Proteomics in biomanufacturing control: Protein dynamics of CHO‐K1 cells and conditioned media during apoptosis and necrosis

Abstract

Cell viability has a critical impact on product quantity and quality during the biomanufacturing of therapeutic proteins. An advanced understanding of changes in the cellular and conditioned media proteomes upon cell stress and death is therefore needed for improved bioprocess control. Here, a high pH/low pH reversed phase data independent 2D-LC-MS discovery proteomics platform was applied to study the cellular and conditioned media proteomes of CHO-K1 apoptosis and necrosis models where cell death was induced by staurosporine exposure or aeration shear in a benchtop bioreactor, respectively. Functional classification of gene ontology terms related to molecular functions, biological processes, and cellular components revealed both cell death independent and specific features. In addition, label free quantitation using the Hi3 approach resulted in a comprehensive shortlist of 23 potential cell viability marker proteins with highest abundance and a significant increase in the conditioned media upon induction of cell death, including proteins related to cellular stress response, signal mediation, cytoskeletal organization, cell differentiation, cell interaction as well as metabolic and proteolytic enzymes which are interesting candidates for translating into targeted analysis platforms for monitoring bioprocessing response and increasing process control.

Mass spectrometric evaluation of upstream and downstream process influences on host cell protein patterns in biopharmaceutical products

“…Overall the intersection of HCPs for the four different mAbs within one platform process is high. The total number of identified proteins within the CCF is in agreement with current studies examining the CHO proteome or the secretome in general …”

Portable Analytical Techniques for Monitoring Volatile Organic Chemicals in Biomanufacturing Processes: Recent Advances and Limitations

“…Clustering methods seek to describe a dataset into groups, or clusters; classification methods attempt to predict information about an unknown sample based on previously acquired data. Common statistical methods for biomanufacturing monitoring include: principal component analysis (PCA) (Albrecht et al, 2018 ; Chen et al, 2020 ) linear discriminant analysis (LDA) (Wang et al, 2012 ; Silva et al, 2017 ), partial least square (PLS) regression/discrimination analysis (Kammies et al, 2016 ; Matthews et al, 2016 ; McCartney et al, 2019 ; Pontius et al, 2020 ; Zavala-Ortiz et al, 2020 ), and artificial neural network (ANN) (López et al, 2017 ; Oyetunde et al, 2018 ).…”

“…Common statistical methods for biomanufacturing monitoring include: principal component analysis (PCA) (Albrecht et al, 2018;Chen et al, 2020) linear discriminant analysis (LDA) (Wang et al, 2012;Silva et al, 2017), partial least square (PLS) regression/discrimination analysis (Kammies et al, 2016;Matthews et al, 2016;McCartney et al, 2019;Pontius et al, 2020;Zavala-Ortiz et al, 2020), and artificial neural network (ANN) (López et al, 2017;Oyetunde et al, 2018). Most e-noses for volatile gas measurement generally rely on the adsorption of gas molecules to the surface of sensors.…”

Fingerprint-based Protein Identification in Cell Culture Medium Using Environment-sensitive Turn-on Fluorescent Polymer

“…As these proteins reflect the state and function of cells for a given environment and time, the set of cell secretory proteins is regarded as a rich source of biomarkers for disease diagnosis and studies on drug sensitivity, as well as therapeutic outcome and prognosis. (1,2) In the field of cell engineering, the biomarker proteins secreted into culture supernatants are routinely monitored for the control of cultured-cell quality, i.e., guarantee of cell activity and function (3) and the in vitro assessment of chemotherapeutic agents. (4,5) Antibody-based techniques are the most widely used for the identification of secretory proteins, (6) with which the specific recognition of target proteins by antibodies affords sensitive detection.…”