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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
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.
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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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