Dissecting insect cell heterogeneity during influenza VLP production using single-cell transcriptomics.

Area of Science:

• Virology
• Molecular Biology
• Biotechnology

Background:

• Insect cell-baculovirus expression vector systems (IC-BEVS) are vital for high-titer recombinant protein production, including virus-like particles (VLPs).
• Cell-to-cell variability during baculovirus infection in insect cells is poorly understood, yet critical for therapeutic protein yields.
• The impact of insect cell heterogeneity on recombinant protein production using IC-BEVS requires detailed investigation.

Purpose of the Study:

• To dissect insect cell population heterogeneity during influenza VLP production in IC-BEVS.
• To characterize the dynamics of baculovirus infection at the single-cell level.
• To identify biological pathways affected by heterogeneity during VLP production.

Main Methods:

• Single-cell RNA sequencing (scRNA-seq) was employed to analyze High Five insect cells during influenza VLP production.
• Clustering and trajectory analysis were used to group cells based on baculovirus gene expression and track infection progression.
• Differential gene expression analysis identified key cellular pathways impacted during infection.

Main Results:

• Insect cell populations exhibit heterogeneity even prior to infection, influenced by factors like the cell cycle.
• Infected cells clustered based on baculovirus gene expression timing and level, correlating with influenza VLP transgene transcript counts.
• Trajectory analysis revealed dynamic changes in pathways including translation, protein folding, degradation, endocytosis, and energy metabolism during infection.

Conclusions:

• scRNA-seq is a powerful tool for dissecting cellular heterogeneity in IC-BEVS.
• Understanding cell variability and infection dynamics is crucial for optimizing recombinant protein production.
• This study provides a foundation for applying scRNA-seq to elucidate and enhance IC-BEVS processes for therapeutic protein manufacturing.