Ribozyme-Enabled Tissue Specificity (RETS): A System for Precise Gene Expression without Specialized Promoters
Year: 2025
Type: article
Abstract: Tissue- or cell-type-specific expression of transgenes is often essential for interrogation of the biological phenomenon or predictable engineering of multicellular organisms but can be stymied by cryptic enhancers that make identification of promoters that generate desired expression profiles challenging. In plants, the months-to-years long timeline associated with prototyping putative tissue-specific promoters in transgenic lines deepens this challenge. We have developed a novel strategy called Ribozyme-Enabled Tissue S pecificity (RETS) that leverages the knowledge of where and when genes are expressed derived from transcriptomic studies to enable tissue-specific expression without needing characterized promoters. It uses a split self-splicing ribozyme based on a group I intron from Tetrahymena thermophila to enable the conditional reconstitution of a transgene mRNA in the presence of a secondary tissue-specific mRNA of choice. We elucidate the design features that enable flexible swapping of transgenes and targets, enhancing transgene expression, and circumventing host RNA interference responses. We then show that these innovations enable tissue-specific and dose-dependent expression of transgenes in Arabidopsis thaliana . Finally, we demonstrate the utility of RETS both for creating genetically encoded biosensors to study the spatiotemporal patterns of gene expression in planta and for engineering tissue-specific changes in organ size. RETS provides a novel avenue to study expression patterns of native loci with nondestructive imaging, complementing the weakness of existing approaches. Additionally, the spatiotemporal control of transgene expression afforded by RETS enables precision engineering of plant phenotypes, which will facilitate enhancing crops without the trade-offs associated with constitutive expression.
Source: ACS Synthetic Biology
Authors: Max M. Combest, Josh Conlin, Vivia Van De Mark, Morgan Boisen, Hadley Colwell, Arjun Khakhar
Institution: Colorado State University
Language: English
Subfield: Biotechnology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4417483908