Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance

Autor: C Brandon, Ogbunugafor, C Scott, Wylie, Ibrahim, Diakite, Daniel M, Weinreich, Daniel L, Hartl
Rok vydání: 2015
Předmět:
Zdroj: PLoS Computational Biology
ISSN: 1553-7358
Popis: The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions—drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR) to two related inhibitors—pyrimethamine and cycloguanil—across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis) influence paths taken at evolutionary “forks in the road” that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC50 and minimal inhibitory concentration (MIC) are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with regards to their basic contribution to the study of empirical adaptive landscapes, and in terms of how they inform new models for the evolution of drug resistance.
Author Summary The adaptive landscape analogy describes the process of evolution by examining how individual mutations in a gene or genome affect the reproductive success of an organism. In certain cases, it can offer insight into what pathways evolution is likely to take in moving between different phenotypes. The analogy has been used by evolutionary biologists to describe a number of phenomena ranging from how mutations affect hemoglobin function to how bacteria evolve resistance to antibiotics. In this study, we combine computational biology with experimental data to examine how the environment—defined as the type of drugs and their amounts—affects the structure of adaptive landscapes for drug resistance in Plasmodium falciparum (the agent responsible for the most deadly form of malaria) with respect to mutations in dihydrofolate reductase (DHFR), an enzyme that plays an important role in drug resistance. We conclude that the environment has a profound effect on how the evolution of drug resistance occurs. In the future, these details should be integrated into models of antimicrobial therapy, as they greatly influence the dynamics of drug resistance evolution.
Databáze: OpenAIRE
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