Rapid Identification of Lineage and Drug Resistance in Clinical Samples of Mycobacterium tuberculosis
Background: Mycobacterium tuberculosis is a slow-growing bacterium, which could delay its diagnosis and, therefore, promote the spread of the disease. Whole-genome sequencing allows us to obtain the complete drug-resistance profile of the strain; however, bacterial cultivation of clinical samples, a...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303844/ https://www.ncbi.nlm.nih.gov/pubmed/37374968 http://dx.doi.org/10.3390/microorganisms11061467 |
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author | Comín, Jéssica Viñuelas, Jesús Lafoz, Carmen Cebollada, Alberto Ibarz, Daniel Iglesias, María-José Samper, Sofía |
author_facet | Comín, Jéssica Viñuelas, Jesús Lafoz, Carmen Cebollada, Alberto Ibarz, Daniel Iglesias, María-José Samper, Sofía |
author_sort | Comín, Jéssica |
collection | PubMed |
description | Background: Mycobacterium tuberculosis is a slow-growing bacterium, which could delay its diagnosis and, therefore, promote the spread of the disease. Whole-genome sequencing allows us to obtain the complete drug-resistance profile of the strain; however, bacterial cultivation of clinical samples, along with complex processing, is required. Methods: In this work, we explore AmpliSeq, an amplicon-based enrichment method for preparing libraries for targeted next-generation sequencing, to identify lineage and drug resistance directly from clinical samples. Results: In our study, 111 clinical samples were tested. The lineage was identified in 100% of the culture-derived samples (52/52), in 95% of the smear (BK)-positive clinical samples (38/40) and in 42.1% of the BK-negative clinical samples (8/19). The drug-resistance profile was accurately identified in all but 11 samples, in which some phenotypic and genotypic discrepancies were found. In this respect, our panels were not exact in the detection of streptomycin resistance for isolates derived from clinical samples, as an extremely high number of SNPs in the rrs and rrl genes were detected due to cross-contamination. Conclusion: This technique has demonstrated high sensitivity in obtaining the drug-resistance profile of the isolates, as even those samples with DNA concentrations below the detection limit of Qubit produced a result. AmpliSeq technology is cheaper than whole-genome sequencing, easy to perform by laboratory technicians and applicable to any microorganism using the Ion Torrent platform. |
format | Online Article Text |
id | pubmed-10303844 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103038442023-06-29 Rapid Identification of Lineage and Drug Resistance in Clinical Samples of Mycobacterium tuberculosis Comín, Jéssica Viñuelas, Jesús Lafoz, Carmen Cebollada, Alberto Ibarz, Daniel Iglesias, María-José Samper, Sofía Microorganisms Article Background: Mycobacterium tuberculosis is a slow-growing bacterium, which could delay its diagnosis and, therefore, promote the spread of the disease. Whole-genome sequencing allows us to obtain the complete drug-resistance profile of the strain; however, bacterial cultivation of clinical samples, along with complex processing, is required. Methods: In this work, we explore AmpliSeq, an amplicon-based enrichment method for preparing libraries for targeted next-generation sequencing, to identify lineage and drug resistance directly from clinical samples. Results: In our study, 111 clinical samples were tested. The lineage was identified in 100% of the culture-derived samples (52/52), in 95% of the smear (BK)-positive clinical samples (38/40) and in 42.1% of the BK-negative clinical samples (8/19). The drug-resistance profile was accurately identified in all but 11 samples, in which some phenotypic and genotypic discrepancies were found. In this respect, our panels were not exact in the detection of streptomycin resistance for isolates derived from clinical samples, as an extremely high number of SNPs in the rrs and rrl genes were detected due to cross-contamination. Conclusion: This technique has demonstrated high sensitivity in obtaining the drug-resistance profile of the isolates, as even those samples with DNA concentrations below the detection limit of Qubit produced a result. AmpliSeq technology is cheaper than whole-genome sequencing, easy to perform by laboratory technicians and applicable to any microorganism using the Ion Torrent platform. MDPI 2023-05-31 /pmc/articles/PMC10303844/ /pubmed/37374968 http://dx.doi.org/10.3390/microorganisms11061467 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Comín, Jéssica Viñuelas, Jesús Lafoz, Carmen Cebollada, Alberto Ibarz, Daniel Iglesias, María-José Samper, Sofía Rapid Identification of Lineage and Drug Resistance in Clinical Samples of Mycobacterium tuberculosis |
title | Rapid Identification of Lineage and Drug Resistance in Clinical Samples of Mycobacterium tuberculosis |
title_full | Rapid Identification of Lineage and Drug Resistance in Clinical Samples of Mycobacterium tuberculosis |
title_fullStr | Rapid Identification of Lineage and Drug Resistance in Clinical Samples of Mycobacterium tuberculosis |
title_full_unstemmed | Rapid Identification of Lineage and Drug Resistance in Clinical Samples of Mycobacterium tuberculosis |
title_short | Rapid Identification of Lineage and Drug Resistance in Clinical Samples of Mycobacterium tuberculosis |
title_sort | rapid identification of lineage and drug resistance in clinical samples of mycobacterium tuberculosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303844/ https://www.ncbi.nlm.nih.gov/pubmed/37374968 http://dx.doi.org/10.3390/microorganisms11061467 |
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