Experimental characterization and prediction of Escherichia coli host cell proteome retention during preparative chromatography.
Roxana DiselaTim NeijenhuisOlivier Le BussyGeoffroy GeldhofMarieke KlijnMartin PabstMarcel OttensPublished in: Biotechnology and bioengineering (2024)
Purification of recombinantly produced biopharmaceuticals involves removal of host cell material, such as host cell proteins (HCPs). For lysates of the common expression host Escherichia coli (E. coli) over 1500 unique proteins can be identified. Currently, understanding the behavior of individual HCPs for purification operations, such as preparative chromatography, is limited. Therefore, we aim to elucidate the elution behavior of individual HCPs from E. coli strain BLR(DE3) during chromatography. Understanding this complex mixture and knowing the chromatographic behavior of each individual HCP improves the ability for rational purification process design. Specifically, linear gradient experiments were performed using ion exchange (IEX) and hydrophobic interaction chromatography, coupled with mass spectrometry-based proteomics to map the retention of individual HCPs. We combined knowledge of protein location, function, and interaction available in literature to identify trends in elution behavior. Additionally, quantitative structure-property relationship models were trained relating the protein 3D structure to elution behavior during IEX. For the complete data set a model with a cross-validated R 2 of 0.55 was constructed, that could be improved to a R 2 of 0.70 by considering only monomeric proteins. Ultimately this study is a significant step toward greater process understanding.
Keyphrases
- mass spectrometry
- escherichia coli
- liquid chromatography
- high speed
- high performance liquid chromatography
- single cell
- tandem mass spectrometry
- cell therapy
- high resolution
- healthcare
- gas chromatography
- systematic review
- capillary electrophoresis
- poor prognosis
- stem cells
- ionic liquid
- binding protein
- staphylococcus aureus
- body composition
- protein protein
- pseudomonas aeruginosa
- small molecule
- electronic health record
- klebsiella pneumoniae
- mesenchymal stem cells
- machine learning
- high intensity
- high density
- resistance training