(298c) Telecommunications Model of Lipoplex-Mediated Gene Delivery

Gene delivery systems transport genetic information encoded as DNA to cells or biological systems, which then transcribe and translate that information into functional proteins.  This process can be thought of as a type of nano-scale communication with the potential to directly alter endogenous gene expression and behavior with applications in functional genomics, tissue engineering, medical devices, and gene therapy.  Although viral gene delivery systems are efficient at gene transfer, nonviral systems are preferred because of their low immunogenicity, inexpensive synthesis, and easy modification.  In nonviral systems, the DNA is typically complexed with cationic lipids or polymers to facilitate gene transfer as the complex traverses putative intracellular barriers, the common culprits to low efficacy of these systems.  Current lack of understanding of the biological mediators of gene delivery limits the design potential of new systems.  Kinetic models can offer perspective and interpretation of unknown or complex cellular mechanisms involved in gene transfer.  However, current models are inadequate and provide only a segmented view of gene delivery kinetics and treat complex routing as averaged or rigid events that are not biologically accurate.  There is a need for new types of models that describe the complete gene delivery process with biological fitness to enable the design of more efficient systems.  

In this work, we propose taking a novel approach to model the nonviral gene delivery process using telecommunications modeling.  Delivery of genetic information to the cell nucleus can be considered in the same way as delivery of a packet of information to the destination computer within a packet switched computer network. In such a network, a packet containing the information is routed through several intermediate nodes before it reaches the destination, sometimes undergoing processing or transcoding within those nodes. This process is similar to gene transfer in which the complex must undergo various steps to achieve transgene expression: internalization, endosome escape, nuclear import, transcription, and translation.  These steps are synonymous with intermediate nodes modeled using queuing theory with several input and output servers.  Since biological processes within a cell can be considered as highly parallel, the queuing network model of gene delivery is solely dependent on kinetic constants.  Through various particle tracking studies, kinetic constants are available in literature which represent the average time for complexes to travel through the various steps in the gene delivery process.  

Here we used a layered communication protocol to model lipoplex delivery to an A431 epithelial cell line taking complex arrival and service time as Poisson processes.  Each cell in the system was considered to consist of a queuing network as simulated lipoplexes were fed into the system and routed to servers.  Stochastic averaging was used to simulate the transport process for a fixed number of individual cells.  Simulation results show a high degree of agreement with experimental data, including internalization, nuclear accumulation, and transfection efficiency.  Interestingly, a kinetic constant for nuclear localized plasmid transcriptional activity had to be incorporated, indicating an unaccounted for process or biological mechanism involved in gene transfer.  Our novel application of queuing theory for modeling nonviral gene delivery provides insight into the pathways and mechanisms of nonviral gene transfer, so that more efficient systems can be designed.