Stable and Promiscuous Galactose Oxidases Engineered by Directed Evolution, Atomistic Design, and Ancestral Sequence Reconstruction.

IF 3.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS ACS Synthetic Biology Pub Date : 2024-12-13 DOI:10.1021/acssynbio.4c00653
Merve Keser, Ivan Mateljak, Roman Kittl, Roland Ludwig, Valeria A Risso, Jose M Sanchez-Ruiz, David Gonzalez-Perez, Miguel Alcalde
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Abstract

Galactose oxidase (GOase) is a versatile biocatalyst with a wide range of potential applications, ranging from synthetic chemistry to bioelectrochemical devices. Previous GOase engineering by directed evolution generated the M-RQW mutant, with unprecedented new-to-nature oxidation activity at the C6-OH group of glucose, and a mutational backbone that helped to unlock its promiscuity toward other molecules, including secondary alcohols. In the current study, we have used the M-RQW mutant as a starting point to engineer a set of GOases that are very thermostable and that are easily produced at high titers in yeast, enzymes with latent activities applicable to sustainable chemistry. To boost the generation of sequence and functional diversity, the directed evolution workflow incorporated one-shot computational mutagenesis by the PROSS algorithm and ancestral sequence reconstruction. This synergetic approach helped produce a rapid rise in functional expression by Pichia pastoris, achieving g/L production in a fed-batch bioreactor while the different GOases designed were resistant to pH and high temperature, with T50 enhancements up to 27 °C over the parental M-RQW. These designs displayed latent activity against glucose and an array of secondary aromatic alcohols with different degrees of bulkiness, becoming a suitable point of departure for the future engineering of industrial GOases.

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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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