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Fine tuning gene expression levels in mammalian cells with engineered microRNA target sites

Abstract:

Precise, analogue regulation of gene expression is critical for development, homeostasis and regeneration in mammals. In contrast, widely employed experimental and therapeutic approaches such as knock-in/out strategies are more suitable for binary control of gene activity, while RNA interference (RNAi) can lead to pervasive off-target effects and unpredictable levels of repression. In this thesis, I report on a method for precise control of gene expression levels in mammalian cells based on engineered, synthetic microRNA response elements (MREs). To develop this system, we first tested a small panel of rationally designed MREs with various mismatches to miR-17 or miR-21. These MRE variants exerted predictable, stepwise control over reporter gene expression in a human cell line. Next, to improve the precision of MRE-based gene tuning, we established a high-throughput sequencing approach for measuring the efficacy of thousands of miR-17 MRE variants in parallel. This allowed us to create a library of microRNA silencing-mediated fine-tuners (miSFITs) of varying strength that can be employed to control the expression of user specified genes. A selection of miSFITs enabled precise, predictable tuning of PD-1, a co-inhibitory receptor expressed on T-cells and an important target for anti-tumour immunotherapy. In addition to tuning a PD-1 transgene in Jurkat T-cells, we successfully introduced miSFITs into the endogenous PD-1 3’UTR in embryonic stem cells using the CRISPR/Cas9 system. To further demonstrate the value of this technology, we also used a panel of miSFITs to tune the expression of a tumour-associated antigen in a mouse melanoma model. This analysis revealed that antigen expression level is a key determinant of the anti-tumour immune response in vitro and in vivo. miSFITs are a powerful tool for modulating gene expression levels with applications in research and cellular engineering.

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Division:
MSD
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Author

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Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


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UUID:
uuid:204ab084-9a54-4e14-8a75-bd7042584de5
Deposit date:
2019-02-28
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