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.

蛋白质的精确测量对于现代生物医学研究至关重要，特别是对于疾病的早期检测和监测、系统生物学和新药开发。更具体地说，患者样品中蛋白质生物标志物的灵敏、特异、快速和低成本检测对于公共卫生是重要的，并且是未来个性化诊断和治疗的关键组成部分。迄今为止，酶联免疫吸附测定在其所有变体中是用于检测蛋白质生物标志物存在的最常见的传感技术。然而，由于低灵敏度，需要校准图来阐明结果，以及需要用于超灵敏测量的先进昂贵仪器，仍然存在许多限制，这大大减少了它们更广泛的应用。该提案旨在通过开发一种简单且低成本但潜在强大的传感器来解决上述缺点，该传感器基于两级信号放大感测机制和机器学习支持的可靠性的集成。 所开发的传感装置对于早期疾病检测是特别期望的，理想地能够以优异的便携性、适应性、准确性和高通量“数字化”（免校准）检测生物标志物的存在。从这项研究中获得的知识和技术将传播给科学界和工业界。该项目将影响研究生，本科生和高中生的教育，将先进的生物传感知识融入他们的教育和实验室培训，并积极与公众和行业公司互动。拟议的传感设备将允许免疫测定作为一种低成本和数字化的方法进行，通过整合三个关键组件，具有潜在单拷贝灵敏度的（免校准）检测技术：1）压电基片与可更换的纳米压印声波微柱共振膜“贴纸”之间的耦合共振，2）通过与检测抗体缀合的单分散金纳米颗粒的均匀银增强实现的微米级质量放大器，以及3）待开发和训练的机器学习算法，以可靠的方式分析生物传感数据，从而允许更准确的检测。颗粒的数量可以直接与生物标志物的数量相关，实现“数字化”传感。所开发的方法不限于免疫分析型免疫测定，也不限于任何特定的蛋白质生物标志物，因此开发传感器可以被推广为用于监测任何感兴趣的生物分子（例如蛋白质生物标志物、病毒和病原体）的通用平台，以确保公共健康和生物安全。这项工作将彻底改变声波为基础的生物传感平台，如果成功。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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