Targeted Metabolic Analysis and MFA of Insect Cells Expressing Influenza HA-VLP

Abstract

Virus-like particles (VLPs) are versatile vaccine carriers for conferring broad protection against influenza by enabling high-level display of multiple hemagglutinin (HA) strains within the same particle construct. The insect cell-baculovirus expression vector system (IC-BEVS) is amongst the most suitable platforms for VLP expression; however, productivities vary greatly with particle complexity (i.e., valency) and the HA strain(s) to be expressed. Understanding the metabolic signatures of insect cells producing different HA-VLPs could help dissect the factors contributing to such fluctuations. In this study, the metabolic traces of insect cells during production of HA-VLPs with different valences and comprising HA strains from different groups/subtypes were assessed using targeted metabolic analysis and metabolic flux analysis. A total of 27 different HA-VLP variants were initially expressed, with titers varying from 32 to 512 HA titer/mL. Metabolic analysis of cells during the production of a subset of HA-VLPs distinct for each category (i.e., group 1 vs. 2, monovalent vs. multivalent) revealed that (i) expression of group-2 VLPs is more challenging than for group-1 ones; (ii) higher metabolic rates are not correlated with higher VLP expression; and (iii) specific metabolites (besides glucose and glutamine) are critical for central carbon metabolism during VLPs expression, e.g., asparagine, serine, glycine, and leucine. Principal component analysis of specific production/consumption rates suggests that HA group/subtype, rather than VLP valency, is the driving factor leading to differences during influenza HA-VLPs production. Nonetheless, no apparent correlation between a given metabolic footprint and expression of specific HA variant and/or VLP design could be derived. Overall, this work gives insights on the metabolic profile of insect High Five cells during the production of different HA-VLPs variants and highlights the importance of understanding the metabolic mechanisms that may play a role on this system’s productivity.