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Latent Tuberculosis: Models, Computational Efforts and the Pathogen’s Regulatory Mechanisms during Dormancy
Latent tuberculosis is a clinical syndrome that occurs after an individual has been exposed to the Mycobacterium tuberculosis (Mtb) Bacillus, the infection has been established and an immune response has been generated to control the pathogen and force it into a quiescent state. Mtb can exit this qu...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2013
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4090907/ https://www.ncbi.nlm.nih.gov/pubmed/25023946 http://dx.doi.org/10.3389/fbioe.2013.00004 |
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author | Magombedze, Gesham Dowdy, David Mulder, Nicola |
author_facet | Magombedze, Gesham Dowdy, David Mulder, Nicola |
author_sort | Magombedze, Gesham |
collection | PubMed |
description | Latent tuberculosis is a clinical syndrome that occurs after an individual has been exposed to the Mycobacterium tuberculosis (Mtb) Bacillus, the infection has been established and an immune response has been generated to control the pathogen and force it into a quiescent state. Mtb can exit this quiescent state where it is unresponsive to treatment and elusive to the immune response, and enter a rapid replicating state, hence causing infection reactivation. It remains a gray area to understand how the pathogen causes a persistent infection and it is unclear whether the organism will be in a slow replicating state or a dormant non-replicating state. The ability of the pathogen to adapt to changing host immune response mechanisms, in which it is exposed to hypoxia, low pH, nitric oxide (NO), nutrient starvation, and several other anti-microbial effectors, is associated with a high metabolic plasticity that enables it to metabolize under these different conditions. Adaptive gene regulatory mechanisms are thought to coordinate how the pathogen changes their metabolic pathways through mechanisms that sense changes in oxygen tension and other stress factors, hence stimulating the pathogen to make necessary adjustments to ensure survival. Here, we review studies that give insights into latency/dormancy regulatory mechanisms that enable infection persistence and pathogen adaptation to different stress conditions. We highlight what mathematical and computational models can do and what they should do to enhance our current understanding of TB latency. |
format | Online Article Text |
id | pubmed-4090907 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-40909072014-07-14 Latent Tuberculosis: Models, Computational Efforts and the Pathogen’s Regulatory Mechanisms during Dormancy Magombedze, Gesham Dowdy, David Mulder, Nicola Front Bioeng Biotechnol Bioengineering and Biotechnology Latent tuberculosis is a clinical syndrome that occurs after an individual has been exposed to the Mycobacterium tuberculosis (Mtb) Bacillus, the infection has been established and an immune response has been generated to control the pathogen and force it into a quiescent state. Mtb can exit this quiescent state where it is unresponsive to treatment and elusive to the immune response, and enter a rapid replicating state, hence causing infection reactivation. It remains a gray area to understand how the pathogen causes a persistent infection and it is unclear whether the organism will be in a slow replicating state or a dormant non-replicating state. The ability of the pathogen to adapt to changing host immune response mechanisms, in which it is exposed to hypoxia, low pH, nitric oxide (NO), nutrient starvation, and several other anti-microbial effectors, is associated with a high metabolic plasticity that enables it to metabolize under these different conditions. Adaptive gene regulatory mechanisms are thought to coordinate how the pathogen changes their metabolic pathways through mechanisms that sense changes in oxygen tension and other stress factors, hence stimulating the pathogen to make necessary adjustments to ensure survival. Here, we review studies that give insights into latency/dormancy regulatory mechanisms that enable infection persistence and pathogen adaptation to different stress conditions. We highlight what mathematical and computational models can do and what they should do to enhance our current understanding of TB latency. Frontiers Media S.A. 2013-08-27 /pmc/articles/PMC4090907/ /pubmed/25023946 http://dx.doi.org/10.3389/fbioe.2013.00004 Text en Copyright © 2013 Magombedze, Dowdy and Mulder. http://creativecommons.org/licenses/by/3.0/ 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) or licensor 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 | Bioengineering and Biotechnology Magombedze, Gesham Dowdy, David Mulder, Nicola Latent Tuberculosis: Models, Computational Efforts and the Pathogen’s Regulatory Mechanisms during Dormancy |
title | Latent Tuberculosis: Models, Computational Efforts and the Pathogen’s Regulatory Mechanisms during Dormancy |
title_full | Latent Tuberculosis: Models, Computational Efforts and the Pathogen’s Regulatory Mechanisms during Dormancy |
title_fullStr | Latent Tuberculosis: Models, Computational Efforts and the Pathogen’s Regulatory Mechanisms during Dormancy |
title_full_unstemmed | Latent Tuberculosis: Models, Computational Efforts and the Pathogen’s Regulatory Mechanisms during Dormancy |
title_short | Latent Tuberculosis: Models, Computational Efforts and the Pathogen’s Regulatory Mechanisms during Dormancy |
title_sort | latent tuberculosis: models, computational efforts and the pathogen’s regulatory mechanisms during dormancy |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4090907/ https://www.ncbi.nlm.nih.gov/pubmed/25023946 http://dx.doi.org/10.3389/fbioe.2013.00004 |
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