Detection of Sub-Nanomolar Concentration of Trypsin by Thickness-Shear Mode Acoustic Biosensor and Spectrophotometry

Abstract

The determination of protease activity is very important for disease diagnosis, drug development, and quality and safety assurance for dairy products. Therefore, the development of low-cost and sensitive methods for assessing protease activity is crucial. We report two approaches for monitoring protease activity: in a volume and at surface, via colorimetric and acoustic wave-based biosensors operated in the thickness-shear mode (TSM), respectively. The TSM sensor was based on a β-casein substrate immobilized on a piezoelectric quartz crystal transducer. After an enzymatic reaction with trypsin, it cleaved the surface-bound β-casein, which increased the resonant frequency of the crystal. The limit of detection (LOD) was 0.48 ± 0.08 nM. A label-free colorimetric assay for trypsin detection has also been performed using β-casein and 6-mercaptohexanol (MCH) functionalized gold nanoparticles (AuNPs/MCH-β-casein). Due to the trypsin cleavage of β-casein, the gold nanoparticles lost shelter, and MCH increased the attractive force between the modified AuNPs. Consequently, AuNPs aggregated, and the red shift of the absorption spectra was observed. Spectrophotometric assay enabled an LOD of 0.42 ± 0.03 nM. The Michaelis-Menten constant, K_M, for reverse enzyme reaction has also been estimated by both methods. This value for the colorimetric assay (0.56 ± 0.10 nM) is lower in comparison with those for the TSM sensor (0.92 ± 0.44 nM). This is likely due to the better access of the trypsin to the β-casein substrate at the surface of AuNPs in comparison with those at the TSM transducer.

Keywords: AuNPs; acoustic wave biosensor; colorimetric assay; trypsin; β-casein.

Figure 1

The scheme for modification of the gold layer on a TSM transducer and the cleavage of β-casein by trypsin.

Figure 2

The scheme for modification of gold nanoparticles (AuNPs) by β-casein and by 6-mercapto-1-hexanol (MCH) as well as the cleavage of β-casein by trypsin. Before enzymatic digestion, functionalized AuNPs were stable due to steric stabilization. After the AuNPs were subjected to protease cleavage, the casein was removed from the surface of AuNPs/MCH/β-casein. This caused the destabilization of the NPs, followed by their aggregation.

Figure 3

Typical kinetics of the changes of resonant frequency, Δf, and motional resistance, ΔR_m, of the thickness-shear mode (TSM) transducer for various modifications. The additions of β-casein, trypsin, and washing of the surface by phosphate-buffered saline (PBS) are shown by arrows.

Figure 4

Plots of changes of frequency, Δf, and motional resistance, ΔR_m, vs. trypsin concentration (C_TRY). Statistically, a value for the standard deviation was obtained from three independent experiments at each trypsin concentration.

Figure 5

Plot of the normalized changes of the resonant frequency Δf_N vs. trypsin concentrations, C_TRY. Standard deviation values are obtained from three independent experiments. The red line is the fit according to the Langmuir isotherm (Equation (2)) with accuracy R² = 0.99.

Figure 6

UV-vis absorption spectra of gold nanoparticles (AuNPs): bare (black), modified by β-casein (red), and subsequently modified by 6-mercapto-1-hexanol (MCH) (blue) as well as AuNPs modified by MCH (magenta).

Figure 7

UV-vis absorption spectra of β-casein and MCH-conjugated AuNPs treated with 10 nM trypsin at different time points. Note that at time 0 and 0.01 min, the spectra are almost identical.

Figure 8

Calibration plots of colorimetric assay. (a) Changes in relative values of absorbance after β-casein and MCH functionalized gold nanoparticles (AuNPs/MCH-β-casein) exposure to trypsin (A₀—exposure time 0 min, A₁₅—exposure time 15 min.) vs. concentration of trypsin (C_TRY). Symbols are experimental data, and the red line is the best fit of Equation (3). (b) Linear part of the calibration curve for calculation of the limit of detection (LOD). Values are means ± SD (n = 3). Red line is the linear regression fit.