DNA Condensates Containing client Silica Nanoparticles (SiNPs) for Theranostic Applications

Biomolecular condensates ̶ dynamic, biomolecule-enriched droplets which arise owing to Liquid-Liquid Phase Separation (LLPS) ̶ have been recently described to be implicated in many key vital processes within cells1,2. Although intracellular LLPS is extremely complex, the use of nucleic acids’ high programmability, governed by Watson–Crick–Franklin base-pairing, offers a straightforward mechanism to form predictable artificial condensates2. Specifically, DNA nanotechnology provides a powerful platform for the engineering of condensates with tuneable structures and functions by capitalizing on the vast toolbox available to the field3. Consequently, recent studies have demonstrated the formation of DNA condensates capable of selective-partitioning target molecules of interest, spatiotemporally controlled biochemical reactions and stimuli-responsive phase-separation and partitioning behaviours 4,5,6,7. Herein, we report on the partitioning of mesoporous silica nanoparticles (SiNPs) into DNA-based condensates. Our strategy leverages DNA nanostars as programmable building blocks for condensate formation, which are rationally designed to include an anchoring single-stranded DNA (ssDNA) overhang for the recruitment and local concentration of SiNPs functionalized with complementary DNA sequences. To explore the parameters governing nanoparticle partitioning, we constructed a toolbox of SiNPs varying in size (from 90 to 700 nm) and surface chemistry (DBCO-modified and carboxylated), allowing us to investigate the combined effects of particle size, surface properties, and sequence-specific hybridization on partitioning behaviour within the condensate. Our findings indicate that there is no strict size threshold limiting SiNP partitioning into DNA condensates and provide insights into how biomolecular condensates mediate selective client loading and molecular interactions. 1. S. Brocca, R. Grandori, S. Longhi, V. Uversky. International Journal of Molecular Sciences, 2020, 21(23), 9045. Doi:10.3390/ijms21239045 2. J. M. Stewart, S. Li, A. A. Tang, M. A. Klocke, M. V. Gobry, G. Fabrini, L. Di Michele, P. W. K. Rothemund, E. Franco. Nature Communications, 2024, 15(1), 6244. Doi:10.1038/s41467-024-50003-x 3. S. Agarwal, D. Osmanovic, M. Dizani, M.A. Klocke, E. Franco. Nature Communications, 2024, 15(1), 1915. Doi:10.1038/s41467-024-46266-z 4. S. Xu, Y. Ouyang, Y. Qin, D. Chen, Z. Duan, D. Song, D. Harries, F. Xia, I. Willner, F. Huang. Nature communications, 2025, 16(1), 3352. Doi:10.1038/s41467-025-58650-4 5. M. Dizani, D. Sorrentino, S. Agarwal, J. M. Stewart, E. Franco. Journal of the American Chemical Society, 2024, 146(43), 29344–29354. Doi:10.1021/jacs.4c07555 6. W. Yu, K. Jin, D. Wang, N. Wang, Y. Li, Y. Liu, J. Li, G. Du, X. Lv, J. Chen, R. Ledesma-Amaro, L. Liu. Nature Communications, 2024, 15(1), 7989. Doi:10.1038/s41467-024-52411-5 7. S. Zhou, X. Ju, H. Chen, Y. Zhang, J. Zheng, K. Wang, X. Yang, J. Liu, Angewandte Chemie (International ed. in English), 2025, e202505316. Doi:10.1002/anie.202505316