An automated method to evaluate the enzyme kinetics of β-glucosidases

On the reproducibility of enzyme reactions and kinetic modelling

Enzyme reactions are highly dependent on reaction conditions. To ensure reproducibility of enzyme reaction parameters, experiments need to be carefully designed and kinetic modeling meticulously executed. Furthermore, to enable quality control of enzyme reaction parameters, the experimental conditions, the modeling process as well as the raw data need to be reported comprehensively. By taking these steps, enzyme reaction parameters can be open and FAIR (findable, accessible, interoperable, re-usable) as well as repeatable, replicable and reproducible. This review discusses these requirements and provides a practical guide to designing initial rate experiments for the determination of enzyme reaction parameters and gives an open, FAIR and re-editable example of the kinetic modeling of an enzyme reaction. Both the guide and example are scripted with Python in Jupyter Notebooks and are publicly available (https://fairdomhub.org/investigations/483/snapshots/1). Finally, the prerequisites of automated data analysis and machine learning algorithms are briefly discussed to provide further motivation for the comprehensive, open and FAIR reporting of enzyme reaction parameters.

Simultaneous enzymatic activity modulation and rapid determination of enzyme kinetics by highly crystalline graphite dots

The research field in enzyme-based biotechnology urgently requires the discovery of new materials and methods with high-performance. Here we report that highly crystalline graphite dots (GDs) can modulate enzyme activities, and simultaneously allow for real-time measurements on enzyme kinetics in combination with mass spectrometry (MS). A well-defined modulation of lipolytic activities from inhibition to enhancement can be realized by selectively coupling lipase enzymes with GDs containing specific functional groups on the surface. As a unique feature of our approach, GDs in the enzyme reaction can simultaneously serve as a versatile matrix for rapid and sensitive detection of the residual enzyme substrate, the intermediate or final product of lipolytic digestion using MS technology. Therefore, enzyme kinetic data can be collected in a real-time, high-throughput format. This work provides a new platform for enzymological research in hybrid bio-catalytic processes with advanced nanotechnology.