The epidemiological fitness cost of drug resistance in Mycobacterium tuberculosis

Abstract

The emergence of antibiotic resistance in Mycobacterium tuberculosis has raised the concern that pathogen strains that are virtually untreatable may become widespread. The acquisition of resistance to antibiotics results in a longer duration of infection in a host, but this resistance may come at a cost through a decreased transmission rate. This raises the question of whether the overall fitness of drugresistant strains is higher than that of sensitive strains-essential information for predicting the spread of the disease. Here, we directly estimate the transmission cost of drug resistance, the rate at which resistance evolves, and the relative fitness of resistant strains. These estimates are made by using explicit models of the transmission and evolution of sensitive and resistant strains of M. tuberculosis, using approximate Bayesian computation, and molecular epidemiology data from Cuba, Estonia, and Venezuela. We find that the transmission cost of drug resistance relative to sensitivity can be as low as 10%, that resistance evolves at rates of Ϸ0.0025-0.02 per case per year, and that the overall fitness of resistant strains is comparable with that of sensitive strains. Furthermore, the contribution of transmission to the spread of drug resistance is very high compared with acquired resistance due to treatment failure (up to 99%). Estimating such parameters directly from in vivo data will be critical to understanding and responding to antibiotic resistance. For instance, projections using our estimates suggest that the prevalence of tuberculosis may decline with successful treatment, but the proportion of cases associated with resistance is likely to increase.antibiotic resistance ͉ approximate Bayesian computation ͉ bacterial evolution ͉ molecular epidemiology ͉ stochastic model

Increasing Viral Dose Causes a Reversal in CD8+ T Cell Immunodominance during Primary Influenza Infection due to Differences in Antigen Presentation, T Cell Avidity, and Precursor Numbers

“…Thus, the influence of Ag presentation on ID appears to vary depending upon Ag dose. This variability might explain why relative differences in Ag presentation, in the context of the ID hierarchy following primary IAV infection at least, were shown by some investigators to have a decisive role (50), whereas others assumed them to be of little consequence (36).…”

“…compute, as is the case for complex stochastic models, such as our IBM (36,37). Provided that the underlying model is close enough to the real system and the experimental observations are well captured by the summary statistics used to estimate the model parameters, this approach provides reliable and satisfying results.…”

“…Provided that the underlying model is close enough to the real system and the experimental observations are well captured by the summary statistics used to estimate the model parameters, this approach provides reliable and satisfying results. For example, previous applications of ABC showed that ABC estimates are accurate in scenarios in which likelihoodbased inference methods are also possible (38), and various groups have used ABC to estimate the evolutionary rates of human or bacterial populations (39,40), the transmission dynamics of Mycobacteria tuberculosis (41), and the fitness cost associated with bacterial drug resistance (36). In keeping with Bayesian statistics, ABC parameter estimates are represented as a posterior distribution that provides information on the likelihood that the unknown parameter falls within a certain range of values.…”

“…ABC is a statistical method that allows de novo inference of parameter estimates in situations in which standard techniques are not applicable or difficult to compute, as is the case for complex stochastic models, such as our IBM (36,37). Therefore, we applied ABC to our IBM-based simulations to formally estimate pMHC-I levels, T CD8+ avidity, and precursor numbers (Materials and Methods), as well as to gain additional insights into the underlying basis for IAV ID.…”

The evolution of drug resistance and the curious orthodoxy of aggressive chemotherapy

“…For many diseases, however, patients are at far higher risk of acquiring resistance from other patients. In TB, for example, up to 99% of cases of drug-resistant infections are acquired from the community (84). In these circumstances, the merits of managing de novo mutations with aggressive chemotherapy are less clear.…”