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Chao Y, Li J, Gong Z, Li C, Ye M, Hong Q, Zhao X, Sun Y, Chen Z, Zhang S, Hu J, Zhang Y, Zhang H, Xu X, Zhang X, Anwar D, Hou Y, Zhang D, Zhang X. Rapid discrimination between tuberculosis and sarcoidosis using next-generation sequencing. Int J Infect Dis 2021; 108:129-136. [PMID: 34004327 DOI: 10.1016/j.ijid.2021.05.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 05/11/2021] [Accepted: 05/12/2021] [Indexed: 11/28/2022] Open
Abstract
OBJECTIVES Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (MTB), has similar clinical, radiological, and histopathological characteristics to sarcoidosis (SA). Accurately distinguishing SA from TB remains a clinical challenge. METHODS A total of 44 TB patients and 47 SA patients who were clinically diagnosed using chest radiography, pathological examination, routine smear microscopy, and microbial culture were enrolled in this study. The MTB genome was captured and sequenced directly from tissue specimens obtained upon operation or biopsy, and the feasibility of next-generation sequencing (NGS) for the MTB genome in the differential diagnosis of TB from SA was evaluated. RESULTS Using a depth >10× and coverage >15% of the sequencing data, TB patients were identified via the NGS approach directly using operation or biopsy specimens without clinical pretreatment. The sensitivity, specificity, and concordance of the NGS method were 81.8% (36/44), 95.7% (45/47), and 89.0% (81/91), respectively (kappa = 0.78, 95% confidence interval 0.65-0.91; P<0.001). CONCLUSIONS This study established an improved NGS strategy for rapidly distinguishing patients with TB from those with SA and has potential clinical benefits.
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Affiliation(s)
- Yencheng Chao
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jieyi Li
- Jiaxing Key Laboratory of Precision Medicine and Companion Diagnostics, Jiaxing Yunying Medical Inspection Co., Ltd., Jiaxing 314000, China; Department of R&D, Shanghai Yunying Medical Technology, Co., Ltd., Shanghai 200016, China
| | - Ziying Gong
- Jiaxing Key Laboratory of Precision Medicine and Companion Diagnostics, Jiaxing Yunying Medical Inspection Co., Ltd., Jiaxing 314000, China; Department of R&D, Shanghai Yunying Medical Technology, Co., Ltd., Shanghai 200016, China
| | - Chun Li
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Maosong Ye
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Qunying Hong
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xiaokai Zhao
- Jiaxing Key Laboratory of Precision Medicine and Companion Diagnostics, Jiaxing Yunying Medical Inspection Co., Ltd., Jiaxing 314000, China; Department of R&D, Shanghai Yunying Medical Technology, Co., Ltd., Shanghai 200016, China
| | - Yonghua Sun
- Jiaxing Key Laboratory of Precision Medicine and Companion Diagnostics, Jiaxing Yunying Medical Inspection Co., Ltd., Jiaxing 314000, China; Department of R&D, Shanghai Yunying Medical Technology, Co., Ltd., Shanghai 200016, China
| | - Zhonghai Chen
- Jiaxing Key Laboratory of Precision Medicine and Companion Diagnostics, Jiaxing Yunying Medical Inspection Co., Ltd., Jiaxing 314000, China; Department of R&D, Shanghai Yunying Medical Technology, Co., Ltd., Shanghai 200016, China
| | - Shaojie Zhang
- Jiaxing Key Laboratory of Precision Medicine and Companion Diagnostics, Jiaxing Yunying Medical Inspection Co., Ltd., Jiaxing 314000, China; Department of R&D, Shanghai Yunying Medical Technology, Co., Ltd., Shanghai 200016, China
| | - Jie Hu
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yong Zhang
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Huijun Zhang
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xiaobo Xu
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xinyu Zhang
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Dilbar Anwar
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yingyong Hou
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
| | - Daoyun Zhang
- Jiaxing Key Laboratory of Precision Medicine and Companion Diagnostics, Jiaxing Yunying Medical Inspection Co., Ltd., Jiaxing 314000, China; Department of R&D, Shanghai Yunying Medical Technology, Co., Ltd., Shanghai 200016, China.
| | - Xin Zhang
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
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Fernandez Do Porto DA, Monteserin J, Campos J, Sosa EJ, Matteo M, Serral F, Yokobori N, Benevento AF, Poklepovich T, Pardo A, Wainmayer I, Simboli N, Castello F, Paul R, Martí M, López B, Turjanski A, Ritacco V. Five-year microevolution of a multidrug-resistant Mycobacterium tuberculosis strain within a patient with inadequate compliance to treatment. BMC Infect Dis 2021; 21:394. [PMID: 33926375 PMCID: PMC8082761 DOI: 10.1186/s12879-021-06069-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 04/14/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Whole-genome sequencing has shown that the Mycobacterium tuberculosis infection process can be more heterogeneous than previously thought. Compartmentalized infections, exogenous reinfections, and microevolution are manifestations of this clonal complexity. The analysis of the mechanisms causing the microevolution -the genetic variability of M. tuberculosis at short time scales- of a parental strain into clonal variants with a patient is a relevant issue that has not been yet completely addressed. To our knowledge, a whole genome sequence microevolution analysis in a single patient with inadequate adherence to treatment has not been previously reported. CASE PRESENTATION In this work, we applied whole genome sequencing analysis for a more in-depth analysis of the microevolution of a parental Mycobacterium tuberculosis strain into clonal variants within a patient with poor treatment compliance in Argentina. We analyzed the whole-genome sequence of 8 consecutive Mycobacterium tuberculosis isolates obtained from a patient within 57-months of intermittent therapy. Nineteen mutations (9 short-term, 10 fixed variants) emerged, most of them associated with drug resistance. The first isolate was already resistant to isoniazid, rifampicin, and streptomycin, thereafter the strain developed resistance to fluoroquinolones and pyrazinamide. Surprisingly, isolates remained susceptible to the pro-drug ethionamide after acquiring a frameshift mutation in ethA, a gene required for its activation. We also found a novel variant, (T-54G), in the 5' untranslated region of whiB7 (T-54G), a region allegedly related to kanamycin resistance. Notably, discrepancies between canonical and phage-based susceptibility testing to kanamycin were previously found for the isolate harboring this mutation. In our patient, microevolution was mainly driven by drug selective pressure. Rare short-term mutations fixed together with resistance-conferring mutations during therapy. CONCLUSIONS This report highlights the relevance of whole-genome sequencing analysis in the clinic for characterization of pre-XDR and MDR resistance profile, particularly in patients with incomplete and/or intermittent treatment.
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Affiliation(s)
- Darío A Fernandez Do Porto
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Johana Monteserin
- Instituto Nacional de Enfermedades Infecciosas-ANLIS Carlos Malbrán, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Josefina Campos
- Instituto Nacional de Enfermedades Infecciosas-ANLIS Carlos Malbrán, Buenos Aires, Argentina
| | - Ezequiel J Sosa
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales, IQUIBICEN, CONICET, Buenos Aires, Argentina
| | - Mario Matteo
- Instituto de Tisioneumonología Raúl F. Vaccarezza, Hospital de Infecciosas Dr. F. J. Muñiz, Buenos Aires, Argentina
| | - Federico Serral
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Noemí Yokobori
- Instituto Nacional de Enfermedades Infecciosas-ANLIS Carlos Malbrán, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Andrés Fernández Benevento
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales, IQUIBICEN, CONICET, Buenos Aires, Argentina
| | - Tomás Poklepovich
- Instituto Nacional de Enfermedades Infecciosas-ANLIS Carlos Malbrán, Buenos Aires, Argentina
| | - Agustín Pardo
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales, IQUIBICEN, CONICET, Buenos Aires, Argentina
| | - Ingrid Wainmayer
- Instituto Nacional de Enfermedades Infecciosas-ANLIS Carlos Malbrán, Buenos Aires, Argentina
| | - Norberto Simboli
- Instituto Nacional de Enfermedades Infecciosas-ANLIS Carlos Malbrán, Buenos Aires, Argentina
| | - Florencia Castello
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Roxana Paul
- Instituto Nacional de Enfermedades Infecciosas-ANLIS Carlos Malbrán, Buenos Aires, Argentina
| | - Marcelo Martí
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales, IQUIBICEN, CONICET, Buenos Aires, Argentina
| | - Beatriz López
- Instituto Nacional de Enfermedades Infecciosas-ANLIS Carlos Malbrán, Buenos Aires, Argentina
| | - Adrián Turjanski
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales, IQUIBICEN, CONICET, Buenos Aires, Argentina.
| | - Viviana Ritacco
- Instituto Nacional de Enfermedades Infecciosas-ANLIS Carlos Malbrán, Buenos Aires, Argentina.
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.
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Merker M, Nikolaevskaya E, Kohl TA, Molina-Moya B, Pavlovska O, Brännberg P, Dudnyk A, Stokich V, Barilar I, Marynova I, Filipova T, Prat C, Sjöstedt A, Dominguez J, Rzhepishevska O, Niemann S. Multidrug- and Extensively Drug-Resistant Mycobacterium tuberculosis Beijing Clades, Ukraine, 2015. Emerg Infect Dis 2021; 26:481-490. [PMID: 32091369 PMCID: PMC7045844 DOI: 10.3201/eid2603.190525] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis (TB) is an emerging threat to TB control in Ukraine, a country with the third highest XDR TB burden globally. We used whole-genome sequencing of a convenience sample to identify bacterial genetic and patient-related factors associated with MDR/XDR TB in this country. MDR/XDR TB was associated with 3 distinct Mycobacterium tuberculosis complex lineage 2 (Beijing) clades, Europe/Russia W148 outbreak, Central Asia outbreak, and Ukraine outbreak, which comprised 68.9% of all MDR/XDR TB strains from southern Ukraine. MDR/XDR TB was also associated with previous treatment for TB and urban residence. The circulation of Beijing outbreak strains harboring broad drug resistance, coupled with constraints in drug supply and limited availability of phenotypic drug susceptibility testing, needs to be considered when new TB management strategies are implemented in Ukraine.
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Asare P, Osei-Wusu S, Baddoo NA, Bedeley E, Otchere ID, Brites D, Loiseau C, Asante-Poku A, Prah DA, Borrell S, Reinhard M, Omari MA, Forson A, Koram KA, Gagneux S, Yeboah-Manu D. Genomic epidemiological analysis identifies high relapse among individuals with recurring tuberculosis and provides evidence of recent household-related transmission of tuberculosis in Ghana. Int J Infect Dis 2021; 106:13-22. [PMID: 33667696 PMCID: PMC8134059 DOI: 10.1016/j.ijid.2021.02.110] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 02/25/2021] [Accepted: 02/25/2021] [Indexed: 11/29/2022] Open
Abstract
Unresolved previous infection as major cause of recurring tuberculosis (TB) in Ghana. Genomic epidemiology identifies high relapse among recurrent TB cases in Ghana. 15-locus MIRU-VNTR typing is sufficient to predict the cause of TB recurrence. Evidence of recent household-related TB transmission in Ghana. Need for increased education by national TB control program.
Objective To retrospectively investigate the cause of recurring tuberculosis (rcTB) among participants with pulmonary TB recruited from a prospective population-based study conducted between July 2012 and December 2015. Methods Mycobacterium tuberculosis complex isolates obtained from rcTB cases were characterized by standard mycobacterial genotyping tools, whole-genome sequencing, and phylogenetic analysis carried out to assess strain relatedness. Results The majority (58.3%, 21/36) of study participants with rcTB episodes had TB recurrence within 12 months post treatment. TB strains with isoniazid (INH) resistance were found in 19.4% (7/36) of participants at the primary episode, of which 29% (2/7) were also rifampicin-resistant. On TB recurrence, an INH-resistant strain was found in a larger proportion of participants, 27.8% (10/36), of which 40% (4/10) were MDR-TB strains. rcTB was attributed to relapse (same strain) in 75.0% (27/36) of participants and 25.0% (9/36) to re-infection. Conclusion Our findings indicate that previous unresolved infectiondue to inadequate treatment, may be the major cause of rcTB.
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Affiliation(s)
- Prince Asare
- Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana (UG), Ghana; West African Centre for Cell Biology of Infectious Pathogens, UG, Ghana; Department of Biochemistry, Cell and Molecular Biology, UG, Ghana.
| | - Stephen Osei-Wusu
- Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana (UG), Ghana
| | | | - Edmund Bedeley
- Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana (UG), Ghana
| | - Isaac Darko Otchere
- Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana (UG), Ghana
| | - Daniela Brites
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Chloé Loiseau
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Adwoa Asante-Poku
- Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana (UG), Ghana
| | - Diana Ahu Prah
- Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana (UG), Ghana
| | - Sonia Borrell
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Miriam Reinhard
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Michael Amo Omari
- Department of Chest Diseases, Korle-Bu Teaching Hospital, Korle-Bu, Accra, Ghana
| | - Audrey Forson
- Department of Chest Diseases, Korle-Bu Teaching Hospital, Korle-Bu, Accra, Ghana
| | - Kwadwo Ansah Koram
- Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana (UG), Ghana
| | - Sebastien Gagneux
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Dorothy Yeboah-Manu
- Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana (UG), Ghana; West African Centre for Cell Biology of Infectious Pathogens, UG, Ghana
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Cresswell FV, Davis AG, Sharma K, Basu Roy R, Ganiem AR, Kagimu E, Solomons R, Wilkinson RJ, Bahr NC, Thuong NTT. Recent Developments in Tuberculous Meningitis Pathogenesis and Diagnostics. Wellcome Open Res 2021; 4:164. [PMID: 33364436 PMCID: PMC7739117 DOI: 10.12688/wellcomeopenres.15506.3] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/15/2021] [Indexed: 12/13/2022] Open
Abstract
The pathogenesis of Tuberculous meningitis (TBM) is poorly understood, but contemporary molecular biology technologies have allowed for recent improvements in our understanding of TBM. For instance, neutrophils appear to play a significant role in the immunopathogenesis of TBM, and either a paucity or an excess of inflammation can be detrimental in TBM. Further, severity of HIV-associated immunosuppression is an important determinant of inflammatory response; patients with the advanced immunosuppression (CD4+ T-cell count of <150 cells/μL) having higher CSF neutrophils, greater CSF cytokine concentrations and higher mortality than those with CD4+ T-cell counts > 150 cells/μL. Host genetics may also influence outcomes with LT4AH genotype predicting inflammatory phenotype, steroid responsiveness and survival in Vietnamese adults with TBM. Whist in Indonesia, CSF tryptophan level was a predictor of survival, suggesting tryptophan metabolism may be important in TBM pathogenesis. These varying responses mean that we must consider whether a "one-size-fits-all" approach to anti-bacillary or immunomodulatory treatment in TBM is truly the best way forward. Of course, to allow for proper treatment, early and rapid diagnosis of TBM must occur. Diagnosis has always been a challenge but the field of TB diagnosis is evolving, with sensitivities of at least 70% now possible in less than two hours with GeneXpert MTB/Rif Ultra. In addition, advanced molecular techniques such as CRISPR-MTB and metagenomic next generation sequencing may hold promise for TBM diagnosis. Host-based biomarkers and signatures are being further evaluated in childhood and adult TBM as adjunctive biomarkers as even with improved molecular assays, cases are still missed. A better grasp of host and pathogen behaviour may lead to improved diagnostics, targeted immunotherapy, and possibly biomarker-based, patient-specific treatment regimens.
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Affiliation(s)
- Fiona V Cresswell
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
- Research Department, Infectious Diseases Institute, Kampala, PO Box 22418, Uganda
- MRC-UVRI-London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda
| | - Angharad G. Davis
- University College London, London, WC1E6BT, UK
- Francis Crick Institute, London, NW1 1AT, UK
- Department of Medicine, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, 7925, South Africa
| | - Kusum Sharma
- Department of Medical Microbiology, Post-graduate Department of Medical Education and Research, Chandigahr, India
| | - Robindra Basu Roy
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
| | - Ahmad Rizal Ganiem
- Department of Neurology, Hasan Sadikin Hospital, Faculty of Medicine. Universitas Padjadjaran, Bandung, Indonesia
| | - Enock Kagimu
- Research Department, Infectious Diseases Institute, Kampala, PO Box 22418, Uganda
| | - Regan Solomons
- Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, South Africa
| | - Robert J. Wilkinson
- Francis Crick Institute, London, NW1 1AT, UK
- Department of Medicine, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, 7925, South Africa
- Department of Infectious Diseases, Imperial College, London, W2 1PG, UK
| | - Nathan C Bahr
- Division of Infectious Diseases. Department of Medicine., University of Kansas, Kansas City, USA
| | | | - Tuberculous Meningitis International Research Consortium
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
- Research Department, Infectious Diseases Institute, Kampala, PO Box 22418, Uganda
- MRC-UVRI-London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda
- University College London, London, WC1E6BT, UK
- Francis Crick Institute, London, NW1 1AT, UK
- Department of Medicine, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, 7925, South Africa
- Department of Medical Microbiology, Post-graduate Department of Medical Education and Research, Chandigahr, India
- Department of Neurology, Hasan Sadikin Hospital, Faculty of Medicine. Universitas Padjadjaran, Bandung, Indonesia
- Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, South Africa
- Department of Infectious Diseases, Imperial College, London, W2 1PG, UK
- Division of Infectious Diseases. Department of Medicine., University of Kansas, Kansas City, USA
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
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Nonghanphithak D, Kaewprasert O, Chaiyachat P, Reechaipichitkul W, Chaiprasert A, Faksri K. Whole-genome sequence analysis and comparisons between drug-resistance mutations and minimum inhibitory concentrations of Mycobacterium tuberculosis isolates causing M/XDR-TB. PLoS One 2020; 15:e0244829. [PMID: 33382836 PMCID: PMC7775048 DOI: 10.1371/journal.pone.0244829] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 12/16/2020] [Indexed: 11/18/2022] Open
Abstract
Drug resistance (DR) remains a major challenge for tuberculosis (TB) control. Whole-genome sequencing (WGS) provides the highest genetic resolution for genotypic drug-susceptibility tests (DST). We compared DST profiles of 60 Mycobacterium tuberculosis isolates which were drug resistant according to agar proportion tests (one poly DR-TB, 34 multidrug-resistant TB and 25 extensively drug-resistant TB). We additionally performed minimum inhibitory concentration (MIC) tests using Sensititre MYCOTBI plates (MYCOTB) and a WGS-based DST. Agreement between WGS-based DST and MYCOTB was high for all drugs except ethambutol (65%) and ethionamide (62%). Isolates harboring the -15 c/t inhA promoter mutation had a significantly lower MIC for isoniazid than did isolates with the katG Ser315Thr mutation (p < 0.001). Similar patterns were seen for ethambutol (embB Gly406Asp vs. embB Met306Ile), streptomycin (gid Gly73Ala vs. rpsL Lys43Arg), moxifloxacin (gyrA Ala90Val vs. gyrA Asp94Gly) and rifabutin (rpoB Asp435Phe/Tyr/Val vs. rpoB Ser450Leu). For genotypic heteroresistance, isolates with lower proportion of mapped read tended to has lower MIC of anti-TB drugs than those with higher proportion. These results emphasize the high applicability of WGS for determination of DR-TB and the association of particular mutations with MIC levels.
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Affiliation(s)
- Ditthawat Nonghanphithak
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
- Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand
| | - Orawee Kaewprasert
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
- Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand
| | - Pratchakan Chaiyachat
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
- Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand
| | - Wipa Reechaipichitkul
- Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand
- Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
| | - Angkana Chaiprasert
- Drug Resistant Tuberculosis Research Fund Laboratory, Research and Development Affairs, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Kiatichai Faksri
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
- Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand
- * E-mail:
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Welekidan LN, Skjerve E, Dejene TA, Gebremichael MW, Brynildsrud O, Tønjum T, Yimer SA. Frequency and patterns of first- and second-line drug resistance-conferring mutations in Mycobacterium tuberculosis isolated from pulmonary tuberculosis patients in a cross-sectional study in Tigray Region, Ethiopia. J Glob Antimicrob Resist 2020; 24:6-13. [PMID: 33279682 DOI: 10.1016/j.jgar.2020.11.017] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Revised: 10/23/2020] [Accepted: 11/17/2020] [Indexed: 10/22/2022] Open
Abstract
OBJECTIVES Tuberculosis (TB) is a preventable and treatable infectious disease, but the continuing emergence and spread of multidrug-resistant TB is threatening global TB control efforts. This study aimed to describe the frequency and patterns of drug resistance-conferring mutations of Mycobacterium tuberculosis (MTB) isolates detected from pulmonary TB patients in Tigray Region, Ethiopia. METHODS A cross-sectional study design was employed to collect sputum samples from pulmonary TB patients between July 2018 to August 2019. Culture and identification tests were done at Tigray Health Research Institute (THRI). Mutations conferring rifampicin (RIF), isoniazid (INH) and fluoroquinolone (FQ) resistance were determined in 227 MTB isolates using GenoType MTBDRplus and GenoType MTBDRsl. RESULTS Mutations conferring resistance to RIF, INH and FQs were detected in 40/227 (17.6%), 41/227 (18.1%) and 2/38 (5.3%) MTB isolates, respectively. The majority of mutations for RIF, INH and FQs occurred at codons rpoB S531L (70%), katG S315T (78%) and gyrA D94Y/N (100%), respectively. This study revealed a significant number of unknown mutations in the rpoB, katG and inhA genes. CONCLUSION High rates of mutations conferring resistance to RIF, INH and FQs were observed in this study. A large number of isolates showed unknown mutations, which require further DNA sequencing analysis. Periodic drug resistance surveillance and scaling-up of drug resistance testing facilities are imperative to prevent the transmission of drug-resistant TB in the community.
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Affiliation(s)
- Letemichael Negash Welekidan
- Department of Para Clinical Sciences, Norwegian University of Life Sciences, P.O. Box 369, 0102 Oslo, Norway; Department of Production Animal Medicine, Norwegian University of Life Sciences, P.O. Box 369, 0102 Oslo, Norway; Department of Medical Microbiology and Immunology, Division of Biomedical Sciences, College of Health Sciences, Mekelle University, P.O. Box 1871, Mekelle, Ethiopia.
| | - Eystein Skjerve
- Department of Production Animal Medicine, Norwegian University of Life Sciences, P.O. Box 369, 0102 Oslo, Norway
| | - Tsehaye Asmelash Dejene
- Department of Medical Microbiology and Immunology, Division of Biomedical Sciences, College of Health Sciences, Mekelle University, P.O. Box 1871, Mekelle, Ethiopia
| | | | - Ola Brynildsrud
- Department of Para Clinical Sciences, Norwegian University of Life Sciences, P.O. Box 369, 0102 Oslo, Norway; Department of Bacteriology and Immunology, Norwegian Institute of Public Health, P.O. Box 222, 0213 Oslo, Norway
| | - Tone Tønjum
- Department of Microbiology, Unit for Genome Dynamics, University of Oslo, P.O. Box 1072, 0316 Oslo, Norway; Department of Microbiology, Unit for Genome Dynamics, Oslo University Hospital, P.O. Box 4950, 0424 Oslo, Norway
| | - Solomon Abebe Yimer
- Department of Microbiology, Unit for Genome Dynamics, Oslo University Hospital, P.O. Box 4950, 0424 Oslo, Norway; Coalition for Epidemic Preparedness Innovations, Oslo, Norway
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The value of the continuous genotyping of multi-drug resistant tuberculosis over 20 years in Spain. Sci Rep 2020; 10:20433. [PMID: 33235225 PMCID: PMC7686341 DOI: 10.1038/s41598-020-77249-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 11/02/2020] [Indexed: 11/16/2022] Open
Abstract
Molecular epidemiology of circulating clinical isolates is crucial to improve prevention strategies. The Spanish Working Group on multidrug resistant tuberculosis (MDR-TB) is a network that monitors the MDR-TB isolates in Spain since 1998. The aim of this study was to present the study of the MDR-TB and extensively drug-resistant tuberculosis (XDR-TB) patterns in Spain using the different recommended genotyping methods over time by a national coordinated system. Based on the proposed genotyping methods in the European Union until 2018, the preservation of one method, MIRU-VNTR, applied to selected clustered strains permitted to maintain our study open for 20 years. The distribution of demographic, clinical and epidemiological characteristics of clustered and non-clustered cases of MDR/XDR tuberculosis with proportion differences as assessed by Pearson’s chi-squared or Fisher’s exact test was compared. The differences in the quantitative variables using the Student's-t test and the Mann–Whitney U test were evaluated. The results obtained showed a total of 48.4% of the cases grouped in 77 clusters. Younger age groups, having a known TB case contact (10.2% vs 4.7%) and XDR-TB (16.5% vs 1.8%) were significantly associated with clustering. The largest cluster corresponded to a Mycobacterium bovis strain mainly spread during the nineties. A total of 68.4% of the clusters detected were distributed among the different Spanish regions and six clusters involving 104 cases were grouped in 17 and 18 years. Comparison of the genotypes obtained with those European genotypes included in The European Surveillance System (TESSy) showed that 87 cases had become part of 20 European clusters. The continuity of MDR strain genotyping in time has offered a widespread picture of the situation that allows better management of this public health problem. It also shows the advantage of maintaining one genotyping method over time, which allowed the comparison between ancient, present and future samples.
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Lempens P, Decroo T, Aung KJM, Hossain MA, Rigouts L, Meehan CJ, Van Deun A, de Jong BC. Initial resistance to companion drugs should not be considered an exclusion criterion for the shorter multidrug-resistant tuberculosis treatment regimen. Int J Infect Dis 2020; 100:357-365. [PMID: 32829049 PMCID: PMC7670168 DOI: 10.1016/j.ijid.2020.08.042] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 08/13/2020] [Accepted: 08/16/2020] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVES We investigated whether companion drug resistance was associated with adverse outcomes of the shorter multidrug-resistant tuberculosis (MDR-TB) treatment regimen in Bangladesh after adjustment for fluoroquinolone resistance. METHODS MDR-TB/rifampicin-resistant tuberculosis patients registered for treatment with a standardized gatifloxacin-based shorter MDR-TB treatment regimen were selected for the study. Drug resistance was determined by the proportion method, gatifloxacin and isoniazid minimum inhibitory concentration testing for selected isolates, and whole-genome sequencing. RESULTS Low-level fluoroquinolone resistance and high-level fluoroquinolone resistance were the most important predictors of adverse outcomes, with pyrazinamide resistance having a significant yet lower impact. In patients with fluoroquinolone-/second-line-injectable-susceptible tuberculosis, non-eligibility for the shorter MDR-TB treatment regimen (initial resistance to pyrazinamide, ethionamide, or ethambutol) was not associated with adverse outcome (adjusted odds ratio 1.01; 95% confidence interval 0.4-2.8). Kanamycin resistance was uncommon (1.3%). Increasing levels of resistance to isoniazid predicted treatment failure, also in a subgroup of patients with high-level fluoroquinolone-resistant tuberculosis. CONCLUSIONS Our results suggest that resistance to companion drugs in the shorter MDR-TB treatment regimen, except kanamycin resistance, is of no clinical importance as long as fluoroquinolone susceptibility is preserved. Hence, contrary to current WHO guidelines, exclusions to the standard regimen are justified only in the case of fluoroquinolone resistance. and possibly kanamycin resistance.
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Affiliation(s)
- Pauline Lempens
- Unit of Mycobacteriology, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium.
| | - Tom Decroo
- Unit of HIV/AIDS and Infectious Diseases, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | | | | | - Leen Rigouts
- Unit of Mycobacteriology, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Conor J Meehan
- Unit of Mycobacteriology, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | | | - Bouke C de Jong
- Unit of Mycobacteriology, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
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Rossetti ML, Almeida da Silva PE, Salvato RS, Reis AJ, Schiefelbein SH, von Groll A, Barcellos RB, Maschmann R, Esteves LS, Spies F, Trespach RR, Dalla Costa ER, Neubauer de Amorim HL. A highly rifampicin resistant Mycobacterium tuberculosis strain emerging in Southern Brazil. Tuberculosis (Edinb) 2020; 125:102015. [PMID: 33137698 DOI: 10.1016/j.tube.2020.102015] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 10/08/2020] [Accepted: 10/18/2020] [Indexed: 11/17/2022]
Abstract
Here we described phenotypical, molecular and epidemiological features of a highly rifampicin-resistant Mycobacterium tuberculosis strain emerging in Southern Brazil, that carries an uncommon insertion of 12 nucleotides at the codon 435 in the rpoB gene. Employing a whole-genome sequencing-based study on drug-resistant Mycobacterium tuberculosis strains, we identified this emergent strain in 16 (9.19%) from 174 rifampicin-resistant clinical strains, all of them belonging to LAM RD115 sublineage. Nine of these 16 strains were available to minimum inhibitory concentration determination and for all of them was found a high rifampicin-resistance level (≥to 32 mg/L). This high resistance level could be explained by structural changes into the RIF binding site of RNA polymerase caused by the insertions, and consequent low-affinity interaction with rifampicin complex confirmed through protein modeling and molecular docking simulations. Epidemiological investigation showed that most of the individuals (56.25%) infected by the studied strains were prison inmate individuals or that spent some time in prison. The phylogenomic approach revealed that strains carrying on insertion belonged to same genomic cluster, evidencing a communal transmission chain involving inmate individuals and community. We stress the importance of tuberculosis genomic surveillance and introduction of measures to interrupt Mycobacterium tuberculosis transmission chain in this region.
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Affiliation(s)
- Maria Lucia Rossetti
- Programa de Pós-Graduação em Biologia Celular e Molecular Aplicada a Saúde, Universidade Luterana do Brasil (ULBRA), Canoas, Rio Grande do Sul, Brazil; Programa de Pós-Graduação em Biologia Celular e Molecular, Centro de Biotecnologia, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Pedro Eduardo Almeida da Silva
- Núcleo de Pesquisa em Microbiologia Médica (NUPEMM), Faculdade de Medicina, Universidade Federal do Rio Grande, Rio Grande, Rio Grande do Sul, Brazil
| | - Richard Steiner Salvato
- Centro de Desenvolvimento Científico e Tecnológico (CDCT), Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; Programa de Pós-Graduação em Biologia Celular e Molecular, Centro de Biotecnologia, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil.
| | - Ana Júlia Reis
- Núcleo de Pesquisa em Microbiologia Médica (NUPEMM), Faculdade de Medicina, Universidade Federal do Rio Grande, Rio Grande, Rio Grande do Sul, Brazil
| | - Sun Hee Schiefelbein
- Programa de Pós-Graduação em Biologia Celular e Molecular Aplicada a Saúde, Universidade Luterana do Brasil (ULBRA), Canoas, Rio Grande do Sul, Brazil; Centro de Desenvolvimento Científico e Tecnológico (CDCT), Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Andrea von Groll
- Programa de Pós-Graduação em Biologia Celular e Molecular Aplicada a Saúde, Universidade Luterana do Brasil (ULBRA), Canoas, Rio Grande do Sul, Brazil
| | - Regina Bones Barcellos
- Centro de Desenvolvimento Científico e Tecnológico (CDCT), Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acadêmico de Tuberculose, Programa de Pós-Graduação em Clínica Médica, Rio de Janeiro, RJ, Brazil
| | - Raquel Maschmann
- Centro de Desenvolvimento Científico e Tecnológico (CDCT), Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Leonardo Souza Esteves
- Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acadêmico de Tuberculose, Programa de Pós-Graduação em Clínica Médica, Rio de Janeiro, RJ, Brazil
| | - Fernanda Spies
- Centro de Desenvolvimento Científico e Tecnológico (CDCT), Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Rubia Raubach Trespach
- Programa de Pós-Graduação em Biologia Celular e Molecular Aplicada a Saúde, Universidade Luterana do Brasil (ULBRA), Canoas, Rio Grande do Sul, Brazil
| | - Elis Regina Dalla Costa
- Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acadêmico de Tuberculose, Programa de Pós-Graduação em Clínica Médica, Rio de Janeiro, RJ, Brazil
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Tunstall T, Portelli S, Phelan J, Clark TG, Ascher DB, Furnham N. Combining structure and genomics to understand antimicrobial resistance. Comput Struct Biotechnol J 2020; 18:3377-3394. [PMID: 33294134 PMCID: PMC7683289 DOI: 10.1016/j.csbj.2020.10.017] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 10/15/2020] [Accepted: 10/17/2020] [Indexed: 02/07/2023] Open
Abstract
Antimicrobials against bacterial, viral and parasitic pathogens have transformed human and animal health. Nevertheless, their widespread use (and misuse) has led to the emergence of antimicrobial resistance (AMR) which poses a potentially catastrophic threat to public health and animal husbandry. There are several routes, both intrinsic and acquired, by which AMR can develop. One major route is through non-synonymous single nucleotide polymorphisms (nsSNPs) in coding regions. Large scale genomic studies using high-throughput sequencing data have provided powerful new ways to rapidly detect and respond to such genetic mutations linked to AMR. However, these studies are limited in their mechanistic insight. Computational tools can rapidly and inexpensively evaluate the effect of mutations on protein function and evolution. Subsequent insights can then inform experimental studies, and direct existing or new computational methods. Here we review a range of sequence and structure-based computational tools, focussing on tools successfully used to investigate mutational effect on drug targets in clinically important pathogens, particularly Mycobacterium tuberculosis. Combining genomic results with the biophysical effects of mutations can help reveal the molecular basis and consequences of resistance development. Furthermore, we summarise how the application of such a mechanistic understanding of drug resistance can be applied to limit the impact of AMR.
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Affiliation(s)
- Tanushree Tunstall
- Department of Infection Biology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
| | - Stephanie Portelli
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Australia
- Structural Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Australia
| | - Jody Phelan
- Department of Infection Biology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
| | - Taane G. Clark
- Department of Infection Biology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
| | - David B. Ascher
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Australia
- Structural Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Australia
| | - Nicholas Furnham
- Department of Infection Biology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
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112
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Portelli S, Myung Y, Furnham N, Vedithi SC, Pires DEV, Ascher DB. Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches. Sci Rep 2020; 10:18120. [PMID: 33093532 PMCID: PMC7581776 DOI: 10.1038/s41598-020-74648-y] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Accepted: 09/21/2020] [Indexed: 01/23/2023] Open
Abstract
Rifampicin resistance is a major therapeutic challenge, particularly in tuberculosis, leprosy, P. aeruginosa and S. aureus infections, where it develops via missense mutations in gene rpoB. Previously we have highlighted that these mutations reduce protein affinities within the RNA polymerase complex, subsequently reducing nucleic acid affinity. Here, we have used these insights to develop a computational rifampicin resistance predictor capable of identifying resistant mutations even outside the well-defined rifampicin resistance determining region (RRDR), using clinical M. tuberculosis sequencing information. Our tool successfully identified up to 90.9% of M. tuberculosis rpoB variants correctly, with sensitivity of 92.2%, specificity of 83.6% and MCC of 0.69, outperforming the current gold-standard GeneXpert-MTB/RIF. We show our model can be translated to other clinically relevant organisms: M. leprae, P. aeruginosa and S. aureus, despite weak sequence identity. Our method was implemented as an interactive tool, SUSPECT-RIF (StrUctural Susceptibility PrEdiCTion for RIFampicin), freely available at https://biosig.unimelb.edu.au/suspect_rif/ .
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Affiliation(s)
- Stephanie Portelli
- Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Victoria, 3010, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, 3004, VIC, Australia
| | - Yoochan Myung
- Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Victoria, 3010, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, 3004, VIC, Australia
| | - Nicholas Furnham
- Department of Infection Biology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | | | - Douglas E V Pires
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, 3004, VIC, Australia
- School of Computing and Information Systems, University of Melbourne, Victoria, 3010, Australia
| | - David B Ascher
- Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Victoria, 3010, Australia.
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, 3004, VIC, Australia.
- Department of Biochemistry, University of Cambridge, Cambridge, UK.
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113
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Jaillard M, Palmieri M, van Belkum A, Mahé P. Interpreting k-mer-based signatures for antibiotic resistance prediction. Gigascience 2020; 9:giaa110. [PMID: 33068113 PMCID: PMC7568433 DOI: 10.1093/gigascience/giaa110] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 07/23/2020] [Accepted: 09/16/2020] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Recent years have witnessed the development of several k-mer-based approaches aiming to predict phenotypic traits of bacteria on the basis of their whole-genome sequences. While often convincing in terms of predictive performance, the underlying models are in general not straightforward to interpret, the interplay between the actual genetic determinant and its translation as k-mers being generally hard to decipher. RESULTS We propose a simple and computationally efficient strategy allowing one to cope with the high correlation inherent to k-mer-based representations in supervised machine learning models, leading to concise and easily interpretable signatures. We demonstrate the benefit of this approach on the task of predicting the antibiotic resistance profile of a Klebsiella pneumoniae strain from its genome, where our method leads to signatures defined as weighted linear combinations of genetic elements that can easily be identified as genuine antibiotic resistance determinants, with state-of-the-art predictive performance. CONCLUSIONS By enhancing the interpretability of genomic k-mer-based antibiotic resistance prediction models, our approach improves their clinical utility and hence will facilitate their adoption in routine diagnostics by clinicians and microbiologists. While antibiotic resistance was the motivating application, the method is generic and can be transposed to any other bacterial trait. An R package implementing our method is available at https://gitlab.com/biomerieux-data-science/clustlasso.
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Affiliation(s)
| | | | | | - Pierre Mahé
- bioMérieux, Chemin de l'Orme, 69280 Marcy l'Etoile, France
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114
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Rivière E, Heupink TH, Ismail N, Dippenaar A, Clarke C, Abebe G, Heusden P, Warren R, Meehan CJ, Van Rie A. Capacity building for whole genome sequencing of Mycobacterium tuberculosis and bioinformatics in high TB burden countries. Brief Bioinform 2020; 22:5917386. [PMID: 33009560 PMCID: PMC8293823 DOI: 10.1093/bib/bbaa246] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 09/02/2020] [Accepted: 09/03/2020] [Indexed: 11/14/2022] Open
Abstract
Background Whole genome sequencing (WGS) is increasingly used for Mycobacterium tuberculosis (Mtb) research. Countries with the highest tuberculosis (TB) burden face important challenges to integrate WGS into surveillance and research. Methods We assessed the global status of Mtb WGS and developed a 3-week training course coupled with long-term mentoring and WGS infrastructure building. Training focused on genome sequencing, bioinformatics and development of a locally relevant WGS research project. The aim of the long-term mentoring was to support trainees in project implementation and funding acquisition. The focus of WGS infrastructure building was on the DNA extraction process and bioinformatics. Findings Compared to their TB burden, Asia and Africa are grossly underrepresented in Mtb WGS research. Challenges faced resulted in adaptations to the training, mentoring and infrastructure building. Out-of-date laptop hardware and operating systems were overcome by using online tools and a Galaxy WGS analysis pipeline. A case studies approach created a safe atmosphere for students to formulate and defend opinions. Because quality DNA extraction is paramount for WGS, a biosafety level 3 and general laboratory skill training session were added, use of commercial DNA extraction kits was introduced and a 2-week training in a highly equipped laboratory was combined with a 1-week training in the local setting. Interpretation By developing and sharing the components of and experiences with a sequencing and bioinformatics training program, we hope to stimulate capacity building programs for Mtb WGS and empower high-burden countries to play an important role in WGS-based TB surveillance and research.
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Affiliation(s)
- Emmanuel Rivière
- Corresponding author: Emmanuel Rivière, Faculty of Medicine and Health Sciences, Tuberculosis Omics Research Consortium, Global Health Institute, University of Antwerp Doornstraat 331, Wilrijk 2610, Belgium. Tel.: +32 32658970; E-mail:
| | | | | | | | | | - Gemeda Abebe
- Mycobacteriology Research Center in Jimma, Ethiopia
| | - Peter Heusden
- South African National Bioinformatics Institute (SANBI)
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115
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Jang JG, Chung JH. Diagnosis and treatment of multidrug-resistant tuberculosis. Yeungnam Univ J Med 2020; 37:277-285. [PMID: 32883054 PMCID: PMC7606956 DOI: 10.12701/yujm.2020.00626] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 08/21/2020] [Accepted: 08/25/2020] [Indexed: 01/05/2023] Open
Abstract
Tuberculosis (TB) is still a major health problem worldwide. Especially, multidrug-resistant TB (MDR-TB), which is defined as TB that shows resistance to both isoniazid and rifampicin, is a barrier in the treatment of TB. Globally, approximately 3.4% of new TB patients and 20% of the patients with a history of previous treatment for TB were diagnosed with MDR-TB. The treatment of MDR-TB requires medications for a long duration (up to 20-24 months) with less effective and toxic second-line drugs and has unfavorable outcomes. However, treatment outcomes are expected to improve due to the introduction of a new agent (bedaquiline), repurposed drugs (linezolid, clofazimine, and cycloserine), and technological advancement in rapid drug sensitivity testing. The World Health Organization (WHO) released a rapid communication in 2018, followed by consolidated guidelines for the treatment of MDR-TB in 2019 based on clinical trials and an individual patient data meta-analysis. In these guidelines, the WHO suggested reclassification of second-line anti-TB drugs and recommended oral treatment regimens that included the new and repurposed agents. The aims of this article are to review the treatment strategies of MDR-TB based on the 2019 WHO guidelines regarding the management of MDR-TB and the diagnostic techniques for detecting resistance, including phenotypic and molecular drug sensitivity tests.
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Affiliation(s)
- Jong Geol Jang
- Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
| | - Jin Hong Chung
- Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
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116
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Tarlykov P, Atavliyeva S, Alenova A, Ramankulov Y. Genomic analysis of Latin American-Mediterranean family of Mycobacterium tuberculosis clinical strains from Kazakhstan. Mem Inst Oswaldo Cruz 2020; 115:e200215. [PMID: 32965331 PMCID: PMC7508292 DOI: 10.1590/0074-02760200215] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 08/20/2020] [Indexed: 11/22/2022] Open
Abstract
The human-adapted strains of the Mycobacterium tuberculosis complex (MTBC) comprise seven phylogenetic lineages originally associated with their geographical distribution. Here, we report the genomes of three drug-resistant clinical isolates of the Latin American-Mediterranean (LAM) family collected in Kazakhstan. We utilised whole-genome sequencing to study the distribution and drug resistance of these isolates. Phylogenetic analysis grouped the genomes described in this study with the sequences from Russia, Uzbekistan, and Kazakhstan belonging to the LAM family. One isolate has acquired extensive drug resistance to seven antituberculosis drugs. Our results suggest at least two multi-drug resistant (MDR)/extensively drug-resistant (XDR)-associated genotypes of the LAM family circulate in Kazakhstan.
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Affiliation(s)
- Pavel Tarlykov
- National Center for Biotechnology, Nur-Sultan, Kazakhstan
| | | | - Arike Alenova
- National Scientific Center for Phthisiopulmonology, Almaty, Kazakhstan
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117
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Characterization of Mycobacterium tuberculosis var. africanum isolated from a patient with pulmonary tuberculosis in Brazil. INFECTION GENETICS AND EVOLUTION 2020; 85:104550. [PMID: 32920193 DOI: 10.1016/j.meegid.2020.104550] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Revised: 08/01/2020] [Accepted: 09/04/2020] [Indexed: 11/22/2022]
Abstract
Human tuberculosis (TB) is caused by members of the Mycobacterium tuberculosis complex (MTBC), including Mycobacterium tuberculosis var. tuberculosis (MTB) and Mycobacterium tuberculosis var. africanum (MAF). While MTB is isolated worldwide, MAF is almost completely restricted to the African continent, and despite the historical proximity between Brazil and Africa during the slave trade, no case of TB being caused by MAF has been reported in Brazil to date. We hereby describe the first case of TB caused by MAF in Brazil comparing its genome against the published ones. A female patient who had never visited Africa presented with clinical symptoms typical of pulmonary TB. Based on 16S rRNA gene sequencing, the cultured isolate was identified as belonging to MTBC and partial sequence of the hsp65 gene was identical to that of MAF. This was confirmed by genotyping based on detection of Single Nucleotide Polymorphism (SNP), Region of Difference (RD) and spoligotyping. The isolate presented the Shared International Typing (SIT) 181. In the whole-genome comparison against MAF genomes available on published EMBL-EBI European Nucleotide Archive (ENA), the Brazilian genome (MAFBRA00707) was identified as belonging to Lineage 6 and clustered with isolates from The Gambia. This is the first report of the isolation of MAF from a patient from Brazil, without evidence of having any contact with an African index case.
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Theron G, Limberis J, Venter R, Smith L, Pietersen E, Esmail A, Calligaro G, Te Riele J, de Kock M, van Helden P, Gumbo T, Clark TG, Fennelly K, Warren R, Dheda K. Bacterial and host determinants of cough aerosol culture positivity in patients with drug-resistant versus drug-susceptible tuberculosis. Nat Med 2020; 26:1435-1443. [PMID: 32601338 PMCID: PMC8353872 DOI: 10.1038/s41591-020-0940-2] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 05/13/2020] [Indexed: 12/27/2022]
Abstract
A burgeoning epidemic of drug-resistant tuberculosis (TB) threatens to derail global control efforts. Although the mechanisms remain poorly clarified, drug-resistant strains are widely believed to be less infectious than drug-susceptible strains. Consequently, we hypothesized that lower proportions of patients with drug-resistant TB would have culturable Mycobacterium tuberculosis from respirable, cough-generated aerosols compared to patients with drug-susceptible TB, and that multiple factors, including mycobacterial genomic variation, would predict culturable cough aerosol production. We enumerated the colony forming units in aerosols (≤10 µm) from 452 patients with TB (227 with drug resistance), compared clinical characteristics, and performed mycobacterial whole-genome sequencing, dormancy phenotyping and drug-susceptibility analyses on M. tuberculosis from sputum. After considering treatment duration, we found that almost half of the patients with drug-resistant TB were cough aerosol culture-positive. Surprisingly, neither mycobacterial genomic variants, lineage, nor dormancy status predicted cough aerosol culture positivity. However, mycobacterial sputum bacillary load and clinical characteristics, including a lower symptom score and stronger cough, were strongly predictive, thereby supporting targeted transmission-limiting interventions. Effective treatment largely abrogated cough aerosol culture positivity; however, this was not always rapid. These data question current paradigms, inform public health strategies and suggest the need to redirect TB transmission-associated research efforts toward host-pathogen interactions.
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Affiliation(s)
- Grant Theron
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute & South African MRC/UCT Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research and South African Medical Research Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Jason Limberis
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute & South African MRC/UCT Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
| | - Rouxjeane Venter
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research and South African Medical Research Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Liezel Smith
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute & South African MRC/UCT Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research and South African Medical Research Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Elize Pietersen
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute & South African MRC/UCT Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
| | - Aliasgar Esmail
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute & South African MRC/UCT Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
| | - Greg Calligaro
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute & South African MRC/UCT Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
| | | | - Marianna de Kock
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research and South African Medical Research Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Paul van Helden
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research and South African Medical Research Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Tawanda Gumbo
- Center for Infectious Diseases Research and Experimental Therapeutics, Baylor University Medical Center, Dallas, TX, USA
| | - Taane G Clark
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
- Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Kevin Fennelly
- Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Robin Warren
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research and South African Medical Research Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Keertan Dheda
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute & South African MRC/UCT Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa.
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.
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119
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He Y, Gong Z, Zhao X, Zhang D, Zhang Z. Comprehensive Determination of Mycobacterium tuberculosis and Nontuberculous Mycobacteria From Targeted Capture Sequencing. Front Cell Infect Microbiol 2020; 10:449. [PMID: 32984073 PMCID: PMC7491257 DOI: 10.3389/fcimb.2020.00449] [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: 02/06/2020] [Accepted: 07/21/2020] [Indexed: 12/27/2022] Open
Abstract
Infection of Mycobacterium tuberculosis (MTB) and nontuberculous mycobacteria (NTM) challenges effective pulmonary infectious disease control. Current phenotypic and molecular assays could not comprehensively and accurately diagnose MTB, NTM, and drug resistance. Next-generation sequencing allows an “all-in-one” approach providing results on expected drug susceptibility testing (DST) and the genotype of NTM strains. In this study, targeted capture sequencing was used to analyze the genetic backgrounds of 4 MTB strains and 32 NTM pathogenic strains in 30 clinical samples, including 14 sputum specimens and 16 bronchoalveolar lavage fluid samples. Through comparing with other TB diagnostic tests, we proved that targeted capture sequencing could be used as a highly sensitive (91.3%) and accurate (83.3%) method to diagnose TB, as well as MGIT 960. Also, we identified 7 NTM strains in 11 patients; among them, seven patients were MTB/NTM co-affected, which indicated that it was a meaningful tool for the diagnosis and treatment of NTM infection diseases in clinic. However, based on a drug-resistant mutation library (1,325 drug resistance loci), only 9 drug resistance strains and 22 drug resistance loci were discovered, having considerable discordance with the drug-resistant results of MGIT 960. Our finding indicated that targeted capture sequencing approach was applicable for the comprehensive and accurate diagnosis of MTB and NTM. However, from data presented here, the DST results identified by next-generation sequencing (NGS) showed a relatively low consistency with MGIT 960, especially in sputum samples. Further work should be done to explore the reasons for low drug-resistance detection rate of NGS.
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Affiliation(s)
- Ya He
- Clinic and Research Center of Tuberculosis, Shanghai Key Lab of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Ziying Gong
- Shanghai Yunying Medical Technology Co., Ltd., Shanghai, China.,Jiaxing Yunying Medical Inspection Co., Ltd., Jiaxing, China
| | - Xiaokai Zhao
- Shanghai Yunying Medical Technology Co., Ltd., Shanghai, China.,Jiaxing Yunying Medical Inspection Co., Ltd., Jiaxing, China
| | - Daoyun Zhang
- Shanghai Yunying Medical Technology Co., Ltd., Shanghai, China.,Jiaxing Yunying Medical Inspection Co., Ltd., Jiaxing, China
| | - Zhongshun Zhang
- Clinic and Research Center of Tuberculosis, Shanghai Key Lab of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
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120
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Whole-Genome Sequencing of a Mycobacterium tuberculosis Strain Belonging to Lineage 1 (Indo-Oceanic) and the East African Indian Spoligotype, Isolated in Jazan, Saudi Arabia. Microbiol Resour Announc 2020; 9:9/33/e00717-20. [PMID: 32817153 PMCID: PMC7427191 DOI: 10.1128/mra.00717-20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
We describe here the draft genome sequence of AY1MRC, a Mycobacterium tuberculosis strain belonging to lineage 1 (Indo-Oceanic) and the East African Indian spoligotype, isolated from a patient with tuberculosis in Jazan, Saudi Arabia.
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121
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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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122
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Dusthackeer A, Saadhali SA, Thangam M, Hassan S, Balasubramanian M, Balasubramanian A, Ramachandran G, Kumar AKH, Thiruvenkadam K, Shanmugam G, Nirmal CR, Rajadas SE, Mohanvel SK, Mondal R. Wild-Type MIC Distribution for Re-evaluating the Critical Concentration of Anti-TB Drugs and Pharmacodynamics Among Tuberculosis Patients From South India. Front Microbiol 2020; 11:1182. [PMID: 32695072 PMCID: PMC7338667 DOI: 10.3389/fmicb.2020.01182] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 05/08/2020] [Indexed: 11/13/2022] Open
Abstract
The World Health Organization (WHO) has developed specific guidelines for critical concentrations (CCs) of antibiotics used for tuberculosis (TB) treatment, which is universally followed for drug susceptibility testing (DST) of clinical specimens. However, the CC of drugs can differ significantly among the mycobacterial species based on the population, geographic location, and the prevalence of the infecting strain in a particular area. The association between CC and the minimal inhibitory concentration (MIC) of anti-TB drugs is poorly understood. In this study, we assessed the MICs of anti-TB drugs, including isoniazid (INH), rifampicin (RMP), moxifloxacin (MXF), ethambutol (ETH), and p-aminosalicylic acid (PAS) on drug-sensitive Mtb isolates from pulmonary TB patients in South India. The MIC assays performed using solid- and liquid-growth media showed changes in the CC of a few of the tested antibiotics compared with the WHO-recommended levels. Our observation suggests that the WHO guidelines could potentially lead to overdiagnosis of drug-resistant cases, which can result in inappropriate therapeutic decisions. To evaluate the correlation between drug-resistance and CC, we performed the whole-genome sequencing for 16 mycobacterial isolates, including two wild-type and 14 resistant isolates. Our results showed that two of the isolates belonged to the W-Beijing lineage, while the rest were of the East-African-Indian type. We identified a total of 74 mutations, including five novel mutations, which are known to be associated with resistance to anti-TB drugs in these isolates. In our previous study, we determined the serum levels of INH and RMP among the same patients recruited in the current study and estimated the MICs of the corresponding infected isolates in these cases. Using these data and the CCs for INH and RMP from the present study, we performed pharmacodynamics (PD) evaluation. The results show that the PD of RMP was subtherapeutic. Together, these observations emphasize the need for optimizing the drug dosage based on the PD of large-scale studies conducted in different geographical settings.
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Affiliation(s)
- Azger Dusthackeer
- Department of Bacteriology, National Institute for Research in Tuberculosis, Chennai, India
| | - Shainaba A Saadhali
- Department of Bacteriology, National Institute for Research in Tuberculosis, Chennai, India
| | | | - Sameer Hassan
- Division of Neurogeriatrics, Karolinska Institutet, Solna, Sweden
| | | | | | - Geetha Ramachandran
- Department of Biochemistry, National Institute for Research in Tuberculosis, Chennai, India
| | - A K Hemanth Kumar
- Department of Biochemistry, National Institute for Research in Tuberculosis, Chennai, India
| | - Kannan Thiruvenkadam
- Department of Epidemiology, National Institute for Research in Tuberculosis, Chennai, India
| | - Govindarajan Shanmugam
- Department of Bacteriology, National Institute for Research in Tuberculosis, Chennai, India
| | | | - Sam Ebenezer Rajadas
- Department of Bacteriology, National Institute for Research in Tuberculosis, Chennai, India
| | | | - Rajesh Mondal
- Department of Bacteriology, National Institute for Research in Tuberculosis, Chennai, India
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123
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Cresswell FV, Davis AG, Sharma K, Basu Roy R, Ganiem AR, Kagimu E, Solomons R, Wilkinson RJ, Bahr NC, Thuong NTT. Recent Developments in Tuberculous Meningitis Pathogenesis and Diagnostics. Wellcome Open Res 2020; 4:164. [PMID: 33364436 PMCID: PMC7739117 DOI: 10.12688/wellcomeopenres.15506.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/24/2020] [Indexed: 12/15/2022] Open
Abstract
The pathogenesis of Tuberculous meningitis (TBM) is poorly understood, but contemporary molecular biology technologies have allowed for recent improvements in our understanding of TBM. For instance, neutrophils appear to play a significant role in the immunopathogenesis of TBM, and either a paucity or an excess of inflammation can be detrimental in TBM. Further, severity of HIV-associated immunosuppression is an important determinant of inflammatory response; patients with the advanced immunosuppression (CD4+ T-cell count of <150 cells/μL) having higher CSF neutrophils, greater CSF cytokine concentrations and higher mortality than those with CD4+ T-cell counts > 150 cells/μL. Host genetics may also influence outcomes with LT4AH genotype predicting inflammatory phenotype, steroid responsiveness and survival in Vietnamese adults with TBM. Whist in Indonesia, CSF tryptophan level was a predictor of survival, suggesting tryptophan metabolism may be important in TBM pathogenesis. These varying responses mean that we must consider whether a "one-size-fits-all" approach to anti-bacillary or immunomodulatory treatment in TBM is truly the best way forward. Of course, to allow for proper treatment, early and rapid diagnosis of TBM must occur. Diagnosis has always been a challenge but the field of TB diagnosis is evolving, with sensitivities of at least 70% now possible in less than two hours with GeneXpert MTB/Rif Ultra. In addition, advanced molecular techniques such as CRISPR-MTB and metagenomic next generation sequencing may hold promise for TBM diagnosis. Host-based biomarkers and signatures are being further evaluated in childhood and adult TBM as adjunctive biomarkers as even with improved molecular assays, cases are still missed. A better grasp of host and pathogen behaviour may lead to improved diagnostics, targeted immunotherapy, and possibly biomarker-based, patient-specific treatment regimens.
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Affiliation(s)
- Fiona V Cresswell
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
- Research Department, Infectious Diseases Institute, Kampala, PO Box 22418, Uganda
- MRC-UVRI-London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda
| | - Angharad G. Davis
- University College London, London, WC1E6BT, UK
- Francis Crick Institute, London, NW1 1AT, UK
- Department of Medicine, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, 7925, South Africa
| | - Kusum Sharma
- Department of Medical Microbiology, Post-graduate Department of Medical Education and Research, Chandigahr, India
| | - Robindra Basu Roy
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
| | - Ahmad Rizal Ganiem
- Department of Neurology, Hasan Sadikin Hospital, Faculty of Medicine. Universitas Padjadjaran, Bandung, Indonesia
| | - Enock Kagimu
- Research Department, Infectious Diseases Institute, Kampala, PO Box 22418, Uganda
| | - Regan Solomons
- Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, South Africa
| | - Robert J. Wilkinson
- Francis Crick Institute, London, NW1 1AT, UK
- Department of Medicine, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, 7925, South Africa
- Department of Infectious Diseases, Imperial College, London, W2 1PG, UK
| | - Nathan C Bahr
- Division of Infectious Diseases. Department of Medicine., University of Kansas, Kansas City, USA
| | | | - Tuberculous Meningitis International Research Consortium
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
- Research Department, Infectious Diseases Institute, Kampala, PO Box 22418, Uganda
- MRC-UVRI-London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda
- University College London, London, WC1E6BT, UK
- Francis Crick Institute, London, NW1 1AT, UK
- Department of Medicine, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, 7925, South Africa
- Department of Medical Microbiology, Post-graduate Department of Medical Education and Research, Chandigahr, India
- Department of Neurology, Hasan Sadikin Hospital, Faculty of Medicine. Universitas Padjadjaran, Bandung, Indonesia
- Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, South Africa
- Department of Infectious Diseases, Imperial College, London, W2 1PG, UK
- Division of Infectious Diseases. Department of Medicine., University of Kansas, Kansas City, USA
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
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124
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Use of whole-genome sequencing to predict Mycobacterium tuberculosis drug resistance in Shanghai, China. Int J Infect Dis 2020; 96:48-53. [DOI: 10.1016/j.ijid.2020.04.039] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 04/14/2020] [Accepted: 04/17/2020] [Indexed: 11/19/2022] Open
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125
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Kone B, Somboro AM, Holl JL, Baya B, Togo AACG, Sarro YDS, Diarra B, Kodio O, Murphy RL, Bishai W, Maiga M, Doumbia S. Exploring the usefulness of molecular epidemiology of tuberculosis in Africa: a systematic review. INTERNATIONAL JOURNAL OF MOLECULAR EPIDEMIOLOGY AND GENETICS 2020; 11:1-15. [PMID: 32714498 PMCID: PMC7373718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 06/05/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Tuberculosis (TB) is caused by Mycobacterium tuberculosis complex (MTBC) and remains a serious global public health threat, especially in resource-limited settings such as the African region. Recent developments in molecular epidemiology tools have significantly improved our understanding of TB transmission patterns and revealed the high genetic diversity of TB isolates across geographical entities in Africa. This study reports the results of a systematic review of current knowledge about MTBC strain diversity and geographical distribution in African regions. METHODS Search tools (PubMed, Embase, Popline, OVID and Africa Wide Information) were employed to identify the relevant literature about prevalence, strain diversity, and geographic distribution of MTBC infection in Africa. RESULTS A total of 59 articles from 739 citations met our inclusion criteria. Most articles reported about patients with presumptive pulmonary TB (73%), fewer reports were on retreatment and treatment failure cases (12%), and presumptive drug resistance cases (3%). Spoligotyping was the most used, alone in 21 studies and in parallel with either the Mycobacterial Interspersed Repetitive Units Variable Number of Tandem Repeats or the Restriction Fragment Length Polymorphism. Various TB lineages were observed across the African continent, with the originally European lineage 4 spotted in all countries studied. CONCLUSION TB molecular epidemiology tools have substantially improved our understanding of the MTBC circulating isolates, their evolution, and diversity in this highly endemic region of Africa. We found that only TB lineage 4 is present throughout all the continent and the clusters identified provides an extended insight into the disease transmission dynamics.
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Affiliation(s)
- Bourahima Kone
- University Clinical Research Center (UCRC)-SEREFO, University of Sciences, Techniques and Technologies of Bamako (USTTB)Bamako, Mali
| | - Anou M Somboro
- University Clinical Research Center (UCRC)-SEREFO, University of Sciences, Techniques and Technologies of Bamako (USTTB)Bamako, Mali
- Medical Biochemistry, School of Laboratory Medicine and Medical Sciences, University of KwaZulu-NatalDurban, South Africa
| | | | - Bocar Baya
- University Clinical Research Center (UCRC)-SEREFO, University of Sciences, Techniques and Technologies of Bamako (USTTB)Bamako, Mali
| | - Antieme ACG Togo
- University Clinical Research Center (UCRC)-SEREFO, University of Sciences, Techniques and Technologies of Bamako (USTTB)Bamako, Mali
| | - Yeya Dit Sadio Sarro
- University Clinical Research Center (UCRC)-SEREFO, University of Sciences, Techniques and Technologies of Bamako (USTTB)Bamako, Mali
| | - Bassirou Diarra
- University Clinical Research Center (UCRC)-SEREFO, University of Sciences, Techniques and Technologies of Bamako (USTTB)Bamako, Mali
| | - Ousmane Kodio
- University Clinical Research Center (UCRC)-SEREFO, University of Sciences, Techniques and Technologies of Bamako (USTTB)Bamako, Mali
| | - Robert L Murphy
- Institute for Global Health, Northwestern UniversityChicago, Illinois, USA
| | - William Bishai
- Center for TB Research, Johns Hopkins UniversityBaltimore, MD, USA
| | - Mamoudou Maiga
- University Clinical Research Center (UCRC)-SEREFO, University of Sciences, Techniques and Technologies of Bamako (USTTB)Bamako, Mali
- Institute for Global Health, Northwestern UniversityChicago, Illinois, USA
| | - Seydou Doumbia
- University Clinical Research Center (UCRC)-SEREFO, University of Sciences, Techniques and Technologies of Bamako (USTTB)Bamako, Mali
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126
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Dohál M, Porvazník I, Pršo K, Rasmussen EM, Solovič I, Mokrý J. Whole-genome sequencing and Mycobacterium tuberculosis: Challenges in sample preparation and sequencing data analysis. Tuberculosis (Edinb) 2020; 123:101946. [PMID: 32741530 DOI: 10.1016/j.tube.2020.101946] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 04/29/2020] [Accepted: 04/30/2020] [Indexed: 12/26/2022]
Abstract
The numbers of patients with tuberculosis (TB) caused by resistant strains are still alarming. Therefore, it is necessary to determine resistance more quickly and precisely, than it is with the currently used phenotypic and genotypic methods. In recent years, technological advances have been made and the whole-genome sequencing (WGS) method has been introduced as a part of routine diagnostics in clinical laboratories. Comparing a wide range of mycobacterial genomic variations with a reference genome leads to a consistent evaluation of molecular-epidemiology and resistance of Mycobacterium tuberculosis (M. tuberculosis) to a wide range of anti-TB drugs. The quality of the obtained sequencing data is closely related to the type of sample and the method used for DNA extraction and sequencing library preparation. Moreover, the correct interpretation of results is also influenced by a bioinformatic data processing. A large number of bioinformatics pipelines are currently available, the sensitivity of which varies due to the different sizes of databases containing relevant mutations. This review focuses on the individual steps included in the sequencing workflow and factors that may affect the interpretation of final results.
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Affiliation(s)
- Matúš Dohál
- Department of Pharmacology and Biomedical Center Martin, Jessenius Faculty of Medicine, Comenius University, Martin, Slovakia.
| | - Igor Porvazník
- National Institute of Tuberculosis, Lung Diseases and Thoracic Surgery, Vyšné Hágy, Slovakia; Faculty of Health, Catholic University, Ružomberok, Slovakia
| | - Kristián Pršo
- Department of Pharmacology and Biomedical Center Martin, Jessenius Faculty of Medicine, Comenius University, Martin, Slovakia
| | - Erik Michael Rasmussen
- International Reference Laboratory of Mycobacteriology, Statens Serum Institut, Copenhagen, Denmark
| | - Ivan Solovič
- National Institute of Tuberculosis, Lung Diseases and Thoracic Surgery, Vyšné Hágy, Slovakia
| | - Juraj Mokrý
- Department of Pharmacology and Biomedical Center Martin, Jessenius Faculty of Medicine, Comenius University, Martin, Slovakia
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127
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Ghosh A, N S, Saha S. Survey of drug resistance associated gene mutations in Mycobacterium tuberculosis, ESKAPE and other bacterial species. Sci Rep 2020; 10:8957. [PMID: 32488120 PMCID: PMC7265455 DOI: 10.1038/s41598-020-65766-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Accepted: 04/09/2020] [Indexed: 02/08/2023] Open
Abstract
Tuberculosis treatment includes broad-spectrum antibiotics such as rifampicin, streptomycin and fluoroquinolones, which are also used against other pathogenic bacteria. We developed Drug Resistance Associated Genes database (DRAGdb), a manually curated repository of mutational data of drug resistance associated genes (DRAGs) across ESKAPE (i.e. Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.) pathogens, and other bacteria with a special focus on Mycobacterium tuberculosis (MTB). Analysis of mutations in drug-resistant genes listed in DRAGdb suggested both homoplasy and pleiotropy to be associated with resistance. Homoplasy was observed in six genes namely gidB, gyrA, gyrB, rpoB, rpsL and rrs. For these genes, drug resistance-associated mutations at codon level were conserved in MTB, ESKAPE and many other bacteria. Pleiotropy was exemplified by a single nucleotide mutation that was associated with resistance to amikacin, gentamycin, rifampicin and vancomycin in Staphylococcus aureus. DRAGdb data also revealed that mutations in some genes such as pncA, inhA, katG and embA,B,C were specific to Mycobacterium species. For inhA and pncA, the mutations in the promoter region along with those in coding regions were associated with resistance to isoniazid and pyrazinamide respectively. In summary, the DRAGdb database is a compilation of all the major MTB drug resistance genes across bacterial species, which allows identification of homoplasy and pleiotropy phenomena of DRAGs.
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Affiliation(s)
- Abhirupa Ghosh
- Division of Bioinformatics, Bose Institute, Kolkata, India
| | - Saran N
- Division of Bioinformatics, Bose Institute, Kolkata, India
| | - Sudipto Saha
- Division of Bioinformatics, Bose Institute, Kolkata, India.
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128
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Tang J, Liu Z, Shi Y, Zhan L, Qin C. Whole Genome and Transcriptome Sequencing of Two Multi-Drug Resistant Mycobacterium tuberculosis Strains to Facilitate Illustrating Their Virulence in vivo. Front Cell Infect Microbiol 2020; 10:219. [PMID: 32500039 PMCID: PMC7242654 DOI: 10.3389/fcimb.2020.00219] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 04/21/2020] [Indexed: 11/29/2022] Open
Abstract
Mycobacterium tuberculosis clinical strains usually possess traits different from the laboratory strains like H37Rv, especially those clinical drug resistant strains. With whole genome and transcriptome sequencing, we depicted the feature of two multi-drug resistant Mtb strains in resistance and virulence. Compared with H37Rv, the differential expressed genes (DEGs) of the MDR strains showed featured enrichment in arginine biosynthesis, fatty acid biosynthesis, and metabolism pathway. In the subset of virulence genes, the overlapping DEGs of the MDR strains exhibited downregulation of the cluster in type VII secretion system. In the mice experiment, the MDR strains showed attenuated but distinct virulence, both in survival rate and pathology. Taken together, the whole genome and transcriptome analysis could help understand the unique feature of the MDR strains both in resistance and virulence.
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Affiliation(s)
- Jun Tang
- Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences (CAMS), Comparative Medicine Center, Peking Union Medical College (PUMC), Beijing, China.,NHC Key Laboratory of Human Disease Comparative Medicine, Beijing, China.,Beijing Key Laboratory for Animal Models of Emerging and Reemerging Infectious, Beijing, China.,Beijing Engineering Research Center for Experimental Animal Models of Human Critical Diseases, Beijing, China.,Tuberculosis Center, Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Zhihao Liu
- Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences (CAMS), Comparative Medicine Center, Peking Union Medical College (PUMC), Beijing, China.,NHC Key Laboratory of Human Disease Comparative Medicine, Beijing, China.,Beijing Key Laboratory for Animal Models of Emerging and Reemerging Infectious, Beijing, China.,Beijing Engineering Research Center for Experimental Animal Models of Human Critical Diseases, Beijing, China.,Tuberculosis Center, Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Ya'nan Shi
- Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences (CAMS), Comparative Medicine Center, Peking Union Medical College (PUMC), Beijing, China.,NHC Key Laboratory of Human Disease Comparative Medicine, Beijing, China.,Beijing Key Laboratory for Animal Models of Emerging and Reemerging Infectious, Beijing, China.,Beijing Engineering Research Center for Experimental Animal Models of Human Critical Diseases, Beijing, China.,Tuberculosis Center, Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Lingjun Zhan
- Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences (CAMS), Comparative Medicine Center, Peking Union Medical College (PUMC), Beijing, China.,NHC Key Laboratory of Human Disease Comparative Medicine, Beijing, China.,Beijing Key Laboratory for Animal Models of Emerging and Reemerging Infectious, Beijing, China.,Beijing Engineering Research Center for Experimental Animal Models of Human Critical Diseases, Beijing, China.,Tuberculosis Center, Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Chuan Qin
- Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences (CAMS), Comparative Medicine Center, Peking Union Medical College (PUMC), Beijing, China.,NHC Key Laboratory of Human Disease Comparative Medicine, Beijing, China.,Beijing Key Laboratory for Animal Models of Emerging and Reemerging Infectious, Beijing, China.,Beijing Engineering Research Center for Experimental Animal Models of Human Critical Diseases, Beijing, China.,Tuberculosis Center, Chinese Academy of Medical Sciences (CAMS), Beijing, China
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Detection of low-frequency resistance-mediating SNPs in next-generation sequencing data of Mycobacterium tuberculosis complex strains with binoSNP. Sci Rep 2020; 10:7874. [PMID: 32398743 PMCID: PMC7217866 DOI: 10.1038/s41598-020-64708-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Accepted: 04/15/2020] [Indexed: 12/30/2022] Open
Abstract
Accurate drug resistance detection is key for guiding effective tuberculosis treatment. While genotypic resistance can be rapidly detected by molecular methods, their application is challenged by mixed mycobacterial populations comprising both susceptible and resistant cells (heteroresistance). For this, next-generation sequencing (NGS) based approaches promise the determination of variants even at low frequencies. However, accurate methods for a valid detection of low-frequency variants in NGS data are currently lacking. To tackle this problem, we developed the variant detection tool binoSNP which allows the determination of low-frequency single nucleotide polymorphisms (SNPs) in NGS datasets from Mycobacterium tuberculosis complex (MTBC) strains. By taking a reference-mapped file as input, binoSNP evaluates each genomic position of interest using a binomial test procedure. binoSNP was validated using in-silico, in-vitro, and serial patient isolates datasets comprising varying genomic coverage depths (100-500×) and SNP allele frequencies (1-30%). Overall, the detection limit for low-frequency SNPs depends on the combination of coverage depth and allele frequency of the resistance-associated mutation. binoSNP allows for valid detection of resistance associated SNPs at a 1% frequency with a coverage ≥400×. In conclusion, binoSNP provides a valid approach to detect low-frequency resistance-mediating SNPs in NGS data from clinical MTBC strains. It can be implemented in automated, end-user friendly analysis tools for NGS data and is a step forward towards individualized TB therapy.
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130
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Genome sequence analysis of multidrug-resistant Mycobacterium tuberculosis from Malaysia. Sci Data 2020; 7:135. [PMID: 32371951 PMCID: PMC7200664 DOI: 10.1038/s41597-020-0475-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 04/02/2020] [Indexed: 11/24/2022] Open
Abstract
Mycobacterium tuberculosis (MTB) is commonly used as a model to study pathogenicity and multiple drug resistance in bacteria. These MTB characteristics are highly dependent on the evolution and phylogeography of the bacterium. In this paper, we describe 15 new genomes of multidrug-resistant MTB (MDRTB) from Malaysia. The assessments and annotations on the genome assemblies suggest that strain differences are due to lineages and horizontal gene transfer during the course of evolution. The genomes show mutations listed in current drug resistance databases and global MTB collections. This genome data will augment existing information available for comparative genomic studies to understand MTB drug resistance mechanisms and evolution. Measurement(s) | DNA • genome • sequence_assembly • sequence feature annotation | Technology Type(s) | DNA sequencing • sequence assembly process • sequence annotation | Factor Type(s) | strain | Sample Characteristic - Organism | Mycobacterium tuberculosis | Sample Characteristic - Location | Malaysia |
Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12130008
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131
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Kouchaki S, Yang Y, Lachapelle A, Walker TM, Walker AS, Peto TEA, Crook DW, Clifton DA. Multi-Label Random Forest Model for Tuberculosis Drug Resistance Classification and Mutation Ranking. Front Microbiol 2020; 11:667. [PMID: 32390972 PMCID: PMC7188832 DOI: 10.3389/fmicb.2020.00667] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 03/24/2020] [Indexed: 12/12/2022] Open
Abstract
Resistance prediction and mutation ranking are important tasks in the analysis of Tuberculosis sequence data. Due to standard regimens for the use of first-line antibiotics, resistance co-occurrence, in which samples are resistant to multiple drugs, is common. Analysing all drugs simultaneously should therefore enable patterns reflecting resistance co-occurrence to be exploited for resistance prediction. Here, multi-label random forest (MLRF) models are compared with single-label random forest (SLRF) for both predicting phenotypic resistance from whole genome sequences and identifying important mutations for better prediction of four first-line drugs in a dataset of 13402 Mycobacterium tuberculosis isolates. Results confirmed that MLRFs can improve performance compared to conventional clinical methods (by 18.10%) and SLRFs (by 0.91%). In addition, we identified a list of candidate mutations that are important for resistance prediction or that are related to resistance co-occurrence. Moreover, we found that retraining our analysis to a subset of top-ranked mutations was sufficient to achieve satisfactory performance. The source code can be found at http://www.robots.ox.ac.uk/~davidc/code.php.
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Affiliation(s)
- Samaneh Kouchaki
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Yang Yang
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
- Oxford-Suzhou Centre for Advanced Research, Suzhou, China
| | - Alexander Lachapelle
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Timothy M. Walker
- Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- National Institute of Health Research Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, United Kingdom
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - A. Sarah Walker
- Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- National Institute of Health Research Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, United Kingdom
- NIHR Biomedical Research Centre, Oxford, United Kingdom
| | | | - Timothy E. A. Peto
- Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- National Institute of Health Research Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, United Kingdom
- NIHR Biomedical Research Centre, Oxford, United Kingdom
| | - Derrick W. Crook
- Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- National Institute of Health Research Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, United Kingdom
- NIHR Biomedical Research Centre, Oxford, United Kingdom
| | - David A. Clifton
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
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132
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KatG as Counterselection Marker for Nontuberculous Mycobacteria. Antimicrob Agents Chemother 2020; 64:64/5/e02508-19. [PMID: 32317266 DOI: 10.1128/aac.02508-19] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
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133
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Acharya B, Acharya A, Gautam S, Ghimire SP, Mishra G, Parajuli N, Sapkota B. Advances in diagnosis of Tuberculosis: an update into molecular diagnosis of Mycobacterium tuberculosis. Mol Biol Rep 2020; 47:4065-4075. [DOI: 10.1007/s11033-020-05413-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 03/28/2020] [Indexed: 01/02/2023]
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134
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Bitar I, Medvecky M, Amlerova J, Papagiannitsis CC, Hrabak J. Frequency of mutations associated with resistance to first- and second-line drugs in multidrug-resistant Mycobacterium tuberculosis isolates. J Glob Antimicrob Resist 2020; 22:275-282. [PMID: 32247078 DOI: 10.1016/j.jgar.2020.03.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 02/27/2020] [Accepted: 03/14/2020] [Indexed: 01/19/2023] Open
Abstract
INTRODUCTION Tuberculosis is considered one of the most fatal diseases worldwide, with an estimation of 10.1 million cases. In this study, whole-genome sequencing was used to determine the genomic characterisation of 40 Mycobacterium tuberculosis isolates from patients with different nationalities hospitalised in the Czech Republic. MATERIALS AND METHODS Susceptibility testing for first-line drugs was performed. DNA was sequenced using the Illumina MiSeq platform. Spoligotype single-nucleotide polymorphisms and mutations in antibiotic-resistant genes were detected, and phylogenetic analysis was performed. RESULTS Samples showing phenotypic resistance to at least one drug were 12 to streptomycin, 11 to isoniazid, 7 to rifampicin, 6 to ethambutol and 5 to pyrazinamide. Phenotypic and genotypic profiles did not match in all cases, suggesting the presence of a novel mutation in some cases and a low expression of resistant genes in others. The presented phylogeny enables the correct assignation of M. tuberculosis lineages and sublineages. Our results suggest that the most dominant lineage in our samples was lineage 4 (33/40). CONCLUSION To our knowledge, this is the first study using this approach to be done in the Czech Republic. Lineage 4 was the predominant lineage identified among our samples. Nevertheless, the dominance of Lineage 4 along with other lineages suggests that infections can originate from different sources.
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Affiliation(s)
- Ibrahim Bitar
- Department of Microbiology, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic; Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic.
| | - Matej Medvecky
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic; CEITEC VFU, University of Veterinary and Pharmaceutical Sciences Brno, Brno, Czech Republic
| | - Jana Amlerova
- Department of Microbiology, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic; Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic
| | - Costas C Papagiannitsis
- Department of Microbiology, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic; Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic
| | - Jaroslav Hrabak
- Department of Microbiology, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic; Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic
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135
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Cui ZJ, Zhang WT, Zhu Q, Zhang QY, Zhang HY. Using a Heat Diffusion Model to Detect Potential Drug Resistance Genes of Mycobacterium tuberculosis. Protein Pept Lett 2020; 27:711-717. [PMID: 32167422 DOI: 10.2174/0929866527666200313113157] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 12/01/2019] [Accepted: 12/21/2019] [Indexed: 01/01/2023]
Abstract
BACKGROUND Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is one of the oldest known and most dangerous diseases. Although the spread of TB was controlled in the early 20th century using antibiotics and vaccines, TB has again become a threat because of increased drug resistance. There is still a lack of effective treatment regimens for a person who is already infected with multidrug-resistant Mtb (MDR-Mtb) or extensively drug-resistant Mtb (XDRMtb). In the past decades, many research groups have explored the drug resistance profiles of Mtb based on sequence data by GWAS, which identified some mutations that were significantly linked with drug resistance, and attempted to explain the resistance mechanisms. However, they mainly focused on several significant mutations in drug targets (e.g. rpoB, katG). Some genes which are potentially associated with drug resistance may be overlooked by the GWAS analysis. OBJECTIVE In this article, our motivation is to detect potential drug resistance genes of Mtb using a heat diffusion model. METHODS All sequencing data, which contained 127 samples of Mtb, i.e. 34 ethambutol-, 65 isoniazid-, 53 rifampicin- and 45 streptomycin-resistant strains. The raw sequence data were preprocessed using Trimmomatic software and aligned to the Mtb H37Rv reference genome using Bowtie2. From the resulting alignments, SAMtools and VarScan were used to filter sequences and call SNPs. The GWAS was performed by the PLINK package to obtain the significant SNPs, which were mapped to genes. The P-values of genes calculated by GWAS were transferred into a heat vector. The heat vector and the Mtb protein-protein interactions (PPI) derived from the STRING database were inputted into the heat diffusion model to obtain significant subnetworks by HotNet2. Finally, the most significant (P < 0.05) subnetworks associated with different phenotypes were obtained. To verify the change of binding energy between the drug and target before and after mutation, the method of molecular dynamics simulation was performed using the AMBER software. RESULTS We identified significant subnetworks in rifampicin-resistant samples. Excitingly, we found rpoB and rpoC, which are drug targets of rifampicin. From the protein structure of rpoB, the mutation location was extremely close to the drug binding site, with a distance of only 3.97 Å. Molecular dynamics simulation revealed that the binding energy of rpoB and rifampicin decreased after D435V mutation. To a large extent, this mutation can influence the affinity of drug-target binding. In addition, topA and pyrG were reported to be linked with drug resistance, and might be new TB drug targets. Other genes that have not yet been reported are worth further study. CONCLUSION Using a heat diffusion model in combination with GWAS results and protein-protein interactions, the significantly mutated subnetworks in rifampicin-resistant samples were found. The subnetwork not only contained the known targets of rifampicin (rpoB, rpoC), but also included topA and pyrG, which are potentially associated with drug resistance. Together, these results offer deeper insights into drug resistance of Mtb, and provides potential drug targets for finding new antituberculosis drugs.
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Affiliation(s)
- Ze-Jia Cui
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei-Tong Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Qiang Zhu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Qing-Ye Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Hong-Yu Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
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Namburete EI, Dippenaar A, Conceição EC, Feliciano C, Nascimento MMPD, Peronni KC, Silva WA, Ferro JJ, Harrison LH, Warren RM, Bollela VR. Phylogenomic assessment of drug-resistant Mycobacterium tuberculosis strains from Beira, Mozambique. Tuberculosis (Edinb) 2020; 121:101905. [PMID: 32063558 PMCID: PMC9300053 DOI: 10.1016/j.tube.2020.101905] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Revised: 12/21/2019] [Accepted: 01/26/2020] [Indexed: 11/24/2022]
Abstract
BACKGROUND Mozambique is a high-burden tuberculosis (TB) country where TB/HIV co-infection and drug resistant TB (DR-TB) incidence is increasing. Whole genome sequencing (WGS) comprehensively describes the molecular epidemiology of TB, allows prediction of DR-TB phenotypes, lineages strains identification and better understanding of transmission chains. OBJECTIVE To describe genetic diversity of DR-TB Mycobacterium tuberculosis isolated in Beira, Mozambique. METHODS Descriptive cross-sectional study with 35 M. tuberculosis isolates, resistant to at least one first-line drug on molecular drug-susceptibility tests (DST). Variant identification, DR prediction and phylogenetic analysis provided by WGS, drug-susceptibility pattern compared to line-probe assay (LPA): Genotype MTBDRTMplus and MTBDRTMsl. FINDINGS Lineage 4 (L4) was the most prevalent: 25 (71.4%) isolates; 5 (14.3%) L1 and 5 (14.3%) L2. WGS showed 33/35 (94.3%) isolates resistant to at least one drug, two pan-susceptible isolates that were previously diagnosed as DR-TB with genotype MTBDRplus. Concordance between WGS and LPA: 88.6% for isoniazid (INH), 85.7% to rifampicin (RPM), 91.4% for quinolones and 100% to second line injectable drugs. There were three possible TB transmission chains, 10 strains showing recent transmission. CONCLUSION WGS provided reliable information about the most frequent lineages related to DR-TB in Beira, Mozambique: L4.3 (LAM), L2 (Beijing) and L1 (EAI) and possible recent transmission chain.
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Affiliation(s)
- Evangelina Inacio Namburete
- Mycobacteria Research Lab at Clinics Hospital from Ribeirão Preto Medical School, University of São Paulo (FMRP-USP), Brazil; Faculty of Health Science, Catholic University of Mozambique, Beira, Mozambique.
| | - Anzaan Dippenaar
- DST-NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, South Africa.
| | - Emilyn Costa Conceição
- Instituto de Microbiologia Paulo de Góes, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373 - bloco i - Cidade Universitária, Rio de Janeiro, RJ, 21941-970, Brazil.
| | - Cinara Feliciano
- Mycobacteria Research Lab at Clinics Hospital from Ribeirão Preto Medical School, University of São Paulo (FMRP-USP), Brazil.
| | | | - Kamila Chagas Peronni
- Center for Medical Genomics, Clinics Hospital at Ribeirão Preto Medical School, University of São Paulo (FMRP-USP), Brazil.
| | - Wilson Araújo Silva
- Center for Medical Genomics, Clinics Hospital at Ribeirão Preto Medical School, University of São Paulo (FMRP-USP), Brazil; Department of Genetics at Ribeirão Preto Medical School, University of São Paulo (FMRP-USP), Brazil.
| | - Josefo João Ferro
- Faculty of Health Science, Catholic University of Mozambique, Beira, Mozambique.
| | - Lee H Harrison
- Infectious Diseases Epidemiology Research Unit, University of Pittsburgh, Pittsburgh, USA.
| | - Robin Mark Warren
- DST-NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, South Africa.
| | - Valdes Roberto Bollela
- Mycobacteria Research Lab at Clinics Hospital from Ribeirão Preto Medical School, University of São Paulo (FMRP-USP), Brazil.
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Salvato RS, Costa ERD, Reis AJ, Schiefelbein SH, Halon ML, Barcellos RB, Unis G, Dias CF, Viveiros M, Portugal I, da Silva PEA, Kritski AL, Perdigão J, Rossetti MLR. First insights into circulating XDR and pre-XDR Mycobacterium tuberculosis in Southern Brazil. INFECTION GENETICS AND EVOLUTION 2020; 78:104127. [DOI: 10.1016/j.meegid.2019.104127] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Revised: 11/20/2019] [Accepted: 11/24/2019] [Indexed: 11/30/2022]
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138
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Cancino-Muñoz I, Moreno-Molina M, Furió V, Goig GA, Torres-Puente M, Chiner-Oms Á, Villamayor LM, Sanz F, Guna-Serrano MR, Comas I. Cryptic Resistance Mutations Associated With Misdiagnoses of Multidrug-Resistant Tuberculosis. J Infect Dis 2020; 220:316-320. [PMID: 30875421 PMCID: PMC6581888 DOI: 10.1093/infdis/jiz104] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 03/11/2019] [Indexed: 11/30/2022] Open
Abstract
Understanding why some multidrug-resistant tuberculosis cases are not detected by rapid phenotypic and genotypic routine clinical tests is essential to improve diagnostic assays and advance toward personalized tuberculosis treatment. Here, we combine whole-genome sequencing with single-colony phenotyping to identify a multidrug-resistant strain that had infected a patient for 9 years. Our investigation revealed the failure of rapid testing and genome-based prediction tools to identify the multidrug-resistant strain. The false-negative findings were caused by uncommon rifampicin and isoniazid resistance mutations. Although whole-genome sequencing data helped to personalize treatment, the patient developed extensively drug-resistant tuberculosis, highlighting the importance of coupling new diagnostic methods with appropriate treatment regimens.
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Affiliation(s)
- Irving Cancino-Muñoz
- Instituto de Biomedicina de Valencia-Consejo Superior de Investigaciones Científicas.,Genomics and Health Unit, FISABIO Public Health, Consorci Hospital General Universitari de València, Valencia, Spain
| | - Miguel Moreno-Molina
- Instituto de Biomedicina de Valencia-Consejo Superior de Investigaciones Científicas
| | - Victoria Furió
- Instituto de Biomedicina de Valencia-Consejo Superior de Investigaciones Científicas
| | - Galo A Goig
- Instituto de Biomedicina de Valencia-Consejo Superior de Investigaciones Científicas
| | - Manuela Torres-Puente
- Instituto de Biomedicina de Valencia-Consejo Superior de Investigaciones Científicas
| | - Álvaro Chiner-Oms
- Unidad Mixta "Infección y Salud Pública," Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)-Conselleria de Sanitat Universal i Salut Pública
| | - Luis M Villamayor
- Genomics and Health Unit, FISABIO Public Health, Consorci Hospital General Universitari de València, Valencia, Spain
| | - Francisco Sanz
- Departamento de Neumología, Consorci Hospital General Universitari de València, Valencia, Spain
| | | | - Iñaki Comas
- Instituto de Biomedicina de Valencia-Consejo Superior de Investigaciones Científicas.,Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, Madrid, Spain
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139
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Katale BZ, Mbelele PM, Lema NA, Campino S, Mshana SE, Rweyemamu MM, Phelan JE, Keyyu JD, Majigo M, Mbugi EV, Dockrell HM, Clark TG, Matee MI, Mpagama S. Whole genome sequencing of Mycobacterium tuberculosis isolates and clinical outcomes of patients treated for multidrug-resistant tuberculosis in Tanzania. BMC Genomics 2020; 21:174. [PMID: 32085703 PMCID: PMC7035673 DOI: 10.1186/s12864-020-6577-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 02/12/2020] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Tuberculosis (TB), particularly multi- and or extensive drug resistant TB, is still a global medical emergency. Whole genome sequencing (WGS) is a current alternative to the WHO-approved probe-based methods for TB diagnosis and detection of drug resistance, genetic diversity and transmission dynamics of Mycobacterium tuberculosis complex (MTBC). This study compared WGS and clinical data in participants with TB. RESULTS This cohort study performed WGS on 87 from MTBC DNA isolates, 57 (66%) and 30 (34%) patients with drug resistant and susceptible TB, respectively. Drug resistance was determined by Xpert® MTB/RIF assay and phenotypic culture-based drug-susceptibility-testing (DST). WGS and bioinformatics data that predict phenotypic resistance to anti-TB drugs were compared with participant's clinical outcomes. They were 47 female participants (54%) and the median age was 35 years (IQR): 29-44). Twenty (23%) and 26 (30%) of participants had TB/HIV co-infection BMI < 18 kg/m2 respectively. MDR-TB participants had MTBC with multiple mutant genes, compared to those with mono or polyresistant TB, and the majority belonged to lineage 3 Central Asian Strain (CAS). Also, MDR-TB was associated with delayed culture-conversion (median: IQR (83: 60-180 vs. 51:30-66) days). WGS had high concordance with both culture-based DST and Xpert® MTB/RIF assay in detecting drug resistance (kappa = 1.00). CONCLUSION This study offers comparison of mutations detected by Xpert and WGS with phenotypic DST of M. tuberculosis isolates in Tanzania. The high concordance between the different methods and further insights provided by WGS such as PZA-DST, which is not routinely performed in most resource-limited-settings, provides an avenue for inclusion of WGS into diagnostic matrix of TB including drug-resistant TB.
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Affiliation(s)
- Bugwesa Z Katale
- Department of Microbiology and Immunology, School of Medicine, Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam, Tanzania
- Tanzania Wildlife Research Institute (TAWIRI), Arusha, Tanzania
| | - Peter M Mbelele
- Kibong'oto Infectious Disease Hospital (KIDH), Sanya Juu, Tanzania
- Department of Global Health and Biomedical Sciences, School of Life Sciences and Bioengineering, Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania
| | - Nsiande A Lema
- Field Epidemiology and Laboratory Training Programme, Dar es Salaam, Tanzania
| | - Susana Campino
- Faculty of Infectious and Tropical Diseases, London School of Hygiene &Tropical Medicine (LSHTM), Keppel Street, London, WC1E 7HT, UK
| | - Stephen E Mshana
- Department of Medical Microbiology, Catholic University of Health and Allied Sciences, Mwanza, Tanzania
| | - Mark M Rweyemamu
- Southern African Centre for Infectious Diseases Surveillance (SACIDS), Sokoine University of Agriculture (SUA), Morogoro, Tanzania
| | - Jody E Phelan
- Faculty of Infectious and Tropical Diseases, London School of Hygiene &Tropical Medicine (LSHTM), Keppel Street, London, WC1E 7HT, UK
| | - Julius D Keyyu
- Tanzania Wildlife Research Institute (TAWIRI), Arusha, Tanzania
| | - Mtebe Majigo
- Department of Microbiology and Immunology, School of Medicine, Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam, Tanzania
| | - Erasto V Mbugi
- Department of Biochemistry, Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam, Tanzania
| | - Hazel M Dockrell
- Faculty of Infectious and Tropical Diseases, London School of Hygiene &Tropical Medicine (LSHTM), Keppel Street, London, WC1E 7HT, UK
| | - Taane G Clark
- Faculty of Infectious and Tropical Diseases, London School of Hygiene &Tropical Medicine (LSHTM), Keppel Street, London, WC1E 7HT, UK
- Faculty of Epidemiology and Population Health, London School of Hygiene &Tropical Medicine (LSHTM), Keppel Street, London, WC1E 7HT, UK
| | - Mecky I Matee
- Department of Microbiology and Immunology, School of Medicine, Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam, Tanzania.
| | - Stellah Mpagama
- Kibong'oto Infectious Disease Hospital (KIDH), Sanya Juu, Tanzania
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140
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Whole genome enrichment approach for rapid detection of Mycobacterium tuberculosis and drug resistance-associated mutations from direct sputum sequencing. Tuberculosis (Edinb) 2020; 121:101915. [PMID: 32279871 DOI: 10.1016/j.tube.2020.101915] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 02/12/2020] [Accepted: 02/17/2020] [Indexed: 11/24/2022]
Abstract
Tuberculosis is the leading cause of death among infectious diseases worldwide. Detection of Mycobacterium tuberculosis (Mtb), using routine culture-based methods is time consuming resulting in delayed diagnosis and poor treatment outcomes. Currently available molecular tests provide faster diagnosis but are able to screen only limited hot-spot mutations. Whole genome sequencing from direct sputum offers a potential solution, however, due to the presence of other microbes and host DNA its use in diagnostic testing remains challenging. In this study, we present a targeted Mtb-enrichment assay for lineage-4 coupled with an improved analysis pipeline that uses 1657 bacterial taxa as background for reducing non-Mtb genome from sputum DNA. This method drastically improved the recovery of Mtb DNA from sputum (Mtb alignment increased from 3% to >65%) as compared to non-enrichment-based sequencing. We obtained >99% Mtb genome coverage as compared to 49% in non-enriched sputum sequencing. We were able to identify Mtb positive samples from controls with 100% accuracy using Mpt64 gene coverage. Our method not only achieved 100% sensitivity to resistance variants profiled by line probe assay (LPA), but also outperformed LPA in determining drug resistance based on phenotypic drug susceptibility tests for 6 anti-tuberculosis drugs (accuracy of 97.7% and 92.8% by enriched WGS and LPA, respectively).
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Perdigão J, Gomes P, Miranda A, Maltez F, Machado D, Silva C, Phelan JE, Brum L, Campino S, Couto I, Viveiros M, Clark TG, Portugal I. Using genomics to understand the origin and dispersion of multidrug and extensively drug resistant tuberculosis in Portugal. Sci Rep 2020; 10:2600. [PMID: 32054988 PMCID: PMC7018963 DOI: 10.1038/s41598-020-59558-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 12/13/2019] [Indexed: 01/12/2023] Open
Abstract
Portugal is a low incidence country for tuberculosis (TB) disease. Now figuring among TB low incidence countries, it has since the 1990s reported multidrug resistant and extensively drug resistant (XDR) TB cases, driven predominantly by two strain-types: Lisboa3 and Q1. This study describes the largest characterization of the evolutionary trajectory of M/XDR-TB strains in Portugal, spanning a time-period of two decades. By combining whole-genome sequencing and phenotypic susceptibility data for 207 isolates, we report the geospatial patterns of drug resistant TB, particularly the dispersion of Lisboa3 and Q1 clades, which underly 64.2% and 94.0% of all MDR-TB and XDR-TB isolates, respectively. Genomic-based similarity and a phylogenetic analysis revealed multiple clusters (n = 16) reflecting ongoing and uncontrolled recent transmission of M/XDR-TB, predominantly associated with the Lisboa3 and Q1 clades. These clades are now thought to be evolving in a polycentric mode across multiple geographical districts. The inferred evolutionary history is compatible with MDR- and XDR-TB originating in Portugal in the 70's and 80's, respectively, but with subsequent multiple emergence events of MDR and XDR-TB particularly involving the Lisboa3 clade. A SNP barcode was defined for Lisboa3 and Q1 and comparison with a phylogeny of global strain-types (n = 28 385) revealed the presence of Lisboa3 and Q1 strains in Europe, South America and Africa. In summary, Portugal displays an unusual and unique epidemiological setting shaped by >40 years of uncontrolled circulation of two main phylogenetic clades, leading to a sympatric evolutionary trajectory towards XDR-TB with the potential for global reach.
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Affiliation(s)
- João Perdigão
- Research Institute for Medicines (iMed.ULisboa), Faculdade de Farmácia, Universidade de Lisboa, Lisboa, Portugal.
| | - Pedro Gomes
- Research Institute for Medicines (iMed.ULisboa), Faculdade de Farmácia, Universidade de Lisboa, Lisboa, Portugal
| | - Anabela Miranda
- Departamento de Doenças Infeciosas, Instituto Nacional de Saúde Dr. Ricardo Jorge, Porto, Portugal
| | - Fernando Maltez
- Research Institute for Medicines (iMed.ULisboa), Faculdade de Farmácia, Universidade de Lisboa, Lisboa, Portugal
- Serviço de Doenças Infecciosas, Hospital de Curry Cabral, Lisboa, Portugal
| | - Diana Machado
- Unidade de Microbiologia Médica, Global Health and Tropical Medicine, GHTM, Instituto de Higiene e Medicina Tropical, IHMT, Universidade Nova de Lisboa, UNL, Lisboa, Portugal
| | - Carla Silva
- Research Institute for Medicines (iMed.ULisboa), Faculdade de Farmácia, Universidade de Lisboa, Lisboa, Portugal
| | - Jody E Phelan
- London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom
| | | | - Susana Campino
- London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom
| | - Isabel Couto
- Unidade de Microbiologia Médica, Global Health and Tropical Medicine, GHTM, Instituto de Higiene e Medicina Tropical, IHMT, Universidade Nova de Lisboa, UNL, Lisboa, Portugal
| | - Miguel Viveiros
- Unidade de Microbiologia Médica, Global Health and Tropical Medicine, GHTM, Instituto de Higiene e Medicina Tropical, IHMT, Universidade Nova de Lisboa, UNL, Lisboa, Portugal
| | - Taane G Clark
- Unidade de Microbiologia Médica, Global Health and Tropical Medicine, GHTM, Instituto de Higiene e Medicina Tropical, IHMT, Universidade Nova de Lisboa, UNL, Lisboa, Portugal
- London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom
| | - Isabel Portugal
- Research Institute for Medicines (iMed.ULisboa), Faculdade de Farmácia, Universidade de Lisboa, Lisboa, Portugal.
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142
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Kardan-Yamchi J, Kazemian H, Battaglia S, Abtahi H, Rahimi Foroushani A, Hamzelou G, Cirillo DM, Ghodousi A, Feizabadi MM. Whole Genome Sequencing Results Associated with Minimum Inhibitory Concentrations of 14 Anti-Tuberculosis Drugs among Rifampicin-Resistant Isolates of Mycobacterium Tuberculosis from Iran. J Clin Med 2020; 9:jcm9020465. [PMID: 32046149 PMCID: PMC7073636 DOI: 10.3390/jcm9020465] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 12/15/2019] [Accepted: 12/18/2019] [Indexed: 01/30/2023] Open
Abstract
Accurate and timely detection of drug resistance can minimize the risk of further resistance development and lead to effective treatment. The aim of this study was to determine the resistance to first/second-line anti-tuberculosis drugs in rifampicin/multidrug-resistant Mycobacterium tuberculosis (RR/MDR-MTB) isolates. Molecular epidemiology of strains was determined using whole genome sequencing (WGS)-based genotyping. A total of 35 RR/MDR-MTB isolates were subjected to drug susceptibility testing against first/second-line drugs using 7H9 Middlebrook in broth microdilution method. Illumina technology was used for paired-end WGS applying a Maxwell 16 Cell DNA Purification kit and the NextSeq platform. Data analysis and single nucleotide polymorphism calling were performed using MTBseq pipeline. The genome-based resistance to each drug among the resistant phenotypes was as follows: rifampicin (97.1%), isoniazid (96.6%), ethambutol (100%), levofloxacin (83.3%), moxifloxacin (83.3%), amikacin (100%), kanamycin (100%), capreomycin (100%), prothionamide (100%), D-cycloserine (11.1%), clofazimine (20%), bedaquiline (0.0%), and delamanid (44.4%). There was no linezolid-resistant phenotype, and a bedaquiline-resistant strain was wild type for related genes. The Beijing, Euro-American, and Delhi-CAS were the most populated lineage/sublineages. Drug resistance-associated mutations were mostly linked to minimum inhibitory concentration results. However, the role of well-known drug-resistant genes for D-cycloserine, clofazimine, bedaquiline, and delamanid was found to be more controversial.
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Affiliation(s)
- Jalil Kardan-Yamchi
- Division of Microbiology, Department of Pathobiology, School of Public Health, Tehran University of Medical Sciences, Tehran 1417653911, Iran;
- Department of Microbiology, School of Medicine, Tehran University of Medical Sciences, Tehran 1417653911, Iran;
| | - Hossein Kazemian
- Department of Microbiology, School of Medicine, Tehran University of Medical Sciences, Tehran 1417653911, Iran;
| | - Simone Battaglia
- Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy; (S.B.)
| | - Hamidreza Abtahi
- Thoracic Research Center, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran 1417653911, Iran;
| | - Abbas Rahimi Foroushani
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran 1417653911, Iran;
| | - Gholamreza Hamzelou
- Tehran Regional Reference Laboratory for Tuberculosis, Tehran University of Medical Sciences, Tehran 1417653911, Iran;
| | - Daniela Maria Cirillo
- Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy; (S.B.)
| | - Arash Ghodousi
- Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy; (S.B.)
- Correspondence: (A.G.); (M.M.F.)
| | - Mohammad Mehdi Feizabadi
- Department of Microbiology, School of Medicine, Tehran University of Medical Sciences, Tehran 1417653911, Iran;
- Thoracic Research Center, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran 1417653911, Iran;
- Correspondence: (A.G.); (M.M.F.)
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143
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Phylogenomic Perspective on a Unique Mycobacterium bovis Clade Dominating Bovine Tuberculosis Infections among Cattle and Buffalos in Northern Brazil. Sci Rep 2020; 10:1747. [PMID: 32019968 PMCID: PMC7000724 DOI: 10.1038/s41598-020-58398-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Accepted: 01/13/2020] [Indexed: 11/08/2022] Open
Abstract
Lack of routine surveillance in countries endemic for bovine tuberculosis (TB) and limited laboratory support contributes to the inability to differentiate the Mycobacterium tuberculosis Complex species, leading to an underestimated burden of the disease. Here, Whole-Genome Sequencing of Mycobacterium bovis isolated from tissues with TB-like lesions obtained from cattle and buffalos at Marajó Island, Brazil, demonstrates that recent transmission of M. bovis is ongoing at distinct sites. Moreover, the M. bovis epidemiology in this setting is herein found to be dominated by an endemic and unique clade composed of strains evolved from a common ancestor that are now genetically differentiated from other M. bovis clades. Additionally, envisioning a rapid strain differentiation and tracing across multiple settings, 28 globally validated strain-specific SNPs were identified, three of which considered as robust markers for the M. bovis Marajó strain. In conclusion, this study contributes with data regarding the identification of a novel M. bovis phylogenetic clade responsible for ongoing transmission events in both cattle and buffalo species in Brazil, provides a framework to investigate the dissemination of this highly prevalent strain and, holds the potential to inform TB control strategies that may help to prevent the spread of bovine and zoonotic TB.
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144
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Klopper M, Heupink TH, Hill-Cawthorne G, Streicher EM, Dippenaar A, de Vos M, Abdallah AM, Limberis J, Merker M, Burns S, Niemann S, Dheda K, Posey J, Pain A, Warren RM. A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic. BMC Med 2020; 18:24. [PMID: 32014024 PMCID: PMC6998097 DOI: 10.1186/s12916-019-1487-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 12/24/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Atypical Beijing genotype Mycobacterium tuberculosis strains are widespread in South Africa and have acquired resistance to up to 13 drugs on multiple occasions. It is puzzling that these strains have retained fitness and transmissibility despite the potential fitness cost associated with drug resistance mutations. METHODS We conducted Illumina sequencing of 211 Beijing genotype M. tuberculosis isolates to facilitate the detection of genomic features that may promote acquisition of drug resistance and restore fitness in highly resistant atypical Beijing forms. Phylogenetic and comparative genomic analysis was done to determine changes that are unique to the resistant strains that also transmit well. Minimum inhibitory concentration (MIC) determination for streptomycin and bedaquiline was done for a limited number of isolates to demonstrate a difference in MIC between isolates with and without certain variants. RESULTS Phylogenetic analysis confirmed that two clades of atypical Beijing strains have independently developed resistance to virtually all the potent drugs included in standard (pre-bedaquiline) drug-resistant TB treatment regimens. We show that undetected drug resistance in a progenitor strain was likely instrumental in this resistance acquisition. In this cohort, ethionamide (ethA A381P) resistance would be missed in first-line drug-susceptible isolates, and streptomycin (gidB L79S) resistance may be missed due to an MIC close to the critical concentration. Subsequent inadequate treatment historically led to amplification of resistance and facilitated spread of the strains. Bedaquiline resistance was found in a small number of isolates, despite lack of exposure to the drug. The highly resistant clades also carry inhA promoter mutations, which arose after ethA and katG mutations. In these isolates, inhA promoter mutations do not alter drug resistance, suggesting a possible alternative role. CONCLUSION The presence of the ethA mutation in otherwise susceptible isolates from ethionamide-naïve patients demonstrates that known exposure is not an adequate indicator of drug susceptibility. Similarly, it is demonstrated that bedaquiline resistance can occur without exposure to the drug. Inappropriate treatment regimens, due to missed resistance, leads to amplification of resistance, and transmission. We put these results into the context of current WHO treatment regimens, underscoring the risks of treatment without knowledge of the full drug resistance profile.
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Affiliation(s)
- Marisa Klopper
- South African Medical Research Council Centre for Tuberculosis Research, DST NRF Centre of Excellence for Biomedical Tuberculosis research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
| | - Tim Hermanus Heupink
- Global Health Institute, Epidemiology and Social Medicine, University of Antwerp, Antwerp, Belgium
| | - Grant Hill-Cawthorne
- Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Elizabeth Maria Streicher
- South African Medical Research Council Centre for Tuberculosis Research, DST NRF Centre of Excellence for Biomedical Tuberculosis research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Anzaan Dippenaar
- South African Medical Research Council Centre for Tuberculosis Research, DST NRF Centre of Excellence for Biomedical Tuberculosis research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Margaretha de Vos
- South African Medical Research Council Centre for Tuberculosis Research, DST NRF Centre of Excellence for Biomedical Tuberculosis research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Abdallah Musa Abdallah
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.,Department of Basic Medical Sciences, College of Medicine, QU Health, Qatar University, Doha, Qatar
| | - Jason Limberis
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute & South African MRC/UCT Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
| | - Matthias Merker
- Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
| | - Scott Burns
- Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, 30329, USA
| | - Stefan Niemann
- Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany.,German Center for Infection Research, Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany
| | - Keertan Dheda
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute & South African MRC/UCT Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa.,Faculty of Infectious and Tropical Diseases, Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, UK
| | - James Posey
- Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, 30329, USA
| | - Arnab Pain
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.,Center for Zoonosis Control, Global Institution for Collaborative Research and Education (GI-CoRE), Hokkaido University, Sapporo, Japan
| | - Robin Mark Warren
- South African Medical Research Council Centre for Tuberculosis Research, DST NRF Centre of Excellence for Biomedical Tuberculosis research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
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145
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Wang WF, Lu MYJ, Cheng TJR, Tang YC, Teng YC, Hwa TY, Chen YH, Li MY, Wu MH, Chuang PC, Jou R, Wong CH, Li WH. Genomic Analysis of Mycobacterium tuberculosis Isolates and Construction of a Beijing Lineage Reference Genome. Genome Biol Evol 2020; 12:3890-3905. [PMID: 31971587 PMCID: PMC7058165 DOI: 10.1093/gbe/evaa009] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/14/2020] [Indexed: 12/03/2022] Open
Abstract
Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis, kills over 1 million people worldwide annually. Development of drug resistance (DR) in the pathogen is a major challenge for TB control. We conducted whole-genome analysis of seven Taiwan M. tuberculosis isolates: One drug susceptible (DS) and five DR Beijing lineage isolates and one DR Euro-American lineage isolate. Developing a new method for DR mutation identification and applying it to the next-generation sequencing (NGS) data from the 6 Beijing lineage isolates, we identified 13 known and 6 candidate DR mutations and provided experimental support for 4 of them. We assembled the genomes of one DS and two DR Beijing lineage isolates and the Euro-American lineage isolate using NGS data. Moreover, using both PacBio and NGS sequencing data, we obtained a high-quality assembly of an extensive DR Beijing lineage isolate. Comparative analysis of these five newly assembled genomes and two published complete genomes revealed a large number of genetic changes, including gene gains and losses, indels and translocations, suggesting rapid evolution of M. tuberculosis. We found the MazEF toxin-antitoxin system in all the seven isolates studied and several interesting mutations in MazEF proteins. Finally, we used the four assembled Beijing lineage genomes to construct a high-quality Beijing lineage reference genome that is DS and contains all the genes in the four genomes. It contains 212 genes not found in the standard reference H37Rv, which is Euro-American. It is therefore a better reference than H37Rv for the Beijing lineage, the predominant lineage in Asia.
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Affiliation(s)
- Woei-Fuh Wang
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
- Center for Precision Medicine, China Medical University Hospital, Taichung, Taiwan
| | - Mei-Yeh Jade Lu
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
| | | | - Yi-Ching Tang
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
| | - Yu-Chuan Teng
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
| | - Teh-Yang Hwa
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
| | - Yi-Hua Chen
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
| | - Meng-Yun Li
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
| | - Mei-Hua Wu
- Tuberculosis Research Center, Centers for Disease Control, Taipei, Taiwan
| | - Pei-Chun Chuang
- Tuberculosis Research Center, Centers for Disease Control, Taipei, Taiwan
| | - Ruwen Jou
- Tuberculosis Research Center, Centers for Disease Control, Taipei, Taiwan
| | - Chi-Huey Wong
- Genome Research Center, Academia Sinica, Taipei, Taiwan
| | - Wen-Hsiung Li
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
- Department of Ecology and Evolution, University of Chicago, Illinois
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146
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Ismail NA, Ismail F, Joseph L, Govender N, Blows L, Kaniga K, Omar SV. Epidemiological cut-offs for Sensititre susceptibility testing of Mycobacterium tuberculosis: interpretive criteria cross validated with whole genome sequencing. Sci Rep 2020; 10:1013. [PMID: 31974497 PMCID: PMC6978314 DOI: 10.1038/s41598-020-57992-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 01/08/2020] [Indexed: 11/20/2022] Open
Abstract
Universal drug susceptibility testing (DST) is an important requirement of the End TB Strategy. The Sensititre broth micro-dilution assay (BMD) tests multiple drugs quantitatively. We defined interpretive criteria for this assay and analysed genotypic-phenotypic relationships. 385 Mycobacterium tuberculosis clinical isolates were processed for BMD and whole genome sequencing. The epidemiological cut-off value 99% (ECV99) amongst genotypically wild type (gWT) strains defined susceptibility. Minimum inhibitory concentration distributions of the resistance-associated variants (RAVs) for each drug were analysed. Susceptibility (µg/mL) criteria were determined as follows: rifampicin (≤0.125), isoniazid (≤0.25), ethambutol (≤2.0), moxifloxacin (≤0.5), levofloxacin (≤1.0), amikacin (≤2.0), kanamycin (≤8.0), capreomycin (≤4.0), clofazimine (≤0.25) and linezolid (≤2.0). Most drugs showed clear separation between gWT and RAV. Isoniazid showed a tri-modal pattern with 14/17 strains at ECV99 harbouring a fabG1 c. -15C > T RAV. Ethambutol RAVs at embB codons 306, 405 and 497 were responsible for resistance and showed differential distributions. Moxifloxacin RAVs (gyrA codon 90) were a dilution or two higher than the ECV99 while gyrB RAVs were uncommon and showed drug specific resistance propensity. Interpretive criteria established were robust facilitating progress towards universal DST and individualised precision medicine. This study demonstrates the value of quantitative DST to accurately interpret mutation data.
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Affiliation(s)
- Nazir A Ismail
- National Institute for Communicable Diseases, Centre for Tuberculosis, Johannesburg, South Africa.
- Department of Medical Microbiology, University of Pretoria, Pretoria, South Africa.
- Department of Internal Medicine, University of Witwatersrand, Johannesburg, South Africa.
| | - Farzana Ismail
- National Institute for Communicable Diseases, Centre for Tuberculosis, Johannesburg, South Africa
- Department of Medical Microbiology, University of Pretoria, Pretoria, South Africa
| | - Lavania Joseph
- National Institute for Communicable Diseases, Centre for Tuberculosis, Johannesburg, South Africa
| | - Netricia Govender
- National Institute for Communicable Diseases, Centre for Tuberculosis, Johannesburg, South Africa
| | - Linsay Blows
- National Institute for Communicable Diseases, Centre for Tuberculosis, Johannesburg, South Africa
| | - Koné Kaniga
- Janssen Research & Development, Titusville, NJ, United States of America
| | - Shaheed V Omar
- National Institute for Communicable Diseases, Centre for Tuberculosis, Johannesburg, South Africa
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147
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Resistance Sniffer: An online tool for prediction of drug resistance patterns of Mycobacterium tuberculosis isolates using next generation sequencing data. Int J Med Microbiol 2020; 310:151399. [PMID: 31980371 DOI: 10.1016/j.ijmm.2020.151399] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Revised: 11/13/2019] [Accepted: 12/29/2019] [Indexed: 11/21/2022] Open
Abstract
The effective control of multidrug resistant tuberculosis (MDR-TB) relies upon the timely diagnosis and correct treatment of all tuberculosis cases. Whole genome sequencing (WGS) has great potential as a method for the rapid diagnosis of drug resistant Mycobacterium tuberculosis (Mtb) isolates. This method overcomes most of the problems that are associated with current phenotypic drug susceptibility testing. However, the application of WGS in the clinical setting has been deterred by data complexities and skill requirements for implementing the technologies as well as clinical interpretation of the next generation sequencing (NGS) data. The proposed diagnostic application was drawn upon recent discoveries of patterns of Mtb clade-specific genetic polymorphisms associated with antibiotic resistance. A catalogue of genetic determinants of resistance to thirteen anti-TB drugs for each phylogenetic clade was created. A computational algorithm for the identification of states of diagnostic polymorphisms was implemented as an online software tool, Resistance Sniffer (http://resistance-sniffer.bi.up.ac.za/), and as a stand-alone software tool to predict drug resistance in Mtb isolates using complete or partial genome datasets in different file formats including raw Illumina fastq read files. The program was validated on sequenced Mtb isolates with data on antibiotic resistance trials available from GMTV database and from the TB Platform of South African Medical Research Council (SAMRC), Pretoria. The program proved to be suitable for probabilistic prediction of drug resistance profiles of individual strains and large sequence data sets.
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148
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Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M, Edalatmand A, Huynh W, Nguyen ALV, Cheng AA, Liu S, Min SY, Miroshnichenko A, Tran HK, Werfalli RE, Nasir JA, Oloni M, Speicher DJ, Florescu A, Singh B, Faltyn M, Hernandez-Koutoucheva A, Sharma AN, Bordeleau E, Pawlowski AC, Zubyk HL, Dooley D, Griffiths E, Maguire F, Winsor GL, Beiko RG, Brinkman FSL, Hsiao WWL, Domselaar GV, McArthur AG. CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res 2020; 48:D517-D525. [PMID: 31665441 PMCID: PMC7145624 DOI: 10.1093/nar/gkz935] [Citation(s) in RCA: 1243] [Impact Index Per Article: 310.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 10/03/2019] [Accepted: 10/08/2019] [Indexed: 02/06/2023] Open
Abstract
The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD's Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.
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Affiliation(s)
- Brian P Alcock
- David Braley Centre for Antibiotic Discovery, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Amogelang R Raphenya
- David Braley Centre for Antibiotic Discovery, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Tammy T Y Lau
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Kara K Tsang
- David Braley Centre for Antibiotic Discovery, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Mégane Bouchard
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Bachelor of Health Sciences Program, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Arman Edalatmand
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - William Huynh
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Anna-Lisa V Nguyen
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Bachelor of Health Sciences Program, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Annie A Cheng
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Sihan Liu
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Sally Y Min
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Anatoly Miroshnichenko
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Hiu-Ki Tran
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Rafik E Werfalli
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Jalees A Nasir
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Martins Oloni
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - David J Speicher
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Alexandra Florescu
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Bachelor of Health Sciences Program, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Bhavya Singh
- Honours Biology Program, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Mateusz Faltyn
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Bachelor of Arts & Science Program, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | | | - Arjun N Sharma
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Emily Bordeleau
- David Braley Centre for Antibiotic Discovery, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Andrew C Pawlowski
- Department of Genetics, Harvard Medical School, Harvard University, Boston, MA 02115, USA
| | - Haley L Zubyk
- David Braley Centre for Antibiotic Discovery, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
| | - Damion Dooley
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, V6T 2B5, British Columbia, Canada
| | - Emma Griffiths
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, V5A 1S6, Canada
| | - Finlay Maguire
- Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, B3H 1W5, Canada
| | - Geoff L Winsor
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, V5A 1S6, Canada
| | - Robert G Beiko
- Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, B3H 1W5, Canada
| | - Fiona S L Brinkman
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, V5A 1S6, Canada
| | - William W L Hsiao
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, V6T 2B5, British Columbia, Canada
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, V5A 1S6, Canada
- British Columbia Centre for Disease Control Public Health Laboratory, Vancouver, British Columbia, V5Z 4R4, Canada
| | - Gary V Domselaar
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, R3E 3R2, Canada
- Department of Medical Microbiology and Infectious Diseases, Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, R3E 0J9, Canada
| | - Andrew G McArthur
- David Braley Centre for Antibiotic Discovery, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
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149
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Wollenberg K, Harris M, Gabrielian A, Ciobanu N, Chesov D, Long A, Taaffe J, Hurt D, Rosenthal A, Tartakovsky M, Crudu V. A retrospective genomic analysis of drug-resistant strains of M. tuberculosis in a high-burden setting, with an emphasis on comparative diagnostics and reactivation and reinfection status. BMC Infect Dis 2020; 20:17. [PMID: 31910804 PMCID: PMC6947865 DOI: 10.1186/s12879-019-4739-z] [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: 09/09/2019] [Accepted: 12/27/2019] [Indexed: 12/01/2022] Open
Abstract
Background Recurrence of drug-resistant tuberculosis (DR-TB) after treatment occurs through relapse of the initial infection or reinfection by a new drug-resistant strain. Outbreaks of DR-TB in high burden regions present unique challenges in determining recurrence status for effective disease management and treatment. In the Republic of Moldova the burden of DR-TB is exceptionally high, with many cases presenting as recurrent. Methods We performed a retrospective analysis of Mycobacterium tuberculosis from Moldova to better understand the genomic basis of drug resistance and its effect on the determination of recurrence status in a high DR-burden environment. To do this we analyzed genomes from 278 isolates collected from 189 patients, including 87 patients with longitudinal samples. These pathogen genomes were sequenced using Illumina technology, and SNP panels were generated for each sample for use in phylogenetic and network analysis. Discordance between genomic resistance profiles and clinical drug-resistance test results was examined in detail to assess the possibility of mixed infection. Results There were clusters of multiple patients with 10 or fewer differences among DR-TB samples, which is evidence of person-to-person transmission of DR-TB. Analysis of longitudinally collected isolates revealed that many infections exhibited little change over time, though 35 patients demonstrated reinfection by divergent (number of differences > 10) lineages. Additionally, several same-lineage sample pairs were found to be more divergent than expected for a relapsed infection. Network analysis of the H3/4.2.1 clade found very close relationships among 61 of these samples, making differentiation of reactivation and reinfection difficult. There was discordance between genomic profile and clinical drug sensitivity test results in twelve samples, and four of these had low level (but not statistically significant) variation at DR SNPs suggesting low-level mixed infections. Conclusions Whole-genome sequencing provided a detailed view of the genealogical structure of the DR-TB epidemic in Moldova, showing that reinfection may be more prevalent than currently recognized. We also found increased evidence of mixed infection, which could be more robustly characterized with deeper levels of genomic sequencing.
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Affiliation(s)
- Kurt Wollenberg
- Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.
| | - Michael Harris
- Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Andrei Gabrielian
- Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Nelly Ciobanu
- Microbiology and Morphology Laboratory, Institute of Phthisiopneumology, Chisnau, Moldova
| | - Dumitru Chesov
- Department of Pneumology and Allergology, Nicolae Testemitanu State University of Medicine and Pharmacy, Chisinau, Moldova.,Division of Clinical Infectious Diseases, Research Center Borstel, Leibniz Lung Center, Borstel, Germany
| | - Alyssa Long
- Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Jessica Taaffe
- Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Darrell Hurt
- Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Alex Rosenthal
- Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Michael Tartakovsky
- Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Valeriu Crudu
- Microbiology and Morphology Laboratory, Institute of Phthisiopneumology, Chisnau, Moldova
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150
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Abakur EHA, Alnour TMS, Abuduhier F, Albalawi FMA, Alfifi KAS. Emergence of Heteroresistance Mycobacterium Tuberculosis in Saudi Arabia. Infect Disord Drug Targets 2020; 20:491-494. [PMID: 30914036 DOI: 10.2174/1871526519666190326141550] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2019] [Revised: 03/10/2019] [Accepted: 03/12/2019] [Indexed: 06/09/2023]
Abstract
PURPOSE Heteroresistant Mycobacterium tuberculosis (MTB) is defined as a group of drug-susceptible and resistant bacteria in a single clinical specimen from tuberculosis (TB) patients. Heteroresistance of MTB is considered a preliminary stage to full resistance. The present study aimed to determine the heteroresistance in Mycobacterium tuberculosis in Tabuk province, in the north of the Kingdom of Saudi Arabia. METHOD GenoType MTBDRplus assay was used to determine mutations associated with isoniazid and rifampicin resistance. RESULTS A total number of 46 confirmed M. tuberculosis positive sputum samples were scanned for heteroresistance. The present study revealed 3 (6.5%) heteroresistant mutations to either rpoB gene alone, 2 (4.4%) to rpoB and 1 (2.2%) to inhA genes. CONCLUSION The detection of heteroresistant mutations could guide the initiation of an appropriate regimen of treatment.
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Affiliation(s)
- Eltayib H Ahmed Abakur
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk,
KSA
- Department of Microbiology and Immunology, Faculty of Medical Laboratory Sciences, Alzaiem Alazhari University,
71491, Tabuk, KSA
| | - Tarig M S Alnour
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk,
KSA
- Department of Microbiology and Immunology, Faculty of Medical Laboratory Sciences, Alzaiem Alazhari University,
71491, Tabuk, KSA
| | - Faisel Abuduhier
- Department of Microbiology and Immunology, Faculty of Medical Laboratory Sciences, Alzaiem Alazhari University,
71491, Tabuk, KSA
| | - Fahad M A Albalawi
- Department of Microbiology and Immunology, Faculty of Medical Laboratory Sciences, Alzaiem Alazhari University,
71491, Tabuk, KSA
| | - Khalid A S Alfifi
- Microbiology Technologist, King Fahad Specialist Hospital, Tabuk, Saudi Arabia
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