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Isolating the sources of heterogeneity in nanoparticle-cell interactions

View ORCID ProfileStuart T Johnston, Matthew Faria, Edmund J Crampin
doi: https://doi.org/10.1101/817569
Stuart T Johnston
1Systems Biology Laboratory, School of Mathematics and Statistics, and Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
2ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, Melbourne School of Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
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  • For correspondence: stuart.johnston@unimelb.edu.au
Matthew Faria
1Systems Biology Laboratory, School of Mathematics and Statistics, and Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
2ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, Melbourne School of Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
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Edmund J Crampin
1Systems Biology Laboratory, School of Mathematics and Statistics, and Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
2ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, Melbourne School of Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
3School of Medicine, Faculty of Medicine Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3010, Australia
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Abstract

Nanoparticles have the potential to enhance therapeutic success and reduce toxicity-based treatment side effects via the targeted delivery of drugs to cells. This delivery relies on complex interactions between numerous biological, chemical and physical processes. The intertwined nature of these processes has thus far hindered attempts to understand their individual impact. Variation in experimental data, such as the number of nanoparticles inside each cell, further inhibits understanding. Here we present a mathematical framework that is capable of examining the impact of individual processes during nanoparticle delivery. We demonstrate that variation in experimental nanoparticle uptake data can be explained by three factors: random nanoparticle motion; variation in nanoparticle-cell interactions; and variation in the maximum nanoparticle uptake per cell. Without all three factors, the experimental data cannot be explained. This work provides insight into biological mecha-nisms that cause heterogeneous responses to treatment, and enables precise identification of treatment-resistant cell subpopulations.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted October 24, 2019.
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Isolating the sources of heterogeneity in nanoparticle-cell interactions
Stuart T Johnston, Matthew Faria, Edmund J Crampin
bioRxiv 817569; doi: https://doi.org/10.1101/817569
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Isolating the sources of heterogeneity in nanoparticle-cell interactions
Stuart T Johnston, Matthew Faria, Edmund J Crampin
bioRxiv 817569; doi: https://doi.org/10.1101/817569

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