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Published on: July 10, 2016
Genetically engineered charge modifications to enhance protein separation in aqueous two-phase systems: Charge
1Department of Chemical Engineering, 2114 Sweeney Hall, Iowa State University, Ames, Iowa 50011.
Genetically engineered protein charge modifications significantly altered partitioning in aqueous two-phase systems. Attractive protein-polymer interactions drove nearly complete partitioning of beta-galactosidase and T4 lysozyme, enhancing separation efficiency.
Area of Science:
- Biochemistry
- Protein Engineering
- Separation Science
Background:
- Protein partitioning in aqueous two-phase systems is crucial for bioseparation.
- Genetically engineered charge modifications offer a method to control protein behavior.
- Previous work examined partitioning based on interfacial potential difference.
Purpose of the Study:
- To investigate charge-directed partitioning of modified proteins in PEG/dextran systems.
- To assess the impact of charged polymers (DEAE-dextran, dextran sulfate) on protein partitioning.
- To compare charge-driven partitioning with potential-driven partitioning.
Main Methods:
- Genetically engineered beta-galactosidase with charged peptide tails.
- Genetically engineered T4 lysozyme with charge-change point mutations.
- Utilized polyethylene glycol (PEG)/dextran systems with charged polymers.
Main Results:
- Attractive forces between proteins and charged polymers led to near-complete partitioning (e.g., beta-galactosidase to DEAE-dextran).
- Fusion tails caused up to 37-fold shifts in partition coefficient (K(p)), exceeding potential-driven effects.
- Point mutations in T4 lysozyme resulted in 4-7 fold shifts in K(p), stronger than potential-driven partitioning.
Conclusions:
- Charge-directed interactions, particularly attractive forces, strongly influence protein partitioning in aqueous two-phase systems.
- Genetically engineered charge modifications provide a powerful tool for enhancing protein separation.
- Protein-polymer aggregation due to strong charge interactions can lead to extreme partitioning outcomes.
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