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. 2004 Sep 9:4:31.
doi: 10.1186/1471-2148-4-31.

Evidence for positive selection on Mycobacterium tuberculosis within patients

Mark M Tanaka  1
Affiliations

Evidence for positive selection on Mycobacterium tuberculosis within patients

Mark M Tanaka. BMC Evol Biol. .

Abstract

Background: While the pathogenesis and epidemiology of tuberculosis are well studied, relatively little is known about the evolution of the infectious agent Mycobacterium tuberculosis, especially at the within-host level. The insertion sequence IS6110 is a genetic marker that is widely used to track the transmission of tuberculosis between individuals. This and other markers may also facilitate our understanding of the disease within patients.

Results: This article presents three lines of evidence supporting the action of positive selection on M. tuberculosis within patients. The arguments are based on a comparison between empirical findings from molecular epidemiology, and population genetic models of evolution. Under the hypothesis of neutrality of genotypes, 1) the mutation rate of the marker IS6110 is unusually high, 2) the time it takes for substitutions to occur within patients is too short, and 3) the amount of polymorphism within patients is too low.

Conclusions: Empirical observations are explained by the action of positive selection during infection, or alternatively by very low effective population sizes. I discuss the possible roles of antibiotic treatment, the host immune system and extrapulmonary dissemination in creating opportunities for positive selection.

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Figures

Figure 1
Figure 1
Estimate of mutation rate when positive selection is acting. The estimate formula image is plotted on a logarithmic scale in base 10. Solid curve: N = 10; Dashed; N = 1000; Dotted: N = 105.
Figure 2
Figure 2
Mean sojourn times as functions of selective coefficient s, for different values of N. Left: from a = 1/N to b = 1 - 1/N; Right: from a = 0.3 to b = 0.7.
Figure 3
Figure 3
Probability of detecting polymorphism in the absence of selection, as a function of N. Two different ranges of detectable polymorphism were used. Dashed curve: (0.1, 0.9); dotted: (0.3, 0.7). We use μ = 7.9 × 10-4. The horizontal bar indicates the observed fraction of polymorphic populations (0.074) from de Boer et al. [22].
Figure 4
Figure 4
Probability of polymorphism as a function of s. Left: the detection threshold is set at 0.3; Right: the detection threshold is set at 0.1. The mutation rate is set to μ = 7.9 × 10-4
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