Using a two species competitive binding model to predict expanded bed breakthrough of a recombinant protein expressed in a high cell density fermentation

Expanded Bed experiments were conducted using a mixed mode (MM) resin to capture and purify a recombinant protein produced in yeast fermentation. Expanded bed breakthrough profiles show an overshoot in column effluent concentration of the target protein in the presence of cells and other broth prote...

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Veröffentlicht in:Biotechnology and bioprocess engineering 2013, 18(3), , pp.546-559
Hauptverfasser: Kelly, William, Kamguia, Guy, Mullen, Peter, Ubiera, Antonio, Göklen, Kent, Huang, Zuyi, Jones, Gerard
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Sprache:eng
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Zusammenfassung:Expanded Bed experiments were conducted using a mixed mode (MM) resin to capture and purify a recombinant protein produced in yeast fermentation. Expanded bed breakthrough profiles show an overshoot in column effluent concentration of the target protein in the presence of cells and other broth proteins, similar to that seen by other researchers when loading two competing species onto packed beds. In this research, a numerical model assuming negligible axial dispersion is developed and first validated for columns loads that contain only the target protein. This model is solved by finite differences in a unique way that uses an embedded analytical-solution to increase solution speed and stability. To model expanded bed breakthrough of the target protein in the actual cell broth, it was assumed that the other non-product proteins in the broth compete for MM resin binding sites and might be represented as a second “average” species via a traditional two-component competitive Langmuir isotherm. Estimates of the Langmuir constant and broth concentration of this second species were then calculated from batch adsorption data. Using these parameters for the second species, and other batch-derived parameters for the target protein with this resin, this unique numerical modeling approach provided results that compare favorably to experimental breakthrough data at various flow rates. Finally, the model was employed for a parameter sensitivity analysis that shows which process variables are most important in determining breakthrough time and the shape and magnitude of the concentration overshoot.
ISSN:1226-8372
1976-3816
DOI:10.1007/s12257-012-0754-2