An Optofluidic Guided-Mode Resonance Platform for Binding Kinetics Applications

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Meryem Beyza Avci;Furkan Kocer;Nimet Yildirim-Tirgil;Chanunthorn Chananonnawathorn;Tossaporn Lertvanithphol;Mati Horprathum;Uraiwan Waiwijit;Sakoolkan Boonruang;Khwanchai Tantiwanichapan;Arif E. Cetin
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引用次数: 0

Abstract

Guided mode resonance (GMR) sensors have emerged as transformative tools in sensing technology, offering exceptional sensitivity, selectivity, and real-time, label-free detection capabilities across diverse applications, including medical diagnostics and environmental monitoring. Their miniaturization potential, cost-effective manufacturing, and wide dynamic range make GMR sensors highly versatile and commercially attractive. In this study, we present an optofluidic GMR platform tailored for real-time analysis of biomolecular interactions without the need for optical labels. The platform integrates a custom-built inverted microscopy system, a high-resolution multispectrometer setup with a spectral resolution of 0.15 nm, and an automated multipump fluid control system, enabling precise and efficient monitoring of binding kinetics between biomolecules. Key outcomes include a refractive index sensitivity of 201.73 nm/RIU and a demonstrated detection limit of 0.15 ng/mL for IgG protein, emphasizing the platform’s suitability for highly sensitive biodetection applications. Additionally, the automated flow methodology enhances efficiency and reproducibility by streamlining chip preparation, ligand/analyte incubation, and postexperiment cleaning, minimizing manual intervention and human error. The self-cleaning feature ensures contamination-free operation, facilitating seamless multiuse experiments. Furthermore, we determined the association constant during the binding of protein A/G and IgG, underscoring the platform’s applicability to real-time binding kinetics studies. These results establish our optofluidic GMR platform as a robust and precise tool for advancing the understanding of complex biomolecular processes.
结合动力学应用的光流体导模共振平台
导模共振(GMR)传感器已成为传感技术中的变革性工具,可在各种应用(包括医疗诊断和环境监测)中提供卓越的灵敏度、选择性和实时、无标签检测功能。它们的小型化潜力、低成本制造和宽动态范围使GMR传感器具有高度的通用性和商业吸引力。在这项研究中,我们提出了一个光流体GMR平台,专门用于实时分析生物分子相互作用,而不需要光学标签。该平台集成了一个定制的倒置显微镜系统,一个光谱分辨率为0.15 nm的高分辨率多光谱仪设置,以及一个自动化的多泵流体控制系统,能够精确有效地监测生物分子之间的结合动力学。主要结果包括折射率灵敏度为201.73 nm/RIU, IgG蛋白的检测限为0.15 ng/mL,强调该平台适用于高灵敏度的生物检测应用。此外,通过简化芯片制备、配体/分析物孵育和实验后清洗,自动化流程方法提高了效率和可重复性,最大限度地减少了人工干预和人为错误。自清洁功能,确保无污染操作,方便无缝多用途实验。此外,我们测定了蛋白A/G与IgG结合过程中的关联常数,强调了该平台对实时结合动力学研究的适用性。这些结果使我们的光流体GMR平台成为一种强大而精确的工具,可以促进对复杂生物分子过程的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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