Development of GFP-based high-throughput screening system for directed evolution of glucose oxidase

Abstract

Glucose oxidase (GOx) mutants with higher activity or stability have important role in industry and in the development of biosensors and biofuel cells. Discovering these mutants can be time-consuming if appropriate high-throughput screening (HTS) systems are not available. GOx gene libraries were successfully screened and sorted using a HTS system based on GOx activity dependent fluorescent labeling of yeast cells with tyramids and quantification of the amount of expressed enzyme by yeast enhanced green fluorescent protein (yGFP) tagging and flow cytometry. For this purpose, we expressed wild type and a mutant GOx as a chimera with the yGFP to confirm differences in catalytic activity between wild-type and mutant GOx. Fluorescence of yGFP is preserved during expression of chimera, and also after the oxidative enzymatic reaction. We have obtained a 2.5-fold enrichment in population of cells expressing active enzyme, and percentage of enzyme variants with enzymatic mean activity higher than wild type activity was increased to 44% after a single round of GOx gene library sorting. We have found two mutants with 1.3 and 2.3-fold increase in Vmax values compared to the wtGOx. By simultaneous detection of protein expression level and enzyme activity we have increased the likelihood of finding GOx variants with increased activity in a single round of flow cytometry sorting.