Directed evolution methods based on high-throughput growth selection enable efficient discovery of enzymes with improved function in vivo. High-throughput selection is particularly useful when engineering oxygenases, which are sensitive to structural perturbations and prone to uncoupled activity. In this work, we combine the principle that reactive oxygen species (ROS) produced by uncoupled oxygenase activity are detrimental to cell fitness with a redox balance-based growth selection method for oxygenase engineering that enables concurrent advancement in catalytic activity and coupling efficiency. As a proof-of-concept, we engineered P450-BM3 for degradation of acenaphthene (ACN), a recalcitrant environmental pollutant. Selection of site-saturation mutagenesis libraries in E. coli strain MX203 identified P450-BM3 variants GVQ-AL and GVQ-D222N, which have both improved coupling efficiency and catalytic activity compared to the starting variant. Computational modeling indicates that the discovered mutations cooperatively optimize binding pocket shape complementarity to ACN, and shift the proteins conformational dynamics to favor the lid-closed, catalytically competent state. We further demonstrated that the selective pressure on coupling efficiency can be tuned by modulating cellular ROS defense mechanisms.

In Dung’s abstract argumentation, arguments are either acceptable or unacceptable, given a chosen notion of acceptability. This gives a coarse way to compare arguments. In this paper, we propose a counting approach for a more fine-gained assessment to arguments by counting the number of their respective attackers and defenders based on argument graph and argument game. An argument is more acceptable if the proponent puts forward more number of defenders for it and the opponent puts forward less number of attackers against it. We show that our counting model has two well-behaved properties: normalization and convergence. Then, we define a counting semantics based on this model, and investigate some general properties of the semantics.

Noncanonical cofactor biomimetics (NCBs) such as nicotinamide mononucleotide (NMN⁺) provide enhanced scalability for biomanufacturing. However, engineering enzymes to accept NCBs is difficult. Here, we establish a growth selection platform to evolve enzymes to utilize NMN⁺-based reducing power. This is based on an orthogonal, NMN⁺-dependent glycolytic pathway in Escherichia coli which can be coupled to any reciprocal enzyme to recycle the ensuing reduced NMN⁺. With a throughput of >10⁶ variants per iteration, the growth selection discovers a Lactobacillus pentosus NADH oxidase variant with ~10-fold increase in NMNH catalytic efficiency and enhanced activity for other NCBs. Molecular modeling and experimental validation suggest that instead of directly contacting NCBs, the mutations optimize the enzyme's global conformational dynamics to resemble the WT with the native cofactor bound. Restoring the enzyme's access to catalytically competent conformation states via deep navigation of protein sequence space with high-throughput evolution provides a universal route to engineer NCB-dependent enzymes.