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.

TSPO was discovered in 1977 and it’s function is still currently unknown. Significant research has suggested that TSPO functions in steroidogenesis to import cholesterol from the mitochondrial outer membrane (MOM) to the mitochondrial inner membrane (MIM) where it is converted into steroids. There were two indications that this is TSPOs main function: its elevated levels in steroidogenic tissue and its primary location in the MOM. There is evidence of TSPO binding cholesterol with high affinity, however there is not currently evidence of TSPO transporting cholesterol. STAR, ACBD1, and ACBD3 are proteins thought to be associated with TSPO and steroidogenesis. However, the distribution of these proteins in various eukaryotes show little similarity suggesting that TSPO functions independently. The function of TSPO in steroid synthesis has been called into question because a well-cited research paper claimed that TSPO knockdown resulted in embryonic lethal mice, however there was no evidence presented from their study and this experiment did not produce the same results when repeated in later studies. There are also studies that show TSPO may not be involved in regulation of sterols, but instead may regulate cell stress. The elevated levels of TSPO during inflammation suggest a role for TSPO in cellular stress. Binding interactions with porphyrins and heme also support that TSPO may modulate stress levels. We used the phylogeny of TSPO in order to gain greater insight into the evolutionary function of TSPO. NCBI BLAST searches revealed that TSPO was present in bacteria and had a widespread but patchy distribution in a small set of eukaryotes. From these initial results, we were prompted to search a larger set of eukaryotes for TSPO. All of the prokaryotic and eukaryotic TSPO sequences were used to create a phylogenetic tree that would provide greater insight into the evolution and function of TSPO. If TSPO was from a common ancestor, it is probable that its function is related to sterol regulation whereas if gained in eukaryotes by horizontal gene transfer from bacteria its function is related to stress regulation. The phylogenetic tree was most consistent with an ancestral origin of TSPO with an evolutionary function related to steroid synthesis regulation. However, there is not sufficient research to confirm the function of TSPO.

Cooperative cellular phenotypes are universal across multicellular life. Division of labor, regulated proliferation, and controlled cell death are essential in the maintenance of a multicellular body. Breakdowns in these cooperative phenotypes are foundational in understanding the initiation and progression of neoplastic diseases, such as cancer. Cooperative cellular phenotypes are straightforward to characterize in extant species but the selective pressures that drove their emergence at the transition(s) to multicellularity have yet to be fully characterized. Here we seek to understand how a dynamic environment shaped the emergence of two mechanisms of regulated cell survival: apoptosis and senescence. We developed an agent-based model to test the time to extinction or stability in each of these phenotypes across three levels of stochastic environments.