MICA:Synthetic untranslated regions for direct delivery of therapeutic mRNAs

Injection of proteins is a common approach for vaccination and therapies where a protein is deficient, such as insulin for diabetes and monoclonal antibodies to treat various diseases, including cancer. An alternative way to provide proteins in patients is to inject an mRNA, which the body then uses to make the protein. This approach has particular utility in situations where a rapid response to a new infectious agent is required, for example in a pandemic. This is because manufacturing a novel mRNA is rapid and more predictable than manufacturing a protein. The efficacy of an mRNA in vivo is influenced by its stability and how well it can be translated to make the protein. These factors are governed in part by the sequences which flank the segment encoding the protein, known as the untranslated regions (UTRs). A stable, highly translated mRNA will produce more protein for longer, which has the potential to reduce the frequency of injections and the dose of mRNA required. This has the advantage of reducing side effects caused by an immune response to the injected mRNA. Furthermore, a smaller dose requirement reduces the manufacturing burden for scaling up a potential vaccine in a pandemic. Thus, there is a critical need to understand how UTRs work and use this knowledge to find the best UTRs to use for mRNA therapeutics.

In this project, we will use synthetic biology to generate novel UTRs which are stable and highly translatable. We will test the efficacy of these synthetic UTRs (SUTRs) in vitro and in vivo using mRNAs encoding proteins of relevance to viral pandemics. We will also develop an artificial intelligence approach to allow in silico design of SUTRs.

Injection of proteins is a common approach for vaccination and other therapies, such as insulin for diabetes and monoclonal antibodies to treat various diseases, including cancer. An alternative way to provide proteins in patients is direct injection of an appropriately formulated mRNA. This approach has particular utility in situations where a rapid response to a new infectious agent is required, for example in a pandemic. This is because manufacturing a novel mRNA is rapid and more predictable than proteins. The efficacy of an mRNA in vivo is influenced by its stability and translatability. These factors are governed in part by untranslated regions (UTRs) flanking the open reading frame. A stable, highly translated mRNA will produce more protein for longer, which has the potential to reduce the frequency of injections and the dose of mRNA required, reducing side effects caused by an immune response to the injected mRNA. Furthermore, a smaller dose requirement reduces the manufacturing burden for scaling up a potential vaccine in a pandemic. Thus, there is a critical need to understand the contribution of UTR sequence determinants to mRNA half-life and translation efficiency, and to use this knowledge to identify optimal UTRs for use in therapeutic mRNAs.
The stability and translatability of an mRNA are partly regulated by trans-acting factors (e.g. RNA binding proteins), which recognise motifs within the UTRs and bind to elicit their activities. We will combine motifs with desirable properties to create synthetic UTRs (SUTRs) selected for stability and translatability. We will also perform directed evolution on naturally occurring UTRs, selected for their intrinsic stability and translatability to generate UTRs with improved characteristics for in vivo administration. Using the knowledge gained from screening SUTRs we will develop an artificial intelligence approach for in silico design of UTRs with optimal properties tailored to specific target tissues.