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.

Two-Component Nanoparticle Vaccine Displaying Glycosylated Spike S1 Domain Induces Neutralizing Antibody Response against SARS-CoV-2 Variants.

Vaccines pave the way out of the SARS-CoV-2 pandemic. Besides mRNA and adenoviral vector vaccines, effective protein-based vaccines are needed for immunization against current and emerging variants. We have developed a virus-like particle (VLP)-based vaccine using the baculovirus-insect cell expression system, a robust production platform known for its scalability, low cost, and safety. Baculoviruses were constructed encoding SARS-CoV-2 spike proteins: full-length S, stabilized secreted S, or the S1 domain. Since subunit S only partially protected mice from SARS-CoV-2 challenge, we produced S1 for conjugation to bacteriophage AP205 VLP nanoparticles using tag/catcher technology. The S1 yield in an insect-cell bioreactor was ∼11 mg/liter, and authentic protein folding, efficient glycosylation, partial trimerization, and ACE2 receptor binding was confirmed. Prime-boost immunization of mice with 0.5 µg S1-VLPs showed potent neutralizing antibody responses against Wuhan and UK/B.1.1.7 SARS-CoV-2 variants. This two-component nanoparticle vaccine can now be further developed to help alleviate the burden of COVID-19. IMPORTANCE Vaccination is essential to reduce disease severity and limit the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Protein-based vaccines are useful to vaccinate the world population and to boost immunity against emerging variants. Their safety profiles, production costs, and vaccine storage temperatures are advantageous compared to mRNA and adenovirus vector vaccines. Here, we use the versatile and scalable baculovirus expression vector system to generate a two-component nanoparticle vaccine to induce potent neutralizing antibody responses against SARS-CoV-2 variants. These nanoparticle vaccines can be quickly adapted as boosters by simply updating the antigen component.