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A Highly Porous Metal-Organic Framework System to Deliver Payloads for Gene Knockdown

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Peer-reviewed

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Abstract

Since first reported, RNA interference (RNAi) has become a widely used tool for cellular genetic knockdown. However, RNA instability and susceptibility to enzymatic degradation have prevented its widespread clinical use. Thus, research efforts are seeking methods to protect the fragile RNA payload during delivery. Here, we report the use of a metal-organic framework (MOF) to load, protect, and deliver small interfering ribonucleic acids (siRNAs). We confirmed the protection of MOF-internalized siRNA from enzymatic degradation. Furthermore, through combined encapsulation of siRNA in the MOF with various cofactors (proton sponge, KALA peptide, and NH4Cl), we show that endosomal retention can be evaded and ensure that gene knockdown is efficacious. In vitro studies after siRNA-MOF complexation demonstrated up to 27% consistent knockdown. We use structured illumination microscopy (SIM) to study the complex’s endocytic uptake. Overall, we demonstrate the potential of these highly porous and biodegradable materials to improve the efficacy and efficiency of future gene therapies.

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Journal Title

Chem

Conference Name

Journal ISSN

2451-9308
2451-9294

Volume Title

5

Publisher

Elsevier

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Except where otherwised noted, this item's license is described as All rights reserved
Sponsorship
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (722380)
Engineering and Physical Sciences Research Council (EP/S009000/1)
Cancer Research UK (C14303/A17197)
Medical Research Council (MR/K015850/1)
Engineering and Physical Sciences Research Council (EP/H018301/1)
Wellcome Trust (089703/Z/09/Z)
Medical Research Council (MR/K02292X/1)
Engineering and Physical Sciences Research Council (EP/L015889/1)
This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (NanoMOFdeli), ERC-2016-COG 726380, and (SUPUVIR) no. 722380. M.H.T. thanks the Gates Cambridge Trust for funding, S. Haddad for helpful discussions, and A. Li for assistance with data visualization. D.F.-J. thanks the Royal Society for funding through a University Research Fellowship. S.B.d.Q.F., F.M.R., and D.I.J. were funded by Cancer Research UK Senior Group Leader Grant CRUK/A15678. O.K.F. gratefully acknowledges DTRA for financial support (grant HDTRA-1-14-1-0014). C.F.K. acknowledges funding from the UK Engineering and Physical Sciences Research Council (grants EP/L015889/1 and EP/H018301/1), the Wellcome Trust (grants 3-3249/Z/16/Z and 089703/Z/09/Z) and the UK Medical Research Council (grants MR/K015850/1 and MR/K02292X/1), and Infinitus (China) Ltd. Computational work was supported by the Cambridge High Performance Computing Cluster, Darwin.