Modeling the potential impact of host population survival on the evolution of M. tuberculosis latency

Tuberculosis (TB) is an infectious disease with a peculiar feature: Upon infection with the causative agent, Mycobacterium Tuberculosis (MTB), most hosts enter a latent state during which no transmission of MTB to new hosts occurs. Only a fraction of latently infected hosts develop TB disease and ca...

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Bibliographic Details
Published in:PloS one 2014-08, Vol.9 (8), p.e105721-e105721
Main Authors: Zheng, Nibiao, Whalen, Christopher C, Handel, Andreas
Format: Article
Language:English
Subjects:
Activation
Adaptation
Analysis
Bacterial infections
Biological Evolution
Biology and Life Sciences
Coevolution
Disease
Disease transmission
Drug resistance
Epidemiology
Evolution
Extinction
Health aspects
HIV
Human behavior
Human immunodeficiency virus
Humans
Immune response
Immune system
Immunity
Infections
Infectious diseases
Influenza
Latency
Latent infection
Latent Tuberculosis - immunology
Latent Tuberculosis - microbiology
Latent Tuberculosis - mortality
Mathematical models
Measles
Medicine and Health Sciences
Models, Biological
Mycobacterium tuberculosis - immunology
Mycobacterium tuberculosis - physiology
Optimization
Ordinary differential equations
Physical Sciences
Population
Populations
Public health
Stochastic Processes
Survival
Systematic review
Tuberculosis
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Summary:Tuberculosis (TB) is an infectious disease with a peculiar feature: Upon infection with the causative agent, Mycobacterium Tuberculosis (MTB), most hosts enter a latent state during which no transmission of MTB to new hosts occurs. Only a fraction of latently infected hosts develop TB disease and can potentially infect new hosts. At first glance, this seems like a waste of transmission potential and therefore an evolutionary suboptimal strategy for MTB. It might be that the human immune response keeps MTB in check in most hosts, thereby preventing it from achieving its evolutionary optimum. Another possible explanation is that long latency and progression to disease in only a fraction of hosts are evolutionary beneficial to MTB by allowing it to persist better in small host populations. Given that MTB has co-evolved with human hosts for millenia or longer, it likely encountered small host populations for a large share of its evolutionary history and had to evolve strategies of persistence. Here, we use a mathematical model to show that indeed, MTB persistence is optimal for an intermediate duration of latency and level of activation. The predicted optimal level of activation is above the observed value, suggesting that human co-evolution has lead to host immunity, which keeps MTB below its evolutionary optimum.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0105721