Colwell, H. | Search bioRxiv

bioRxiv2025

Elucidating design principles for Ribozyme-Enabled Tissue Specificity (RETS) to allow precise expression without specialized promoters.

Tissue- or cell type- specific expression of transgenes is often essential for interrogation of 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 Specificity (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 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 as well as for engineering tissue-specific changes in organ size. RETS provides a novel avenue to study expression patterns of native loci with non-destructive 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.

synthetic biology↗

bioRxiv2025

Molecular Bonsai: Elucidating the design principles for engineering plant organ size

Enhancements to crop morphology, such as the semi-dwarfing that helped drive the green revolution, are often driven by changes in gene expression. These are challenging to translate across species, which slows the rate of crop improvement. Synthetic transcription factors (SynTFs) offer a rapid alternative to generate targeted alterations to gene expression. However, the complexity of developmental pathways makes it unclear how to best apply them to predictably engineer morphology. In this work, we explore whether mathematical modeling can guide SynTF-based gene expression modulation to help elucidate the design principles of engineering organ size. We targeted genes in the phytohormone, gibberellin (GA), signaling pathway, which is a central regulator of cell expansion. We demonstrate that modulation of GA signaling gene expression can generate consistent dwarfing across tissues and environments in Arabidopsis thaliana, and that the degree of dwarfing is dependent on the strength of regulation, as predicted by modeling. We further validate the models predictive power by demonstrating its capacity to predict the qualitative impacts of different regulatory architectures for engineering organ size. Additionally, we develop expression parameterized models to quantitatively predict organ size and elucidate how temperature will affect growth. Finally, we show that these insights can be generalized for engineering organ size in tomato (Solanum lycopersicum). This work creates a framework for predictable engineering of an agriculturally important trait across tissues and plant species. It also serves as a proof-of-concept for how mathematical models can guide SynTF-based alterations in gene expression to enable bottom-up design of plant phenotypes. Significance StatementWhile traditional breeding approaches have identified mutations that enhance crop performance via targeted gene expression changes, these are not easily translated across varieties and species. Synthetic transcription factors (SynTFs) offer an avenue to generate such changes de novo, but the optimal regulatory architectures necessary to generate desired phenotypes remain unclear. We demonstrate how mathematical models can be used to guide SynTF deployment and elucidate the design principles for engineering organ size, an agriculturally important trait, via modulation of gibberellin signaling. In addition to revealing regulatory architectures that can consistently increase or decrease organ size across a range of tissues, environments, and plant species, this work demonstrates how model-guided SynTF-based modulation of gene dosage can be used to predictably engineer plants.

synthetic biology↗