Automated measurement of apparent protein solubility to rapidly assess complex parameter interactions

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• 作者：Annette Berg¹ ; ^{annette.berg@sanofi.com" class="auth_mail} ; Maren Schuetz² ; ^{marenschuetz@googlemail.com" class="auth_mail} ; Florian Dismer³ ; Juergen Hubbuch ; ^{juergen.hubbuch@kit.edu" class="auth_mail}
• 关键词：High throughput experimentation ; Cohn equation ; Protein solubility ; Precipitation ; Formulation ; Excipient screen
• 刊名：Food and Bioproducts Processing
• 出版年：April, 2014
• 年：2014
• 卷：92
• 期：2
• 页码：133-142
• 全文大小：2183 K

文摘

Characterization of protein solubility in downstream processing steps is important to either prevent protein aggregation, e.g. during inclusion body refolding, hydrophobic interaction chromatography and formulation or to decrease solubility, e.g. for selective precipitation or crystallization. In general we distinguish between thermodynamic solubility at equilibrium and kinetically driven apparent solubility.

In our study we used a high throughput screening method established on a liquid handling robot to rapidly assess an apparent solubility of lysozyme and its dependence on parameters such as pH, ionic strength and additive concentration. Combinatorial effects were measured in a reasonable amount of time with high data density and low material consumption.

Parameter interactions were observed between solvent pH and temperature. With increasing margin of pH from the isoelectric point, the effect of temperature was more pronounced. In addition, we found an influence of ionic strength on the additive induced changes in apparent solubility for all systems. PEG 300 and Tween 20 improved lysozyme apparent solubility at high salt concentrations. For sorbitol and sucrose, two distinct regions of maximum apparent solubility were found depending on the additive concentration. While an explanation for single parameter effects was possible, e.g. for pH by correlating net charge and solubility, this became difficult with increasing number of parameters. By reducing the experimental effort, it was possible to build a solid data basis to elucidate the mechanism of lysozyme aggregation and to find industrial relevant regions of increased solubility. Our approach is thus a powerful tool not only for process optimization but also for an increased understanding of precipitation.