Host cell proteins (HCPs) are process-related impurities generated during biotherapeutic protein production. HCPs can be problematic if they pose a significant metabolic demand, degrade product quality, or contaminate the final product. Here, we present an effort to create a "clean" Chinese hamster ovary (CHO) cell by disrupting multiple genes to eliminate HCPs. Using a model of CHO cell protein secretion, we predict that the elimination of unnecessary HCPs could have a non-negligible impact on protein production. We analyze the HCP content of 6-protein, 11-protein, and 14-protein knockout clones. These cell lines exhibit a substantial reduction in total HCP content (40%-70%). We also observe higher productivity and improved growth characteristics in specific clones. The reduced HCP content facilitates purification of a monoclonal antibody. Thus, substantial improvements can be made in protein titer and purity through large-scale HCP deletion, providing an avenue to increased quality and affordability of high-value biopharmaceuticals.

Different methods for spectral preprocessing were compared in relation to the ability to distinguish between fungal isolates and growth stages for Penicillium camemberti grown on cheese substrate. The best classification results were obtained by temperatureand wavelength-extended multivariate signal correction (TWEMSC) preprocessing, whereby three patterns of variation in nearinfrared (NIR) log(1/R) spectra of fungal colonies could be separated mathematically: (1) physical light scattering and its wavelength dependency, (2) differences in light absorption of water due to varying sample temperature, etc., and (3) differences in light absorption between different fungal isolates. With this preprocessing, discriminant partial least squares (PLS) regression yielded 100% correct classification of three isolates, both within the cross-validated calibration set and in two independent test sets of samples.

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