Stochastic model-assisted development of efficient low-dose viral transduction in microfluidics

Area of Science:

• Biotechnology
• Microfluidics
• Gene Therapy

Background:

• Adenoviruses are widely used gene transfer vectors, but face challenges with infection efficiency and host cell toxicity.
• Existing methods often require high viral doses, increasing toxicity risks.

Purpose of the Study:

• To develop a versatile tool for enhanced gene expression using low viral doses.
• To create a microfluidic platform for controlled, sequential viral transduction.
• To couple experimental methods with a predictive mathematical model.

Main Methods:

• Development of a 10-channel microfluidic platform with sequential perfusion stages.
• Construction of a stochastic mathematical model for predicting cell infection and virus distribution.
• Coupling of the microfluidic system and mathematical model for experimental strategy optimization.
• Infection of human foreskin fibroblasts with adenoviruses carrying the EGFP gene.

Main Results:

• Demonstrated efficient viral transduction at low adenovirus doses through repeated pulses.
• Showcased enhanced exogenous gene expression using the sequential microfluidic infection system.
• Validated the predictive capabilities of the coupled mathematical and microfluidic model.

Conclusions:

• The developed microfluidic system and mathematical model offer an efficient strategy for low-dose adenovirus gene transfer.
• Sequential perfusion enhances gene expression and mitigates toxicity associated with higher viral loads.
• This approach provides a versatile tool for optimizing gene transfer applications.