Research output: Contribution to journal › Article › peer-review
Kuo Ching Mei, Artur Ghazaryan, Er Zhen Teoh, Huw D. Summers, Yueting Li, Belén Ballesteros, Justyna Piasecka, Adam Walters, Robert C. Hider, Volker Mailänder, Khuloud T. Al-Jamal
Original language | English |
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Article number | 1802732 |
Journal | Advanced Materials |
Volume | 30 |
Issue number | 40 |
Early online date | 24 Aug 2018 |
DOIs | |
Accepted/In press | 11 Jul 2018 |
E-pub ahead of print | 24 Aug 2018 |
Published | 4 Oct 2018 |
Additional links |
adma.201802732.pdf, 2.58 MB, application/pdf
Uploaded date:21 Sep 2020
Version:Final published version
Licence:CC BY
Hard corona (HC) protein, i.e., the environmental proteins of the biological medium that are bound to a nanosurface, is known to affect the biological fate of a nanomedicine. Due to the size, curvature, and specific surface area (SSA) 3-factor interactions inherited in the traditional 3D nanoparticle, HC-dependent bio–nano interactions are often poorly probed and interpreted. Here, the first HC-by-design case study in 2D is demonstrated that sequentially and linearly changes the HC quantity using functionalized graphene oxide (GO) nanosheets. The HC quantity and HC quality are analyzed using NanoDrop and label-free liquid chromatography–mass spectrometry (LC-MS) followed by principal component analysis (PCA). Cellular responses (uptake and cytotoxicity in J774 cell model) are compared using imaging cytometry and the modified lactate dehydrogenase assays, respectively. Cellular uptake linearly and solely correlates with HC quantity (R2 = 0.99634). The nanotoxicity, analyzed by retrospective design of experiment (DoE), is found to be dependent on the nanomaterial uptake (primary), HC composition (secondary), and nanomaterial exposure dose (tertiary). This unique 2D design eliminates the size–curvature–SSA multifactor interactions and can serve as a reliable screening platform to uncover HC-dependent bio–nano interactions to enable the next-generation quality-by-design (QbD) nanomedicines for better clinical translation.
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