Stochastic Model-Assisted Development of Efficient Low-Dose Viral Transduction in Microfluidics

Adenoviruses are commonly used in vitro as gene transfer vectors in multiple applications. Nevertheless, issues such as low infection efficiency and toxicity effects on host cells have not been resolved yet. This work aims at developing a new versatile tool to enhance the expression of transduced genes while working at low viral doses in a sequential manner. We developed a microfluidic platform with automatically controlled sequential perfusion stages, which includes 10 independent channels. In addition, we built a stochastic mathematical model, accounting for the discrete nature of cells and viruses, to predict not only the percentage of infected cells, but also the associated infecting-virus distribution in the cell population. Microfluidic system and mathematical model were coupled to define an efficient experimental strategy. We used human foreskin fibroblasts, infected by replication-incompetent adenoviruses carrying EGFP gene, as the testing system. Cell characterization was performed through fluorescence microscopy, followed by image analysis. We explored the effect of different aspects: perfusion, multiplicity of infection, and temporal patterns of infection. We demonstrated feasibility of performing efficient viral transduction at low doses, by repeated pulses of cell-virus contact. This procedure also enhanced the exogenous gene expression in the sequential microfluidic infection system compared to a single infection at a higher, nontoxic, viral dose.