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Vasanthaiah S, Verma R, Kumar A, Bandari AK, George J, Rastogi M, Manjunath GK, Sharma J, Kumar A, Subramani J, Chawla K, Pandey A. Culture-Free Whole Genome Sequencing of Mycobacterium tuberculosis Using Ligand-Mediated Bead Enrichment Method. Open Forum Infect Dis 2024; 11:ofae320. [PMID: 38957687 PMCID: PMC11218775 DOI: 10.1093/ofid/ofae320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 06/12/2024] [Indexed: 07/04/2024] Open
Abstract
Background Direct whole genome sequencing (WGS) of Mycobacterium tuberculosis (Mtb) can be used as a tool to study drug resistance, mixed infections, and within-host diversity. However, WGS is challenging to obtain from clinical samples due to low number of bacilli against a high background. Methods We prospectively collected 34 samples (sputum, n = 17; bronchoalveolar lavage, n = 13; and pus, n = 4) from patients with active tuberculosis (TB). Prior to DNA extraction, we used a ligand-mediated magnetic bead method to enrich Mtb from clinical samples and performed WGS on Illumina platform. Results Mtb was definitively identified based on WGS from 88.2% (30/34) of the samples, of which 35.3% (12/34) were smear negative. The overall median genome coverage was 15.2% (interquartile range [IQR], 7.7%-28.2%). There was a positive correlation between load of bacilli on smears and genome coverage (P < .001). We detected 58 genes listed in the World Health Organization mutation catalogue in each positive sample (median coverage, 85% [IQR, 61%-94%]), enabling the identification of mutations missed by routine diagnostics. Mutations causing resistance to rifampicin, isoniazid, streptomycin, and ethambutol were detected in 5 of 34 (14.7%) samples, including the rpoB S441A mutation that confers resistance to rifampicin, which is not covered by Xpert MTB/RIF. Conclusions We demonstrate the feasibility of magnetic bead-based enrichment for culture-free WGS of Mtb from clinical specimens, including smear-negative samples. This approach can also be integrated with low-cost sequencing workflows such as targeted sequencing for rapid detection of Mtb and drug resistance.
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Affiliation(s)
- Shruthi Vasanthaiah
- Manipal Academy of Higher Education, Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
| | - Renu Verma
- Manipal Academy of Higher Education, Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
| | - Ajay Kumar
- Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Aravind K Bandari
- Manipal Academy of Higher Education, Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
| | - John George
- Manipal Academy of Higher Education, Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
- Department of Laboratory Medicine and Pathology, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Mona Rastogi
- Manipal Academy of Higher Education, Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
| | - Gowrang Kasaba Manjunath
- Manipal Academy of Higher Education, Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
| | - Jyoti Sharma
- Manipal Academy of Higher Education, Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
| | - Abhishek Kumar
- Manipal Academy of Higher Education, Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
| | | | - Kiran Chawla
- Department of Microbiology, Kasturba Medical College Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Akhilesh Pandey
- Manipal Academy of Higher Education, Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
- Department of Laboratory Medicine and Pathology, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA
- Center for Molecular Medicine, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
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Akpobolokemi T, Martinez-Nunez RT, Raimi-Abraham BT. Tackling the global impact of substandard and falsified and unregistered/unlicensed anti-tuberculosis medicines. MEDICINE ACCESS @ POINT OF CARE 2022; 6:23992026211070406. [PMID: 36204519 PMCID: PMC9413333 DOI: 10.1177/23992026211070406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 12/15/2021] [Indexed: 11/16/2022] Open
Abstract
Substandard and falsified (SF) medicines are a global health challenge with the
World Health Organization (WHO) estimating that 1 in 10 of medicines in low- and
middle-income countries (LMICs) are SF. Antimicrobials (i.e. antimalarials,
antibiotics) are the most commonly reported SF medicines. SF medicines
contribute significantly to the global burden of infectious diseases and
antimicrobial resistance (AMR). This article discusses the challenges associated
with the global impact of SF and unregistered/unlicensed antimicrobials with a
focus on anti-TB medicines. Tuberculosis (TB) is the 13th leading cause of death
worldwide, and is currently the second leading cause of death from a single
infectious agent, ranking after COVID-19 and above HIV/AIDS. Specifically in the
case of TB, poor quality of anti-TB medicines is among the drivers of the
emergence of drug-resistant TB pathogens. In this article, we highlight and
discuss challenges including the emergence of SF associated AMR, patient
mistrust and lack of relevant data. We also present study reports to inform
meaningful change. Recommended solutions involve the adaptation of interventions
from high-income countries (HICs) to LMICS, the need for improvement in the
uptake of medication authentication tools in LMICs, increased stewardship, and
the need for global and regional multidisciplinary legal and policy cooperation,
resulting in improved legal sanctions.
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Affiliation(s)
- Tamara Akpobolokemi
- Institute of Pharmaceutical Science, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences & Medicine, King’s College London, London, UK
| | - Rocio Teresa Martinez-Nunez
- Department of Infectious Diseases, School of Immunology & Microbial Sciences, Faculty of Life Sciences & Medicine, King’s College London, Guy’s Hospital, London, UK
| | - Bahijja Tolulope Raimi-Abraham
- Institute of Pharmaceutical Science, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences & Medicine, King’s College London, London, UK
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Li G, Guo Q, Liu H, Wan L, Jiang Y, Li M, Zhao LL, Zhao X, Liu Z, Wan K. Detection of Resistance to Fluoroquinolones and Second-Line Injectable Drugs Among Mycobacterium tuberculosis by a Reverse Dot Blot Hybridization Assay. Infect Drug Resist 2020; 13:4091-4104. [PMID: 33204126 PMCID: PMC7666996 DOI: 10.2147/idr.s270209] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 10/07/2020] [Indexed: 01/23/2023] Open
Abstract
Background Reliable and timely determination of second-line drug resistance is essential for early initiation effective anti-tubercular treatment among multi-drug resistant (MDR) patients and blocking the spread of MDR and extensively drug-resistant tuberculosis. Molecular methods have the potency to provide accurate and rapid drug susceptibility results. We aimed to establish and evaluate the accuracy of a reverse dot blot hybridization (RDBH) assay to simultaneously detect the resistance of fluoroquinolones (FQs), kanamycin (KN), amikacin (AMK), capreomycin (CPM) and second-line injectable drugs (SLIDs) in Mycobacterium tuberculosis. Methods We established and evaluated the accuracy of the RDBH assay by comparing to the phenotypic drug susceptibility testing (DST) and sequencing in 170 M. tuberculosis, of which 94 and 27 were respectively resistant to ofloxacin (OFX) and SLIDs. Results The results show that, compared to phenotypic DST, the sensitivity and specificity of the RDBH assay for resistance detection were 63.8% and 100.0% for OFX, 60.0% and 100.0% for KN, 61.5% and 98.1% for AMK, 50.0% and 99.3% for CPM, and 55.6% and 100% for SLIDs, respectively; compared to sequencing, the sensitivity and specificity of the RDBH assay were 95.2% and 100.0% for OFX, 93.8% and 100.0% for SLIDs or KN (both based on mutations in rrs 1400 region and eis promoter), and 91.6% and 100.0% for AMK or CPM (both based on mutations in rrs 1400 region), respectively. The turnaround time of the RDBH assay was 7 h for testing 42 samples. Conclusion Our data suggested that compared to sequencing, the RDBH assay could serve as a rapid and reliable method for testing the resistance of M. tuberculosis against OFX and SLIDs, enabling early administration of appropriate treatment regimens among MDR tuberculosis patients.
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Affiliation(s)
- Guilian Li
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China
| | - Qian Guo
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China.,Department of Molecular Biology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, People's Republic of China
| | - Haican Liu
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China
| | - Li Wan
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China
| | - Yi Jiang
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China
| | - Machao Li
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China
| | - Li-Li Zhao
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China
| | - Xiuqin Zhao
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China
| | - Zhiguang Liu
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China
| | - Kanglin Wan
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China
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