Secreted Trimeric Chikungunya Virus Spikes from Insect Cells : Production, Purification, and Glycosylation Status

Chikungunya virus (CHIKV) is a rapidly emerging mosquito-borne virus that causes a severe febrile illness with long-lasting arthralgia in humans. As there is no vaccine to protect humans and limit CHIKV epidemics, the virus continues to be a global public health concern. The CHIKV envelope glycoproteins E1 and E2 are important immunogens; therefore, the aim of this study is to produce trimeric CHIKV spikes in insect cells using the baculovirus expression system. The CHIKV E1 and E2 ectodomains were covalently coupled by a flexible linker that replaces the 6K transmembrane protein. The C-terminal E1 transmembrane was replaced by a Strep-tag II for the purification of secreted spikes from the culture fluid. After production in Sf9 suspension cells (product yields of 5.8–7.6 mg/L), the CHIKV spikes were purified by Strep-Tactin affinity chromatography, which successfully cleared the co-produced baculoviruses. Bis(sulfosuccinimidyl)suberate cross-linking demonstrated that the spikes are secreted as trimers. PNGase F treatment showed that the spikes are glycosylated. LC–MS/MS-based glycoproteomic analysis confirmed the glycosylation and revealed that the majority are of the mannose-or hybrid-type N-glycans and <2% have complex-type N-glycans. The LC –MS/MS analysis also revealed three O-glycosylation sites in E1. In conclusion, the trimeric, glycosylated CHIKV spikes have been successfully produced in insect cells and are now available for vaccination studies

Relocation of the attTn7 Transgene Insertion Site in Bacmid DNA Enhances Baculovirus Genome Stability and Recombinant Protein Expression in Insect Cells

Baculovirus expression vectors are successfully used for the commercial production of complex (glyco)proteins in eukaryotic cells. The genome engineering of single-copy baculovirus infectious clones (bacmids) in E. coli has been valuable in the study of baculovirus biology, but bacmids are not yet widely applied as expression vectors. An important limitation of first-generation bacmids for large-scale protein production is the rapid loss of gene of interest (GOI) expression. The instability is caused by the mini-F replicon in the bacmid backbone, which is non-essential for baculovirus replication in insect cells, and carries the adjacent GOI in between attTn7 transposition sites. In this paper, we test the hypothesis that relocation of the attTn7 transgene insertion site away from the mini-F replicon prevents deletion of the GOI, thereby resulting in higher and prolonged recombinant protein expression levels. We applied lambda red genome engineering combined with SacB counterselection to generate a series of bacmids with relocated attTn7 sites and tested their performance by comparing the relative expression levels of different GOIs. We conclude that GOI expression from the odv-e56 (pif-5) locus results in higher overall expression levels and is more stable over serial passages compared to the original bacmid. Finally, we evaluated this improved next-generation bacmid during a bioreactor scale-up of Sf9 insect cells in suspension to produce enveloped chikungunya virus-like particles as a model vaccine.</p

Real-time online monitoring of insect cell proliferation and baculovirus infection using digital differential holographic microscopy and machine learning

Real-time, detailed online information on cell cultures is essential for understanding modern biopharmaceutical production processes. The determination of key parameters, such as cell density and viability, is usually based on the offline sampling of bioreactors. Gathering offline samples is invasive, has a low time resolution, and risks altering or contaminating the production process. In contrast, measuring process parameters online provides more safety for the process, has a high time resolution, and thus can aid in timely process control actions. We used online double differential digital holographic microscopy (D3HM) and machine learning to perform non-invasive online cell concentration and viability monitoring of insect cell cultures in bioreactors. The performance of D3HM and the machine learning model was tested for a selected variety of baculovirus constructs, products, and multiplicities of infection (MOI). The results show that with online holographic microscopy insect cell proliferation and baculovirus infection can be monitored effectively in real time with high resolution for a broad range of process parameters and baculovirus constructs. The high-resolution data generated by D3HM showed the exact moment of peak cell densities and temporary events caused by feeding. Furthermore, D3HM allowed us to obtain information on the state of the cell culture at the individual cell level. Combining this detailed, real-time information about cell cultures with methodical machine learning models can increase process understanding, aid in decision-making, and allow for timely process control actions during bioreactor production of recombinant proteins