Simulation Modeling of Pooling for Combinatorial Protein Engineering

Abstract

Pooling in directed-evolution experiments will greatly increase the throughput of screening systems, but important parameters such as the number of good mutants created and the activity level increase of the good mutants will depend highly on the protein being engineered. The authors developed and validated a Monte Carlo simulation model of pooling that allows the testing of various scenarios in silico before starting experimentation. Using a simplified test system of 2 enzymes, β-galactosidase (supermutant, or greatly improved enzyme) and β-glucuronidase (dud, or enzyme with ancestral level of activity), the model accurately predicted the number of supermutants detected in experiments within a factor of 2. Additional simulations using more complex activity distributions show the versatility of the model. Pooling is most suited to cases such as the directed evolution of new function in a protein, where the background level of activity is minimized, making it easier to detect small increases in activity level. Pooling is most successful when a sensitive assay is employed. Using the model will increase the throughput of screening procedures for directed-evolution experiments and thus lead to speedier engineering of proteins. Key words: directed evolution, high-throughput screening, Monte Carlo simulation, protein engineering INTRODUCTION POOLING IS THE SIMULTANEOUS ANALYSIS of multiple samples followed by the deconvolution of pools that show promising results. Similar techniques have been used to increase throughput in combinatorial chemistry for drug discovery, 1,2 genome sequencing and chromosome mapping, 3-6 oligonucleotide microarrays, 7,8 and testing of biological samples such as blood for the presence of organisms, contaminants, or characteristics of interest. [9][10][11][12] As noted by Bruno et al,5 "Whenever the objective is to find 'needles in a haystack' a reliable test indicating whether at least one needle occurs in a specific part of the haystack can greatly facilitate the isolation of the needles." In each case, the object is to balance the increase in sample size obtained by pooling with the decrease in ability to detect the analyte of interest. If pools become too large, the signal from the organism in question will be lost in the background of the assay. Directed evolution is an iterative method of protein engineering in which 1 or more genes that code for the protein of interest are subjected to random mutagenesis or recombination.13,14 The resulting variants, or mutant proteins, must then be sorted into good and bad performers. If the activity of interest cannot be tied to host survival (selection), then each mutant must be assayed individually, a process called screening. Because of the time-and resourceintensive nature of screening, laboratories are typically limited to screening 10 5 to 10 7 mutants per round of directed evolution. 15 The capacity limit affects the way error-prone PCR experiments are conducted: because the higher the mutation frequency, the larger the number of inactive muta...

Directed Evolution of an Enantioselective Enoate‐Reductase: Testing the Utility of Iterative Saturation Mutagenesis

“…We reasoned that a viable approach could be the concept of pooling mutant libraries, as for example in the Bommarius approach. [31] In the present study we developed a different pooling strategy based on the original concept of Phizicky regarding the screening of predefined pools of proteins derived from genome sequencing as a method for linking defined biological activities with previously uncharacterized proteins. [32] A possible pitfall in this approach is the low signal to noise ratio of the detected parameter due to the high background; this relates to high amounts of cells without activity, thereby masking the sought-after enzyme property.…”

Gerichtete Evolution stereoselektiver Enzyme: Eine ergiebige Katalysator‐Quelle für asymmetrische Reaktionen

“…[84] Ein interessanter Fall betrifft die gelenkte Evolution [18] Obwohl ISM naturgemäß relativ kleine Mutantenbibliotheken erfordert, wollten wir das Screening-Aufkommen noch weiter durch Pooling [24] (Abschnitt 1) reduzieren. Ausgehend von der von Phizicky vorgestellten Idee, [85] wonach prädefinierte Pools von Proteinen aus Genomsequenzen gescreent werden, entwickelten wir ein stufenweises GC-basiertes Protokoll (Schema 22).…”

Discovery and Protein Engineering of Biocatalysts for Organic Synthesis

“…The first uses a set of related sequences, which are randomly combined (e.g., gene shuffling [38] ) whereas the latter focuses on changing one single protein sequence [e.g., error-prone polymerase chain reaction (epPCR [39] ) or site saturation mutagenesis [40] ]. An interesting method using Monte-Carlo simulations has been proven to successfully find active variants among many inactive clones, [43] but still a very sensitive activity assay is needed. [41] Directed evolution is a powerful tool in enzyme design, but still with limitations.…”