1 James C. Samuelson (ed.), Enzyme Engineering: Methods and Protocols, Methods in Molecular Biology, vol. 978, DOI 10.1007/978-1-62703-293-3_1, © Springer Science+Business Media New York 2013 Chapter 1 A Tripartite Fusion System for the Selection of Protein Variants with Increased Stability In Vivo Linda Foit and James C.A. Bardwell Abstract We describe here a genetic selection system that directly links protein stability to antibiotic resistance, allowing one to directly select for mutations that stabilize proteins in vivo. Our technique is based on a tripartite fusion in which the protein to be stabilized is inserted into the middle of the reporter protein b-lactamase via a flexible linker. The gene encoding the inserted protein is then mutagenized using error- prone PCR and the resulting plasmid library plated on media supplemented with increasing concentrations of b-lactam antibiotic. Mutations that stabilize the protein of interest can easily be identified on the basis of their increased antibiotic resistance compared to cells expressing the unmutated tripartite fusion. Key words: Genetic selection, Protein stability , Protein evolution, Mutagenesis, Reporter protein, Tripartite fusion, Sandwich fusion Most soluble, globular proteins exhibit only marginal thermody- namic stabilities between approximately -5 and -10 kcal/mol (1, 2). Such low protein stability imposes significant challenges on the use of these polypeptides in many biotechnological, biomedi- cal, and practical applications, where large amounts of stable and soluble protein are needed. The identification of stabilizing muta- tions, however, is difficult, since most random amino acid substitu- tions actually decrease stability (3–5). Computational methods that estimate the effect of mutations on protein stability are avail- able but usually require detailed structural knowledge about the target protein, information that is often not available. Unfortunately, though computational methods are often good at predicting the destabilizing effect of mutations they are generally less accurate at predicting stabilizing mutations (6). 1. Introduction