global pandemic Lineage 2 and Lineage 4 Mtb strains due in part to a deletion in a polyketide synthase implicated in host-pathogen interactions. There are a number of Mtb GWAS studies that have led to novel genetic determinants of in vitro drug resistance and tolerance. Previous Mtb GWAS analyses with clinical outcomes did not experimentally test any predicted phenotypes of the clinical strains. Published laboratory-based studies of Mtb clinical strains involve relatively small numbers of strains, do not identify the genetic basis of relevant phenotypes, or link findings to the corresponding clinical outcomes. There are two recent studies of other pathogens that describe phenogenomic analyses. One study of 331 M. abscessus clinical strains performed one-by-one phenotyping to identify bacterial features associated with clearance of infection and another details a competition experiment utilizing three barcoded Plasmodium falciparum clinical isolates to assay antimalarial fitness and resistance. Added value of this study: We developed a functional genomics platform to perform high-throughput phenotyping of Mtb clinical strains. We then used these phenotypes as intermediate traits to identify novel bacterial genetic features associated with clinical outcomes. We leveraged this platform with a sample of 158 Mtb clinical strains from a cross sectional study of Mtb transmission in Ho Chi Minh City, Vietnam. To enable high-throughput phenotyping of large numbers of Mtb clinical isolates, we applied a DNA barcoding approach that has not been previously utilized for the high-throughput analysis of Mtb clinical strains. This approach allowed us to perform pooled competitive fitness assays, tracking strain fitness using deep sequencing. We measured the replicative fitness of the clinical strains in multiplicate under 14 metabolic and antibiotic stress condition. To our knowledge, this is the largest phenotypic screen of Mtb clinical isolates to date. We performed bacterial GWAS to delineate the Mtb genetic variants associated with each fitness phenotype, identifying monogenic associations with several conditions. We then defined Mtb phenotypic and genetic features associated with clinical outcomes. We find that a subclade of Mtb strains, defined by variants largely involved in fatty acid metabolic pathways, share a universal slow growth phenotype that is associated with cavitary disease, treatment failure and increased transmission potential in Vietnam. We also find that mutations in Rv1339 , a poorly characterized phosphodiesterase, also associate with slow growth in vitro and with treatment failure in patients. Implications of all the available evidence: Phenogenomic profiling demonstrates that Mtb strains exhibit distinct growth characteristics under metabolic and antibiotic stress conditions. These fitness profiles can serve as intermediate traits for GWAS and association with clinical outcomes. Intermediate phenotyping allows us to examine potential processes by which bacterial strain differences contribute to clinical outcomes. Our study identifies clinical strains with slow growth phenotypes under in vitro models of antibiotic and host-like metabolic conditions that are associated with adverse clinical outcomes. It is possible that the bacterial intermediate phenotypes we identified are directly related to the mechanisms of these outcomes, or they may serve as markers for the causal yet unidentified bacterial determinants. Via the intermediate phenotyping, we also discovered a surprising diversity in Mtb responses to the new anti-mycobacterial drugs that target central metabolic processes, which will be important in considering roll-out of these new agents. Our study and others that have identified Mtb determinants of TB clinical and epidemiological phenotypes should inform efforts to improve diagnostics and drug regimen design.
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Du DH, Geskus RB, Zhao Y, Codecasa LR, Cirillo DM, van Crevel R, Pascapurnama DN, Chaidir L, Niemann S, Diel R, Omar SV, Grandjean L, Rokadiya S, Ortitz AT, Lân NH, Hà ÐTM, Smith EG, Robinson E, Dedicoat M, Nhat LTH, Thwaites GE, Van LH, Thuong NTT, Walker TM. The effect of M. tuberculosis lineage on clinical phenotype. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.14.23287284. [PMID: 36993190 PMCID: PMC10055556 DOI: 10.1101/2023.03.14.23287284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Eight lineages of Mycobacterium tuberculosis sensu stricto are described. Single-country or small observational data suggest differences in clinical phenotype between lineages. We present strain lineage and clinical phenotype data from 12,246 patients from 3 low-incidence and 5 high-incidence countries. We used multivariable logistic regression to explore the effect of lineage on site of disease and on cavities on chest radiography, given pulmonary TB; multivariable multinomial logistic regression to investigate types of extra-pulmonary TB, given lineage; and accelerated failure time and Cox proportional-hazards models to explore the effect of lineage on time to smear and culture-conversion. Mediation analyses quantified the direct effects of lineage on outcomes. Pulmonary disease was more likely among patients with lineage(L) 2, L3 or L4, than L1 (adjusted odds ratio (aOR) 1.79, (95% confidence interval 1.49-2.15), p<0.001; aOR=1.40(1.09-1.79), p=0.007; aOR=2.04(1.65-2.53), p<0.001, respectively). Among patients with pulmonary TB, those with L1 had greater risk of cavities on chest radiography versus those with L2 (aOR=0.69(0.57-0.83), p<0.001) and L4 strains (aOR=0.73(0.59-0.90), p=0.002). L1 strains were more likely to cause osteomyelitis among patients with extra-pulmonary TB, versus L2-4 (p=0.033, p=0.008 and p=0.049 respectively). Patients with L1 strains showed shorter time-to-sputum smear conversion than for L2. Causal mediation analysis showed the effect of lineage in each case was largely direct. The pattern of clinical phenotypes seen with L1 strains differed from modern lineages (L2-4). This has implications for clinical management and could influence clinical trial selection strategies.
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Affiliation(s)
- Duc Hong Du
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Ronald B Geskus
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - Luigi Ruffo Codecasa
- Regional TB Reference Centre/Istituto Villa Marelli- ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
| | | | - Reinout van Crevel
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Lidya Chaidir
- Division of Microbiology, Department of Biomedical Science, Faculty of Medicine, Padjadjaran University, Bandung, West Java, Indonesia
| | - Stefan Niemann
- Research Center Borstel, Germany
- German Center for Infection Research, partner site Hamburg-Lübeck-Borstel-Riems, Germany
| | - Roland Diel
- University Hospital Schleswig-Holstein, Campus Kiel, Germany
- Lung Clinic Grosshansdorf, Germany, Airway Disease Center North (ARCN), German Center for Lung Research (DZL)
| | | | | | | | | | | | | | - E Grace Smith
- TB Unit and National Mycobacterial Reference Service, UK Health Security Agency, UK
| | - Esther Robinson
- TB Unit and National Mycobacterial Reference Service, UK Health Security Agency, UK
| | - Martin Dedicoat
- TB Unit and National Mycobacterial Reference Service, UK Health Security Agency, UK
- University Hospitals Birmingham NHS Foundation Trust, UK
| | | | - Guy E Thwaites
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Le Hong Van
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Nguyen Thuy Thuong Thuong
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Timothy M Walker
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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29
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Ashton PM, Cha J, Anscombe C, Thuong NTT, Thwaites GE, Walker TM. Distribution and origins of Mycobacterium tuberculosis L4 in Southeast Asia. Microb Genom 2023; 9:mgen000955. [PMID: 36729036 PMCID: PMC9997747 DOI: 10.1099/mgen.0.000955] [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: 08/01/2022] [Accepted: 12/21/2022] [Indexed: 02/03/2023] Open
Abstract
Molecular and genomic studies have revealed that Mycobacterium tuberculosis Lineage 4 (L4, Euro-American lineage) emerged in Europe before becoming distributed around the globe by trade routes, colonial migration and other historical connections. Although L4 accounts for tens or hundreds of thousands of tuberculosis (TB) cases in multiple Southeast Asian countries, phylogeographical studies have either focused on a single country or just included Southeast Asia as part of a global analysis. Therefore, we interrogated public genomic data to investigate the historical patterns underlying the distribution of L4 in Southeast Asia and surrounding countries. We downloaded 6037 genomes associated with 29 published studies, focusing on global analyses of L4 and Asian studies of M. tuberculosis. We identified 2256 L4 genomes including 968 from Asia. We show that 81 % of L4 in Thailand, 51 % of L4 in Vietnam and 9 % of L4 in Indonesia belong to sub-lineages of L4 that are rarely seen outside East and Southeast Asia (L4.2.2, L4.4.2 and L4.5). These sub-lineages have spread between East and Southeast Asian countries, with no recent European ancestor. Although there is considerable uncertainty about the exact direction and order of intra-Asian M. tuberculosis dispersal, due to differing sampling frames between countries, our analysis suggests that China may be the intermediate location between Europe and Southeast Asia for two of the three predominantly East and Southeast Asian L4 sub-lineages (L4.2.2 and L4.5). This new perspective on L4 in Southeast Asia raises the possibility of investigating host population-specific evolution and highlights the need for more structured sampling from Southeast Asian countries to provide more certainty of the historical and current routes of dispersal.
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Affiliation(s)
- Philip M. Ashton
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Jaeyoon Cha
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
| | - Catherine Anscombe
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Nguyen T. T. Thuong
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Guy E. Thwaites
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Timothy M. Walker
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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Hurtado-Páez U, Álvarez Zuluaga N, Arango Isaza RE, Contreras-Moreira B, Rouzaud F, Robledo J. Pan-genome association study of Mycobacterium tuberculosis lineage-4 revealed specific genes related to the high and low prevalence of the disease in patients from the North-Eastern area of Medellín, Colombia. Front Microbiol 2023; 13:1076797. [PMID: 36687645 PMCID: PMC9846648 DOI: 10.3389/fmicb.2022.1076797] [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: 10/22/2022] [Accepted: 12/12/2022] [Indexed: 01/06/2023] Open
Abstract
Mycobacterium tuberculosis (Mtb) lineage 4 is responsible for the highest burden of tuberculosis (TB) worldwide. This lineage has been the most prevalent lineage in Colombia, especially in the North-Eastern (NE) area of Medellin, where it has been shown to have a high prevalence of LAM9 SIT42 and Haarlem1 SIT62 sublineages. There is evidence that regardless of environmental factors and host genetics, differences among sublineages of Mtb strains play an important role in the course of infection and disease. Nevertheless, the genetic basis of the success of a sublineage in a specific geographic area remains uncertain. We used a pan-genome-wide association study (pan-GWAS) of 47 Mtb strains isolated from NE Medellin between 2005 and 2008 to identify the genes responsible for the phenotypic differences among high and low prevalence sublineages. Our results allowed the identification of 12 variants in 11 genes, of which 4 genes showed the strongest association to low prevalence (mmpL12, PPE29, Rv1419, and Rv1762c). The first three have been described as necessary for invasion and intracellular survival. Polymorphisms identified in low prevalence isolates may suggest related to a fitness cost of Mtb, which might reflect a decrease in their capacity to be transmitted or to cause an active infection. These results contribute to understanding the success of some sublineages of lineage-4 in a specific geographical area.
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Affiliation(s)
- Uriel Hurtado-Páez
- Corporación para Investigaciones Biológicas (CIB), Medellín, Colombia,*Correspondence: Uriel Hurtado-Páez,
| | | | - Rafael Eduardo Arango Isaza
- Corporación para Investigaciones Biológicas (CIB), Medellín, Colombia,Facultad de Ciencias, Universidad Nacional de Colombia (UNAL), Medellín, Colombia
| | - Bruno Contreras-Moreira
- Estación Experimental de Aula Dei–Consejo Superior de Investigaciones Científicas (EEAD-CSIC), Zaragoza, Spain,Fundación ARAID, Zaragoza, Spain
| | | | - Jaime Robledo
- Corporación para Investigaciones Biológicas (CIB), Medellín, Colombia,Escuela de Ciencias de la Salud, Universidad Pontificia Bolivariana (UPB), Medellín, Colombia
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31
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Ascher DB, Kaminskas LM, Myung Y, Pires DEV. Using Graph-Based Signatures to Guide Rational Antibody Engineering. Methods Mol Biol 2023; 2552:375-397. [PMID: 36346604 DOI: 10.1007/978-1-0716-2609-2_21] [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] [Indexed: 06/16/2023]
Abstract
Antibodies are essential experimental and diagnostic tools and as biotherapeutics have significantly advanced our ability to treat a range of diseases. With recent innovations in computational tools to guide protein engineering, we can now rationally design better antibodies with improved efficacy, stability, and pharmacokinetics. Here, we describe the use of the mCSM web-based in silico suite, which uses graph-based signatures to rapidly identify the structural and functional consequences of mutations, to guide rational antibody engineering to improve stability, affinity, and specificity.
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Affiliation(s)
- David B Ascher
- Structural Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Parkville, VIC, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Department of Biochemistry, Cambridge University, Cambridge, UK
- School of Chemistry and Molecular Biosciences, University of Queensland, St Lucia, Queensland, Australia
| | - Lisa M Kaminskas
- School of Biological Sciences, University of Queensland, St Lucia, QLD, Australia
| | - Yoochan Myung
- Structural Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Parkville, VIC, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- School of Chemistry and Molecular Biosciences, University of Queensland, St Lucia, Queensland, Australia
| | - Douglas E V Pires
- Structural Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Parkville, VIC, Australia.
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
- School of Computing and Information Systems, University of Melbourne, Parkville, VIC, Australia.
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32
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Renardy ME, Gillen C, Yang Z, Mukasa L, Bates J, Butler R, Kirschner DE. Disease phenotypic and geospatial features vary across genetic lineages for Tuberculosis within Arkansas, 2010-2020. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0001580. [PMID: 36963087 PMCID: PMC10022325 DOI: 10.1371/journal.pgph.0001580] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 01/16/2023] [Indexed: 02/25/2023]
Abstract
Tuberculosis (TB) elimination in the United States remains elusive, and community-specific, localized intervention strategies may be necessary to meet elimination goals. A better understanding of the genotypic diversity of Mtb, the population subgroups affected by different TB strains, and differences in disease presentation associated with these strains can aid in identifying risk groups and designing tailored interventions. We analyze TB incidence and genotype data from all Arkansas counties over an 11-year time span from 2010 through 2020. We use statistical methods and geographic information systems (GIS) to identify demographic and disease phenotypic characteristics that are associated with different Mtb genetic lineages in the study area. We found the following variables to be significantly associated with genetic lineage (p<0.05): patient county, patient birth country, patient ethnicity, race, IGRA result, disease site, chest X-ray result, whether or not a case was identified as part of a cluster, patient age, occupation risk, and date arrived in the US. Different Mtb lineages affect different subpopulations in Arkansas. Lineage 4 (EuroAmerican) and Lineage 2 (East Asian) are most prevalent, although the spatial distributions differ substantially, and lineage 2 (East Asian) is more frequently associated with case clusters. The Marshallese remain a particularly high-risk group for TB in Arkansas.
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Affiliation(s)
- Marissa E Renardy
- Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Craig Gillen
- Department of Biology, AdventHealth University, Orlando, FL, United States of America
| | - Zhenhua Yang
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Leonard Mukasa
- Arkansas Department of Health, Little Rock, AR, United States of America
- Epidemiology Department in the, Boozman College of Public Health at the University of Arkansas Center for Health Sciences, Little Rock, AR, United States of America
| | - Joseph Bates
- Arkansas Department of Health, Little Rock, AR, United States of America
- Epidemiology Department in the, Boozman College of Public Health at the University of Arkansas Center for Health Sciences, Little Rock, AR, United States of America
| | - Russ Butler
- Department of Biology, AdventHealth University, Orlando, FL, United States of America
| | - Denise E Kirschner
- Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
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Distribution of Mycobacterium tuberculosis Lineages and Drug Resistance in Upper Myanmar. Trop Med Infect Dis 2022; 7:tropicalmed7120448. [PMID: 36548703 PMCID: PMC9781755 DOI: 10.3390/tropicalmed7120448] [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: 11/14/2022] [Revised: 12/09/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022] Open
Abstract
Mycobacterium tuberculosis complex (MTBC) is divided into 9 whole genome sequencing (WGS) lineages. Among them, lineages 1−4 are widely distributed. Multi-drug resistant tuberculosis (MDR-TB) is a major public health threat. For effective TB control, there is a need to obtain genetic information on lineages of Mycobacterium tuberculosis (Mtb) and to understand distribution of lineages and drug resistance. This study aimed to describe the distribution of major lineages and drug resistance patterns of Mtb in Upper Myanmar. This was a cross-sectional study conducted with 506 sequenced isolates. We found that the most common lineage was lineage 2 (n = 223, 44.1%). The most common drug resistance mutation found was streptomycin (n = 44, 8.7%). Lineage 2 showed a higher number of MDR-TB compared to other lineages. There were significant associations between lineages of Mtb and drug resistance patterns, and between lineages and geographical locations of Upper Myanmar (p value < 0.001). This information on the distribution of Mtb lineages across the geographical areas will support a lot for the better understanding of TB transmission and control in Myanmar and other neighboring countries. Therefore, closer collaboration in cross border tuberculosis control is recommended.
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Saelens JW, Sweeney MI, Viswanathan G, Xet-Mull AM, Jurcic Smith KL, Sisk DM, Hu DD, Cronin RM, Hughes EJ, Brewer WJ, Coers J, Champion MM, Champion PA, Lowe CB, Smith CM, Lee S, Stout JE, Tobin DM. An ancestral mycobacterial effector promotes dissemination of infection. Cell 2022; 185:4507-4525.e18. [PMID: 36356582 PMCID: PMC9691622 DOI: 10.1016/j.cell.2022.10.019] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 08/27/2022] [Accepted: 10/16/2022] [Indexed: 11/11/2022]
Abstract
The human pathogen Mycobacterium tuberculosis typically causes lung disease but can also disseminate to other tissues. We identified a M. tuberculosis (Mtb) outbreak presenting with unusually high rates of extrapulmonary dissemination and bone disease. We found that the causal strain carried an ancestral full-length version of the type VII-secreted effector EsxM rather than the truncated version present in other modern Mtb lineages. The ancestral EsxM variant exacerbated dissemination through enhancement of macrophage motility, increased egress of macrophages from established granulomas, and alterations in macrophage actin dynamics. Reconstitution of the ancestral version of EsxM in an attenuated modern strain of Mtb altered the migratory mode of infected macrophages, enhancing their motility. In a zebrafish model, full-length EsxM promoted bone disease. The presence of a derived nonsense variant in EsxM throughout the major Mtb lineages 2, 3, and 4 is consistent with a role for EsxM in regulating the extent of dissemination.
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Affiliation(s)
- Joseph W Saelens
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Mollie I Sweeney
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Gopinath Viswanathan
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Ana María Xet-Mull
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Kristen L Jurcic Smith
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Dana M Sisk
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Daniel D Hu
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Rachel M Cronin
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Erika J Hughes
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - W Jared Brewer
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Jörn Coers
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA; Department of Immunology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Matthew M Champion
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA; Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Patricia A Champion
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA; Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Craig B Lowe
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Clare M Smith
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Sunhee Lee
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA; Department of Medicine, Duke University School of Medicine, Durham, NC 27710, USA; Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX 77555, USA.
| | - Jason E Stout
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, USA; Division of Infectious Diseases and International Health, Duke University School of Medicine, Durham, NC 27710, USA.
| | - David M Tobin
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA; Department of Immunology, Duke University School of Medicine, Durham, NC 27710, USA.
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35
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Dale K, Globan M, Horan K, Sherry N, Ballard S, Tay EL, Bittmann S, Meagher N, Price DJ, Howden BP, Williamson DA, Denholm J. Whole genome sequencing for tuberculosis in Victoria, Australia: A genomic implementation study from 2017 to 2020. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 28:100556. [PMID: 36034164 PMCID: PMC9405109 DOI: 10.1016/j.lanwpc.2022.100556] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
BACKGROUND Whole genome sequencing (WGS) is increasingly used by tuberculosis (TB) programs to monitor Mycobacterium tuberculosis (Mtb) transmission. We aimed to characterise the molecular epidemiology of TB and Mtb transmission in the low-incidence setting of Victoria, Australia, and assess the utility of WGS. METHODS WGS was performed on all first Mtb isolates from TB cases from 2017 to 2020. Potential clusters (≤12 single nucleotide polymorphisms [SNPs]) were investigated for epidemiological links. Transmission events in highly-related (≤5 SNPs) clusters were classified as likely or possible, based on the presence or absence of an epidemiological link, respectively. Case characteristics and transmission settings (as defined by case relationship) were summarised. Poisson regression was used to examine associations with secondary case number. FINDINGS Of 1844 TB cases, 1276 (69.2%) had sequenced isolates, with 182 (14.2%) in 54 highly-related clusters, 2-40 cases in size. Following investigation, 140 cases (11.0% of sequenced) were classified as resulting from likely/possible local-transmission, including 82 (6.4%) for which transmission was likely. Common identified transmission settings were social/religious (26.4%), household (22.9%) and family living in different households (7.1%), but many were uncertain (41.4%). While household transmission featured in many clusters (n = 24), clusters were generally smaller (median = 3 cases) than the fewer that included transmission in social/religious settings (n = 12, median = 7.5 cases). Sputum-smear-positivity was associated with higher secondary case numbers. INTERPRETATION WGS results suggest Mtb transmission commonly occurs outside the household in our low-incidence setting. Further work is required to optimise the use of WGS in public health management of TB. FUNDING The Victorian Tuberculosis Program receives block funding for activities including case management and contact tracing from the Victorian Department of Health. No specific funding for this report was received by manuscript authors or the Victorian Tuberculosis Program, and the funders had no role in the study design, data collection, data analysis, interpretation or report writing.
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Affiliation(s)
- Katie Dale
- Victorian Tuberculosis Program, Melbourne Health, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Maria Globan
- Victorian Infectious Diseases Reference Laboratory (VIDRL), at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Kristy Horan
- Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Norelle Sherry
- Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Susan Ballard
- Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Ee Laine Tay
- Communicable Disease Epidemiology and Surveillance, Health Protection Branch, Public Health Division, Department of Health, Victoria, Australia
| | - Simone Bittmann
- Victorian Tuberculosis Program, Melbourne Health, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Niamh Meagher
- Department of Infectious Diseases at the Doherty Institute for Infection & Immunity, The University of Melbourne and Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - David J. Price
- Department of Infectious Diseases at the Doherty Institute for Infection & Immunity, The University of Melbourne and Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Benjamin P. Howden
- Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
- Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Deborah A. Williamson
- Victorian Infectious Diseases Reference Laboratory (VIDRL), at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Justin Denholm
- Victorian Tuberculosis Program, Melbourne Health, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
- Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
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Shu Q, Rajagopal M, Fan J, Zhan L, Kong X, He Y, Rotcheewaphan S, Lyon CJ, Sha W, Zelazny AM, Hu T. Peptidomic analysis of mycobacterial secreted proteins enables species identification. VIEW 2022. [DOI: 10.1002/viw.20210019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Affiliation(s)
- Qingbo Shu
- Center for Cellular and Molecular Diagnostics Department of Biochemistry and Molecular Biology School of Medicine Tulane University New Orleans Louisiana USA
| | - Meena Rajagopal
- Department of Laboratory Medicine, Clinical Center National Institutes of Health Bethesda Maryland USA
| | - Jia Fan
- Center for Cellular and Molecular Diagnostics Department of Biochemistry and Molecular Biology School of Medicine Tulane University New Orleans Louisiana USA
| | - Lingpeng Zhan
- Center for Cellular and Molecular Diagnostics Department of Biochemistry and Molecular Biology School of Medicine Tulane University New Orleans Louisiana USA
| | - Xiangxing Kong
- Center for Cellular and Molecular Diagnostics Department of Biochemistry and Molecular Biology School of Medicine Tulane University New Orleans Louisiana USA
| | - Yifan He
- Clinic and Research Center of Tuberculosis, Shanghai Pulmonary Hospital Tongji University School of Medicine Shanghai People's Republic of China
| | - Suwatchareeporn Rotcheewaphan
- Department of Laboratory Medicine, Clinical Center National Institutes of Health Bethesda Maryland USA
- Department of Microbiology, Faculty of Medicine Chulalongkorn University Bangkok Thailand
| | - Christopher J. Lyon
- Center for Cellular and Molecular Diagnostics Department of Biochemistry and Molecular Biology School of Medicine Tulane University New Orleans Louisiana USA
| | - Wei Sha
- Clinic and Research Center of Tuberculosis, Shanghai Pulmonary Hospital Tongji University School of Medicine Shanghai People's Republic of China
| | - Adrian M. Zelazny
- Department of Laboratory Medicine, Clinical Center National Institutes of Health Bethesda Maryland USA
| | - Tony Hu
- Center for Cellular and Molecular Diagnostics Department of Biochemistry and Molecular Biology School of Medicine Tulane University New Orleans Louisiana USA
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Shanmugam SK, Kumar N, Sembulingam T, Ramalingam SB, Selvaraj A, Rajendhiran U, Solaiyappan S, Tripathy SP, Natrajan M, Chandrasekaran P, Swaminathan S, Parkhill J, Peacock SJ, Ranganathan UDK. Mycobacterium tuberculosis Lineages Associated with Mutations and Drug Resistance in Isolates from India. Microbiol Spectr 2022; 10:e0159421. [PMID: 35442078 PMCID: PMC9241780 DOI: 10.1128/spectrum.01594-21] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Accepted: 03/03/2022] [Indexed: 12/12/2022] Open
Abstract
Current knowledge on resistance-conferring determinants in Mycobacterium tuberculosis is biased toward globally dominant lineages 2 and 4. In contrast, lineages 1 and 3 are predominant in India. In this study, we performed whole-genome sequencing of 498 MDR M. tuberculosis isolates from India to determine the prevalence of drug resistance mutations and to understand the genomic diversity. A retrospective collection of 498 M. tuberculosis isolates submitted to the National Institute for Research in Tuberculosis for phenotypic susceptibility testing between 2014 to 2016 were sequenced. Genotypic resistance prediction was performed using known resistance-conferring determinants. Genotypic and phenotypic results for 12 antituberculosis drugs were compared, and sequence data were explored to characterize lineages and their association with drug resistance. Four lineages were identified although lineage 1 predominated (43%). The sensitivity of prediction for isoniazid and rifampicin was 92% and 98%, respectively. We observed lineage-specific variations in the proportion of isolates with resistance-conferring mutations, with drug resistance more common in lineages 2 and 3. Disputed mutations (codons 430, 435, 445, and 452) in the rpoB gene were more common in isolates other than lineage 2. Phylogenetic analysis and pairwise SNP difference revealed high genetic relatedness of lineage 2 isolates. WGS based resistance prediction has huge potential, but knowledge of regional and national diversity is essential to achieve high accuracy for resistance prediction. IMPORTANCE Current knowledge on resistance-conferring determinants in Mycobacterium tuberculosis is biased toward globally dominant lineages 2 and 4. In contrast, lineages 1 and 3 are predominant in India. We performed whole-genome sequencing of 498 MDR M. tuberculosis isolates from India to determine the prevalence of drug resistance mutations and to understand genomic diversity. Four lineages were identified although lineage 1 predominated (43%). The sensitivity of prediction for isoniazid and rifampicin was 92% and 98%, respectively. We observed lineage-specific variations in the proportion of isolates with resistance-conferring mutations, with drug resistance more common in lineages 2 and 3. Disputed mutations (codons 430, 435, 445, and 452) in the rpoB gene were more common in isolates other than lineage 2. Phylogenetic analysis and pairwise SNP difference revealed high genetic relatedness of lineage 2 isolates. WGS based resistance prediction has huge potential, but knowledge of regional and national diversity is essential to achieve high accuracy for resistance prediction.
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Affiliation(s)
- Siva Kumar Shanmugam
- Indian Council of Medical Research (ICMR)-National Institute for Research in Tuberculosis, Chennai, India
| | - Narender Kumar
- Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom
| | - Tamilzhalagan Sembulingam
- Indian Council of Medical Research (ICMR)-National Institute for Research in Tuberculosis, Chennai, India
| | - Suresh Babu Ramalingam
- Indian Council of Medical Research (ICMR)-National Institute for Research in Tuberculosis, Chennai, India
| | - Ashok Selvaraj
- Indian Council of Medical Research (ICMR)-National Institute for Research in Tuberculosis, Chennai, India
| | - Udhayakumar Rajendhiran
- Indian Council of Medical Research (ICMR)-National Institute for Research in Tuberculosis, Chennai, India
| | - Sudha Solaiyappan
- Indian Council of Medical Research (ICMR)-National Institute for Research in Tuberculosis, Chennai, India
| | - Srikanth P. Tripathy
- Indian Council of Medical Research (ICMR)-National Institute for Research in Tuberculosis, Chennai, India
| | - Mohan Natrajan
- Indian Council of Medical Research (ICMR)-National Institute for Research in Tuberculosis, Chennai, India
| | | | | | - Julian Parkhill
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Sharon J. Peacock
- Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom
| | - Uma Devi K. Ranganathan
- Indian Council of Medical Research (ICMR)-National Institute for Research in Tuberculosis, Chennai, India
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38
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Menardo F. Understanding drivers of phylogenetic clustering and terminal branch lengths distribution in epidemics of Mycobacterium tuberculosis. eLife 2022; 11:76780. [PMID: 35762734 PMCID: PMC9239681 DOI: 10.7554/elife.76780] [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: 01/04/2022] [Accepted: 06/15/2022] [Indexed: 11/13/2022] Open
Abstract
Detecting factors associated with transmission is important to understand disease epidemics, and to design effective public health measures. Clustering and terminal branch lengths (TBL) analyses are commonly applied to genomic data sets of Mycobacterium tuberculosis (MTB) to identify sub-populations with increased transmission. Here, I used a simulation-based approach to investigate what epidemiological processes influence the results of clustering and TBL analyses, and whether differences in transmission can be detected with these methods. I simulated MTB epidemics with different dynamics (latency, infectious period, transmission rate, basic reproductive number R0, sampling proportion, sampling period, and molecular clock), and found that all considered factors, except for the length of the infectious period, affect the results of clustering and TBL distributions. I show that standard interpretations of this type of analyses ignore two main caveats: (1) clustering results and TBL depend on many factors that have nothing to do with transmission, (2) clustering results and TBL do not tell anything about whether the epidemic is stable, growing, or shrinking, unless all the additional parameters that influence these metrics are known, or assumed identical between sub-populations. An important consequence is that the optimal SNP threshold for clustering depends on the epidemiological conditions, and that sub-populations with different epidemiological characteristics should not be analyzed with the same threshold. Finally, these results suggest that different clustering rates and TBL distributions, that are found consistently between different MTB lineages, are probably due to intrinsic bacterial factors, and do not indicate necessarily differences in transmission or evolutionary success.
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Affiliation(s)
- Fabrizio Menardo
- Department of Plant and Microbial Biology, University of Zurich, Zurich, Switzerland
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Walker TM, Choisy M, Dedicoat M, Drennan PG, Wyllie D, Yang-Turner F, Crook DW, Robinson ER, Walker AS, Smith EG, Peto TE. Mycobacterium tuberculosis transmission in Birmingham, UK, 2009-19: An observational study. THE LANCET REGIONAL HEALTH. EUROPE 2022; 17:100361. [PMID: 35345560 PMCID: PMC8956939 DOI: 10.1016/j.lanepe.2022.100361] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Background Over 10-years of whole-genome sequencing (WGS) of Mycobacterium tuberculosis in Birmingham presents an opportunity to explore epidemiological trends and risk factors for transmission in new detail. Methods Between 1st January 2009 and 15th June 2019, we obtained the first WGS isolate from every patient resident in a postcode district covered by Birmingham's centralised tuberculosis service. Data on patients' sex, country of birth, social risk-factors, anatomical locus of disease, and strain lineage were collected. Poisson harmonic regression was used to assess seasonal variation in case load and a mixed-effects multivariable Cox proportionate hazards model was used to assess risk factors for a future case arising in clusters defined by a 5 single nucleotide polymorphism (SNP) threshold, and by 12 SNPs in a sensitivity analysis. Findings 511/1653 (31%) patients were genomically clustered with another. A seasonal variation in diagnoses was observed, peaking in spring, but only among clustered cases. Risk-factors for a future clustered case included UK-birth (aHR=2·03 (95%CI 1·35-3·04), p < 0·001), infectious (pulmonary/laryngeal/miliary) tuberculosis (aHR=3·08 (95%CI 1·98-4·78), p < 0·001), and M. tuberculosis lineage 3 (aHR=1·91 (95%CI 1·03-3·56), p = 0·041) and 4 (aHR=2·27 (95%CI 1·21-4·26), p = 0·011), vs. lineage 1. Similar results pertained to 12 SNP clusters, for which social risk-factors were also significant (aHR 1·72 (95%CI 1·02-2·93), p = 0·044). There was marked heterogeneity in transmission patterns between postcode districts. Interpretation There is seasonal variation in the diagnosis of genomically clustered, but not non-clustered, cases. Risk factors for clustering include UK-birth, infectious forms of tuberculosis, and infection with lineage 3 or 4. Funding Wellcome Trust, MRC, UKHSA.
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Affiliation(s)
- Timothy M. Walker
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, UK
- Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
| | - Marc Choisy
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, UK
- Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
| | - Martin Dedicoat
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Philip G. Drennan
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, UK
- Oxford University Hospitals NHS Foundation Trust, UK
| | - David Wyllie
- TB Unit and National Mycobacterial Reference Service, UK Health Security Agency, UK
| | - Fan Yang-Turner
- NIHR Oxford Biomedical Research Centre, University of Oxford, UK
| | - Derrick W. Crook
- Oxford University Hospitals NHS Foundation Trust, UK
- NIHR Oxford Biomedical Research Centre, University of Oxford, UK
| | - Esther R. Robinson
- TB Unit and National Mycobacterial Reference Service, UK Health Security Agency, UK
| | - A. Sarah Walker
- NIHR Oxford Biomedical Research Centre, University of Oxford, UK
| | - E. Grace Smith
- TB Unit and National Mycobacterial Reference Service, UK Health Security Agency, UK
| | - Timothy E.A. Peto
- Oxford University Hospitals NHS Foundation Trust, UK
- NIHR Oxford Biomedical Research Centre, University of Oxford, UK
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40
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Origin and Global Expansion of Mycobacterium tuberculosis Complex Lineage 3. Genes (Basel) 2022; 13:genes13060990. [PMID: 35741753 PMCID: PMC9222951 DOI: 10.3390/genes13060990] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 05/14/2022] [Accepted: 05/19/2022] [Indexed: 11/25/2022] Open
Abstract
Simple Summary Tuberculosis still causes 1.5 million deaths annually and is mainly caused by Mycobacterium tuberculosis complex strains belonging to three evolutionary modern lineages (Lineages 2–4). While Lineage 2 and Lineage 4 virtually conquered the world, Lineage 3 is particularly successful in Northern and Eastern Africa, as well as in Southern Asia, the suspected evolutionary origin of these strains. Here, we sought to understand how Lineage 3 strains came to the African continent. To this end, we performed routine genotyping to characterize over 2500 clinical isolates from 38 countries. We then selected a representative collection of 373 isolates for a whole-genome analysis and a modeling approach to infer the geographic origin of different sublineages. In fact, the origin of Lineage 3 could be located in India, and we found evidence for independent introductions of four distinct sublineages into North/East Africa, in line with known ancient exchanges and migrations between both world regions. Our study illustrates that the evolutionary history of humans and their pathogens are closely connected and further provides a systematic understanding of the genomic diversity of Lineage 3, which could be important for the development of new tuberculosis vaccines or new therapeutics. Abstract Mycobacterium tuberculosis complex (MTBC) Lineage 3 (L3) strains are abundant in world regions with the highest tuberculosis burden. To investigate the population structure and the global diversity of this major lineage, we analyzed a dataset comprising 2682 L3 strains from 38 countries over 5 continents, by employing 24-loci mycobacterial interspersed repetitive unit-variable number of tandem repeats genotyping (MIRU-VNTR) and drug susceptibility testing. We further combined whole-genome sequencing (WGS) and phylogeographic analysis for 373 strains representing the global L3 genetic diversity. Ancestral state reconstruction confirmed that the origin of L3 strains is located in Southern Asia and further revealed multiple independent introduction events into North-East and East Africa. This study provides a systematic understanding of the global diversity of L3 strains and reports phylogenetic variations that could inform clinical trials which evaluate the effectivity of new drugs/regimens or vaccine candidates.
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Bainomugisa A, Lavu E, Pandey S, Majumdar S, Banamu J, Coulter C, Marais B, Coin L, Graham SM, du Cros P. Evolution and spread of a highly drug resistant strain of Mycobacterium tuberculosis in Papua New Guinea. BMC Infect Dis 2022; 22:437. [PMID: 35524232 PMCID: PMC9077924 DOI: 10.1186/s12879-022-07414-2] [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: 12/28/2021] [Accepted: 04/12/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Molecular mechanisms determining the transmission and prevalence of drug resistant tuberculosis (DR-TB) in Papua New Guinea (PNG) are poorly understood. We used genomic and drug susceptibility data to explore the evolutionary history, temporal acquisition of resistance and transmission dynamics of DR-TB across PNG. METHODS We performed whole genome sequencing on isolates from Central Public Health Laboratory, PNG, collected 2017-2019. Data analysis was done on a composite dataset that also included 100 genomes previously sequenced from Daru, PNG (2012-2015). RESULTS Sampled isolates represented 14 of the 22 PNG provinces, the majority (66/94; 70%) came from the National Capital District (NCD). In the composite dataset, 91% of strains were Beijing 2.2.1.1, identified in 13 provinces. Phylogenetic tree of Beijing strains revealed two clades, Daru dominant clade (A) and NCD dominant clade (B). Multi-drug resistance (MDR) was repeatedly and independently acquired, with the first MDR cases in both clades noted to have emerged in the early 1990s, while fluoroquinolone resistance emerged in 2009 (95% highest posterior density 2000-2016). We identified the presence of a frameshift mutation within Rv0678 (p.Asp47fs) which has been suggested to confer resistance to bedaquiline, despite no known exposure to the drug. Overall genomic clustering was significantly associated with rpoC compensatory and inhA promoter mutations (p < 0.001), with high percentage of most genomic clusters (12/14) identified in NCD, reflecting its role as a potential national amplifier. CONCLUSIONS The acquisition and evolution of drug resistance among the major clades of Beijing strain threaten the success of DR-TB treatment in PNG. With continued transmission of this strain in PNG, genotypic drug resistance surveillance using whole genome sequencing is essential for improved public health response to outbreaks. With occurrence of resistance to newer drugs such as bedaquiline, knowledge of full drug resistance profiles will be important for optimal treatment selection.
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Affiliation(s)
| | - Evelyn Lavu
- University of Papua New Guinea, Port Moresby, Papua New Guinea.,Central Public Health Laboratory, Port Moresby, Papua New Guinea
| | - Sushil Pandey
- Queensland Mycobacteria Reference Laboratory, Brisbane, QLD, Australia
| | - Suman Majumdar
- Burnet Institute, 85 Commercial Road, Melbourne, VIC, 3004, Australia.,University of Melbourne Department of Paediatrics and Murdoch Childrens Research Institute, Royal Children's Hospital, Melbourne, VIC, Australia
| | - Jennifer Banamu
- Central Public Health Laboratory, Port Moresby, Papua New Guinea
| | - Chris Coulter
- Queensland Mycobacteria Reference Laboratory, Brisbane, QLD, Australia
| | - Ben Marais
- University of Sydney, Sydney, NSW, Australia
| | - Lachlan Coin
- Peter Doherty Institute, Melbourne, VIC, Australia
| | - Stephen M Graham
- Burnet Institute, 85 Commercial Road, Melbourne, VIC, 3004, Australia.,University of Melbourne Department of Paediatrics and Murdoch Childrens Research Institute, Royal Children's Hospital, Melbourne, VIC, Australia
| | - Philipp du Cros
- Burnet Institute, 85 Commercial Road, Melbourne, VIC, 3004, Australia.
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42
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Gene evolutionary trajectories in Mycobacterium tuberculosis reveal temporal signs of selection. Proc Natl Acad Sci U S A 2022; 119:e2113600119. [PMID: 35452305 PMCID: PMC9173582 DOI: 10.1073/pnas.2113600119] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
SignificancePrevious attempts to identify the action of natural selection in the Mycobacterium tuberculosis complex (MTBC) were limited by sample size and averaging across time and lineages. We investigate changes in selective pressures across time for every single gene of the MTBC. We developed a methodology to analyze temporal signals of selection in a large dataset (∼5,000 complete genomes) and showed that 1) almost half of the genes seem to have been under positive selection at some point in time; 2) experimentally confirmed epitopes tend to accumulate more mutations in deeper branches than in external branches; and 3) temporal signals identify genes that were conserved in the past but under positive selection in the present, suggesting ongoing adaptation to the host.
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Marin M, Vargas R, Harris M, Jeffrey B, Epperson LE, Durbin D, Strong M, Salfinger M, Iqbal Z, Akhundova I, Vashakidze S, Crudu V, Rosenthal A, Farhat MR. Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome. Bioinformatics 2022; 38:1781-1787. [PMID: 35020793 PMCID: PMC8963317 DOI: 10.1093/bioinformatics/btac023] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 12/23/2021] [Accepted: 01/07/2022] [Indexed: 02/04/2023] Open
Abstract
MOTIVATION Short-read whole-genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences and sequencing bias reduces the performance of variant calling using short-read alignment, but the loss in recall and specificity has not been adequately characterized. To benchmark short-read variant calling, we used 36 diverse clinical Mycobacterium tuberculosis (Mtb) isolates dually sequenced with Illumina short-reads and PacBio long-reads. We systematically studied the short-read variant calling accuracy and the influence of sequence uniqueness, reference bias and GC content. RESULTS Reference-based Illumina variant calling demonstrated a maximum recall of 89.0% and minimum precision of 98.5% across parameters evaluated. The approach that maximized variant recall while still maintaining high precision (<99%) was tuning the mapping quality filtering threshold, i.e. confidence of the read mapping (recall = 85.8%, precision = 99.1%, MQ ≥ 40). Additional masking of repetitive sequence content is an alternative conservative approach to variant calling that increases precision at cost to recall (recall = 70.2%, precision = 99.6%, MQ ≥ 40). Of the genomic positions typically excluded for Mtb, 68% are accurately called using Illumina WGS including 52/168 PE/PPE genes (34.5%). From these results, we present a refined list of low confidence regions across the Mtb genome, which we found to frequently overlap with regions with structural variation, low sequence uniqueness and low sequencing coverage. Our benchmarking results have broad implications for the use of WGS in the study of Mtb biology, inference of transmission in public health surveillance systems and more generally for WGS applications in other organisms. AVAILABILITY AND IMPLEMENTATION All relevant code is available at https://github.com/farhat-lab/mtb-illumina-wgs-evaluation. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Maximillian Marin
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Roger Vargas
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Michael Harris
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20894, USA
| | - Brendan Jeffrey
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20894, USA
| | - L Elaine Epperson
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO 80206, USA
| | - David Durbin
- Mycobacteriology Reference Laboratory, Advanced Diagnostic Laboratories, National Jewish Health, Denver, CO 80206, USA
| | - Michael Strong
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO 80206, USA
| | - Max Salfinger
- College of Public Health and Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
| | - Zamin Iqbal
- EMBL-EBI, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Irada Akhundova
- Scientific Research Institute of Lung Diseases, Ministry of Health, Baku AZ1014, Azerbaijan
| | - Sergo Vashakidze
- Department of Medicine, The University of Georgia, Tbilisi 0171, Georgia
- National Center for Tuberculosis and Lung Diseases, Ministry of Health, Tbilisi 0171, Georgia
| | - Valeriu Crudu
- Phthisiopneumology Institute, Ministry of Health, Chisinau 2025, Republic of Moldova
| | - Alex Rosenthal
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20894, USA
| | - Maha Reda Farhat
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
- Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
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Hussien B, Zewude A, Wondale B, Hailu A, Ameni G. Spoligotyping of Clinical Isolates of Mycobacterium tuberculosis Complex Species in the Oromia Region of Ethiopia. Front Public Health 2022; 10:808626. [PMID: 35372211 PMCID: PMC8970530 DOI: 10.3389/fpubh.2022.808626] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/03/2022] [Indexed: 11/22/2022] Open
Abstract
Background Tuberculosis (TB) is a leading cause of morbidity and mortality in Ethiopia. Investigation of the Mycobacterium tuberculosis complex (MTBC) species circulating in the Ethiopian population would contribute to the efforts made to control TB in the country. Therefore, this study was conducted to investigate the MTBC species and spoligo patterns in the Oromia region (central) of Ethiopia. Methods A cross-sectional study design was used to recruit 450 smear positive pulmonary TB (PTB) cases from the Oromia region between September 2017 and August 2018. Mycobacteria were isolated from sputum samples on the Lowenstein Jensen (LJ) medium. Molecular identification of the isolates was performed by spoligotyping. The results of spoligotyping were transferred into a query box in the SITVIT2 database and Run TB-Lineage in the TB Insight website for the identification of spoligo international type (SIT) number and linages of the isolates, respectively. Statistical Product and Service Solutions (SPSS) 20 was applied for statistical analysis. Results Three hundred and fifteen isolates were grouped under 181 different spoligotype patterns. The most dominantly isolated spoligotype pattern was SIT149 and it consisted of 23 isolates. The majority of the isolates were grouped under Euro-American (EA), East-African-Indian (EAI), and Indo-Oceanic (IO) lineages. These lineages consisted of 79.4, 9.8, and 9.8% of the isolates, respectively. One hundred and sixty-five of the isolates were classified under 31 clustered spoligotypes whereas the remaining 150 were singleton types. Furthermore, 91.1% of the total isolates were classified as orphan types. Clustering of spoligotypes was associated (p < 0.001) with EAI lineage. Conclusion SIT149 and EA lineage were predominantly isolated from the Oromia region substantiating the findings of the similar studies conducted in other regions of Ethiopia. The observation of significant number of singleton and orphan spoligotypes warrants for additional genetic typing of the isolates using method(s) with a better discriminatory power than spoligotyping.
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Affiliation(s)
- Bedru Hussien
- Department of Public Health, Goba Referral Hospital, Madda Walabu University, Goba, Ethiopia
| | - Aboma Zewude
- Malaria and Neglected Tropical Diseases Research Team, Ethiopian Public Health Institute, Ministry of Health, Addis Ababa, Ethiopia
- Department of Veterinary Medicine, College of Agriculture and Veterinary Medicine, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Biniam Wondale
- Department of Biology, Arba Minch University, Arba Minch, Ethiopia
| | - Awraris Hailu
- Department of Public Health, College of Health Sciences, Debre Birhan University, Debre Birhan, Ethiopia
| | - Gobena Ameni
- Department of Veterinary Medicine, College of Agriculture and Veterinary Medicine, United Arab Emirates University, Al Ain, United Arab Emirates
- Aklilu Lemma Institute of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia
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Pan Q, Nguyen TB, Ascher DB, Pires DEV. Systematic evaluation of computational tools to predict the effects of mutations on protein stability in the absence of experimental structures. Brief Bioinform 2022; 23:bbac025. [PMID: 35189634 PMCID: PMC9155634 DOI: 10.1093/bib/bbac025] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 01/13/2022] [Accepted: 01/30/2022] [Indexed: 12/26/2022] Open
Abstract
Changes in protein sequence can have dramatic effects on how proteins fold, their stability and dynamics. Over the last 20 years, pioneering methods have been developed to try to estimate the effects of missense mutations on protein stability, leveraging growing availability of protein 3D structures. These, however, have been developed and validated using experimentally derived structures and biophysical measurements. A large proportion of protein structures remain to be experimentally elucidated and, while many studies have based their conclusions on predictions made using homology models, there has been no systematic evaluation of the reliability of these tools in the absence of experimental structural data. We have, therefore, systematically investigated the performance and robustness of ten widely used structural methods when presented with homology models built using templates at a range of sequence identity levels (from 15% to 95%) and contrasted performance with sequence-based tools, as a baseline. We found there is indeed performance deterioration on homology models built using templates with sequence identity below 40%, where sequence-based tools might become preferable. This was most marked for mutations in solvent exposed residues and stabilizing mutations. As structure prediction tools improve, the reliability of these predictors is expected to follow, however we strongly suggest that these factors should be taken into consideration when interpreting results from structure-based predictors of mutation effects on protein stability.
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Affiliation(s)
- Qisheng Pan
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia
- School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane City, Queensland 4072, Australia
- Systems and Computational Biology, Bio21 Institute, University of Melbourne, 30 Flemington Rd, Parkville, Victoria 3052, Australia
| | - Thanh Binh Nguyen
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia
- School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane City, Queensland 4072, Australia
- Systems and Computational Biology, Bio21 Institute, University of Melbourne, 30 Flemington Rd, Parkville, Victoria 3052, Australia
| | - David B Ascher
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia
- School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane City, Queensland 4072, Australia
- Systems and Computational Biology, Bio21 Institute, University of Melbourne, 30 Flemington Rd, Parkville, Victoria 3052, Australia
- Department of Biochemistry, University of Cambridge, 80 Tennis Ct Rd, Cambridge CB2 1GA, UK
| | - Douglas E V Pires
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia
- School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane City, Queensland 4072, Australia
- Systems and Computational Biology, Bio21 Institute, University of Melbourne, 30 Flemington Rd, Parkville, Victoria 3052, Australia
- School of Computing and Information Systems, University of Melbourne, Melbourne, Victoria 3053, Australia
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Smith CM, Baker RE, Proulx MK, Mishra BB, Long JE, Park SW, Lee HN, Kiritsy MC, Bellerose MM, Olive AJ, Murphy KC, Papavinasasundaram K, Boehm FJ, Reames CJ, Meade RK, Hampton BK, Linnertz CL, Shaw GD, Hock P, Bell TA, Ehrt S, Schnappinger D, Pardo-Manuel de Villena F, Ferris MT, Ioerger TR, Sassetti CM. Host-pathogen genetic interactions underlie tuberculosis susceptibility in genetically diverse mice. eLife 2022; 11:74419. [PMID: 35112666 PMCID: PMC8846590 DOI: 10.7554/elife.74419] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/27/2022] [Indexed: 11/21/2022] Open
Abstract
The outcome of an encounter with Mycobacterium tuberculosis (Mtb) depends on the pathogen’s ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically diverse Collaborative Cross (CC) mouse panel in conjunction with a library of Mtb mutants to create a resource for associating bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis of Mtb transposon mutant fitness (TnSeq) across the CC panel revealed that many virulence pathways are only required in specific host microenvironments, identifying a large fraction of the pathogen’s genome that has been maintained to ensure fitness in a diverse population. Both immunological and bacterial traits can be associated with genetic variants distributed across the mouse genome, making the CC a unique population for identifying specific host-pathogen genetic interactions that influence pathogenesis.
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Affiliation(s)
- Clare M Smith
- Department of Molecular Genetics and Microbiology, Duke University, Durham, United States
| | - Richard E Baker
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Megan K Proulx
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Bibhuti B Mishra
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Jarukit E Long
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Sae Woong Park
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | - Ha-Na Lee
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | - Michael C Kiritsy
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Michelle M Bellerose
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Andrew J Olive
- Microbiology and Molecular Genetics, Michigan State University, East Lansing, United States
| | - Kenan C Murphy
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Kadamba Papavinasasundaram
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Frederick J Boehm
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Charlotte J Reames
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Rachel K Meade
- Department of Molecular Genetics and Microbiology, Duke University, Durham, United States
| | - Brea K Hampton
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Colton L Linnertz
- Department of Genetics, University of North Carolina at Chapel Hill, Morrisville, United States
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Pablo Hock
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Timothy A Bell
- Department of Genetics,, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Sabine Ehrt
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | - Dirk Schnappinger
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | | | - Martin T Ferris
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Thomas R Ioerger
- Department of Computer Science and Engineering, Texas A&M University, College Station, United States
| | - Christopher M Sassetti
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
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Yang C, Sobkowiak B, Naidu V, Codreanu A, Ciobanu N, Gunasekera KS, Chitwood MH, Alexandru S, Bivol S, Russi M, Havumaki J, Cudahy P, Fosburgh H, Allender CJ, Centner H, Engelthaler DM, Menzies NA, Warren JL, Crudu V, Colijn C, Cohen T. Phylogeography and transmission of M. tuberculosis in Moldova: A prospective genomic analysis. PLoS Med 2022; 19:e1003933. [PMID: 35192619 PMCID: PMC8903246 DOI: 10.1371/journal.pmed.1003933] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Revised: 03/08/2022] [Accepted: 01/31/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The incidence of multidrug-resistant tuberculosis (MDR-TB) remains critically high in countries of the former Soviet Union, where >20% of new cases and >50% of previously treated cases have resistance to rifampin and isoniazid. Transmission of resistant strains, as opposed to resistance selected through inadequate treatment of drug-susceptible tuberculosis (TB), is the main driver of incident MDR-TB in these countries. METHODS AND FINDINGS We conducted a prospective, genomic analysis of all culture-positive TB cases diagnosed in 2018 and 2019 in the Republic of Moldova. We used phylogenetic methods to identify putative transmission clusters; spatial and demographic data were analyzed to further describe local transmission of Mycobacterium tuberculosis. Of 2,236 participants, 779 (36%) had MDR-TB, of whom 386 (50%) had never been treated previously for TB. Moreover, 92% of multidrug-resistant M. tuberculosis strains belonged to putative transmission clusters. Phylogenetic reconstruction identified 3 large clades that were comprised nearly uniformly of MDR-TB: 2 of these clades were of Beijing lineage, and 1 of Ural lineage, and each had additional distinct clade-specific second-line drug resistance mutations and geographic distributions. Spatial and temporal proximity between pairs of cases within a cluster was associated with greater genomic similarity. Our study lasted for only 2 years, a relatively short duration compared with the natural history of TB, and, thus, the ability to infer the full extent of transmission is limited. CONCLUSIONS The MDR-TB epidemic in Moldova is associated with the local transmission of multiple M. tuberculosis strains, including distinct clades of highly drug-resistant M. tuberculosis with varying geographic distributions and drug resistance profiles. This study demonstrates the role of comprehensive genomic surveillance for understanding the transmission of M. tuberculosis and highlights the urgency of interventions to interrupt transmission of highly drug-resistant M. tuberculosis.
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Affiliation(s)
- Chongguang Yang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | | | - Vijay Naidu
- Department of Mathematics, Simon Fraser University, Burnaby, Canada
| | | | - Nelly Ciobanu
- Phthisiopneumology Institute, Chisinau, Republic of Moldova
| | - Kenneth S. Gunasekera
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Melanie H. Chitwood
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | | | - Stela Bivol
- Center for Health Policies and Studies, Chisinau, Republic of Moldova
| | - Marcus Russi
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Joshua Havumaki
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Patrick Cudahy
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Heather Fosburgh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | | | - Heather Centner
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
| | - David M. Engelthaler
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
| | - Nicolas A. Menzies
- Department of Global Health and Population, and Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Joshua L. Warren
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Valeriu Crudu
- Phthisiopneumology Institute, Chisinau, Republic of Moldova
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University, Burnaby, Canada
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
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Mudliar SKR, Kulsum U, Rufai SB, Umpo M, Nyori M, Singh S. Snapshot of Mycobacterium tuberculosis Phylogenetics from an Indian State of Arunachal Pradesh Bordering China. Genes (Basel) 2022. [DOI: https://doi.org/10.3390/genes13020263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Uncontrolled transmission of Mycobacterium tuberculosis (M. tuberculosis, MTB) drug resistant strains is a challenge to control efforts of the global tuberculosis program. Due to increasing multi-drug resistant (MDR) cases in Arunachal Pradesh, a northeastern state of India, the tracking and tracing of these resistant MTB strains is crucial for infection control and spread of drug resistance. This study aims to correlate the phenotypic DST, genomic DST (gDST) and phylogenetic analysis of MDR-MTB strains in the region. Of the total 200 samples 22 (11%) patients suspected of MDR-TB and 160 (80%) previously treated MDR-TB cases, 125 (62.5%) were identified as MTB. MGIT-960 SIRE DST detected 71/125 (56.8%) isolates as MDR/RR-MTB of which 22 (30.9%) were detected resistant to second-line drugs. Whole-genome sequencing of 65 isolates and their gDST found Ser315Thr mutation in katG (35/45; 77.8%) and Ser531Leu mutation in rpoB (21/41; 51.2%) associated with drug resistance. SNP barcoding categorized the dataset with Lineage2 (41; 63.1%) being predominant followed by Lineage3 (10; 15.4%), Lineage1 (8; 12.3%) and Lineage4 (6; 9.2%) respectively. Phylogenetic assignment by cgMLST gave insights of two Beijing sub-lineages viz; 2.2.1 (SNP difference < 19) and 2.2.1.2 (SNP difference < 9) associated with recent ongoing transmission in Arunachal Pradesh. This study provides insights in identifying two virulent Beijing sub-lineages (sub-lineage 2.2.1 and 2.2.1.2) with ongoing transmission of TB drug resistance in Arunachal Pradesh.
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Mudliar SKR, Kulsum U, Rufai SB, Umpo M, Nyori M, Singh S. Snapshot of Mycobacterium tuberculosis Phylogenetics from an Indian State of Arunachal Pradesh Bordering China. Genes (Basel) 2022. [DOI: https:/doi.org/10.3390/genes13020263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Uncontrolled transmission of Mycobacterium tuberculosis (M. tuberculosis, MTB) drug resistant strains is a challenge to control efforts of the global tuberculosis program. Due to increasing multi-drug resistant (MDR) cases in Arunachal Pradesh, a northeastern state of India, the tracking and tracing of these resistant MTB strains is crucial for infection control and spread of drug resistance. This study aims to correlate the phenotypic DST, genomic DST (gDST) and phylogenetic analysis of MDR-MTB strains in the region. Of the total 200 samples 22 (11%) patients suspected of MDR-TB and 160 (80%) previously treated MDR-TB cases, 125 (62.5%) were identified as MTB. MGIT-960 SIRE DST detected 71/125 (56.8%) isolates as MDR/RR-MTB of which 22 (30.9%) were detected resistant to second-line drugs. Whole-genome sequencing of 65 isolates and their gDST found Ser315Thr mutation in katG (35/45; 77.8%) and Ser531Leu mutation in rpoB (21/41; 51.2%) associated with drug resistance. SNP barcoding categorized the dataset with Lineage2 (41; 63.1%) being predominant followed by Lineage3 (10; 15.4%), Lineage1 (8; 12.3%) and Lineage4 (6; 9.2%) respectively. Phylogenetic assignment by cgMLST gave insights of two Beijing sub-lineages viz; 2.2.1 (SNP difference < 19) and 2.2.1.2 (SNP difference < 9) associated with recent ongoing transmission in Arunachal Pradesh. This study provides insights in identifying two virulent Beijing sub-lineages (sub-lineage 2.2.1 and 2.2.1.2) with ongoing transmission of TB drug resistance in Arunachal Pradesh.
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50
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Mudliar SKR, Kulsum U, Rufai SB, Umpo M, Nyori M, Singh S. Snapshot of Mycobacterium tuberculosis Phylogenetics from an Indian State of Arunachal Pradesh Bordering China. Genes (Basel) 2022; 13:genes13020263. [PMID: 35205308 PMCID: PMC8872330 DOI: 10.3390/genes13020263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/21/2022] [Accepted: 01/25/2022] [Indexed: 02/07/2023] Open
Abstract
Uncontrolled transmission of Mycobacterium tuberculosis (M. tuberculosis, MTB) drug resistant strains is a challenge to control efforts of the global tuberculosis program. Due to increasing multi-drug resistant (MDR) cases in Arunachal Pradesh, a northeastern state of India, the tracking and tracing of these resistant MTB strains is crucial for infection control and spread of drug resistance. This study aims to correlate the phenotypic DST, genomic DST (gDST) and phylogenetic analysis of MDR-MTB strains in the region. Of the total 200 samples 22 (11%) patients suspected of MDR-TB and 160 (80%) previously treated MDR-TB cases, 125 (62.5%) were identified as MTB. MGIT-960 SIRE DST detected 71/125 (56.8%) isolates as MDR/RR-MTB of which 22 (30.9%) were detected resistant to second-line drugs. Whole-genome sequencing of 65 isolates and their gDST found Ser315Thr mutation in katG (35/45; 77.8%) and Ser531Leu mutation in rpoB (21/41; 51.2%) associated with drug resistance. SNP barcoding categorized the dataset with Lineage2 (41; 63.1%) being predominant followed by Lineage3 (10; 15.4%), Lineage1 (8; 12.3%) and Lineage4 (6; 9.2%) respectively. Phylogenetic assignment by cgMLST gave insights of two Beijing sub-lineages viz; 2.2.1 (SNP difference < 19) and 2.2.1.2 (SNP difference < 9) associated with recent ongoing transmission in Arunachal Pradesh. This study provides insights in identifying two virulent Beijing sub-lineages (sub-lineage 2.2.1 and 2.2.1.2) with ongoing transmission of TB drug resistance in Arunachal Pradesh.
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Affiliation(s)
- Shiv kumar Rashmi Mudliar
- Department of Microbiology, All India Institute of Medical Sciences, Bhopal 462020, Madhya Pradesh, India; (S.k.R.M.); (U.K.)
| | - Umay Kulsum
- Department of Microbiology, All India Institute of Medical Sciences, Bhopal 462020, Madhya Pradesh, India; (S.k.R.M.); (U.K.)
| | - Syed Beenish Rufai
- Infectious Diseases and Immunity in Global Health Program, Research Institute of the McGill University Health Center, Montreal, QC H4A 3J1, Canada;
- McGill International TB Center, Montreal, QC H4A 3J1, Canada
| | - Mika Umpo
- Tomo Riba Institute of Health & Medical Sciences, Naharlagun 791110, Arunachal Pradesh, India;
| | - Moi Nyori
- State TB Cell, Naharlagun 791110, Arunachal Pradesh, India;
| | - Sarman Singh
- Department of Microbiology, All India Institute of Medical Sciences, Bhopal 462020, Madhya Pradesh, India; (S.k.R.M.); (U.K.)
- Correspondence: ; Tel.: +91-9810813435
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