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Kontsevaya I, Cabibbe AM, Cirillo DM, DiNardo AR, Frahm N, Gillespie SH, Holtzman D, Meiwes L, Petruccioli E, Reimann M, Ruhwald M, Sabiiti W, Saluzzo F, Tagliani E, Goletti D. Update on the diagnosis of tuberculosis. Clin Microbiol Infect 2024; 30:1115-1122. [PMID: 37490968 DOI: 10.1016/j.cmi.2023.07.014] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 07/11/2023] [Accepted: 07/18/2023] [Indexed: 07/27/2023]
Abstract
BACKGROUND Tuberculosis (TB) remains a global public health threat, and the development of rapid and precise diagnostic tools is the key to enabling the early start of treatment, monitoring response to treatment, and preventing the spread of the disease. OBJECTIVES An overview of recent progress in host- and pathogen-based TB diagnostics. SOURCES We conducted a PubMed search of recent relevant articles and guidelines on TB screening and diagnosis. CONTENT An overview of currently used methods and perspectives in the following areas of TB diagnostics is provided: immune-based diagnostics, X-ray, clinical symptoms and scores, cough detection, culture of Mycobacterium tuberculosis and identifying its resistance profile using phenotypic and genotypic methods, including next-generation sequencing, sputum- and non-sputum-based molecular diagnosis of TB and monitoring of response to treatment. IMPLICATIONS A brief overview of the most relevant advances and changes in international guidelines regarding screening and diagnosing TB is provided in this review. It aims at reviewing all relevant areas of diagnostics, including both pathogen- and host-based methods.
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Affiliation(s)
- Irina Kontsevaya
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany; German Center for Infection Research (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany; Respiratory Medicine & International Health, University of Lübeck, Lübeck, Germany; Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.
| | | | - Daniela Maria Cirillo
- Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Andrew R DiNardo
- Global TB Program, Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA; Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Nicole Frahm
- Clinical Development, Bill & Melinda Gates Medical Research Institute, Cambridge, MA, USA
| | | | - David Holtzman
- Clinical Development, Bill & Melinda Gates Medical Research Institute, Cambridge, MA, USA; Section of Infectious Diseases, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Lennard Meiwes
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany; German Center for Infection Research (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany; Respiratory Medicine & International Health, University of Lübeck, Lübeck, Germany
| | - Elisa Petruccioli
- Translational Research Unit, National Institute for Infectious Diseases (INMI) "Lazzaro Spallanzani" - IRCCS, Rome, Italy
| | - Maja Reimann
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany; German Center for Infection Research (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany; Respiratory Medicine & International Health, University of Lübeck, Lübeck, Germany
| | | | - Wilber Sabiiti
- School of Medicine, University of St Andrews, St Andrews, United Kingdom
| | - Francesca Saluzzo
- Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Elisa Tagliani
- Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Delia Goletti
- Translational Research Unit, National Institute for Infectious Diseases (INMI) "Lazzaro Spallanzani" - IRCCS, Rome, Italy
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Dixit A, Ektefaie Y, Kagal A, Freschi L, Karyakarte R, Lokhande R, Groschel M, Tornheim JA, Gupte N, Pradhan NN, Paradkar MS, Deshmukh S, Kadam D, Schito M, Engelthaler DM, Gupta A, Golub J, Mave V, Farhat M. Drug resistance and epidemiological success of modern Mycobacterium tuberculosis lineages in western India. J Infect Dis 2024:jiae240. [PMID: 38819323 DOI: 10.1093/infdis/jiae240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 04/24/2024] [Accepted: 05/03/2024] [Indexed: 06/01/2024] Open
Abstract
BACKGROUND Transmission is contributing to the slow decline of tuberculosis (TB) incidence globally. Drivers of TB transmission in India, the country estimated to carry a quarter of the World's burden, are not well studied. We conducted a genomic epidemiology study to compare epidemiological success, host factors and drug resistance (DR) among the four major Mycobacterium tuberculosis (Mtb) lineages (L1-4) circulating in Pune, India. METHODS We performed whole-genome sequencing (WGS) of Mtb sputum culture-positive isolates from participants in two prospective cohort studies and predicted genotypic susceptibility using a validated random forest model. We used maximum likelihood estimation to build phylogenies. We compared lineage specific phylogenetic and time-scaled metrics to assess epidemiological success. RESULTS Of the 642 isolates that underwent WGS, 612 met sequence quality criteria. Most isolates belonged to L3 (44.6%). The majority (61.1%) of multidrug-resistant isolates belonged to L2 (P < 0.001). In molecular dating, L2 demonstrated a higher rate and more recent resistance acquisition. We measured higher clustering, and time-scaled haplotypic density (THD) for L4 and L2 compared to L3 and/or L1 suggesting higher epidemiological success. L4 demonstrated higher THD and clustering (OR 5.1 (95% CI 2.3-12.3) in multivariate models controlling for host factors and DR. CONCLUSION L2 shows a higher frequency of DR and both L2 and L4 demonstrate evidence of higher epidemiological success than L3 or L1 in the study setting. Our findings highlight the need for contact tracing around TB cases, and heightened surveillance of TB DR in India.
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Affiliation(s)
- Avika Dixit
- Division of Infectious Diseases, Boston Children's Hospital, Boston MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston MA, USA
| | - Yasha Ektefaie
- Department of Biomedical Informatics, Harvard Medical School, Boston MA, USA
| | - Anju Kagal
- Byramjee-Jeejeebhoy Government Medical College, Pune, India
| | - Luca Freschi
- Department of Biomedical Informatics, Harvard Medical School, Boston MA, USA
| | | | - Rahul Lokhande
- Byramjee-Jeejeebhoy Government Medical College, Pune, India
| | - Matthias Groschel
- Department of Biomedical Informatics, Harvard Medical School, Boston MA, USA
| | - Jeffrey A Tornheim
- Center for Clinical Global Health Education, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Center for Tuberculosis Research, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nikhil Gupte
- Center for Clinical Global Health Education, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins India, Pune, India
| | - Neeta N Pradhan
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins India, Pune, India
| | - Mandar S Paradkar
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins India, Pune, India
| | - Sona Deshmukh
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins India, Pune, India
| | - Dileep Kadam
- Byramjee-Jeejeebhoy Government Medical College, Pune, India
| | | | | | - Amita Gupta
- Center for Clinical Global Health Education, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of International Health, Johns Hopkins Bloomberg School of Public Heath, Baltimore, MD, USA
| | - Jonathan Golub
- Center for Tuberculosis Research, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Vidya Mave
- Center for Clinical Global Health Education, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins India, Pune, India
| | - Maha Farhat
- Department of Biomedical Informatics, Harvard Medical School, Boston MA, USA
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA
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3
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Esteves LS, Gomes LL, Brites D, Fandinho FCO, Bhering M, Pereira MADS, Conceição EC, Salvato R, da Costa BP, Medeiros RFDM, Caldas PCDS, Redner P, Dalcolmo MP, Eldholm V, Gagneux S, Rossetti ML, Kritski AL, Suffys PN. Genetic Characterization and Population Structure of Drug-Resistant Mycobacterium tuberculosis Isolated from Brazilian Patients Using Whole-Genome Sequencing. Antibiotics (Basel) 2024; 13:496. [PMID: 38927163 PMCID: PMC11200758 DOI: 10.3390/antibiotics13060496] [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: 04/12/2024] [Revised: 05/21/2024] [Accepted: 05/22/2024] [Indexed: 06/28/2024] Open
Abstract
The present study aimed to determine the genetic diversity of isolates of Mycobacterium tuberculosis (Mtb) from presumed drug-resistant tuberculosis patients from several states of Brazil. The isolates had been submitted to conventional drug susceptibility testing for first- and second-line drugs. Multidrug-resistant (MDR-TB) (54.8%) was the most frequent phenotypic resistance profile, in addition to an important high frequency of pre-extensive resistance (p-XDR-TB) (9.2%). Using whole-genome sequencing (WGS), we characterized 298 Mtb isolates from Brazil. Besides the analysis of genotype distribution and possible correlations between molecular and clinical data, we determined the performance of an in-house WGS pipeline with other online pipelines for Mtb lineages and drug resistance profile definitions. Sub-lineage 4.3 (52%) was the most frequent genotype, and the genomic approach revealed a p-XDR-TB level of 22.5%. We detected twenty novel mutations in three resistance genes, and six of these were observed in eight phenotypically resistant isolates. A cluster analysis of 170 isolates showed that 43.5% of the TB patients belonged to 24 genomic clusters, suggesting considerable ongoing transmission of DR-TB, including two interstate transmissions. The in-house WGS pipeline showed the best overall performance in drug resistance prediction, presenting the best accuracy values for five of the nine drugs tested. Significant associations were observed between suffering from fatal disease and genotypic p-XDR-TB (p = 0.03) and either phenotypic (p = 0.006) or genotypic (p = 0.0007) ethambutol resistance. The use of WGS analysis improved our understanding of the population structure of MTBC in Brazil and the genetic and clinical data correlations and demonstrated its utility for surveillance efforts regarding the spread of DR-TB, hopefully helping to avoid the emergence of even more resistant strains and to reduce TB incidence and mortality rates.
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Affiliation(s)
- Leonardo Souza Esteves
- Programa Acadêmico de Tuberculose da Faculdade de Medicina, Centro de Ciências da Saúde, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-590, RJ, Brazil;
- Centro de Desenvolvimento Científico e Tecnológico (CDCT), Secretaria Estadual de Saúde (SES-RS), Porto Alegre 90450-190, RS, Brazil;
- Laboratório de Biologia Molecular Aplicado à Micobactérias, Fundação Oswaldo Cruz (FIOCRUZ), Instituto Oswaldo Cruz (IOC), Rio de Janeiro 21040-360, RJ, Brazil; (L.L.G.); (P.N.S.)
| | - Lia Lima Gomes
- Laboratório de Biologia Molecular Aplicado à Micobactérias, Fundação Oswaldo Cruz (FIOCRUZ), Instituto Oswaldo Cruz (IOC), Rio de Janeiro 21040-360, RJ, Brazil; (L.L.G.); (P.N.S.)
| | - Daniela Brites
- Swiss Tropical and Public Health Institute (Swiss TPH), CH-4123 Allschwil, Switzerland; (D.B.); (S.G.)
- University of Basel, CH-4001 Basel, Switzerland
| | - Fátima Cristina Onofre Fandinho
- Centro de Referência Professor Hélio Fraga, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 22780-195, RJ, Brazil; (F.C.O.F.); (M.B.); (M.A.d.S.P.); (B.P.d.C.); (R.F.d.M.M.); (P.C.d.S.C.); (P.R.); (M.P.D.)
| | - Marcela Bhering
- Centro de Referência Professor Hélio Fraga, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 22780-195, RJ, Brazil; (F.C.O.F.); (M.B.); (M.A.d.S.P.); (B.P.d.C.); (R.F.d.M.M.); (P.C.d.S.C.); (P.R.); (M.P.D.)
| | - Márcia Aparecida da Silva Pereira
- Centro de Referência Professor Hélio Fraga, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 22780-195, RJ, Brazil; (F.C.O.F.); (M.B.); (M.A.d.S.P.); (B.P.d.C.); (R.F.d.M.M.); (P.C.d.S.C.); (P.R.); (M.P.D.)
| | - Emilyn Costa Conceição
- Department of Science and Innovation—National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa;
| | - Richard Salvato
- Centro de Desenvolvimento Científico e Tecnológico (CDCT), Secretaria Estadual de Saúde (SES-RS), Porto Alegre 90450-190, RS, Brazil;
| | - Bianca Porphirio da Costa
- Centro de Referência Professor Hélio Fraga, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 22780-195, RJ, Brazil; (F.C.O.F.); (M.B.); (M.A.d.S.P.); (B.P.d.C.); (R.F.d.M.M.); (P.C.d.S.C.); (P.R.); (M.P.D.)
| | - Reginalda Ferreira de Melo Medeiros
- Centro de Referência Professor Hélio Fraga, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 22780-195, RJ, Brazil; (F.C.O.F.); (M.B.); (M.A.d.S.P.); (B.P.d.C.); (R.F.d.M.M.); (P.C.d.S.C.); (P.R.); (M.P.D.)
| | - Paulo Cesar de Souza Caldas
- Centro de Referência Professor Hélio Fraga, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 22780-195, RJ, Brazil; (F.C.O.F.); (M.B.); (M.A.d.S.P.); (B.P.d.C.); (R.F.d.M.M.); (P.C.d.S.C.); (P.R.); (M.P.D.)
| | - Paulo Redner
- Centro de Referência Professor Hélio Fraga, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 22780-195, RJ, Brazil; (F.C.O.F.); (M.B.); (M.A.d.S.P.); (B.P.d.C.); (R.F.d.M.M.); (P.C.d.S.C.); (P.R.); (M.P.D.)
| | - Margareth Pretti Dalcolmo
- Centro de Referência Professor Hélio Fraga, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 22780-195, RJ, Brazil; (F.C.O.F.); (M.B.); (M.A.d.S.P.); (B.P.d.C.); (R.F.d.M.M.); (P.C.d.S.C.); (P.R.); (M.P.D.)
| | - Vegard Eldholm
- Norwegian Institute of Public Health, 0213 Oslo, Norway;
| | - Sebastien Gagneux
- Swiss Tropical and Public Health Institute (Swiss TPH), CH-4123 Allschwil, Switzerland; (D.B.); (S.G.)
- University of Basel, CH-4001 Basel, Switzerland
| | - Maria Lucia Rossetti
- Laboratório de Biologia Molecular, Universidade Luterana do Brasil (ULBRA), Canoas 92425-020, RS, Brazil;
| | - Afrânio Lineu Kritski
- Programa Acadêmico de Tuberculose da Faculdade de Medicina, Centro de Ciências da Saúde, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-590, RJ, Brazil;
| | - Philip Noel Suffys
- Laboratório de Biologia Molecular Aplicado à Micobactérias, Fundação Oswaldo Cruz (FIOCRUZ), Instituto Oswaldo Cruz (IOC), Rio de Janeiro 21040-360, RJ, Brazil; (L.L.G.); (P.N.S.)
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Utpatel C, Zavaleta M, Rojas-Bolivar D, Mühlbach A, Picoy J, Portugal W, Esteve-Solé A, Alsina L, Miotto P, Bartholomeu DC, Sanchez J, Cuadros DF, Alarcon JO, Niemann S, Huaman MA. Prison as a driver of recent transmissions of multidrug-resistant tuberculosis in Callao, Peru: a cross-sectional study. LANCET REGIONAL HEALTH. AMERICAS 2024; 31:100674. [PMID: 38500964 PMCID: PMC10945431 DOI: 10.1016/j.lana.2024.100674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 01/01/2024] [Accepted: 01/03/2024] [Indexed: 03/20/2024]
Abstract
Background We sought to identify resistance patterns and key drivers of recent multidrug-resistant tuberculosis (MDR-TB) transmission in a TB-prevalent area in Peru. Methods Cross-sectional study including MDR Mycobacterium tuberculosis complex (Mtbc) strains identified in Callao-Peru between April 2017 and February 2019. Mtbc DNA was extracted for whole genome sequencing which was used for phylogenetic inference, clustering, and resistance mutation analyses. Clusters indicative of recent transmission were defined based on a strain-to-strain distance of ≤5 (D5) single nucleotide polymorphisms (SNPs). Epidemiologic factors linked to MDR-TB clustering were analyzed using Poisson regression. Findings 171 unique MDR-Mtbc strains were included; 22 (13%) had additional fluoroquinolone resistance and were classified as pre-XDR. Six strains (3.5%) harboured bedaquiline (BDQ) resistance mutations and were classified as MDR + BDQ. 158 (92%) Mtbc strains belonged to lineage 4 and 13 (8%) to lineage 2. Using a cluster threshold of ≤5 SNPs, 98 (57%) strains were grouped in one of the 17 D5 clusters indicative of recent transmission, ranging in size from 2 to the largest cluster formed by 53 4.3.3 strains (group_1). Lineage 4.3.3 strains showed the overall highest cluster rate (43%). In multivariate analyses, current or previous imprisonment was independently associated with being part of any MDR-TB transmission clusters (adjusted prevalence ratio [aPR], 1.45; 95% CI, 1.09-1.92). Interpretation Pre-XDR-TB emerged in more than 10% of the MDR-TB strains investigated. Transmission of 4.3.3 Mtbc strains especially of the dominant group_1 clone is a major driver of the MDR-TB epidemic in Callao. Current or previous imprisonment was linked to recent MDR-TB transmissions, indicating an important role of prisons in driving the MDR-TB epidemic. Funding This work was supported in part by the ERANet-LAC Network of the European Union, Latin America and the Caribbean Countries on Joint Innovation and Research Activities, and FONDECYT. Additional support was received from Leibniz Science Campus Evolutionary Medicine of the Lung, the Deutsche Forschungsgemeinschaft (German Research Foundation, under Germany's Excellence Strategy-EXC 2167 Precision Medicine in Inflammation), and the Research Training Group 2501 TransEvo.
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Affiliation(s)
- Christian Utpatel
- Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
| | - Milagros Zavaleta
- Centro de Investigaciones Tecnológicas, Biomedicas y Medioambientales, Callao, Peru
| | - Daniel Rojas-Bolivar
- Centro de Investigaciones Tecnológicas, Biomedicas y Medioambientales, Callao, Peru
| | - Andreas Mühlbach
- Centro de Investigaciones Tecnológicas, Biomedicas y Medioambientales, Callao, Peru
| | - Janet Picoy
- Direccion Regional de Salud del Callao, Callao, Peru
| | | | - Ana Esteve-Solé
- Allergy and Clinical Immunology Department, Hospital Sant Joan de Déu Institut de Recerca Sant Joan de Déu, Universitat de Barcelona, Barcelona, Spain
| | - Laia Alsina
- Allergy and Clinical Immunology Department, Hospital Sant Joan de Déu Institut de Recerca Sant Joan de Déu, Universitat de Barcelona, Barcelona, Spain
| | - Paolo Miotto
- Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Daniella C. Bartholomeu
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Minas Gerais, Brazil
| | - Jorge Sanchez
- Centro de Investigaciones Tecnológicas, Biomedicas y Medioambientales, Callao, Peru
| | - Diego F. Cuadros
- Department of Geography and GIS, Health Geography and Disease Modeling Laboratory, University of Cincinnati, Cincinnati, USA
| | - Jorge O. Alarcon
- Centro de Investigaciones Tecnológicas, Biomedicas y Medioambientales, Callao, Peru
- Epidemiology Section, Instituto de Medicina Tropical, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | - Stefan Niemann
- Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
- German Center for Infection Research, Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany
| | - Moises A. Huaman
- Centro de Investigaciones Tecnológicas, Biomedicas y Medioambientales, Callao, Peru
- Department of Internal Medicine, Division of Infectious Diseases, University of Cincinnati, Cincinnati, USA
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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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6
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Hall MB, Coin LJM. Pangenome databases improve host removal and mycobacteria classification from clinical metagenomic data. Gigascience 2024; 13:giae010. [PMID: 38573185 PMCID: PMC10993716 DOI: 10.1093/gigascience/giae010] [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: 09/18/2023] [Revised: 01/10/2024] [Accepted: 02/27/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Culture-free real-time sequencing of clinical metagenomic samples promises both rapid pathogen detection and antimicrobial resistance profiling. However, this approach introduces the risk of patient DNA leakage. To mitigate this risk, we need near-comprehensive removal of human DNA sequences at the point of sequencing, typically involving the use of resource-constrained devices. Existing benchmarks have largely focused on the use of standardized databases and largely ignored the computational requirements of depletion pipelines as well as the impact of human genome diversity. RESULTS We benchmarked host removal pipelines on simulated and artificial real Illumina and Nanopore metagenomic samples. We found that construction of a custom kraken database containing diverse human genomes results in the best balance of accuracy and computational resource usage. In addition, we benchmarked pipelines using kraken and minimap2 for taxonomic classification of Mycobacterium reads using standard and custom databases. With a database representative of the Mycobacterium genus, both tools obtained improved specificity and sensitivity, compared to the standard databases for classification of Mycobacterium tuberculosis. Computational efficiency of these custom databases was superior to most standard approaches, allowing them to be executed on a laptop device. CONCLUSIONS Customized pangenome databases provide the best balance of accuracy and computational efficiency when compared to standard databases for the task of human read removal and M. tuberculosis read classification from metagenomic samples. Such databases allow for execution on a laptop, without sacrificing accuracy, an especially important consideration in low-resource settings. We make all customized databases and pipelines freely available.
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Affiliation(s)
- Michael B Hall
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, 3000 Victoria, Australia
| | - Lachlan J M Coin
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, 3000 Victoria, Australia
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Walter KS, Cohen T, Mathema B, Colijn C, Sobkowiak B, Comas I, Goig GA, Croda J, Andrews JR. Signatures of transmission in within-host M. tuberculosis variation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.28.23300451. [PMID: 38234741 PMCID: PMC10793532 DOI: 10.1101/2023.12.28.23300451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Background Because M. tuberculosis evolves slowly, transmission clusters often contain multiple individuals with identical consensus genomes, making it difficult to reconstruct transmission chains. Finding additional sources of shared M. tuberculosis variation could help overcome this problem. Previous studies have reported M. tuberculosis diversity within infected individuals; however, whether within-host variation improves transmission inferences remains unclear. Methods To evaluate the transmission information present in within-host M. tuberculosis variation, we re-analyzed publicly available sequence data from three household transmission studies, using household membership as a proxy for transmission linkage between donor-recipient pairs. Findings We found moderate levels of minority variation present in M. tuberculosis sequence data from cultured isolates that varied significantly across studies (mean: 6, 7, and 170 minority variants above a 1% minor allele frequency threshold, outside of PE/PPE genes). Isolates from household members shared more minority variants than did isolates from unlinked individuals in the three studies (mean 98 shared minority variants vs. 10; 0.8 vs. 0.2, and 0.7 vs. 0.2, respectively). Shared within-host variation was significantly associated with household membership (OR: 1.51 [1.30,1.71], for one standard deviation increase in shared minority variants). Models that included shared within-host variation improved the accuracy of predicting household membership in all three studies as compared to models without within-host variation (AUC: 0.95 versus 0.92, 0.99 versus 0.95, and 0.93 versus 0.91). Interpretation Within-host M. tuberculosis variation persists through culture and could enhance the resolution of transmission inferences. The substantial differences in minority variation recovered across studies highlights the need to optimize approaches to recover and incorporate within-host variation into automated phylogenetic and transmission inference. Funding NIAID: 5K01AI173385.
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Affiliation(s)
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, USA
| | - Barun Mathema
- Department of Epidemiology, Columbia University Mailman School of Public Health; New York, United States
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University; Burnaby, Canada
| | - Benjamin Sobkowiak
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, USA
| | - Iñaki Comas
- Institute of Biomedicine of Valencia (CSIC), Valencia, Spain
| | - Galo A Goig
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Julio Croda
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, USA
- Federal University of Mato Grosso do Sul - UFMS, Campo Grande, MS, Brazil
- Oswaldo Cruz Foundation Mato Grosso do Sul, Mato Grosso do Sul, Brazil
| | - Jason R Andrews
- Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA
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Meaza A, Riviere E, Bonsa Z, Rennie V, Gebremicael G, de Diego-Fuertes M, Meehan CJ, Medhin G, Abebe G, Ameni G, Van Rie A, Gumi B. Genomic transmission clusters and circulating lineages of Mycobacterium tuberculosis among refugees residing in refugee camps in Ethiopia. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2023; 116:105530. [PMID: 38008242 DOI: 10.1016/j.meegid.2023.105530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 11/15/2023] [Accepted: 11/19/2023] [Indexed: 11/28/2023]
Abstract
BACKGROUND Understanding the transmission dynamics of Mycobacterium tuberculosis (Mtb) could benefit the design of tuberculosis (TB) prevention and control strategies for refugee populations. Whole Genome Sequencing (WGS) has not yet been used to document the Mtb transmission dynamics among refugees in Ethiopia. We applied WGS to accurately identify transmission clusters and Mtb lineages among TB cases in refugee camps in Ethiopia. METHOD AND DESIGN We conducted a cross-sectional study of 610 refugees in refugee camps in Ethiopia presenting with symptoms of TB. WGS data of 67 isolates was analyzed using the Maximum Accessible Genome for Mtb Analysis (MAGMA) pipeline; iTol and FigTree were used to visualize phylogenetic trees, lineages, and the presence of transmission clusters. RESULTS Mtb culture-positive refugees originated from South Sudan (52/67, 77.6%), Somalia (9/67, 13.4%). Eritrea (4/67, 6%), and Sudan (2/67, 3%). The majority (52, 77.6%) of the isolates belonged to Mtb lineage (L) 3, and one L9 was identified from a Somalian refugee. The vast majority (82%) of the isolates were pan-susceptible Mtb, and none were multi-drug-resistant (MDR)-TB. Based on the 5-single nucleotide polymorphisms cutoff, we identified eight potential transmission clusters containing 23.9% of the isolates. Contact investigation confirmed epidemiological links with either family or social interaction within the refugee camps or with neighboring refugee camps. CONCLUSION Four lineages (L1, L3, L4, and L9) were identified, with the majority of strains being L3, reflecting the Mtb L3 dominance in South Sudan, where the majority of refugees originated from. Recent transmission among refugees was relatively low (24%), likely due to the short study period. The improved understanding of the Mtb transmission dynamics using WGS in refugee camps could assist in designing effective TB control programs for refugees.
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Affiliation(s)
- Abyot Meaza
- Aklilu Lemma Institute of Pathobiology (ALIPB), Addis Ababa University (AAU), PO Box 1176, Sefere Selam campus, Addis Ababa, Ethiopia; Ethiopian Public Health Institute (EPHI), PO Box 1242, Swaziland Street, Addis Ababa, Ethiopia.
| | - Emmanuel Riviere
- Family Medicine and Population Health (FAMPOP), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Zegeye Bonsa
- Mycobacteriology Research Center, Jimma University, Jimma, Ethiopia
| | - Vincent Rennie
- Family Medicine and Population Health (FAMPOP), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Gebremedhin Gebremicael
- Ethiopian Public Health Institute (EPHI), PO Box 1242, Swaziland Street, Addis Ababa, Ethiopia
| | - Miguel de Diego-Fuertes
- Family Medicine and Population Health (FAMPOP), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Conor J Meehan
- Department of Biosciences, Nottingham Trent University, Nottingham, UK
| | - Girmay Medhin
- Aklilu Lemma Institute of Pathobiology (ALIPB), Addis Ababa University (AAU), PO Box 1176, Sefere Selam campus, Addis Ababa, Ethiopia
| | - Gemeda Abebe
- Mycobacteriology Research Center, Jimma University, Jimma, Ethiopia; Department of Medical Laboratory Sciences, Jimma University, Jimma, Ethiopia
| | - Gobena Ameni
- Aklilu Lemma Institute of Pathobiology (ALIPB), Addis Ababa University (AAU), PO Box 1176, Sefere Selam campus, Addis Ababa, Ethiopia; Department of Veterinary Medicine, College of Agriculture and Veterinary Medicine, United Arab Emirates University, PO Box 15551, Al Ain, United Arab Emirates
| | - Annelies Van Rie
- Family Medicine and Population Health (FAMPOP), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Balako Gumi
- Aklilu Lemma Institute of Pathobiology (ALIPB), Addis Ababa University (AAU), PO Box 1176, Sefere Selam campus, Addis Ababa, Ethiopia
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9
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Mijiti P, Liu C, Hong C, Li M, Tan X, Zheng K, Li B, Ji L, Mao Q, Jiang Q, Takiff H, Fang H, Tan W, Gao Q. Implications for TB control among migrants in large cities in China: A prospective population-based genomic epidemiology study in Shenzhen. Emerg Microbes Infect 2023; 13:2287119. [PMID: 37990991 PMCID: PMC10810669 DOI: 10.1080/22221751.2023.2287119] [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: 08/29/2023] [Accepted: 11/19/2023] [Indexed: 11/23/2023]
Abstract
Internal migrants are a challenge for TB control in large Chinese cities and understanding this epidemiology is crucial for designing effective control and prevention strategies. We conducted a prospective genomic epidemiological study of culture-positive TB patients diagnosed between June 1, 2018 and May 31, 2021 in the Longhua District of Shenzhen. Treatment status was obtained from local and national TB registries and all isolates were sequenced. Genomic clusters were defined as strains differing by ≤12 SNPs. Risk factors for clustering were identified with multivariable analysis and then Bayesian models and TransPhylo were used to infer the timing of transmission within clusters. Of the 2277 culture-positive patients, 70.1% (1596/2277) were migrants: 72.1% (1043/1446) of the migrants patients developed TB within two years of arriving in Longhua; 38.8% within 6 months of arriving; and 12.3% (104/843) had TB symptoms when they arrived. Only 15.4% of Longhua strains were in genomic clusters. More than one third (33.6%) of patients were not treated in Shenzhen but were involved in nearly one third of the recent transmission events. Clustering was associated with migrants not treated in Shenzhen, males, and teachers/trainers. TB in Longhua is prinicipally due to reactivation of infections in migrants, but a proportion may have had clinical or incipient TB upon arrival in the district. Patients diagnosed but not treated in Longhua were involved in recent local TB transmission. Controlling TB in Shenzhen will require strategies to comprehensively diagnose and treat active TB in the internal migrant population.
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Affiliation(s)
- Peierdun Mijiti
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, People’s Republic of China
- Xinjiang Medical University, School of Public Health, Department of Epidemiology, Wulumuqi, People's Republic of China
| | - Changwei Liu
- Longhua District Center for Chronic Disease Control, Shenzhen, People’s Republic of China
| | - Chuangyue Hong
- Shenzhen Center for Chronic Disease Control, Shenzhen, People’s Republic of China
| | - Meng Li
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, People’s Republic of China
| | - Xiaoping Tan
- Longhua District Center for Chronic Disease Control, Shenzhen, People’s Republic of China
| | - Kaiqiao Zheng
- Longhua District Center for Chronic Disease Control, Shenzhen, People’s Republic of China
| | - Bin Li
- Longhua District Center for Chronic Disease Control, Shenzhen, People’s Republic of China
| | - Lecai Ji
- Shenzhen Center for Chronic Disease Control, Shenzhen, People’s Republic of China
| | - Qizhi Mao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, People’s Republic of China
| | - Qi Jiang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, People’s Republic of China
| | - Howard Takiff
- Laboratorio de Genética Molecular, CMBC, IVIC, Caracas, Venezuela
| | - Hongxia Fang
- Longhua District Center for Chronic Disease Control, Shenzhen, People’s Republic of China
| | - Weiguo Tan
- Shenzhen Center for Chronic Disease Control, Shenzhen, People’s Republic of China
| | - Qian Gao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, People’s Republic of China
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10
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Li M, Lu L, Jiang Q, Jiang Y, Yang C, Li J, Zhang Y, Zou J, Li Y, Dai W, Hong J, Takiff H, Shen X, Guo X, Yuan Z, Gao Q. Genotypic and spatial analysis of transmission dynamics of tuberculosis in Shanghai, China: a 10-year prospective population-based surveillance study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 38:100833. [PMID: 37790084 PMCID: PMC10544272 DOI: 10.1016/j.lanwpc.2023.100833] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 06/02/2023] [Accepted: 06/15/2023] [Indexed: 10/05/2023]
Abstract
Background With improved tuberculosis (TB) control programs, the incidence of TB in China declined dramatically over the past few decades, but recently the rate of decrease has slowed, especially in large cities such as Shanghai. To help formulate strategies to further reduce TB incidence, we performed a 10-year study in Songjiang, a district of Shanghai, to delineate the characteristics, transmission patterns, and dynamic changes of the local TB burden. Methods We conducted a population-based study of culture-positive pulmonary TB patients diagnosed in Songjiang during 2011-2020. Genomic clusters were defined with a threshold distance of 12-single-nucleotide-polymorphisms based on whole-genome sequencing, and risk factors for clustering were identified by logistic regression. Transmission inference was performed using phybreak. The distances between the residences of patients were compared to the genomic distances of their isolates. Spatial patient hotspots were defined with kernel density estimation. Findings Of 2212 enrolled patients, 74.7% (1652/2212) were internal migrants. The clustering rate (25.2%, 558/2212) and spatial concentrations of clustered and unclustered patients were unchanged over the study period. Migrants had significantly higher TB rates but less clustering than residents. Clustering was highest in male migrants, younger patients and both residents and migrants employed in physical labor. Only 22.1% of transmission events occurred between residents and migrants, with residents more likely to transmit to migrants. The clustering risk decreased rapidly with increasing distances between patient residences, but more than half of clustered patient pairs lived ≥5 km apart. Epidemiologic links were identified for only 15.6% of clustered patients, mostly in close contacts. Interpretation Although some of the TB in Songjiang's migrant population is caused by strains brought by infected migrants, local, recent transmission is an important driver of the TB burden. These results suggest that further reductions in TB incidence require novel strategies to detect TB early and interrupt urban transmission. Funding Shanghai Municipal Science and Technology Major Project (ZD2021CY001), National Natural Science Foundation of China (82272376), National Research Council of Science and Technology Major Project of China (2017ZX10201302-006).
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Affiliation(s)
- Meng Li
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
| | - Liping Lu
- Department of Tuberculosis Control, Songjiang District Center for Disease Control and Prevention, Shanghai, China
| | - Qi Jiang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
- School of Public Health, Renmin Hospital Public Health Research Institute, Wuhan University, Wuhan, China
| | - Yuan Jiang
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institute of Preventive Medicine, Shanghai, China
| | - Chongguang Yang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Jing Li
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institute of Preventive Medicine, Shanghai, China
| | - Yangyi Zhang
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institute of Preventive Medicine, Shanghai, China
| | - Jinyan Zou
- Department of Tuberculosis Control, Songjiang District Center for Disease Control and Prevention, Shanghai, China
| | - Yong Li
- Department of Tuberculosis Control, Songjiang District Center for Disease Control and Prevention, Shanghai, China
| | - Wenqi Dai
- Department of Clinical Laboratory, Songjiang District Central Hospital, Shanghai, China
| | - Jianjun Hong
- Department of Tuberculosis Control, Songjiang District Center for Disease Control and Prevention, Shanghai, China
| | - Howard Takiff
- Laboratorio de Genética Molecular, CMBC, Instituto Venezolano de Investigaciones Científicas, IVIC, Caracas, Venezuela
| | - Xin Shen
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institute of Preventive Medicine, Shanghai, China
| | - Xiaoqin Guo
- Department of Tuberculosis Control, Songjiang District Center for Disease Control and Prevention, Shanghai, China
| | - Zhengan Yuan
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institute of Preventive Medicine, Shanghai, China
| | - Qian Gao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
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11
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O'Connell J, McNally C, Stanistreet D, de Barra E, McConkey SJ. Ending tuberculosis: the cost of missing the World Health Organization target in a low-incidence country. Ir J Med Sci 2023; 192:1547-1553. [PMID: 36121600 PMCID: PMC9483873 DOI: 10.1007/s11845-022-03150-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 09/05/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND Ending tuberculosis (TB) is a global priority and targets for doing so are outlined in the World Health Organization (WHO) End TB Strategy. For low-incidence countries, eliminating TB requires high levels of wealth, low levels of income inequality and effective TB programmes and services that can meet the needs of people who have not benefited from these and are still at risk of TB. In Ireland, numerous reports have noted a need for more funding for TB prevention and control. AIM The aim of this research was to estimate the cost of not meeting the WHO End TB target of a 90% reduction in TB incidence in Ireland between 2015 and 2035. METHODS The cost of projected TB cases between 2022 and 2035 is estimated based on trends in surveillance data for the period 2015 to 2019 and outcomes reported in the literature. RESULTS Between 2022 and 2035, it is projected that a failure to meet the WHO End TB Strategy target will result in an additional 989 cases of TB, 577.3 disability-adjusted life years and 35 deaths with TB in Ireland. The cost of this is estimated to be €70.779 million. CONCLUSION Given the estimated cost, Ireland's current prospects of eliminating TB and the tendency towards programmatic funding internationally, greater investment in TB prevention and control in Ireland is justifiable. A national elimination strategy with actions at the levels of the social determinants of health, the health system and the TB programme should be funded.
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Affiliation(s)
- James O'Connell
- Department of International Health and Tropical Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland.
| | - Cora McNally
- Department of International Health and Tropical Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Infectious Diseases, Beaumont Hospital, Dublin, Ireland
| | - Debbi Stanistreet
- Department of Public Health and Epidemiology, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Eoghan de Barra
- Department of International Health and Tropical Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Infectious Diseases, Beaumont Hospital, Dublin, Ireland
| | - Samuel J McConkey
- Department of International Health and Tropical Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Infectious Diseases, Beaumont Hospital, Dublin, Ireland
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Singh H, Rupal A, Al Omari O, Jani C, Ahmed A, Khaliqdina S, Walker A, Shalhoub J, Thomson C, Marshall DC, Salciccioli JD. Trends in pulmonary tuberculosis mortality between 1985 and 2018: an observational analysis. BMC Pulm Med 2023; 23:184. [PMID: 37237250 DOI: 10.1186/s12890-023-02458-9] [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: 09/08/2022] [Accepted: 04/28/2023] [Indexed: 05/28/2023] Open
Abstract
BACKGROUND Pulmonary tuberculosis (TB) is a major source of global morbidity and mortality. Latent infection has enabled it to spread to a quarter of the world's population. The late 1980s and early 1990s saw an increase in the number of TB cases related to the HIV epidemic, and the spread of multidrug-resistant TB. Few studies have reported pulmonary TB mortality trends. Our study reports and compares trends in pulmonary TB mortality. METHODS We utilized the World Health Organization (WHO) mortality database from 1985 through 2018 to analyze TB mortality using the International Classification of Diseases-10 codes. Based on the availability and quality of data, we investigated 33 countries including two countries from the Americas; 28 countries from Europe; and 3 countries from the Western Pacific region. Mortality rates were dichotomized by sex. We computed age-standardized death rates per 100,000 population using the world standard population. Time trends were investigated using joinpoint regression analysis. RESULTS We observed a uniform decrease in mortality in all countries across the study period except the Republic of Moldova, which showed an increase in female mortality (+ 0.12 per 100,000 population). Among all countries, Lithuania had the greatest reduction in male mortality (-12) between 1993-2018, and Hungary had the greatest reduction in female mortality (-1.57) between 1985-2017. For males, Slovenia had the most rapid recent declining trend with an estimated annual percentage change (EAPC) of -47% (2003-2016), whereas Croatia showed the fastest increase (EAPC, + 25.0% [2015-2017]). For females, New Zealand had the most rapid declining trend (EAPC, -47.2% [1985-2015]), whereas Croatia showed a rapid increase (EAPC, + 24.9% [2014-2017]). CONCLUSIONS Pulmonary TB mortality is disproportionately higher among Central and Eastern European countries. This communicable disease cannot be eliminated from any one region without a global approach. Priority action areas include ensuring early diagnosis and successful treatment to the most vulnerable groups such as people of foreign origin from countries with a high burden of TB and incarcerated population. Incomplete reporting of TB-related epidemiological data to WHO excluded high-burden countries and limited our study to 33 countries only. Improvement in reporting is crucial to accurately identify changes in epidemiology, the effect of new treatments, and management approaches.
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Affiliation(s)
- Harpreet Singh
- Division of Pulmonary and Critical Care Medicine, Medical College of Wisconsin, Milwaukee, WI, USA
- Medical Data Research Collaborative, London, UK
| | - Arashdeep Rupal
- Medical Data Research Collaborative, London, UK
- Division of Pulmonary, Critical Care Medicine, University of South Florida, Tampa, FL, USA
| | - Omar Al Omari
- Medical Data Research Collaborative, London, UK
- Department of Medicine, Mount Auburn Hospital, Beth Israel Lahey Health, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Chinmay Jani
- Medical Data Research Collaborative, London, UK
- Department of Medicine, Mount Auburn Hospital, Beth Israel Lahey Health, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Alaaeldin Ahmed
- Medical Data Research Collaborative, London, UK
- Department of Medicine, Mount Auburn Hospital, Beth Israel Lahey Health, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Shoheera Khaliqdina
- Department of Medicine, Mount Auburn Hospital, Beth Israel Lahey Health, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Alexander Walker
- Medical Data Research Collaborative, London, UK
- Division of Pulmonary, Critical Care & Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Joseph Shalhoub
- Medical Data Research Collaborative, London, UK
- Department of Surgery and Cancer, Imperial College of London, London, UK
- Imperial Vascular Unit, Imperial College Healthcare NHS Trust, London, UK
| | - Carey Thomson
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Mount Auburn Hospital, Beth Israel Lahey Health, Cambridge, MA, USA
| | - Dominic C Marshall
- Division of Pulmonary and Critical Care Medicine, Mount Auburn Hospital, Beth Israel Lahey Health, Cambridge, MA, USA.
- National Heart and Lung Institute, Imperial College London, London, UK.
| | - Justin D Salciccioli
- Medical Data Research Collaborative, London, UK
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care, Brigham and Women's Hospital, Boston, MA, USA
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Guo H, An J, Li S, Ding B, Zhang Z, Shu W, Shang Y, Wang Y, Cheng K, Wang Y, Xue Z, Ren W, Pan J, Luo T, Pang Y. Transmission and resistome of extremely drug-resistant tuberculosis in Beijing, China: A retrospective population-based epidemiological study. J Infect Public Health 2023; 16:1193-1200. [PMID: 37271100 DOI: 10.1016/j.jiph.2023.05.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 01/10/2023] [Accepted: 05/17/2023] [Indexed: 06/06/2023] Open
Abstract
BACKGROUND In this study, we utilized whole genome sequencing (WGS) of clinical extremely drug-resistant tuberculosis (EDR-TB) strains collected during 2014-2020 in Beijing to detect clustered strains. METHODS A retrospective cohort study was conducted by inclusion of EDR-TB patients with positive cultures in Beijing between 2014 and 2020. RESULTS A total of 95 EDR-TB patients were included in our analysis. Up on the WGS based genotyping, 94 (94/95, 98.9%) out of 95 were identified as lineage 2 (East Asia). The pairwise genomic distance analysis identified 7 clusters, ranging in size from 2 to 5 isolates. The clustering rate of EDR-TB was 21.1%; while no patients had significantly higher odds of clustering. All isolates harbor rpoB RRDR mutations that confer RIF resistance and katG or inhA promoter mutations that confer INH resistance. Of 95 EDR-TB isolates, a total of 15 mutation types were recorded in the transcriptional regulator mmpR5. In vitro susceptibility testing results revealed that 14 (14/15, 93.3%) out of 15 mutation types were resistant to CFZ; whereas only 3 (3/15, 20.0%) showed resistance to BDQ. Interestingly, 12 isolates harbored mutations within rrl locus, whereas only mutations at positions 2294 and 2296 conferred CLA resistance. Favorable outcomes of EDR-TB patients were positively associated with more effective drugs in the regimes. CONCLUSION WGS data demonstrate limited transmission of EDR-TB in this metropolis city. WGS-based drug susceptibility predictions will bring benefits to EDR-TB patients to formulate optimal therapeutic regimens.
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Affiliation(s)
- Haiping Guo
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Postal No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China
| | - Jun An
- Medical Record Department, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing 101149, PR China
| | - Shanshan Li
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Postal No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China
| | - Beichuan Ding
- Clinical Center on TB, Beijing Institute of Tuberculosis Control, Beijing 101149, PR China
| | - Zhiguo Zhang
- Clinical laboratory, Beijing Changping District Tuberculosis Prevention and Control Institute, Beijing 101149, PR China
| | - Wei Shu
- Clinical Center on TB, Beijing Chest Hospital, Capital Medical University/ Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing 101149, PR China
| | - Yuanyuan Shang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Postal No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China
| | - Yi Wang
- Laboratory of Infection and Immunity, Department of Pathogen Biology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Postal No 17, People's South Road, Chengdu 610041, PR China
| | - Ken Cheng
- Laboratory of Infection and Immunity, Department of Pathogen Biology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Postal No 17, People's South Road, Chengdu 610041, PR China
| | - Yufeng Wang
- Department of Laboratory Quality Control, Innovation Alliance on Tuberculosis Diagnosis and Treatment (Beijing), Beijing 101149, PR China
| | - Zhongtan Xue
- Department of Laboratory Quality Control, Innovation Alliance on Tuberculosis Diagnosis and Treatment (Beijing), Beijing 101149, PR China
| | - Weicong Ren
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Postal No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China
| | - Junhua Pan
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Postal No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
| | - Tao Luo
- Laboratory of Infection and Immunity, Department of Pathogen Biology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Postal No 17, People's South Road, Chengdu 610041, PR China.
| | - Yu Pang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Postal No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
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Contact investigation of tuberculosis in Shanghai, China: A 13-year cohort. Tuberculosis (Edinb) 2023; 139:102323. [PMID: 36805089 DOI: 10.1016/j.tube.2023.102323] [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: 11/19/2022] [Revised: 02/04/2023] [Accepted: 02/12/2023] [Indexed: 02/17/2023]
Abstract
OBJECTIVES Tuberculosis (TB) contact investigation is an effective strategy for TB control. We established a close-contact cohort to evaluate the effect of contact investigation in Shanghai, China. METHODS Close contacts of bacteria-positive TB cases diagnosed from 2009 to 2018 in the Songjiang District of Shanghai were screened and followed up until 2021 through symptom examination or other alternatives, and the incidence and risk factors for developing active TB among close contacts were assessed by survival analysis and WGS. RESULTS 7018 close contacts of 2861 bacteria-positive TB cases were investigated. The median follow-up time was 7.4 years. 97 close contacts (185/100,000, 95%CI: 151-226) developed TB. Survival analysis showed that index cases who were in younger age groups, living in urban settings, smear-positive, and reported a healthcare-seeking delay for TB had higher risks of generating contact cases. Close contacts with matched strains developed TB at an average of 26.5 months based on WGS. CONCLUSION A 2-year ideally longer follow-up for close contacts would be beneficial. To improve early case detection, more attention needs to be paid to those contacts whose index cases were living in urban settings, were smear-positive, had a healthcare-seeking delay for TB, and/or were aged ≤18 years.
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Miyahara R, Piboonsiri P, Chiyasirinroje B, Imsanguan W, Nedsuwan S, Yanai H, Tokunaga K, Palittapongarnpim P, Murray M, Mahasirimongkol S. Risk for Prison-to-Community Tuberculosis Transmission, Thailand, 2017-2020. Emerg Infect Dis 2023; 29:477-483. [PMID: 36823074 PMCID: PMC9973682 DOI: 10.3201/eid2903.221023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023] Open
Abstract
To determine contributions of previously incarcerated persons to tuberculosis (TB) transmission in the community, we performed a healthcare facility-based cohort study of TB patients in Thailand during 2017-2020. We used whole-genome sequencing of Mycobacterium tuberculosis isolates from patients to identify genotypic clusters and assess the association between previous incarceration and TB transmission in the community. We identified 4 large genotype clusters (>10 TB patients/cluster); 28% (14/50) of the patients in those clusters were formerly incarcerated. Formerly incarcerated TB patients were more likely than nonincarcerated patients to be included in large clusters. TB patients within the large genotype clusters were geographically dispersed throughout Chiang Rai Province. Community TB transmission in the community was associated with the presence of formerly incarcerated individuals in Thailand. To reduce the risk for prison-to-community transmission, we recommend TB screening at the time of entry and exit from prisons and follow-up screening in the community.
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Advances in the Microbiological Diagnosis of Prosthetic Joint Infections. Diagnostics (Basel) 2023; 13:diagnostics13040809. [PMID: 36832297 PMCID: PMC9954824 DOI: 10.3390/diagnostics13040809] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 01/31/2023] [Accepted: 02/17/2023] [Indexed: 02/25/2023] Open
Abstract
A significant number of prosthetic joint infections (PJI) are culture-negative and/or misinterpreted as aseptic failures in spite of the correct implementation of diagnostic culture techniques, such as tissue sample processing in a bead mill, prolonged incubation time, or sonication of removed implants. Misinterpretation may lead to unnecessary surgery and needless antimicrobial treatment. The diagnostic value of non-culture techniques has been investigated in synovial fluid, periprosthetic tissues, and sonication fluid. Different feasible improvements, such as real-time technology, automated systems and commercial kits are now available to support microbiologists. In this review, we describe non-culture techniques based on nucleic acid amplification and sequencing methods. Polymerase chain reaction (PCR) is a frequently used technique in most microbiology laboratories which allows the detection of a nucleic acid fragment by sequence amplification. Different PCR types can be used to diagnose PJI, each one requiring the selection of appropriate primers. Henceforward, thanks to the reduced cost of sequencing and the availability of next-generation sequencing (NGS), it will be possible to identify the whole pathogen genome sequence and, additionally, to detect all the pathogen sequences present in the joint. Although these new techniques have proved helpful, strict conditions need to be observed in order to detect fastidious microorganisms and rule out contaminants. Specialized microbiologists should assist clinicians in interpreting the result of the analyses at interdisciplinary meetings. New technologies will gradually be made available to improve the etiologic diagnoses of PJI, which will remain an important cornerstone of treatment. Strong collaboration among all specialists involved is essential for the correct diagnosis of PJI.
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17
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Hall MB, Rabodoarivelo MS, Koch A, Dippenaar A, George S, Grobbelaar M, Warren R, Walker TM, Cox H, Gagneux S, Crook D, Peto T, Rakotosamimanana N, Grandjean Lapierre S, Iqbal Z. Evaluation of Nanopore sequencing for Mycobacterium tuberculosis drug susceptibility testing and outbreak investigation: a genomic analysis. THE LANCET. MICROBE 2023; 4:e84-e92. [PMID: 36549315 PMCID: PMC9892011 DOI: 10.1016/s2666-5247(22)00301-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 09/07/2022] [Accepted: 10/10/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Mycobacterium tuberculosis whole-genome sequencing (WGS) has been widely used for genotypic drug susceptibility testing (DST) and outbreak investigation. For both applications, Illumina technology is used by most public health laboratories; however, Nanopore technology developed by Oxford Nanopore Technologies has not been thoroughly evaluated. The aim of this study was to determine whether Nanopore sequencing data can provide equivalent information to Illumina for transmission clustering and genotypic DST for M tuberculosis. METHODS In this genomic analysis, we analysed 151 M tuberculosis isolates from Madagascar, South Africa, and England, which were collected between 2011 and 2018, using phenotypic DST and matched Illumina and Nanopore data. Illumina sequencing was done with the MiSeq, HiSeq 2500, or NextSeq500 platforms and Nanopore sequencing was done on the MinION or GridION platforms. Using highly reliable PacBio sequencing assemblies and pairwise distance correlation between Nanopore and Illumina data, we optimise Nanopore variant filters for detecting single-nucleotide polymorphisms (SNPs; using BCFtools software). We then used those SNPs to compare transmission clusters identified by Nanopore with the currently used UK Health Security Agency Illumina pipeline (COMPASS). We compared Illumina and Nanopore WGS-based DST predictions using the Mykrobe software and mutation catalogue. FINDINGS The Nanopore BCFtools pipeline identified SNPs with a median precision of 99·3% (IQR 99·1-99·6) and recall of 90·2% (88·1-94·2) compared with a precision of 99·6% (99·4-99·7) and recall of 91·9% (87·6-98·6) using the Illumina COMPASS pipeline. Using a threshold of 12 SNPs for putative transmission clusters, Illumina identified 98 isolates as unrelated and 53 as belonging to 19 distinct clusters (size range 2-7). Nanopore reproduced 15 out of 19 clusters perfectly; two clusters were merged into one cluster, one cluster had a single sample missing, and one cluster had an additional sample adjoined. Illumina-based clusters were also closely replicated using a five SNP threshold and clustering accuracy was maintained using mixed Illumina and Nanopore datasets. Genotyping resistance variants with Nanopore was highly concordant with Illumina, having zero discordant SNPs across more than 3000 SNPs and four insertions or deletions (indels), across 60 000 indels. INTERPRETATION Illumina and Nanopore technologies can be used independently or together by public health laboratories performing M tuberculosis genotypic DST and outbreak investigations. As a result, clinical and public health institutions making decisions on which sequencing technology to adopt for tuberculosis can base the choice on cost (which varies by country), batching, and turnaround time. FUNDING Academy for Medical Sciences, Oxford Wellcome Institutional Strategic Support Fund, and the Swiss South Africa Joint Research Award (Swiss National Science Foundation and South African National Research Foundation).
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Affiliation(s)
- Michael B Hall
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Marie Sylvianne Rabodoarivelo
- Mycobacteriology Unit, Institut Pasteur de Madagascar, Antananarivo, Madagascar; Departamento de Microbiología, Medicina Preventiva y Salud Pública, Universidad de Zaragoza, Zaragoza, Spain
| | - Anastasia Koch
- SAMRC/NHLS/UCT Molecular Mycobacteriology Research Unit and DST-NRF Centre of Excellence for Biomedical TB Research, Department of Pathology, University of Cape Town, Cape Town, South Africa; Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Anzaan Dippenaar
- Department of Science and Innovation-National Research Foundation Centre for 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, Tygerberg, South Africa; Tuberculosis Omics Research Consortium, Family Medicine and Population Health, Institute of Global Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Sophie George
- Nuffield Department of Clinical Medicine, John Radcliffe Hospital, Oxford University, Oxford, UK
| | - Melanie Grobbelaar
- Department of Science and Innovation-National Research Foundation Centre for 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, Tygerberg, South Africa
| | - Robin Warren
- Department of Science and Innovation-National Research Foundation Centre for 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, Tygerberg, South Africa
| | - Timothy M Walker
- Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
| | - Helen Cox
- Division of Medical Microbiology, Department of Pathology, University of Cape Town, Cape Town, South Africa; Wellcome Centre for Infectious Disease Research in Africa, University of Cape Town, Cape Town, South Africa; Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Sebastien Gagneux
- Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Derrick Crook
- Nuffield Department of Clinical Medicine, John Radcliffe Hospital, Oxford University, Oxford, UK
| | - Tim Peto
- Nuffield Department of Clinical Medicine, John Radcliffe Hospital, Oxford University, Oxford, UK
| | | | - Simon Grandjean Lapierre
- Mycobacteriology Unit, Institut Pasteur de Madagascar, Antananarivo, Madagascar; Department of Microbiology, Infectious Diseases and Immunology, Université de Montréal, Montréal, QC, Canada; Immunopathology Axis, Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montréal, QC, Canada
| | - Zamin Iqbal
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.
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18
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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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19
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Phelan J, Gomez-Gonzalez PJ, Andreu N, Omae Y, Toyo-Oka L, Yanai H, Miyahara R, Nedsuwan S, de Sessions PF, Campino S, Sallah N, Parkhill J, Smittipat N, Palittapongarnpim P, Mushiroda T, Kubo M, Tokunaga K, Mahasirimongkol S, Hibberd ML, Clark TG. Genome-wide host-pathogen analyses reveal genetic interaction points in tuberculosis disease. Nat Commun 2023; 14:549. [PMID: 36725857 PMCID: PMC9892022 DOI: 10.1038/s41467-023-36282-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 01/24/2023] [Indexed: 02/03/2023] Open
Abstract
The genetics underlying tuberculosis (TB) pathophysiology are poorly understood. Human genome-wide association studies have failed so far to reveal reproducible susceptibility loci, attributed in part to the influence of the underlying Mycobacterium tuberculosis (Mtb) bacterial genotype on the outcome of the infection. Several studies have found associations of human genetic polymorphisms with Mtb phylo-lineages, but studies analysing genome-genome interactions are needed. By implementing a phylogenetic tree-based Mtb-to-human analysis for 714 TB patients from Thailand, we identify eight putative genetic interaction points (P < 5 × 10-8) including human loci DAP and RIMS3, both linked to the IFNγ cytokine and host immune system, as well as FSTL5, previously associated with susceptibility to TB. Many of the corresponding Mtb markers are lineage specific. The genome-to-genome analysis reveals a complex interactome picture, supports host-pathogen adaptation and co-evolution in TB, and has potential applications to large-scale studies across many TB endemic populations matched for host-pathogen genomic diversity.
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Affiliation(s)
- Jody Phelan
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | | | - Nuria Andreu
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Yosuke Omae
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Licht Toyo-Oka
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hideki Yanai
- Fukujuji Hospital and Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Kiyose, Japan
| | - Reiko Miyahara
- Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan
| | | | | | - Susana Campino
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Neneh Sallah
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Julian Parkhill
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Nat Smittipat
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathumthani, Thailand
| | - Prasit Palittapongarnpim
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathumthani, Thailand
| | | | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Katsushi Tokunaga
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Surakameth Mahasirimongkol
- Medical Genetics Center, Medical Life Sciences Institute, Department of Medical Sciences, Ministry of Public Health, Nonthaburi, Thailand
| | - Martin L Hibberd
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
| | - Taane G Clark
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom.
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20
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Sanabria GE, Sequera G, Aguirre S, Méndez J, Dos Santos PCP, Gustafson NW, Godoy M, Ortiz A, Cespedes C, Martínez G, García-Basteiro AL, Andrews JR, Croda J, Walter KS. Phylogeography and transmission of Mycobacterium tuberculosis spanning prisons and surrounding communities in Paraguay. Nat Commun 2023; 14:303. [PMID: 36658111 PMCID: PMC9849832 DOI: 10.1038/s41467-023-35813-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 01/04/2023] [Indexed: 01/20/2023] Open
Abstract
Recent rises in incident tuberculosis (TB) cases in Paraguay and the increasing concentration of TB within prisons highlight the urgency of targeting strategies to interrupt transmission and prevent new infections. However, whether specific cities or carceral institutions play a disproportionate role in transmission remains unknown. We conducted prospective genomic surveillance, sequencing 471 Mycobacterium tuberculosis complex genomes, from inside and outside prisons in Paraguay's two largest urban areas, Asunción and Ciudad del Este, from 2016 to 2021. We found genomic evidence of frequent recent transmission within prisons and transmission linkages spanning prisons and surrounding populations. We identified a signal of frequent M. tuberculosis spread between urban areas and marked recent population size expansion of the three largest genomic transmission clusters. Together, our findings highlight the urgency of strengthening TB control programs to reduce transmission risk within prisons in Paraguay, where incidence was 70 times that outside prisons in 2021.
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Affiliation(s)
| | - Guillermo Sequera
- Instituto de Salud Global de Barcelona (ISGLOBAL), Barcelona, Spain
- Programa Nacional de Control de la Tuberculosis, Ministerio de Salud Pública y Bienestar Social (MSPyBS), Asunción, Paraguay
| | - Sarita Aguirre
- Programa Nacional de Control de la Tuberculosis, Ministerio de Salud Pública y Bienestar Social (MSPyBS), Asunción, Paraguay
| | - Julieta Méndez
- Instituto Regional de Investigación en Salud, Caaguazú, Paraguay
| | - Paulo César Pereira Dos Santos
- Postgraduate Program in Infectious and Parasitic Diseases, Federal University of Mato Grosso do Sul, Mato Grosso do Sul, Brazil
| | - Natalie Weiler Gustafson
- Laboratorio Central de Salud Pública (LCSP), Ministerio de Salud Publica y Bienestar Social (MSPyBS), Asunción, Paraguay
| | - Margarita Godoy
- Laboratorio Central de Salud Pública (LCSP), Ministerio de Salud Publica y Bienestar Social (MSPyBS), Asunción, Paraguay
| | - Analía Ortiz
- Instituto Regional de Investigación en Salud, Caaguazú, Paraguay
| | - Cynthia Cespedes
- Programa Nacional de Control de la Tuberculosis, Ministerio de Salud Pública y Bienestar Social (MSPyBS), Asunción, Paraguay
| | - Gloria Martínez
- Instituto Regional de Investigación en Salud, Caaguazú, Paraguay
| | - Alberto L García-Basteiro
- Instituto de Salud Global de Barcelona (ISGLOBAL), Barcelona, Spain
- Centro de Investigação em Saude de Manhiça (CISM), Maputo, Mozambique
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Barcelona, Spain
| | - Jason R Andrews
- Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Julio Croda
- Federal University of Mato Grosso do Sul - UFMS, Campo Grande, MS, Brazil
- Oswaldo Cruz Foundation Mato Grosso do Sul, Mato Grosso do Sul, Brazil
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, USA
| | - Katharine S Walter
- Division of Epidemiology, University of Utah, Salt Lake City, UT, 84105, USA.
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21
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Smith JP, Cohen T, Dowdy D, Shrestha S, Gandhi NR, Hill AN. Quantifying Mycobacterium tuberculosis Transmission Dynamics Across Global Settings: A Systematic Analysis. Am J Epidemiol 2023; 192:133-145. [PMID: 36227246 PMCID: PMC10144641 DOI: 10.1093/aje/kwac181] [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: 03/15/2022] [Revised: 07/23/2022] [Accepted: 10/10/2022] [Indexed: 01/11/2023] Open
Abstract
The degree to which individual heterogeneity in the production of secondary cases ("superspreading") affects tuberculosis (TB) transmission has not been systematically studied. We searched for population-based or surveillance studies in which whole genome sequencing was used to estimate TB transmission and in which the size distributions of putative TB transmission clusters were enumerated. We fitted cluster-size-distribution data to a negative binomial branching process model to jointly infer the transmission parameters $R$ (the reproduction number) and the dispersion parameter, $k$, which quantifies the propensity of superspreading in a population (generally, lower values of $k$ ($<1.0$) suggest increased heterogeneity). Of 4,796 citations identified in our initial search, 9 studies from 8 global settings met the inclusion criteria (n = 5 studies of all TB; n = 4 studies of drug-resistant TB). Estimated $R$ values (range, 0.10-0.73) were below 1.0, consistent with declining epidemics in the included settings; estimated $k$ values were well below 1.0 (range, 0.02-0.48), indicating the presence of substantial individual-level heterogeneity in transmission across all settings. We estimated that a minority of cases (range, 2%-31%) drive the majority (80%) of ongoing TB transmission at the population level. Identifying sources of heterogeneity and accounting for them in TB control may have a considerable impact on mitigating TB transmission.
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Affiliation(s)
- Jonathan P Smith
- Correspondence to Dr. Jonathan Smith, Yale School of Public Health, Yale University, 60 College Street, New Haven, CT 06510 (e-mail: )
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22
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Analysis of the twenty-six largest outbreaks of tuberculosis in Aragon using whole-genome sequencing for surveillance purposes. Sci Rep 2022; 12:18766. [PMID: 36335223 PMCID: PMC9637126 DOI: 10.1038/s41598-022-23343-1] [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: 06/29/2022] [Accepted: 10/30/2022] [Indexed: 11/08/2022] Open
Abstract
The incidence of tuberculosis in Aragon, Spain, is around ten cases per 100,000 inhabitants. Since 2004, a molecular surveillance protocol has been carried out; therefore, all M. tuberculosis strains are genotyped. Recently, whole-genome sequencing has been implemented for relevant isolates. The aim of this work is to characterise at the molecular level the causative strains of the 26 largest outbreaks of the community (including ten or more cases), genotyped by IS6110-RFLP and causing 26% of tuberculosis cases. To achieve this objective, two or three isolates of each IS6110-cluster belonging to different years were selected for sequencing. We found that strains of lineages L4.8, L4.3 and L4.1.2 were the most frequent. The threshold of 12 SNPs as the maximum distance for confirming the belonging to an outbreak was met for 18 of the 26 IS6110-clusters. Four pairs of isolates with more than 90 SNPs were identified as not belonging to the same strain, and four other pairs were kept in doubt as the number of SNPs was close to 12, between 14 and 35. The study of Regions of Difference revealed that they are lineage conserved. Moreover, we could analyse the IS6110 locations for all genome-sequenced isolates, finding some frequent locations in isolates belonging to the same lineage and certain IS6110 movements between the paired isolates. In the vast majority, these movements were not captured by the IS6110-RFLP pattern. After classifying the genes containing SNP by their functional category, we could confirm that the number of SNPs detected in genes considered as virulence factors and the number of cases the strain produced were not related, suggesting that a particular SNP is more relevant than the number. The characteristics found in the most successful strains in our community could be useful for other researchers in epidemiology, virulence and pathogenesis.
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23
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Yin J, Zhang H, Gao Z, Jiang H, Qin L, Zhu C, Gao Q, He X, Li W. Transmission of multidrug-resistant tuberculosis in Beijing, China: An epidemiological and genomic analysis. Front Public Health 2022; 10:1019198. [PMID: 36408017 PMCID: PMC9672842 DOI: 10.3389/fpubh.2022.1019198] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 10/13/2022] [Indexed: 11/06/2022] Open
Abstract
Background Understanding multidrug-resistant tuberculosis (MDR-TB) transmission patterns is crucial for controlling the disease. We aimed to identify high-risk populations and geographic settings of MDR-TB transmission. Methods We conducted a population-based retrospective study of MDR-TB patients in Beijing from 2018 to 2020, and assessed MDR-TB recent transmission using whole-genome sequencing of isolates. Geospatial analysis was conducted with kernel density estimation. We combined TransPhylo software with epidemiological investigation data to construct transmission networks. Logistic regression analysis was utilized to identify risk factors for recent transmission. Results We included 241 MDR-TB patients, of which 146 (60.58%) were available for genomic analysis. Drug resistance prediction showed that resistance to fluoroquinolones (FQs) was as high as 39.74% among new cases. 36 (24.66%) of the 146 MDR strains were grouped into 12 genome clusters, suggesting recent transmission of MDR strains. 44.82% (13/29) of the clustered patients lived in the same residential community, adjacent residential community or the same street as other cases. The inferred transmission chain found a total of 6 transmission events in 3 clusters; of these, 4 transmission events occurred in residential areas and nearby public places. Logistic regression analysis revealed that being aged 25-34 years-old was a risk factor for recent transmission. Conclusions The recent transmission of MDR-TB in Beijing is severe, and residential areas are common sites of transmission; high levels of FQs drug resistance suggest that FQs should be used with caution unless resistance can be ruled out by laboratory testing.
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Affiliation(s)
- Jinfeng Yin
- Beijing Chest Hospital, Capital Medical University, Beijing, China,National Tuberculosis Clinical Laboratory, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Hongwei Zhang
- Tuberculosis Prevention and Control Institute, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Zhidong Gao
- Tuberculosis Prevention and Control Institute, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Hui Jiang
- Beijing Chest Hospital, Capital Medical University, Beijing, China,National Tuberculosis Clinical Laboratory, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Liyi Qin
- Beijing Chest Hospital, Capital Medical University, Beijing, China,National Tuberculosis Clinical Laboratory, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Chendi Zhu
- Beijing Chest Hospital, Capital Medical University, Beijing, China,National Tuberculosis Clinical Laboratory, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Qian Gao
- Key Laboratory of Medical Molecular Virology, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Xiaoxin He
- Tuberculosis Prevention and Control Institute, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Weimin Li
- Beijing Chest Hospital, Capital Medical University, Beijing, China,National Tuberculosis Clinical Laboratory, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China,*Correspondence: Weimin Li
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24
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Brown TS, Robinson DA, Buckee CO, Mathema B. Connecting the dots: understanding how human mobility shapes TB epidemics. Trends Microbiol 2022; 30:1036-1044. [PMID: 35597716 PMCID: PMC10068677 DOI: 10.1016/j.tim.2022.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 04/18/2022] [Accepted: 04/19/2022] [Indexed: 01/13/2023]
Abstract
Tuberculosis (TB) remains a leading infectious cause of death worldwide. Reducing TB infections and TB-related deaths rests ultimately on stopping forward transmission from infectious to susceptible individuals. Critical to this effort is understanding how human host mobility shapes the transmission and dispersal of new or existing strains of Mycobacterium tuberculosis (Mtb). Important questions remain unanswered. What kinds of mobility, over what temporal and spatial scales, facilitate TB transmission? How do human mobility patterns influence the dispersal of novel Mtb strains, including emergent drug-resistant strains? This review summarizes the current state of knowledge on mobility and TB epidemic dynamics, using examples from three topic areas, including inference of genetic and spatial clustering of infections, delineating source-sink dynamics, and mapping the dispersal of novel TB strains, to examine scientific questions and methodological issues within this topic. We also review new data sources for measuring human mobility, including mobile phone-associated movement data, and discuss important limitations on their use in TB epidemiology.
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Affiliation(s)
- Tyler S Brown
- Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Infectious Diseases Division, Massachusetts General Hospital, Boston, MA, USA
| | - D Ashley Robinson
- Department of Microbiology and Immunology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Caroline O Buckee
- Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Barun Mathema
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
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25
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Dale K, Globan M, Horan K, Sherry N, Ballard S, Tay EL, Bittmann S, Meagher N, Price DJ, Howden BP, Williamson DA, Denholm J. Whole genome sequencing for tuberculosis in Victoria, Australia: A genomic implementation study from 2017 to 2020. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 28:100556. [PMID: 36034164 PMCID: PMC9405109 DOI: 10.1016/j.lanwpc.2022.100556] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Background Whole genome sequencing (WGS) is increasingly used by tuberculosis (TB) programs to monitor Mycobacterium tuberculosis (Mtb) transmission. We aimed to characterise the molecular epidemiology of TB and Mtb transmission in the low-incidence setting of Victoria, Australia, and assess the utility of WGS. Methods WGS was performed on all first Mtb isolates from TB cases from 2017 to 2020. Potential clusters (≤12 single nucleotide polymorphisms [SNPs]) were investigated for epidemiological links. Transmission events in highly-related (≤5 SNPs) clusters were classified as likely or possible, based on the presence or absence of an epidemiological link, respectively. Case characteristics and transmission settings (as defined by case relationship) were summarised. Poisson regression was used to examine associations with secondary case number. Findings Of 1844 TB cases, 1276 (69.2%) had sequenced isolates, with 182 (14.2%) in 54 highly-related clusters, 2-40 cases in size. Following investigation, 140 cases (11.0% of sequenced) were classified as resulting from likely/possible local-transmission, including 82 (6.4%) for which transmission was likely. Common identified transmission settings were social/religious (26.4%), household (22.9%) and family living in different households (7.1%), but many were uncertain (41.4%). While household transmission featured in many clusters (n = 24), clusters were generally smaller (median = 3 cases) than the fewer that included transmission in social/religious settings (n = 12, median = 7.5 cases). Sputum-smear-positivity was associated with higher secondary case numbers. Interpretation WGS results suggest Mtb transmission commonly occurs outside the household in our low-incidence setting. Further work is required to optimise the use of WGS in public health management of TB. Funding The Victorian Tuberculosis Program receives block funding for activities including case management and contact tracing from the Victorian Department of Health. No specific funding for this report was received by manuscript authors or the Victorian Tuberculosis Program, and the funders had no role in the study design, data collection, data analysis, interpretation or report writing.
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Affiliation(s)
- Katie Dale
- Victorian Tuberculosis Program, Melbourne Health, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Maria Globan
- Victorian Infectious Diseases Reference Laboratory (VIDRL), at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Kristy Horan
- Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Norelle Sherry
- Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Susan Ballard
- Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Ee Laine Tay
- Communicable Disease Epidemiology and Surveillance, Health Protection Branch, Public Health Division, Department of Health, Victoria, Australia
| | - Simone Bittmann
- Victorian Tuberculosis Program, Melbourne Health, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Niamh Meagher
- Department of Infectious Diseases at the Doherty Institute for Infection & Immunity, The University of Melbourne and Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - David J. Price
- Department of Infectious Diseases at the Doherty Institute for Infection & Immunity, The University of Melbourne and Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Benjamin P. Howden
- Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
- Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Deborah A. Williamson
- Victorian Infectious Diseases Reference Laboratory (VIDRL), at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Justin Denholm
- Victorian Tuberculosis Program, Melbourne Health, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
- Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
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26
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Epidemiological cut-off values for a 96-well broth microdilution plate for high-throughput research antibiotic susceptibility testing of M. tuberculosis. Eur Respir J 2022; 60:2200239. [PMID: 35301246 PMCID: PMC9556810 DOI: 10.1183/13993003.00239-2022] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 02/22/2022] [Indexed: 12/15/2022]
Abstract
Drug susceptibility testing of M. tuberculosis is rooted in a binary susceptible/resistant paradigm. While there are considerable advantages in measuring the minimum inhibitory concentrations (MICs) of a panel of drugs for an isolate, it is necessary to measure the epidemiological cut-off values (ECOFF/ECVs) to permit comparison with qualitative data. Here we present ECOFF/ECVs for 13 anti-tuberculosis compounds, including bedaquiline and delamanid, derived from 20 637 clinical isolates collected by 14 laboratories based in 11 countries on five continents. Each isolate was incubated for 14 days on a dry 96-well broth microdilution plate and then read. Resistance to most of the drugs due to prior exposure is expected and the MIC distributions for many of the compounds are complex, and therefore a phenotypically wild-type population could not be defined. Since a majority of samples also underwent genetic sequencing, we defined a genotypically wild-type population and measured the MIC of the 99th percentile by direct measurement and via fitting a Gaussian using interval regression. The proposed ECOFF/ECVs were then validated by comparing with the MIC distributions of high-confidence genetic variants that confer resistance and with qualitative drug susceptibility tests obtained via the Mycobacterial Growth Indicator Tube (MGIT) system or Microscopic-Observation Drug Susceptibility (MODS) assay. These ECOFF/ECVs will inform and encourage the more widespread adoption of broth microdilution: this is a cheap culture-based method that tests the susceptibility of 12-14 antibiotics on a single 96-well plate and so could help personalise the treatment of tuberculosis.
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Affiliation(s)
- The CRyPTIC Consortium
- For a list of all members of the CRyPTIC Consortium and their affiliations, please see the section at the end of this article
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27
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Meumann EM, Krause VL, Baird R, Currie BJ. Using Genomics to Understand the Epidemiology of Infectious Diseases in the Northern Territory of Australia. Trop Med Infect Dis 2022; 7:tropicalmed7080181. [PMID: 36006273 PMCID: PMC9413455 DOI: 10.3390/tropicalmed7080181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 08/09/2022] [Accepted: 08/11/2022] [Indexed: 11/16/2022] Open
Abstract
The Northern Territory (NT) is a geographically remote region of northern and central Australia. Approximately a third of the population are First Nations Australians, many of whom live in remote regions. Due to the physical environment and climate, and scale of social inequity, the rates of many infectious diseases are the highest nationally. Molecular typing and genomic sequencing in research and public health have provided considerable new knowledge on the epidemiology of infectious diseases in the NT. We review the applications of genomic sequencing technology for molecular typing, identification of transmission clusters, phylogenomics, antimicrobial resistance prediction, and pathogen detection. We provide examples where these methodologies have been applied to infectious diseases in the NT and discuss the next steps in public health implementation of this technology.
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Affiliation(s)
- Ella M. Meumann
- Global and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Darwin 0810, Australia
- Department of Infectious Diseases, Division of Medicine, Royal Darwin Hospital, Darwin 0810, Australia
- Correspondence:
| | - Vicki L. Krause
- Northern Territory Centre for Disease Control, Northern Territory Government, Darwin 0810, Australia
| | - Robert Baird
- Territory Pathology, Royal Darwin Hospital, Darwin 0810, Australia
| | - Bart J. Currie
- Global and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Darwin 0810, Australia
- Department of Infectious Diseases, Division of Medicine, Royal Darwin Hospital, Darwin 0810, Australia
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28
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A data compendium associating the genomes of 12,289 Mycobacterium tuberculosis isolates with quantitative resistance phenotypes to 13 antibiotics. PLoS Biol 2022; 20:e3001721. [PMID: 35944069 PMCID: PMC9363010 DOI: 10.1371/journal.pbio.3001721] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 06/21/2022] [Indexed: 11/19/2022] Open
Abstract
The Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC) presents here a data compendium of 12,289 Mycobacterium tuberculosis global clinical isolates, all of which have undergone whole-genome sequencing and have had their minimum inhibitory concentrations to 13 antitubercular drugs measured in a single assay. It is the largest matched phenotypic and genotypic dataset for M. tuberculosis to date. Here, we provide a summary detailing the breadth of data collected, along with a description of how the isolates were selected, collected, and uniformly processed in CRyPTIC partner laboratories across 23 countries. The compendium contains 6,814 isolates resistant to at least 1 drug, including 2,129 samples that fully satisfy the clinical definitions of rifampicin resistant (RR), multidrug resistant (MDR), pre-extensively drug resistant (pre-XDR), or extensively drug resistant (XDR). The data are enriched for rare resistance-associated variants, and the current limits of genotypic prediction of resistance status (sensitive/resistant) are presented by using a genetic mutation catalogue, along with the presence of suspected resistance-conferring mutations for isolates resistant to the newly introduced drugs bedaquiline, clofazimine, delamanid, and linezolid. Finally, a case study of rifampicin monoresistance demonstrates how this compendium could be used to advance our genetic understanding of rare resistance phenotypes. The data compendium is fully open source and it is hoped that it will facilitate and inspire future research for years to come.
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29
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Cancino-Muñoz I, López MG, Torres-Puente M, Villamayor LM, Borrás R, Borrás-Máñez M, Bosque M, Camarena JJ, Colijn C, Colomer-Roig E, Colomina J, Escribano I, Esparcia-Rodríguez O, García-García F, Gil-Brusola A, Gimeno C, Gimeno-Gascón A, Gomila-Sard B, Gónzales-Granda D, Gonzalo-Jiménez N, Guna-Serrano MR, López-Hontangas JL, Martín-González C, Moreno-Muñoz R, Navarro D, Navarro M, Orta N, Pérez E, Prat J, Rodríguez JC, Ruiz-García MM, Vanaclocha H, Comas I. Population-based sequencing of Mycobacterium tuberculosis reveals how current population dynamics are shaped by past epidemics. eLife 2022; 11:76605. [PMID: 35880398 PMCID: PMC9323001 DOI: 10.7554/elife.76605] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 07/07/2022] [Indexed: 11/13/2022] Open
Abstract
Transmission is a driver of tuberculosis (TB) epidemics in high-burden regions, with assumed negligible impact in low-burden areas. However, we still lack a full characterization of transmission dynamics in settings with similar and different burdens. Genomic epidemiology can greatly help to quantify transmission, but the lack of whole genome sequencing population-based studies has hampered its application. Here, we generate a population-based dataset from Valencia region and compare it with available datasets from different TB-burden settings to reveal transmission dynamics heterogeneity and its public health implications. We sequenced the whole genome of 785 Mycobacterium tuberculosis strains and linked genomes to patient epidemiological data. We use a pairwise distance clustering approach and phylodynamic methods to characterize transmission events over the last 150 years, in different TB-burden regions. Our results underscore significant differences in transmission between low-burden TB settings, i.e., clustering in Valencia region is higher (47.4%) than in Oxfordshire (27%), and similar to a high-burden area as Malawi (49.8%). By modeling times of the transmission links, we observed that settings with high transmission rate are associated with decades of uninterrupted transmission, irrespective of burden. Together, our results reveal that burden and transmission are not necessarily linked due to the role of past epidemics in the ongoing TB incidence, and highlight the need for in-depth characterization of transmission dynamics and specifically tailored TB control strategies.
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Affiliation(s)
- Irving Cancino-Muñoz
- Tuberculosis Genomics Unit, Instituto de Biomedicina de Valencia (IBV-CSIC), Valencia, Spain
| | - Mariana G López
- Tuberculosis Genomics Unit, Instituto de Biomedicina de Valencia (IBV-CSIC), Valencia, Spain
| | - Manuela Torres-Puente
- Tuberculosis Genomics Unit, Instituto de Biomedicina de Valencia (IBV-CSIC), Valencia, Spain
| | - Luis M Villamayor
- Unidad Mixta "Infección y Salud Pública" (FISABIO-CSISP), Valencia, Spain
| | - Rafael Borrás
- Microbiology Service, Hospital Clínico Universitario, Valencia, Spain
| | - María Borrás-Máñez
- Microbiology and Parasitology Service, Hospital Universitario de La Ribera, Alzira, Spain
| | | | - Juan J Camarena
- Microbiology Service, Hospital Universitario Dr Peset, Valencia, Spain
| | - Caroline Colijn
- Department of Mathematics, Faculty of Science, Simon Fraser University, Burnaby, Canada
| | - Ester Colomer-Roig
- Unidad Mixta "Infección y Salud Pública" (FISABIO-CSISP), Valencia, Spain.,Microbiology Service, Hospital Universitario Dr Peset, Valencia, Spain
| | - Javier Colomina
- Microbiology Service, Hospital Clínico Universitario, Valencia, Spain
| | - Isabel Escribano
- Microbiology Laboratory, Hospital Virgen de los Lirios, Alcoy, Spain
| | | | | | - Ana Gil-Brusola
- Microbiology Service, Hospital Universitari i Politècnic La Fe, Valencia, Spain
| | - Concepción Gimeno
- Microbiology Service, Hospital General Universitario de Valencia, Valencia, Spain
| | | | - Bárbara Gomila-Sard
- Microbiology Service, Hospital General Universitario de Castellón, Castellón, Spain
| | | | | | | | | | - Coral Martín-González
- Microbiology Service, Hospital Universitario de San Juan de Alicante, Alicantes, Spain
| | - Rosario Moreno-Muñoz
- Microbiology Service, Hospital General Universitario de Castellón, Castellón, Spain
| | - David Navarro
- Microbiology Service, Hospital Clínico Universitario, Valencia, Spain
| | - María Navarro
- Microbiology Service, Hospital de la Vega Baixa, Orihuela, Spain
| | - Nieves Orta
- Microbiology Service, Hospital Universitario de San Juan de Alicante, Alicantes, Spain
| | - Elvira Pérez
- Subdirección General de Epidemiología y Vigilancia de la Salud y Sanidad Ambiental de Valencia (DGSP), Valencia, Spain
| | - Josep Prat
- Microbiology Service, Hospital de Sagunto, Sagunto, Spain
| | | | | | - Hermelinda Vanaclocha
- Subdirección General de Epidemiología y Vigilancia de la Salud y Sanidad Ambiental de Valencia (DGSP), Valencia, Spain
| | | | - Iñaki Comas
- Tuberculosis Genomics Unit, Instituto de Biomedicina de Valencia (IBV-CSIC), Valencia, Spain.,CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
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30
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Saavedra Cervera B, López MG, Chiner-Oms Á, García AM, Cancino-Muñoz I, Torres-Puente M, Villamayor L, Madrazo-Moya C, Mambuque E, Sequera GV, Respeito D, Blanco S, Augusto O, López-Varela E, García-Basteiro AL, Comas I. Fine-grain population structure and transmission patterns of Mycobacterium tuberculosis in southern Mozambique, a high TB/HIV burden area. Microb Genom 2022; 8. [PMID: 35787782 PMCID: PMC9455694 DOI: 10.1099/mgen.0.000844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Genomic studies of the Mycobacterium tuberculosis complex (MTBC) might shed light on the dynamics of its transmission, especially in high-burden settings, where recent outbreaks are embedded in the complex natural history of the disease. To this end, we conducted a 1 year prospective surveillance-based study in Mozambique. We applied whole-genome sequencing (WGS) to 295 positive cultures. We fully characterized MTBC isolates by phylogenetics and dating evaluation, and carried out a molecular epidemiology analysis to investigate further associations with pre-defined transmission risk factors. The majority of strains (49.5%, 136/275) belonged to lineage (L) 4; 57.8 % of them (159/275) were in genomic transmission clusters (cut-off 5 SNPs), and a strikingly high proportion (45.5%) shared an identical genotype (0 SNP pairwise distance). We found two ‘likely endemic’ clades, comprising 67 strains, belonging to L1.2, which dated back to the late 19th century and were associated with recent spread among people living with human immunodeficiency virus (PLHIV). We describe for the first time the population structure of MTBC in our region, a high tuberculosis (TB)/HIV burden area. Clustering analysis revealed an unforeseen pattern of spread and high rates of progression to active TB, suggesting weaknesses in TB control activities. The long-term presence of local strains in Mozambique, which were responsible for large transmission among HIV/TB-coinfected patients, calls into question the role of HIV in TB transmission.
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Affiliation(s)
- Belén Saavedra Cervera
- PhD Programin Medicine and Translational Research, Universitat de Barcelona, Barcelona, Spain.,Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique.,ISGlobal, Hospital Clínic - Universitat de Barcelona, Barcelona, Spain
| | - Mariana G López
- Instituto de Biomedicina de Valencia (IBV), CSIC, Valencia, Spain
| | | | - Ana María García
- Instituto de Biomedicina de Valencia (IBV), CSIC, Valencia, Spain.,Universidad de Valencia, Valencia, Spain
| | | | | | | | | | - Edson Mambuque
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
| | | | - Durval Respeito
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
| | - Silvia Blanco
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
| | - Orvalho Augusto
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
| | - Elisa López-Varela
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique.,ISGlobal, Hospital Clínic - Universitat de Barcelona, Barcelona, Spain
| | - Alberto L García-Basteiro
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique.,ISGlobal, Hospital Clínic - Universitat de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Barcelona, Spain
| | - Iñaki Comas
- Instituto de Biomedicina de Valencia (IBV), CSIC, Valencia, Spain.,CIBER in Epidemiology and Public Health, Madrid, Spain
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31
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Whole-genome sequencing of Mycobacterium tuberculosis from Cambodia. Sci Rep 2022; 12:7693. [PMID: 35562174 PMCID: PMC9095694 DOI: 10.1038/s41598-022-10964-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 04/04/2022] [Indexed: 01/07/2023] Open
Abstract
Cambodia has one of the highest tuberculosis (TB) incidence rates in the WHO Western Pacific region. Remarkably though, the prevalence of multidrug-resistant TB (MDR-TB) remains low. We explored the genetic diversity of Mycobacterium tuberculosis (MTB) circulating in this unique setting using whole-genome sequencing (WGS). From October 2017 until January 2018, we collected one hundred sputum specimens from consenting adults older than 21 years of age, newly diagnosed with bacteriologically confirmed TB in 3 districts of Phnom Penh and Takeo provinces of Cambodia before they commence on their TB treatment, where eighty MTB isolates were successfully cultured and sequenced. Majority of the isolates belonged to Lineage 1 (Indo-Oceanic) (69/80, 86.25%), followed by Lineage 2 (East Asian) (10/80, 12.5%) and Lineage 4 (Euro-American) (1/80, 1.25%). Phenotypic resistance to both streptomycin and isoniazid was found in 3 isolates (3/80, 3.75%), while mono-resistance to streptomycin and isoniazid was identical at 2.5% (N = 2 each). None of the isolates tested was resistant to either rifampicin or ethambutol. The specificities of genotypic prediction for resistance to all drugs tested were 100%, while the sensitivities of genotypic resistance predictions to isoniazid and streptomycin were lower at 40% (2/5) and 80% (4/5) respectively. We identified 8 clusters each comprising of two to five individuals all residing in the Takeo province, making up half (28/56, 50%) of all individuals sampled in the province, indicating the presence of multiple ongoing transmission events. All clustered isolates were of Lineage 1 and none are resistant to any of the drugs tested. This study while demonstrating the relevance and utility of WGS in predicting drug resistance and inference of disease transmission, highlights the need to increase the representation of genotype-phenotype TB data from low and middle income countries in Asia and Africa to improve the accuracies for prediction of drug resistance.
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32
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Nelson KN, Talarico S, Poonja S, McDaniel CJ, Cilnis M, Chang AH, Raz K, Noboa WS, Cowan L, Shaw T, Posey J, Silk BJ. Mutation of Mycobacterium tuberculosis and Implications for Using Whole-Genome Sequencing for Investigating Recent Tuberculosis Transmission. Front Public Health 2022; 9:790544. [PMID: 35096744 PMCID: PMC8793027 DOI: 10.3389/fpubh.2021.790544] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/09/2021] [Indexed: 11/26/2022] Open
Abstract
Tuberculosis (TB) control programs use whole-genome sequencing (WGS) of Mycobacterium tuberculosis (Mtb) for detecting and investigating TB case clusters. Existence of few genomic differences between Mtb isolates might indicate TB cases are the result of recent transmission. However, the variable and sometimes long duration of latent infection, combined with uncertainty in the Mtb mutation rate during latency, can complicate interpretation of WGS results. To estimate the association between infection duration and single nucleotide polymorphism (SNP) accumulation in the Mtb genome, we first analyzed pairwise SNP differences among TB cases from Los Angeles County, California, with strong epidemiologic links. We found that SNP distance alone was insufficient for concluding that cases are linked through recent transmission. Second, we describe a well-characterized cluster of TB cases in California to illustrate the role of genomic data in conclusions regarding recent transmission. Longer presumed latent periods were inconsistently associated with larger SNP differences. Our analyses suggest that WGS alone cannot be used to definitively determine that a case is attributable to recent transmission. Methods for integrating clinical, epidemiologic, and genomic data can guide conclusions regarding the likelihood of recent transmission, providing local public health practitioners with better tools for monitoring and investigating TB transmission.
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Affiliation(s)
- Kristin N Nelson
- Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Sarah Talarico
- Division of Tuberculosis Elimination, National Center for HIV/AIDS (Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome), Viral Hepatitis, STD (Sexually Transmitted Diseases), and Tuberculosis (TB) Prevention, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Shameer Poonja
- Los Angeles County Department of Public Health, Los Angeles, CA, United States
| | - Clinton J McDaniel
- Division of Tuberculosis Elimination, National Center for HIV/AIDS (Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome), Viral Hepatitis, STD (Sexually Transmitted Diseases), and Tuberculosis (TB) Prevention, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Martin Cilnis
- TB Control Branch, California Department of Public Health, Richmond, CA, United States
| | - Alicia H Chang
- Los Angeles County Department of Public Health, Los Angeles, CA, United States
| | - Kala Raz
- Division of Tuberculosis Elimination, National Center for HIV/AIDS (Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome), Viral Hepatitis, STD (Sexually Transmitted Diseases), and Tuberculosis (TB) Prevention, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Wendy S Noboa
- Los Angeles County Department of Public Health, Los Angeles, CA, United States
| | - Lauren Cowan
- Division of Tuberculosis Elimination, National Center for HIV/AIDS (Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome), Viral Hepatitis, STD (Sexually Transmitted Diseases), and Tuberculosis (TB) Prevention, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Tambi Shaw
- TB Control Branch, California Department of Public Health, Richmond, CA, United States
| | - James Posey
- Division of Tuberculosis Elimination, National Center for HIV/AIDS (Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome), Viral Hepatitis, STD (Sexually Transmitted Diseases), and Tuberculosis (TB) Prevention, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Benjamin J Silk
- Division of Tuberculosis Elimination, National Center for HIV/AIDS (Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome), Viral Hepatitis, STD (Sexually Transmitted Diseases), and Tuberculosis (TB) Prevention, Centers for Disease Control and Prevention, Atlanta, GA, United States
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33
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Dookie N, Khan A, Padayatchi N, Naidoo K. Application of Next Generation Sequencing for Diagnosis and Clinical Management of Drug-Resistant Tuberculosis: Updates on Recent Developments in the Field. Front Microbiol 2022; 13:775030. [PMID: 35401475 PMCID: PMC8988194 DOI: 10.3389/fmicb.2022.775030] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 02/17/2022] [Indexed: 11/30/2022] Open
Abstract
The World Health Organization’s End TB Strategy prioritizes universal access to an early diagnosis and comprehensive drug susceptibility testing (DST) for all individuals with tuberculosis (TB) as a key component of integrated, patient-centered TB care. Next generation whole genome sequencing (WGS) and its associated technology has demonstrated exceptional potential for reliable and comprehensive resistance prediction for Mycobacterium tuberculosis isolates, allowing for accurate clinical decisions. This review presents a descriptive analysis of research describing the potential of WGS to accelerate delivery of individualized care, recent advances in sputum-based WGS technology and the role of targeted sequencing for resistance detection. We provide an update on recent research describing the mechanisms of resistance to new and repurposed drugs and the dynamics of mixed infections and its potential implication on TB diagnosis and treatment. Whilst the studies reviewed here have greatly improved our understanding of recent advances in this arena, it highlights significant challenges that remain. The wide-spread introduction of new drugs in the absence of standardized DST has led to rapid emergence of drug resistance. This review highlights apparent gaps in our knowledge of the mechanisms contributing to resistance for these new drugs and challenges that limit the clinical utility of next generation sequencing techniques. It is recommended that a combination of genotypic and phenotypic techniques is warranted to monitor treatment response, curb emerging resistance and further dissemination of drug resistance.
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Affiliation(s)
- Navisha Dookie
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa
- *Correspondence: Navisha Dookie,
| | - Azraa Khan
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa
| | - Nesri Padayatchi
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa
- South African Medical Research Council (SAMRC), CAPRISA HIV-TB Pathogenesis and Treatment Research Unit, Durban, South Africa
| | - Kogieleum Naidoo
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa
- South African Medical Research Council (SAMRC), CAPRISA HIV-TB Pathogenesis and Treatment Research Unit, Durban, South Africa
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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: 2] [Impact Index Per Article: 1.0] [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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35
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Yang T, Gan M, Liu Q, Liang W, Tang Q, Luo G, Zuo T, Guo Y, Hong C, Li Q, Tan W, Gao Q. SAM-TB: a whole genome sequencing data analysis website for detection of Mycobacterium tuberculosis drug resistance and transmission. Brief Bioinform 2022; 23:6535677. [PMID: 35211720 PMCID: PMC8921607 DOI: 10.1093/bib/bbac030] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 12/28/2021] [Accepted: 01/25/2022] [Indexed: 01/28/2023] Open
Abstract
Whole genome sequencing (WGS) can provide insight into drug-resistance, transmission chains and the identification of outbreaks, but data analysis remains an obstacle to its routine clinical use. Although several drug-resistance prediction tools have appeared, until now no website integrates drug-resistance prediction with strain genetic relationships and species identification of nontuberculous mycobacteria (NTM). We have established a free, function-rich, user-friendly online platform for MTB WGS data analysis (SAM-TB, http://samtb.szmbzx.com) that integrates drug-resistance prediction for 17 antituberculosis drugs, detection of variants, analysis of genetic relationships and NTM species identification. The accuracy of SAM-TB in predicting drug-resistance was assessed using 3177 sequenced clinical isolates with results of phenotypic drug-susceptibility tests (pDST). Compared to pDST, the sensitivity of SAM-TB for detecting multidrug-resistant tuberculosis was 93.9% [95% confidence interval (CI) 92.6–95.1%] with specificity of 96.2% (95% CI 95.2–97.1%). SAM-TB also analyzes the genetic relationships between multiple strains by reconstructing phylogenetic trees and calculating pairwise single nucleotide polymorphism (SNP) distances to identify genomic clusters. The incorporated mlstverse software identifies NTM species with an accuracy of 98.2% and Kraken2 software can detect mixed MTB and NTM samples. SAM-TB also has the capacity to share both sequence data and analysis between users. SAM-TB is a multifunctional integrated website that uses WGS raw data to accurately predict antituberculosis drug-resistance profiles, analyze genetic relationships between multiple strains and identify NTM species and mixed samples containing both NTM and MTB. SAM-TB is a useful tool for guiding both treatment and epidemiological investigation.
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Affiliation(s)
- Tingting Yang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, China
| | | | | | | | | | - Geyang Luo
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Sciences, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity and Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Tianyu Zuo
- Fudan University, Shanghai, China. Presently, he is a data analyst in patsnap, Shanghai, China
| | - Yongchao Guo
- Shenzhen Uni-medica Technology Co., Ltd, Shenzhen, China
| | - Chuangyue Hong
- Shenzhen Center for Chronic Disease Control, Shenzhen, China
| | | | - Weiguo Tan
- Shenzhen Center for Chronic Disease Control, Shenzhen, China
| | - Qian Gao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Sciences, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity and Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
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Waddington C, Carey ME, Boinett CJ, Higginson E, Veeraraghavan B, Baker S. Exploiting genomics to mitigate the public health impact of antimicrobial resistance. Genome Med 2022; 14:15. [PMID: 35172877 PMCID: PMC8849018 DOI: 10.1186/s13073-022-01020-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 02/04/2022] [Indexed: 12/13/2022] Open
Abstract
Antimicrobial resistance (AMR) is a major global public health threat, which has been largely driven by the excessive use of antimicrobials. Control measures are urgently needed to slow the trajectory of AMR but are hampered by an incomplete understanding of the interplay between pathogens, AMR encoding genes, and mobile genetic elements at a microbial level. These factors, combined with the human, animal, and environmental interactions that underlie AMR dissemination at a population level, make for a highly complex landscape. Whole-genome sequencing (WGS) and, more recently, metagenomic analyses have greatly enhanced our understanding of these processes, and these approaches are informing mitigation strategies for how we better understand and control AMR. This review explores how WGS techniques have advanced global, national, and local AMR surveillance, and how this improved understanding is being applied to inform solutions, such as novel diagnostic methods that allow antimicrobial use to be optimised and vaccination strategies for better controlling AMR. We highlight some future opportunities for AMR control informed by genomic sequencing, along with the remaining challenges that must be overcome to fully realise the potential of WGS approaches for international AMR control.
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Affiliation(s)
- Claire Waddington
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, CB2 0AW, UK.,Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
| | - Megan E Carey
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, CB2 0AW, UK.,Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
| | | | - Ellen Higginson
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, CB2 0AW, UK.,Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
| | - Balaji Veeraraghavan
- Department of Microbiology, Christian Medical College, Vellore, Tamil Nadu, India
| | - Stephen Baker
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, CB2 0AW, UK. .,Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK.
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Evaluating the Quality of Latent Tuberculosis Infection Screening in Ireland: A Single-Centre Retrospective Cohort Study. Trop Med Infect Dis 2022; 7:tropicalmed7020019. [PMID: 35202214 PMCID: PMC8880574 DOI: 10.3390/tropicalmed7020019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 01/22/2022] [Accepted: 01/26/2022] [Indexed: 02/04/2023] Open
Abstract
Ireland is a country with a low incidence of tuberculosis (TB) (5.6 cases per 100,000 population in 2019) that should be aiming for TB elimination (fewer than 1 case per million of population). To achieve TB elimination in low-incidence countries, programmatic latent tuberculosis infection (LTBI) management is important. This requires high-quality latent tuberculosis infection (LTBI) screening. Aim: To assess the quality of LTBI screening in a tertiary centre in Ireland using a framework. Methods: A retrospective review of the health care records of patients screened for TB in a tertiary centre in Ireland using an interferon-gamma release assay (IGRA) between 2016 and 2018 was performed. Three domains from the Institute of Medicine framework for health care quality, effectiveness, efficiency, and equity, were applied to measure the quality of LTBI screening. Results: Forty patients had LTBI and an indication for treatment, of whom 20% (8/40) were not offered treatment by the health care provider, 2.5% (1/40) did not accept treatment, and 10% (4/40) did not complete treatment. Seventy-five percent (6/8) of patients not offered treatment were non-Irish. The cost of screening per LTBI case identified was EUR 2048. Conclusions: This study evaluated the quality of LTBI screening using a framework and identified that LTBI screening in this tertiary centre needs to be scaled and expanded, and that treatment initiation needs to be improved, particularly among non-Irish nationals.
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Leavitt SV, Horsburgh CR, Lee RS, Tibbs AM, White LF, Jenkins HE. What Can Genetic Relatedness Tell Us About Risk Factors for Tuberculosis Transmission? Epidemiology 2022; 33:55-64. [PMID: 34847084 PMCID: PMC8638913 DOI: 10.1097/ede.0000000000001414] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND To stop tuberculosis (TB), the leading infectious cause of death globally, we need to better understand transmission risk factors. Although many studies have identified associations between individual-level covariates and pathogen genetic relatedness, few have identified characteristics of transmission pairs or explored how closely covariates associated with genetic relatedness mirror those associated with transmission. METHODS We simulated a TB-like outbreak with pathogen genetic data and estimated odds ratios (ORs) to correlate each covariate and genetic relatedness. We used a naive Bayes approach to modify the genetic links and nonlinks to resemble the true links and nonlinks more closely and estimated modified ORs with this approach. We compared these two sets of ORs with the true ORs for transmission. Finally, we applied this method to TB data in Hamburg, Germany, and Massachusetts, USA, to find pair-level covariates associated with transmission. RESULTS Using simulations, we found that associations between covariates and genetic relatedness had the same relative magnitudes and directions as the true associations with transmission, but biased absolute magnitudes. Modifying the genetic links and nonlinks reduced the bias and increased the confidence interval widths, more accurately capturing error. In Hamburg and Massachusetts, pairs were more likely to be probable transmission links if they lived in closer proximity, had a shorter time between observations, or had shared ethnicity, social risk factors, drug resistance, or genotypes. CONCLUSIONS We developed a method to improve the use of genetic relatedness as a proxy for transmission, and aid in understanding TB transmission dynamics in low-burden settings.
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Affiliation(s)
- Sarah V Leavitt
- From the Boston University School of Public Health, Department of Biostatistics, Boston, MA
| | - C Robert Horsburgh
- Boston University School of Public Health, Department of Epidemiology, Boston, MA
| | - Robyn S Lee
- University of Toronto, Dalla Lana School of Public Health, Epidemiology Division, Toronto, ON, Canada
| | | | - Laura F White
- From the Boston University School of Public Health, Department of Biostatistics, Boston, MA
| | - Helen E Jenkins
- From the Boston University School of Public Health, Department of Biostatistics, Boston, MA
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Asare P, Asante-Poku A, Osei-Wusu S, Otchere ID, Yeboah-Manu D. The Relevance of Genomic Epidemiology for Control of Tuberculosis in West Africa. Front Public Health 2021; 9:706651. [PMID: 34368069 PMCID: PMC8342769 DOI: 10.3389/fpubh.2021.706651] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 06/29/2021] [Indexed: 12/30/2022] Open
Abstract
Tuberculosis (TB), an airborne infectious disease caused by Mycobacterium tuberculosis complex (MTBC), remains a global health problem. West Africa has a unique epidemiology of TB that is characterized by medium- to high-prevalence. Moreover, the geographical restriction of M. africanum to the sub-region makes West Africa have an extra burden to deal with a two-in-one pathogen. The region is also burdened with low case detection, late reporting, poor treatment adherence leading to development of drug resistance and relapse. Sporadic studies conducted within the subregion report higher burden of drug resistant TB (DRTB) than previously thought. The need for more sensitive and robust tools for routine surveillance as well as to understand the mechanisms of DRTB and transmission dynamics for the design of effective control tools, cannot be overemphasized. The advancement in molecular biology tools including traditional fingerprinting and next generation sequencing (NGS) technologies offer reliable tools for genomic epidemiology. Genomic epidemiology provides in-depth insight of the nature of pathogens, circulating strains and their spread as well as prompt detection of the emergence of new strains. It also offers the opportunity to monitor treatment and evaluate interventions. Furthermore, genomic epidemiology can be used to understand potential emergence and spread of drug resistant strains and resistance mechanisms allowing the design of simple but rapid tools. In this review, we will describe the local epidemiology of MTBC, highlight past and current investigations toward understanding their biology and spread as well as discuss the relevance of genomic epidemiology studies to TB control in West Africa.
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Affiliation(s)
- Prince Asare
- College of Health Sciences, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana
| | - Adwoa Asante-Poku
- College of Health Sciences, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana
| | - Stephen Osei-Wusu
- College of Health Sciences, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana
| | - Isaac Darko Otchere
- College of Health Sciences, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana
| | - Dorothy Yeboah-Manu
- College of Health Sciences, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana
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Eldholm V, Rønning JO, Mengshoel AT, Arnesen T. Import and transmission of Mycobacterium orygis and Mycobacterium africanum, Norway. BMC Infect Dis 2021; 21:562. [PMID: 34118874 PMCID: PMC8199368 DOI: 10.1186/s12879-021-06269-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 06/02/2021] [Indexed: 11/25/2022] Open
Abstract
Background The aim of the current study was to improve our understanding of the origins and transmission of Mycobacterium africanum (MAF) in Norway. Methods Whole-genome sequences (WGS) were generated for all (n = 29) available clinical isolates received at the Norwegian National Reference Laboratory for Mycobacteria (NRL) and identified as MAF in Norway, in the period 2010–2020. Phylogenetic analyses were performed. Results The analyses indicated several imports of MAF lineage 6 from both East and West African countries, whereas MAF lineage 5 was restricted to patients with West African connections. We also find evidence for transmission of MAF in Norway. Finally, our analyses revealed that a group of isolates from patients originating in South Asia, identified as MAF by means of a commercial line-probe assay, in fact belonged to Mycobacterium orygis. Conclusions Most MAF cases in Norway are the result of import, but transmission is occurring within Norway.
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Affiliation(s)
- Vegard Eldholm
- National Reference Laboratory for Mycobacteria, Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway.
| | - Janne O Rønning
- National Reference Laboratory for Mycobacteria, Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Anne Torunn Mengshoel
- National Reference Laboratory for Mycobacteria, Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Trude Arnesen
- National Reference Laboratory for Mycobacteria, Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
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Martínez-Lirola M, Jajou R, Mathys V, Martin A, Cabibbe AM, Valera A, Sola-Campoy PJ, Abascal E, Rodríguez-Maus S, Garrido-Cárdenas JA, Bonillo M, Chiner-Oms Á, López B, Vallejo-Godoy S, Comas I, Muñoz P, Cirillo DM, van Soolingen D, Pérez-Lago L, García de Viedma D. Integrative transnational analysis to dissect tuberculosis transmission events along the migratory route from Africa to Europe. J Travel Med 2021; 28:6211020. [PMID: 33822988 DOI: 10.1093/jtm/taab054] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 01/26/2021] [Accepted: 03/24/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND Growing international migration has increased the complexity of tuberculosis transmission patterns. Italy's decision to close its borders in 2018 made of Spain the new European porte entrée for migration from the Horn of Africa (HA). In one of the first rescues of migrants from this region at the end of 2018, tuberculosis was diagnosed in eight subjects, mainly unaccompanied minors. METHODS Mycobacterium tuberculosis isolates from these recently arrived migrants were analysed by Mycobacterial Interspersed Repetitive-Unit/Variable-Number of Tandem Repeat (MIRU-VNTR) and subsequent whole genome sequencing (WGS) analysis. Data were compared with those from collections from other European countries receiving migrants from the HA and a strain-specific PCR was applied for a fast searching of common strains. Infections in a cellular model were performed to assess strain virulence. RESULTS MIRU-VNTR analysis allowed identifying an epidemiological cluster involving three of the eight cases from Somalia (0 single-nucleotide polymorphisms between isolates, HA cluster). Following detailed interviews revealed that two of these cases had shared the same migratory route in most of the trip and had spent a long time at a detention camp in Libya. To confirm potential en route transmission for the three cases, we searched the same strain in collections from other European countries receiving migrants from the HA. MIRU-VNTR, WGS and a strain-specific PCR for the HA strain were applied. The same strain was identified in 12 cases from Eritrea diagnosed soon after their arrival in 2018 to the Netherlands, Belgium and Italy. Intracellular replication rate of the strain did not reveal abnormal virulence. CONCLUSIONS Our study suggests a potential en route transmission of a pan-susceptible strain, which caused at least 15 tuberculosis cases in Somalian and Eritrean migrants diagnosed in four different European countries.
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Affiliation(s)
| | - Rana Jajou
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Vanessa Mathys
- Unit Bacterial Diseases Service, Infectious Diseases in Humans, Sciensano, Brussels, Belgium
| | - Anandi Martin
- Université catholique de Louvain (UCLouvain) & Syngulon, 4102, Seraing, Belgium
| | - Andrea Maurizio Cabibbe
- Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Ana Valera
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Pedro J Sola-Campoy
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Estefanía Abascal
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Sandra Rodríguez-Maus
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | | | - Magdalena Bonillo
- Unidad de Prevención, Promoción y Vigilancia de la Salud del Área Sanitaria Norte de Almería. Consejería de Salud. Junta de Andalucia, Almería, Spain
| | - Álvaro Chiner-Oms
- Centro Superior de Investigación en Salud Pública (FISABIO)-Universitat de València, Valencia, Spain
| | - Begoña López
- UPPV Distrito Sanitario Granada metropolitano, Granada, Spain
| | | | - Iñaki Comas
- Instituto de Biomedicina de Valencia-CSIC, Valencia, Spain.,CIBER Salud Pública (CIBERESP), Madrid, Spain
| | - Patricia Muñoz
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,CIBER Enfermedades Respiratorias (CIBERES), Madrid, Spain.,Departamento de Medicina, Universidad Complutense, Madrid, Spain
| | - Daniela Maria Cirillo
- Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Dick van Soolingen
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Laura Pérez-Lago
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Darío García de Viedma
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,CIBER Enfermedades Respiratorias (CIBERES), Madrid, Spain
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Abascal E, Genestet C, Valera A, Herranz M, Martinez-Lirola M, Muñoz P, Dumitrescu O, García de Viedma D. Assessment of closely related Mycobacterium tuberculosis variants with different transmission success and in vitro infection dynamics. Sci Rep 2021; 11:11041. [PMID: 34040136 PMCID: PMC8155013 DOI: 10.1038/s41598-021-90568-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 05/06/2021] [Indexed: 11/10/2022] Open
Abstract
Whole genome sequencing (WGS) is able to differentiate closely related Mycobacterium tuberculosis variants within the same transmission cluster. Our aim was to evaluate if this higher discriminatory power may help identify and characterize more actively transmitted variants and understand the factors behind their success. We selected a robust MIRU-VNTR-defined cluster from Almería, Spain (22 cases throughout 2003–2019). WGS allowed discriminating, within the same epidemiological setting, between a successfully transmitted variant and seven closely related variants that did not lead to secondary cases, or were involved in self-limiting transmission (one single secondary case). Intramacrophagic growth of representative variants was evaluated in an in vitro infection model using U937 cells. Intramacrophage multiplication ratios (CFUs at Day 4/CFUs at Day 0) were higher for the actively transmitted variant (range 5.3–10.7) than for the unsuccessfully transmitted closely related variants (1.5–3.95). Two SNPs, mapping at the DNA binding domain of DnaA and at kdpD, were found to be specific of the successful variant.
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Affiliation(s)
- Estefanía Abascal
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, C/Dr. Esquerdo 46, 28007, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
| | - Charlotte Genestet
- CIRI - Centre International de Recherche en Infectiologie, Ecole Normale Supérieure de Lyon, Inserm U1111, CNRS UMR5308, Université Claude Bernard Lyon-1, 69007, Lyon, France.,Laboratoire de bactériologie, Institut des Agents Infectieux, Hospices Civils de Lyon, 69317, Lyon Cedex 04, France
| | - Ana Valera
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, C/Dr. Esquerdo 46, 28007, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
| | - Marta Herranz
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, C/Dr. Esquerdo 46, 28007, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain.,CIBER Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | | | - Patricia Muñoz
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, C/Dr. Esquerdo 46, 28007, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain.,CIBER Enfermedades Respiratorias (CIBERES), Madrid, Spain.,Departamento de Medicina, Universidad Complutense de Madrid, Madrid, Spain
| | - Oana Dumitrescu
- CIRI - Centre International de Recherche en Infectiologie, Ecole Normale Supérieure de Lyon, Inserm U1111, CNRS UMR5308, Université Claude Bernard Lyon-1, 69007, Lyon, France.,Laboratoire de bactériologie, Institut des Agents Infectieux, Hospices Civils de Lyon, 69317, Lyon Cedex 04, France
| | - Darío García de Viedma
- Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, C/Dr. Esquerdo 46, 28007, Madrid, Spain. .,Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain. .,CIBER Enfermedades Respiratorias (CIBERES), Madrid, Spain.
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Leavitt SV, Lee RS, Sebastiani P, Horsburgh CR, Jenkins HE, White LF. Estimating the relative probability of direct transmission between infectious disease patients. Int J Epidemiol 2021; 49:764-775. [PMID: 32211747 DOI: 10.1093/ije/dyaa031] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 02/07/2020] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Estimating infectious disease parameters such as the serial interval (time between symptom onset in primary and secondary cases) and reproductive number (average number of secondary cases produced by a primary case) are important in understanding infectious disease dynamics. Many estimation methods require linking cases by direct transmission, a difficult task for most diseases. METHODS Using a subset of cases with detailed genetic and/or contact investigation data to develop a training set of probable transmission events, we build a model to estimate the relative transmission probability for all case-pairs from demographic, spatial and clinical data. Our method is based on naive Bayes, a machine learning classification algorithm which uses the observed frequencies in the training dataset to estimate the probability that a pair is linked given a set of covariates. RESULTS In simulations, we find that the probabilities estimated using genetic distance between cases to define training transmission events are able to distinguish between truly linked and unlinked pairs with high accuracy (area under the receiver operating curve value of 95%). Additionally, only a subset of the cases, 10-50% depending on sample size, need to have detailed genetic data for our method to perform well. We show how these probabilities can be used to estimate the average effective reproductive number and apply our method to a tuberculosis outbreak in Hamburg, Germany. CONCLUSIONS Our method is a novel way to infer transmission dynamics in any dataset when only a subset of cases has rich contact investigation and/or genetic data.
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Affiliation(s)
- Sarah V Leavitt
- School of Public Health, Department of Biostatistics, Boston University, Boston, MA, USA
| | - Robyn S Lee
- Harvard T.H. Chan School of Public Health, Boston, MA, USA.,University of Toronto Dalla Lana School of Public Health Epidemiology Division, Toronto, ON, Canada
| | - Paola Sebastiani
- School of Public Health, Department of Biostatistics, Boston University, Boston, MA, USA
| | - C Robert Horsburgh
- School of Public Health, Department of Epidemiology, Boston University, Boston, MA, USA
| | - Helen E Jenkins
- School of Public Health, Department of Biostatistics, Boston University, Boston, MA, USA
| | - Laura F White
- School of Public Health, Department of Biostatistics, Boston University, Boston, MA, USA
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44
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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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45
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Didelot X, Kendall M, Xu Y, White PJ, McCarthy N. Genomic Epidemiology Analysis of Infectious Disease Outbreaks Using TransPhylo. Curr Protoc 2021; 1:e60. [PMID: 33617114 PMCID: PMC7995038 DOI: 10.1002/cpz1.60] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Comparing the pathogen genomes from several cases of an infectious disease has the potential to help us understand and control outbreaks. Many methods exist to reconstruct a phylogeny from such genomes, which represents how the genomes are related to one another. However, such a phylogeny is not directly informative about transmission events between individuals. TransPhylo is a software tool implemented as an R package designed to bridge the gap between pathogen phylogenies and transmission trees. TransPhylo is based on a combined model of transmission between hosts and pathogen evolution within each host. It can simulate both phylogenies and transmission trees jointly under this combined model. TransPhylo can also reconstruct a transmission tree based on a dated phylogeny, by exploring the space of transmission trees compatible with the phylogeny. A transmission tree can be represented as a coloring of a phylogeny where each color represents a different host of the pathogen, and TransPhylo provides convenient ways to plot these colorings and explore the results. This article presents the basic protocols that can be used to make the most of TransPhylo. © 2021 The Authors. Basic Protocol 1: First steps with TransPhylo Basic Protocol 2: Simulation of outbreak data Basic Protocol 3: Inference of transmission Basic Protocol 4: Exploring the results of inference.
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Affiliation(s)
- Xavier Didelot
- School of Life Sciences and Department of StatisticsUniversity of WarwickUnited Kingdom
| | - Michelle Kendall
- School of Life Sciences and Department of StatisticsUniversity of WarwickUnited Kingdom
| | - Yuanwei Xu
- Center for Computational Biology, Institute of Cancer and Genomic SciencesUniversity of BirminghamUnited Kingdom
| | - Peter J. White
- Department of Infectious Disease Epidemiology, School of Public HealthImperial College LondonUnited Kingdom
- Medical Research Council Centre for Global Infectious Disease Analysis, School of Public HealthImperial College LondonUnited Kingdom
- National Institute for Health Research Health Protection Research Unit in Modelling and Health Economics, School of Public HealthImperial College LondonUnited Kingdom
- Modelling and Economics Unit, National Infection ServicePublic Health EnglandLondonUnited Kingdom
| | - Noel McCarthy
- Warwick Medical SchoolUniversity of WarwickUnited Kingdom
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46
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Chee CBE, Lim LKY, Ong RTH, Sng LH, Hsu LY, Lee VJM, Wang YT. Whole genome sequencing analysis of multidrug-resistant tuberculosis in Singapore, 2006-2018. Eur J Clin Microbiol Infect Dis 2020; 40:1079-1083. [PMID: 33190171 DOI: 10.1007/s10096-020-04100-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 11/05/2020] [Indexed: 01/29/2023]
Abstract
There were 290 multidrug-resistant (MDR)-TB cases diagnosed in Singapore from 2006 to 2018. Eighty-one percent were foreign-born. Spoligotyping and MIRU-VNTR methods identified 108 patients in 24 clusters. The Beijing spoligotype accounted for 22 clusters. Whole genome sequencing (WGS) analysis reduced the number of clustered patients and clusters to 43 and nine respectively. One MIRU cluster was redefined into three WGS clusters. All the clusters had foreign-born source cases. Forty percent of local-born, versus 9% of foreign-born, MDR-TB cases belonged to WGS clusters. WGS more accurately elucidated potential MDR-TB transmission which was overestimated by conventional genotyping methods in Singapore.
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Affiliation(s)
| | - Leo K Y Lim
- TB Control Unit, Tan Tock Seng Hospital, Singapore, Singapore
| | - Rick T H Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Li Hwei Sng
- Singapore General Hospital, Singapore, Singapore
| | - Li Yang Hsu
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | | | - Yee Tang Wang
- TB Control Unit, Tan Tock Seng Hospital, Singapore, Singapore
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47
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Drysdale SB, Kelly DF, Morgan M, Peto T, Crook D, Matthews PC, Walker TM. Case Report: Disseminated, rifampicin resistant Mycobacterium bovis (BCG) infection in an immunocompromised child. Wellcome Open Res 2020; 5:242. [PMID: 33283057 PMCID: PMC7682502 DOI: 10.12688/wellcomeopenres.16280.1] [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] [Accepted: 09/07/2020] [Indexed: 11/20/2022] Open
Abstract
Background: Bacillus Calmette-Guérin (BCG) is a live-attenuated vaccine used world-wide for prevention of tuberculosis disease. In some immunocompromised hosts it has the potential to cause disease. As with other members of the M. tuberculosis complex it has the potential for acquiring drug resistance. Methods: We reviewed 10 years of paediatric clinical BCG strains referred to our clinical microbiology laboratory in Oxford where they underwent whole genome sequencing. We present a case series comparing clinical, pathogen genetic and pathogen phenotypic data, and consider the clinical implications. Results: We identified 15 BCG isolates from 8 children under 16 years old. Only one child had clinical disease with the other seven reported as local inoculation-site reactions. Case 1 suffered disseminated disease secondary to an undiagnosed IL-12/IFNγ receptor defect and the BCG isolates evolved two different rifampicin resistance mutations. Across all 15 isolates, phenotypic resistance to each first line drug was seen. Conclusions: BCG is a safe and effective vaccine in children. Most clinical specimens in our series were not related to disease. However, in the context of rare pathogen-specific immunocompromise, BCG can cause pathology and acquire drug resistance under selection from therapy.
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Affiliation(s)
- Simon B Drysdale
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford University, Oxford, UK.,Paediatric Infectious Diseases Research Group, St George's, University of London, London, UK
| | - Dominic F Kelly
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford University, Oxford, UK
| | - Marcus Morgan
- Department of Microbiology and Infectious Diseases, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Tim Peto
- NIHR Oxford Biomedical Research Centre, Oxford University, Oxford, UK.,Department of Microbiology and Infectious Diseases, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Derrick Crook
- NIHR Oxford Biomedical Research Centre, Oxford University, Oxford, UK.,Department of Microbiology and Infectious Diseases, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Philippa C Matthews
- NIHR Oxford Biomedical Research Centre, Oxford University, Oxford, UK.,Department of Microbiology and Infectious Diseases, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.,Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Timothy M Walker
- Department of Microbiology and Infectious Diseases, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.,Oxford University Clinical Research Unit, University of Oxford, Ho Chi Minh City, Vietnam
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48
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DNA Thermo-Protection Facilitates Whole-Genome Sequencing of Mycobacteria Direct from Clinical Samples. J Clin Microbiol 2020; 58:JCM.00670-20. [PMID: 32719032 PMCID: PMC7512152 DOI: 10.1128/jcm.00670-20] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Accepted: 07/15/2020] [Indexed: 02/03/2023] Open
Abstract
Mycobacterium tuberculosis is the leading cause of death from bacterial infection. Improved rapid diagnosis and antimicrobial resistance determination, such as by whole-genome sequencing, are required. Our aim was to develop a simple, low-cost method of preparing DNA for sequencing direct from M. tuberculosis-positive clinical samples (without culture). Simultaneous sputum liquefaction, bacteria heat inactivation (99°C/30 min), and enrichment for mycobacteria DNA were achieved using an equal volume of thermo-protection buffer (4 M KCl, 0. Mycobacterium tuberculosis is the leading cause of death from bacterial infection. Improved rapid diagnosis and antimicrobial resistance determination, such as by whole-genome sequencing, are required. Our aim was to develop a simple, low-cost method of preparing DNA for sequencing direct from M. tuberculosis-positive clinical samples (without culture). Simultaneous sputum liquefaction, bacteria heat inactivation (99°C/30 min), and enrichment for mycobacteria DNA were achieved using an equal volume of thermo-protection buffer (4 M KCl, 0.05 M HEPES buffer, pH 7.5, 0.1% dithiothreitol [DTT]). The buffer emulated intracellular conditions found in hyperthermophiles, thus protecting DNA from rapid thermodegradation, which renders it a poor template for sequencing. Initial validation experiments employed mycobacteria DNA, either extracted or intracellular. Next, mock clinical samples (infection-negative human sputum spiked with 0 to 105Mycobacterium bovis BCG cells/ml) underwent liquefaction in thermo-protection buffer and heat inactivation. DNA was extracted and sequenced. Human DNA degraded faster than mycobacteria DNA, resulting in target enrichment. Four replicate experiments achieved M. tuberculosis detection at 101 BCG cells/ml, with 31 to 59 M. tuberculosis complex reads. Maximal genome coverage (>97% at 5× depth) occurred at 104 BCG cells/ml; >91% coverage (1× depth) occurred at 103 BCG cells/ml. Final validation employed M. tuberculosis-positive clinical samples (n = 20), revealing that initial sample volumes of ≥1 ml typically yielded higher mean depths of M. tuberculosis genome coverage, with an overall range of 0.55 to 81.02. A mean depth of 3 gave >96% 1-fold tuberculosis (TB) genome coverage (in 15/20 clinical samples). A mean depth of 15 achieved >99% 5-fold genome coverage (in 9/20 clinical samples). In summary, direct-from-sample sequencing of M. tuberculosis genomes was facilitated by a low-cost thermo-protection buffer.
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49
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Jajou R, Kohl TA, Walker T, Norman A, Cirillo DM, Tagliani E, Niemann S, de Neeling A, Lillebaek T, Anthony RM, van Soolingen D. Towards standardisation: comparison of five whole genome sequencing (WGS) analysis pipelines for detection of epidemiologically linked tuberculosis cases. ACTA ACUST UNITED AC 2020; 24. [PMID: 31847944 PMCID: PMC6918587 DOI: 10.2807/1560-7917.es.2019.24.50.1900130] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Background Whole genome sequencing (WGS) is a reliable tool for studying tuberculosis (TB) transmission. WGS data are usually processed by custom-built analysis pipelines with little standardisation between them. Aim To compare the impact of variability of several WGS analysis pipelines used internationally to detect epidemiologically linked TB cases. Methods From the Netherlands, 535 Mycobacterium tuberculosis complex (MTBC) strains from 2016 were included. Epidemiological information obtained from municipal health services was available for all mycobacterial interspersed repeat unit-variable number of tandem repeat (MIRU-VNTR) clustered cases. WGS data was analysed using five different pipelines: one core genome multilocus sequence typing (cgMLST) approach and four single nucleotide polymorphism (SNP)-based pipelines developed in Oxford, United Kingdom; Borstel, Germany; Bilthoven, the Netherlands and Copenhagen, Denmark. WGS clusters were defined using a maximum pairwise distance of 12 SNPs/alleles. Results The cgMLST approach and Oxford pipeline clustered all epidemiologically linked cases, however, in the other three SNP-based pipelines one epidemiological link was missed due to insufficient coverage. In general, the genetic distances varied between pipelines, reflecting different clustering rates: the cgMLST approach clustered 92 cases, followed by 84, 83, 83 and 82 cases in the SNP-based pipelines from Copenhagen, Oxford, Borstel and Bilthoven respectively. Conclusion Concordance in ruling out epidemiological links was high between pipelines, which is an important step in the international validation of WGS data analysis. To increase accuracy in identifying TB transmission clusters, standardisation of crucial WGS criteria and creation of a reference database of representative MTBC sequences would be advisable.
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Affiliation(s)
- Rana Jajou
- These authors contributed equally.,Center of Epidemiology and Surveillance of infectious diseases, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.,Tuberculosis Reference Laboratory, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Thomas A Kohl
- German Center for Infection Research, Borstel site, Borstel, Germany.,Molecular and Experimental Mycobacteriology, Forschungszentrum Borstel, Borstel, Germany.,These authors contributed equally
| | - Timothy Walker
- Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Anders Norman
- International Reference Laboratory of Mycobacteriology, Statens Serum Institut, Copenhagen, Denmark
| | - Daniela Maria Cirillo
- Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisa Tagliani
- Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Niemann
- German Center for Infection Research (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Germany.,Molecular and Experimental Mycobacteriology, Forschungszentrum Borstel, Borstel, Germany
| | - Albert de Neeling
- Tuberculosis Reference Laboratory, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Troels Lillebaek
- Global Health Section, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.,International Reference Laboratory of Mycobacteriology, Statens Serum Institut, Copenhagen, Denmark
| | - Richard M Anthony
- Tuberculosis Reference Laboratory, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Dick van Soolingen
- Tuberculosis Reference Laboratory, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
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50
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Walter KS, Colijn C, Cohen T, Mathema B, Liu Q, Bowers J, Engelthaler DM, Narechania A, Lemmer D, Croda J, Andrews JR. Genomic variant-identification methods may alter Mycobacterium tuberculosis transmission inferences. Microb Genom 2020; 6:mgen000418. [PMID: 32735210 PMCID: PMC7641424 DOI: 10.1099/mgen.0.000418] [Citation(s) in RCA: 12] [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: 04/17/2020] [Accepted: 07/15/2020] [Indexed: 12/31/2022] Open
Abstract
Pathogen genomic data are increasingly used to characterize global and local transmission patterns of important human pathogens and to inform public health interventions. Yet, there is no current consensus on how to measure genomic variation. To test the effect of the variant-identification approach on transmission inferences for Mycobacterium tuberculosis, we conducted an experiment in which five genomic epidemiology groups applied variant-identification pipelines to the same outbreak sequence data. We compared the variants identified by each group in addition to transmission and phylogenetic inferences made with each variant set. To measure the performance of commonly used variant-identification tools, we simulated an outbreak. We compared the performance of three mapping algorithms, five variant callers and two variant filters in recovering true outbreak variants. Finally, we investigated the effect of applying increasingly stringent filters on transmission inferences and phylogenies. We found that variant-calling approaches used by different groups do not recover consistent sets of variants, which can lead to conflicting transmission inferences. Further, performance in recovering true variation varied widely across approaches. While no single variant-identification approach outperforms others in both recovering true genome-wide and outbreak-level variation, variant-identification algorithms calibrated upon real sequence data or that incorporate local reassembly outperform others in recovering true pairwise differences between isolates. The choice of variant filters contributed to extensive differences across pipelines, and applying increasingly stringent filters rapidly eroded the accuracy of transmission inferences and quality of phylogenies reconstructed from outbreak variation. Commonly used approaches to identify M. tuberculosis genomic variation have variable performance, particularly when predicting potential transmission links from pairwise genetic distances. Phylogenetic reconstruction may be improved by less stringent variant filtering. Approaches that improve variant identification in repetitive, hypervariable regions, such as long-read assemblies, may improve transmission inference.
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Affiliation(s)
- Katharine S. Walter
- Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University, Burnaby, BC, Canada
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Barun Mathema
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, New York, USA
| | - Qingyun Liu
- School of Basic Medical Science of Fudan University, Shanghai, PR China
| | - Jolene Bowers
- Translational Genomics Research Institute, Flagstaff, AZ, USA
| | | | | | - Darrin Lemmer
- Translational Genomics Research Institute, Flagstaff, AZ, USA
| | - Julio Croda
- School of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, Brazil
- Oswaldo Cruz Foundation, Campo Grande, Brazil
| | - Jason R. Andrews
- Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA
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