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Automation and Optimization of Protein Expression and Purification on a Novel Robotic Platform
Author(s) -
Matthew Wollerton,
Richard Wales,
Jonathan A. Bullock,
Ian R. Hudson,
Mark Beggs
Publication year - 2006
Publication title -
jala
Language(s) - English
Resource type - Journals
eISSN - 1540-2452
pISSN - 1535-5535
DOI - 10.1016/j.jala.2006.08.002
Subject(s) - computational biology , bottleneck , protein expression , protein purification , automation , lysis , escherichia coli , target protein , affinity chromatography , biology , bioreactor , computer science , artificial intelligence , biochemistry , chemistry , engineering , gene , enzyme , embedded system , mechanical engineering , botany
This article describes a novel robotic system for protein expression and purification. This area has traditionally proved a bottleneck in pharmaceutical discovery owing to the difficulty and unpredictability of outcome in evaluating multiple sets of expression conditions that will yield biologically active protein in sufficient quantity to meet the demands of discovery teams. This position has been exacerbated by the requirement of structural biology groups to have access to 100 mg scale quantities of pure protein for early and complex structural studies. The Piccolo robotic system described here was able to perform multiple parallel induction, expression, and single stage protein purification of a target protein (6-His tagged β-galactosidase) using a model E. coli expression system. The Piccolo system monitored E. coli cell growth automatically and rescheduled tasks dynamically based on individual instances of cell growth within purpose built 24-well bioreactor units termed culture vessel blocks. On completion of protein expression, the system performed cell lysis and purification of the expressed β-galactosidase through Ni-NTA histidine affinity chromatography. We show that alterations in the induction and expression conditions used resulted in changes in the yield of expressed β-galactosidase. In addition to the E. coli studies described here, the system is also applicable for other bacterial species and for eukaryotic cell culture applications. The Piccolo robotic system has the capacity to allow exploration of hundreds of different combinations of expression variables within a working week thereby allowing rapid identification of optimal conditions for expressing the biologically active protein of interest. This strategy confers a significant increase in the parallel processing capability of protein expression groups and goes a long way to addressing the current protein expression bottleneck.

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