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A Coarse-Grained Simulation Framework to Study Polyethylenimine-DNA Nanoparticles in Gene Delivery
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- Author / Creator
- Mahajan, Subhamoy
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Cellular DNAs contain genetic information vital for the functioning of the cells. Corruption of this
information, or genetic disorders, can lead to various diseases. A potential treatment is to deliver
exogenous DNAs with the correct genetic information to malignant cells to achieve a therapeutic
response. However, DNAs are prone to degradation and are not efficient in overcoming cellular
barriers, thus requiring specialized gene carriers. Among the non-viral gene carriers, the polymer
polyethylenimine (PEI) has shown potential. Adding PEI to DNA forms nanoparticles (NPs) that
protect DNA from degradation and help it overcome cellular barriers such as cellular uptake,
endosomal escape, and nuclear trafficking. The efficacy of gene delivery depends on the properties
of PEIs and NPs but their relationship is not well understood. Current experimental studies are
limited because molecules inside cells cannot be observed with infinite precision, whereas current
molecular simulations have not modeled large systems relevant for gene delivery.
This dissertation studies various steps of PEI-DNA gene delivery using large-scale coarsegrained
(CG) molecular dynamics simulations. Three main studies have been performed. The first
study includes the development of a CG forcefield for PEIs that capture its diverse molecular
properties (degree of branching, molecular weight, and protonation ratio) and interaction with
DNA. In the second study, the molecular aggregation mechanism behind PEI-DNA NP formation
was explored using CG simulations with a large number of PEIs and DNAs at different N/P ratios.
The aggregation was found to be dependent on the diffusion of PEIs, DNAs, and NPs and their
electrostatic interactions. The N/P ratio was found to be an important control parameter for
electrostatic interactions that can alter NP properties such as size, size distribution, shape, and rate
of NP growth. Furthermore, for a high N/P ratio, a two-step addition of PEIs was found to make
the NPs smaller and more spherical, which has the potential to increase the efficacy of cellular uptake. The third study performed large-scale CG simulations to determine the effects of
endosomal acidification on PEI-DNA NPs, an inevitable step in gene delivery. Simulations of
endosomal acidification revealed that NP undergoes structural changes. NPs prepared at low N/P
ratio underwent further aggregation, whereas at high N/P ratio they dissociated. Dissociation of
NPs increased the osmotic pressure and reduced the NP’s size that respectively help endosomal
escape and nuclear trafficking. These findings support the observation of the strong efficacy of
gene delivery at a high N/P ratio. The structural changes in the NP during dissociation were
explained using a free energy landscape of PEIs, which revealed dissociation to be driven by
repulsion between PEIs bound to the same DNA pair and repulsion between DNAs. These
observations suggest a PEI with moderate molecular weight and degree of branching can increase
NP dissociation and thereby the efficacy of gene delivery.
To assist the comparison of molecular simulations with experimental fluorescence
microscopy used to study gene delivery, a new in-silico fluorescence microscopy technique was
developed. The new technique converted molecular simulation trajectories into images that are
comparable to the images obtained from experimental fluorescence microscopy. The crossvalidation
of in-silico images, experimental images, and molecular simulations bridged their
analysis and generated new information such as determining the occurrence of NP dissociation in
experimental images that were not originally reported. Comparison of in-silico images and
molecular simulations can also determine equivalence of properties for future comparison between
experiments and simulations. Furthermore, the comparison can be used to assess and develop
image analysis algorithms for experimental images.
Overall, this dissertation developed a framework for performing and analyzing large-scale
CG simulations of different steps in PEI-DNA gene delivery and its comparison with experiments. -
- Graduation date
- Spring 2022
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- Type of Item
- Thesis
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- Degree
- Doctor of Philosophy
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- License
- This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.