Linda van Oosten

The novel mosquito‐borne Tembusu virus (TMUV, family Flaviviridae ) was discovered as the cause of a severe outbreak of egg‐drop syndrome affecting ducks in Southeast Asia in 2010. TMUV infection can also lead to high mortality in various additional avian species such as geese, pigeons, and chickens. This study describes the construction of an infectious cDNA clone of a contemporary duck‐isolate (TMUV WU2016). The virus recovered after transfection of BHK‐21 cells shows enhanced virus replication compared to the mosquito‐derived MM1775 strain. Next, the WU2016 cDNA clone was modified to create a SP6 promoter‐driven, self‐amplifying mRNA (replicon) capable of expressing a range of different reporter genes (Renilla luciferase, mScarlet, mCherry, and GFP) and viral (glyco)proteins of avian influenza virus (AIV; family Orthomyxoviridae ), infectious bursal disease virus (IDBV; family Bunyaviridae ) and infectious bronchitis virus (IBV; family Coronaviridae ). The current study demonstrates the flexibility of the TMUV replicon system, to produce different heterologous proteins over an extended period of time and its potential use as a platform technology for novel poultry vaccines.

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.