Self-assembling mRNA origami (mRNA-OG), a class of unimolecular RNA nanostructures that encode protein-coding sequences within higher-order, programmable, and compact nucleic acid architectures, is developed and established as a new design parameter for mRNA therapeutics that can affect its functionality, delivery properties, and immune sensing.
Abstract
Messenger RNA (mRNA) therapeutics have transformed vaccination and protein replacement strategies, yet efforts to improve their performance have focused largely on sequence engineering, nucleotide modification, and delivery vehicles. Here we show that mRNA function can be controlled by rational design of higher-order RNA architectures. We develop self-assembling mRNA origami (mRNA-OG), a class of unimolecular RNA nanostructures that encode protein-coding sequences within higher-order, programmable, and compact nucleic acid architectures. Using computational design and experimental validation, we demonstrate that mRNA-OG folds into well-defined nanostructures while remaining translationally competent in mammalian cells. Although folded mRNA-OG recruits ribosomes comparably to unfolded constructs, it produces lower protein output, indicating that RNA architecture can directly influence translational efficiency. The compact geometry of mRNA-OG also enhances encapsulation by cationic lipid delivery systems, suggesting a structural route to improved cargo packaging. Beyond its effects on translation, mRNA architecture modulates innate immune recognition. In primary human dendritic cells, folded and unfolded mRNA-OG elicit distinct cytokine programs and differential activation of stress-response pathways, including a modest induction of the integrated stress response that is not fully explained by canonical PKR signaling. Our results establish programmable structure as a new design parameter for mRNA therapeutics that can affect its functionality, delivery properties, and immune sensing.
This review synthesizes the current design principles governing mRNA-DNA hybrid origami assembly, including helicity adjustment, crossover geometry and folding condition optimization, and examines the structural requirements for translational competence.
Eeva Enlund, Carmine D'Amico, Sharon Saarinen et al.· Current Opinion in Chemical...· 0 citations
Efficient intracellular delivery of neoantigen-encoded mRNAs is central to the development of effective cancer vaccines and immunotherapies. However, how the nanoscale geometry of delivery carriers impacts mRNA delivery remains poorly understood, largely because conventional delivery platforms do not readily permit sys...
Meng-Xi Zheng, A. Dwivedy, Dhanush Gandavadi et al.· bioRxiv· 0 citations
Messenger RNA (mRNA) vaccines have reshaped modern vaccinology by enabling rapid antigen design, scalable manufacturing, and coordinated induction of humoral and cellular immunity. Their clinical success has established mRNA as a versatile platform for infectious diseases, cancer immunotherapy, and emerging therapeutic...
Hong Wang, Ran Zhuo, Jun-Jun Wu et al.· Signal Transduction and Targ...· 0 citations
A quantitative framework based on five key performance dimensions: dynamic range, temporal kinetics, output efficiency, spatial fidelity, and cycle retention is proposed, which discusses the emerging roles for computational modeling and artificial intelligence in enabling multiobjective optimization of these metrics an...
Pengwen Chen, Abdulaziz Alhussan, P. Cullis et al.· ACS Nano Medicine· 0 citations
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.