4.8 Article

Single-particle combinatorial multiplexed liposome fusion mediated by DNA

Journal

NATURE CHEMISTRY
Volume 14, Issue 5, Pages 558-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41557-022-00912-5

Keywords

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Funding

  1. Villum Foundation [18333]
  2. Lundbeck Foundation [R250-2017-1293, R346-2020-1759]
  3. Villum Foundation young investigator fellowship [10099]
  4. Carlsberg Foundation Distinguished Associate Professor Program [CF16-0797]
  5. NovoNordisk Center for Biopharmaceuticals and Biobarriers in Drug Delivery [NNF16OC0021948]
  6. Novo Nordisk Foundation [NNF14CC0001]

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In this study, a single-particle combinatorial multiplexed liposome fusion mediated by DNA is presented, enabling multistep and non-deterministic fusion of nanocontainers. Efficient and leakage-free stochastic fusion sequences were observed for arrays of target liposomes functionalized with individual DNA strands and labeled with distinct chromophores. The method allows high-throughput combinatorial multiplex screens using minimal material.
Combinatorial high-throughput methodologies are central for both screening and discovery in synthetic biochemistry and biomedical sciences. They are, however, often reliant on large-scale analyses and thus limited by a long running time and excessive materials cost. We here present a single-particle combinatorial multiplexed liposome fusion mediated by DNA for parallelized multistep and non-deterministic fusion of individual subattolitre nanocontainers. We observed directly the efficient (>93%) and leakage free stochastic fusion sequences for arrays of surface-tethered target liposomes with six freely diffusing populations of cargo liposomes, each functionalized with individual lipidated single-stranded DNA and fluorescently barcoded by a distinct ratio of chromophores. The stochastic fusion resulted in a distinct permutation of fusion sequences for each autonomous nanocontainer. Real-time total internal reflection imaging allowed the direct observation of >16,000 fusions and 566 distinct fusion sequences accurately classified using machine learning. The high-density arrays of surface-tethered target nanocontainers (similar to 42,000 containers per mm(2)) offers entire combinatorial multiplex screens using only picograms of material.

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