Development of techniques for testing the effect of the E1 region on adenovirus integration /

Adenoviral vectors are currently the most widely used gene therapeutic vectors, but their inability to integrate into host chromosomal DNA shortened their transgene expression and limited their use in clinical trials. In this project, we initially planned to develop a technique to test the effect of the early region 1 (E1) on adenovirus integration by comparing the integration efficiencies between an E1-deleted adenoviral vector (SubE1) and an Elcontaining vector (SubE3). However, we did not harvest any SubE3 virus, even if we repeated the transfection and successfully rescued the SubE1 virus (2/4 transfections generated viruses) and positive control virus (6/6). The failure of rescuing SubE3 could be caused by the instability of the genomic plasmid pFG173, as it had frequent intemal deletions when we were purifying It. Therefore, we developed techniques to test the effect of E1 on homologous recombination (HR) since literature suggested that adenovirus integration is initiated by HR. We attempted to silence the E1 in 293 cells by transfecting E1A/B-specific small interfering RNA (siRNA). However, no silenced phenotype was observed, even if we varied the concentrations of E1A/B siRNA (from 30 nM to 270 nM) and checked the silencing effects at different time points (48, 72, 96 h). One possible explanation would be that the E1A/B siRNA sequences are not potent enough to Induce the silenced phenotype. For evaluating HR efficiencies, an HR assay system based on bacterial transfonmatJon was designed. We constmcted two plasmids ( designated as pUC19-dl1 and pUC19-dl2) containing different defective lacZa cassettes (forming white colonies after transformation) that can generate a functional lacZa cassette (forming blue colonies) through HR after transfecting into 293 cells. The HR efficiencies would be expressed as the percentages of the blue colonies among all the colonies. Unfortunately, after transfonnation of plasmid isolated from 293 cells, no colony was found, even at a transformation efficiency of 1.8x10^ colonies/pg pUC19, suggesting the sensitivity of this system was low. To enhance the sensitivity, PCR was used. We designed a set of primers that can only amplify the recombinant plasmid fomied through HR. Therefore, the HR efficiencies among different treatments can be evaluated by the amplification results, and this system could be used to test the effect of E1 region on adenovirus integration. In addition, to our knowledge there was no previous studies using PCR/ Realtime PCR to evaluate HR efficiency, so this system also provides a PCR-based method to carry out the HR assays.

Genetic programming for the RoboCup Rescue Simulation System

The Robocup Rescue Simulation System (RCRSS) is a dynamic system of multi-agent interaction, simulating a large-scale urban disaster scenario. Teams of rescue agents are charged with the tasks of minimizing civilian casualties and infrastructure damage while competing against limitations on time, communication, and awareness. This thesis provides the first known attempt of applying Genetic Programming (GP) to the development of behaviours necessary to perform well in the RCRSS. Specifically, this thesis studies the suitability of GP to evolve the operational behaviours required of each type of rescue agent in the RCRSS. The system developed is evaluated in terms of the consistency with which expected solutions are the target of convergence as well as by comparison to previous competition results. The results indicate that GP is capable of converging to some forms of expected behaviour, but that additional evolution in strategizing behaviours must be performed in order to become competitive. An enhancement to the standard GP algorithm is proposed which is shown to simplify the initial search space allowing evolution to occur much quicker. In addition, two forms of population are employed and compared in terms of their apparent effects on the evolution of control structures for intelligent rescue agents. The first is a single population in which each individual is comprised of three distinct trees for the respective control of three types of agents, the second is a set of three co-evolving subpopulations one for each type of agent. Multiple populations of cooperating individuals appear to achieve higher proficiencies in training, but testing on unseen instances raises the issue of overfitting.