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Modelling a silent epidemic: A review of the in vitro models of latent tuberculosis

  • Savannah E.R. Gibson
  • , James Harrison
  • , Jonathan A.G. Cox*
  • *Corresponding author for this work
  • Aston University

Research output: Contribution to journal › Review article › peer-review

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Abstract

Tuberculosis (TB) is the primary cause of death by a single infectious agent; responsible for around two million deaths in 2016. A major virulence factor of TB is the ability to enter a latent or Non-Replicating Persistent (NRP) state which is presumed untreatable. Approximately 1.7 billion people are latently infected with TB and on reactivation many of these infections are drug resistant. As the current treatment is ineffective and diagnosis remains poor, millions of people have the potential to reactivate into active TB disease. The immune system seeks to control the TB infection by containing the bacteria in a granuloma, where it is exposed to stressful anaerobic and nutrient deprived conditions. It is thought to be these environmental conditions that trigger the NRP state. A number of in vitro models have been developed that mimic conditions within the granuloma to a lesser or greater extent. These different models have all been utilised for the research of different characteristics of NRP Mycobacterium tuberculosis, however their disparity in approach and physiological relevance often results in inconsistencies and a lack of consensus between studies. This review provides a summation of the different NRP models and a critical analysis of their respective advantages and disadvantages relating to their physiological relevance.

Original languageEnglish
Article number88
JournalPathogens
Volume7
Issue number4
DOIs
Publication statusPublished - 15 Nov 2018

Bibliographical note

© 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).

Funding

Funding: This research was funded by the Academy of Medical Sciences and Global Challenges Research Fund with a Springboard Grant (SBF003\1088:). Acknowledgments: J.A.G.C. is grateful to the Academy of Medical Sciences and Global Challenges Research Fund for supporting the Mycobacterial Research Group at Aston University. S.E.R.G. is supported by a PhD Studentship funded by Aston University.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Antibiotic
  • Drug discovery
  • Latency
  • Mycobacterium tuberculosis
  • Non-replicating persistent
  • Tuberculosis

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