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Detecting and quantifying nanoparticle-mediated biomolecule delivery in plants

Nature Reviews Methods Primers volume 3, Article number: 16 (2023) Cite this article

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New nanomaterials are being developed for efficient biomolecule delivery to plants. However, detection and quantification of plant cell entry are challenging and currently rely on subjective methods that lack proper controls. The necessary considerations of performing nanoparticle-mediated delivery in plants and how to accurately quantify delivery efficiency are discussed.

The genetic engineering of plants may be the answer to sustainably feeding the growing global population under the changing climate. Yet, delivery of macromolecules to walled plant cells has been the bottleneck since the discovery of genetic manipulation techniques. Initially, plant genetic engineering research has relied on pathogenic bacteria, such as Agrobacterium tumefaciens, to deliver gene-editing cargoes to plants. However, these bacteria are highly limited by the species of plants that they can deliver to and cargo type, as they can only deliver DNA cargoes. More recently, various nanoparticle strategies have been developed to address the limitations of A. tumefaciens1,2,3. These nanoparticles are hypothesized to work independently of plant species, as they can enter the cells of numerous plant species and deliver a diverse set of genetic engineering cargoes, including DNA, RNA and proteins4,5,6,7. Therefore, nanoparticle-mediated biomolecule delivery can be the key approach for unlocking the full potential of plant genetic engineering.

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Fig. 1: Nanoparticle-mediated biomolecule delivery to plants.

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Acknowledgements

The author thanks the Resnick Sustainability Institute at Caltech and the Henry Luce Foundation for funding.

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  1. Department of Chemical Engineering, California Institute of Technology, Pasadena, CA, USA

    Gozde S. Demirer

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Correspondence to Gozde S. Demirer.

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Demirer, G.S. Detecting and quantifying nanoparticle-mediated biomolecule delivery in plants. Nat Rev Methods Primers 3, 16 (2023). https://doi.org/10.1038/s43586-023-00213-2

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