Abstract
Gene amplifications are universal mutations, contributing to important biological issues such as antibiotic resistance and cancer, as well as evolutionary topics like genetic diversity and gene clustering. Despite their widespread presence and importance, the underlying mechanisms of gene amplification mutations remain unclear. In order to increase our understanding of these mechanisms and investigate their genetic and environmental components, my research goal is to optimize a previously published gene amplification model system in the bacterium Acinetobacter baylyi. While the current Acinetobacter system has provided an elegant model to study gene amplification mutations, researchers have reported wide variation in measured mutation accumulation and mutant frequencies between repeated experiments. This variation has made it difficult to test and identify various genetic and environmental components involved in gene amplification mechanisms. To optimize this system, I tested different elements potentially causing experimental variation, specifically examining different ingredients of the selective minimum benzoate media and alternative protocol techniques in pre-growth media and incubation temperatures. Ultimately, this will ensure a higher repeatability and confidence level for future research investigating genetic and environmental variables, as well as increase experimental efficiency.