Identifying Intracellular pDNA Losses From a Model of Nonviral Gene Delivery

A Simple Queuing Model for Molecular Communications Receivers

The complexity of molecular communications system, involving a massive number of interacting entities, makes scalability a fundamental property of simulators and modeling tools. A typical scenario is that of targeted drug delivery systems, which makes use of biological nanomachines close to a biological target, able to release molecules in the diseased area. In this paper, we propose a simple but reliable receiver model for diffusion-based molecular communication systems tackling the time needed for analyzing such a system. The proposed model consists of using an equivalent markovian queuing model, which reproduces the aggregate behavior of thousands of receptors spread over the receiver surface. It takes into account not only the fact that the absorption of molecules can occur only through receptors, but also that absorption is not an instantaneous process and may require a significant time during which the receptor is not available to bind to other molecules. Our results, expressed in terms of number of absorbed molecules and average number of busy receptors, demonstrate that the proposed approach is in good agreement with results obtained through particle-based simulations of a large number of receptors, although the time taken for obtaining the results with the proposed model is an order of magnitudes lower than the simulation time. We believe that this model can be the precursor of novel class of models based on similar principles that allow realizing reliable simulations of much larger systems.

Stochastic Simulation of Cellular Metabolism

Increased technological methods have enabled the investigation of biology at nanoscale levels. Such systems require the use of computational methods to comprehend the complex interactions that occur. The dynamics of metabolic systems have been traditionally described utilizing differential equations without fully capturing the heterogeneity of biological systems. Stochastic modeling approaches have recently emerged with the capacity to incorporate the statistical properties of such systems. However, the processing of stochastic algorithms is a computationally intensive task with intrinsic limitations. Alternatively, the queueing theory approach, historically used in the evaluation of telecommunication networks, can significantly reduce the computational power required to generate simulated results while simultaneously reducing the expansion of errors. We present here the application of queueing theory to simulate stochastic metabolic networks with high efficiency. With the use of glycolysis as a well understood biological model, we demonstrate the power of the proposed modeling methods discussed herein. Furthermore, we describe the simulation and pharmacological inhibition of glycolysis to provide an example of modeling capabilities.

Effects of Circular DNA Length on Transfection Efficiency by Electroporation into HeLa Cells

The ability to produce extremely small and circular supercoiled vectors has opened new territory for improving non-viral gene therapy vectors. In this work, we compared transfection of supercoiled DNA vectors ranging from 383 to 4,548 bp, each encoding shRNA against GFP under control of the H1 promoter. We assessed knockdown of GFP by electroporation into HeLa cells. All of our vectors entered cells in comparable numbers when electroporated with equal moles of DNA. Despite similar cell entry, we found length-dependent differences in how efficiently the vectors knocked down GFP. As vector length increased up to 1,869 bp, GFP knockdown efficiency per mole of transfected DNA increased. From 1,869 to 4,257 bp, GFP knockdown efficiency per mole was steady, then decreased with increasing vector length. In comparing GFP knockdown with equal masses of vectors, we found that the shorter vectors transfect more efficiently per nanogram of DNA transfected. Our results rule out cell entry and DNA mass as determining factors for gene knockdown efficiency via electroporation. The length-dependent effects we have uncovered are likely explained by differences in nuclear translocation or transcription. These data add an important step towards clinical applications of non-viral vector delivery.