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Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis

Mixed infections of Mycobacterium tuberculosis, defined as the coexistence of multiple genetically distinct strains within a single host, have been associated with unfavorable treatment outcomes. Different methods have been used to detect mixed infections, but their performances have not been carefu...

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Autores principales: Chen, Yiwang, Jiang, Qi, Liu, Qingyun, Gan, Mingyu, Takiff, Howard E., Gao, Qian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10269500/
https://www.ncbi.nlm.nih.gov/pubmed/37098911
http://dx.doi.org/10.1128/spectrum.03570-22
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author Chen, Yiwang
Jiang, Qi
Liu, Qingyun
Gan, Mingyu
Takiff, Howard E.
Gao, Qian
author_facet Chen, Yiwang
Jiang, Qi
Liu, Qingyun
Gan, Mingyu
Takiff, Howard E.
Gao, Qian
author_sort Chen, Yiwang
collection PubMed
description Mixed infections of Mycobacterium tuberculosis, defined as the coexistence of multiple genetically distinct strains within a single host, have been associated with unfavorable treatment outcomes. Different methods have been used to detect mixed infections, but their performances have not been carefully evaluated. To compare the sensitivity of whole-genome sequencing (WGS) and variable-number tandem repeats (VNTR) typing to detect mixed infections, we prepared 10 artificial samples composed of DNA mixtures from two strains in different proportions and retrospectively collected 1,084 clinical isolates. The limit of detection (LOD) for the presence of a minor strain was 5% for both WGS and VNTR typing. The overall clinical detection rate of mixed infections was 3.7% (40/1,084) for the two methods combined, WGS identified 37/1,084 (3.4%), and VNTR typing identified 14/1,084 (1.3%), including 11 also identified by WGS. Multivariate analysis demonstrated that retreatment patients had a 2.7 times (95% confidence interval [CI], 1.2 to 6.0) higher risk of mixed infections than new cases. Collectively, WGS is a more reliable tool to identify mixed infections than VNTR typing, and mixed infections are more common in retreated patients. IMPORTANCE Mixed infections of M. tuberculosis have the potential to render treatment regimens ineffective and affect the transmission dynamics of the disease. VNTR typing, currently the most widely used method for the detection of mixed infections, detects mixed infections only by interrogating a small fraction of the M. tuberculosis genome, which necessarily limits sensitivity. With the introduction of WGS, it became possible to study the entire genome, but no quantitative comparison has yet been undertaken. Our systematic comparison of the ability of WGS and VNTR typing to detect mixed infections, using both artificial samples and clinical isolates, revealed the superior performance of WGS at a high sequencing depth (~100×) and found that mixed infections are more common in patients being retreated for tuberculosis (TB) in the populations studied. This provides valuable information for the application of WGS in the detection of mixed infections and the implications of mixed infections for tuberculosis control.
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spelling pubmed-102695002023-06-16 Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis Chen, Yiwang Jiang, Qi Liu, Qingyun Gan, Mingyu Takiff, Howard E. Gao, Qian Microbiol Spectr Research Article Mixed infections of Mycobacterium tuberculosis, defined as the coexistence of multiple genetically distinct strains within a single host, have been associated with unfavorable treatment outcomes. Different methods have been used to detect mixed infections, but their performances have not been carefully evaluated. To compare the sensitivity of whole-genome sequencing (WGS) and variable-number tandem repeats (VNTR) typing to detect mixed infections, we prepared 10 artificial samples composed of DNA mixtures from two strains in different proportions and retrospectively collected 1,084 clinical isolates. The limit of detection (LOD) for the presence of a minor strain was 5% for both WGS and VNTR typing. The overall clinical detection rate of mixed infections was 3.7% (40/1,084) for the two methods combined, WGS identified 37/1,084 (3.4%), and VNTR typing identified 14/1,084 (1.3%), including 11 also identified by WGS. Multivariate analysis demonstrated that retreatment patients had a 2.7 times (95% confidence interval [CI], 1.2 to 6.0) higher risk of mixed infections than new cases. Collectively, WGS is a more reliable tool to identify mixed infections than VNTR typing, and mixed infections are more common in retreated patients. IMPORTANCE Mixed infections of M. tuberculosis have the potential to render treatment regimens ineffective and affect the transmission dynamics of the disease. VNTR typing, currently the most widely used method for the detection of mixed infections, detects mixed infections only by interrogating a small fraction of the M. tuberculosis genome, which necessarily limits sensitivity. With the introduction of WGS, it became possible to study the entire genome, but no quantitative comparison has yet been undertaken. Our systematic comparison of the ability of WGS and VNTR typing to detect mixed infections, using both artificial samples and clinical isolates, revealed the superior performance of WGS at a high sequencing depth (~100×) and found that mixed infections are more common in patients being retreated for tuberculosis (TB) in the populations studied. This provides valuable information for the application of WGS in the detection of mixed infections and the implications of mixed infections for tuberculosis control. American Society for Microbiology 2023-04-26 /pmc/articles/PMC10269500/ /pubmed/37098911 http://dx.doi.org/10.1128/spectrum.03570-22 Text en Copyright © 2023 Chen et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Chen, Yiwang
Jiang, Qi
Liu, Qingyun
Gan, Mingyu
Takiff, Howard E.
Gao, Qian
Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis
title Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis
title_full Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis
title_fullStr Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis
title_full_unstemmed Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis
title_short Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis
title_sort whole-genome sequencing exhibits better diagnostic performance than variable-number tandem repeats for identifying mixed infections of mycobacterium tuberculosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10269500/
https://www.ncbi.nlm.nih.gov/pubmed/37098911
http://dx.doi.org/10.1128/spectrum.03570-22
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