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Xiao YX, Chan TH, Liu KH, Jou R. Define SNP thresholds for delineation of tuberculosis transmissions using whole-genome sequencing. Microbiol Spectr 2024:e0041824. [PMID: 38916321 DOI: 10.1128/spectrum.00418-24] [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: 02/19/2024] [Accepted: 05/26/2024] [Indexed: 06/26/2024] Open
Abstract
For facilitating tuberculosis (TB) control, we used a whole-genome sequencing (WGS)-based approach to delineate transmission networks in a country with an intermediate burden of TB. A cluster was defined as Mycobacterium tuberculosis isolates with identical genotypes, and an outbreak was defined as clustered cases with epidemiological links (epi-links). To refine a cluster predefined using space oligonucleotide typing and mycobacterial interspersed repetitive unit variable tandem repeat typing, we analyzed one pansusceptible TB (C1) and three multidrug-resistant (MDR)-TB (C2-C4) clusters from different scenarios. Pansusceptible TB cluster (C1) consisting of 28 cases had ≤5 single nucleotide polymorphisms (SNPs) difference between their isolates. C1 was a definite outbreak, with cases attending the same junior high school in 2012. Three MDR-TB clusters (C2-C4) with distinct genotypes were identified, each consisting of 12-22 cases. Some of the cases had either ≤5 or ≤15 SNPs difference with clear or probable epi-links. Of note, even though WGS could effectively assist TB contact tracing, we still observed missing epi-links in some cases within the same cluster. Our results showed that thresholds of ≤5 and ≤15 SNPs difference between isolates were used to categorize definite and probable TB transmission, respectively. Furthermore, a higher SNP threshold might be required to define an MDR-TB outbreak. WGS still needs to be combined with classical epidemiological methods for improving outbreak investigations. Importantly, different SNP thresholds have to be applied to define outbreaks. IMPORTANCE TB is a chronic disease. Depending on host factors and TB burden, clusters of cases may continue to increase for several years. Conventional genotyping methods overestimate TB transmission, hampering precise detection of outbreaks and comprehensive surveillance. WGS can be used to obtain SNP information of M. tuberculosis to improve discriminative limitations of conventional methods and to strengthen delineation of transmission networks. It is important to define the country-specific SNP thresholds for investigation of transmission. This study demonstrated the use of thresholds of ≤5 and ≤15 SNPs difference between isolates to categorize definite and probable transmission, respectively. Different SNP thresholds should be applied while a higher cutoff was required to define an MDR-TB outbreak. The utilization of SNP thresholds proves to be crucial for guiding public health interventions, eliminating the need for unnecessary public health actions, and potentially uncovering undisclosed TB transmissions.
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Affiliation(s)
- Yu-Xin Xiao
- Tuberculosis Research Center, Centers for Disease Control, Ministry of Health and Welfare, Taipei, Taiwan
- Reference Laboratory of Mycobacteriology, Centers for Disease Control, Ministry of Health and Welfare, Taipei, Taiwan
| | - Tai-Hua Chan
- Tuberculosis Research Center, Centers for Disease Control, Ministry of Health and Welfare, Taipei, Taiwan
- Reference Laboratory of Mycobacteriology, Centers for Disease Control, Ministry of Health and Welfare, Taipei, Taiwan
| | - Kuang-Hung Liu
- Tuberculosis Research Center, Centers for Disease Control, Ministry of Health and Welfare, Taipei, Taiwan
- Reference Laboratory of Mycobacteriology, Centers for Disease Control, Ministry of Health and Welfare, Taipei, Taiwan
| | - Ruwen Jou
- Tuberculosis Research Center, Centers for Disease Control, Ministry of Health and Welfare, Taipei, Taiwan
- Reference Laboratory of Mycobacteriology, Centers for Disease Control, Ministry of Health and Welfare, Taipei, Taiwan
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2
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Kim D, Shin JI, Yoo IY, Jo S, Chu J, Cho WY, Shin SH, Chung YJ, Park YJ, Jung SH. GenoMycAnalyzer: a web-based tool for species and drug resistance prediction for Mycobacterium genomes. BMC Genomics 2024; 25:387. [PMID: 38643090 PMCID: PMC11031912 DOI: 10.1186/s12864-024-10320-3] [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: 03/04/2024] [Accepted: 04/17/2024] [Indexed: 04/22/2024] Open
Abstract
BACKGROUND Drug-resistant tuberculosis (TB) is a major threat to global public health. Whole-genome sequencing (WGS) is a useful tool for species identification and drug resistance prediction, and many clinical laboratories are transitioning to WGS as a routine diagnostic tool. However, user-friendly and high-confidence automated bioinformatics tools are needed to rapidly identify M. tuberculosis complex (MTBC) and non-tuberculous mycobacteria (NTM), detect drug resistance, and further guide treatment options. RESULTS We developed GenoMycAnalyzer, a web-based software that integrates functions for identifying MTBC and NTM species, lineage and spoligotype prediction, variant calling, annotation, drug-resistance determination, and data visualization. The accuracy of GenoMycAnalyzer for genotypic drug susceptibility testing (gDST) was evaluated using 5,473 MTBC isolates that underwent phenotypic DST (pDST). The GenoMycAnalyzer database was built to predict the gDST for 15 antituberculosis drugs using the World Health Organization mutational catalogue. Compared to pDST, the sensitivity of drug susceptibilities by the GenoMycAnalyzer for first-line drugs ranged from 95.9% for rifampicin (95% CI 94.8-96.7%) to 79.6% for pyrazinamide (95% CI 76.9-82.2%), whereas those for second-line drugs ranged from 98.2% for levofloxacin (95% CI 90.1-100.0%) to 74.9% for capreomycin (95% CI 69.3-80.0%). Notably, the integration of large deletions of the four resistance-conferring genes increased gDST sensitivity. The specificity of drug susceptibilities by the GenoMycAnalyzer ranged from 98.7% for amikacin (95% CI 97.8-99.3%) to 79.5% for ethionamide (95% CI 76.4-82.3%). The incorporated Kraken2 software identified 1,284 mycobacterial species with an accuracy of 98.8%. GenoMycAnalyzer also perfectly predicted lineages for 1,935 MTBC and spoligotypes for 54 MTBC. CONCLUSIONS GenoMycAnalyzer offers both web-based and graphical user interfaces, which can help biologists with limited access to high-performance computing systems or limited bioinformatics skills. By streamlining the interpretation of WGS data, the GenoMycAnalyzer has the potential to significantly impact TB management and contribute to global efforts to combat this infectious disease. GenoMycAnalyzer is available at http://www.mycochase.org .
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Affiliation(s)
- Doyoung Kim
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jeong-Ih Shin
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Integrated Research Center for Genomic Polymorphism, Precision Medicine Research Center, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - In Young Yoo
- Department of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Sungjin Jo
- Department of Laboratory Medicine, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jiyon Chu
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | | | | | - Yeun-Jun Chung
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Integrated Research Center for Genomic Polymorphism, Precision Medicine Research Center, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Departments of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Yeon-Joon Park
- Department of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Seung-Hyun Jung
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea.
- Integrated Research Center for Genomic Polymorphism, Precision Medicine Research Center, College of Medicine, The Catholic University of Korea, Seoul, Korea.
- Departments of Biochemistry, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seoch-Gu, Seoul, 06591, Republic of Korea.
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Zaporojan N, Negrean RA, Hodișan R, Zaporojan C, Csep A, Zaha DC. Evolution of Laboratory Diagnosis of Tuberculosis. Clin Pract 2024; 14:388-416. [PMID: 38525709 PMCID: PMC10961697 DOI: 10.3390/clinpract14020030] [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: 12/28/2023] [Revised: 02/15/2024] [Accepted: 02/19/2024] [Indexed: 03/26/2024] Open
Abstract
Tuberculosis (TB) is an infectious disease of global public health importance caused by the Mycobacterium tuberculosis complex. Despite advances in diagnosis and treatment, this disease has worsened with the emergence of multidrug-resistant strains of tuberculosis. We aim to present and review the history, progress, and future directions in the diagnosis of tuberculosis by evaluating the current methods of laboratory diagnosis of tuberculosis, with a special emphasis on microscopic examination and cultivation on solid and liquid media, as well as an approach to molecular assays. The microscopic method, although widely used, has its limitations, and the use and evaluation of other techniques are essential for a complete and accurate diagnosis. Bacterial cultures, both in solid and liquid media, are essential methods in the diagnosis of TB. Culture on a solid medium provides specificity and accuracy, while culture on a liquid medium brings rapidity and increased sensitivity. Molecular tests such as LPA and Xpert MTB/RIF have been found to offer significant benefits in the rapid and accurate diagnosis of TB, including drug-resistant forms. These tests allow the identification of resistance mutations and provide essential information for choosing the right treatment. We conclude that combined diagnostic methods, using several techniques and approaches, provide the best result in the laboratory diagnosis of TB. Improving the quality and accessibility of tests, as well as the implementation of advanced technologies, is essential to help improve the sensitivity, efficiency, and accuracy of TB diagnosis.
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Affiliation(s)
- Natalia Zaporojan
- Doctoral School of Biomedical Sciences, University of Oradea, Str. Universitatii 1, 410087 Oradea, Romania; (N.Z.)
| | - Rodica Anamaria Negrean
- Department of Preclinical Disciplines, Faculty of Medicine and Pharmacy, University of Oradea, P-ta 1 December 10, 410087 Oradea, Romania
| | - Ramona Hodișan
- Doctoral School of Biomedical Sciences, University of Oradea, Str. Universitatii 1, 410087 Oradea, Romania; (N.Z.)
- Department of Preclinical Disciplines, Faculty of Medicine and Pharmacy, University of Oradea, P-ta 1 December 10, 410087 Oradea, Romania
| | - Claudiu Zaporojan
- Emergency County Hospital Bihor, Str. Republicii 37, 410167 Oradea, Romania
| | - Andrei Csep
- Department of Psycho-Neurosciences and Recovery, Faculty of Medicine and Pharmacy, University of Oradea, P-ta 1 December 10, 410087 Oradea, Romania
| | - Dana Carmen Zaha
- Doctoral School of Biomedical Sciences, University of Oradea, Str. Universitatii 1, 410087 Oradea, Romania; (N.Z.)
- Department of Preclinical Disciplines, Faculty of Medicine and Pharmacy, University of Oradea, P-ta 1 December 10, 410087 Oradea, Romania
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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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Hazra D, Lam C, Chawla K, Sintchenko V, Dhyani VS, Venkatesh BT. Impact of Whole-Genome Sequencing of Mycobacterium tuberculosis on Treatment Outcomes for MDR-TB/XDR-TB: A Systematic Review. Pharmaceutics 2023; 15:2782. [PMID: 38140122 PMCID: PMC10747601 DOI: 10.3390/pharmaceutics15122782] [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: 10/25/2023] [Revised: 11/29/2023] [Accepted: 12/11/2023] [Indexed: 12/24/2023] Open
Abstract
The emergence and persistence of drug-resistant tuberculosis is a major threat to global public health. Our objective was to assess the applicability of whole-genome sequencing (WGS) to detect genomic markers of drug resistance and explore their association with treatment outcomes for multidrug-resistant/extensively drug-resistant tuberculosis (MDR/XDR-TB). METHODS Five electronic databases were searched for studies published in English from the year 2000 onward. Two reviewers independently conducted the article screening, relevant data extraction, and quality assessment. The data of the included studies were synthesized with a narrative method and are presented in a tabular format. RESULTS The database search identified 949 published articles and 8 studies were included. An unfavorable treatment outcome was reported for 26.6% (488/1834) of TB cases, which ranged from 9.7 to 51.3%. Death was reported in 10.5% (194/1834) of total cases. High-level fluoroquinolone resistance (due to gyrA 94AAC and 94GGC mutations) was correlated as the cause of unfavorable treatment outcomes and reported in three studies. Other drug resistance mutations, like kanamycin high-level resistance mutations (rrs 1401G), rpoB Ile491Phe, and ethA mutations, conferring prothionamide resistance were also reported. The secondary findings from this systematic review involved laboratory aspects of WGS, including correlations with phenotypic DST, cost, and turnaround time, or the impact of WGS results on public health actions, such as determining transmission events within outbreaks. CONCLUSIONS WGS has a significant capacity to provide accurate and comprehensive drug resistance data for MDR/XDR-TB, which can inform personalized drug therapy to optimize treatment outcomes.
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Affiliation(s)
- Druti Hazra
- Department of Microbiology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India;
| | - Connie Lam
- Sydney Institute for Infectious Diseases, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia;
- Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, Sydney, NSW 2145, Australia
| | - Kiran Chawla
- Department of Microbiology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India;
| | - Vitali Sintchenko
- Sydney Institute for Infectious Diseases, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia;
- Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, Sydney, NSW 2145, Australia
| | - Vijay Shree Dhyani
- Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India;
| | - Bhumika T. Venkatesh
- Public Health Evidence South Asia, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India;
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6
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Kim NY, Kim DY, Chu J, Jung SH. pncA Large Deletion is the Characteristic of Pyrazinamide-Resistant Mycobacterium tuberculosis belonging to the East Asian Lineage. Infect Chemother 2023; 55:247-256. [PMID: 37407242 DOI: 10.3947/ic.2023.0037] [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: 04/05/2023] [Accepted: 05/10/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Pyrazinamide (PZA) is often used as an add-on agent in the treatment of multidrug-resistant tuberculosis, regardless of phenotypic drug susceptibility testing (pDST) results. However, evaluating the effectiveness of PZA is challenging because of its low pH activity, which can result in unreliable pDST results. This study aimed to investigate the genomic characteristics associated with PZA resistance that can be used to develop genotypic DST. MATERIALS AND METHODS A publicly available whole genome sequencing (WGS) dataset of 10,725 Mycobacterium tuberculosis complex genomes (3,326 phenotypically PZA-resistant and 7,399 phenotypically PZA-susceptible isolates) were analyzed. RESULTS In total, 2,934 pncA non-silent mutations were identified in 2,880 isolates (26.9%). Detected mutations were found throughout the entire coding region of pncA in a scattered pattern, of which the most frequent mutation was p.Q10P (n = 278), followed by p.H57D (n = 167) and c.-11A>G (n = 122). The sensitivity and specificity of the group 1 or 2 mutations reported by the World Health Organization (WHO) mutational catalogue were 73.0% and 98.9%, respectively. We further identified 18 novel pncA mutations that were significantly associated with phenotypically PZA-resistant. In addition to these mutations, we identified 102 large deletions in the pncA gene, and all but two isolates were phenotypically resistant to PZA isolates. Notably, pncA deletions were mutually exclusive to pncA mutations, and more than half of the isolates with pncA large deletions belonged to the East Asian lineage (67.6%). The sensitivity, specificity, positive predictive value, and negative predictive value of the pooled variants (group 1 or 2 mutations, novel resistance-associated mutations, and large deletions of the pncA gene) were 79.0%, 98.9%, 97.0%, and 91.3%, respectively. The area under the curve (AUC) value for the pooled variants was significantly higher than the AUC value for the group 1 or 2 mutations (P <0.001), indicating that the pooled variants have a better discriminative ability for predicting PZA resistance. CONCLUSION Using WGS, we found that the pncA mutations are scattered without specific mutational hotspots, and large deletions associated with PZA resistance are more common in the East Asian lineage of M. tuberculosis isolates. Our data also demonstrated the reliability of group 1 or 2 mutations presented in the WHO mutation catalogue and the need for further investigation on group 3 mutations, contributing to the evaluation of the current knowledge base on mutations associated with the PZA-resistant M. tuberculosis complex.
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Affiliation(s)
- Na Yung Kim
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Do Young Kim
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jiyon Chu
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Seung-Hyun Jung
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Department of Biochemistry, Precision Medicine Research Center, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Integrated Research Center for Genomic Polymorphism, College of Medicine, The Catholic University of Korea, Seoul, Korea.
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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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Naz S, Paritosh K, Sanyal P, Khan S, Singh Y, Varshney U, Nandicoori VK. GWAS and functional studies suggest a role for altered DNA repair in the evolution of drug resistance in Mycobacterium tuberculosis. eLife 2023; 12:75860. [PMID: 36695572 PMCID: PMC9876569 DOI: 10.7554/elife.75860] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 01/11/2023] [Indexed: 01/26/2023] Open
Abstract
The emergence of drug resistance in Mycobacterium tuberculosis (Mtb) is alarming and demands in-depth knowledge for timely diagnosis. We performed genome-wide association analysis using 2237 clinical strains of Mtb to identify novel genetic factors that evoke drug resistance. In addition to the known direct targets, we identified for the first time, a strong association between mutations in DNA repair genes and the multidrug-resistant phenotype. To evaluate the impact of variants identified in the clinical samples in the evolution of drug resistance, we utilized knockouts and complemented strains in Mycobacterium smegmatis and Mtb. Results show that variant mutations compromised the functions of MutY and UvrB. MutY variant showed enhanced survival compared with wild-type (Rv) when the Mtb strains were subjected to multiple rounds of ex vivo antibiotic stress. In an in vivo guinea pig infection model, the MutY variant outcompeted the wild-type strain. We show that novel variant mutations in the DNA repair genes collectively compromise their functions and contribute to better survival under antibiotic/host stress conditions.
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Affiliation(s)
- Saba Naz
- National Institute of ImmunologyNew DelhiIndia
- Centre for Cellular and Molecular BiologyHyderabadIndia
- Department of Zoology, University of DelhiDelhiIndia
| | - Kumar Paritosh
- Centre for Genetic Manipulation of Crop Plants, University of Delhi South CampusNew DelhiIndia
| | | | - Sidra Khan
- National Institute of ImmunologyNew DelhiIndia
| | | | - Umesh Varshney
- Department of Microbiology and Cell Biology, Indian Institute of Science BangaloreBangaloreIndia
| | - Vinay Kumar Nandicoori
- National Institute of ImmunologyNew DelhiIndia
- Centre for Cellular and Molecular BiologyHyderabadIndia
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9
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Green AG, Yoon CH, Chen ML, Ektefaie Y, Fina M, Freschi L, Gröschel MI, Kohane I, Beam A, Farhat M. A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis. Nat Commun 2022; 13:3817. [PMID: 35780211 PMCID: PMC9250494 DOI: 10.1038/s41467-022-31236-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 06/10/2022] [Indexed: 11/30/2022] Open
Abstract
Long diagnostic wait times hinder international efforts to address antibiotic resistance in M. tuberculosis. Pathogen whole genome sequencing, coupled with statistical and machine learning models, offers a promising solution. However, generalizability and clinical adoption have been limited by a lack of interpretability, especially in deep learning methods. Here, we present two deep convolutional neural networks that predict antibiotic resistance phenotypes of M. tuberculosis isolates: a multi-drug CNN (MD-CNN), that predicts resistance to 13 antibiotics based on 18 genomic loci, with AUCs 82.6-99.5% and higher sensitivity than state-of-the-art methods; and a set of 13 single-drug CNNs (SD-CNN) with AUCs 80.1-97.1% and higher specificity than the previous state-of-the-art. Using saliency methods to evaluate the contribution of input sequence features to the SD-CNN predictions, we identify 18 sites in the genome not previously associated with resistance. The CNN models permit functional variant discovery, biologically meaningful interpretation, and clinical applicability.
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Affiliation(s)
- Anna G Green
- Department of Biomedical Informatics, Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
| | - Chang Ho Yoon
- Department of Biomedical Informatics, Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
- Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, OX37LF, UK
| | - Michael L Chen
- Department of Biomedical Informatics, Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
- Stanford University School of Medicine, 291 Campus Dr, Stanford, CA, 94305, USA
| | - Yasha Ektefaie
- Department of Biomedical Informatics, Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
| | - Mack Fina
- Harvard College, Cambridge, MA, 02138, USA
| | - Luca Freschi
- Department of Biomedical Informatics, Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
| | - Matthias I Gröschel
- Department of Biomedical Informatics, Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
| | - Isaac Kohane
- Department of Biomedical Informatics, Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
| | - Andrew Beam
- Department of Biomedical Informatics, Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA.
| | - Maha Farhat
- Department of Biomedical Informatics, Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA.
- Division of Pulmonary & Critical Care, Massachusetts General Hospital, 55 Fruit St, Boston, MA, 02114, USA.
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10
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Abstract
Defining the precise relationship between resistance mutations and quantitative phenotypic drug susceptibility testing will increase the value of whole-genome sequencing (WGS) for predicting tuberculosis drug resistance. However, a large number of WGS data sets currently lack corresponding quantitative phenotypic data—the MICs. Using MYCOTBI plates, we determined the MICs to nine antituberculosis drugs for 154 clinical multidrug-resistant tuberculosis isolates from the Shenzhen Center for Chronic Disease Control in Shenzhen, China. Comparing MICs with predicted drug-resistance profiles inferred by WGS showed that WGS could predict the levels of resistance to isoniazid, rifampicin, streptomycin, fluoroquinolones, and aminoglycosides. We also found some mutations that may not be associated with drug resistance, such as EmbB D328G, mutations in the gid gene, and C−12T in the eis promoter. However, some strains carrying the same mutations showed different levels of resistance to the corresponding drugs. The MICs of different strains with the RpsL K88R, fabG1 C−15T mutations and some with mutations in embB and rpoB, had MICs to the corresponding drugs that varied by 8-fold or more. This variation is unexplained but could be influenced by the bacterial genetic background. Additionally, we found that 32.3% of rifampicin-resistant isolates were rifabutin-susceptible, particularly those with rpoB mutations H445D, H445L, H445S, D435V, D435F, L452P, S441Q, and S441V. Studying the influence of bacterial genetic background on the MIC and the relationship between rifampicin-resistant mutations and rifabutin resistance levels should improve the ability of WGS to guide the selection of medical treatment regimens. IMPORTANCE Whole-genome sequencing (WGS) has excellent potential in drug-resistance prediction. The MICs are essential indications of adding a particular antituberculosis drug dosage or changing the entire treatment regimen. However, the relationship between many known drug-resistant mutations and MICs is unclear, especially for rarer ones. The results showed that WGS could predict resistance levels to isoniazid, rifampicin, streptomycin, fluoroquinolones, and aminoglycosides. However, some mutations may not be associated with drug resistance, and some others may confer various MICs to strains carrying them. Also, 32.3% of rifampicin (RIF)-resistant strains were classified as sensitive to rifabutin (RFB), and some mutations in the rpoB gene may be associated with this phenotype. Our data on the MIC distribution of strains with some rarer mutations add to the accumulated data on the resistance level associated with such mutations to help guide further research and draw meaningful conclusions.
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11
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Wang M, Zhang Y, Huang C, Li J, Shen X, Zhao G, Jiang Y, Pan Q. A Whole-Genome Sequencing-Based Study to Delineate the Risk and Characteristics of Tuberculosis Transmission in an Insular Population Over 10 Years in Shanghai. Front Microbiol 2022; 12:768659. [PMID: 35250898 PMCID: PMC8888905 DOI: 10.3389/fmicb.2021.768659] [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: 09/01/2021] [Accepted: 12/31/2021] [Indexed: 11/13/2022] Open
Abstract
Background Tuberculosis (TB) has remained a tough problem in China. This study aims to identify the risk of tuberculosis transmission and to assess its characteristics. Methods We performed a molecular epidemiological study for patients with culture-positive Mycobacterium tuberculosis (M. tuberculosis) in Shanghai, from 2009 to 2018. Demographic information was obtained from the Tuberculosis Information Management System. Whole-genome sequencing (WGS) was conducted with a threshold of 12 single-nucleotide polymorphisms (SNPs) to distinguish the genomic cluster. To analyze the characteristics of TB transmission, the contact investigation for clustered cases was performed. Results In total, 94 (27.25%) of the 345 enrolled patients were grouped into 42 genomic clusters, indicating local transmission of M. tuberculosis strains. Compared to a health system delay <14 days, patients with a health system delay ≥14 days [adjusted odds ratios (AOR) = 2.57, 95% confidence interval (CI): 1.34–4.95] were more likely to be clustered. Patients under 65 years old (AOR = 3.11, 95% CI: 1.76–5.49), residents (AOR = 2.43, 95% CI: 1.18–4.99), and Beijing genotype strains (AOR = 3.35, 95% CI: 1.32–8.53) were associated with increased risk of clustering. Interestingly, patients with resistance to isoniazid (AOR = 2.36, 95% CI: 1.15–4.88) had a higher risk of transmission. Sixteen confirmed/probable epidemiological links were identified. Local transmission of imported cases and household transmission were prominent. Conclusion Health system delay is a crucial factor for TB transmission. Patients with resistance to isoniazid should be priority targets for contact investigation to reduce transmission.
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Affiliation(s)
- Min Wang
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.,Department of Epidemiology, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - Yangyi Zhang
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.,Department of Epidemiology, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - Cheng Huang
- Department of Tuberculosis Control, Chongming District Center for Disease Control and Prevention, Shanghai, China
| | - Jing Li
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Xin Shen
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Genming Zhao
- Department of Epidemiology, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - Yuan Jiang
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Qichao Pan
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
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12
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Cox H, Salaam-Dreyer Z, Goig GA, Nicol MP, Menardo F, Dippenaar A, Mohr-Holland E, Daniels J, Cudahy PGT, Borrell S, Reinhard M, Doetsch A, Beisel C, Reuter A, Furin J, Gagneux S, Warren RM. Potential contribution of HIV during first-line tuberculosis treatment to subsequent rifampicin-monoresistant tuberculosis and acquired tuberculosis drug resistance in South Africa: a retrospective molecular epidemiology study. LANCET MICROBE 2021; 2:e584-e593. [PMID: 34766068 PMCID: PMC8563432 DOI: 10.1016/s2666-5247(21)00144-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Background South Africa has a high burden of rifampicin-resistant tuberculosis (including multidrug-resistant [MDR] tuberculosis), with increasing rifampicin-monoresistant (RMR) tuberculosis over time. Resistance acquisition during first-line tuberculosis treatment could be a key contributor to this burden, and HIV might increase the risk of acquiring rifampicin resistance. We assessed whether HIV during previous treatment was associated with RMR tuberculosis and resistance acquisition among a retrospective cohort of patients with MDR or rifampicin-resistant tuberculosis. Methods In this retrospective cohort study, we included all patients routinely diagnosed with MDR or rifampicin-resistant tuberculosis in Khayelitsha, Cape Town, South Africa, between Jan 1, 2008, and Dec 31, 2017. Patient-level data were obtained from a prospective database, complemented by data on previous tuberculosis treatment and HIV from a provincial health data exchange. Stored MDR or rifampicin-resistant tuberculosis isolates from patients underwent whole-genome sequencing (WGS). WGS data were used to infer resistance acquisition versus transmission, by identifying genomically unique isolates (single nucleotide polymorphism threshold of five). Logistic regression analyses were used to assess factors associated with RMR tuberculosis and genomic uniqueness. Findings The cohort included 2041 patients diagnosed with MDR or rifampicin-resistant tuberculosis between Jan 1, 2008, and Dec 31, 2017; of those, 463 (22·7%) with RMR tuberculosis and 1354 (66·3%) with previous tuberculosis treatment. In previously treated patients, HIV positivity during previous tuberculosis treatment versus HIV negativity (adjusted odds ratio [OR] 2·07, 95% CI 1·35–3·18), and three or more previous tuberculosis treatment episodes versus one (1·96, 1·21–3·17) were associated with RMR tuberculosis. WGS data showing MDR or rifampicin-resistant tuberculosis were available for 1169 patients; 360 (30·8%) isolates were identified as unique. In previously treated patients, RMR tuberculosis versus MDR tuberculosis (adjusted OR 4·96, 3·40–7·23), HIV positivity during previous tuberculosis treatment (1·71, 1·03–2·84), and diagnosis in 2013–17 (1·42, 1·02–1·99) versus 2008–12, were associated with uniqueness. In previously treated patients with RMR tuberculosis, HIV positivity during previous treatment (adjusted OR 5·13, 1·61–16·32) was associated with uniqueness as was female sex (2·50 [1·18–5·26]). Interpretation These data suggest that HIV contributes to rifampicin-resistance acquisition during first-line tuberculosis treatment and that this might be driving increasing RMR tuberculosis over time. Large-scale prospective cohort studies are required to further quantify this risk. Funding Swiss National Science Foundation, South African National Research Foundation, and Wellcome Trust.
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Affiliation(s)
- Helen Cox
- Division of Medical Microbiology, Department of Pathology, University of Cape Town, Cape Town, South Africa.,Institute of Infectious Disease and Molecular Medicine, Wellcome Centre for Infectious Disease Research, University of Cape Town, Cape Town, South Africa
| | - Zubeida Salaam-Dreyer
- Division of Medical Microbiology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Galo A Goig
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Mark P Nicol
- Division of Infection and Immunity, School of Biomedical Sciences, University of Western Australia, Perth, WA, Australia
| | - Fabrizio Menardo
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Anzaan Dippenaar
- Tuberculosis Omics Research Consortium, Family Medicine and Population Health, Institute of Global Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | | | - Johnny Daniels
- Médecins Sans Frontières, Khayelitsha, Cape Town, South Africa
| | - Patrick G T Cudahy
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Sonia Borrell
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Miriam Reinhard
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Anna Doetsch
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | | | - Anja Reuter
- Médecins Sans Frontières, Khayelitsha, Cape Town, South Africa
| | - Jennifer Furin
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
| | - Sebastien Gagneux
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Robin M Warren
- DST-NRF Centre of Excellence for Biomedical Tuberculosis Research/SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
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13
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Whole-genome sequencing as a tool for studying the microevolution of drug-resistant serial Mycobacterium tuberculosis isolates. Tuberculosis (Edinb) 2021; 131:102137. [PMID: 34673379 DOI: 10.1016/j.tube.2021.102137] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 09/14/2021] [Accepted: 10/03/2021] [Indexed: 11/21/2022]
Abstract
Treatment of drug-resistant tuberculosis requires extended use of more toxic and less effective drugs and may result in retreatment cases due to failure, abandonment or disease recurrence. It is therefore important to understand the evolutionary process of drug resistance in Mycobacterium tuberculosis. We here in describe the microevolution of drug resistance in serial isolates from six previously treated patients. Drug resistance was initially investigated through phenotypic methods, followed by genotypic approaches. The use of whole-genome sequencing allowed the identification of mutations in the katG, rpsL and rpoB genes associated with drug resistance, including the detection of rare mutations in katG and mixed populations of strains. Molecular docking simulation studies of the impact of observed mutations on isoniazid binding were also performed. Whole-genome sequencing detected 266 single nucleotide polymorphisms between two isolates obtained from one patient, suggesting a case of exogenous reinfection. In conclusion, sequencing technologies can detect rare mutations related to drug resistance, identify subpopulations of resistant strains, and identify diverse populations of strains due to exogenous reinfection, thus improving tuberculosis control by guiding early implementation of appropriate clinical and therapeutic interventions.
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14
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Freschi L, Vargas R, Husain A, Kamal SMM, Skrahina A, Tahseen S, Ismail N, Barbova A, Niemann S, Cirillo DM, Dean AS, Zignol M, Farhat MR. Population structure, biogeography and transmissibility of Mycobacterium tuberculosis. Nat Commun 2021; 12:6099. [PMID: 34671035 PMCID: PMC8528816 DOI: 10.1038/s41467-021-26248-1] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 09/06/2021] [Indexed: 01/10/2023] Open
Abstract
Mycobacterium tuberculosis is a clonal pathogen proposed to have co-evolved with its human host for millennia, yet our understanding of its genomic diversity and biogeography remains incomplete. Here we use a combination of phylogenetics and dimensionality reduction to reevaluate the population structure of M. tuberculosis, providing an in-depth analysis of the ancient Indo-Oceanic Lineage 1 and the modern Central Asian Lineage 3, and expanding our understanding of Lineages 2 and 4. We assess sub-lineages using genomic sequences from 4939 pan-susceptible strains, and find 30 new genetically distinct clades that we validate in a dataset of 4645 independent isolates. We find a consistent geographically restricted or unrestricted pattern for 20 groups, including three groups of Lineage 1. The distribution of terminal branch lengths across the M. tuberculosis phylogeny supports the hypothesis of a higher transmissibility of Lineages 2 and 4, in comparison with Lineages 3 and 1, on a global scale. We define an expanded barcode of 95 single nucleotide substitutions that allows rapid identification of 69 M. tuberculosis sub-lineages and 26 additional internal groups. Our results paint a higher resolution picture of the M. tuberculosis phylogeny and biogeography.
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Affiliation(s)
- Luca Freschi
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| | - Roger Vargas
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Ashaque Husain
- Directorate General of Health Services, Ministry of Health and Family Welfare, Dhaka, Bangladesh
| | - S M Mostofa Kamal
- Department of Pathology and Microbiology, National Institute of Diseases of the Chest and Hospital, Dhaka, Bangladesh
| | - Alena Skrahina
- Republican Scientific and Practical Centre for Pulmonology and Tuberculosis, Minsk, Belarus
| | - Sabira Tahseen
- National Reference Laboratory, National Tuberculosis Control Programme, Islamabad, Pakistan
| | - Nazir Ismail
- National Institute for Communicable Diseases, Sandringham, South Africa
- Department of Medical Microbiology, University of Pretoria, Pretoria, South Africa
| | - Anna Barbova
- Central Reference Laboratory on Tuberculosis Microbiological Diagnostics, Ministry of Health, Kiev, Ukraine
| | - Stefan Niemann
- Molecular and Experimental Mycobacteriology, Borstel Research Centre, Borstel, Germany
| | - Daniela Maria Cirillo
- Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Anna S Dean
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Matteo Zignol
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Maha Reda Farhat
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA.
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15
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Gatt YE, Margalit H. Common Adaptive Strategies Underlie Within-Host Evolution of Bacterial Pathogens. Mol Biol Evol 2021; 38:1101-1121. [PMID: 33118035 PMCID: PMC7947768 DOI: 10.1093/molbev/msaa278] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Within-host adaptation is a hallmark of chronic bacterial infections, involving substantial genomic changes. Recent large-scale genomic data from prolonged infections allow the examination of adaptive strategies employed by different pathogens and open the door to investigate whether they converge toward similar strategies. Here, we compiled extensive data of whole-genome sequences of bacterial isolates belonging to miscellaneous species sampled at sequential time points during clinical infections. Analysis of these data revealed that different species share some common adaptive strategies, achieved by mutating various genes. Although the same genes were often mutated in several strains within a species, different genes related to the same pathway, structure, or function were changed in other species utilizing the same adaptive strategy (e.g., mutating flagellar genes). Strategies exploited by various bacterial species were often predicted to be driven by the host immune system, a powerful selective pressure that is not species specific. Remarkably, we find adaptive strategies identified previously within single species to be ubiquitous. Two striking examples are shifts from siderophore-based to heme-based iron scavenging (previously shown for Pseudomonas aeruginosa) and changes in glycerol-phosphate metabolism (previously shown to decrease sensitivity to antibiotics in Mycobacterium tuberculosis). Virulence factors were often adaptively affected in different species, indicating shifts from acute to chronic virulence and virulence attenuation during infection. Our study presents a global view on common within-host adaptive strategies employed by different bacterial species and provides a rich resource for further studying these processes.
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Affiliation(s)
- Yair E Gatt
- Department of Microbiology and Molecular Genetics, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Hanah Margalit
- Department of Microbiology and Molecular Genetics, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
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16
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Emergence of additional drug resistance during treatment of multidrug-resistant tuberculosis in China: a prospective cohort study. Clin Microbiol Infect 2021; 27:1805-1813. [PMID: 33895338 DOI: 10.1016/j.cmi.2021.04.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 03/30/2021] [Accepted: 04/06/2021] [Indexed: 12/26/2022]
Abstract
OBJECTIVES Little is known about how additional second-line drug resistance emerges during multidrug-resistant tuberculosis (MDR-TB) treatment. The present study aimed to investigate the influence of microevolution, exogenous reinfection and mixed infection on second-line drug resistance during the recommended 2-year MDR-TB treatment. METHODS Individuals with MDR-TB were enrolled between 2013 and 2016 in a multicentre prospective observational cohort study and were followed up for 2 years until treatment completion. Whole-genome sequencing (WGS) was applied for serial Mycobacterium tuberculosis isolates from study participants throughout the treatment, to study the role of microevolution, exogenous reinfection and mixed infection in the development of second-line drug resistance. RESULTS Of the 286 enrolled patients with MDR-TB, 63 (22.0%) M. tuberculosis isolates developed additional drug resistance during the MDR-TB treatment, including 5 that fulfilled the criteria of extensively drug-resistant TB. By comparing WGS data of serial isolates retrieved from the patients throughout treatment, 41 (65.1%) of the cases of additional second-line drug resistance were the result of exogenous reinfection, 18 (28.6%) were caused by acquired drug resistance, i.e. microevolution, while the remaining 4 (6.3%) were caused by mixed infections with drug-resistant and drug-susceptible strains. In multivariate analysis, previous TB treatment (adjusted hazard ratio (aHR) 2.51, 95% CI 1.51-4.18), extensive disease on chest X-ray (aHR 3.39, 95% CI 2.03-5.66) and type 2 diabetes mellitus (aHR 4.00, 95% CI 2.22-7.21) were independent risk factors associated with the development of additional second-line drug resistance. CONCLUSIONS A large proportion of additional second-line drug resistance emerging during MDR-TB treatment was attributed to exogenous reinfection, indicating the urgency of infection control in health facilities as well as the need for repeated drug susceptibility testing throughout MDR-TB treatment.
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17
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Cheng B, Behr MA, Howden BP, Cohen T, Lee RS. Reporting practices for genomic epidemiology of tuberculosis: a systematic review of the literature using STROME-ID guidelines as a benchmark. THE LANCET. MICROBE 2021; 2:e115-e129. [PMID: 33842904 PMCID: PMC8034592 DOI: 10.1016/s2666-5247(20)30201-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
BACKGROUND Pathogen genomics have become increasingly important in infectious disease epidemiology and public health. The Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID) guidelines were developed to outline a minimum set of criteria that should be reported in genomic epidemiology studies to facilitate assessment of study quality. We evaluate such reporting practices, using tuberculosis as an example. METHODS For this systematic review, we initially searched MEDLINE, Embase Classic, and Embase on May 3, 2017, using the search terms "tuberculosis" and "genom* sequencing". We updated this initial search on April 23, 2019, and also included a search of bioRxiv at this time. We included studies in English, French, or Spanish that recruited patients with microbiologically confirmed tuberculosis and used whole genome sequencing for typing of strains. Non-human studies, conference abstracts, and literature reviews were excluded. For each included study, the number and proportion of fulfilled STROME-ID criteria were recorded by two reviewers. A comparison of the mean proportion of fulfilled STROME-ID criteria before and after publication of the STROME-ID guidelines (in 2014) was done using a two-tailed t test. Quasi-Poisson regression and tobit regression were used to examine associations between study characteristics and the number and proportion of fulfilled STROME-ID criteria. This study was registered with PROSPERO, CRD42017064395. FINDINGS 976 titles and abstracts were identified by our primary search, with an additional 16 studies identified in bioRxiv. 114 full texts (published between 2009 and 2019) were eligible for inclusion. The mean proportion of STROME-ID criteria fulfilled was 50% (SD 12; range 16-75). The proportion of criteria fulfilled was similar before and after STROME-ID publication (51% [SD 11] vs 46% [14], p=0·26). The number of criteria reported (among those applicable to all studies) was not associated with impact factor, h-index, country of affiliation of senior author, or sample size of isolates. Similarly, the proportion of criteria fulfilled was not associated with these characteristics, with the exception of a sample size of isolates of 277 or more (the highest quartile). In terms of reproducibility, 100 (88%) studies reported which bioinformatic tools were used, but only 33 (33%) reported corresponding version numbers. Sequencing data were available for 86 (75%) studies. INTERPRETATION The reporting of STROME-ID criteria in genomic epidemiology studies of tuberculosis between 2009 and 2019 was low, with implications for assessment of study quality. The considerable proportion of studies without bioinformatics version numbers or sequencing data available highlights a key concern for reproducibility.
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Affiliation(s)
- Brianna Cheng
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
| | - Marcel A Behr
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
| | - Benjamin P Howden
- The Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
| | | | - Robyn S Lee
- Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
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18
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Blake KS, Choi J, Dantas G. Approaches for characterizing and tracking hospital-associated multidrug-resistant bacteria. Cell Mol Life Sci 2021; 78:2585-2606. [PMID: 33582841 PMCID: PMC8005480 DOI: 10.1007/s00018-020-03717-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 10/26/2020] [Accepted: 11/17/2020] [Indexed: 12/24/2022]
Abstract
Hospital-associated infections are a major concern for global public health. Infections with antibiotic-resistant pathogens can cause empiric treatment failure, and for infections with multidrug-resistant bacteria which can overcome antibiotics of "last resort" there exists no alternative treatments. Despite extensive sanitization protocols, the hospital environment is a potent reservoir and vector of antibiotic-resistant organisms. Pathogens can persist on hospital surfaces and plumbing for months to years, acquire new antibiotic resistance genes by horizontal gene transfer, and initiate outbreaks of hospital-associated infections by spreading to patients via healthcare workers and visitors. Advancements in next-generation sequencing of bacterial genomes and metagenomes have expanded our ability to (1) identify species and track distinct strains, (2) comprehensively profile antibiotic resistance genes, and (3) resolve the mobile elements that facilitate intra- and intercellular gene transfer. This information can, in turn, be used to characterize the population dynamics of hospital-associated microbiota, track outbreaks to their environmental reservoirs, and inform future interventions. This review provides a detailed overview of the approaches and bioinformatic tools available to study isolates and metagenomes of hospital-associated bacteria, and their multi-layered networks of transmission.
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Affiliation(s)
- Kevin S Blake
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
| | - JooHee Choi
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Gautam Dantas
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA.
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19
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Islam MS, Chughtai AA, Nazneen A, Chowdhury KIA, Islam MT, Tarannum S, Islam SMH, Banu S, Seale H. A tuberculin skin test survey among healthcare workers in two public tertiary care hospitals in Bangladesh. PLoS One 2020; 15:e0243951. [PMID: 33332458 PMCID: PMC7745963 DOI: 10.1371/journal.pone.0243951] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 11/30/2020] [Indexed: 12/14/2022] Open
Abstract
In Bangladesh, there is currently no data on the burden of latent TB infection (LTBI) amongst hospital healthcare workers (HCWs). This study aimed to determine the prevalence of LTBI and compare the prevalence among HCWs in two public tertiary care hospitals. Between September 2018 and August 2019, we conducted a cross-sectional study in two public tertiary care general hospitals. Using a survey and tuberculin skin test (TST), we assessed risk factors for LTBI, adjusting for known and plausible confounders. In addition, a facility assessment was undertaken to understand the implementation of relevant IPC measures. The prevalence of LTBI among HCWs was 42%. HCWs spent a median of 6 hours (SD = 1.76, IQR 2.00) per day and attended an average of 1.87 pulmonary TB patients per week. HCWs did not receive any TB IPC training, the wards lacked a symptom checklist to screen patients for TB, and no masks were available for coughing patients. Seventy-seven percent reportedly did not use any facial protection (masks or respirators) while caring for patients. In the multivariable model adjusting for hospital level clustering effect, TST positivity was significantly higher among HCWs aged 35-45 years (aOR1.36, 95% CI: 1.06-1.73) and with >3 years of service (aOR 1.67, 95% CI: 1.62-1.72). HCWs working in the medicine ward had 3.65 (95% CI: 2.20-6.05) times, and HCWs in the gynecology and obstetrics ward had 2.46 (95% CI: 1.42-4.27) times higher odds of TST positivity compared to HCWs working in administrative areas. This study identified high prevalence of LTBI among HCWs. This may be due to the level of exposure to pulmonary TB patients, and/or limited use of personal protective equipment along with poor implementation of TB IPC in the hospitals. Considering the high prevalence of LTBI, we recommend the national TB program consider providing preventative therapy to the HCWs as the high-risk group, and implement TB IPC in the hospitals.
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Affiliation(s)
- Md Saiful Islam
- Infectious Diseases Division, Program for Emerging Infections, icddr,b, Dhaka, Bangladesh
- School of Population Health, University of New South Wales, Sydney, Australia
| | | | - Arifa Nazneen
- Infectious Diseases Division, Program for Emerging Infections, icddr,b, Dhaka, Bangladesh
| | | | | | - Sayeeda Tarannum
- Infectious Diseases Division, Program for Emerging Infections, icddr,b, Dhaka, Bangladesh
| | - S. M. Hasibul Islam
- Infectious Diseases Division, Program for Emerging Infections, icddr,b, Dhaka, Bangladesh
| | - Sayera Banu
- Infectious Diseases Division, Program for Emerging Infections, icddr,b, Dhaka, Bangladesh
| | - Holly Seale
- School of Population Health, University of New South Wales, Sydney, Australia
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20
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Guimaraes AMS, Zimpel CK. Mycobacterium bovis: From Genotyping to Genome Sequencing. Microorganisms 2020; 8:E667. [PMID: 32375210 PMCID: PMC7285088 DOI: 10.3390/microorganisms8050667] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 04/17/2020] [Accepted: 04/21/2020] [Indexed: 12/15/2022] Open
Abstract
Mycobacterium bovis is the main pathogen of bovine, zoonotic, and wildlife tuberculosis. Despite the existence of programs for bovine tuberculosis (bTB) control in many regions, the disease remains a challenge for the veterinary and public health sectors, especially in developing countries and in high-income nations with wildlife reservoirs. Current bTB control programs are mostly based on test-and-slaughter, movement restrictions, and post-mortem inspection measures. In certain settings, contact tracing and surveillance has benefited from M. bovis genotyping techniques. More recently, whole-genome sequencing (WGS) has become the preferential technique to inform outbreak response through contact tracing and source identification for many infectious diseases. As the cost per genome decreases, the application of WGS to bTB control programs is inevitable moving forward. However, there are technical challenges in data analyses and interpretation that hinder the implementation of M. bovis WGS as a molecular epidemiology tool. Therefore, the aim of this review is to describe M. bovis genotyping techniques and discuss current standards and challenges of the use of M. bovis WGS for transmission investigation, surveillance, and global lineages distribution. We compiled a series of associated research gaps to be explored with the ultimate goal of implementing M. bovis WGS in a standardized manner in bTB control programs.
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Affiliation(s)
- Ana M. S. Guimaraes
- Laboratory of Applied Research in Mycobacteria, Department of Microbiology, University of São Paulo, São Paulo 01246-904, Brazil;
| | - Cristina K. Zimpel
- Laboratory of Applied Research in Mycobacteria, Department of Microbiology, University of São Paulo, São Paulo 01246-904, Brazil;
- Department of Preventive Veterinary Medicine and Animal Health, University of São Paulo, São Paulo 01246-904, Brazil
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21
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AlMatar M, Var I, Kayar B, Köksal F. Differential Expression of Resistant and Efflux Pump Genes in MDR-TB Isolates. Endocr Metab Immune Disord Drug Targets 2020; 20:271-287. [DOI: 10.2174/1871530319666191009153834] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 06/21/2019] [Accepted: 07/22/2019] [Indexed: 12/20/2022]
Abstract
Background:Numerous investigations demonstrate efflux as a worldwide bacterial mode of action which contributes to the resistance of drugs. The activity of antibiotics, which subjects to efflux, can be improved by the combined usage of efflux inhibitors. However, the efflux role to the overall levels of antibiotic resistance of clinical M. tuberculosis isolates is inadequately comprehended and is still disregarded by many.Method:Here, we assessed the contribution of resistant genes associated with isoniazid (INH) and rifampin (R) resistance to the levels of drug resistance in the (27) clinical isolates of MDR-TB. Additionally, the role of the resistance for six putative drug efflux pump genes to the antibiotics was investigated. The level of katG expression was down-regulated in 24/27 (88.88%) of MDR-TB isolates. Of the 27 MDR-TB isolates, inhA, oxyR-ahpC, and rpoB showed either overexpression or up-regulation in 8 (29.62%), 4 (14.81 %), and 24 (88.88%), respectively. Moreover, the efflux pump genes drrA, drrB, efpA, Rv2459, Rv1634, and Rv1250 were overexpressed under INH/RIF plus fresh pomegranate juice (FPJ) stress signifying the efflux pumps contribution to the overall levels of the resistance of MDR-TB isolates.Conclusion:These results displayed that the levels of drug resistance of MDR-TB clinical isolates are due to combination among drug efflux pump and the presence of mutations in target genes, a truth which is often ignored by the specialists of tuberculosis in favour of the almost undoubted significance of drug target- gene mutations for the resistance in M. tuberculosis.
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Affiliation(s)
- Manaf AlMatar
- Department of Biotechnology, Institute of Natural and Applied Sciences (Fen Bilimleri Enstitusu), Cukurova University, Adana, Turkey
| | - Işıl Var
- Department of Food Engineering, Agricultural Faculty, Cukurova University, Adana, Turkey
| | - Begüm Kayar
- Department of Medical Microbiology, Faculty of Medicine, Cukurova University, Adana, Turkey
| | - Fatih Köksal
- Department of Medical Microbiology, Faculty of Medicine, Cukurova University, Adana, Turkey
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22
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Anyansi C, Keo A, Walker BJ, Straub TJ, Manson AL, Earl AM, Abeel T. QuantTB - a method to classify mixed Mycobacterium tuberculosis infections within whole genome sequencing data. BMC Genomics 2020; 21:80. [PMID: 31992201 PMCID: PMC6986090 DOI: 10.1186/s12864-020-6486-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 01/13/2020] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND Mixed infections of Mycobacterium tuberculosis and antibiotic heteroresistance continue to complicate tuberculosis (TB) diagnosis and treatment. Detection of mixed infections has been limited to molecular genotyping techniques, which lack the sensitivity and resolution to accurately estimate the multiplicity of TB infections. In contrast, whole genome sequencing offers sensitive views of the genetic differences between strains of M. tuberculosis within a sample. Although metagenomic tools exist to classify strains in a metagenomic sample, most tools have been developed for more divergent species, and therefore cannot provide the sensitivity required to disentangle strains within closely related bacterial species such as M. tuberculosis. Here we present QuantTB, a method to identify and quantify individual M. tuberculosis strains in whole genome sequencing data. QuantTB uses SNP markers to determine the combination of strains that best explain the allelic variation observed in a sample. QuantTB outputs a list of identified strains, their corresponding relative abundances, and a list of drugs for which resistance-conferring mutations (or heteroresistance) have been predicted within the sample. RESULTS We show that QuantTB has a high degree of resolution and is capable of differentiating communities differing by less than 25 SNPs and identifying strains down to 1× coverage. Using simulated data, we found QuantTB outperformed other metagenomic strain identification tools at detecting strains and quantifying strain multiplicity. In a real-world scenario, using a dataset of 50 paired clinical isolates from a study of patients with either reinfections or relapses, we found that QuantTB could detect mixed infections and reinfections at rates concordant with a manually curated approach. CONCLUSION QuantTB can determine infection multiplicity, identify hetero-resistance patterns, enable differentiation between relapse and re-infection, and clarify transmission events across seemingly unrelated patients - even in low-coverage (1×) samples. QuantTB outperforms existing tools and promises to serve as a valuable resource for both clinicians and researchers working with clinical TB samples.
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Affiliation(s)
- Christine Anyansi
- Delft Bioinformatics Lab, Delft University of Technology, Van Mourik Broekmanweg 6, Delft, 2628XE, The Netherlands.,Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA
| | - Arlin Keo
- Delft Bioinformatics Lab, Delft University of Technology, Van Mourik Broekmanweg 6, Delft, 2628XE, The Netherlands
| | - Bruce J Walker
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.,Applied Invention, LLC, 486 Green Street, Cambridge, MA, 02139, USA
| | - Timothy J Straub
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.,Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Abigail L Manson
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA
| | - Ashlee M Earl
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA
| | - Thomas Abeel
- Delft Bioinformatics Lab, Delft University of Technology, Van Mourik Broekmanweg 6, Delft, 2628XE, The Netherlands. .,Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
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23
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Dai E, Zhang H, Zhou X, Song Q, Li D, Luo L, Xu X, Jiang W, Ling H. MycoResistance: a curated resource of drug resistance molecules in Mycobacteria. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2019:5530356. [PMID: 31290951 PMCID: PMC6619405 DOI: 10.1093/database/baz074] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 05/08/2019] [Accepted: 05/16/2019] [Indexed: 12/01/2022]
Abstract
The emergence and spread of drug-resistant Mycobacterium tuberculosis is of global concern. To improve the understanding of drug resistance in Mycobacteria, numerous studies have been performed to discover diagnostic markers and genetic determinants associated with resistance to anti-tuberculosis drug. However, the related information is scattered in a massive body of literature, which is inconvenient for researchers to investigate the molecular mechanism of drug resistance. Therefore, we manually collected 1707 curated associations between 73 compounds and 132 molecules (including coding genes and non-coding RNAs) in 6 mycobacterial species from 465 studies. The experimental details of molecular epidemiology and mechanism exploration research were also summarized and recorded in our work. In addition, multidrug resistance and extensively drug resistance molecules were also extracted to interpret the molecular mechanisms that are responsible for cross resistance among anti-tuberculosis drugs. Finally, we constructed an omnibus repository named MycoResistance, a user friendly interface to conveniently browse, search and download all related entries. We hope that this elaborate database will serve as a beneficial resource for mechanism explanations, precise diagnosis and effective treatment of drug-resistant mycobacterial strains.
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Affiliation(s)
- Enyu Dai
- Department of Microbiology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China
| | - Hao Zhang
- Department of Microbiology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Wu Lien-Teh Institute, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Department of Parasitology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Heilongjiang Provincial Key Laboratory of Infection and Immunity, Xuefu Road, Nangang District, Harbin, China.,Key Laboratory of Pathogen Biology, 194 Xuefu Road, Nangang District, Harbin, P. R. China
| | - Xu Zhou
- Department of Biomedical Engineering, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Jiangjun Avenue, Jiangning District, Nanjing, P.R. China
| | - Qian Song
- Department of Biomedical Engineering, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Jiangjun Avenue, Jiangning District, Nanjing, P.R. China
| | - Di Li
- Department of Microbiology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Wu Lien-Teh Institute, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Department of Parasitology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Heilongjiang Provincial Key Laboratory of Infection and Immunity, Xuefu Road, Nangang District, Harbin, China.,Key Laboratory of Pathogen Biology, 194 Xuefu Road, Nangang District, Harbin, P. R. China
| | - Lei Luo
- Department of Microbiology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Wu Lien-Teh Institute, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Department of Parasitology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Heilongjiang Provincial Key Laboratory of Infection and Immunity, Xuefu Road, Nangang District, Harbin, China.,Key Laboratory of Pathogen Biology, 194 Xuefu Road, Nangang District, Harbin, P. R. China
| | - Xinyu Xu
- Department of Microbiology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Wu Lien-Teh Institute, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Department of Parasitology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Heilongjiang Provincial Key Laboratory of Infection and Immunity, Xuefu Road, Nangang District, Harbin, China.,Key Laboratory of Pathogen Biology, 194 Xuefu Road, Nangang District, Harbin, P. R. China
| | - Wei Jiang
- Department of Biomedical Engineering, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Jiangjun Avenue, Jiangning District, Nanjing, P.R. China
| | - Hong Ling
- Department of Microbiology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Wu Lien-Teh Institute, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Department of Parasitology, Harbin Medical University, Xuefu Road, Nangang District, Harbin, China.,Heilongjiang Provincial Key Laboratory of Infection and Immunity, Xuefu Road, Nangang District, Harbin, China.,Key Laboratory of Pathogen Biology, 194 Xuefu Road, Nangang District, Harbin, P. R. China
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24
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Mulholland CV, Shockey AC, Aung HL, Cursons RT, O'Toole RF, Gautam SS, Brites D, Gagneux S, Roberts SA, Karalus N, Cook GM, Pepperell CS, Arcus VL. Dispersal of Mycobacterium tuberculosis Driven by Historical European Trade in the South Pacific. Front Microbiol 2019; 10:2778. [PMID: 31921003 PMCID: PMC6915100 DOI: 10.3389/fmicb.2019.02778] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Accepted: 11/14/2019] [Indexed: 12/30/2022] Open
Abstract
Mycobacterium tuberculosis (Mtb) is a globally distributed bacterial pathogen whose population structure has largely been shaped by the activities of its obligate human host. Oceania was the last major global region to be reached by Europeans and is the last region for which the dispersal and evolution of Mtb remains largely unexplored. Here, we investigated the evolutionary history of the Euro-American L4.4 sublineage and its dispersal to the South Pacific. Using a phylodynamics approach and a dataset of 236 global Mtb L4.4 genomes we have traced the origins and dispersal of L4.4 strains to New Zealand. These strains are predominantly found in indigenous Māori and Pacific people and we identify a clade of European, likely French, origin that is prevalent in indigenous populations in both New Zealand and Canada. Molecular dating suggests the expansion of European trade networks in the early 19th century drove the dispersal of this clade to the South Pacific. We also identify historical and social factors within the region that have contributed to the local spread and expansion of these strains, including recent Pacific migrations to New Zealand and the rapid urbanization of Māori in the 20th century. Our results offer new insight into the expansion and dispersal of Mtb in the South Pacific and provide a striking example of the role of historical European migrations in the global dispersal of Mtb.
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Affiliation(s)
- Claire V Mulholland
- School of Science, University of Waikato, Hamilton, New Zealand.,Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand
| | - Abigail C Shockey
- Department of Medical Microbiology and Immunology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Htin L Aung
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand.,Department of Microbiology and Immunology, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Ray T Cursons
- School of Science, University of Waikato, Hamilton, New Zealand
| | - Ronan F O'Toole
- School of Medicine, University of Tasmania, Hobart, TAS, Australia.,School of Molecular Sciences, La Trobe University, Melbourne, VIC, Australia
| | - Sanjay S Gautam
- School of Medicine, University of Tasmania, Hobart, TAS, Australia
| | - Daniela Brites
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Sebastien Gagneux
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | | | | | - Gregory M Cook
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand.,Department of Microbiology and Immunology, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Caitlin S Pepperell
- Department of Medical Microbiology and Immunology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.,Department of Medicine, Division of Infectious Diseases, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Vickery L Arcus
- School of Science, University of Waikato, Hamilton, New Zealand.,Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand
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25
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Antibiotic resistance of Mycobacterium tuberculosis complex in Africa: A systematic review of current reports of molecular epidemiology, mechanisms and diagnostics. J Infect 2019; 79:550-571. [DOI: 10.1016/j.jinf.2019.10.006] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 10/13/2019] [Indexed: 12/11/2022]
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26
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Stimson J, Gardy J, Mathema B, Crudu V, Cohen T, Colijn C. Beyond the SNP Threshold: Identifying Outbreak Clusters Using Inferred Transmissions. Mol Biol Evol 2019; 36:587-603. [PMID: 30690464 DOI: 10.1093/molbev/msy242] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Whole-genome sequencing (WGS) is increasingly used to aid the understanding of pathogen transmission. A first step in analyzing WGS data is usually to define "transmission clusters," sets of cases that are potentially linked by direct transmission. This is often done by including two cases in the same cluster if they are separated by fewer single-nucleotide polymorphisms (SNPs) than a specified threshold. However, there is little agreement as to what an appropriate threshold should be. We propose a probabilistic alternative, suggesting that the key inferential target for transmission clusters is the number of transmissions separating cases. We characterize this by combining the number of SNP differences and the length of time over which those differences have accumulated, using information about case timing, molecular clock, and transmission processes. Our framework has the advantage of allowing for variable mutation rates across the genome and can incorporate other epidemiological data. We use two tuberculosis studies to illustrate the impact of our approach: with British Columbia data by using spatial divisions; with Republic of Moldova data by incorporating antibiotic resistance. Simulation results indicate that our transmission-based method is better in identifying direct transmissions than a SNP threshold, with dissimilarity between clusterings of on average 0.27 bits compared with 0.37 bits for the SNP-threshold method and 0.84 bits for randomly permuted data. These results show that it is likely to outperform the SNP-threshold method where clock rates are variable and sample collection times are spread out. We implement the method in the R package transcluster.
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Affiliation(s)
- James Stimson
- Department of Mathematics, Imperial College London, London, UK
| | - Jennifer Gardy
- British Columbia Centre for Disease Control, Communicable Disease Prevention and Control Services, Vancouver, Canada.,School of Population and Public Health, University of British Columbia, Vancouver, Canada
| | - Barun Mathema
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, USA
| | - Valeriu Crudu
- Phthisiopneumology Institute, Chisinau, Republic of Moldova
| | - Ted Cohen
- Yale University School of Public Health, New Haven
| | - Caroline Colijn
- Department of Mathematics, Imperial College London, London, UK.,Department of Mathematics, Simon Fraser University, Vancouver, Canada
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27
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Cohen KA, Manson AL, Abeel T, Desjardins CA, Chapman SB, Hoffner S, Birren BW, Earl AM. Extensive global movement of multidrug-resistant M. tuberculosis strains revealed by whole-genome analysis. Thorax 2019; 74:882-889. [PMID: 31048508 PMCID: PMC6788793 DOI: 10.1136/thoraxjnl-2018-211616] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 01/28/2019] [Accepted: 02/25/2019] [Indexed: 11/22/2022]
Abstract
Background While the international spread of multidrug-resistant (MDR) Mycobacterium tuberculosis strains is an acknowledged public health threat, a broad and more comprehensive examination of the global spread of MDR-tuberculosis (TB) using whole-genome sequencing has not yet been performed. Methods In a global dataset of 5310 M. tuberculosis whole-genome sequences isolated from five continents, we performed a phylogenetic analysis to identify and characterise clades of MDR-TB with respect to geographic dispersion. Results Extensive international dissemination of MDR-TB was observed, with identification of 32 migrant MDR-TB clades with descendants isolated in 17 unique countries. Relatively recent movement of strains from both Beijing and non-Beijing lineages indicated successful global spread of varied genetic backgrounds. Migrant MDR-TB clade members shared relatively recent common ancestry, with a median estimate of divergence of 13–27 years. Migrant extensively drug-resistant (XDR)-TB clades were not observed, although development of XDR-TB within migratory MDR-TB clades was common. Conclusions Application of genomic techniques to investigate global MDR migration patterns revealed extensive global spread of MDR clades between countries of varying TB burden. Further expansion of genomic studies to incorporate isolates from diverse global settings into a single analysis, as well as data sharing platforms that facilitate genomic data sharing across country lines, may allow for future epidemiological analyses to monitor for international transmission of MDR-TB. In addition, efforts to perform routine whole-genome sequencing on all newly identified M. tuberculosis, like in England, will serve to better our understanding of the transmission dynamics of MDR-TB globally.
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Affiliation(s)
- Keira A Cohen
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Abigail L Manson
- Broad Institute of Harvard and M.I.T, Cambridge, Massachusetts, USA
| | - Thomas Abeel
- Broad Institute of Harvard and M.I.T, Cambridge, Massachusetts, USA.,Delft Bioinformatics Lab, Technische Universiteit Delft Faculteit Technische Natuurwetenschappen, Delft, Netherlands
| | | | - Sinead B Chapman
- Broad Institute of Harvard and M.I.T, Cambridge, Massachusetts, USA
| | - Sven Hoffner
- Department of Public Health Sciences, Karolinska Institute, Stockholm, Sweden
| | - Bruce W Birren
- Broad Institute of Harvard and M.I.T, Cambridge, Massachusetts, USA
| | - Ashlee M Earl
- Broad Institute of Harvard and M.I.T, Cambridge, Massachusetts, USA
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28
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Dixit A, Freschi L, Vargas R, Calderon R, Sacchettini J, Drobniewski F, Galea JT, Contreras C, Yataco R, Zhang Z, Lecca L, Kolokotronis SO, Mathema B, Farhat MR. Whole genome sequencing identifies bacterial factors affecting transmission of multidrug-resistant tuberculosis in a high-prevalence setting. Sci Rep 2019; 9:5602. [PMID: 30944370 PMCID: PMC6447560 DOI: 10.1038/s41598-019-41967-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 03/20/2019] [Indexed: 11/09/2022] Open
Abstract
Whole genome sequencing (WGS) can elucidate Mycobacterium tuberculosis (Mtb) transmission patterns but more data is needed to guide its use in high-burden settings. In a household-based TB transmissibility study in Peru, we identified a large MIRU-VNTR Mtb cluster (148 isolates) with a range of resistance phenotypes, and studied host and bacterial factors contributing to its spread. WGS was performed on 61 of the 148 isolates. We compared transmission link inference using epidemiological or genomic data and estimated the dates of emergence of the cluster and antimicrobial drug resistance (DR) acquisition events by generating a time-calibrated phylogeny. Using a set of 12,032 public Mtb genomes, we determined bacterial factors characterizing this cluster and under positive selection in other Mtb lineages. Four of the 61 isolates were distantly related and the remaining 57 isolates diverged ca. 1968 (95%HPD: 1945-1985). Isoniazid resistance arose once and rifampin resistance emerged subsequently at least three times. Emergence of other DR types occurred as recently as within the last year of sampling. We identified five cluster-defining SNPs potentially contributing to transmissibility. In conclusion, clusters (as defined by MIRU-VNTR typing) may be circulating for decades in a high-burden setting. WGS allows for an enhanced understanding of transmission, drug resistance, and bacterial fitness factors.
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Affiliation(s)
- Avika Dixit
- Boston Children's Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
| | | | | | | | | | | | | | | | | | - Zibiao Zhang
- Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Leonid Lecca
- Harvard Medical School, Boston, MA, USA
- Socios En Salud, Lima, Peru
| | | | - Barun Mathema
- Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Maha R Farhat
- Harvard Medical School, Boston, MA, USA
- Massachussetts General Hospital, Boston, MA, USA
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29
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Oppong YEA, Phelan J, Perdigão J, Machado D, Miranda A, Portugal I, Viveiros M, Clark TG, Hibberd ML. Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance. BMC Genomics 2019; 20:252. [PMID: 30922221 PMCID: PMC6440112 DOI: 10.1186/s12864-019-5615-3] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 03/15/2019] [Indexed: 12/30/2022] Open
Abstract
Background Continuing evolution of the Mycobacterium tuberculosis (Mtb) complex genomes associated with resistance to anti-tuberculosis drugs is threatening tuberculosis disease control efforts. Both multi- and extensively drug resistant Mtb (MDR and XDR, respectively) are increasing in prevalence, but the full set of Mtb genes involved are not known. There is a need for increased sensitivity of genome-wide approaches in order to elucidate the genetic basis of anti-microbial drug resistance and gain a more detailed understanding of Mtb genome evolution in a context of widespread antimicrobial therapy. Population structure within the Mtb complex, due to clonal expansion, lack of lateral gene transfer and low levels of recombination between lineages, may be reducing statistical power to detect drug resistance associated variants. Results To investigate the effect of lineage-specific effects on the identification of drug resistance associations, we applied genome-wide association study (GWAS) and convergence-based (PhyC) methods to multiple drug resistance phenotypes of a global dataset of Mtb lineages 2 and 4, using both lineage-wise and combined approaches. We identify both well-established drug resistance variants and novel associations; uniquely identifying associations for both lineage-specific and -combined GWAS analyses. We report 17 potential novel associations between antimicrobial resistance phenotypes and Mtb genomic variants. Conclusions For GWAS, both lineage-specific and -combined analyses are useful, whereas PhyC may perform better in contexts of greater diversity. Unique associations with XDR in lineage-specific analyses provide evidence of diverging evolutionary trajectories between lineages 2 and 4 in response to antimicrobial drug therapy. Electronic supplementary material The online version of this article (10.1186/s12864-019-5615-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yaa E A Oppong
- Pathogen Molecular Biology Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
| | - Jody Phelan
- Pathogen Molecular Biology Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - João Perdigão
- iMed.ULisboa - Research Institute for Medicines, Faculdade de Farmácia, Universidade de Lisboa, Lisbon, Portugal
| | - Diana Machado
- Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, UNL, Lisbon, Portugal
| | - Anabela Miranda
- National Mycobacterium Reference Laboratory, Porto, Portugal
| | - Isabel Portugal
- iMed.ULisboa - Research Institute for Medicines, Faculdade de Farmácia, Universidade de Lisboa, Lisbon, Portugal
| | - Miguel Viveiros
- Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, UNL, Lisbon, Portugal
| | - Taane G Clark
- Pathogen Molecular Biology Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,Faculty of Epidemiology and Population Health, LSHTM, London, UK
| | - Martin L Hibberd
- Pathogen Molecular Biology Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
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30
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Deciphering Within-Host Microevolution of Mycobacterium tuberculosis through Whole-Genome Sequencing: the Phenotypic Impact and Way Forward. Microbiol Mol Biol Rev 2019; 83:83/2/e00062-18. [PMID: 30918049 DOI: 10.1128/mmbr.00062-18] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
The Mycobacterium tuberculosis genome is more heterogenous and less genetically stable within the host than previously thought. Currently, only limited data exist on the within-host microevolution, diversity, and genetic stability of M. tuberculosis As a direct consequence, our ability to infer M. tuberculosis transmission chains and to understand the full complexity of drug resistance profiles in individual patients is limited. Furthermore, apart from the acquisition of certain drug resistance-conferring mutations, our knowledge on the function of genetic variants that emerge within a host and their phenotypic impact remains scarce. We performed a systematic literature review of whole-genome sequencing studies of serial and parallel isolates to summarize the knowledge on genetic diversity and within-host microevolution of M. tuberculosis We identified genomic loci of within-host emerged variants found across multiple studies and determined their functional relevance. We discuss important remaining knowledge gaps and finally make suggestions on the way forward.
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Udwadia ZF, Tornheim JA, Ganatra S, DeLuca A, Rodrigues CS, Gupta A. Few eligible for the newly recommended short course MDR-TB regimen at a large Mumbai private clinic. BMC Infect Dis 2019; 19:94. [PMID: 30691407 PMCID: PMC6350313 DOI: 10.1186/s12879-019-3726-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Accepted: 01/14/2019] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND India has the world's highest tuberculosis burden, and Mumbai is particularly affected by multidrug resistant tuberculosis (MDR-TB). WHO recommends short, intensive treatment ("Short Course") for previously untreated pulmonary MDR-TB patients but does not require universal drug susceptibility testing (DST) before Short Course. DST would likely screen out many MDR-TB patients in places like Mumbai with significant drug resistance. METHODS MDR-TB patients at a private clinic were recruited for a prospective observational cohort. Short Course eligibility was evaluated by clinical criteria and DST results. Eligibility by DST was classified as rifampin monoresistance (as tested by Xpert MTB/RIF), rifampin, fluoroquinolones, and 2nd-line injectable drugs resistance (as tested by line probe assays) and resistance to other drugs. RESULTS Of 559 participants with MDR-TB, 33% met clinical eligibility for Short Course. DST for rifampin, fluoroquinolones, and 2nd-line injectable drugs excluded 74.7% of participants. Complete phenotypic DST excluded 96.6% of participants. Prior treatment with either 1st or 2nd-line drugs did not significantly affect eligibility. CONCLUSIONS In a global MDR-TB hotspot, < 5% of participants with MDR-TB were appropriate for Short Course by clinical characteristics and DST results. Rapid molecular testing would not sufficiently identify drug resistance in this population. Eligibility rates were not significantly reduced by prior TB treatment.
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Affiliation(s)
- Zarir F. Udwadia
- Medical Research Centre, P.D. Hinduja National Hospital, Veer Savarkar Road, Mahim, Mumbai, Maharashtra 400016 India
| | - Jeffrey A. Tornheim
- Division of Infectious Diseases, Center for Clinical Global Health Education, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Phipps 521, Baltimore, MD 21287 USA
| | - Shashank Ganatra
- Medical Research Centre, P.D. Hinduja National Hospital, Veer Savarkar Road, Mahim, Mumbai, Maharashtra 400016 India
| | - Andrea DeLuca
- Division of Global Disease Epidemiology and Control, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21287 USA
| | - Camilla S. Rodrigues
- Medical Research Centre, P.D. Hinduja National Hospital, Veer Savarkar Road, Mahim, Mumbai, Maharashtra 400016 India
| | - Amita Gupta
- Division of Infectious Diseases, Center for Clinical Global Health Education, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Phipps 521, Baltimore, MD 21287 USA
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Lalor MK, Casali N, Walker TM, Anderson LF, Davidson JA, Ratna N, Mullarkey C, Gent M, Foster K, Brown T, Magee J, Barrett A, Crook DW, Drobniewski F, Thomas HL, Abubakar I. The use of whole-genome sequencing in cluster investigation of a multidrug-resistant tuberculosis outbreak. Eur Respir J 2018; 51:13993003.02313-2017. [PMID: 29748309 DOI: 10.1183/13993003.02313-2017] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Accepted: 04/26/2018] [Indexed: 11/05/2022]
Abstract
We used whole-genome sequencing (WGS) to delineate transmission networks and investigate the benefits of WGS during cluster investigation.We included clustered cases of multidrug-resistant (MDR) tuberculosis (TB)/extensively drug-resistant (XDR) TB linked by mycobacterial interspersed repetitive unit variable tandem repeat (MIRU-VNTR) strain typing or epidemiological information in the national cluster B1006, notified between 2007 and 2013 in the UK. We excluded from further investigation cases whose isolates differed by greater than 12 single nucleotide polymorphisms (SNPs). Data relating to patients' social networks were collected.27 cases were investigated and 22 had WGS, eight of which (36%) were excluded as their isolates differed by more than 12 SNPs to other cases. 18 cases were ruled into the transmission network based on genomic and epidemiological information. Evidence of transmission was inconclusive in seven out of 18 cases (39%) in the transmission network following WGS and epidemiological investigation.This investigation of a drug-resistant TB cluster illustrates the opportunities and limitations of WGS in understanding transmission in a setting with a high proportion of migrant cases. The use of WGS should be combined with classical epidemiological methods. However, not every cluster will be solvable, regardless of the quality of genomic data.
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Affiliation(s)
- Maeve K Lalor
- Tuberculosis Section, National Infection Service, Public Health England, London, UK.,Institute for Global Health, University College London, London, UK
| | - Nicola Casali
- PHE National Mycobacterium Reference Service South, Public Health England, London, UK.,Dept of Infectious Diseases, Imperial College London, London, UK
| | - Timothy M Walker
- Nuffield Dept of Medicine, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Laura F Anderson
- Tuberculosis Section, National Infection Service, Public Health England, London, UK
| | - Jennifer A Davidson
- Tuberculosis Section, National Infection Service, Public Health England, London, UK
| | - Natasha Ratna
- Tuberculosis Section, National Infection Service, Public Health England, London, UK
| | - Cathy Mullarkey
- TB Health Visiting Service, Leeds Community Healthcare, Leeds, UK
| | - Mike Gent
- Yorkshire and the Humber Public Health England Centre, Public Health England, Leeds, UK
| | - Kirsty Foster
- North East Public Health England Centre, Public Health England, Newcastle, UK
| | - Tim Brown
- PHE National Mycobacterium Reference Service South, Public Health England, London, UK
| | - John Magee
- PHE North of England Mycobacterium Reference Centre, Freeman Hospital, Newcastle, UK.,School of Biology, Newcastle University, Newcastle, UK
| | - Anne Barrett
- PHE North of England Mycobacterium Reference Centre, Freeman Hospital, Newcastle, UK
| | - Derrick W Crook
- Nuffield Dept of Medicine, John Radcliffe Hospital, University of Oxford, Oxford, UK.,National Infection Service, Public Health England, London, UK
| | - Francis Drobniewski
- PHE National Mycobacterium Reference Service South, Public Health England, London, UK.,Dept of Infectious Diseases, Imperial College London, London, UK
| | - H Lucy Thomas
- Tuberculosis Section, National Infection Service, Public Health England, London, UK
| | - Ibrahim Abubakar
- Tuberculosis Section, National Infection Service, Public Health England, London, UK.,Institute for Global Health, University College London, London, UK
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Kigozi E, Kasule GW, Musisi K, Lukoye D, Kyobe S, Katabazi FA, Wampande EM, Joloba ML, Kateete DP. Prevalence and patterns of rifampicin and isoniazid resistance conferring mutations in Mycobacterium tuberculosis isolates from Uganda. PLoS One 2018; 13:e0198091. [PMID: 29847567 PMCID: PMC5976185 DOI: 10.1371/journal.pone.0198091] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 05/14/2018] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Accurate diagnosis of tuberculosis, especially by using rapid molecular assays, can reduce transmission of drug resistant tuberculosis in communities. However, the frequency of resistance conferring mutations varies with geographic location of Mycobacterium tuberculosis, and this affects the efficiency of rapid molecular assays in detecting resistance. This has created need for characterizing drug resistant isolates from different settings to investigate frequencies of resistance conferring mutations. Here, we describe the prevalence and patterns of rifampicin- and isoniazid- resistance conferring mutations in isolates from Uganda, which could be useful in the management of MDR-TB patients in Uganda and other countries in sub-Saharan Africa. RESULTS Ninety seven M. tuberculosis isolates were characterized, of which 38 were MDR, seven rifampicin-resistant, 12 isoniazid-mono-resistant, and 40 susceptible to rifampicin and isoniazid. Sequence analysis of the rpoB rifampicin-resistance determining region (rpoB/RRDR) revealed mutations in six codons: 588, 531, 526, 516, 513, and 511, of which Ser531Leu was the most frequent (40%, 18/45). Overall, the three mutations (Ser531Leu, His526Tyr, Asp516Tyr) frequently associated with rifampicin-resistance occurred in 76% of the rifampicin resistant isolates while 18% (8/45) of the rifampicin-resistant isolates lacked mutations in rpoB/RRDR. Furthermore, sequence analysis of katG and inhA gene promoter revealed mainly the Ser315Thr (76%, 38/50) and C(-15)T (8%, 4/50) mutations, respectively. These two mutations combined, which are frequently associated with isoniazid-resistance, occurred in 88% of the isoniazid resistant isolates. However, 20% (10/50) of the isoniazid-resistant isolates lacked mutations both in katG and inhA gene promoter. The sensitivity of sequence analysis of rpoB/RRDR for rifampicin-resistance via detection of high confidence mutations (Ser531Leu, His526Tyr, Asp516Tyr) was 81%, while it was 77% for analysis of katG and inhA gene promoter to detect isoniazid-resistance via detection of high confidence mutations (Ser315Thr, C(-15)T, T(-8)C). Furthermore, considering the circulating TB genotypes in Uganda, the isoniazid-resistance conferring mutations were more frequent in M. tuberculosis lineage 4/sub-lineage Uganda, perhaps explaining why this genotype is weakly associated with MDR-TB. CONCLUSION Sequence analysis of rpoB/RRDR, katG and inhA gene promoter is useful in detecting rifampicin/isoniazid resistant M. tuberculosis isolates in Uganda however, about ≤20% of the resistant isolates lack known resistance-conferring mutations hence rapid molecular assays may not detect them as resistant.
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Affiliation(s)
- Edgar Kigozi
- Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
- Department of Medical Microbiology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
| | | | - Kenneth Musisi
- National Tuberculosis Reference Laboratory, Kampala, Uganda
| | - Deus Lukoye
- National Tuberculosis/Leprosy Program Ministry of Health, Kampala, Uganda
| | - Samuel Kyobe
- Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
| | - Fred Ashaba Katabazi
- Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
- Department of Medical Microbiology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
| | - Eddie M. Wampande
- Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
- College of Veterinary Medicine, Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
| | - Moses L. Joloba
- Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
- Department of Medical Microbiology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
| | - David Patrick Kateete
- Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
- Department of Medical Microbiology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
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Coll F, Phelan J, Hill-Cawthorne GA, Nair MB, Mallard K, Ali S, Abdallah AM, Alghamdi S, Alsomali M, Ahmed AO, Portelli S, Oppong Y, Alves A, Bessa TB, Campino S, Caws M, Chatterjee A, Crampin AC, Dheda K, Furnham N, Glynn JR, Grandjean L, Minh Ha D, Hasan R, Hasan Z, Hibberd ML, Joloba M, Jones-López EC, Matsumoto T, Miranda A, Moore DJ, Mocillo N, Panaiotov S, Parkhill J, Penha C, Perdigão J, Portugal I, Rchiad Z, Robledo J, Sheen P, Shesha NT, Sirgel FA, Sola C, Oliveira Sousa E, Streicher EM, Helden PV, Viveiros M, Warren RM, McNerney R, Pain A, Clark TG. Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis. Nat Genet 2018; 50:307-316. [PMID: 29358649 DOI: 10.1038/s41588-017-0029-0] [Citation(s) in RCA: 201] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Accepted: 12/01/2017] [Indexed: 12/30/2022]
Abstract
To characterize the genetic determinants of resistance to antituberculosis drugs, we performed a genome-wide association study (GWAS) of 6,465 Mycobacterium tuberculosis clinical isolates from more than 30 countries. A GWAS approach within a mixed-regression framework was followed by a phylogenetics-based test for independent mutations. In addition to mutations in established and recently described resistance-associated genes, novel mutations were discovered for resistance to cycloserine, ethionamide and para-aminosalicylic acid. The capacity to detect mutations associated with resistance to ethionamide, pyrazinamide, capreomycin, cycloserine and para-aminosalicylic acid was enhanced by inclusion of insertions and deletions. Odds ratios for mutations within candidate genes were found to reflect levels of resistance. New epistatic relationships between candidate drug-resistance-associated genes were identified. Findings also suggest the involvement of efflux pumps (drrA and Rv2688c) in the emergence of resistance. This study will inform the design of new diagnostic tests and expedite the investigation of resistance and compensatory epistatic mechanisms.
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Affiliation(s)
- Francesc Coll
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Jody Phelan
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Grant A Hill-Cawthorne
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
- Sydney Emerging Infections and Biosecurity Institute and School of Public Health, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Mridul B Nair
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Kim Mallard
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Shahjahan Ali
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Abdallah M Abdallah
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Saad Alghamdi
- Laboratory Medicine Department, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Mona Alsomali
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Abdallah O Ahmed
- Department of Microbiology, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Stephanie Portelli
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Melbourne, Victoria, Australia
| | - Yaa Oppong
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Adriana Alves
- National Mycobacterium Reference Laboratory, Porto, Portugal
| | | | - Susana Campino
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Maxine Caws
- Liverpool School of Tropical Medicine, Liverpool, UK
- Pham Ngoc Thach Hospital for TB and Lung Diseases, Ho Chi Minh City, Vietnam
| | | | - Amelia C Crampin
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
- Karonga Prevention Study, Chilumba, Karonga, Malawi
| | - Keertan Dheda
- Lung Infection and Immunity Unit, UCT Lung Institute, University of Cape Town, Groote Schuur Hospital, Cape Town, South Africa
| | - Nicholas Furnham
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Judith R Glynn
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
- Karonga Prevention Study, Chilumba, Karonga, Malawi
| | - Louis Grandjean
- Laboratorio de Enfermedades Infecciosas, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Dang Minh Ha
- Pham Ngoc Thach Hospital for TB and Lung Diseases, Ho Chi Minh City, Vietnam
| | - Rumina Hasan
- Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
| | - Zahra Hasan
- Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
| | - Martin L Hibberd
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Moses Joloba
- Department of Medical Microbiology, Makerere University College of Health Sciences, Kampala, Uganda
| | - Edward C Jones-López
- Section of Infectious Diseases, Department of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, MA, USA
| | | | - Anabela Miranda
- National Mycobacterium Reference Laboratory, Porto, Portugal
| | - David J Moore
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Laboratorio de Enfermedades Infecciosas, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Nora Mocillo
- Reference Laboratory of Tuberculosis Control, Buenos Aires, Argentina
| | - Stefan Panaiotov
- National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria
| | | | - Carlos Penha
- Instituto Gulbenkian de Ciência, Lisbon, Portugal
| | - João Perdigão
- iMed.ULisboa-Research Institute for Medicines, Faculdade de Farmácia, Universidade de Lisboa, Lisbon, Portugal
| | - Isabel Portugal
- iMed.ULisboa-Research Institute for Medicines, Faculdade de Farmácia, Universidade de Lisboa, Lisbon, Portugal
| | - Zineb Rchiad
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Jaime Robledo
- Corporación para Investigaciones Biológicas, Universidad Pontificia Bolivariana, Medellín, Colombia
| | - Patricia Sheen
- Lung Infection and Immunity Unit, UCT Lung Institute, University of Cape Town, Groote Schuur Hospital, Cape Town, South Africa
| | | | - Frik A Sirgel
- Division of Molecular Biology and Human Genetics, SAMRC Centre for Tuberculosis Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Christophe Sola
- Institute for Integrative Cell Biology, CEA, CNRS, Université Paris-Saclay, Orsay, France
| | - Erivelton Oliveira Sousa
- Centro de Pesquisas Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Laboratorio Central de Saúde Pública Professor Gonçalo Moniz, Salvador, Brazil
| | - Elizabeth M Streicher
- Division of Molecular Biology and Human Genetics, SAMRC Centre for Tuberculosis Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Paul Van Helden
- Division of Molecular Biology and Human Genetics, SAMRC Centre for Tuberculosis Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Miguel Viveiros
- Unidade de Microbiologia Médica, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa (UNL), Lisbon, Portugal
| | - Robert M Warren
- Division of Molecular Biology and Human Genetics, SAMRC Centre for Tuberculosis Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Ruth McNerney
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.
- Lung Infection and Immunity Unit, UCT Lung Institute, University of Cape Town, Groote Schuur Hospital, Cape Town, South Africa.
| | - Arnab Pain
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
- Global Station for Zoonosis Control, Global Institution for Collaborative Research and Education (GI-CoRE), Hokkaido University, Sapporo, Japan.
| | - Taane G Clark
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
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Votintseva AA, Bradley P, Pankhurst L, Del Ojo Elias C, Loose M, Nilgiriwala K, Chatterjee A, Smith EG, Sanderson N, Walker TM, Morgan MR, Wyllie DH, Walker AS, Peto TEA, Crook DW, Iqbal Z. Same-Day Diagnostic and Surveillance Data for Tuberculosis via Whole-Genome Sequencing of Direct Respiratory Samples. J Clin Microbiol 2017; 55:1285-1298. [PMID: 28275074 PMCID: PMC5405248 DOI: 10.1128/jcm.02483-16] [Citation(s) in RCA: 216] [Impact Index Per Article: 30.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Accepted: 02/28/2017] [Indexed: 12/03/2022] Open
Abstract
Routine full characterization of Mycobacterium tuberculosis is culture based, taking many weeks. Whole-genome sequencing (WGS) can generate antibiotic susceptibility profiles to inform treatment, augmented with strain information for global surveillance; such data could be transformative if provided at or near the point of care. We demonstrate a low-cost method of DNA extraction directly from patient samples for M. tuberculosis WGS. We initially evaluated the method by using the Illumina MiSeq sequencer (40 smear-positive respiratory samples obtained after routine clinical testing and 27 matched liquid cultures). M. tuberculosis was identified in all 39 samples from which DNA was successfully extracted. Sufficient data for antibiotic susceptibility prediction were obtained from 24 (62%) samples; all results were concordant with reference laboratory phenotypes. Phylogenetic placement was concordant between direct and cultured samples. With Illumina MiSeq/MiniSeq, the workflow from patient sample to results can be completed in 44/16 h at a reagent cost of £96/£198 per sample. We then employed a nonspecific PCR-based library preparation method for sequencing on an Oxford Nanopore Technologies MinION sequencer. We applied this to cultured Mycobacterium bovis strain BCG DNA and to combined culture-negative sputum DNA and BCG DNA. For flow cell version R9.4, the estimated turnaround time from patient to identification of BCG, detection of pyrazinamide resistance, and phylogenetic placement was 7.5 h, with full susceptibility results 5 h later. Antibiotic susceptibility predictions were fully concordant. A critical advantage of MinION is the ability to continue sequencing until sufficient coverage is obtained, providing a potential solution to the problem of variable amounts of M. tuberculosis DNA in direct samples.
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Affiliation(s)
- Antonina A Votintseva
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Phelim Bradley
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Louise Pankhurst
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Carlos Del Ojo Elias
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Matthew Loose
- School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
| | | | | | - E Grace Smith
- Regional Centre for Mycobacteriology, PHE Public Health Laboratory, Birmingham Heartlands Hospital, Birmingham, United Kingdom
- Public Health England, Wellington House, Lambeth, London, United Kingdom
| | - Nicolas Sanderson
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Timothy M Walker
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Marcus R Morgan
- Microbiology Laboratory, John Radcliffe Hospital, Oxford University Hospitals NHS Trust, Oxford, United Kingdom
| | - David H Wyllie
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
- Public Health England, Wellington House, Lambeth, London, United Kingdom
- The Jenner Institute, University of Oxford, Oxford, United Kingdom
| | - A Sarah Walker
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
- National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, United Kingdom
| | - Tim E A Peto
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
- National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, United Kingdom
| | - Derrick W Crook
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
- Public Health England, Wellington House, Lambeth, London, United Kingdom
- The Jenner Institute, University of Oxford, Oxford, United Kingdom
| | - Zamin Iqbal
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
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36
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Outcomes, infectiousness, and transmission dynamics of patients with extensively drug-resistant tuberculosis and home-discharged patients with programmatically incurable tuberculosis: a prospective cohort study. THE LANCET RESPIRATORY MEDICINE 2017; 5:269-281. [DOI: 10.1016/s2213-2600(16)30433-7] [Citation(s) in RCA: 95] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2016] [Revised: 11/06/2016] [Accepted: 11/15/2016] [Indexed: 11/20/2022]
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37
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Manson AL, Cohen KA, Abeel T, Desjardins CA, Armstrong DT, Barry CE, Brand J, Chapman SB, Cho SN, Gabrielian A, Gomez J, Jodals AM, Joloba M, Jureen P, Lee JS, Malinga L, Maiga M, Nordenberg D, Noroc E, Romancenco E, Salazar A, Ssengooba W, Velayati AA, Winglee K, Zalutskaya A, Via LE, Cassell GH, Dorman SE, Ellner J, Farnia P, Galagan JE, Rosenthal A, Crudu V, Homorodean D, Hsueh PR, Narayanan S, Pym AS, Skrahina A, Swaminathan S, Van der Walt M, Alland D, Bishai WR, Cohen T, Hoffner S, Birren BW, Earl AM. Genomic analysis of globally diverse Mycobacterium tuberculosis strains provides insights into the emergence and spread of multidrug resistance. Nat Genet 2017; 49:395-402. [PMID: 28092681 PMCID: PMC5402762 DOI: 10.1038/ng.3767] [Citation(s) in RCA: 169] [Impact Index Per Article: 24.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Accepted: 12/14/2016] [Indexed: 11/09/2022]
Abstract
Multidrug-resistant tuberculosis (MDR-TB), caused by drug resistant strains of Mycobacterium tuberculosis, is an increasingly serious problem worldwide. In this study, we examined a dataset of 5,310 M. tuberculosis whole genome sequences from five continents. Despite great diversity with respect to geographic point of isolation, genetic background and drug resistance, patterns of drug resistance emergence were conserved globally. We have identified harbinger mutations that often precede MDR. In particular, the katG S315T mutation, conferring resistance to isoniazid, overwhelmingly arose before rifampicin resistance across all lineages, geographic regions, and time periods. Molecular diagnostics that include markers for rifampicin resistance alone will be insufficient to identify pre-MDR strains. Incorporating knowledge of pre-MDR polymorphisms, particularly katG S315, into molecular diagnostics will enable targeted treatment of patients with pre-MDR-TB to prevent further development of MDR-TB.
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Affiliation(s)
- Abigail L Manson
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Keira A Cohen
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,KwaZulu-Natal Research Institute for TB and HIV (K-RITH), Durban, South Africa.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Thomas Abeel
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands
| | | | - Derek T Armstrong
- Center for Tuberculosis Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Clifton E Barry
- National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, Maryland, USA
| | - Jeannette Brand
- Medical Research Council, TB Platform, Pretoria, South Africa
| | | | - Sinéad B Chapman
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Sang-Nae Cho
- International Tuberculosis Research Center, Changwon and Department of Microbiology, Yonsei University College of Medicine, Seoul, South Korea
| | - Andrei Gabrielian
- Office of Cyber Infrastructure and Computational Biology, National Institutes of Health, Rockville, Maryland, USA
| | - James Gomez
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Andreea M Jodals
- Clinical Hospital of Pneumology Leon Daniello, Cluj Napoca, Romania
| | - Moses Joloba
- Department of Medical Microbiology, Mycobacteriology Laboratory, Makerere University, Kampala, Uganda
| | | | - Jong Seok Lee
- International Tuberculosis Research Center, Changwon and Department of Microbiology, Yonsei University College of Medicine, Seoul, South Korea
| | | | - Mamoudou Maiga
- University of Sciences, Techniques and Technologies of Bamako (USTTB), Bamako, Mali
| | | | - Ecaterina Noroc
- Microbiology and Morphology Laboratory, Phthisiopneumology Institute, Chisinau, Moldova
| | - Elena Romancenco
- Microbiology and Morphology Laboratory, Phthisiopneumology Institute, Chisinau, Moldova
| | - Alex Salazar
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands
| | - Willy Ssengooba
- Department of Medical Microbiology, Mycobacteriology Laboratory, Makerere University, Kampala, Uganda
| | - A A Velayati
- Mycobacteriology Research Centre, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Kathryn Winglee
- Center for Tuberculosis Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Aksana Zalutskaya
- Republican Research and Practical Centre for Pulmonology and Tuberculosis, Minsk, Belarus
| | - Laura E Via
- National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, Maryland, USA
| | - Gail H Cassell
- Department of Global Health and Social Medicine, Harvard Medical School, Division of Global Health Equity, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Susan E Dorman
- Center for Tuberculosis Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jerrold Ellner
- Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts, USA
| | - Parissa Farnia
- Mycobacteriology Research Centre, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - James E Galagan
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,Department of Biomedical Engineering and Microbiology, Boston University, Boston, Massachusetts, USA
| | - Alex Rosenthal
- Office of Cyber Infrastructure and Computational Biology, National Institutes of Health, Rockville, Maryland, USA
| | - Valeriu Crudu
- Microbiology and Morphology Laboratory, Phthisiopneumology Institute, Chisinau, Moldova
| | | | - Po-Ren Hsueh
- National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan
| | | | - Alexander S Pym
- KwaZulu-Natal Research Institute for TB and HIV (K-RITH), Durban, South Africa
| | - Alena Skrahina
- Republican Research and Practical Centre for Pulmonology and Tuberculosis, Minsk, Belarus
| | | | | | - David Alland
- Rutgers-New Jersey Medical School, Newark, New Jersey, USA
| | - William R Bishai
- KwaZulu-Natal Research Institute for TB and HIV (K-RITH), Durban, South Africa.,Center for Tuberculosis Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Ted Cohen
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
| | | | - Bruce W Birren
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Ashlee M Earl
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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38
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Guthrie JL, Gardy JL. A brief primer on genomic epidemiology: lessons learned from Mycobacterium tuberculosis. Ann N Y Acad Sci 2016; 1388:59-77. [PMID: 28009051 DOI: 10.1111/nyas.13273] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Revised: 09/02/2016] [Accepted: 09/13/2016] [Indexed: 12/13/2022]
Abstract
Genomics is now firmly established as a technique for the investigation and reconstruction of communicable disease outbreaks, with many genomic epidemiology studies focusing on revealing transmission routes of Mycobacterium tuberculosis. In this primer, we introduce the basic techniques underlying transmission inference from genomic data, using illustrative examples from M. tuberculosis and other pathogens routinely sequenced by public health agencies. We describe the laboratory and epidemiological scenarios under which genomics may or may not be used, provide an introduction to sequencing technologies and bioinformatics approaches to identifying transmission-informative variation and resistance-associated mutations, and discuss how variation must be considered in the light of available clinical and epidemiological information to infer transmission.
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Affiliation(s)
- Jennifer L Guthrie
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jennifer L Gardy
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada.,Communicable Disease Prevention and Control Services, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
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39
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Phelan J, O’Sullivan DM, Machado D, Ramos J, Whale AS, O’Grady J, Dheda K, Campino S, McNerney R, Viveiros M, Huggett JF, Clark TG. The variability and reproducibility of whole genome sequencing technology for detecting resistance to anti-tuberculous drugs. Genome Med 2016; 8:132. [PMID: 28003022 PMCID: PMC5178084 DOI: 10.1186/s13073-016-0385-x] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 11/30/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The emergence of resistance to anti-tuberculosis drugs is a serious and growing threat to public health. Next-generation sequencing is rapidly gaining traction as a diagnostic tool for investigating drug resistance in Mycobacterium tuberculosis to aid treatment decisions. However, there are few little data regarding the precision of such sequencing for assigning resistance profiles. METHODS We investigated two sequencing platforms (Illumina MiSeq, Ion Torrent PGM™) and two rapid analytic pipelines (TBProfiler, Mykrobe predictor) using a well characterised reference strain (H37Rv) and clinical isolates from patients with tuberculosis resistant to up to 13 drugs. Results were compared to phenotypic drug susceptibility testing. To assess analytical robustness individual DNA samples were subjected to repeated sequencing. RESULTS The MiSeq and Ion PGM systems accurately predicted drug-resistance profiles and there was high reproducibility between biological and technical sample replicates. Estimated variant error rates were low (MiSeq 1 per 77 kbp, Ion PGM 1 per 41 kbp) and genomic coverage high (MiSeq 51-fold, Ion PGM 53-fold). MiSeq provided superior coverage in GC-rich regions, which translated into incremental detection of putative genotypic drug-specific resistance, including for resistance to para-aminosalicylic acid and pyrazinamide. The TBProfiler bioinformatics pipeline was concordant with reported phenotypic susceptibility for all drugs tested except pyrazinamide and para-aminosalicylic acid, with an overall concordance of 95.3%. When using the Mykrobe predictor concordance with phenotypic testing was 73.6%. CONCLUSIONS We have demonstrated high comparative reproducibility of two sequencing platforms, and high predictive ability of the TBProfiler mutation library and analytical pipeline, when profiling resistance to first- and second-line anti-tuberculosis drugs. However, platform-specific variability in coverage of some genome regions may have implications for predicting resistance to specific drugs. These findings may have implications for future clinical practice and thus deserve further scrutiny, set within larger studies and using updated mutation libraries.
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Affiliation(s)
- Jody Phelan
- Department of Pathogen Molecular Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT London, UK
| | | | - Diana Machado
- Unidade de Microbiologia Médica, Global Health and Tropical Medicine, GHTM, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Lisbon, Portugal
| | - Jorge Ramos
- Unidade de Microbiologia Médica, Global Health and Tropical Medicine, GHTM, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Lisbon, Portugal
| | - Alexandra S. Whale
- Molecular Biology, LGC Ltd, Queens Road, Teddington, Middlesex TW11 0LY UK
| | - Justin O’Grady
- Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ UK
| | - Keertan Dheda
- Division of Pulmonary Medicine and UCT Lung Institute, Lung Infection and Immunity Unit, University of Cape Town, Groote Schuur Hospital, Observatory, 7925, Cape Town, South Africa
| | - Susana Campino
- Department of Pathogen Molecular Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT London, UK
| | - Ruth McNerney
- Division of Pulmonary Medicine and UCT Lung Institute, Lung Infection and Immunity Unit, University of Cape Town, Groote Schuur Hospital, Observatory, 7925, Cape Town, South Africa
| | - Miguel Viveiros
- Unidade de Microbiologia Médica, Global Health and Tropical Medicine, GHTM, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Lisbon, Portugal
| | - Jim F. Huggett
- Molecular Biology, LGC Ltd, Queens Road, Teddington, Middlesex TW11 0LY UK
- School of Biosciences & Medicine, Faculty of Health & Medical Science, University of Surrey, Guildford, GU2 7XH UK
| | - Taane G. Clark
- Department of Pathogen Molecular Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT London, UK
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, WC1E 7HT London, UK
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40
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Ellington MJ, Ekelund O, Aarestrup FM, Canton R, Doumith M, Giske C, Grundman H, Hasman H, Holden MTG, Hopkins KL, Iredell J, Kahlmeter G, Köser CU, MacGowan A, Mevius D, Mulvey M, Naas T, Peto T, Rolain JM, Samuelsen Ø, Woodford N. The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST Subcommittee. Clin Microbiol Infect 2016; 23:2-22. [PMID: 27890457 DOI: 10.1016/j.cmi.2016.11.012] [Citation(s) in RCA: 317] [Impact Index Per Article: 39.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 11/18/2016] [Indexed: 12/11/2022]
Abstract
Whole genome sequencing (WGS) offers the potential to predict antimicrobial susceptibility from a single assay. The European Committee on Antimicrobial Susceptibility Testing established a subcommittee to review the current development status of WGS for bacterial antimicrobial susceptibility testing (AST). The published evidence for using WGS as a tool to infer antimicrobial susceptibility accurately is currently either poor or non-existent and the evidence / knowledge base requires significant expansion. The primary comparators for assessing genotypic-phenotypic concordance from WGS data should be changed to epidemiological cut-off values in order to improve differentiation of wild-type from non-wild-type isolates (harbouring an acquired resistance). Clinical breakpoints should be a secondary comparator. This assessment will reveal whether genetic predictions could also be used to guide clinical decision making. Internationally agreed principles and quality control (QC) metrics will facilitate early harmonization of analytical approaches and interpretive criteria for WGS-based predictive AST. Only data sets that pass agreed QC metrics should be used in AST predictions. Minimum performance standards should exist and comparative accuracies across different WGS laboratories and processes should be measured. To facilitate comparisons, a single public database of all known resistance loci should be established, regularly updated and strictly curated using minimum standards for the inclusion of resistance loci. For most bacterial species the major limitations to widespread adoption for WGS-based AST in clinical laboratories remain the current high-cost and limited speed of inferring antimicrobial susceptibility from WGS data as well as the dependency on previous culture because analysis directly on specimens remains challenging. For most bacterial species there is currently insufficient evidence to support the use of WGS-inferred AST to guide clinical decision making. WGS-AST should be a funding priority if it is to become a rival to phenotypic AST. This report will be updated as the available evidence increases.
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Affiliation(s)
- M J Ellington
- Antimicrobial Resistance and Healthcare Associated Infections (AMRHAI) Reference Unit, National Infection Service, Public Health England, London, UK
| | - O Ekelund
- Department of Clinical Microbiology and the EUCAST Development Laboratory, Kronoberg Region, Central Hospital, Växjö, Sweden
| | - F M Aarestrup
- National Food Institute, Research Group for Genomic Epidemiology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - R Canton
- Servicio de Microbiología, Hospital Ramón y Cajal and Instituto Ramón y Cajal de Investigación Sanitaria, Madrid, Spain
| | - M Doumith
- Antimicrobial Resistance and Healthcare Associated Infections (AMRHAI) Reference Unit, National Infection Service, Public Health England, London, UK
| | - C Giske
- Department of Laboratory Medicine, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | - H Grundman
- University Medical Centre Freiburg, Infection Prevention and Hospital Hygiene, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - H Hasman
- Statens Serum Institute, Department of Microbiology and Infection Control, Copenhagen, Denmark
| | - M T G Holden
- School of Medicine, Medical & Biological Sciences, North Haugh, University of St Andrews, UK
| | - K L Hopkins
- Antimicrobial Resistance and Healthcare Associated Infections (AMRHAI) Reference Unit, National Infection Service, Public Health England, London, UK
| | - J Iredell
- Westmead Institute for Medical Research, University of Sydney and Marie Bashir Institute, Sydney, NSW, Australia
| | - G Kahlmeter
- Department of Clinical Microbiology and the EUCAST Development Laboratory, Kronoberg Region, Central Hospital, Växjö, Sweden
| | - C U Köser
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - A MacGowan
- Department of Medical Microbiology, North Bristol NHS Trust, Southmead Hospital, Bristol, UK
| | - D Mevius
- Central Veterinary Institute (CVI) part of Wageningen University and Research Centre (WUR), Lelystad, The Netherlands; Department of Infectious Diseases and Immunology, Utrecht University, Utrecht, The Netherlands
| | - M Mulvey
- National Microbiology Laboratory, Winnipeg, Manitoba, Canada
| | - T Naas
- French National Reference Centre for Antibiotic Resistance, Bacteriology-Hygiene unit, Hôpital Bicêtre, APHP, LabEx LERMIT, University Paris Sud, Le Kremlin-Bicêtre, France
| | - T Peto
- Nuffield Department of Medicine, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - J-M Rolain
- PU-PH des Disciplines Pharmaceutiques, 1-URMITE CNRS IRD UMR 6236, IHU Méditerranée Infection, Valorization and Transfer, Aix Marseille Université, Faculté de Médecine et de Pharmacie, Marseille, France
| | - Ø Samuelsen
- Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, University Hospital of North Norway, Department of Microbiology and Infection Control, Tromsø, Norway
| | - N Woodford
- Antimicrobial Resistance and Healthcare Associated Infections (AMRHAI) Reference Unit, National Infection Service, Public Health England, London, UK.
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41
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Faksri K, Xia E, Tan JH, Teo YY, Ong RTH. In silico region of difference (RD) analysis of Mycobacterium tuberculosis complex from sequence reads using RD-Analyzer. BMC Genomics 2016; 17:847. [PMID: 27806686 PMCID: PMC5093977 DOI: 10.1186/s12864-016-3213-1] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Accepted: 10/25/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Whole-genome sequencing is increasingly used in clinical diagnosis of tuberculosis and study of Mycobacterium tuberculosis complex (MTC). MTC consists of several genetically homogenous mycobacteria species which can cause tuberculosis in humans and animals. Regions of difference (RDs) are commonly regarded as gold standard genetic markers for MTC classification. RESULTS We develop RD-Analyzer, a tool that can accurately infer the species and lineage of MTC isolates from sequence reads based on the presence and absence of a set of 31 RDs. Applied on a publicly available diverse set of 377 sequenced MTC isolates from known major species and lineages, RD-Analyzer achieved an accuracy of 98.14 % (370/377) in species prediction and a concordance of 98.47 % (257/261) in Mycobacterium tuberculosis lineage prediction compared to predictions based on single nucleotide polymorphism markers. By comparing respective sequencing read depths on each genomic position between isolates of different sublineages, we were able to identify the known RD markers in different sublineages of Lineage 4 and provide support for six potential delineating markers having high sensitivities and specificities for sublineage prediction. An extended version of RD-Analyzer was thus developed to allow user-defined RDs for lineage prediction. CONCLUSIONS RD-Analyzer is a useful and accurate tool for species, lineage and sublineage prediction using known RDs of MTC from sequence reads and is extendable to accepting user-defined RDs for analysis. RD-Analyzer is written in Python and is freely available at https://github.com/xiaeryu/RD-Analyzer .
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Affiliation(s)
- Kiatichai Faksri
- Department of Microbiology Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.,Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand
| | - Eryu Xia
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore
| | - Jun Hao Tan
- Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #10-01, Singapore, 117549, Singapore
| | - Yik-Ying Teo
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #10-01, Singapore, 117549, Singapore.,Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore.,Life Sciences Institute, National University of Singapore, Singapore, Singapore.,Genome Institute of Singapore, Singapore, Singapore
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #10-01, Singapore, 117549, Singapore.
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42
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Stucki D, Brites D, Jeljeli L, Coscolla M, Liu Q, Trauner A, Fenner L, Rutaihwa L, Borrell S, Luo T, Gao Q, Kato-Maeda M, Ballif M, Egger M, Macedo R, Mardassi H, Moreno M, Tudo Vilanova G, Fyfe J, Globan M, Thomas J, Jamieson F, Guthrie JL, Asante-Poku A, Yeboah-Manu D, Wampande E, Ssengooba W, Joloba M, Henry Boom W, Basu I, Bower J, Saraiva M, Vaconcellos SEG, Suffys P, Koch A, Wilkinson R, Gail-Bekker L, Malla B, Ley SD, Beck HP, de Jong BC, Toit K, Sanchez-Padilla E, Bonnet M, Gil-Brusola A, Frank M, Penlap Beng VN, Eisenach K, Alani I, Wangui Ndung'u P, Revathi G, Gehre F, Akter S, Ntoumi F, Stewart-Isherwood L, Ntinginya NE, Rachow A, Hoelscher M, Cirillo DM, Skenders G, Hoffner S, Bakonyte D, Stakenas P, Diel R, Crudu V, Moldovan O, Al-Hajoj S, Otero L, Barletta F, Jane Carter E, Diero L, Supply P, Comas I, Niemann S, Gagneux S. Mycobacterium tuberculosis lineage 4 comprises globally distributed and geographically restricted sublineages. Nat Genet 2016; 48:1535-1543. [PMID: 27798628 PMCID: PMC5238942 DOI: 10.1038/ng.3704] [Citation(s) in RCA: 242] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Accepted: 09/27/2016] [Indexed: 12/30/2022]
Abstract
Generalist and specialist species differ in the breadth of their ecological niches. Little is known about the niche width of obligate human pathogens. Here we analyzed a global collection of Mycobacterium tuberculosis lineage 4 clinical isolates, the most geographically widespread cause of human tuberculosis. We show that lineage 4 comprises globally distributed and geographically restricted sublineages, suggesting a distinction between generalists and specialists. Population genomic analyses showed that, whereas the majority of human T cell epitopes were conserved in all sublineages, the proportion of variable epitopes was higher in generalists. Our data further support a European origin for the most common generalist sublineage. Hence, the global success of lineage 4 reflects distinct strategies adopted by different sublineages and the influence of human migration.
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Affiliation(s)
- David Stucki
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland
| | - Daniela Brites
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland
| | - Leïla Jeljeli
- Forschungszentrum Borstel, Germany.,Institut Pasteur de Tunis, Université de Tunis El Manar, Tunis, Tunisia
| | - Mireia Coscolla
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland
| | - Qingyun Liu
- The Key Laboratory of Medical Molecular Virology of Ministries of Education and Health, Institutes of Biomedical Sciences and Institute of Medical Microbiology, School of Basic Medical Science of Fudan University, Shanghai, China
| | - Andrej Trauner
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland
| | - Lukas Fenner
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland.,Institute for Social and Preventive Medicine, University of Bern, Switzerland
| | - Liliana Rutaihwa
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland
| | - Sonia Borrell
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland
| | - Tao Luo
- Laboratory of Infection and Immunity, School of Basic Medical Science, West China Center of Medical Sciences, Sichuan University, Chengdu, Sichuan 610041, China
| | - Qian Gao
- The Key Laboratory of Medical Molecular Virology of Ministries of Education and Health, Institutes of Biomedical Sciences and Institute of Medical Microbiology, School of Basic Medical Science of Fudan University, Shanghai, China
| | | | - Marie Ballif
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland.,Institute for Social and Preventive Medicine, University of Bern, Switzerland
| | - Matthias Egger
- Institute for Social and Preventive Medicine, University of Bern, Switzerland
| | - Rita Macedo
- Laboratòrio de Saùde Publica, Lisbon, Portugal
| | - Helmi Mardassi
- Institut Pasteur de Tunis, Université de Tunis El Manar, Tunis, Tunisia
| | | | | | - Janet Fyfe
- Victorian Infectious Diseases Reference Laboratory, Victoria, Australia
| | - Maria Globan
- Victorian Infectious Diseases Reference Laboratory, Victoria, Australia
| | | | | | | | - Adwoa Asante-Poku
- Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana
| | - Dorothy Yeboah-Manu
- Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana
| | - Eddie Wampande
- Department of Medical Microbiology, Makerere University, Kampala, Uganda
| | - Willy Ssengooba
- Department of Medical Microbiology, Makerere University, Kampala, Uganda.,Department of Global Health, University of Amsterdam, Amsterdam, the Netherlands
| | - Moses Joloba
- Department of Medical Microbiology, Makerere University, Kampala, Uganda
| | - W Henry Boom
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, USA
| | - Indira Basu
- LabPlus, Auckland City Hospital, Auckland, New Zealand
| | - James Bower
- LabPlus, Auckland City Hospital, Auckland, New Zealand
| | - Margarida Saraiva
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal.,ICVS/3B's - PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | | | | | - Anastasia Koch
- Institute of Infectious Disease and Molecular Medicine and Department of Clinical Laboratory Sciences, University of Cape Town, South Africa
| | - Robert Wilkinson
- Institute of Infectious Disease and Molecular Medicine and Department of Clinical Laboratory Sciences, University of Cape Town, South Africa.,Department of Medicine, Imperial College London, UK.,The Francis Crick Institute Mill Hill Laboratory, London, UK
| | - Linda Gail-Bekker
- Institute of Infectious Disease and Molecular Medicine and Department of Clinical Laboratory Sciences, University of Cape Town, South Africa
| | - Bijaya Malla
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland
| | - Serej D Ley
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland.,Papua New Guinea Institute of Medical Research, Goroka, PNG
| | - Hans-Peter Beck
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland
| | | | - Kadri Toit
- Tartu University Hospital United Laboratories, Mycobacteriology, Tartu, Estonia
| | | | | | - Ana Gil-Brusola
- Department of Microbiology, University Hospital La Fe, Valencia, Spain
| | - Matthias Frank
- Institute of Tropical Medicine, University of Tübingen, Tübingen, Germany
| | - Veronique N Penlap Beng
- Institute Laboratory for Tuberculosis Research (LTR), Biotechnology Center (BTC), University of Yaoundé I, Yaoundé, Cameroon
| | - Kathleen Eisenach
- Department of Pathology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Issam Alani
- Department of Medical Laboratory Technology, Faculty of Medical Technology, Baghdad, Iraq
| | - Perpetual Wangui Ndung'u
- Institute of Tropical Medicine and Infectious Diseases (ITROMID), Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya
| | - Gunturu Revathi
- Department of Pathology, Aga Khan University Hospital (AKUH), Nairobi, Kenya
| | - Florian Gehre
- Insitute of Tropical Medicine, Antwerp, Belgium.,Medical Research Council, Fajara, the Gambia
| | | | - Francine Ntoumi
- Institute of Tropical Medicine, University of Tübingen, Tübingen, Germany.,Fondation Congolaise pour la Recherche Médicale, Université Marien Gouabi, Brazzaville, Congo
| | - Lynsey Stewart-Isherwood
- Right to Care and the Clinical HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa
| | - Nyanda E Ntinginya
- National Institute of Medical Research, Mbeya Medical Research Centre (NIMR-MMRC), Mbeya, Tanzania
| | - Andrea Rachow
- Division of Infectious Diseases and Tropical Medicine, Medical Centre of the University of Munich, Munich, Germany; German Centre for Infection Research (DZIF), partner site Munich, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, Medical Centre of the University of Munich, Munich, Germany; German Centre for Infection Research (DZIF), partner site Munich, Germany
| | - Daniela Maria Cirillo
- Emerging Bacterial Pathogens Unit, IRCCS, San Raffaele Scientific Institute, Milan, Italy
| | - Girts Skenders
- Riga East University Hospital, Centre of Tuberculosis and Lung Diseases, Riga, Latvia
| | - Sven Hoffner
- WHO Supranational TB Reference Laboratory, Department of Microbiology, The Public Health Agency of Sweden, Solna, Sweden
| | - Daiva Bakonyte
- Department of Immunology and Cell Biology, Institute of Biotechnology, Vilnius University, Vilnius, Lithuania
| | - Petras Stakenas
- Department of Immunology and Cell Biology, Institute of Biotechnology, Vilnius University, Vilnius, Lithuania
| | - Roland Diel
- Institute for Epidemiology, Schleswig-Holstein University Hospital, Kiel, Germany
| | - Valeriu Crudu
- National Tuberculosis Reference Laboratory, Phthysiopneumology Institute, Chisinau, Republic of Moldova
| | - Olga Moldovan
- 'Marius Nasta' Pneumophtisiology Institute, Bucharest, Romania
| | - Sahal Al-Hajoj
- Department of Infection and Immunity, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Larissa Otero
- Instituto de Medicina Tropical Alexander von Humboldt, Molecular Epidemiology Unit-Tuberculosis, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Francesca Barletta
- Instituto de Medicina Tropical Alexander von Humboldt, Molecular Epidemiology Unit-Tuberculosis, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - E Jane Carter
- Alpert School of Medicine at Brown University, Providence, Rhode Island, USA.,Moi University School of Medicine, Eldoret, Kenya
| | - Lameck Diero
- Moi University School of Medicine, Eldoret, Kenya
| | - Philip Supply
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, U1019 - UMR 8204 - CIIL - Centre d'Infection et d'Immunité de Lille, F-59000 Lille, France
| | - Iñaki Comas
- Institute of Biomedicine of Valencia (IBV-CSIC), 46010, Valencia, Spain.,CIBER Epidemiology and Public Health, Madrid, Spain
| | - Stefan Niemann
- Forschungszentrum Borstel, Germany.,German Center for Infection Research, Borstel Site, Borstel, Germany
| | - Sebastien Gagneux
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Switzerland
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Papaventsis D, Casali N, Kontsevaya I, Drobniewski F, Cirillo DM, Nikolayevskyy V. Whole genome sequencing of Mycobacterium tuberculosis for detection of drug resistance: a systematic review. Clin Microbiol Infect 2016; 23:61-68. [PMID: 27665704 DOI: 10.1016/j.cmi.2016.09.008] [Citation(s) in RCA: 74] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Revised: 09/10/2016] [Accepted: 09/15/2016] [Indexed: 01/02/2023]
Abstract
OBJECTIVES We conducted a systematic review to determine the diagnostic accuracy of whole genome sequencing (WGS) of Mycobacterium tuberculosis for the detection of resistance to first- and second-line anti-tuberculosis (TB) drugs. METHODS The study was conducted according to the criteria of the Preferred Reporting Items for Systematic Reviews group. A total of 20 publications were included. The sensitivity, specificity, positive-predictive value and negative-predictive value of WGS using phenotypic drug susceptibility testing methods as a reference standard were determined. RESULTS Anti-TB agents tested included all first-line drugs, a variety of reserve drugs, as well as new drugs. Polymorphisms in a total of 53 genes were tested for associations with drug resistance. Pooled sensitivity and specificity values for detection of resistance to selected first-line drugs were 0.98 (95% CI 0.93-0.98) and 0.98 (95% CI 0.98-1.00) for rifampicin and 0.97 (95% CI 0.94-0.99) and 0.93 (95% CI 0.91-0.96) for isoniazid, respectively. Due to high heterogeneity in study designs, lack of data, knowledge of resistance mechanisms and clarity on exclusion of phylogenetic markers, there was a significant variation in analytical performance of WGS for the remaining first-line, reserved drugs and new drugs. CONCLUSIONS Whole genome sequencing could be considered a promising alternative to existing phenotypic and molecular drug susceptibility testing methods for rifampicin and isoniazid pending standardization of analytical pipelines. To ensure clinical relevance of WGS for detection of M. tuberculosis complex drug resistance, future studies should include information on clinical outcomes.
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Affiliation(s)
- D Papaventsis
- National Reference Laboratory for Mycobacteria, Sotiria Chest Diseases Hospital, Athens, Greece
| | - N Casali
- Department of Medicine, Imperial College London, London, UK
| | - I Kontsevaya
- Department of Medicine, Imperial College London, London, UK
| | - F Drobniewski
- Department of Medicine, Imperial College London, London, UK
| | - D M Cirillo
- Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - V Nikolayevskyy
- Department of Medicine, Imperial College London, London, UK; PHE National Mycobacterium Reference Laboratory, London, UK.
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44
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Fox GJ, Schaaf HS, Mandalakas A, Chiappini E, Zumla A, Marais BJ. Preventing the spread of multidrug-resistant tuberculosis and protecting contacts of infectious cases. Clin Microbiol Infect 2016; 23:147-153. [PMID: 27592087 DOI: 10.1016/j.cmi.2016.08.024] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2016] [Revised: 08/24/2016] [Accepted: 08/25/2016] [Indexed: 01/23/2023]
Abstract
Prevention of multidrug-resistant and extensively drug-resistant tuberculosis (MDR/XDR-TB) is a top priority for global TB control, given the need to limit epidemic spread and considering the high cost, toxicity and poor treatment outcomes with available therapies. We performed a systematic literature review to evaluate the evidence for strategies to reduce MDR/XDR-TB transmission and disease progression. Rapid detection and timely initiation of effective treatment is critical to rendering MDR/XDR-TB cases non-infectious. The scale-up of rapid molecular testing has transformed the capacity of high-incidence settings to identify and treat patients with MDR/XDR-TB. Optimized infection control measures in hospitals and clinics are critical to protect other patients and healthcare workers, whereas creative measures to reduce transmission within community hotspots require consideration. Targeted screening of high-risk communities may enhance early case-detection and limit the spread of MDR/XDR-TB. Among infected contacts, preventive therapy promises to reduce the risk of disease progression. This is supported by observational cohort studies, but randomized trials are urgently needed to confirm these observations and guide policy formulation. Substantial investment in MDR/XDR-TB prevention and care will be critical if the ambitious global goal of TB elimination is to be realized.
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Affiliation(s)
- G J Fox
- Sydney Medical School, University of Sydney, Sydney, Australia.
| | - H S Schaaf
- Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - A Mandalakas
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - E Chiappini
- Paediatric Infectious Disease Unit, Meyer University Hospital, Department of Health Science, University of Florence, Florence, Italy
| | - A Zumla
- University College London and NIHR Biomedical Research Centre, UCL Hospitals NHS Foundation Trust, London, UK
| | - B J Marais
- The Children's Hospital at Westmead and the Marie Bashir Institute for Infectious Diseases and Biosecurity (MBI), University of Sydney, Sydney, Australia
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45
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Silva Feliciano C, Rodrigues Plaça J, Peronni K, Araújo Silva W, Roberto Bollela V. Evaluation of resistance acquisition during tuberculosis treatment using whole genome sequencing. Braz J Infect Dis 2016; 20:290-3. [PMID: 27004922 PMCID: PMC9425402 DOI: 10.1016/j.bjid.2016.01.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Revised: 12/21/2015] [Accepted: 01/05/2016] [Indexed: 12/03/2022] Open
Abstract
Tuberculosis (TB) is still considered a major global public health problem in the world and there is a concern about the worldwide increase of drug-resistance (DR). This paper describes the analysis of three Mycobacterium tuberculosis isolates from a single patient collected over a long treatment period of time. DR was initially investigated through phenotypic testing, followed by line probe assays (LPAs) and whole genome sequencing (WGS). It presents an intriguing situation where a multidrug-resistant (MDR-) TB case was diagnosed and treated based only on late phenotypic drug susceptibility testing of isolate 1. During the treatment, another two isolates were cultivated: isolate 2, nine months after starting MDR-TB treatment; and isolate 3, cultivated five months later, during regular use of anti-TB drugs. These two isolates were evaluated using molecular LPA and WGS, retrospectively. All mutations detected by LPA were also detected in the WGS, including conversion from fluoroquinolones susceptibility to resistance from isolate 2 to isolate 3. WGS showed additional mutations, including some which may confer resistance to other drugs not tested (terizidone/cycloserine) and mutations with no correspondent resistance in drug susceptibility testing (streptomycin and second-line injectable drugs).
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46
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Phelan J, Coll F, McNerney R, Ascher DB, Pires DEV, Furnham N, Coeck N, Hill-Cawthorne GA, Nair MB, Mallard K, Ramsay A, Campino S, Hibberd ML, Pain A, Rigouts L, Clark TG. Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance. BMC Med 2016; 14:31. [PMID: 27005572 PMCID: PMC4804620 DOI: 10.1186/s12916-016-0575-9] [Citation(s) in RCA: 87] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2015] [Accepted: 02/02/2016] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance. METHODS To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods. RESULTS The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites. CONCLUSIONS Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel resistance mutations to improve the design of tuberculosis control measures, such as diagnostics, and inform patient management.
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Affiliation(s)
- Jody Phelan
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Francesc Coll
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Ruth McNerney
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,University of Cape Town Lung Institute, Lung Infection & Immunity Unit, Old Main Building, Groote Schuur Hospital, Observatory, Cape Town, 7925, South Africa
| | - David B Ascher
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK
| | - Douglas E V Pires
- Centro de Pesquisas René Rachou, Fundação Oswaldo Cruz, Avenida Augusto de Lima 1715, Belo Horizonte, 30190-002, Brazil
| | - Nick Furnham
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Nele Coeck
- Mycobacteriology Unit, Institute of Tropical Medicine, Antwerp, Belgium
| | - Grant A Hill-Cawthorne
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.,Sydney Emerging Infections and Biosecurity Institute and School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW, 2006, Australia
| | - Mridul B Nair
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Kim Mallard
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Andrew Ramsay
- Special Programme for Research and Training in Tropical Diseases (TDR), World Health Organisation, Geneva, Switzerland
| | - Susana Campino
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Martin L Hibberd
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Arnab Pain
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Leen Rigouts
- Mycobacteriology Unit, Institute of Tropical Medicine, Antwerp, Belgium.,Department of Biomedical Sciences, Antwerp University, Antwerp, Belgium
| | - Taane G Clark
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK. .,Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK. .,Department of Pathogen Molecular Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK.
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47
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Hatherell HA, Colijn C, Stagg HR, Jackson C, Winter JR, Abubakar I. Interpreting whole genome sequencing for investigating tuberculosis transmission: a systematic review. BMC Med 2016; 14:21. [PMID: 27005433 PMCID: PMC4804562 DOI: 10.1186/s12916-016-0566-x] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2015] [Accepted: 01/23/2016] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Whole genome sequencing (WGS) is becoming an important part of epidemiological investigations of infectious diseases due to greater resolution and cost reductions compared to traditional typing approaches. Many public health and clinical teams will increasingly use WGS to investigate clusters of potential pathogen transmission, making it crucial to understand the benefits and assumptions of the analytical methods for investigating the data. We aimed to understand how different approaches affect inferences of transmission dynamics and outline limitations of the methods. METHODS We comprehensively searched electronic databases for studies that presented methods used to interpret WGS data for investigating tuberculosis (TB) transmission. Two authors independently selected studies for inclusion and extracted data. Due to considerable methodological heterogeneity between studies, we present summary data with accompanying narrative synthesis rather than pooled analyses. RESULTS Twenty-five studies met our inclusion criteria. Despite the range of interpretation tools, the usefulness of WGS data in understanding TB transmission often depends on the amount of genetic diversity in the setting. Where diversity is small, distinguishing re-infections from relapses may be impossible; interpretation may be aided by the use of epidemiological data, examining minor variants and deep sequencing. Conversely, when within-host diversity is large, due to genetic hitchhiking or co-infection of two dissimilar strains, it is critical to understand how it arose. Greater understanding of microevolution and mixed infection will enhance interpretation of WGS data. CONCLUSIONS As sequencing studies have sampled more intensely and integrated multiple sources of information, the understanding of TB transmission and diversity has grown, but there is still much to be learnt about the origins of diversity that will affect inferences from these data. Public health teams and researchers should combine epidemiological, clinical and WGS data to strengthen investigations of transmission.
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Affiliation(s)
- Hollie-Ann Hatherell
- CoMPLEX, University College London, London, WC1E 6BT, UK. .,Centre for Infectious Disease Epidemiology, Infection and Population Health, University College London, London, WC1E 6JB, UK.
| | - Caroline Colijn
- Department of Mathematics, Imperial College London, London, SW7 2AZ, UK
| | - Helen R Stagg
- Centre for Infectious Disease Epidemiology, Infection and Population Health, University College London, London, WC1E 6JB, UK
| | - Charlotte Jackson
- Centre for Infectious Disease Epidemiology, Infection and Population Health, University College London, London, WC1E 6JB, UK
| | - Joanne R Winter
- Centre for Infectious Disease Epidemiology, Infection and Population Health, University College London, London, WC1E 6JB, UK
| | - Ibrahim Abubakar
- Centre for Infectious Disease Epidemiology, Infection and Population Health, University College London, London, WC1E 6JB, UK.,Medical Research Council Clinical Trials Unit, 125 Kingsway, London, WC2B 6NH, UK
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48
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Rapid, comprehensive, and affordable mycobacterial diagnosis with whole-genome sequencing: a prospective study. THE LANCET RESPIRATORY MEDICINE 2015; 4:49-58. [PMID: 26669893 PMCID: PMC4698465 DOI: 10.1016/s2213-2600(15)00466-x] [Citation(s) in RCA: 212] [Impact Index Per Article: 23.6] [Reference Citation Analysis] [Abstract] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Revised: 10/17/2015] [Accepted: 10/28/2015] [Indexed: 12/01/2022]
Abstract
Background Slow and cumbersome laboratory diagnostics for Mycobacterium tuberculosis complex (MTBC) risk delayed treatment and poor patient outcomes. Whole-genome sequencing (WGS) could potentially provide a rapid and comprehensive diagnostic solution. In this prospective study, we compare real-time WGS with routine MTBC diagnostic workflows. Methods We compared sequencing mycobacteria from all newly positive liquid cultures with routine laboratory diagnostic workflows across eight laboratories in Europe and North America for diagnostic accuracy, processing times, and cost between Sept 6, 2013, and April 14, 2014. We sequenced specimens once using local Illumina MiSeq platforms and processed data centrally using a semi-automated bioinformatics pipeline. We identified species or complex using gene presence or absence, predicted drug susceptibilities from resistance-conferring mutations identified from reference-mapped MTBC genomes, and calculated genetic distance to previously sequenced UK MTBC isolates to detect outbreaks. WGS data processing and analysis was done by staff masked to routine reference laboratory and clinical results. We also did a microcosting analysis to assess the financial viability of WGS-based diagnostics. Findings Compared with routine results, WGS predicted species with 93% (95% CI 90–96; 322 of 345 specimens; 356 mycobacteria specimens submitted) accuracy and drug susceptibility also with 93% (91–95; 628 of 672 specimens; 168 MTBC specimens identified) accuracy, with one sequencing attempt. WGS linked 15 (16% [95% CI 10–26]) of 91 UK patients to an outbreak. WGS diagnosed a case of multidrug-resistant tuberculosis before routine diagnosis was completed and discovered a new multidrug-resistant tuberculosis cluster. Full WGS diagnostics could be generated in a median of 9 days (IQR 6–10), a median of 21 days (IQR 14–32) faster than final reference laboratory reports were produced (median of 31 days [IQR 21–44]), at a cost of £481 per culture-positive specimen, whereas routine diagnosis costs £518, equating to a WGS-based diagnosis cost that is 7% cheaper annually than are present diagnostic workflows. Interpretation We have shown that WGS has a scalable, rapid turnaround, and is a financially feasible method for full MTBC diagnostics. Continued improvements to mycobacterial processing, bioinformatics, and analysis will improve the accuracy, speed, and scope of WGS-based diagnosis. Funding National Institute for Health Research, Department of Health, Wellcome Trust, British Colombia Centre for Disease Control Foundation for Population and Public Health, Department of Clinical Microbiology, Trinity College Dublin.
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49
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Kendall EA, Fofana MO, Dowdy DW. Burden of transmitted multidrug resistance in epidemics of tuberculosis: a transmission modelling analysis. THE LANCET RESPIRATORY MEDICINE 2015; 3:963-72. [PMID: 26597127 PMCID: PMC4684734 DOI: 10.1016/s2213-2600(15)00458-0] [Citation(s) in RCA: 135] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2015] [Revised: 10/22/2015] [Accepted: 10/25/2015] [Indexed: 11/26/2022]
Abstract
Background Multidrug-resistant tuberculosis (MDR-TB) can be acquired through de novo mutation during TB treatment or through transmission from other individuals with active MDR-TB. Understanding the balance between these two mechanisms is essential when allocating resources for MDR-TB. Methods We constructed a dynamic transmission model of an MDR-TB epidemic, allowing for both treatment-related acquisition and person-to-person transmission of resistance. We used national TB notification data to inform Bayesian estimates of the fraction of each country’s 2013 MDR-TB incidence that resulted from MDR transmission rather than treatment-related MDR acquisition. Findings Global estimates of 3·5% MDR-TB prevalence among new TB notifications and 20·5% among retreatment notifications translate into an estimate that resistance transmission rather than acquisition accounts for a median 96% (95% UR: 68–100%) of all incident MDR-TB, and 61% (16–95%) of incident MDR-TB in previously-treated individuals. The estimated percentage of MDR-TB resulting from transmission varied substantially with different countries’ notification data; for example, we estimated this percentage at 48% (30–75%) of MDR-TB in Bangladesh, versus 99% (91–100%) in Uzbekistan. Estimates were most sensitive to estimates of the transmissibility of MDR strains, the probability of acquiring MDR during tuberculosis treatment, and the responsiveness of MDR TB to first-line treatment. Interpretation Notifications of MDR prevalence from most high-burden settings are most consistent with the vast majority of incident MDR-TB resulting from transmission rather than new treatment-related acquisition of resistance. Merely improving the treatment of drug-susceptible TB is unlikely to greatly reduce future MDR-TB incidence. Improved diagnosis and treatment of MDR-TB – including new tests and drug regimens – should be highly prioritized.
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Affiliation(s)
- Emily A Kendall
- Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, MD, USA.
| | - Mariam O Fofana
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - David W Dowdy
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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50
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Coscolla M, Barry PM, Oeltmann JE, Koshinsky H, Shaw T, Cilnis M, Posey J, Rose J, Weber T, Fofanov VY, Gagneux S, Kato-Maeda M, Metcalfe JZ. Genomic epidemiology of multidrug-resistant Mycobacterium tuberculosis during transcontinental spread. J Infect Dis 2015; 212:302-10. [PMID: 25601940 PMCID: PMC4490235 DOI: 10.1093/infdis/jiv025] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2014] [Accepted: 01/06/2015] [Indexed: 11/12/2022] Open
Abstract
The transcontinental spread of multidrug-resistant (MDR) tuberculosis is poorly characterized in molecular epidemiologic studies. We used genomic sequencing to understand the establishment and dispersion of MDR Mycobacterium tuberculosis within a group of immigrants to the United States. We used a genomic epidemiology approach to study a genotypically matched (by spoligotype, IS6110 restriction fragment length polymorphism, and mycobacterial interspersed repetitive units-variable number of tandem repeat signature) lineage 2/Beijing MDR strain implicated in an outbreak of tuberculosis among refugees in Thailand and consecutive cases within California. All 46 MDR M. tuberculosis genomes from both Thailand and California were highly related, with a median difference of 10 single-nucleotide polymorphisms (SNPs). The Wat Tham Krabok (WTK) strain is a new sequence type distinguished from all known Beijing strains by 55 SNPs and a genomic deletion (Rv1267c) associated with increased fitness. Sequence data revealed a highly prevalent MDR strain that included several closely related but distinct allelic variants within Thailand, rather than the occurrence of a single outbreak. In California, sequencing data supported multiple independent introductions of WTK with subsequent transmission and reactivation within the state, as well as a potential super spreader with a prolonged infectious period. Twenty-seven drug resistance-conferring mutations and 4 putative compensatory mutations were found within WTK strains. Genomic sequencing has substantial epidemiologic value in both low- and high-burden settings in understanding transmission chains of highly prevalent MDR strains.
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Affiliation(s)
- Mireia Coscolla
- Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute
- University of Basel, Switzerland
| | - Pennan M. Barry
- Division of Communicable Disease Control, Center for Infectious Diseases, California Department of Public Health, Richmond
| | | | | | - Tambi Shaw
- Division of Communicable Disease Control, Center for Infectious Diseases, California Department of Public Health, Richmond
| | - Martin Cilnis
- Division of Communicable Disease Control, Center for Infectious Diseases, California Department of Public Health, Richmond
| | - Jamie Posey
- Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jordan Rose
- Division of Pulmonary and Critical Care Medicine, Francis J. Curry International Tuberculosis Center, San Francisco General Hospital, University of California
| | - Terry Weber
- Division of Communicable Disease Control, Center for Infectious Diseases, California Department of Public Health, Richmond
| | | | - Sebastien Gagneux
- Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute
- University of Basel, Switzerland
| | - Midori Kato-Maeda
- Division of Pulmonary and Critical Care Medicine, Francis J. Curry International Tuberculosis Center, San Francisco General Hospital, University of California
| | - John Z. Metcalfe
- Division of Pulmonary and Critical Care Medicine, Francis J. Curry International Tuberculosis Center, San Francisco General Hospital, University of California
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