Massively parallel RNA device engineering
Abstract/Contents
- Abstract
- Synthetic RNA devices sense drugs and metabolites to precisely and dynamically control gene expression inside cells, with the potential to transform medicine and biomanufacturing. The unique advantage of RNA devices lies in RNA's capacity to generate novel sensors that nature has yet to evolve. This is enabled by SELEX (Systematic evolution of ligands by exponential enrichment), in which large nucleic acid libraries are iteratively enriched for high-affinity aptamers de novo to bind proteins or small molecules. However, the number of small molecule-binding aptamers is still severely limited, as only a handful have been reported to be successfully integrated into RNA devices for intracellular use. Currently available quantitative assays in mammalian cell systems are limited in throughput and standardization, which hinders rapid iteration and predictable reuse of engineered devices for biomedical applications. We aimed to develop new platform technologies that 1) significantly accelerate the design-build-test cycle of engineering RNA devices in mammalian cells by integrating existing aptamer sensors, and 2) streamline the de novo generation of RNA devices with novel sensing capabilities. Leveraging massively parallel RNA-seq and FACS-seq assays, we developed techniques for quantitative and high-throughput measurements of the regulatory function of ribozyme-based RNA devices at both the mRNA and protein expression levels directly inside mammalian cells. With the newly developed methods, we identified highly performing RNA devices that respond to theophylline, xanthine, cyclic-di-GMP and folinic acid from tens of thousands of device library sequences. Furthermore, we found sequence and structural motifs that underlie the function of this class of RNA devices, which may in turn inform future rational design. To facilitate the discovery of new small molecule RNA biosensors, we developed De novo Rapid In Vitro Evolution of RNA biosensors (DRIVER), an automated, in vitro evolution platform coupled with a NGS cleavage assay that directly generates small molecule-sensing RNA devices. By alternately selecting for cleaving and non-cleaving sequences in the absence and presence of complex small molecule pools, DRIVER efficiently enriches a library of 10^12-13 sequences for novel ribozyme-based RNA devices. Thus far, we have discovered novel RNA biosensors to a variety of plant natural products and therapeutics. Furthermore, we demonstrated that several in vitro evolved RNA biosensors can be directly applied to function inside yeast and mammalian cells. Finally, the data-rich nature of DRIVER will shed light on the sequence requirements of high-sensitivity RNA biosensors, which will benefit rational design of libraries towards more efficient evolution efforts.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Xiang, Shengnan |
|---|---|
| Degree supervisor | Smolke, Christina D |
| Thesis advisor | Smolke, Christina D |
| Thesis advisor | Altman, Russ |
| Thesis advisor | Covert, Markus |
| Degree committee member | Altman, Russ |
| Degree committee member | Covert, Markus |
| Associated with | Stanford University, Department of Bioengineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Joy S. Xiang. |
|---|---|
| Note | Submitted to the Department of Bioengineering. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Shengnan Xiang
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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