All Publications

  • Detection and Discrimination of Single Nucleotide Polymorphisms by Quantification of CRISPR-Cas Catalytic Efficiency. Analytical chemistry Blanluet, C., Huyke, D. A., Ramachandran, A., Avaro, A. S., Santiago, J. G. 2022


    The specificity of CRISPR-Cas12 assays is attractive for the detection of single nucleotide polymorphisms (SNPs) implicated in, e.g., cancer and SARS-CoV-2 variants. Such assays often employ endpoint measurements of SNP or wild type (WT) activated Cas12 trans-cleavage activity; however, the fundamental kinetic effects of SNP versus WT activation remain unknown. We here show that endpoint-based assays are limited by arbitrary experimental choices (like used reporter concentration and assay duration) and work best for known target concentrations. More importantly, we show that SNP (versus WT) activation results in measurable kinetic shifts in the Cas12 trans-cleavage substrate affinity (KM) and apparent catalytic efficiency (kcat*/KM). To address endpoint-based assay limitations, we then develop an assay based on the quantification of Michaelis-Menten parameters and apply this assay to a 20 base pair WT target of the SARS-CoV-2 E gene. We find that the kcat*/KM measured for WT is 130-fold greater than the lowest kcat*/KM among all 60 measured SNPs (compared to a 4.8-fold for endpoint fluorescence of the same SNP). KM also offers a strong ability to distinguish SNPs, varies 27-fold over all the cases, and, importantly, is insensitive to the target concentration. Last, we point out trends among kinetic rates and SNP base and location within the CRISPR-Cas12 targeted region.

    View details for DOI 10.1021/acs.analchem.2c03338

    View details for PubMedID 36251847

  • Uncertainty Quantification of Michaelis-Menten Kinetic Rates and Its Application to the Analysis of CRISPR-Based Diagnostics. Angewandte Chemie (International ed. in English) Avaro, A. S., Santiago, J. G. 2022


    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 [[EQUATION]] , [[EQUATION]] , and catalytic efficiency [[EQUATION]] . 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.

    View details for DOI 10.1002/anie.202209527

    View details for PubMedID 36117459

  • Web-Based Open-Source Tool for Isotachophoresis. Analytical chemistry Avaro, A. S., Sun, Y., Jiang, K., Bahga, S. S., Santiago, J. G. 2021


    We present the development of a client-side web-based simulator for complex electrophoresis phenomena, including isotachophoresis. The simulation tool is called Client-based Application for Fast Electrophoresis Simulation (CAFES). CAFES uses the broad cross-browser compatibility of JavaScript to provide a rapid and easy-to-use tool for coupled unsteady electromigration, diffusion, and equilibrium electrolyte reactions among multiple weak electrolytes. The code uses a stationary grid (for simplicity) and an adaptive time step to provide reliable estimates of ion concentration dynamics (including pH profile evolution), requiring no prior installation nor compilation. CAFES also offers a large database of commonly used species and their relevant physicochemical properties. We present a validation of predictions from CAFES by comparing them to experimental data of peak- and plateau-mode isotachophoresis experiments. The code yields accurate estimates of interface velocity, plateau length and relative intensity, and pH variations while significantly reducing the computation time compared to existing codes. The tool is open-source and available for free at

    View details for DOI 10.1021/acs.analchem.1c03925

    View details for PubMedID 34788021