Abstract
Plants represent commercially relevant production systems for recombinant proteins and chemical compounds. Effective genetic engineering depends on precise control of heterologous gene expression, which remains challenging due to complex transcriptional and post-transcriptional regulation, endogenous gene silencing mechanisms, and notably because of limited number of tools for allowing robust, fine-tuned control of expression levels across different systems/organisms. Some of the most common issues associated with plant expression systems are addressed with our plant-optimized version of a previously developed fungal universal synthetic expression system (SES). Plant SES demonstrates several favorable characteristics for robust heterologous gene expression, including highly constitutive function with apparently reduced sensitivity to endogenous silencing in transient assays, without requiring p19 co‑expression under the tested conditions. These together provide simple, predictable tuning of gene expression levels, and the potential for very high expression levels of the target genes. In all these features, SES shows higher and more stable transcript levels than Cauliflower Mosaic Virus (CaMV) 35 S promoter-based constructs in our experimental setups. The functionality of plant SES was tested by expressing mCherry and three commercially relevant proteins: fungal glucose oxidase (GOX), protein A and human vascular endothelial growth factor 165 (VEGF16) from diverse organisms, supporting high-level accumulation of recombinant proteins. In addition, plant SES retains full functionality in both plant and fungal hosts, which makes this expression system a useful tool for a multitude of genetic engineering applications in other eukaryotic organisms.
| Original language | English |
|---|---|
| Article number | 62 |
| Journal | Plant Molecular Biology |
| Volume | 116 |
| DOIs | |
| Publication status | Published - 2026 |
| MoE publication type | A1 Journal article-refereed |
Funding
This work was supported by the Academy of Finland (grant 321853 to KMOC and grant 350592 to HR).
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