Volume 61, Issue 45 e202209527
Research Article

Uncertainty Quantification of Michaelis–Menten Kinetic Rates and Its Application to the Analysis of CRISPR-Based Diagnostics

Alexandre S. Avaro

Alexandre S. Avaro

Department of Mechanical Engineering, Stanford University, 418 Panama Mall, Stanford, CA 94305 USA

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Prof. Juan G. Santiago

Corresponding Author

Prof. Juan G. Santiago

Department of Mechanical Engineering, Stanford University, 418 Panama Mall, Stanford, CA 94305 USA

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First published: 19 September 2022
Citations: 18

Graphical Abstract

The estimation of Michaelis–Menten kinetic parameters is highly sensitive to small experimental errors, even though the quantification of such parameters is critical. Monte Carlo simulations show that the kinetic efficiency, which governs limit of detection of assays that require low background, is the most precise kinetic parameter.

Abstract

Michaelis–Menten kinetics is an essential model to rationalize enzyme reactions. The quantification of Michaelis–Menten parameters can be very challenging as it is sensitive to even small experimental errors. We here present a quantification of the uncertainty inherent to the experimental determination of kinetic rate parameters for enzymatic reactions. We study the influence of several sources of uncertainty and bias, including the inner filter effect, pipetting errors, number of points in the Michaelis–Menten curve, and flat-field correction. Using Monte Carlo simulations and analyses of experimental data, we compute typical uncertainties of urn:x-wiley:14337851:media:anie202209527:anie202209527-math-0001 , urn:x-wiley:14337851:media:anie202209527:anie202209527-math-0002 , and catalytic efficiency urn:x-wiley:14337851:media:anie202209527:anie202209527-math-0003 . As a salient example, we analyze the extraction of such parameters for CRISPR-Cas systems. CRISPR diagnostics have recently attracted much interest and yet reports of these enzymatic kinetic rates have been highly unreliable and inconsistent.

Conflict of interest

The authors declare no conflict of interest.

Data Availability Statement

The data that support the findings of this study are available in the supplementary material of this article.

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.