Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven 5612 AE, The Netherlands.
Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven 5612 AE, The Netherlands.
ACS Sens. 2023 Nov 24;8(11):4216-4225. doi: 10.1021/acssensors.3c01549. Epub 2023 Nov 13.
To control and optimize the speed of a molecular biosensor, it is crucial to quantify and understand the mechanisms that underlie the time-dependent response of the sensor. Here, we study how the kinetic properties of a particle-based sandwich immunosensor depend on underlying parameters, such as reactant concentrations and the size of the reaction chamber. The data of the measured sensor responses could be fitted with single-exponential curves, with characteristic response times that depend on the analyte concentration and the binder concentrations on the particle and substrate. By comparing characteristic response times at different incubation configurations, the data clarifies how two distinct reaction pathways play a role in the sandwich immunosensor, namely, analyte binding first to particles and thereafter to the substrate, and analyte binding first to the substrate and thereafter to a particle. For a concrete biosensor design, we found that the biosensor is dominated by the reaction pathway where analyte molecules bind first to the substrate and thereafter to a particle. Within this pathway, the binding of a particle to the substrate-bound analyte dominates the sensor response time. Thus, the probability of a particle interacting with the substrate was identified as the main direction to improve the speed of the biosensor while maintaining good sensitivity. We expect that the developed immunosensor and research methodology can be generally applied to understand the reaction mechanisms and optimize the kinetic properties of sandwich immunosensors with particle labels.
为了控制和优化分子生物传感器的速度,定量理解和阐明传感器时间响应的基础机制至关重要。在这里,我们研究了基于颗粒的三明治免疫传感器的动力学特性如何取决于潜在参数,例如反应物浓度和反应腔的大小。测量的传感器响应数据可以用单指数曲线拟合,特征响应时间取决于分析物浓度以及颗粒和基质上的结合物浓度。通过比较不同孵育配置下的特征响应时间,数据阐明了两种不同的反应途径如何在三明治免疫传感器中发挥作用,即分析物首先与颗粒结合,然后与基质结合,以及分析物首先与基质结合,然后与颗粒结合。对于具体的生物传感器设计,我们发现生物传感器主要由分析物分子首先与基质结合,然后与颗粒结合的反应途径主导。在这条途径中,颗粒与基质结合的分析物的结合主导着传感器的响应时间。因此,颗粒与基质相互作用的概率被确定为在保持良好灵敏度的同时提高生物传感器速度的主要方向。我们期望所开发的免疫传感器和研究方法可以广泛应用于理解反应机制并优化具有颗粒标记的三明治免疫传感器的动力学特性。