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Incorporation of Organ-Specific MicroRNA Target Sequences to Improve Gene Therapy Specificity:

Thesis advisor: Vassilios Bezzerides / The aim of this study was to utilize a massively parallel reporter assay (MPRA) to identify organ-specific microRNA (miRNA) target sequences to refine the timing and expression of transgene expression for gene therapy. We previously had developed a cardiac gene therapy for Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT) using a systemically delivered adeno-associated virus (AAV9) vector. We hypothesized that incorporation of organ specific miRNA target sites into our vector construct could improve our therapy’s tissue specificity due to the ability of miRNAs to silence transgene expression. Initially, we attempted to incorporate mir-124 target sequences into our vector to detarget the brain. Although these initial attempts were unsuccessful, the study allowed us to develop a protocol to test the effectiveness of miRNA target sequences. Thereafter, we developed a method to screen thousands of putative miRNA target sequences simultaneously. In this study, target sequences of miRNAs specific to the heart, brain and liver were incorporated into a plasmid library. This plasmid library was subsequently made into AAV and injected into mice from a CPVT transgenic line. Total DNA and RNA was later extracted from the target organs, converted into genomic DNA (gDNA) and complementary DNA (cDNA) libraries respectively, and sent for amplicon sequencing. We analyzed the results using Comparative Microbiome Analysis 2.0 software (CoMA) and a custom python script to count the occurrence of each specified barcode per sample. In doing so, we showed that the miRNA suppression mechanism is not only effective but also organ specific. Furthermore, we developed a second script to create a combinatorial library from a set list of miRNA target sequences enabling us to efficiently test thousands of target sequence combinations at once. In doing so, we will be able to identify effective miRNA target sequence combinations to further improve gene therapy specificity. / Thesis (BS) — Boston College, 2021. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Biology.

Identiferoai:union.ndltd.org:BOSTON/oai:dlib.bc.edu:bc-ir_109174
Date January 2021
CreatorsSamenuk, Thomas
PublisherBoston College
Source SetsBoston College
LanguageEnglish
Detected LanguageEnglish
TypeText, thesis
Formatelectronic, application/pdf
RightsCopyright is held by the author, with all rights reserved, unless otherwise noted.

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