A Coarse-Grained Simulation Framework to Study Polyethylenimine-DNA Nanoparticles in Gene Delivery
Creators: Mahajan, Subhamoy
Publisher: name: University of Alberta Library
Year: 2022

<p>Cellular DNAs contain genetic information vital for the functioning of the cells. Corruption of this<br>
information, or genetic disorders, can lead to various diseases. A potential treatment is to deliver<br>
exogenous DNAs with the correct genetic information to malignant cells to achieve a therapeutic<br>
response. However, DNAs are prone to degradation and are not efficient in overcoming cellular<br>
barriers, thus requiring specialized gene carriers. Among the non-viral gene carriers, the polymer<br>
polyethylenimine (PEI) has shown potential. Adding PEI to DNA forms nanoparticles (NPs) that<br>
protect DNA from degradation and help it overcome cellular barriers such as cellular uptake,<br>
endosomal escape, and nuclear trafficking. The efficacy of gene delivery depends on the properties<br>
of PEIs and NPs but their relationship is not well understood. Current experimental studies are<br>
limited because molecules inside cells cannot be observed with infinite precision, whereas current<br>
molecular simulations have not modeled large systems relevant for gene delivery.<br>
This dissertation studies various steps of PEI-DNA gene delivery using large-scale coarsegrained<br>
(CG) molecular dynamics simulations. Three main studies have been performed. The first<br>
study includes the development of a CG forcefield for PEIs that capture its diverse molecular<br>
properties (degree of branching, molecular weight, and protonation ratio) and interaction with<br>
DNA. In the second study, the molecular aggregation mechanism behind PEI-DNA NP formation<br>
was explored using CG simulations with a large number of PEIs and DNAs at different N/P ratios.<br>
The aggregation was found to be dependent on the diffusion of PEIs, DNAs, and NPs and their<br>
electrostatic interactions. The N/P ratio was found to be an important control parameter for<br>
electrostatic interactions that can alter NP properties such as size, size distribution, shape, and rate<br>
of NP growth. Furthermore, for a high N/P ratio, a two-step addition of PEIs was found to make<br>
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<br>
endosomal acidification on PEI-DNA NPs, an inevitable step in gene delivery. Simulations of<br>
endosomal acidification revealed that NP undergoes structural changes. NPs prepared at low N/P<br>
ratio underwent further aggregation, whereas at high N/P ratio they dissociated. Dissociation of<br>
NPs increased the osmotic pressure and reduced the NP’s size that respectively help endosomal<br>
escape and nuclear trafficking. These findings support the observation of the strong efficacy of<br>
gene delivery at a high N/P ratio. The structural changes in the NP during dissociation were<br>
explained using a free energy landscape of PEIs, which revealed dissociation to be driven by<br>
repulsion between PEIs bound to the same DNA pair and repulsion between DNAs. These<br>
observations suggest a PEI with moderate molecular weight and degree of branching can increase<br>
NP dissociation and thereby the efficacy of gene delivery.<br>
To assist the comparison of molecular simulations with experimental fluorescence<br>
microscopy used to study gene delivery, a new in-silico fluorescence microscopy technique was<br>
developed. The new technique converted molecular simulation trajectories into images that are<br>
comparable to the images obtained from experimental fluorescence microscopy. The crossvalidation<br>
of in-silico images, experimental images, and molecular simulations bridged their<br>
analysis and generated new information such as determining the occurrence of NP dissociation in<br>
experimental images that were not originally reported. Comparison of in-silico images and<br>
molecular simulations can also determine equivalence of properties for future comparison between<br>
experiments and simulations. Furthermore, the comparison can be used to assess and develop<br>
image analysis algorithms for experimental images.<br>
Overall, this dissertation developed a framework for performing and analyzing large-scale<br>
CG simulations of different steps in PEI-DNA gene delivery and its comparison with experiments.</p>