Fluorescent Biosensor-Guided Engineering of Enzyme Cascades for Electrochemical Applications

Substrate channeling is a strategy for enhancing flux and yield in enzymatic cascades and is increasingly relevant for applications in biocatalysis, biotechnology, and bioelectrochemical systems. However, efforts to engineer channeling are limited by the lack of high-throughput methods to evaluate and optimize channeling efficiency. Here, we present a fluorescence-based screening assay to rapidly assess substrate channeling in a model system involving fumarase and malate dehydrogenase, two sequential enzymes from the Krebs cycle. By expressing genetic fusions in Escherichia coli, quantifying intermediate (malate) and product (NADH) formation in lysate using orthogonal fluorescent readouts, and comparing product-to-intermediate ratios, we screened a library of linker variants designed to promote electrostatic channeling. A top-performing construct was identified and validated through classical channeling assays. This hit demonstrated increased product yield and current output when immobilized on electrodes with a bilayer architecture, highlighting utility in bioelectrocatalysis. We further showed that the channeling linker could be applied to a de novo designed single-chain fumarase, which preserved channeling capability and exhibited improved thermal stability. These results establish a strategy for engineering and evolving substrate channeling, which can be extended to the screening of other multienzymatic cascades via the design of specific substrate-tailored fluorescent sensors, with broad implications for pathway optimization and enzyme design in synthetic biology, bioprocessing, and energy applications.

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Publication Details

Journal
ACS Catalysis
Published
2026-02-25
DOI
https://doi.org/10.1021/acscatal.5c08170
Primary Topic
Electrochemical sensors and biosensors
Type
article
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article

Fluorescent Biosensor-Guided Engineering of Enzyme Cascades for Electrochemical Applications

Ming C. Hammond, Nathan J. Ricks, Monica Brachi, Egor Baiarashov et al.
ACS Catalysis
Electrochemical sensors and biosensors
article

Fluorescent Biosensor-Guided Engineering of Enzyme Cascades for Electrochemical Applications

Ming C. Hammond, Nathan J. Ricks, Monica Brachi, Egor Baiarashov, FNU Arun, Shelley D. Minteer
article en

Abstract

Substrate channeling is a strategy for enhancing flux and yield in enzymatic cascades and is increasingly relevant for applications in biocatalysis, biotechnology, and bioelectrochemical systems. However, efforts to engineer channeling are limited by the lack of high-throughput methods to evaluate and optimize channeling efficiency. Here, we present a fluorescence-based screening assay to rapidly assess substrate channeling in a model system involving fumarase and malate dehydrogenase, two sequential enzymes from the Krebs cycle. By expressing genetic fusions in Escherichia coli, quantifying intermediate (malate) and product (NADH) formation in lysate using orthogonal fluorescent readouts, and comparing product-to-intermediate ratios, we screened a library of linker variants designed to promote electrostatic channeling. A top-performing construct was identified and validated through classical channeling assays. This hit demonstrated increased product yield and current output when immobilized on electrodes with a bilayer architecture, highlighting utility in bioelectrocatalysis. We further showed that the channeling linker could be applied to a de novo designed single-chain fumarase, which preserved channeling capability and exhibited improved thermal stability. These results establish a strategy for engineering and evolving substrate channeling, which can be extended to the screening of other multienzymatic cascades via the design of specific substrate-tailored fluorescent sensors, with broad implications for pathway optimization and enzyme design in synthetic biology, bioprocessing, and energy applications.

ACS CatalysisVol. 16(5)
Missouri University of Science and Technology (US), University of Utah (US), Center for Genomic Science (IT)
Affordable and clean energy
Openalex Percentile: Top 45%
Electrochemical sensors and biosensors
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