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.

Apolipoprotein (ApoE) plays an important role in the transport of lipids in the brain for normal functioning. There are three different isoforms of ApoE which are coded for by three alleles (E2, E3, E4). Patients carrying at least one copy of ApoE E4 are known to be at higher risk for developing Alzheimer’s disease (AD) and earlier onset of symptoms. This is due to the buildup of amyloid plaques and neurofibrillary tangles of the brain from the accumulation of tau proteins, which are associated with the progression of Alzheimer’s disease. However, findings on ApoE E2 have shown that it may be a protective allele since it is linked to a decreased risk of formation of amyloid plaques and neurofibrillary tangles. To study this phenomenon within the context of a local population group, polymerase chain reaction and gel electrophoresis were conducted on extracted DNA samples. The principal goal in this research study was to genotype ApoE variants using single nucleotide polymorphism (SNP) specific primers, and polymerase chain reaction to analyze the frequency in the Tempe population to determine future healthcare needs.