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Recent discoveries in biology have highlighted the importance of protein and RNA-based condensates as an alternative to classical membrane-bound organelles. Here, we demonstrate the design of pure RNA condensates from nanostructured, star-shaped RNA motifs. We generate condensates using two different RNA nanostar architectures: multi-stranded nanostars whose binding interactions are programmed via linear overhangs, and single-stranded nanostars whose interactions are programmed via kissing loops. Through systematic sequence design, we demonstrate that both architectures can produce orthogonal (distinct and immiscible) condensates, which can be individually tracked via fluorogenic aptamers. We also show that aptamers make it possible to recruit peptides and proteins to the condensates with high specificity. Successful co-transcriptional formation of condensates from single-stranded nanostars suggests that they may be genetically encoded and produced in living cells. We provide a library of orthogonal RNA condensates that can be modularly customized and offer a route toward creating systems of functional artificial organelles for the task of compartmentalizing molecules and biochemical reactions. 

Condensation of RNA and proteins is central to cellular functions, and the ability to program it would be valuable in synthetic biology and synthetic cell science. Here we introduce a modular platform for engineering synthetic RNA condensates from tailor-made, branched RNA nanostructures that fold and assemble co-transcriptionally. Up to three orthogonal condensates can form simultaneously and selectively accumulate fluorophores through embedded fluorescent light-up aptamers. The RNA condensates can be expressed within synthetic cells to produce membrane-less organelles with a controlled number and relative size, and showing the ability to capture proteins using selective protein-binding aptamers. The affinity between otherwise orthogonal nanostructures can be modulated by introducing dedicated linker constructs, enabling the production of bi-phasic RNA condensates with a prescribed degree of interphase mixing and diverse morphologies. The in situ expression of programmable RNA condensates could underpin the spatial organization of functionalities in both biological and synthetic cells. 

The diversity and heterogeneity of biomarkers has made the development of general methods for single-step quantification of analytes difficult. For individual biomarkers, electrochemical methods that detect a conformational change in an affinity binder upon analyte binding have shown promise. However, because the conformational change must operate within a nanometer-scale working distance, an entirely new sensor, with a unique conformational change, must be developed for each analyte. Here, we demonstrate a modular electrochemical biosensor, built from DNA origami, which is easily adapted to diverse molecules by merely replacing its analyte binding domains. Instead of relying on a unique nanometer-scale movement of a single redox reporter, all sensor variants rely on the same 100-nm scale conformational change, which brings dozens of reporters close enough to a gold electrode surface that a signal can be measured via square-wave voltammetry, a standard electrochemical technique. To validate our sensor’s mechanism, we used single-stranded DNA as an analyte, and optimized the number of redox reporters and various linker lengths. Adaptation of the sensor to streptavidin and Platelet-Derived Growth Factor-BB (PDGF-BB) analytes was achieved by simply adding biotin or anti-PDGF aptamers to appropriate DNA linkers. Geometrically optimized streptavidin sensors exhibited signal gain and limit of detection markedly better than comparable reagentless electrochemical sensors. After use, the same sensors could be regenerated under mild conditions: Performance was largely maintained over four cycles of DNA strand displacement and rehybridization. By leveraging the modularity of DNA nanostructures, our work provides a straightforward route to the single-step quantification of arbitrary nucleic acids and proteins.