Protein Production and Crystallization at the Joint Center for Structural Genomics

By definition, structural genomics centers must be able to address a large number of diverse protein targets. The methods developed should permit parallel and cost-effective processing while allowing for the diverse nature of proteins. Our approach to this problem is a multi-tiered effort where targets are characterized and categorized by behavior and processed in parallel by appropriate methods. The Joint Center for Structural Genomics (JCSG) has applied this tactic to create a fully integrated and scaleable structure determination pipeline. Highlights of the development of the current pipeline for protein production and crystallization are presented here.     

Moving through three‐dimensional phase diagrams of monoclonal antibodies

Protein phase behavior characterization is a multivariate problem due to the high amount of influencing parameters and the diversity of the proteins. Single influences on the protein are not understood and fundamental knowledge remains to be obtained. For this purpose, a systematic screening method was developed to characterize the influence of fluid phase conditions on the phase behavior of proteins in three‐dimensional phase diagrams. This approach was applied to three monoclonal antibodies to investigate influences of pH, protein and salt concentrations, with five different salts being tested. Although differences exist between the antibodies, this extensive study confirmed the general applicability of the Hofmeister series over the broad parameter range analyzed. The influence of the different salts on the aggregation (crystallization and precipitation) probability was described qualitatively using this Hofmeister series, with a differentiation between crystallization and precipitation being impossible, however. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:1103–1113, 2014     

Application of simplex‐based experimental optimization to challenging bioprocess development problems: Case studies in downstream processing

The identification of feasible operating conditions during the early stages of bioprocess development is implemented frequently through High Throughput (HT) studies. These typically employ techniques based on regression analysis, such as Design of Experiments. In this work, an alternative approach, based on a previously developed variant of the Simplex algorithm, is compared to the conventional regression‐based method for three experimental systems involving polishing chromatography and protein refolding. This Simplex algorithm variant was found to be more effective in identifying superior operating conditions, and in fact it reached the global optimum in most cases involving multiple optima. By contrast, the regression‐based method often failed to reach the global optimum, and in many cases reached poor operating conditions. The Simplex‐based method is further shown to be robust in dealing with noisy experimental data, and requires fewer experiments than regression‐based methods to reach favorable operating conditions. The Simplex‐variant also lends itself to the use of HT analytical methods, when they are available, which can assist in avoiding analytical bottlenecks. It is suggested that this Simplex‐variant is ideally suited to rapid optimization in early‐phase process development. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:404–419, 2016     

温度影响蛋白质结晶的研究现状

温度控制作为调控蛋白质结晶过程的手段,在结晶实验中被广泛采用。热历史效应作为蛋白质结晶实验中新的影响因素,已被越来越多的科学家所重视。控制温度可以改变蛋白质的溶解度,进一步改变溶液的过饱和度,从而影响结晶过程。我们简要总结了温度对蛋白质结晶的影响及应用温度技术控制蛋白质晶体生长的各种技术,为蛋白质结晶工作提供理论和实验依据。