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.

Bermuda Land Snails make up a genus called Poecilozonites that is endemic to Bermuda and is extensively present in its fossil record. These snails were also integral to the creation of the theory of punctuated equilibrium. The DNA of mollusks is difficult to sequence because of a class of proteins called mucopolysaccharides that are present in high concentrations in mollusk tissue, and are not removed with standard DNA extraction methods. They inhibit Polymerase Chain Reactions (PCRs) and interfere with Next Generation Sequencing methods. This paper will discuss the DNA extraction methods that were designed to remove the inhibitory proteins that were tested on another gastropod species (Pomacea canaliculata). These were chosen because they are invasive and while they are not pulmonates, they are similar enough to Bermuda Land Snails to reliably test extraction methods. The methods that were tested included two commercially available kits: the Qiagen Blood and Tissue Kit and the Omega Biotek Mollusc Extraction Kit, and one Hexadecyltrimethylammonium Bromide (CTAB) Extraction method that was modified for use on mollusk tissue. The Blood and Tissue kit produced some DNA, the mollusk kit produced almost none, and the CTAB Extraction Method produced the highest concentrations on average, and may prove to be the most viable option for future extractions. PCRs attempted with the extracted DNA have all failed, though it is likely due to an issue with reagents. Further spectrographic analysis of the DNA from the test extractions has shown that they were successful at removing mucopolysaccharides. When the protocol is optimized, it will be used to extract DNA from the tissue from six individuals from each of the two extant species of Bermuda Land Snails. This DNA will be used in several experiments involving Next Generation Sequencing, with the goal of assembling a variety of genome data. These data will then be used to a construct reference genome for Bermuda Land Snails. The genomes generated by this project will be used in population genetic analyses between individuals of the same species, and between individuals of different species. These analyses will then be used to aid in conservation efforts for the species.

Cancer rates vary between people, between cultures, and between tissue types, driven by clinically relevant distinctions in the risk factors that lead to different cancer types. Despite the importance of cancer location in human health, little is known about tissue-specific cancers in non-human animals. We can gain significant insight into how evolutionary history has shaped mechanisms of cancer suppression by examining how life history traits impact cancer susceptibility across species. Here, we perform multi-level analysis to test how species-level life history strategies are associated with differences in neoplasia prevalence, and apply this to mammary neoplasia within mammals. We propose that the same patterns of cancer prevalence that have been reported across species will be maintained at the tissue-specific level. We used a combination of factor analysis and phylogenetic regression on 13 life history traits across 90 mammalian species to determine the correlation between a life history trait and how it relates to mammary neoplasia prevalence. The factor analysis presented ways to calculate quantifiable underlying factors that contribute to covariance of entangled life history variables. A greater risk of mammary neoplasia was found to be correlated most significantly with shorter gestation length. With this analysis, a framework is provided for how different life history modalities can influence cancer vulnerability. Additionally, statistical methods developed for this project present a framework for future comparative oncology studies and have the potential for many diverse applications.

Our cells need constant fuel and oxygen for the body to work properly and maintain cellular function. In high altitudes tissue oxygen levels fall and the body must work against this hypoxic challenge to maintain energetics and limit oxidative stress. Mammals living at high altitudes are challenged to sustain thermogenesis and aerobic exercise despite reduced amounts of available oxygen. Enhancements in oxidative capacity and oxygen diffusion capacity of skeletal muscle may be necessary to compensate for insufficient oxygen supply in tissues. Hypoxic conditions can cause a switch from aerobic metabolism to anaerobic metabolism. Due to previous research of Graham Scott and colleagues on “Adaptive Modifications of Muscle Phenotype in High-Altitude Deer Mice” and the SMack Lab at Arizona State University, the question of how low atmospheric oxygen levels affects the enzymatic activity in the gastrocnemius muscle of Gelada Monkeys compared to Rhesus Macaque Monkeys was researched. Lactate Dehydrogenase (LDH) activity was measured in the gastrocnemius tissue of 6 Gelada Monkeys (highland) and 6 Rhesus Macaque monkeys (lowland). LDH was expected to be greater in Gelada tissue samples due to heightened anaerobic metabolism in the presence of limited available oxygen in high altitude environments. Results showed higher LDH in Rhesus Macaque samples compared to Gelada samples, but this difference was not statistically significant. Despite nonsignificant data, this experiment is insightful into the effects of Hypoxic adaptation in skeletal muscle enzymatic activity in primates.