Currently, southern resident killer whales (Orcinus orca) comprise a population of eighty-seven individuals. It is believed that disturbance by vessels may affect key behaviors and mask echolocation, which is critical for foraging and communication. Within the Puget Sound, Southern Residents are exposed routinely to commercial whale watching, and vessel interaction has been listed as a contributing factor to their endangered status. The National Oceanic and Atmospheric Administration are currently implementing vessel guidelines to decrease anthropogenic influences on this population. Beginning in summer 2011 these federal laws came into affect. Understanding boater behavior on the water is essential for federal enforcement and revision of current laws. By working with Soundwatch, an organization that has been documenting vessel interactions for 18 years, I assisted in data collection, entry, and analyzing boater density and trends. In the summer of 2011 2,500 incidents were observed including violations of federal law and voluntary guidelines. The top incidents that were observed were being within 200 yards of a whale, being inshore of whales, and parking in their path. On average 12 vessels were surrounding this population on a daily basis, with the majority being whale watch boats. Private vessels, generally due to their irregularity on the water, do not generally know about the new federal law or guidelines. Resulting in private boats accounting for 58% of the observed incidents. In addition to assisting with data gathering and analyzing I will compare the 2011 results to 2010 report. Providing a summary of themes observed on the water and future recommendations for federal law revision. Moving forward it will be critical to enforce current laws, and understand the dynamics between vessels and whales. My project will provide a succinct summary of 2011 trends and compare them with previously observed boater interactions.

A key issue in synthetic biology is the evolutionary robustness of synthetic circuits. Creation of robust circuits requires the development of design criteria to extend evolutionary timescales, and insight into the relative evolutionary fitness of different circuit designs. Experimentally, this research requires the use of multiple cell culture runs that are time-consuming and laborious. To accelerate this work, development of a high-throughput, automated, and parallel mini-chemostat and turbidostat device is proposed. While the development of nutrient-replenishing chemostat devices dates back to 1950, and the usage of such devices is well-documented, even modern chemostats are not well-suited to evolutionary experiments. Current designs face significant issues of equipment fouling, specialized complexity, and prohibitive cost. Presently there is a lack of cost-effective options for highly parallel milliliter-scale chemostat devices which can be applied to problems in synthetic biology. The proposed device is small and modular, utilizing multiple standard petri dishes for parallel culture experiments. The design features integrated media refreshment and temperature control mechanisms. Visible and fluorescent direct-view, real-time imaging systems are included. The device is constructed of readily-available parts to maintain low cost. Parts are modular such that used petri dishes can be easily removed, disposed of, and replaced. The design is scalable such that numerous devices can be stacked or tiled for parallel experiments. At present, design and fabrication of the device hardware have been completed, and the device has been verified functional for an operational period of at least 24 hours. Directed evolution experiments to measure of loss-of-functionality mutations in engineered E. coli will be conducted to assess live-culture performance of the device. An open-source software package and electronic microcontroller system are being developed to allow for automated real-time measurement and customization of growth and measurement parameters.

Industry and academia often use approaches from systems biology in therapeutic protein production. Maximizing the yield of therapeutics from a cell culture is an important need. Current computational approaches use flux balance analysis (FBA) to predict outcomes given certain inputs with the goal of increased protein production. FBA is a method for tracking fluxes within a biological system and studying these systems quantitatively. While commonly implemented within the biotechnology industry, few studies quantitatively validate the results of FBA. This project attempts to conduct a thorough in silico comparison between fluxes determined through FBA and the steady-state fluxes via kinetic simulation. I developed a method for constructing realistic but synthetic networks. Each network features randomly-generated reactions, including a biomass function around which the reaction rates are optimized. The optimization of the model’s kinetic parameters is crucial, for FBA assumes such when determining its solution of fluxes. A genetic algorithm is then applied to select the combination of rate constants that optimize the biomass function. The fittest “organism” determined through genetic algorithms and in silico evolution and the resulting steady-state fluxes will then be statistically compared against the solution of FBA. This assessment of FBA using kinetic simulations could give the scientific community a clearer view of this methodology and its capabilities. Further experimentation and analysis of the findings could direct other groups to where exactly FBA succeeds and where it falls short, thus pointing out the areas that require additional attention. In addition, the construction of synthetic, randomly-generated metabolic networks is novel. The applications of these networks could expand beyond the intentions of this project. It could provide others with a useful tool for tutorial building and a limitless supply of artificial networks for testing and validating other methods or applications.