Expediting adenovirus titer assays via an algorithmic live-cell imaging technique

Area of Science:

• Biotechnology
• Virology
• Cell Biology

Background:

• Virus-based therapeutics require efficient manufacturing processes.
• Traditional infectious virus titration methods are slow and prone to errors, hindering development.
• Live-cell imaging offers potential for high-throughput analysis but lacks optimized parameters.

Purpose of the Study:

• To develop a high-throughput infectious titer assay for adenovirus using live-cell imaging.
• To establish an algorithmic approach for optimizing viewing and analysis parameters.
• To create a statistical workflow for accurate adenovirus quantification.

Main Methods:

• Utilized an Incucyte Live-Cell Analysis System for adenovirus expressing a GFP-transgene.
• Developed an algorithmic approach to optimize live-cell imaging parameters.
• Created a statistical workflow for quantifying infectious adenovirus in dilution series.
• Validated the assay against Hexon staining, a gold-standard method.

Main Results:

• Developed a high-throughput infectious titer assay for adenovirus.
• Achieved high correlation (Pearson coefficient of 0.9) with the gold-standard Hexon staining.
• Successfully adapted the assay for 96-well plates, increasing sample throughput fivefold.
• Demonstrated the applicability of the algorithmic approach and statistical workflow for similar assays.

Conclusions:

• The developed live-cell imaging assay provides a fast and accurate method for adenovirus titration in preclinical settings.
• Optimized viewing and analysis parameters are crucial for successful implementation of live-cell imaging assays.
• The methodology is adaptable for various virus titration applications, supporting advancements in virus-based therapeutics.