Collaborative Research: A Low-Cost, "Digital" Biosensing Platform with Single Protein Biomarker Sensitivity

合作研究：具有单一蛋白质生物标志物敏感性的低成本“数字”生物传感平台

• 批准号: 1916213
• 负责人: Jing Zhao
• 金额: $ 20.41万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1916213&HistoricalAwards=false
• 关键词: Collaborative; Research; Low; Cost; Digital

Accurate measurements of proteins are critical for modern biomedical research, particularly for early detection and monitoring of disease, systems biology, and new drug development. More specifically, sensitive, specific, fast, and low-cost detection of proteins biomarkers in patient samples is of importance for public health and a key component of future personalized diagnostics and therapy. To date, enzyme-linked immune-sorbent assays in all their variants are the most common sensing techniques employed to detect the presence of protein biomarkers. However, a number of limitations still exist that greatly diminish their broader applications due to the low-sensitivity, the requirement of a calibration plot to elucidate the results, and the need for advanced costly instruments for ultrasensitive measurement. This proposal aims to address the aforementioned drawbacks by developing a simple and low-cost, but potentially powerful sensor based on the integration of a two-level signal amplification sensing mechanism and machine-learning-enabled reliability. The developed sensing devices are particularly desirable for early disease detection, ideally capable of "digitally" (calibration-free) detecting the presence of biomarkers with excellent portability, adaptability, accuracy, and high throughput. The knowledge and technology gained from this research will be disseminated to the scientific community and industry. This project will impact the education of the graduate, undergraduate and high school students by integrating advanced biosensing knowledge into their educational and laboratory training, and also actively interacting with general public and industry companies.The proposed sensing device will allow immunoassay to be performed as a low-cost and digital (calibration-free) detection technique with potential single copy sensitivity through integration of three key components: 1) a coupled resonance between a piezoelectric substrate and a replaceable nanoimprinted acoustic wave micropillar resonance film "sticker", 2) a micron-sized mass amplifier realized through uniform silver enhancement of mono-dispersed gold nanoparticles conjugated with detection antibody, and 3) machine learning algorithms to be developed and trained to analyze the biosensing data in a reliable way, thus allowing more accurate detection. The number of the particles can be directly correlated to the number of biomarkers, realizing "digital" sensing. The developed methodology is not restricted to sandwich-type immunoassays, nor is the assay limited to any particular protein biomarker and therefore the develop sensor can be generalized as a universal platform for monitoring any biomolecule of interest such as protein biomarkers, viruses, and pathogens for assuring public health and biosafety. The work will revolutionize the acoustic wave-based biosensing platform if successful.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

蛋白质的准确测量对于现代生物医学研究至关重要，特别是对疾病，系统生物学和新药物开发的早期发现和监测。更具体地说，对患者样本中蛋白质生物标志物的敏感，特异性，快速和低成本检测对于公共卫生和未来个性化诊断和治疗的关键组成部分至关重要。迄今为止，在所有变体中，酶联免疫吸收测定是检测蛋白质生物标志物存在的最常见感应技术。但是，由于低敏，对阐明结果的校准图的需求以及对超敏感测量的高级代价工具的需求，仍然存在许多局限性，这些局限性仍然大大减少了其更广泛的应用。该提案旨在通过基于两级信号放大传感机制和机器学习启用的可靠性的集成来开发简单而低成本但可能具有强大功能的传感器来解决上述缺点。 对于早期疾病检测，开发的传感设备特别理想，理想能够“以数字方式”（无校准）检测具有良好可移植性，适应性，准确性和高吞吐量的生物标志物的存在。从这项研究中获得的知识和技术将被传播到科学界和工业。 This project will impact the education of the graduate, undergraduate and high school students by integrating advanced biosensing knowledge into their educational and laboratory training, and also actively interacting with general public and industry companies.The proposed sensing device will allow immunoassay to be performed as a low-cost and digital (calibration-free) detection technique with potential single copy sensitivity through integration of three key components: 1) a coupled resonance between a压电电底物和可替换的纳米印刷波微印微颗粒谐振膜“贴纸”，2）通过均匀的银色增强单分散金纳米粒子的均匀银色增强，通过均匀的银色增强，与检测抗体进行了分析和训练的综合综合综合综合的质量，以分析和训练有素的生物群体，从准确检测。粒子的数量可以与生物标志物的数量直接相关，从而意识到“数字”感应。开发的方法不仅限于三明治型免疫测定法，也不限于任何特定蛋白质生物标志物的测定法，因此开发传感器可以被概括为监测任何感兴趣的生物分子的通用平台，例如蛋白质生物标志物，病毒和病原体，以确保公共健康和生物属性。如果成功的话，这项工作将彻底改变基于声波的生物传感平台。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准被认为值得通过评估来获得支持。

项目成果

SERS-Enabled Sensitive Detection of Plant Volatile Biomarker Methyl Salicylate

SERS 灵敏检测植物挥发性生物标志物水杨酸甲酯

• DOI: 10.1021/acs.jpcc.1c09185
• 发表时间: 2022
• 期刊: The Journal of Physical Chemistry C
• 作者: Song, Chen;Wang, Yongchen;Lei, Yu;Zhao, Jing
• 通讯作者: Zhao, Jing