Evolutionary Dynamics of Candida albicans during In Vitro Evolution

Abstract

While mechanisms of resistance to major antifungal agents have been characterized in Candida albicans, little is known about the evolutionary trajectories during the emergence of drug resistance. Here, we examined the evolutionary dynamics of C. albicans that evolved in vitro in the presence or absence of fluconazole using the visualizing evolution in real-time (VERT) method, a novel experimental approach that facilitates the systematic isolation of adaptive mutants that arise in the population. We found an increase in the frequency of adaptive events in the presence of fluconazole compared to the no-drug controls. Analysis of the evolutionary dynamics revealed that mutations that led to increased drug resistance appeared frequently and that mutants with increased levels of resistance arose in independent lineages. Interestingly, most adaptive mutants with increased fitness in the presence of the drug did not exhibit a significant fitness decrease in the absence of the drug, supporting the idea that rapid resistance can arise from mutations in strains maintained in the population prior to exposure to the drug.The emergence of antimicrobial drug resistance in pathogens is a process of adaptive evolution, generally as a result of genetic mutations. Depending on the size of the population, the rate of mutation, and the relative fitness coefficients, the population may be heterogeneous, consisting of multiple resistant genotypes competing for expansion in a process called "clonal interference" (10, 12). Determining the evolutionary dynamics during adaptation is important for understanding the fundamental principles underlying how eukaryotic microbes evolve resistance to antimicrobial agents, a process that differs from that in bacteria because it is unlikely to involve horizontal gene transfer (1, 6).It is important to understand the frequencies with which adaptive mutants arise and expand, the evolutionary trajectories (the order of occurrence of adaptive mutations), and the potential convergence or divergence in the adaptive mechanisms between parallel populations in order to better appreciate how drug resistance can emerge in pathogens growing within the host. For example, knowledge of the frequency and order in which drug-resistant mutants arise in the population and whether the early-arising resistance mechanisms play a role in the level of drug resistance ultimately reached in the population can be used to predict the likely trajectory of a clinical infection and to develop appropriate therapeutic strategies.Candida albicans is the fourth most common cause of nosocomial infections, resulting in rates of mortality in U.S. hospitals that approach 50% (23,24,44). Emergence of resistance to almost all major antifungal agents used in treating C. albicans infections has been reported (15,22,29). Among the existing classes of antifungal drugs, azoles are the most commonly used, due to their low toxicity and their oral availability. The fact that they are fungistatic rather than fungicidal provides a clear opportunity...

Distinct Roles of Candida albicans Drug Resistance Transcription Factors TAC1 , MRR1 , and UPC2 in Virulence

“…However, these alterations did not affect the in vitro fitness of C. albicans (28). The notion of a neutral fitness cost upon azole exposure in vitro has been confirmed by others (29).…”

The Candida Pathogenic Species Complex

“…The parasexual cycle results in a very high level of aneuploidy (Forche et al 2008). Aneuploidy also frequently occurs during exposure to antifungal drugs and is likely to be an important adaptive response (Perepnikhatka et al 1999;Selmecki et al 2009Selmecki et al , 2010Huang et al 2011;Hill et al 2013).…”

Visualizing evolution in real time to determine the molecular mechanisms of n-butanol tolerance in Escherichia coli

“…To help alleviate the limitation of traditional evolutionary engineering approaches, here, we demonstrate the use of a recently developed adaptive evolution method, called visualizing evolution in real-time (VERT) (Huang et al, 2011;Kao and Sherlock, 2008), combined with genome shuffling, for the engineering and characterization of complex phenotypes in microbial systems. Using different fluorescently marked (but otherwise isogenic) strains, VERT can be used to readily determine when adaptive events occur (the expansion of adaptive mutants in the population) and to facilitate the isolation of those mutants from the population.…”