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The ribosome is the quintessential antibacterial drug target, with many structurally and mechanistically distinct classes of antibacterial agents acting by inhibiting ribosome function. Detecting and quantifying ribosome inhibition by small molecules and investigating their binding modes and mechanisms of action are critical to antibacterial drug discovery and development efforts. To develop a ribosome inhibition assay that is operationally simple, yet provides direct information on the drug target and the mechanism of action, we have developed engineered E. coli strains harboring an orthogonal ribosome controlled green fluorescent protein reporter that produce fluorescent signal when the O-ribosome is inhibited. As a proof of concept, we demonstrate that these strains act as sensitive and quantitative detectors of ribosome inhibition by a set of 12 structurally diverse 2-deoxystreptamine (2-DOS) aminoglycoside antibiotics, which target the A-site in helix 44 of the 16S rRNA. To prove the generality and promote the application of the system, we extended this system for detecting ribosome inhibition by a variety of structurally and mechanistically distinct drug classes targeting both small and large subunits of the ribosome. We have engineered E. coli strains capable of detecting O-ribosome inhibition by other drugs targeting the 16S rRNA including the non-2-DOS aminoglycosides streptomycin and kasugamycin, and the aminocyclitol spectinomycin. Through integration of the Ribo-T tethered ribosome system with our system, we can also detect ribosome inhibition by the 23S rRNA inhibitors erythromycin, lincomycin and linezolid. These results suggest the generalizability of our strategy. We then applied the system to screen a set of spectinomycin analogs with unknown activity to demonstrate potential application. Three spectinomycin analogs were shown to possess higher or similar anti-ribosome activity compared to the parent compound. We have also modified our system to enable rapid directed evolution of rRNA variants with specific properties from large rRNA libraries to study the impact of rRNA sequence variation on ribosome activity and drug resistance. By replacing the fluorescence reporter gene with the chloramphenicol acetyltransferase (CAT) gene, we are able to select for functional rRNA mutants and quantify their catalytic activities. A variety of drug-resistant and drug-dependent rRNA mutants, as well as hyper- and hypo-active mutants were found. We also performed directed evolution to select ribosome mutants capable of supporting cell growth, yet confer resistance to aminoglycoside antibiotics. Only two mutants (A1408G and G1491U) were identified from this experiment; and both mutants have broad spectrum aminoglycoside resistance. Our results demonstrate that the O-ribosome controlled reporter system is capable of efficiently identifying new rRNA mutants with unique properties. We suggest that our directed evolution approach has the potential to provide new insights into mechanisms of ribosome inhibition and evolution of antibiotic resistance.

In the United States, voting is one of the most fundamental rights protected by the federal law. However, there is a growing concern over voter disenfranchisement and system inequity caused by long waiting lines. Studies have found that inappropriate voting resource allocation has deterred hundreds of thousands of U.S. citizens from voting. This research proposes an analytic framework to quantify the number of deterred voters and assess the resulting political consequences. We apply this framework to the 2012 Sandoval County General Election in New Mexico to study whether electoral outcomes were altered by “effective disenfranchisement” for a few closely contested offices. Furthermore, Indifference-Zone Generalized Binary Search (IZGBS) is developed to determine the minimum sets of resources needed to satisfy a given service level for elections with one or multiple bottleneck resources. What makes the problem challenging is the service level generally needs to be evaluated using discrete event simulations, which is slow and noisy. For example, there are no analytical methods to estimate the waiting time of the 99th percentile voter. Thus, simulation-based ranking and selection (R&S), also known as design and analysis of R&S experiments, are preferred than stochastic integer programming methods in this type of problems. The proposed approach incorporates constrained R&S with Generalized Binary Search (GBS) to provide computationally efficient and rigorous solutions. It also explores the intuitive monotone assumption that adding resources cannot harm average performance for relevant Discrete Event Simulation (DES) models, which has received little attention in the simulation literature previously.The method is based on the assumption of normal populations (but not requiring equal variances). Therefore, special attention is given to quantile-related outputs that are associated with asymptotically normal estimates. The asymptote is in the number of simulated voters on Election Day, which is often over one thousand. Later, IZGBS is applied to the Franklin County of Ohio and Sandoval County of New Mexico to establish the resource requirement so that voters can expect to wait less than thirty minutes. Several topics are suggested for future research, including building on IZGBS to provide optimization solutions for more general problems.

In this thesis, a modified framework for a multinational manufacturing corporation is presented. A new pricing strategy is also proposed to determine reasonable prices candidates. Additionally, two new geographical orientations are applied, which are regional/global product specialization and transnational vertical integration. This framework could help an enterprise to determine geographical orientations, locations, manufacturing system configurations, technology levels, selling prices, as well as customer demands, and provide a reasonable combination of those factors to maximize the profit. The results of experiments show that the proposed pricing strategy is more efficient than the original one. In addition, the new geographical strategies provide more choices of locations, which make the framework more realistic.