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Implementation of targeted next-generation sequencing for the diagnosis of drug-resistant tuberculosis in low-resource settings: a programmatic model, challenges, and initial outcomes
Targeted next-generation sequencing (tNGS) from clinical specimens has the potential to become a comprehensive tool for routine drug-resistance (DR) prediction of Mycobacterium tuberculosis complex strains (MTBC), the causative agent of tuberculosis (TB). However, TB mainly affects low- and middle-i...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10478709/ https://www.ncbi.nlm.nih.gov/pubmed/37674674 http://dx.doi.org/10.3389/fpubh.2023.1204064 |
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author | de Araujo, Leonardo Cabibbe, Andrea Maurizio Mhuulu, Lusia Ruswa, Nunurai Dreyer, Viola Diergaardt, Azaria Günther, Gunar Claassens, Mareli Gerlach, Christiane Utpatel, Christian Cirillo, Daniela Maria Nepolo, Emmanuel Niemann, Stefan |
author_facet | de Araujo, Leonardo Cabibbe, Andrea Maurizio Mhuulu, Lusia Ruswa, Nunurai Dreyer, Viola Diergaardt, Azaria Günther, Gunar Claassens, Mareli Gerlach, Christiane Utpatel, Christian Cirillo, Daniela Maria Nepolo, Emmanuel Niemann, Stefan |
author_sort | de Araujo, Leonardo |
collection | PubMed |
description | Targeted next-generation sequencing (tNGS) from clinical specimens has the potential to become a comprehensive tool for routine drug-resistance (DR) prediction of Mycobacterium tuberculosis complex strains (MTBC), the causative agent of tuberculosis (TB). However, TB mainly affects low- and middle-income countries, in which the implementation of new technologies have specific needs and challenges. We propose a model for programmatic implementation of tNGS in settings with no or low previous sequencing capacity/experience. We highlight the major challenges and considerations for a successful implementation. This model has been applied to build NGS capacity in Namibia, an upper middle-income country located in Southern Africa and suffering from a high-burden of TB and TB-HIV, and we describe herein the outcomes of this process. |
format | Online Article Text |
id | pubmed-10478709 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104787092023-09-06 Implementation of targeted next-generation sequencing for the diagnosis of drug-resistant tuberculosis in low-resource settings: a programmatic model, challenges, and initial outcomes de Araujo, Leonardo Cabibbe, Andrea Maurizio Mhuulu, Lusia Ruswa, Nunurai Dreyer, Viola Diergaardt, Azaria Günther, Gunar Claassens, Mareli Gerlach, Christiane Utpatel, Christian Cirillo, Daniela Maria Nepolo, Emmanuel Niemann, Stefan Front Public Health Public Health Targeted next-generation sequencing (tNGS) from clinical specimens has the potential to become a comprehensive tool for routine drug-resistance (DR) prediction of Mycobacterium tuberculosis complex strains (MTBC), the causative agent of tuberculosis (TB). However, TB mainly affects low- and middle-income countries, in which the implementation of new technologies have specific needs and challenges. We propose a model for programmatic implementation of tNGS in settings with no or low previous sequencing capacity/experience. We highlight the major challenges and considerations for a successful implementation. This model has been applied to build NGS capacity in Namibia, an upper middle-income country located in Southern Africa and suffering from a high-burden of TB and TB-HIV, and we describe herein the outcomes of this process. Frontiers Media S.A. 2023-08-03 /pmc/articles/PMC10478709/ /pubmed/37674674 http://dx.doi.org/10.3389/fpubh.2023.1204064 Text en Copyright © 2023 de Araujo, Cabibbe, Mhuulu, Ruswa, Dreyer, Diergaardt, Günther, Claassens, Gerlach, Utpatel, Cirillo, Nepolo and Niemann. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health de Araujo, Leonardo Cabibbe, Andrea Maurizio Mhuulu, Lusia Ruswa, Nunurai Dreyer, Viola Diergaardt, Azaria Günther, Gunar Claassens, Mareli Gerlach, Christiane Utpatel, Christian Cirillo, Daniela Maria Nepolo, Emmanuel Niemann, Stefan Implementation of targeted next-generation sequencing for the diagnosis of drug-resistant tuberculosis in low-resource settings: a programmatic model, challenges, and initial outcomes |
title | Implementation of targeted next-generation sequencing for the diagnosis of drug-resistant tuberculosis in low-resource settings: a programmatic model, challenges, and initial outcomes |
title_full | Implementation of targeted next-generation sequencing for the diagnosis of drug-resistant tuberculosis in low-resource settings: a programmatic model, challenges, and initial outcomes |
title_fullStr | Implementation of targeted next-generation sequencing for the diagnosis of drug-resistant tuberculosis in low-resource settings: a programmatic model, challenges, and initial outcomes |
title_full_unstemmed | Implementation of targeted next-generation sequencing for the diagnosis of drug-resistant tuberculosis in low-resource settings: a programmatic model, challenges, and initial outcomes |
title_short | Implementation of targeted next-generation sequencing for the diagnosis of drug-resistant tuberculosis in low-resource settings: a programmatic model, challenges, and initial outcomes |
title_sort | implementation of targeted next-generation sequencing for the diagnosis of drug-resistant tuberculosis in low-resource settings: a programmatic model, challenges, and initial outcomes |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10478709/ https://www.ncbi.nlm.nih.gov/pubmed/37674674 http://dx.doi.org/10.3389/fpubh.2023.1204064 |
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