CHARACTERIZATION OF POLYUBIQUITIN CHAINS BY MASS SPECTROMETRY

The work outlined in this dissertation will allow biochemists and cellular biologists to characterize polyubiquitin chains involved in their cellular environment by following a facile mass spectrometric based workflow. The characterization of polyubiquitin chains has been of interest since their discovery in 1984. The profound effects of ubiquitination on the movement and processing of cellular proteins depend exclusively on the structures of mono and polyubiquitin modifications anchored or unanchored on the protein within the cellular environment. However, structure-function studies have been hindered by the difficulty in identifying complex chain structures due to limited instrument capabilities of the past. Genetic mutations or reiterative immunoprecipitations have been used previously to characterize the polyubiquitin chains, but their tedium makes it difficult to study a broad ubiquitinome. Top-down and middle-out mass spectral based proteomic studies have been reported for polyubiquitin and have had success in characterizing parts of the chain, but no method to date has been successful at differentiating all theoretical ubiquitin chain isomers (ubiquitin chain lengths from dimer to tetramer alone have 1340 possible isomers). The workflow presented here can identify chain length, topology and linkages present using a chromatographic-time-scale compatible, LC-MS/MS based workflow. To accomplish this feat, the strategy had to exploit the most recent advances in top-down mass spectrometry. This included the most advanced electron transfer dissociation (ETD) activation and sensitivity for large masses from the orbitrap Fusion Lumos. The spectral interpretation had to be done manually with the aid of a graphical interface to assign mass shifts because of a lack of software capable to interpret fragmentation across isopeptide linkages. However, the method outlined can be applied to any mass spectral based system granted it results in extensive fragmentation across the polyubiquitin chain; making this method adaptable to future advances in the field.

A Ride-Sharing System with High Capacity Vehicles and Flexible Meeting Points

In many major cities, fixed route transit systems such as bus and rail serve millions of trips per day. These systems have people collect at common locations (the station or stop), and board at common times (for example according to a predetermined schedule or headway). By using common service locations and times, these modes can consolidate many trips that have similar origins and destinations or overlapping routes. However, the routes are not sensitive to changing travel patterns, and have no way of identifying which trips are going unserved, or are poorly served, by the existing routes. On the opposite end of the spectrum, personal modes of transportation, such as a private vehicle or taxi, offer service to and from the exact origin and destination of a rider, at close to exactly the time they desire to travel. Despite the apparent increased convenience to users, the presence of a large number of small vehicles results in a disorganized, and potentially congested road network during high demand periods. The focus of the research presented in this paper is to develop a system that possesses both the on-demand nature of a personal mode, with the efficiency of shared modes. In this system, users submit their request for travel, but are asked to make small compromises in their origin and destination location by walking to a nearby meeting point, as well as slightly modifying their time of travel, in order to accommodate other passengers. Because the origin and destination location of the request can be adjusted, this is a more general case of the Dial-a-Ride problem with time windows. The solution methodology uses a graph clustering algorithm coupled with a greedy insertion technique. A case study is presented using actual requests for taxi trips in Washington DC, and shows a significant decrease in the number of vehicles required to serve the demand.