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Dippenaar A, Costa Conceição E, Wells F, Loubser J, Mann B, De Diego Fuertes M, Rennie V, Warren RM, Van Rie A. Exploring the potential of Oxford Nanopore Technologies sequencing for Mycobacterium tuberculosis sequencing: An assessment of R10 flowcells and V14 chemistry. PLoS One 2024; 19:e0303938. [PMID: 38843147 PMCID: PMC11156342 DOI: 10.1371/journal.pone.0303938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 05/03/2024] [Indexed: 06/09/2024] Open
Abstract
Oxford Nanopore Technologies (ONT) sequencing is a promising technology. We assessed the performance of the new ONT R10 flowcells and V14 rapid sequencing chemistry for Mtb whole genome sequencing of Mycobacterium tuberculosis (Mtb) DNA extracted from clinical primary liquid cultures (CPLCs). Using the recommended protocols for MinION Mk1C, R10.4.1 MinION flowcells, and the ONT Rapid Sequencing Kit V14 on six CPLC samples, we obtained a pooled library yield of 10.9 ng/μl, generated 1.94 Gb of sequenced bases and 214k reads after 48h in a first sequencing run. Only half (49%) of all generated reads met the Phred Quality score threshold (>8). To assess if the low data output and sequence quality were due to impurities present in DNA extracted directly from CPLCs, we added a pre-library preparation bead-clean-up step and included purified DNA obtained from an Mtb subculture as a control sample in a second sequencing run. The library yield for DNA extracted from four CPLCs and one Mtb subculture (control) was similar (10.0 ng/μl), 2.38 Gb of bases and 822k reads were produced. The quality was slightly better with 66% of the produced reads having a Phred Quality >8. A third run of DNA from six CPLCs with bead clean-up pre-processing produced a low library yield (±1 Gb of bases, 166k reads) of low quality (51% of reads with a Phred Quality score >8). A median depth of coverage above 10× was only achieved for five of 17 (29%) sequenced libraries. Compared to Illumina WGS of the same samples, accurate lineage predictions and full drug resistance profiles from the generated ONT data could not be determined by TBProfiler. Further optimization of the V14 ONT rapid sequencing chemistry and library preparation protocol is needed for clinical Mtb WGS applications.
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Affiliation(s)
- Anzaan Dippenaar
- Department of Family Medicine and Population Health, Global Health Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Emilyn Costa Conceição
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Felicia Wells
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Johannes Loubser
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Brendon Mann
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Miguel De Diego Fuertes
- Department of Family Medicine and Population Health, Global Health Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Vincent Rennie
- Department of Family Medicine and Population Health, Global Health Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Robin Mark Warren
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Annelies Van Rie
- Department of Family Medicine and Population Health, Global Health Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
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Kwak N, Lee S, Kim S, Song E, Yim JJ, Shim TS, Jeon D, Jhun BW, Seok KH, Kim S, Kwon S, Mok J. QMAC-DST for Rapid Detection of Drug Resistance in Pulmonary Tuberculosis Patients: A Multicenter Pre-Post Comparative Study. J Clin Med 2024; 13:2941. [PMID: 38792481 PMCID: PMC11122353 DOI: 10.3390/jcm13102941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Revised: 04/16/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
Background/Objectives: This study explores the impact of QMAC-DST, a rapid, fully automated phenotypic drug susceptibility test (pDST), on the treatment of tuberculosis (TB) patients. Methods: This pre-post comparative study, respectively, included pulmonary TB patients who began TB treatment between 1 December 2020 and 31 October 2021 (pre-period; pDST using the Löwenstein-Jensen (LJ) DST (M-kit DST)) and between 1 November 2021 and 30 September 2022 (post-period; pDST using the QMAC-DST) in five university-affiliated tertiary care hospitals in South Korea. We compared the turnaround times (TATs) of pDSTs and the time to appropriate treatment for patients whose anti-TB drugs were changed based on these tests between the groups. All patients were permitted to use molecular DSTs (mDSTs). Results: A total of 182 patients (135 in the M-kit DST group and 47 in the QMAC-DST group) were included. The median TAT was 36 days for M-kit DST (interquartile range (IQR), 30-39) and 12 days for QMAC-DST (IQR, 9-15), with the latter being significantly shorter (p < 0.001). Of the total patients, 10 (5.5%) changed their anti-TB drugs based on the mDST or pDST results after initiating TB treatment (8 in the M-kit DST group and 2 in the QMAC-DST group). In the M-kit DST group, three (37.5%) patients changed anti-TB drugs based on the pDST results. In the QMAC-DST group, all changes were due to mDST results; therefore, calculating the time to appropriate treatment for patients whose anti-TB drugs were changed based on pDST results was not feasible. In the QMAC-DST group, 46.8% of patients underwent the first-line line probe assay compared to 100.0% in the M-kit DST group (p < 0.001), indicating that rapid QMAC-DST results provide quicker assurance of the ongoing treatment by confirming susceptibility to the current anti-TB drugs. Conclusions: QMAC-DST delivers pDST results more rapidly than LJ-DST, ensuring faster confirmation for the current treatment regimen.
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Affiliation(s)
- Nakwon Kwak
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Hospital, Seoul 03080, Republic of Korea; (N.K.)
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Sangyeop Lee
- QuantaMatrix Inc., 131 Gasan digital 1-ro, Geumcheon-gu, Seoul 08506, Republic of Korea; (S.L.)
| | - Suyeoun Kim
- QuantaMatrix Inc., 131 Gasan digital 1-ro, Geumcheon-gu, Seoul 08506, Republic of Korea; (S.L.)
| | - Eunbee Song
- QuantaMatrix Inc., 131 Gasan digital 1-ro, Geumcheon-gu, Seoul 08506, Republic of Korea; (S.L.)
| | - Jae-Joon Yim
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Hospital, Seoul 03080, Republic of Korea; (N.K.)
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Tae Sun Shim
- Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Republic of Korea
| | - Doosoo Jeon
- Department of Internal Medicine, Pusan National University Yangsan Hospital, Yangsan 50612, Republic of Korea
- Department of Internal Medicine, Pusan National University School of Medicine, Busan 49241, Republic of Korea
| | - Byung Woo Jhun
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Kwang-Hyuk Seok
- Department of Laboratory Medicine, The Korean Institute of Tuberculosis, Cheongju 28158, Republic of Korea
| | - Saerom Kim
- Department of Internal Medicine, Pusan National University Hospital, 179 Gudeok-ro, Seo-gu, Busan 49241, Republic of Korea
| | - Sunghoon Kwon
- QuantaMatrix Inc., 131 Gasan digital 1-ro, Geumcheon-gu, Seoul 08506, Republic of Korea; (S.L.)
| | - Jeongha Mok
- Department of Internal Medicine, Pusan National University School of Medicine, Busan 49241, Republic of Korea
- Department of Internal Medicine, Pusan National University Hospital, 179 Gudeok-ro, Seo-gu, Busan 49241, Republic of Korea
- Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea
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Dippenaar A, Ismail N, Heupink TH, Grobbelaar M, Loubser J, Van Rie A, Warren RM. Droplet based whole genome amplification for sequencing minute amounts of purified Mycobacterium tuberculosis DNA. Sci Rep 2024; 14:9931. [PMID: 38689002 PMCID: PMC11061190 DOI: 10.1038/s41598-024-60545-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 04/24/2024] [Indexed: 05/02/2024] Open
Abstract
Implementation of whole genome sequencing (WGS) for patient care is hindered by limited Mycobacterium tuberculosis (Mtb) in clinical specimens and slow Mtb growth. We evaluated droplet multiple displacement amplification (dMDA) for amplification of minute amounts of Mtb DNA to enable WGS as an alternative to other Mtb enrichment methods. Purified genomic Mtb-DNA (0.1, 0.5, 1, and 5 pg) was encapsulated and amplified using the Samplix Xdrop-instrument and sequenced alongside a control sample using standard Illumina protocols followed by MAGMA-analysis. The control and 5 pg input dMDA samples underwent nanopore sequencing followed by Nanoseq and TB-profiler analysis. dMDA generated 105-2400 ng DNA from the 0.1-5 pg input DNA, respectively. Followed by Illumina WGS, dMDA raised mean sequencing depth from 7 × for 0.1 pg input DNA to ≥ 60 × for 5 pg input and the control sample. Bioinformatic analysis revealed a high number of false positive and false negative variants when amplifying ≤ 0.5 pg input DNA. Nanopore sequencing of the 5 pg dMDA sample presented excellent coverage depth, breadth, and accurate strain characterization, albeit elevated false positive and false negative variants compared to Illumina-sequenced dMDA sample with identical Mtb DNA input. dMDA coupled with Illumina WGS for samples with ≥ 5 pg purified Mtb DNA, equating to approximately 1000 copies of the Mtb genome, offers precision for drug resistance, phylogeny, and transmission insights.
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Affiliation(s)
- Anzaan Dippenaar
- Tuberculosis Omics Research Consortium, Department of Family Medicine and Population Health, Global Health Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium.
| | - Nabila Ismail
- South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Tim H Heupink
- Tuberculosis Omics Research Consortium, Department of Family Medicine and Population Health, Global Health Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Melanie Grobbelaar
- South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Johannes Loubser
- South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Annelies Van Rie
- Tuberculosis Omics Research Consortium, Department of Family Medicine and Population Health, Global Health Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Robin M Warren
- South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
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Umpeleva T, Chetverikova E, Belyaev D, Eremeeva N, Boteva T, Golubeva L, Vakhrusheva D, Vasilieva I. Identification of genetic determinants of bedaquiline resistance in Mycobacterium tuberculosis in Ural region, Russia. Microbiol Spectr 2024; 12:e0374923. [PMID: 38345388 PMCID: PMC10913728 DOI: 10.1128/spectrum.03749-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/24/2024] [Indexed: 03/06/2024] Open
Abstract
Collecting data on rare Mycobacterium tuberculosis (Mtb) clinical isolates with resistance to the new anti-tuberculosis drug bedaquiline is an important task for improving antimicrobial susceptibility testing methods. Nanopore whole genome sequencing, the proportion method on Middlebrook 7H11 medium, and BACTEC MGIT 960 assays were used to analyze genotypic and phenotypic resistance to bedaquiline. We found four mutations: atpE I66M, atpE А63Р, Rv0678 А36Т, and Rv0678 S53P in five isolates with different levels of phenotypic bedaquiline resistance. IMPORTANCE Bedaquiline (BDQ) is a new anti-tuberculosis drug. The phenotypic and genotypic data describing the mechanism of drug resistance are critical for the design of rapid and accurate diagnostic tests. We consider that our work, which describes genotypic and phenotypic resistance to BDQ, can contribute to the standardization of drug susceptibility testing.
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Affiliation(s)
- Tatiana Umpeleva
- Department of Microbiology and Preclinical Research, National Medical Research Center of Phthisiopulmonology and Infection Disease, Yekaterinburg, Russia
| | - Elena Chetverikova
- Department of Microbiology and Preclinical Research, National Medical Research Center of Phthisiopulmonology and Infection Disease, Yekaterinburg, Russia
| | - Danila Belyaev
- Department of Microbiology and Preclinical Research, National Medical Research Center of Phthisiopulmonology and Infection Disease, Yekaterinburg, Russia
- Laboratory of Medical Chemistry, Postovsky Institute of Organic Synthesis, Ural Branch of the Russian Academy of Sciences, Yekaterinburg, Russia
| | - Natalya Eremeeva
- Department of Microbiology and Preclinical Research, National Medical Research Center of Phthisiopulmonology and Infection Disease, Yekaterinburg, Russia
| | - Tatiana Boteva
- Department of Microbiology and Preclinical Research, National Medical Research Center of Phthisiopulmonology and Infection Disease, Yekaterinburg, Russia
| | - Ludmila Golubeva
- Department of Microbiology and Preclinical Research, National Medical Research Center of Phthisiopulmonology and Infection Disease, Yekaterinburg, Russia
| | - Diana Vakhrusheva
- Department of Microbiology and Preclinical Research, National Medical Research Center of Phthisiopulmonology and Infection Disease, Yekaterinburg, Russia
| | - Irina Vasilieva
- Administration, National Medical Research Center of Phthisiopulmonology and Infection Disease, Moscow, Russia
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Hall MB, Coin LJM. Pangenome databases improve host removal and mycobacteria classification from clinical metagenomic data. Gigascience 2024; 13:giae010. [PMID: 38573185 PMCID: PMC10993716 DOI: 10.1093/gigascience/giae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 01/10/2024] [Accepted: 02/27/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Culture-free real-time sequencing of clinical metagenomic samples promises both rapid pathogen detection and antimicrobial resistance profiling. However, this approach introduces the risk of patient DNA leakage. To mitigate this risk, we need near-comprehensive removal of human DNA sequences at the point of sequencing, typically involving the use of resource-constrained devices. Existing benchmarks have largely focused on the use of standardized databases and largely ignored the computational requirements of depletion pipelines as well as the impact of human genome diversity. RESULTS We benchmarked host removal pipelines on simulated and artificial real Illumina and Nanopore metagenomic samples. We found that construction of a custom kraken database containing diverse human genomes results in the best balance of accuracy and computational resource usage. In addition, we benchmarked pipelines using kraken and minimap2 for taxonomic classification of Mycobacterium reads using standard and custom databases. With a database representative of the Mycobacterium genus, both tools obtained improved specificity and sensitivity, compared to the standard databases for classification of Mycobacterium tuberculosis. Computational efficiency of these custom databases was superior to most standard approaches, allowing them to be executed on a laptop device. CONCLUSIONS Customized pangenome databases provide the best balance of accuracy and computational efficiency when compared to standard databases for the task of human read removal and M. tuberculosis read classification from metagenomic samples. Such databases allow for execution on a laptop, without sacrificing accuracy, an especially important consideration in low-resource settings. We make all customized databases and pipelines freely available.
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Affiliation(s)
- Michael B Hall
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, 3000 Victoria, Australia
| | - Lachlan J M Coin
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, 3000 Victoria, Australia
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Walter KS, Cohen T, Mathema B, Colijn C, Sobkowiak B, Comas I, Goig GA, Croda J, Andrews JR. Signatures of transmission in within-host M. tuberculosis variation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.28.23300451. [PMID: 38234741 PMCID: PMC10793532 DOI: 10.1101/2023.12.28.23300451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Background Because M. tuberculosis evolves slowly, transmission clusters often contain multiple individuals with identical consensus genomes, making it difficult to reconstruct transmission chains. Finding additional sources of shared M. tuberculosis variation could help overcome this problem. Previous studies have reported M. tuberculosis diversity within infected individuals; however, whether within-host variation improves transmission inferences remains unclear. Methods To evaluate the transmission information present in within-host M. tuberculosis variation, we re-analyzed publicly available sequence data from three household transmission studies, using household membership as a proxy for transmission linkage between donor-recipient pairs. Findings We found moderate levels of minority variation present in M. tuberculosis sequence data from cultured isolates that varied significantly across studies (mean: 6, 7, and 170 minority variants above a 1% minor allele frequency threshold, outside of PE/PPE genes). Isolates from household members shared more minority variants than did isolates from unlinked individuals in the three studies (mean 98 shared minority variants vs. 10; 0.8 vs. 0.2, and 0.7 vs. 0.2, respectively). Shared within-host variation was significantly associated with household membership (OR: 1.51 [1.30,1.71], for one standard deviation increase in shared minority variants). Models that included shared within-host variation improved the accuracy of predicting household membership in all three studies as compared to models without within-host variation (AUC: 0.95 versus 0.92, 0.99 versus 0.95, and 0.93 versus 0.91). Interpretation Within-host M. tuberculosis variation persists through culture and could enhance the resolution of transmission inferences. The substantial differences in minority variation recovered across studies highlights the need to optimize approaches to recover and incorporate within-host variation into automated phylogenetic and transmission inference. Funding NIAID: 5K01AI173385.
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Affiliation(s)
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, USA
| | - Barun Mathema
- Department of Epidemiology, Columbia University Mailman School of Public Health; New York, United States
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University; Burnaby, Canada
| | - Benjamin Sobkowiak
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, USA
| | - Iñaki Comas
- Institute of Biomedicine of Valencia (CSIC), Valencia, Spain
| | - Galo A Goig
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Julio Croda
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, USA
- Federal University of Mato Grosso do Sul - UFMS, Campo Grande, MS, Brazil
- Oswaldo Cruz Foundation Mato Grosso do Sul, Mato Grosso do Sul, Brazil
| | - Jason R Andrews
- Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA
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Hemeg HA, Albulushi HO, Ozbak HA, Ali HM, Alahmadi EK, Almutawif YA, Alhuofie ST, Alaeq RA, Alhazmi AA, Najim MA, Hanafy AM. Evaluating the Sensitivity of Different Molecular Techniques for Detecting Mycobacterium tuberculosis Complex in Patients with Pulmonary Infection. Pol J Microbiol 2023; 72:421-431. [PMID: 37934050 PMCID: PMC10725165 DOI: 10.33073/pjm-2023-040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 10/04/2023] [Indexed: 11/08/2023] Open
Abstract
This study aimed to evaluate the accuracy of detecting drug-resistant Mycobacterium tuberculosis complex (MTBC)-specific DNA in sputum specimens from 48 patients diagnosed with pulmonary tuberculosis. The presence of MTBC DNA in the specimens was validated using the GeneXpert MTB/RIF system and compared with a specific PCR assay targeting the IS6110 and the mtp40 gene sequence fragments. Additionally, the results obtained by multiplex PCR assays to detect the most frequently encountered rifampin, isoniazid, and ethambutol resistance-conferring mutations were matched with those obtained by GeneXpert and phenotypic culture-based drug susceptibility tests. Of the 48 sputum samples, 25 were positive for MTBC using the GeneXpert MTB/RIF test. Nevertheless, the IS6110 and mtp40 single-step PCR revealed the IS6110 in 27 of the 48 sputum samples, while the mtp40 gene fragment was found in only 17 of them. Furthermore, multiplex PCR assays detected drug-resistant conferring mutations in 21 (77.8%) of the 27 samples with confirmed MTBC DNA, 10 of which contained single drug-resistant conferring mutations towards ethambutol and two towards rifampin, and the remaining nine contained double-resistant mutations for ethambutol and rifampin. In contrast, only five sputum specimens (18.5%) contained drug-resistant MTBC isolates, and two contained mono-drug-resistant MTBC species toward ethambutol and rifampin, respectively, and the remaining three were designated as multi-drug resistant toward both drugs using GeneXpert and phenotypic culture-based drug susceptibility tests. Such discrepancies in the results emphasize the need to develop novel molecular tests that associate with phenotypic non-DNA-based assays to improve the detection of drug-resistant isolates in clinical specimens in future studies.
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Affiliation(s)
- Hassan A. Hemeg
- Medical Laboratory Technology Department, College of Applied Medical Sciences, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
| | - Hamzah O. Albulushi
- Biology Department, College of Science, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
| | - Hani A. Ozbak
- Medical Laboratory Technology Department, College of Applied Medical Sciences, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
| | - Hamza M. Ali
- Medical Laboratory Technology Department, College of Applied Medical Sciences, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
| | - Emad K. Alahmadi
- Medical Laboratory Technology Department, College of Applied Medical Sciences, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
| | - Yahya A. Almutawif
- Medical Laboratory Technology Department, College of Applied Medical Sciences, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
| | - Sari T. Alhuofie
- Medical Laboratory Technology Department, College of Applied Medical Sciences, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
| | - Rana A. Alaeq
- Medical Laboratory Technology Department, College of Applied Medical Sciences, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
| | - Areej A. Alhazmi
- Medical Laboratory Technology Department, College of Applied Medical Sciences, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
| | - Mustafa A. Najim
- Medical Laboratory Technology Department, College of Applied Medical Sciences, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
| | - Ahmed M. Hanafy
- Biology Department, College of Science, Taibah University, Al-Madinah, Kingdom of Saudi Arabia
- Department of Microbiology, Faculty of Science, Ain Shams University, Cairo, Egypt
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Ismail N, Dippenaar A, Morgan G, Grobbelaar M, Wells F, Caffry J, Morais C, Gizynski K, McGurk D, Boada E, Murton H, Warren RM, Van Rie A. Microfluidic Capture of Mycobacterium tuberculosis from Clinical Samples for Culture-Free Whole-Genome Sequencing. Microbiol Spectr 2023; 11:e0111423. [PMID: 37358439 PMCID: PMC10433858 DOI: 10.1128/spectrum.01114-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 05/25/2023] [Indexed: 06/27/2023] Open
Abstract
Mycobacterium tuberculosis whole-genome sequencing (WGS) is a powerful tool as it can provide data on population diversity, drug resistance, disease transmission, and mixed infections. Successful WGS is still reliant on high concentrations of DNA obtained through M. tuberculosis culture. Microfluidics technology plays a valuable role in single-cell research but has not yet been assessed as a bacterial enrichment strategy for culture-free WGS of M. tuberculosis. In a proof-of-principle study, we evaluated the use of Capture-XT, a microfluidic lab-on-chip cleanup and pathogen concentration platform to enrich M. tuberculosis bacilli from clinical sputum specimens for downstream DNA extraction and WGS. Three of the four (75%) samples processed by the microfluidics application passed the library preparation quality control, compared to only one of the four (25%) samples not enriched by the microfluidics M. tuberculosis capture application. WGS data were of sufficient quality, with mapping depth of ≥25× and 9 to 27% of reads mapping to the reference genome. These results suggest that microfluidics-based M. tuberculosis cell capture might be a promising method for M. tuberculosis enrichment in clinical sputum samples, which could facilitate culture-free M. tuberculosis WGS. IMPORTANCE Diagnosis of tuberculosis is effective using molecular methods; however, a comprehensive characterization of the resistance profile of Mycobacterium tuberculosis often requires culturing and phenotypic drug susceptibility testing or culturing followed by whole-genome sequencing (WGS). The phenotypic route can take anywhere from 1 to >3 months to result, by which point the patient may have acquired additional drug resistance. The WGS route is a very attractive option; however, culturing is the rate-limiting step. In this original article, we provide proof-of-principle evidence that microfluidics-based cell capture can be used on high-bacillary-load clinical samples for culture-free WGS.
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Affiliation(s)
- Nabila Ismail
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Anzaan Dippenaar
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Tuberculosis Omics Research Consortium, Family Medicine and Population Health, Institute of Global Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | | | - Melanie Grobbelaar
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Felicia Wells
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | | | | | | | - David McGurk
- QuantuMDx Ltd., Newcastle upon Tyne, United Kingdom
| | | | | | - Robin M. Warren
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Annelies Van Rie
- Tuberculosis Omics Research Consortium, Family Medicine and Population Health, Institute of Global Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
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Su J, Lui WW, Lee Y, Zheng Z, Siu GKH, Ng TTL, Zhang T, Lam TTY, Lao HY, Yam WC, Tam KKG, Leung KSS, Lam TW, Leung AWS, Luo R. Evaluation of Mycobacterium tuberculosis enrichment in metagenomic samples using ONT adaptive sequencing and amplicon sequencing for identification and variant calling. Sci Rep 2023; 13:5237. [PMID: 37002338 PMCID: PMC10066345 DOI: 10.1038/s41598-023-32378-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 03/27/2023] [Indexed: 04/03/2023] Open
Abstract
Sensitive detection of Mycobacterium tuberculosis (TB) in small percentages in metagenomic samples is essential for microbial classification and drug resistance prediction. However, traditional methods, such as bacterial culture and microscopy, are time-consuming and sometimes have limited TB detection sensitivity. Oxford nanopore technologies (ONT) MinION sequencing allows rapid and simple sample preparation for sequencing. Its recently developed adaptive sequencing selects reads from targets while allowing real-time base-calling to achieve sequence enrichment or depletion during sequencing. Another common enrichment method is PCR amplification of the target TB genes. In this study, we compared both methods using ONT MinION sequencing for TB detection and variant calling in metagenomic samples using both simulation runs and those with synthetic and patient samples. We found that both methods effectively enrich TB reads from a high percentage of human (95%) and other microbial DNA. Adaptive sequencing with readfish and UNCALLDE achieved a 3.9-fold and 2.2-fold enrichment compared to the control run. We provide a simple automatic analysis framework to support the detection of TB for clinical use, openly available at https://github.com/HKU-BAL/ONT-TB-NF . Depending on the patient's medical condition and sample type, we recommend users evaluate and optimize their workflow for different clinical specimens to improve the detection limit.
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Affiliation(s)
- Junhao Su
- Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Wui Wang Lui
- Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - YanLam Lee
- Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Zhenxian Zheng
- Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Gilman Kit-Hang Siu
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China
| | - Timothy Ting-Leung Ng
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China
| | - Tong Zhang
- Department of Computer Science and Engineering, Department of Mathematics, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR, China
| | - Tommy Tsan-Yuk Lam
- State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health Limited, 19W Hong Kong Science & Technology Parks, Pak Shek Kok, Hong Kong SAR, China
| | - Hiu-Yin Lao
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China
| | - Wing-Cheong Yam
- Department of Microbiology, Lee Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Kingsley King-Gee Tam
- Department of Microbiology, Lee Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Kenneth Siu-Sing Leung
- Department of Microbiology, Lee Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Tak-Wah Lam
- Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Amy Wing-Sze Leung
- Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China.
| | - Ruibang Luo
- Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China.
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10
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In silico evaluation of WHO-endorsed molecular methods to detect drug resistant tuberculosis. Sci Rep 2022; 12:17741. [PMID: 36273016 PMCID: PMC9587982 DOI: 10.1038/s41598-022-21025-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 09/21/2022] [Indexed: 01/18/2023] Open
Abstract
Universal drug susceptibility testing (DST) for tuberculosis is a major goal of the END TB strategy. PCR-based molecular diagnostic tests have been instrumental in increasing DST globally and several assays have now been endorsed by the World Health Organization (WHO) for use in the diagnosis of drug resistance. These endorsed assays, however, each interrogate a limited number of mutations associated with resistance, potentially limiting their sensitivity compared to sequencing-based methods. We applied an in silico method to compare the sensitivity and specificity of WHO-endorsed molecular based diagnostics to the mutation set identified by the WHO mutations catalogue using phenotypic DST as the reference. We found that, in silico, the mutation sets used by probe-based molecular diagnostic tests to identify rifampicin, isoniazid, pyrazinamide, levofloxacin, moxifloxacin, amikacin, capreomycin and kanamycin resistance produced similar sensitivities and specificities to the WHO mutation catalogue. PCR-based diagnostic tests were most sensitive for drugs where mechanisms of resistance are well established and localised to small genetic regions or a few prevalent mutations. Approaches using sequencing technologies can provide advantages for drugs where our knowledge of resistance is limited, or where complex resistance signatures exist.
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11
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Dookie N, Khan A, Padayatchi N, Naidoo K. Application of Next Generation Sequencing for Diagnosis and Clinical Management of Drug-Resistant Tuberculosis: Updates on Recent Developments in the Field. Front Microbiol 2022; 13:775030. [PMID: 35401475 PMCID: PMC8988194 DOI: 10.3389/fmicb.2022.775030] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 02/17/2022] [Indexed: 11/30/2022] Open
Abstract
The World Health Organization’s End TB Strategy prioritizes universal access to an early diagnosis and comprehensive drug susceptibility testing (DST) for all individuals with tuberculosis (TB) as a key component of integrated, patient-centered TB care. Next generation whole genome sequencing (WGS) and its associated technology has demonstrated exceptional potential for reliable and comprehensive resistance prediction for Mycobacterium tuberculosis isolates, allowing for accurate clinical decisions. This review presents a descriptive analysis of research describing the potential of WGS to accelerate delivery of individualized care, recent advances in sputum-based WGS technology and the role of targeted sequencing for resistance detection. We provide an update on recent research describing the mechanisms of resistance to new and repurposed drugs and the dynamics of mixed infections and its potential implication on TB diagnosis and treatment. Whilst the studies reviewed here have greatly improved our understanding of recent advances in this arena, it highlights significant challenges that remain. The wide-spread introduction of new drugs in the absence of standardized DST has led to rapid emergence of drug resistance. This review highlights apparent gaps in our knowledge of the mechanisms contributing to resistance for these new drugs and challenges that limit the clinical utility of next generation sequencing techniques. It is recommended that a combination of genotypic and phenotypic techniques is warranted to monitor treatment response, curb emerging resistance and further dissemination of drug resistance.
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Affiliation(s)
- Navisha Dookie
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa
- *Correspondence: Navisha Dookie,
| | - Azraa Khan
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa
| | - Nesri Padayatchi
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa
- South African Medical Research Council (SAMRC), CAPRISA HIV-TB Pathogenesis and Treatment Research Unit, Durban, South Africa
| | - Kogieleum Naidoo
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa
- South African Medical Research Council (SAMRC), CAPRISA HIV-TB Pathogenesis and Treatment Research Unit, Durban, South Africa
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12
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Saeed DK, Shakoor S, Razzak SA, Hasan Z, Sabzwari SF, Azizullah Z, Kanji A, Nasir A, Shafiq S, Ghanchi NK, Hasan R. Variants associated with Bedaquiline (BDQ) resistance identified in Rv0678 and efflux pump genes in Mycobacterium tuberculosis isolates from BDQ naïve TB patients in Pakistan. BMC Microbiol 2022; 22:62. [PMID: 35209842 PMCID: PMC8876534 DOI: 10.1186/s12866-022-02475-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 02/15/2022] [Indexed: 11/16/2022] Open
Abstract
Background Mutations in the Rv0678, pepQ and atpE genes of Mycobacterium tuberculosis (MTB) have been reported to be associated with reduced antimycobacterial susceptibility to bedaquiline (BDQ). Resistance conferring mutations in treatment naïve MTB strains is likely to have implications for BDQ based new drug regimen that aim to shorten treatment duration. We therefore investigated the genetic basis of resistance to BDQ in MTB clinical isolates from BDQ naïve TB patients from Pakistan. In addition, mutations in genes associated with efflux pumps were investigated as an alternate mechanism of resistance. Methods Based on convenience sampling, we studied 48 MTB clinical isolates from BDQ naïve TB patients. These isolates (from our strain bank) included 38 MDR/pre-XDR/XDR (10 BDQ resistant, 8 BDQ intermediate and 20 BDQ susceptible) and 10 pan drug susceptible MTB isolates. All strains were subjected to whole genome sequencing and genomes were analysed to identify variants in Rv0678, pepQ, atpE, Rv1979c, mmpLS and mmpL5 and drug resistance associated efflux pump genes. Results Of the BDQ resistant and intermediate strains 44% (8/18) had variants in Rv0678 including; two reported mutations S63R/G, six previously unreported variants; L40F, R50Q and R107C and three frameshift mutations; G25fs, D64fs and D109fs. Variants in efflux pumps; Rv1273c (G462K), Rv0507c (R426H) and Rv1634c (E198R) were found to be present in drug resistant isolates including BDQ resistant and intermediate isolates. E198R in efflux pump gene Rv1634c was the most frequently occurring variant in BDQ resistant and intermediate isolates (n = 10). Conclusion We found RAVs in Rv0678 to be commonly associated with BDQ resistance. Further confirmation of the role of variants in efflux pump genes in resistance is required so that they may be incorporated in genome-based diagnostics for drug resistant MTB. Supplementary Information The online version contains supplementary material available at 10.1186/s12866-022-02475-4.
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Affiliation(s)
- Dania Khalid Saeed
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan
| | - Sadia Shakoor
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan
| | - Safina Abdul Razzak
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan
| | - Zahra Hasan
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan
| | - Saba Faraz Sabzwari
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan
| | - Zahida Azizullah
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan
| | - Akbar Kanji
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan
| | - Asghar Nasir
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan
| | - Samreen Shafiq
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan
| | - Najia Karim Ghanchi
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan
| | - Rumina Hasan
- Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan. .,Faculty of Infectious and Tropical Diseases, London School Hygiene and Tropical Medicine, London, UK.
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13
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Dippenaar A, Goossens SN, Grobbelaar M, Oostvogels S, Cuypers B, Laukens K, Meehan CJ, Warren RM, van Rie A. Nanopore Sequencing for Mycobacterium tuberculosis: a Critical Review of the Literature, New Developments, and Future Opportunities. J Clin Microbiol 2022; 60:e0064621. [PMID: 34133895 PMCID: PMC8769739 DOI: 10.1128/jcm.00646-21] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
The next-generation, short-read sequencing technologies that generate comprehensive, whole-genome data with single nucleotide resolution have already advanced tuberculosis diagnosis, treatment, surveillance, and source investigation. Their high costs, tedious and lengthy processes, and large equipment remain major hurdles for research use in high tuberculosis burden countries and implementation into routine care. The portable next-generation sequencing devices developed by Oxford Nanopore Technologies (ONT) are attractive alternatives due to their long-read sequence capability, compact low-cost hardware, and continued improvements in accuracy and throughput. A systematic review of the published literature demonstrated limited uptake of ONT sequencing in tuberculosis research and clinical care. Of the 12 eligible articles presenting ONT sequencing data on at least one Mycobacterium tuberculosis sample, four addressed software development for long-read ONT sequencing data with potential applications for M. tuberculosis. Only eight studies presented results of ONT sequencing of M. tuberculosis, of which five performed whole-genome and three did targeted sequencing. Based on these findings, we summarize the standard processes, reflect on the current limitations of ONT sequencing technology, and the research needed to overcome the main hurdles. The low capital cost, portable nature and continued improvement in the performance of ONT sequencing make it an attractive option for sequencing for research and clinical care, but limited data are available on its application in the tuberculosis field. Important research investment is needed to unleash the full potential of ONT sequencing for tuberculosis research and care.
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Affiliation(s)
- Anzaan Dippenaar
- Tuberculosis Omics Research Consortium, Family Medicine and Population Health, Institute of Global Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
- Unit of Mycobacteriology, Institute of Tropical Medicine, Antwerp, Belgium
| | - Sander N. Goossens
- Tuberculosis Omics Research Consortium, Family Medicine and Population Health, Institute of Global Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Melanie Grobbelaar
- Department of Science and Innovation-National Research Foundation Centre for Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Selien Oostvogels
- Tuberculosis Omics Research Consortium, Family Medicine and Population Health, Institute of Global Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Bart Cuypers
- Department of Computer Science, University of Antwerp, Antwerp, Belgium
- Molecular Parasitology Group, Institute of Tropical Medicine, Antwerp, Belgium
| | - Kris Laukens
- Molecular Parasitology Group, Institute of Tropical Medicine, Antwerp, Belgium
| | - Conor J. Meehan
- Unit of Mycobacteriology, Institute of Tropical Medicine, Antwerp, Belgium
- School of Chemistry and Bioscience, Faculty of Life Science, University of Bradford, Bradford, West Yorkshire, United Kingdom
| | - Robin M. Warren
- Department of Science and Innovation-National Research Foundation Centre for Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Annelies van Rie
- Tuberculosis Omics Research Consortium, Family Medicine and Population Health, Institute of Global Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
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14
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Sharma A, Machado E, Lima KVB, Suffys PN, Conceição EC. Tuberculosis drug resistance profiling based on machine learning: A literature review. Braz J Infect Dis 2022; 26:102332. [PMID: 35176257 PMCID: PMC9387475 DOI: 10.1016/j.bjid.2022.102332] [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: 10/18/2021] [Revised: 12/18/2021] [Accepted: 01/01/2022] [Indexed: 11/30/2022] Open
Abstract
Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), is one of the top 10 causes of death worldwide. Drug-resistant tuberculosis (DR-TB) poses a major threat to the World Health Organization's “End TB” strategy which has defined its target as the year 2035. In 2019, there were close to 0.5 million cases of DRTB, of which 78% were resistant to multiple TB drugs. The traditional culture-based drug susceptibility test (DST - the current gold standard) often takes multiple weeks and the necessary laboratory facilities are not readily available in low-income countries. Whole genome sequencing (WGS) technology is rapidly becoming an important tool in clinical and research applications including transmission detection or prediction of DR-TB. For the latter, many tools have recently been developed using curated database(s) of known resistance conferring mutations. However, documenting all the mutations and their effect is a time-taking and a continuous process and therefore Machine Learning (ML) techniques can be useful for predicting the presence of DR-TB based on WGS data. This can pave the way to an earlier detection of drug resistance and consequently more efficient treatment when compared to the traditional DST.
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15
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Gliddon HD, Frampton D, Munsamy V, Heaney J, Pataillot-Meakin T, Nastouli E, Pym AS, Steyn AJC, Pillay D, McKendry RA. A Rapid Drug Resistance Genotyping Workflow for Mycobacterium tuberculosis, Using Targeted Isothermal Amplification and Nanopore Sequencing. Microbiol Spectr 2021; 9:e0061021. [PMID: 34817282 PMCID: PMC8612157 DOI: 10.1128/spectrum.00610-21] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 10/11/2021] [Indexed: 12/24/2022] Open
Abstract
Phenotypic drug susceptibility testing (DST) for tuberculosis (TB) requires weeks to yield results. Although molecular tests rapidly detect drug resistance-associated mutations (DRMs), they are not scalable to cover the full genome and the many DRMs that can predict resistance. Whole-genome sequencing (WGS) methods are scalable, but if conducted directly on sputum, typically require a target enrichment step, such as nucleic acid amplification. We developed a targeted isothermal amplification-nanopore sequencing workflow for rapid prediction of drug resistance of TB isolates. We used recombinase polymerase amplification (RPA) to perform targeted isothermal amplification (37°C for 90 min) of three regions within the Mycobacterium tuberculosis genome, followed by nanopore sequencing on the MinION. We tested 29 mycobacterial genomic DNA extracts from patients with drug-resistant (DR) TB and compared our results to those of WGS by Illumina and phenotypic DST to evaluate the accuracy of prediction of resistance to rifampin and isoniazid. Amplification by RPA showed fidelity equivalent to that of high-fidelity PCR (100% concordance). Nanopore sequencing generated DRM predictions identical to those of WGS, with considerably faster sequencing run times of minutes rather than days. The sensitivity and specificity of rifampin resistance prediction for our workflow were 96.3% (95% confidence interval [CI], 81.0 to 99.9%) and 100.0% (95% CI, 15.8 to 100.0%), respectively. For isoniazid resistance prediction, the sensitivity and specificity were 100.0% (95% CI, 86.3 to 100.0%) and 100.0% (95% CI, 39.8 to 100.0%), respectively. The workflow consumable costs per sample are less than £100. Our rapid and low-cost drug resistance genotyping workflow provides accurate prediction of rifampin and isoniazid resistance, making it appropriate for use in resource-limited settings. IMPORTANCE Current methods for diagnosing drug-resistant tuberculosis are time consuming, resulting in delays in patients receiving treatment and in transmission onwards. They also require a high level of laboratory infrastructure, which is often only available at centralized facilities, resulting in further delays to diagnosis and additional barriers to deployment in resource-limited settings. This article describes a new workflow that can diagnose drug-resistant TB in a shorter time, with less equipment, and for a lower price than current methods. The amount of TB DNA is first increased without the need for bulky and costly thermocycling equipment. The DNA is then read using a portable sequencer called a MinION, which indicates whether there are tell-tale changes in the DNA that indicate whether the TB strain is drug resistant. Our workflow could play an important role in the future in the fight against the public health challenge that is TB drug resistance.
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Affiliation(s)
- Harriet D. Gliddon
- London Centre for Nanotechnology, Faculty of Mathematics and Physical Sciences, University College London, London, United Kingdom
- National Public Health Speciality Training Programme, South West, United Kingdom
| | - Dan Frampton
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - Vanisha Munsamy
- Africa Health Research Institute, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Jude Heaney
- Department of Virology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Thomas Pataillot-Meakin
- Department of Virology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Eleni Nastouli
- Department of Virology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Alexander S. Pym
- Africa Health Research Institute, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Adrie J. C. Steyn
- Africa Health Research Institute, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Deenan Pillay
- Division of Infection and Immunity, University College London, London, United Kingdom
- Africa Health Research Institute, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Rachel A. McKendry
- London Centre for Nanotechnology, Faculty of Mathematics and Physical Sciences, University College London, London, United Kingdom
- Division of Medicine, University College London, London, United Kingdom
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16
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Cuevas-Córdoba B, Fresno C, Haase-Hernández JI, Barbosa-Amezcua M, Mata-Rocha M, Muñoz-Torrico M, Salazar-Lezama MA, Martínez-Orozco JA, Narváez-Díaz LA, Salas-Hernández J, González-Covarrubias V, Soberón X. A bioinformatics pipeline for Mycobacterium tuberculosis sequencing that cleans contaminant reads from sputum samples. PLoS One 2021; 16:e0258774. [PMID: 34699523 PMCID: PMC8547644 DOI: 10.1371/journal.pone.0258774] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 10/06/2021] [Indexed: 12/30/2022] Open
Abstract
Next-Generation Sequencing (NGS) is widely used to investigate genomic variation. In several studies, the genetic variation of Mycobacterium tuberculosis has been analyzed in sputum samples without previous culture, using target enrichment methodologies for NGS. Alignments obtained by different programs generally map the sequences under default parameters, and from these results, it is assumed that only Mycobacterium reads will be obtained. However, variants of interest microorganism in clinical samples can be confused with a vast collection of reads from other bacteria, viruses, and human DNA. Currently, there are no standardized pipelines, and the cleaning success is never verified since there is a lack of rigorous controls to identify and remove reads from other sputum-microorganisms genetically similar to M. tuberculosis. Therefore, we designed a bioinformatic pipeline to process NGS data from sputum samples, including several filters and quality control points to identify and eliminate non-M. tuberculosis reads to obtain a reliable genetic variant report. Our proposal uses the SURPI software as a taxonomic classifier to filter input sequences and perform a mapping that provides the highest percentage of Mycobacterium reads, minimizing the reads from other microorganisms. We then use the filtered sequences to perform variant calling with the GATK software, ensuring the mapping quality, realignment, recalibration, hard-filtering, and post-filter to increase the reliability of the reported variants. Using default mapping parameters, we identified reads of contaminant bacteria, such as Streptococcus, Rhotia, Actinomyces, and Veillonella. Our final mapping strategy allowed a sequence identity of 97.8% between the input reads and the whole M. tuberculosis reference genome H37Rv using a genomic edit distance of three, thus removing 98.8% of the off-target sequences with a Mycobacterium reads loss of 1.7%. Finally, more than 200 unreliable genetic variants were removed during the variant calling, increasing the report’s reliability.
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Affiliation(s)
- Betzaida Cuevas-Córdoba
- Laboratorio de Farmacogenómica, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, México
- Instituto de Investigaciones Biológicas, Universidad Veracruzana, Xalapa, Veracruz, México
| | - Cristóbal Fresno
- Departamento de Desarrollo Tecnológico, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, México
| | - Joshua I. Haase-Hernández
- Departamento de Desarrollo Tecnológico, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, México
| | - Martín Barbosa-Amezcua
- Laboratorio de Farmacogenómica, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, México
| | - Minerva Mata-Rocha
- Laboratorio de Farmacogenómica, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, México
| | - Marcela Muñoz-Torrico
- Clínica de Tuberculosis y Enfermedades Pleurales, Instituto Nacional de Enfermedades Respiratorias (INER), Ciudad de México, México
| | - Miguel A. Salazar-Lezama
- Clínica de Tuberculosis y Enfermedades Pleurales, Instituto Nacional de Enfermedades Respiratorias (INER), Ciudad de México, México
| | - José A. Martínez-Orozco
- Clínica de Tuberculosis y Enfermedades Pleurales, Instituto Nacional de Enfermedades Respiratorias (INER), Ciudad de México, México
| | - Luis A. Narváez-Díaz
- Clínica de Tuberculosis y Enfermedades Pleurales, Instituto Nacional de Enfermedades Respiratorias (INER), Ciudad de México, México
| | - Jorge Salas-Hernández
- Clínica de Tuberculosis y Enfermedades Pleurales, Instituto Nacional de Enfermedades Respiratorias (INER), Ciudad de México, México
| | - Vanessa González-Covarrubias
- Laboratorio de Farmacogenómica, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, México
- * E-mail: (XS); (VGC)
| | - Xavier Soberón
- Laboratorio de Farmacogenómica, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, México
- * E-mail: (XS); (VGC)
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17
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Maruri F, Guo Y, Blackman A, van der Heijden YF, Rebeiro PF, Sterling TR. Resistance-Conferring Mutations on Whole-Genome Sequencing of Fluoroquinolone-resistant and -Susceptible Mycobacterium tuberculosis Isolates: A Proposed Threshold for Identifying Resistance. Clin Infect Dis 2021; 72:1910-1918. [PMID: 32348473 PMCID: PMC8315129 DOI: 10.1093/cid/ciaa496] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 04/24/2020] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Fluoroquinolone resistance in Mycobacterium tuberculosis (Mtb) is conferred by DNA gyrase mutations, but not all fluoroquinolone-resistant Mtb isolates have mutations detected. The optimal allele frequency threshold to identify resistance-conferring mutations by whole-genome sequencing is unknown. METHODS Phenotypically ofloxacin-resistant and lineage-matched ofloxacin-susceptible Mtb isolates underwent whole-genome sequencing at an average coverage depth of 868 reads. Polymorphisms within the quinolone-resistance-determining region (QRDR) of gyrA and gyrB were identified. The allele frequency threshold using the Genome Analysis Toolkit pipeline was ~8%; allele-level data identified the predominant variant allele frequency and mutational burden (ie, sum of all variant allele frequencies in the QRDR) in gyrA, gyrB, and gyrA + gyrB for each isolate. Receiver operating characteristic (ROC) curves assessed the optimal measure of allele frequency and potential thresholds for identifying phenotypically resistant isolates. RESULTS Of 42 ofloxacin-resistant Mtb isolates, area under the ROC curve (AUC) was highest for predominant variant allele frequency, so that measure was used to evaluate optimal mutation detection thresholds. AUCs for 8%, 2.5%, and 0.8% thresholds were 0.8452, 0.9286, and 0.9069, respectively. Sensitivity and specificity were 69% and 100% for 8%, 86% and 100% for 2.5%, 91% and 91% for 0.8%. The sensitivity of the 2.5% and 0.8% thresholds were significantly higher than the 8% threshold (P = .016 and .004, respectively) but not significantly different between one another (P = .5). CONCLUSIONS A predominant mutation allele frequency threshold of 2.5% had the highest AUC for detecting DNA gyrase mutations that confer ofloxacin resistance, and was therefore the optimal threshold.
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Affiliation(s)
- Fernanda Maruri
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- Vanderbilt Tuberculosis Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Yan Guo
- Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico, USA
| | - Amondrea Blackman
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- Vanderbilt Tuberculosis Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Yuri F van der Heijden
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- Vanderbilt Tuberculosis Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- The Aurum Institute, Johannesburg, South Africa
| | - Peter F Rebeiro
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- Vanderbilt Tuberculosis Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Timothy R Sterling
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- Vanderbilt Tuberculosis Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
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18
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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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19
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Laniado-Laborín R. Clinical Interpretation of Drug Susceptibility Tests in Tuberculosis. CURRENT RESPIRATORY MEDICINE REVIEWS 2021. [DOI: 10.2174/1573398x16999201007164411] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
:
Prompt and accurate diagnosis of drug resistance is essential for optimal treatment of
drug-resistant tuberculosis. However, only 20% of the more than half a million patients eligible for
the treatment of MDR-TB/RR-TB receive an appropriate drug regimen. Drug-resistant TB regimens
must include a sufficient number of effective medications, a significant challenge for clinicians
worldwide, as most are forced to make therapeutic decisions without any, or very little information
on drug susceptibility testing. Although phenotypic DST is still commonly regarded as the
gold standard for determining M. tuberculosis susceptibility to antituberculosis drugs, it has several
limitations, mainly its prolonged turnaround time. Molecular methods based on M. tuberculosis genomic
DNA sequencing have been developed during the past two decades, to identify the most
common mutations involved in drug resistance. The Xpert
®
MTB/RIF is a real-time polymerase
chain reaction that offers results in less than two hours and has an overall sensitivity for rifampin resistance
of 96% and 98% specificity. Line probe assays (LPAs) are commercial DNA strip-based
tests for detecting the most frequent mutations responsible for resistance to rifampin, isoniazid, fluoroquinolones,
and second-line injectable drugs.
:
Discrepancies between phenotypic and genotyping methods are a problem that the clinician will
face in everyday practice. However, any resistance result (with any type of test) in a person with
risk factors for harboring resistant microorganisms should be considered appropriate while the results
of complementary tests are available.
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Affiliation(s)
- Rafael Laniado-Laborín
- Clinica y Laboratorio de Tuberculosis, Hospital General Tijuana, ISESALUD, Mexicali, Mexico
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20
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Robust detection of point mutations involved in multidrug-resistant Mycobacterium tuberculosis in the presence of co-occurrent resistance markers. PLoS Comput Biol 2020; 16:e1008518. [PMID: 33347430 PMCID: PMC7785249 DOI: 10.1371/journal.pcbi.1008518] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 01/05/2021] [Accepted: 11/11/2020] [Indexed: 11/23/2022] Open
Abstract
Tuberculosis disease is a major global public health concern and the growing prevalence of drug-resistant Mycobacterium tuberculosis is making disease control more difficult. However, the increasing application of whole-genome sequencing as a diagnostic tool is leading to the profiling of drug resistance to inform clinical practice and treatment decision making. Computational approaches for identifying established and novel resistance-conferring mutations in genomic data include genome-wide association study (GWAS) methodologies, tests for convergent evolution and machine learning techniques. These methods may be confounded by extensive co-occurrent resistance, where statistical models for a drug include unrelated mutations known to be causing resistance to other drugs. Here, we introduce a novel ‘cannibalistic’ elimination algorithm (“Hungry, Hungry SNPos”) that attempts to remove these co-occurrent resistant variants. Using an M. tuberculosis genomic dataset for the virulent Beijing strain-type (n = 3,574) with phenotypic resistance data across five drugs (isoniazid, rifampicin, ethambutol, pyrazinamide, and streptomycin), we demonstrate that this new approach is considerably more robust than traditional methods and detects resistance-associated variants too rare to be likely picked up by correlation-based techniques like GWAS. Tuberculosis is one of the deadliest infectious diseases, being responsible for more than one million deaths per year. The causing bacteria are becoming increasingly drug-resistant, which is hampering disease control. At the same time, an unprecedented amount of bacterial whole-genome sequencing is increasingly informing clinical practice. In order to detect the genetic alterations responsible for developing drug resistance and predict resistance status from genomic data, bio-statistical methods and machine learning models have been employed. However, due to strongly overlapping drug resistance phenotypes and genotypes in multidrug-resistant datasets, the results of these correlation-based approaches frequently also contain mutations related to resistance against other drugs. In the past, this issue has often been ignored or partially resolved by either restricting the input data or in post-analysis screening—with both strategies relying on prior information. Here we present a heuristic algorithm for finding resistance-associated variants and demonstrate that it is considerably more robust towards co-occurrent resistance compared to traditional techniques. The software is available at https://github.com/julibeg/HHS.
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21
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Baines SL, da Silva AG, Carter GP, Jennison A, Rathnayake I, Graham RM, Sintchenko V, Wang Q, Rockett RJ, Timms VJ, Martinez E, Ballard S, Tomita T, Isles N, Horan KA, Pitchers W, Stinear TP, Williamson DA, Howden BP, Seemann T. Complete microbial genomes for public health in Australia and the Southwest Pacific. Microb Genom 2020; 6:mgen000471. [PMID: 33180013 PMCID: PMC8116684 DOI: 10.1099/mgen.0.000471] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 10/21/2020] [Indexed: 12/13/2022] Open
Abstract
Complete genomes of microbial pathogens are essential for the phylogenomic analyses that increasingly underpin core public health laboratory activities. Here, we announce a BioProject (PRJNA556438) dedicated to sharing complete genomes chosen to represent a range of pathogenic bacteria with regional importance to Australia and the Southwest Pacific; enriching the catalogue of globally available complete genomes for public health while providing valuable strains to regional public health microbiology laboratories. In this first step, we present 26 complete high-quality bacterial genomes. Additionally, we describe here a framework for reconstructing complete microbial genomes and highlight some of the challenges and considerations for accurate and reproducible genome reconstruction.
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Affiliation(s)
- Sarah L. Baines
- Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria 3001, Australia
| | - Anders Gonçalves da Silva
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria 3001, Australia
| | - Glen P. Carter
- Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria 3001, Australia
| | - Amy Jennison
- Public Health Microbiology, Queensland Reference Centre for Microbial and Public Health Genomics, Forensic and Scientific Services, Queensland Department of Health, Archerfield, Queensland 4108, Australia
| | - Irani Rathnayake
- Public Health Microbiology, Queensland Reference Centre for Microbial and Public Health Genomics, Forensic and Scientific Services, Queensland Department of Health, Archerfield, Queensland 4108, Australia
| | - Rikki M. Graham
- Public Health Microbiology, Queensland Reference Centre for Microbial and Public Health Genomics, Forensic and Scientific Services, Queensland Department of Health, Archerfield, Queensland 4108, Australia
| | - Vitali Sintchenko
- Centre for Infectious Diseases and Microbiology – Public Health, Westmead Hospital and NSW Health Pathology, Sydney, New South Wales 2145, Australia
- Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney, Sydney, New South Wales 2006, Australia
| | - Qinning Wang
- Centre for Infectious Diseases and Microbiology – Public Health, Westmead Hospital and NSW Health Pathology, Sydney, New South Wales 2145, Australia
| | - Rebecca J. Rockett
- Centre for Infectious Diseases and Microbiology – Public Health, Westmead Hospital and NSW Health Pathology, Sydney, New South Wales 2145, Australia
- Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney, Sydney, New South Wales 2006, Australia
| | - Verlaine J. Timms
- Centre for Infectious Diseases and Microbiology – Public Health, Westmead Hospital and NSW Health Pathology, Sydney, New South Wales 2145, Australia
- Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney, Sydney, New South Wales 2006, Australia
| | - Elena Martinez
- Centre for Infectious Diseases and Microbiology – Public Health, Westmead Hospital and NSW Health Pathology, Sydney, New South Wales 2145, Australia
| | - Susan Ballard
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria 3001, Australia
| | - Takehiro Tomita
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria 3001, Australia
| | - Nicole Isles
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria 3001, Australia
| | - Kristy A. Horan
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria 3001, Australia
| | - William Pitchers
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria 3001, Australia
| | - Timothy P. Stinear
- Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria 3001, Australia
| | - Deborah A. Williamson
- Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria 3001, Australia
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria 3001, Australia
| | - Benjamin P. Howden
- Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria 3001, Australia
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria 3001, Australia
| | - Torsten Seemann
- Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria 3001, Australia
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria 3001, Australia
| | - Communicable Diseases Genomics Network (CDGN)
- Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria 3001, Australia
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria 3001, Australia
- Public Health Microbiology, Queensland Reference Centre for Microbial and Public Health Genomics, Forensic and Scientific Services, Queensland Department of Health, Archerfield, Queensland 4108, Australia
- Centre for Infectious Diseases and Microbiology – Public Health, Westmead Hospital and NSW Health Pathology, Sydney, New South Wales 2145, Australia
- Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney, Sydney, New South Wales 2006, Australia
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22
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Raj A, Baliga S, Shenoy MS, Dhanashree B, Mithra PP, Nambiar SK, Sharon L. Validity of a CB-NAAT assay in diagnosing tuberculosis in comparison to culture: A study from an urban area of South India. J Clin Tuberc Other Mycobact Dis 2020; 21:100198. [PMID: 33204853 PMCID: PMC7649623 DOI: 10.1016/j.jctube.2020.100198] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
•CB-NAAT performance compared in 831 suspected pulmonary and extrapulmonary suspected cases.•The conventional stained smear and CB-NAAT results were compared to the MGIT culture.•Sensitivity and specificity of CB-NAAT was 84.43% and 94.93%.•The rapid results from CB-NAAT confirms its use in the tuberculosis diagnostic algorithm.•The benefits of disease diagnosis and prevention outweighs the price tag of the CB-NAAT tests.•This is more so for the resource poor countries where the burden of the disease is high.
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Affiliation(s)
- Aishwarya Raj
- Department of Biophysics, National Institute of Mental Health and Neuro Sciences (Institute of National Importance), Bengaluru, India
| | - Shrikala Baliga
- Department of Microbiology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India
- Manipal McGill Centre for Infectious Diseases, PSPH, Manipal, India
| | - M. Suchitra Shenoy
- Department of Microbiology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India
- Manipal McGill Centre for Infectious Diseases, PSPH, Manipal, India
| | - B. Dhanashree
- Department of Microbiology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India
- Manipal McGill Centre for Infectious Diseases, PSPH, Manipal, India
| | - P. Prasanna Mithra
- Department of Community Medicine, Kasturba Medical College, Mangalore, India
| | - Smitha K. Nambiar
- Department of Microbiology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India
| | - Leesha Sharon
- Department of Microbiology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India
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23
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Advances in the diagnosis of tuberculosis- Journey from smear microscopy to whole genome sequencing. Indian J Tuberc 2020; 67:S61-S68. [PMID: 33308673 DOI: 10.1016/j.ijtb.2020.09.026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 09/24/2020] [Indexed: 12/14/2022]
Abstract
The laboratory plays an important role in diagnosing tuberculosis (TB) and the identification and drug sensitivity testing (DST) of Mycobacterium tuberculosis. With a timely diagnosis and treatment with appropriate anti-TB drugs, most people who develop TB can be cured and onward transmission of infection curtailed. For a long time, laboratories used only microscopy and conventional culture-based diagnosis, however these procedures are slow and may require 3-4 weeks to yield results. Given the increasing rate of drug resistance, it has been necessary to look for new and rapid diagnostic methods. Various molecular based diagnostic technologies became available in the beginning of early 90s, providing rapid detection, identification and DST of M. tuberculosis. Molecular technologies offer the greatest potential for laboratories because they have the highest sensitivity and specificity. The present article will review some of the new methodology that has been introduced in the clinical laboratory.
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24
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Application of Targeted Next-Generation Sequencing Assay on a Portable Sequencing Platform for Culture-Free Detection of Drug-Resistant Tuberculosis from Clinical Samples. J Clin Microbiol 2020; 58:JCM.00632-20. [PMID: 32727827 PMCID: PMC7512157 DOI: 10.1128/jcm.00632-20] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 07/21/2020] [Indexed: 12/21/2022] Open
Abstract
Targeted next-generation sequencing (tNGS) has emerged as a comprehensive alternative to existing methods for drug susceptibility testing (DST) of Mycobacterium tuberculosis from patient sputum samples for clinical diagnosis of drug-resistant tuberculosis (DR-TB). However, the complexity of sequencing platforms has limited their uptake in low-resource settings. The goal of this study was to evaluate the use of the tNGS-based DST solution Genoscreen Deeplex Myc-TB, for use on the compact, low-cost Oxford Nanopore Technologies MinION sequencer. One hundred four DNA samples extracted from smear-positive sputum sediments, previously sequenced using the Deeplex assay on an Illumina MiniSeq, were resequenced on MinION after applying a custom library preparation. MinION read quality, mapping statistics, and variant calling were computed using an in-house pipeline and compared to the reference MiniSeq data. The average percentage of MinION reads mapped to an H37RV reference genome was 90.8%, versus 99.5% on MiniSeq. The mean depths of coverage were 4,151× and 4,177× on MinION and MiniSeq, respectively, with heterogeneous distribution across targeted genes. Composite reference coverage breadth was >99% for both platforms. We observed full concordance between technologies in reporting the clinically relevant drug-resistant markers, including full gene deletions. In conclusion, we demonstrated that the workflow and sequencing data obtained from Deeplex on MinION are comparable to those for the MiniSeq, despite the higher raw error rates on MinION, with the added advantage of MinION's portability, versatility, and low capital costs. Targeted NGS on MinION is a promising DST solution for rapidly providing clinically relevant data to manage complex DR-TB cases.
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25
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Application of machine learning algorithm and modified high resolution DNA melting curve analysis for molecular subtyping of Salmonella isolates from various epidemiological backgrounds in northern Thailand. World J Microbiol Biotechnol 2020; 36:103. [PMID: 32613458 DOI: 10.1007/s11274-020-02874-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 06/21/2020] [Indexed: 10/23/2022]
Abstract
Food poisoning from consumption of food contaminated with non-typhoidal Salmonella spp. is a global problem. A modified high resolution DNA melting curve analysis (m-HRMa) was introduced to provide effective discrimination among closely related HRM curves of amplicons generated from selected Salmonella genome sequences enabled Salmonella spp. to be classified into discrete clusters. Combination of m-HRMa with serogroup identification (ms-HRMa) helped improve assignment of Salmonella spp. into clusters. In addition, a machine learning (dynamic time warping) algorithm (DTW) was employed to provide a simple and rapid protocol for clustering analysis as well as to create phylogeny tree of Salmonella strains (n = 40) collected from home, farms and slaughter houses in northern Thailand. Applications of DTW and ms-HRMa clustering analyses were capable of generating molecular signatures of the Salmonella isolates, resulting in 25 ms-HRM and 28 DTW clusters compared to 14 clusters from a standard HRM analysis, and the combination of both analyses permitted molecular subtyping of each Salmonella isolate. Results from DTW and ms-HRMa cluster analyses were in good agreement with that obtained from enterobacterial repetitive intergenic consensus sequence PCR clustering. While conventional serotyping of Clusters 1 and 2 revealed six different Salmonella serotypes, the majority being S. Weltevraden, the new Salmonella subtyping protocol identified five S. Weltevraden subtypes with S.Weltevreden subtype DTW4-M1 being predominant. Based on knowledge of the sources of Salmonella subtypes, transmission of S. Weltevraden in northern Thailand was likely to be farm-to-farm through contaminated chicken stool. In conclusion, the rapid, robust and specific Salmonella subtyping developed in the study can be performed in a local setting, enabling swift control and preventive measures to be initiated against potential epidemics of salmonellosis.
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26
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Wisittipanit N, Pulsrikarn C, Srisong S, Srimora R, Kittiwan N, Poonchareon K. CRISPR 2 PCR and high resolution melting profiling for identification and characterization of clinically-relevant Salmonella enterica subsp. enterica. PeerJ 2020; 8:e9113. [PMID: 32587791 PMCID: PMC7304428 DOI: 10.7717/peerj.9113] [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: 11/01/2019] [Accepted: 04/10/2020] [Indexed: 12/15/2022] Open
Abstract
Background Nontyphoidal Salmonella spp. constitute a major bacterial cause of food poisoning. Each Salmonella serotype causes distinct virulence to humans. Method A small cohort study was conducted to characterize several aspects of Salmonella isolates obtained from stool of diarrheal patients (n = 26) admitted to Phayao Ram Hospital, Phayao province, Thailand. A simple CRISPR 2 molecular analysis was developed to rapidly type Salmonella isolates employing both uniplex and high resolution melting (HRM) curve analysis. Results CRISPR 2 monoplex PCR generated a single Salmonella serotype-specific amplicon, showing S. 4,[5],12:i:- with highest frequency (42%), S. Enteritidis (15%) and S. Stanley (11%); S. Typhimurium was not detected. CRISPR 2 HRM-PCR allowed further classification of S. 4,[5],12:i:- isolates based on their specific CRISPR 2 signature sequences. The highest prevalence of Salmonella infection was during the summer season (April to August). Additional studies were conducted using standard multiplex HRM-PCR typing, which confirmed CRISPR 2 PCR results and, using a machine-learning algorithm, clustered the majority of Salmonella serotypes into six clades; repetitive element-based (ERIC) PCR, which clustered the serotypes into three clades only; antibiogram profiling, which revealed the majority resistant to ampicillin (69%); and test for extended spectrum β-lactamase production (two isolates) and PCR-based detection of bla alleles. Conclusion CRISPR 2 PCR provided a simple assay for detection and identification of clinically-relevant Salmonella serotypes. In conjunction with antibiogram profiling and rapid assay for β-lactamase producers, this approach should facilitate detection and appropriate treatment of Salmonellosis in a local hospital setting. In addition, CRISPR 2 HRM-PCR profiling enabled clustering of S. 4,[5],12:i:-isolates according to CRISPR 2 locus signature sequences, indicative of their different evolutionary trajectories, thereby providing a powerful tool for future epidemiological studies of virulent Salmonella serotypes.
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Affiliation(s)
- Nuttachat Wisittipanit
- Department of Material Engineering, School of Science, Mae Fah Luang University, Chiang Rai, Thailand
| | - Chaiwat Pulsrikarn
- Department of Medical Sciences, WHO National Salmonella and Shigella Center, National Institute of Health, Ministry of Public Health, Nonthaburi, Thailand
| | - Sudarat Srisong
- Division of Biochemistry, School of Medical Sciences, University of Phayao, Phayao, Thailand
| | - Rungthiwa Srimora
- Division of Biochemistry, School of Medical Sciences, University of Phayao, Phayao, Thailand
| | - Nattinee Kittiwan
- Veterinary Research and Development Center (Upper Northern Region), Lampang, Thailand
| | - Kritchai Poonchareon
- Division of Biochemistry, School of Medical Sciences, University of Phayao, Phayao, Thailand
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27
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Colman RE, Suresh A, Dolinger DL, Muñoz T, Denkinger CM, Rodwell TC. Review of automated DNA extraction systems for sequencing-based solutions for drug-resistant tuberculosis detection. Diagn Microbiol Infect Dis 2020; 98:115096. [PMID: 32623232 DOI: 10.1016/j.diagmicrobio.2020.115096] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 04/25/2020] [Accepted: 05/24/2020] [Indexed: 11/16/2022]
Abstract
Robust clinical specimen nucleic acid extraction instrumentation and methods are critical to the performance of downstream molecular diagnostics for the diagnosis of drug-resistant tuberculosis (DR-TB). Currently, there is a high level of interest in sequencing-based solutions for rapid and comprehensive DR-TB testing from primary specimens (i.e., sputum). However, there is no standardized or fully automated sputum extraction system that has been widely implemented for use with Mycobacterium tuberculosis complex-containing sputum specimens. For sequencing-based technologies to be widely adopted in clinical laboratory settings in low- and middle-income countries, automated extraction technologies will be important to enhance scalability and reliability and to standardize performance of the downstream assays. Additionally, the ease of automatic technologies allows for faster uptake in laboratories currently without the expertise or infrastructure to perform manual extractions at the same automated throughput. This work is intended to provide an initial specification comparison of available automated DNA extraction systems that could serve as front-end components for existing and future sequencing approaches and provide the framework for future evaluations.
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Affiliation(s)
- Rebecca E Colman
- Foundation for Innovative New Diagnostics, Geneva, Switzerland; Department of Medicine, University of California, San Diego, California, USA.
| | - Anita Suresh
- Foundation for Innovative New Diagnostics, Geneva, Switzerland
| | - David L Dolinger
- Foundation for Innovative New Diagnostics, Geneva, Switzerland; QuantuMDx, Group Ltd. Newcastle upon Tyne, United Kingdom
| | - Taylor Muñoz
- Department of Medicine, University of California, San Diego, California, USA
| | - Claudia M Denkinger
- Foundation for Innovative New Diagnostics, Geneva, Switzerland; Division of Tropical Medicine, University Hospital Heidelberg, Germany
| | - Timothy C Rodwell
- Foundation for Innovative New Diagnostics, Geneva, Switzerland; Department of Medicine, University of California, San Diego, California, USA
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Kukhtin AV, Norville R, Bueno A, Qu P, Parrish N, Murray M, Chandler DP, Holmberg RC, Cooney CG. A Benchtop Automated Sputum-to-Genotype System Using a Lab-on-a-Film Assembly for Detection of Multidrug-Resistant Mycobacterium tuberculosis. Anal Chem 2020; 92:5311-5318. [PMID: 32142258 PMCID: PMC7354060 DOI: 10.1021/acs.analchem.9b05853] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Automated genotyping of drug-resistant Mycobacterium tuberculosis (MTB) directly from sputum is challenging for three primary reasons. First, the sample matrix, sputum, is highly viscous and heterogeneous, posing a challenge for sample processing. Second, acid-fast MTB bacilli are difficult to lyse. And third, there are hundreds of MTB mutations that confer drug resistance. An additional constraint is that MTB is most prevalent where test affordability is paramount. We address the challenge of sample homogenization and cell lysis using magnetic rotation of an external magnet, at high (5000) rpm, to induce the rotation of a disposable stir disc that causes chaotic mixing of glass beads ("MagVor"). Nucleic acid is purified using a pipet tip with an embedded matrix that isolates nucleic acid ("TruTip"). We address the challenge of cost and genotyping multiple mutations using 203 porous three-dimensional gel elements printed on a film substrate and enclosed in a microfluidic laminate assembly ("Lab-on-a-Film"). This Lab-on-a-Film assembly (LFA) serves as a platform for amplification, hybridization, washing, and fluorescent imaging, while maintaining a closed format to prevent amplicon contamination of the workspace. We integrated and automated MagVor homogenization, TruTip purification, and LFA amplification in a multisample, sputum-to-genotype system. Using this system, we report detection down to 43 cfu/mL of MTB bacilli from raw sputum.
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Affiliation(s)
- Alexander V Kukhtin
- Akonni Biosystems, Inc., 400 Sagner Avenue, Suite 300, Frederick, Maryland 21701, United States
| | - Ryan Norville
- Akonni Biosystems, Inc., 400 Sagner Avenue, Suite 300, Frederick, Maryland 21701, United States
| | - Arial Bueno
- Akonni Biosystems, Inc., 400 Sagner Avenue, Suite 300, Frederick, Maryland 21701, United States
| | - Peter Qu
- Akonni Biosystems, Inc., 400 Sagner Avenue, Suite 300, Frederick, Maryland 21701, United States
| | - Nicole Parrish
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, United States
| | - Megan Murray
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Darrell P Chandler
- Akonni Biosystems, Inc., 400 Sagner Avenue, Suite 300, Frederick, Maryland 21701, United States
| | - Rebecca C Holmberg
- Akonni Biosystems, Inc., 400 Sagner Avenue, Suite 300, Frederick, Maryland 21701, United States
| | - Christopher G Cooney
- Akonni Biosystems, Inc., 400 Sagner Avenue, Suite 300, Frederick, Maryland 21701, United States
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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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Baffoe-Bonnie A, Houpt ER, Turner L, Dodge D, Heysell SK. Drug-Susceptible and Multidrug-Resistant Mycobacterium tuberculosis in a Single Patient. Emerg Infect Dis 2019; 25:2120-2121. [PMID: 31454310 PMCID: PMC6810186 DOI: 10.3201/eid2511.180638] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
A patient who had initial infection with mixed strains of drug-susceptible and multidrug-resistant tuberculosis was presumed to have acquired drug resistance before confirmation that sequential strains were genotypically distinct. Transmitted infection with mixed strains is likely underappreciated; identifying these infections requires spoligotyping and whole-genome sequencing.
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Effectiveness of BOX-PCR in Differentiating Genetic Relatedness among Salmonella enterica Serotype 4,[5],12:i:- Isolates from Hospitalized Patients and Minced Pork Samples in Northern Thailand. Int J Microbiol 2019; 2019:5086240. [PMID: 31316564 PMCID: PMC6604291 DOI: 10.1155/2019/5086240] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 04/18/2019] [Indexed: 11/25/2022] Open
Abstract
Salmonella enterica Serotype 4,[5],12:i:-, a monophasic variant of S. Typhimurium, with high virulence and multidrug resistance is distributed globally causing pathogenicity to both humans and domesticated animals. BOX-A1R-based repetitive extragenic palindromic-PCR (BOX)-PCR proved to be superior to three other repetitive element-based PCR typing methods, namely, enterobacterial repetitive intergenic consensus (ERIC)-, poly-trinucleotide (GTG)5-, and repetitive extragenic palindromic (REP)-PCR (carried out under a single optimized amplification condition), in differentiating genetic relatedness among S. 4,[5],12:i:- isolates from feces of hospitalized patients (n=12) and isolates from minced pork samples of S. 4,[5],12:i:- (n=6), S. Typhimurium (n=6), and Salmonella Serogroup B (n=4) collected from different regions of northern Thailand. Construction of phylogenetic trees from amplicon size patterns allowed allocation of Salmonella isolates into clusters of similar genetic relatedness, with BOX-PCR generating more unique clusters for each serotype than the other three typing methods. BOX-, (GTG)5-, and REP-PCR indicated significant genetic relatedness between S. 4,[5],12:i:- isolates 1 and 9 from hospitalized patients and S. 4,[5],12:i:- isolate en 29 from minced pork, suggesting a possible route of transmission. Thus, BOX-PCR provides a suitable molecular typing method for discriminating genetic relatedness among Salmonella spp. of the same and different serotypes and should be suitable for application in typing and tracking route of transmission in Salmonella outbreaks.
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32
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Nguyen TNA, Anton-Le Berre V, Bañuls AL, Nguyen TVA. Molecular Diagnosis of Drug-Resistant Tuberculosis; A Literature Review. Front Microbiol 2019; 10:794. [PMID: 31057511 PMCID: PMC6477542 DOI: 10.3389/fmicb.2019.00794] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Accepted: 03/28/2019] [Indexed: 11/13/2022] Open
Abstract
Drug-resistant tuberculosis is a global health problem that hinders the progress of tuberculosis eradication programs. Accurate and early detection of drug-resistant tuberculosis is essential for effective patient care, for preventing tuberculosis spread, and for limiting the development of drug-resistant strains. Culture-based drug susceptibility tests are the gold standard method for the detection of drug-resistant tuberculosis, but they are time-consuming and technically challenging, especially in low- and middle-income countries. Nowadays, different nucleic acid-based assays that detect gene mutations associated with resistance to drugs used to treat tuberculosis are available. These tests vary in type and number of targets and in sensitivity and specificity. In this review, we will describe the available molecular tests for drug-resistant tuberculosis detection and discuss their advantages and limitations.
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Affiliation(s)
- Thi Ngoc Anh Nguyen
- UMR MIVEGEC, Institute of Research for Development, Centre National de la Recherche Scientifique, University of Montpellier, Montpellier, France.,Laboratory of Tuberculosis, Department of Bacteriology, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam.,LMI Drug Resistance in South East Asia, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam
| | | | - Anne-Laure Bañuls
- UMR MIVEGEC, Institute of Research for Development, Centre National de la Recherche Scientifique, University of Montpellier, Montpellier, France.,LMI Drug Resistance in South East Asia, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam
| | - Thi Van Anh Nguyen
- Laboratory of Tuberculosis, Department of Bacteriology, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam.,LMI Drug Resistance in South East Asia, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam
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Cabibbe AM, Walker TM, Niemann S, Cirillo D. Whole genome sequencing of Mycobacterium tuberculosis. Eur Respir J 2018; 52:13993003.01163-2018. [DOI: 10.1183/13993003.01163-2018] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Accepted: 09/02/2018] [Indexed: 11/05/2022]
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Comas I, Gardy JL. TB Transmission: Closing the Gaps. EBioMedicine 2018; 34:4-5. [PMID: 30072212 PMCID: PMC6116352 DOI: 10.1016/j.ebiom.2018.07.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Accepted: 07/16/2018] [Indexed: 01/01/2023] Open
Affiliation(s)
- Iñaki Comas
- Biomedicine Institute of Valencia IBV-CSIC, Valencia, Spain; CIBER in Epidemiology and Public Health, Spain.
| | - Jennifer L Gardy
- School of Population and Public Health, University of British Columbia, Vancouver, Canada; British Columbia Centre for Disease Control, Vancouver, Canada.
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35
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Thakore N, Norville R, Franke M, Calderon R, Lecca L, Villanueva M, Murray MB, Cooney CG, Chandler DP, Holmberg RC. Automated TruTip nucleic acid extraction and purification from raw sputum. PLoS One 2018; 13:e0199869. [PMID: 29975759 PMCID: PMC6033430 DOI: 10.1371/journal.pone.0199869] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 05/30/2018] [Indexed: 12/12/2022] Open
Abstract
Automated nucleic acid extraction from primary (raw) sputum continues to be a significant technical challenge for molecular diagnostics. In this work, we developed a prototype open-architecture, automated nucleic acid workstation that includes a mechanical homogenization and lysis function integrated with heating and TruTip purification; optimized an extraction protocol for raw sputum; and evaluated system performance on primary clinical specimens. Eight samples could be processed within 70 min. The system efficiently homogenized primary sputa and doubled nucleic acid recovery relative to an automated protocol that did not incorporate sample homogenization. Nucleic acid recovery was at least five times higher from raw sputum as compared to that of matched sediments regardless of smear or culture grade, and the automated workstation reproducibly recovered PCR-detectable DNA to at least 80 CFU mL-1 raw sputum. M. tuberculosis DNA was recovered and detected from 122/123 (99.2%) and 124/124 (100%) primary sputum and sediment extracts, respectively. There was no detectable cross-contamination across 53 automated system runs and amplification or fluorescent inhibitors (if present) were not detectable. The open fluidic architecture of the prototype automated workstation yields purified sputum DNA that can be used for any molecular diagnostic test. The ability to transfer TruTip protocols between personalized, on-demand pipetting tools and the fully automated workstation also affords public health agencies an opportunity to standardize sputum nucleic acid sample preparation procedures, reagents, and quality control across multiple levels of the health care system.
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Affiliation(s)
- Nitu Thakore
- Akonni Biosystems, Inc., Frederick, Maryland, United States of America
| | - Ryan Norville
- Akonni Biosystems, Inc., Frederick, Maryland, United States of America
| | - Molly Franke
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | | | - Leonid Lecca
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Socios En Salud Sucursal Perú, Carabayllo, Lima, Peru
| | | | - Megan B. Murray
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
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McNerney R, Zignol M, Clark TG. Use of whole genome sequencing in surveillance of drug resistant tuberculosis. Expert Rev Anti Infect Ther 2018; 16:433-442. [PMID: 29718745 DOI: 10.1080/14787210.2018.1472577] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION The threat of resistance to anti-tuberculosis drugs is of global concern. Current efforts to monitor resistance rely on phenotypic testing where cultured bacteria are exposed to critical concentrations of the drugs. Capacity for such testing is low in TB endemic countries. Drug resistance is caused by mutations in the Mycobacterium tuberculosis genome and whole genome sequencing to detect these mutations offers an alternative means of assessing resistance. Areas covered: The challenges of assessing TB drug resistance are discussed. Progress in elucidating the M. tuberculosis resistome and evidence of the accuracy of next generation sequencing for detecting resistance is reviewed. Expert Commentary: There are considerable advantages to using next generation sequencing for TB drug resistance surveillance. Accuracy is high for detecting resistance to the major first-line drugs but is currently lower for the second-line drugs due to our incomplete knowledge regarding resistance causing mutations. With the advances in sequencing technology and the opportunity to replace phenotypic drug susceptibility testing with safer and more cost effective methods it would appear that the question is when to implement. Current bottlenecks are sample extraction to allow whole genome sequencing directly from sputum and the lack of bioinformatics expertise in some TB endemic countries.
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Affiliation(s)
- Ruth McNerney
- a Division of Pulmonary Medicine, Department of Medicine , University of Cape Town , Cape Town , South Africa
| | - Matteo Zignol
- b Global Tuberculosis Programme , World Health Organization , Geneva , Switzerland
| | - Taane G Clark
- c Faculty of Infectious and Tropical Diseases and Faculty of Epidemiology and Population Health , London School of Hygiene & Tropical Medicine , London , United Kingdom
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Tuberculosis: advances and challenges in development of new diagnostics and biomarkers. THE LANCET. INFECTIOUS DISEASES 2018; 18:e199-e210. [PMID: 29580818 DOI: 10.1016/s1473-3099(18)30111-7] [Citation(s) in RCA: 204] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 12/18/2017] [Accepted: 01/02/2018] [Indexed: 11/23/2022]
Abstract
Tuberculosis remains the leading cause of death from an infectious disease worldwide. Early and accurate diagnosis and detection of drug-sensitive and drug-resistant tuberculosis is essential for achieving global tuberculosis control. Despite the introduction of the Xpert MTB/RIF assay as the first-line rapid tuberculosis diagnostic test, the gap between global estimates of incidence and new case notifications is 4·1 million people. More accurate, rapid, and cost-effective screening tests are needed to improve case detection. Diagnosis of extrapulmonary tuberculosis and tuberculosis in children, people living with HIV, and pregnant women remains particularly problematic. The diagnostic molecular technology landscape has continued to expand, including the development of tests for resistance to several antituberculosis drugs. Biomarkers are urgently needed to indicate progression from latent infection to clinical disease, to predict risk of reactivation after cure, and to provide accurate endpoints for drug and vaccine trials. Sophisticated bioinformatic computational tools and systems biology approaches are being applied to the discovery and validation of biomarkers, with substantial progress taking place. New data have been generated from the study of T-cell responses and T-cell function, serological studies, flow cytometric-based assays, and protein and gene expression studies. Alternative diagnostic strategies under investigation as potential screening and triaging tools include non-sputum-based detection with breath-based tests and automated digital radiography. We review developments and key achievements in the search for new tuberculosis diagnostics and biomarkers. We highlight gaps and challenges in evaluation and rollout of new diagnostics and biomarkers, and prioritise areas needing further investment, including impact assessment and cost-benefit studies.
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Zignol M, Cabibbe AM, Dean AS, Glaziou P, Alikhanova N, Ama C, Andres S, Barbova A, Borbe-Reyes A, Chin DP, Cirillo DM, Colvin C, Dadu A, Dreyer A, Driesen M, Gilpin C, Hasan R, Hasan Z, Hoffner S, Hussain A, Ismail N, Kamal SMM, Khanzada FM, Kimerling M, Kohl TA, Mansjö M, Miotto P, Mukadi YD, Mvusi L, Niemann S, Omar SV, Rigouts L, Schito M, Sela I, Seyfaddinova M, Skenders G, Skrahina A, Tahseen S, Wells WA, Zhurilo A, Weyer K, Floyd K, Raviglione MC. Genetic sequencing for surveillance of drug resistance in tuberculosis in highly endemic countries: a multi-country population-based surveillance study. THE LANCET. INFECTIOUS DISEASES 2018; 18:675-683. [PMID: 29574065 PMCID: PMC5968368 DOI: 10.1016/s1473-3099(18)30073-2] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 01/05/2018] [Accepted: 01/30/2018] [Indexed: 12/02/2022]
Abstract
Background In many countries, regular monitoring of the emergence of resistance to anti-tuberculosis drugs is hampered by the limitations of phenotypic testing for drug susceptibility. We therefore evaluated the use of genetic sequencing for surveillance of drug resistance in tuberculosis. Methods Population-level surveys were done in hospitals and clinics in seven countries (Azerbaijan, Bangladesh, Belarus, Pakistan, Philippines, South Africa, and Ukraine) to evaluate the use of genetic sequencing to estimate the resistance of Mycobacterium tuberculosis isolates to rifampicin, isoniazid, ofloxacin, moxifloxacin, pyrazinamide, kanamycin, amikacin, and capreomycin. For each drug, we assessed the accuracy of genetic sequencing by a comparison of the adjusted prevalence of resistance, measured by genetic sequencing, with the true prevalence of resistance, determined by phenotypic testing. Findings Isolates were taken from 7094 patients with tuberculosis who were enrolled in the study between November, 2009, and May, 2014. In all tuberculosis cases, the overall pooled sensitivity values for predicting resistance by genetic sequencing were 91% (95% CI 87–94) for rpoB (rifampicin resistance), 86% (74–93) for katG, inhA, and fabG promoter combined (isoniazid resistance), 54% (39–68) for pncA (pyrazinamide resistance), 85% (77–91) for gyrA and gyrB combined (ofloxacin resistance), and 88% (81–92) for gyrA and gyrB combined (moxifloxacin resistance). For nearly all drugs and in most settings, there was a large overlap in the estimated prevalence of drug resistance by genetic sequencing and the estimated prevalence by phenotypic testing. Interpretation Genetic sequencing can be a valuable tool for surveillance of drug resistance, providing new opportunities to monitor drug resistance in tuberculosis in resource-poor countries. Before its widespread adoption for surveillance purposes, there is a need to standardise DNA extraction methods, recording and reporting nomenclature, and data interpretation. Funding Bill & Melinda Gates Foundation, United States Agency for International Development, Global Alliance for Tuberculosis Drug Development.
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Affiliation(s)
- Matteo Zignol
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland.
| | - Andrea Maurizio Cabibbe
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland; San Raffaele Scientific Institute, Milan, Italy
| | - Anna S Dean
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Philippe Glaziou
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Natavan Alikhanova
- Scientific Research Institute of Lung Diseases, Ministry of Health, Baku, Azerbaijan
| | - Cecilia Ama
- National Tuberculosis Reference Laboratory, Manila, Philippines
| | - Sönke Andres
- National Reference Laboratory for Mycobacteria, Borstel Research Centre, Borstel, Germany
| | - Anna Barbova
- Central Reference Laboratory on Tuberculosis Microbiological Diagnostics, Ministry of Health, Kiev, Ukraine
| | | | | | | | - Charlotte Colvin
- Bureau for Global Health, US Agency for International Development, Washington, DC, USA
| | - Andrei Dadu
- Regional Office for Europe, World Health Organization, Copenhagen, Denmark
| | - Andries Dreyer
- National Institute for Communicable Diseases, Sandringham, South Africa
| | - Michèle Driesen
- Mycobacteriology Unit, Institute of Tropical Medicine, Antwerp, Belgium
| | - Christopher Gilpin
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Rumina Hasan
- Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
| | - Zahra Hasan
- Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
| | - Sven Hoffner
- Department of Microbiology, Tumour and Cell Biology, Karolinska Institute, Stockholm, Sweden
| | - Alamdar Hussain
- National Reference Laboratory, National Tuberculosis Control Programme, Islamabad, Pakistan
| | - Nazir Ismail
- National Institute for Communicable Diseases, Sandringham, South Africa; Department of Medical Microbiology, University of Pretoria, Pretoria, South Africa
| | - S M Mostofa Kamal
- Department of Pathology and Microbiology, National Institute of Diseases of the Chest and Hospital, Dhaka, Bangladesh
| | - Faisal Masood Khanzada
- National Reference Laboratory, National Tuberculosis Control Programme, Islamabad, Pakistan
| | | | - Thomas Andreas Kohl
- Molecular and Experimental Mycobacteriology, Borstel Research Centre, Borstel, Germany
| | - Mikael Mansjö
- Department of Microbiology, Public Health Agency of Sweden, Solna, Sweden
| | | | - Ya Diul Mukadi
- Bureau for Global Health, US Agency for International Development, Washington, DC, USA
| | - Lindiwe Mvusi
- Tuberculosis Control and Management Unit, National Department of Health, Pretoria, South Africa
| | - Stefan Niemann
- Molecular and Experimental Mycobacteriology, Borstel Research Centre, Borstel, Germany
| | - Shaheed V Omar
- National Institute for Communicable Diseases, Sandringham, South Africa
| | - Leen Rigouts
- Mycobacteriology Unit, Institute of Tropical Medicine, Antwerp, Belgium; Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | | | - Ivita Sela
- Department of Mycobacteriology, Tuberculosis and Lung Disease Centre, Riga East University Hospital, Riga, Latvia
| | - Mehriban Seyfaddinova
- Scientific Research Institute of Lung Diseases, Ministry of Health, Baku, Azerbaijan
| | - Girts Skenders
- Department of Mycobacteriology, Tuberculosis and Lung Disease Centre, Riga East University Hospital, Riga, Latvia
| | - Alena Skrahina
- Republican Scientific and Practical Centre for Pulmonology and Tuberculosis, Minsk, Belarus
| | - Sabira Tahseen
- National Reference Laboratory, National Tuberculosis Control Programme, Islamabad, Pakistan
| | - William A Wells
- Bureau for Global Health, US Agency for International Development, Washington, DC, USA
| | - Alexander Zhurilo
- National Institute of Phthisiology And Pulmonology, National Academy of Medical Science of Ukraine, Kiev, Ukraine
| | - Karin Weyer
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Katherine Floyd
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Mario C Raviglione
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
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39
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Point of care diagnostics for tuberculosis. Pulmonology 2018; 24:73-85. [DOI: 10.1016/j.rppnen.2017.12.002] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 12/07/2017] [Indexed: 01/01/2023] Open
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40
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Heyckendorf J, Andres S, Köser CU, Olaru ID, Schön T, Sturegård E, Beckert P, Schleusener V, Kohl TA, Hillemann D, Moradigaravand D, Parkhill J, Peacock SJ, Niemann S, Lange C, Merker M. What Is Resistance? Impact of Phenotypic versus Molecular Drug Resistance Testing on Therapy for Multi- and Extensively Drug-Resistant Tuberculosis. Antimicrob Agents Chemother 2018; 62:e01550-17. [PMID: 29133554 PMCID: PMC5786814 DOI: 10.1128/aac.01550-17] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2017] [Accepted: 10/26/2017] [Indexed: 12/29/2022] Open
Abstract
Rapid and accurate drug susceptibility testing (DST) is essential for the treatment of multi- and extensively drug-resistant tuberculosis (M/XDR-TB). We compared the utility of genotypic DST assays with phenotypic DST (pDST) using Bactec 960 MGIT or Löwenstein-Jensen to construct M/XDR-TB treatment regimens for a cohort of 25 consecutive M/XDR-TB patients and 15 possible anti-TB drugs. Genotypic DST results from Cepheid GeneXpert MTB/RIF (Xpert) and line probe assays (LPAs; Hain GenoType MTBDRplus 2.0 and MTBDRsl 2.0) and whole-genome sequencing (WGS) were translated into individual algorithm-derived treatment regimens for each patient. We further analyzed if discrepancies between the various methods were due to flaws in the genotypic or phenotypic test using MIC results. Compared with pDST, the average agreement in the number of drugs prescribed in genotypic regimens ranged from just 49% (95% confidence interval [CI], 39 to 59%) for Xpert and 63% (95% CI, 56 to 70%) for LPAs to 93% (95% CI, 88 to 98%) for WGS. Only the WGS regimens did not contain any drugs to which pDST showed resistance. Importantly, MIC testing revealed that pDST likely underestimated the true rate of resistance for key drugs (rifampin, levofloxacin, moxifloxacin, and kanamycin) because critical concentrations (CCs) were too high. WGS can be used to rule in resistance even in M/XDR strains with complex resistance patterns, but pDST for some drugs is still needed to confirm susceptibility and construct the final regimens. Some CCs for pDST need to be reexamined to avoid systematic false-susceptible results in low-level resistant isolates.
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Affiliation(s)
- Jan Heyckendorf
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany
- German Center for Infection Research (DZIF), Partner site Hamburg-Lübeck-Borstel, Borstel, Germany
- International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany
| | - Sönke Andres
- Division of Mycobacteriology (National Tuberculosis Reference Laboratory), Research Center Borstel, Borstel, Germany
| | - Claudio U Köser
- Department of Genetics, University of Cambridge, Cambridge, United Kingdom
| | - Ioana D Olaru
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany
- German Center for Infection Research (DZIF), Partner site Hamburg-Lübeck-Borstel, Borstel, Germany
| | - Thomas Schön
- Department of Infectious Diseases and Clinical Microbiology, Kalmar County Hospital, Kalmar, Sweden
- Department of Clinical and Experimental Medicine, Division of Medical Microbiology, Linköping University, Linköping, Sweden
| | - Erik Sturegård
- Clinical Microbiology, Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Patrick Beckert
- German Center for Infection Research (DZIF), Partner site Hamburg-Lübeck-Borstel, Borstel, Germany
- Division of Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
| | - Viola Schleusener
- Division of Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
| | - Thomas A Kohl
- German Center for Infection Research (DZIF), Partner site Hamburg-Lübeck-Borstel, Borstel, Germany
- Division of Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
| | - Doris Hillemann
- Division of Mycobacteriology (National Tuberculosis Reference Laboratory), Research Center Borstel, Borstel, Germany
| | | | | | - Sharon J Peacock
- Department of Genetics, University of Cambridge, Cambridge, United Kingdom
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Stefan Niemann
- German Center for Infection Research (DZIF), Partner site Hamburg-Lübeck-Borstel, Borstel, Germany
- Division of Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
| | - Christoph Lange
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany
- German Center for Infection Research (DZIF), Partner site Hamburg-Lübeck-Borstel, Borstel, Germany
- International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany
- Department of Medicine, Karolinska Institute, Stockholm, Sweden
- Department of Medicine, University of Namibia School of Medicine, Windhoek, Namibia
| | - Matthias Merker
- German Center for Infection Research (DZIF), Partner site Hamburg-Lübeck-Borstel, Borstel, Germany
- Division of Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
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41
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Coll F, Phelan J, Hill-Cawthorne GA, Nair MB, Mallard K, Ali S, Abdallah AM, Alghamdi S, Alsomali M, Ahmed AO, Portelli S, Oppong Y, Alves A, Bessa TB, Campino S, Caws M, Chatterjee A, Crampin AC, Dheda K, Furnham N, Glynn JR, Grandjean L, Minh Ha D, Hasan R, Hasan Z, Hibberd ML, Joloba M, Jones-López EC, Matsumoto T, Miranda A, Moore DJ, Mocillo N, Panaiotov S, Parkhill J, Penha C, Perdigão J, Portugal I, Rchiad Z, Robledo J, Sheen P, Shesha NT, Sirgel FA, Sola C, Oliveira Sousa E, Streicher EM, Helden PV, Viveiros M, Warren RM, McNerney R, Pain A, Clark TG. Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis. Nat Genet 2018; 50:307-316. [PMID: 29358649 DOI: 10.1038/s41588-017-0029-0] [Citation(s) in RCA: 194] [Impact Index Per Article: 32.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Accepted: 12/01/2017] [Indexed: 12/30/2022]
Abstract
To characterize the genetic determinants of resistance to antituberculosis drugs, we performed a genome-wide association study (GWAS) of 6,465 Mycobacterium tuberculosis clinical isolates from more than 30 countries. A GWAS approach within a mixed-regression framework was followed by a phylogenetics-based test for independent mutations. In addition to mutations in established and recently described resistance-associated genes, novel mutations were discovered for resistance to cycloserine, ethionamide and para-aminosalicylic acid. The capacity to detect mutations associated with resistance to ethionamide, pyrazinamide, capreomycin, cycloserine and para-aminosalicylic acid was enhanced by inclusion of insertions and deletions. Odds ratios for mutations within candidate genes were found to reflect levels of resistance. New epistatic relationships between candidate drug-resistance-associated genes were identified. Findings also suggest the involvement of efflux pumps (drrA and Rv2688c) in the emergence of resistance. This study will inform the design of new diagnostic tests and expedite the investigation of resistance and compensatory epistatic mechanisms.
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Affiliation(s)
- Francesc Coll
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Jody Phelan
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Grant A Hill-Cawthorne
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
- Sydney Emerging Infections and Biosecurity Institute and School of Public Health, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Mridul B Nair
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Kim Mallard
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Shahjahan Ali
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Abdallah M Abdallah
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Saad Alghamdi
- Laboratory Medicine Department, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Mona Alsomali
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Abdallah O Ahmed
- Department of Microbiology, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Stephanie Portelli
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Melbourne, Victoria, Australia
| | - Yaa Oppong
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Adriana Alves
- National Mycobacterium Reference Laboratory, Porto, Portugal
| | | | - Susana Campino
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Maxine Caws
- Liverpool School of Tropical Medicine, Liverpool, UK
- Pham Ngoc Thach Hospital for TB and Lung Diseases, Ho Chi Minh City, Vietnam
| | | | - Amelia C Crampin
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
- Karonga Prevention Study, Chilumba, Karonga, Malawi
| | - Keertan Dheda
- Lung Infection and Immunity Unit, UCT Lung Institute, University of Cape Town, Groote Schuur Hospital, Cape Town, South Africa
| | - Nicholas Furnham
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Judith R Glynn
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
- Karonga Prevention Study, Chilumba, Karonga, Malawi
| | - Louis Grandjean
- Laboratorio de Enfermedades Infecciosas, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Dang Minh Ha
- Pham Ngoc Thach Hospital for TB and Lung Diseases, Ho Chi Minh City, Vietnam
| | - Rumina Hasan
- Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
| | - Zahra Hasan
- Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
| | - Martin L Hibberd
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Moses Joloba
- Department of Medical Microbiology, Makerere University College of Health Sciences, Kampala, Uganda
| | - Edward C Jones-López
- Section of Infectious Diseases, Department of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, MA, USA
| | | | - Anabela Miranda
- National Mycobacterium Reference Laboratory, Porto, Portugal
| | - David J Moore
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Laboratorio de Enfermedades Infecciosas, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Nora Mocillo
- Reference Laboratory of Tuberculosis Control, Buenos Aires, Argentina
| | - Stefan Panaiotov
- National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria
| | | | - Carlos Penha
- Instituto Gulbenkian de Ciência, Lisbon, Portugal
| | - João Perdigão
- iMed.ULisboa-Research Institute for Medicines, Faculdade de Farmácia, Universidade de Lisboa, Lisbon, Portugal
| | - Isabel Portugal
- iMed.ULisboa-Research Institute for Medicines, Faculdade de Farmácia, Universidade de Lisboa, Lisbon, Portugal
| | - Zineb Rchiad
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Jaime Robledo
- Corporación para Investigaciones Biológicas, Universidad Pontificia Bolivariana, Medellín, Colombia
| | - Patricia Sheen
- Lung Infection and Immunity Unit, UCT Lung Institute, University of Cape Town, Groote Schuur Hospital, Cape Town, South Africa
| | | | - Frik A Sirgel
- Division of Molecular Biology and Human Genetics, SAMRC Centre for Tuberculosis Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Christophe Sola
- Institute for Integrative Cell Biology, CEA, CNRS, Université Paris-Saclay, Orsay, France
| | - Erivelton Oliveira Sousa
- Centro de Pesquisas Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Laboratorio Central de Saúde Pública Professor Gonçalo Moniz, Salvador, Brazil
| | - Elizabeth M Streicher
- Division of Molecular Biology and Human Genetics, SAMRC Centre for Tuberculosis Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Paul Van Helden
- Division of Molecular Biology and Human Genetics, SAMRC Centre for Tuberculosis Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Miguel Viveiros
- Unidade de Microbiologia Médica, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa (UNL), Lisbon, Portugal
| | - Robert M Warren
- Division of Molecular Biology and Human Genetics, SAMRC Centre for Tuberculosis Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Ruth McNerney
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.
- Lung Infection and Immunity Unit, UCT Lung Institute, University of Cape Town, Groote Schuur Hospital, Cape Town, South Africa.
| | - Arnab Pain
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
- Global Station for Zoonosis Control, Global Institution for Collaborative Research and Education (GI-CoRE), Hokkaido University, Sapporo, Japan.
| | - Taane G Clark
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
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42
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Schleusener V, Köser CU, Beckert P, Niemann S, Feuerriegel S. Mycobacterium tuberculosis resistance prediction and lineage classification from genome sequencing: comparison of automated analysis tools. Sci Rep 2017; 7:46327. [PMID: 28425484 PMCID: PMC7365310 DOI: 10.1038/srep46327] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Accepted: 03/15/2017] [Indexed: 11/25/2022] Open
Abstract
Whole-genome sequencing (WGS) has the potential to accelerate drug-susceptibility testing (DST) to design appropriate regimens for drug-resistant tuberculosis (TB). Several recently developed automated software tools promise to standardize the analysis and interpretation of WGS data. We assessed five tools (CASTB, KvarQ, Mykrobe Predictor TB, PhyResSE, and TBProfiler) with regards to DST and phylogenetic lineage classification, which we compared with phenotypic DST, Sanger sequencing, and traditional typing results for a collection of 91 strains. The lineage classifications by the tools generally only differed in the resolution of the results. However, some strains could not be classified at all and one strain was misclassified. The sensitivities and specificities for isoniazid and rifampicin resistance of the tools were high, whereas the results for ethambutol, pyrazinamide, and streptomycin resistance were more variable. False-susceptible DST results were mainly due to missing mutations in the resistance catalogues that the respective tools employed for data interpretation. Notably, we also found cases of false-resistance because of the misclassification of polymorphisms as resistance mutations. In conclusion, the performance of current WGS analysis tools for DST is highly variable. Sustainable business models and a shared, high-quality catalogue of resistance mutations are needed to ensure the clinical utility of these tools.
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Affiliation(s)
- Viola Schleusener
- Division of Molecular and Experimental Mycobacteriology Group, Research Center Borstel, Borstel, Germany
| | - Claudio U. Köser
- Department of Genetics, University of Cambridge, Cambridge, United Kingdom
| | - Patrick Beckert
- Division of Molecular and Experimental Mycobacteriology Group, Research Center Borstel, Borstel, Germany
- German Center for Infection Research, Borstel Site, Borstel Germany
| | - Stefan Niemann
- Division of Molecular and Experimental Mycobacteriology Group, Research Center Borstel, Borstel, Germany
- German Center for Infection Research, Borstel Site, Borstel Germany
| | - Silke Feuerriegel
- Division of Molecular and Experimental Mycobacteriology Group, Research Center Borstel, Borstel, Germany
- German Center for Infection Research, Borstel Site, Borstel Germany
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Abstract
Whole-genome sequencing has taken a leading role in epidemiologic studies of tuberculosis, but thus far, its real-time clinical utility has been low, in part because of the requirement for culture. In their report in this issue, Votintseva et al. (A. A. Votintseva, P. Bradley, L. Pankhurst, C. del Ojo Elias, M. Loose, K. Nilgiriwala, A. Chatterjee, E. G. Smith, N. Sanderson, T. M. Walker, M. R. Morgan, D. H. Wyllie, A. S. Walker, T. E. A. Peto, D. W. Crook, and Z. Iqbal, J Clin Microbiol 55:1285-1298, 2017, https://doi.org/10.1128/JCM.02483-16) present a new method for extracting Mycobacterium tuberculosis DNA directly from smear-positive respiratory samples, making it feasible to generate drug resistance predictions and phylogenetic trees in 44 h with the Illumina MiSeq. They also illustrate the potential for a <24-h turnaround time from DNA extraction to clinically relevant results with Illumina MiniSeq and Oxford Nanopore Technologies MinION. We comment on the promise and limitations of these approaches.
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44
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Petersen E, Maeurer M, Marais B, Migliori GB, Mwaba P, Ntoumi F, Vilaplana C, Kim K, Schito M, Zumla A. World TB Day 2017: Advances, Challenges and Opportunities in the "End-TB" Era. Int J Infect Dis 2017; 56:1-5. [PMID: 28232006 DOI: 10.1016/j.ijid.2017.02.012] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Affiliation(s)
- Eskild Petersen
- Institute of Clinical Medicine, University of Aarhus, Denmark; The Royal Hospital, Muscat, Oman.
| | - Markus Maeurer
- Therapeutic Immunology (TIM) Division, Department of Laboratory Medicine, Karolinska University Hospital Huddinge, and Centre for Allogeneic Stem Cell Transplantation, Karolinska University Hospital Huddinge, Stockholm, Sweden.
| | - Ben Marais
- The Children's Hospital at Westmead and Centre for Research Excellence in Tuberculosis (TB-CRE), Marie Bashir Institute for Infectious Diseases and Biosecurity (MBI), University of Sydney, Australia.
| | | | - Peter Mwaba
- UNZA-UCLMS Research and Training Project, University Teaching Hospital, Lusaka, Zambia.
| | - Francine Ntoumi
- Fondation Congolaise pour la Recherche Médicale, Faculté des Sciences de la Santé, Marien Ngouabi University, Brazzaville, Congo; Institute for Tropical Medicine, University of Tübingen, Tübingen, Germany.
| | - Cris Vilaplana
- Unitat de Tuberculosi Experimental Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i PujolEdifici Laboratoris de Recerca Can Ruti Campus, Barcelona, Spain.
| | - Kami Kim
- Department of Medicine (Infectious Diseases), of Microbiology & Immunology and of Pathology, Albert Einstein College of Medicine, Bronx, NY, USA.
| | - Marco Schito
- Critical Path to TB Drug Regimens, Critical Path Institute, Tucson, Arizona, USA.
| | - Alimuddin Zumla
- Center for Clinical Microbiology, Division of Infection and Immunity, University College London, and the National Institute of Health Research Biomedical Research Centre at UCLHospitals, London, United Kingdom.
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