Development of Persistent DNA Vectors for Safe and Lasting Non-viral Gene Therapies

Overview

Scaffold/MatrixAttachment Regions (S/MARs) are specific regions of DNA that help to stabilize chromatin structure and regulate gene expression by facilitating interactions between DNA and the nuclear matrix. Non-viral plasmid vectors used for gene therapy have severe limitations s uch as short -term cargo gene expression due to rapid loss of the plasmid DNA in the cell. The objective of this project was to develop a non-viral plasmid vector that is able to persist and replicate at high levels to combat the short gene expression from rapid loss and silencing of plasmid DNA. It was hypothesized that inserting S/MARs into proTLx-Kplasmids would cause the GFP and luciferase reporter genes in the plasmid to persist and replicate at a higher level. The project used subcloning to insert an N-DISar2 S/MAR element into a proTLx- Kplasmid that contained GFP and luciferase reporter genes. The resulting plasmid was transfected into M17 cells which had GFP, and luciferase intensity measured at intervals of every 5 cell passage. The cells transfected with the S/MARs proTLx-Kplasmids were compared to a control group of cells transfected with proTLx-Kplasmids that didn’t contain any S/MARs elements. From passage 5 to passage 10, the GFP expression from the cell with a S/MAR containing plasmid incr eased by 104 RLU while the cell without a S/MAR decreased by 4322 RLU. S/MAR elements aided plasmids in tethering to and entering the nucleus, to transcribe and replicate the genes at higher levels. Oregon A Novel Entropy Based Heuristic Algorithm For Solving The Maximum Matching Problem In K - partite Hypergraphs Arjun Agarwal Jesuit High School, Portland, OR The purpose of this research is to develop fast, efficient, and innovative algorithms to solve the maximum matching problem in k-partite hypergraphs using entropy -based heuristics. Matching in k-partite hypergraphs is a class of NP-complete partitioning problems in graph theory. 3D Matching (3DM), a special case of the problem when k = 3, was part of Karp’s 21 original NP-complete problems. Graph matching, an active area of computer science research, has extensive applications in network flows, finding winn ing strategies in perfect information games, and problems involving scheduling and planning of resources. Worst case performance of a factor of k from optimum is an existing gap of traditional heuristic algorithms, 3DM-RND, as they do not use any information about the state of the graph. Entropy based algorithms iteratively build the solution by optimizing the state of the graph at each step. Two variants of the algorithm, 3DM-ENT1 and 3DM -ENT2, were developed and compared to 3DM -RND. The hypergraphs were transformed into a regular graph and an optimum solution was generated by iteratively moving to a least constrained state based on vertex degrees. On an average, 3DM -ENT1, 3DM-ENT2 and 3DM-RND were within 5%, 10% and 30% of the optimum solutions. 3DM-ENT1 and 3DM-ENT2 performed 30% better than 3DM-RND. The time complexity of 3DM -RND, 3DM-ENT1 and 3DM -ENT2 are O(E2), O(E 3) and O(E2) respectively, where Eis the number of hyperedges in the graph. A novel connection density metric was developed to characterize topological properties of graphs and predict expected performance.

Competition history

• JSHS 2024 Category not listed

Resources

• National JSHS abstract book ↗

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