One of the largest problems facing modern medicine is drug resistance. Many classes of drugs can be rendered ineffective if their target is able to acquire beneficial mutations. While this is an excellent showcase of the power of evolution, it necessitates the development of increasingly stronger drugs to combat resistant pathogens. Not only is this strategy costly and time consuming, it is also unsustainable. To contend with this problem, many multi-drug treatment strategies are being explored. Previous studies have shown that resistance to some drug combinations is not possible, for example, resistance to a common antifungal drug, fluconazole, seems impossible in the presence of radicicol. We believe that in order to understand the viability of multi-drug strategies in combating drug resistance, we must understand the full spectrum of resistance mutations that an organism can develop, not just the most common ones. It is possible that rare mutations exist that are resistant to both drugs. Knowing the frequency of such mutations is important for making predictions about how problematic they will be when multi-drug strategies are used to treat human disease. This experiment aims to expand on previous research on the evolution of drug resistance in S. cerevisiae by using molecular barcodes to track ~100,000 evolving lineages simultaneously. The barcoded cells were evolved with serial transfers for seven weeks (200 generations) in three concentrations of the antifungal Fluconazole, three concentrations of the Hsp90 inhibitor Radicicol, and in four combinations of Fluconazole and Radicicol. Sequencing data was used to track barcode frequencies over the course of the evolution, allowing us to observe resistant lineages as they rise and quantify differences in resistance evolution across the different conditions. We were able to successfully observe over 100,000 replicates simultaneously, revealing many adaptive lineages in all conditions. Our results also show clear differences across drug concentrations and combinations, with the highest drug concentrations exhibiting distinct behaviors.

Despite its well-documented preference for much more humid climates, the yellow fever mosquito, or Aedes aegypti, has inhabited Arizona since 1951. Their presence is of great concern as they can transmit many deadly diseases, including yellow fever, chikungunya, Zika, and dengue fever, putting the residents of the Phoenix Metropolitan Area at risk. Maricopa County Vector Control has made an extensive effort to reduce this risk mainly through the act of fogging insecticides during the night in areas where mosquito numbers exceed a threshold. However, given the well-known temperature-toxicity relationships in insect species, fogging at night may be less or more effective —depending on the relationship— due to the colder temperatures at these times. Additionally, insecticide resistance testing has always been performed at temperatures not usually experienced during fogging, adding to the uncertainty on how useful those test outcomes are. This study took the first steps in determining the effects of temperature on the toxicity of a commonly used insecticide, deltamethrin, on Aedes aegypti by developing a dose response curve on a lab strain at a standard lab temperature of 25°C by performing a CDC bottle bioassay. The diagnostic dose was found to be 50 μg/mL and the lethal dose, 50% (LD50, the dose required to kill half of the test mosquitoes) was found to be 9 μg/mL. Future testing would need to be completed to compare the deltamethrin dose response curve developed in this study with deltamethrin dose response curves at various different temperatures.