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Sadovska D, Ozere I, Pole I, Ķimsis J, Vaivode A, Vīksna A, Norvaiša I, Bogdanova I, Ulanova V, Čapligina V, Bandere D, Ranka R. Unraveling tuberculosis patient cluster transmission chains: integrating WGS-based network with clinical and epidemiological insights. Front Public Health 2024; 12:1378426. [PMID: 38832230 PMCID: PMC11144917 DOI: 10.3389/fpubh.2024.1378426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 05/07/2024] [Indexed: 06/05/2024] Open
Abstract
Background Tuberculosis remains a global health threat, and the World Health Organization reports a limited reduction in disease incidence rates, including both new and relapse cases. Therefore, studies targeting tuberculosis transmission chains and recurrent episodes are crucial for developing the most effective control measures. Herein, multiple tuberculosis clusters were retrospectively investigated by integrating patients' epidemiological and clinical information with median-joining networks recreated based on whole genome sequencing (WGS) data of Mycobacterium tuberculosis isolates. Methods Epidemiologically linked tuberculosis patient clusters were identified during the source case investigation for pediatric tuberculosis patients. Only M. tuberculosis isolate DNA samples with previously determined spoligotypes identical within clusters were subjected to WGS and further median-joining network recreation. Relevant clinical and epidemiological data were obtained from patient medical records. Results We investigated 18 clusters comprising 100 active tuberculosis patients 29 of whom were children at the time of diagnosis; nine patients experienced recurrent episodes. M. tuberculosis isolates of studied clusters belonged to Lineages 2 (sub-lineage 2.2.1) and 4 (sub-lineages 4.3.3, 4.1.2.1, 4.8, and 4.2.1), while sub-lineage 4.3.3 (LAM) was the most abundant. Isolates of six clusters were drug-resistant. Within clusters, the maximum genetic distance between closely related isolates was only 5-11 single nucleotide variants (SNVs). Recreated median-joining networks, integrated with patients' diagnoses, specimen collection dates, sputum smear microscopy, and epidemiological investigation results indicated transmission directions within clusters and long periods of latent infection. It also facilitated the identification of potential infection sources for pediatric patients and recurrent active tuberculosis episodes refuting the reactivation possibility despite the small genetic distance of ≤5 SNVs between isolates. However, unidentified active tuberculosis cases within the cluster, the variable mycobacterial mutation rate in dormant and active states, and low M. tuberculosis genetic variability inferred precise transmission chain delineation. In some cases, heterozygous SNVs with an allelic frequency of 10-73% proved valuable in identifying direct transmission events. Conclusion The complex approach of integrating tuberculosis cluster WGS-data-based median-joining networks with relevant epidemiological and clinical data proved valuable in delineating epidemiologically linked patient transmission chains and deciphering causes of recurrent tuberculosis episodes within clusters.
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Affiliation(s)
- Darja Sadovska
- Laboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Iveta Ozere
- Centre of Tuberculosis and Lung Diseases, Riga East University Hospital, Upeslejas, Latvia
- Department of Infectology, Riga Stradiņš University, Riga, Latvia
| | - Ilva Pole
- Centre of Tuberculosis and Lung Diseases, Riga East University Hospital, Upeslejas, Latvia
| | - Jānis Ķimsis
- Laboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Annija Vaivode
- Laboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Anda Vīksna
- Centre of Tuberculosis and Lung Diseases, Riga East University Hospital, Upeslejas, Latvia
- Department of Infectology, Riga Stradiņš University, Riga, Latvia
| | - Inga Norvaiša
- Centre of Tuberculosis and Lung Diseases, Riga East University Hospital, Upeslejas, Latvia
| | - Ineta Bogdanova
- Centre of Tuberculosis and Lung Diseases, Riga East University Hospital, Upeslejas, Latvia
| | - Viktorija Ulanova
- Laboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Valentīna Čapligina
- Laboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Dace Bandere
- Department of Pharmaceutical Chemistry, Riga Stradiņš University, Riga, Latvia
| | - Renāte Ranka
- Laboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia
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Allen A, Magee R, Devaney R, Ardis T, McNally C, McCormick C, Presho E, Doyle M, Ranasinghe P, Johnston P, Kirke R, Harwood R, Farrell D, Kenny K, Smith J, Gordon S, Ford T, Thompson S, Wright L, Jones K, Prodohl P, Skuce R. Whole-Genome sequencing in routine Mycobacterium bovis epidemiology - scoping the potential. Microb Genom 2024; 10:001185. [PMID: 38354031 PMCID: PMC10926703 DOI: 10.1099/mgen.0.001185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 01/09/2024] [Indexed: 02/16/2024] Open
Abstract
Mycobacterium bovis the main agent of bovine tuberculosis (bTB), presents as a series of spatially-localised micro-epidemics across landscapes. Classical molecular typing methods applied to these micro-epidemics, based on genotyping a few variable loci, have significantly improved our understanding of potential epidemiological links between outbreaks. However, they have limited utility owing to low resolution. Conversely, whole-genome sequencing (WGS) provides the highest resolution data available for molecular epidemiology, producing richer outbreak tracing, insights into phylogeography and epidemic evolutionary history. We illustrate these advantages by focusing on a common single lineage of M. bovis (1.140) from Northern Ireland. Specifically, we investigate the spatial sub-structure of 20 years of herd-level multi locus VNTR analysis (MLVA) surveillance data and WGS data from a down sampled subset of isolates of this MLVA type over the same time frame. We mapped 2108 isolate locations of MLVA type 1.140 over the years 2000-2022. We also mapped the locations of 148 contemporary WGS isolates from this lineage, over a similar geographic range, stratifying by single nucleotide polymorphism (SNP) relatedness cut-offs of 15 SNPs. We determined a putative core range for the 1.140 MLVA type and SNP-defined sequence clusters using a 50 % kernel density estimate, using cattle movement data to inform on likely sources of WGS isolates found outside of core ranges. Finally, we applied Bayesian phylogenetic methods to investigate past population history and reproductive number of the 1.140 M. bovis lineage. We demonstrate that WGS SNP-defined clusters exhibit smaller core ranges than the established MLVA type - facilitating superior disease tracing. We also demonstrate the superior functionality of WGS data in determining how this lineage was disseminated across the landscape, likely via cattle movement and to infer how its effective population size and reproductive number has been in flux since its emergence. These initial findings highlight the potential of WGS data for routine monitoring of bTB outbreaks.
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Affiliation(s)
- Adrian Allen
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Ryan Magee
- Queen’s University Belfast, school of Biological Sciences, UK
| | - Ryan Devaney
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Tara Ardis
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Caitlín McNally
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Carl McCormick
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Eleanor Presho
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Michael Doyle
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Purnika Ranasinghe
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Philip Johnston
- Department of Agriculture, Environment and Rural Affairs for Northern Ireland, Belfast, UK
| | - Raymond Kirke
- Department of Agriculture, Environment and Rural Affairs for Northern Ireland, Belfast, UK
| | - Roland Harwood
- Department of Agriculture, Environment and Rural Affairs for Northern Ireland, Belfast, UK
| | - Damien Farrell
- Central Veterinary Research Laboratory, Kildare, Ireland
- University College Dublin, Dublin, Ireland
| | - Kevin Kenny
- Central Veterinary Research Laboratory, Kildare, Ireland
| | | | | | - Tom Ford
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Suzan Thompson
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Lorraine Wright
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Kerri Jones
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Paulo Prodohl
- Queen’s University Belfast, school of Biological Sciences, UK
| | - Robin Skuce
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
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Morey-León G, Mejía-Ponce PM, Granda Pardo JC, Muñoz-Mawyin K, Fernández-Cadena JC, García-Moreira E, Andrade-Molina D, Licona-Cassani C, Berná L. A precision overview of genomic resistance screening in Ecuadorian isolates of Mycobacterium tuberculosis using web-based bioinformatics tools. PLoS One 2023; 18:e0294670. [PMID: 38051742 DOI: 10.1371/journal.pone.0294670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Accepted: 11/07/2023] [Indexed: 12/07/2023] Open
Abstract
INTRODUCTION Tuberculosis (TB) is among the deadliest diseases worldwide, and its impact is mainly due to the continuous emergence of resistant isolates during treatment due to the laborious process of resistance diagnosis, nonadherence to treatment and circulation of previously resistant isolates of Mycobacterium tuberculosis. In this study, we evaluated the performance and functionalities of web-based tools, including Mykrobe, TB-profiler, PhyResSE, KvarQ, and SAM-TB, for detecting resistance in 88 Ecuadorian isolates of Mycobacterium tuberculosis drug susceptibility tested previously. Statistical analysis was used to determine the correlation between genomic and phenotypic analysis. Our results showed that with the exception of KvarQ, all tools had the highest correlation with the conventional drug susceptibility test (DST) for global resistance detection (98% agreement and 0.941 Cohen's kappa), while SAM-TB, PhyResSE, TB-profiler and Mykrobe had better correlations with DST for first-line drug analysis individually. We also identified that in our study, only 50% of mutations characterized by the web-based tools in the rpoB, katG, embB, pncA, gyrA and rrs regions were canonical and included in the World Health Organization (WHO) catalogue. Our findings suggest that SAM-TB, PhyResSE, TB-profiler and Mykrobe were efficient in determining canonical resistance-related mutations, but more analysis is needed to improve second-line detection. Improving surveillance programs using whole-genome sequencing tools for first-line drugs, MDR-TB and XDR-TB is essential to understand the molecular epidemiology of TB in Ecuador. IMPORTANCE Tuberculosis, an infectious disease caused by Mycobacterium tuberculosis, most commonly affects the lungs and is often spread through the air when infected people cough, sneeze, or spit. However, despite the existence of effective drug treatment, patient adherence, long duration of treatment, and late diagnosis have reduced the effectiveness of therapy and increased drug resistance. The increase in resistant cases, added to the impact of the COVID-19 pandemic, has highlighted the importance of implementing efficient and timely diagnostic methodologies worldwide. The significance of our research is in evaluating and identifying a more efficient and user-friendly web-based tool to characterize resistance in Mycobacterium tuberculosis by whole-genome sequencing, which will allow more routine application to improve TB strain surveillance programs locally.
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Affiliation(s)
- Gabriel Morey-León
- Facultad de Ciencias de la Salud, Universidad Espíritu Santo, Samborondón, Ecuador
- Universidad de la República, Montevideo, Uruguay
- University of Guayaquil, Guayaquil, Ecuador
| | - Paulina M Mejía-Ponce
- Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Monterrey, Nuevo León, México
| | - Juan Carlos Granda Pardo
- Centro de Referencia Nacional de Micobacterias, Instituto Nacional de Investigación en Salud Pública Dr Leopoldo Izquieta Perez, INSPI-LIP, Guayaquil, Ecuador
| | - Karen Muñoz-Mawyin
- Laboratorio de Ciencias Ómicas, Universidad Espíritu Santo, Samborondón, Ecuador
| | | | | | - Derly Andrade-Molina
- Facultad de Ciencias de la Salud, Universidad Espíritu Santo, Samborondón, Ecuador
- Laboratorio de Ciencias Ómicas, Universidad Espíritu Santo, Samborondón, Ecuador
| | | | - Luisa Berná
- Laboratorio de Interacciones Hospedero-Patógeno, Unidad de Biología Molecular, Institut Pasteur de Montevideo, Montevideo, Uruguay
- Unidad de Genómica Evolutiva, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay
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Shaw B, von Bredow B, Tsan A, Garner O, Yang S. Clinical Whole-Genome Sequencing Assay for Rapid Mycobacterium tuberculosis Complex First-Line Drug Susceptibility Testing and Phylogenetic Relatedness Analysis. Microorganisms 2023; 11:2538. [PMID: 37894195 PMCID: PMC10609454 DOI: 10.3390/microorganisms11102538] [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: 07/26/2023] [Revised: 09/25/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
The global rise of drug resistant tuberculosis has highlighted the need for improved diagnostic technologies that provide rapid and reliable drug resistance results. Here, we develop and validate a whole genome sequencing (WGS)-based test for identification of mycobacterium tuberculosis complex (MTB) drug resistance to rifampin, isoniazid, pyrazinamide, ethambutol, and streptomycin. Through comparative analysis of drug resistance results from WGS-based testing and phenotypic drug susceptibility testing (DST) of 38 clinical MTB isolates from patients receiving care in Los Angeles, CA, we found an overall concordance between methods of 97.4% with equivalent performance across culture media. Critically, prospective analysis of 11 isolates showed that WGS-based testing provides results an average of 36 days faster than phenotypic culture-based methods. We showcase the additional benefits of WGS data by investigating a suspected laboratory contamination event and using phylogenetic analysis to search for cryptic local transmission, finding no evidence of community spread amongst our patient population in the past six years. WGS-based testing for MTB drug resistance has the potential to greatly improve diagnosis of drug resistant MTB by accelerating turnaround time while maintaining accuracy and providing additional benefits for infection control, lab safety, and public health applications.
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Affiliation(s)
- Bennett Shaw
- Department of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA; (B.S.); (B.v.B.); (A.T.); (O.G.)
| | - Benjamin von Bredow
- Department of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA; (B.S.); (B.v.B.); (A.T.); (O.G.)
- Department of Pathology, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA
| | - Allison Tsan
- Department of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA; (B.S.); (B.v.B.); (A.T.); (O.G.)
| | - Omai Garner
- Department of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA; (B.S.); (B.v.B.); (A.T.); (O.G.)
| | - Shangxin Yang
- Department of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA; (B.S.); (B.v.B.); (A.T.); (O.G.)
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Koleske BN, Jacobs WR, Bishai WR. The Mycobacterium tuberculosis genome at 25 years: lessons and lingering questions. J Clin Invest 2023; 133:e173156. [PMID: 37781921 PMCID: PMC10541200 DOI: 10.1172/jci173156] [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] [Indexed: 10/03/2023] Open
Abstract
First achieved in 1998 by Cole et al., the complete genome sequence of Mycobacterium tuberculosis continues to provide an invaluable resource to understand tuberculosis (TB), the leading cause of global infectious disease mortality. At the 25-year anniversary of this accomplishment, we describe how insights gleaned from the M. tuberculosis genome have led to vital tools for TB research, epidemiology, and clinical practice. The increasing accessibility of whole-genome sequencing across research and clinical settings has improved our ability to predict antibacterial susceptibility, to track epidemics at the level of individual outbreaks and wider historical trends, to query the efficacy of the bacille Calmette-Guérin (BCG) vaccine, and to uncover targets for novel antitubercular therapeutics. Likewise, we discuss several recent efforts to extract further discoveries from this powerful resource.
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Affiliation(s)
- Benjamin N. Koleske
- Center for Tuberculosis Research, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - William R. Jacobs
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - William R. Bishai
- Center for Tuberculosis Research, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
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