Collaborative Research: Characterization of Nanosensor Field-Assisted Detection of Biomarkers at Ultralow Concentration

合作研究：超低浓度生物标志物纳米传感器现场辅助检测的表征

• 批准号: 1064574
• 负责人: Walter Hu
• 金额: $ 17.51万
• 依托单位: University of Texas at Dallas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1064574&HistoricalAwards=false
• 关键词: Collaborative; Research; Characterization; Nanosensor; Field

1067502/1064574Liu/HuThis proposal aims to quantify the biomarker detection process and solve the puzzle ofbiosensor detection at ultralow concentration (femto molar or fM), which is of vital importance forearly diagnostics of diseases. Despite the significant progress achieved in biosensors in recentyears, the fundamental understanding of biosensor detection process and bio-nano interfacialinteraction at ultralow concentrations is very limited, which has hindered the interpretation ofexperimental results as well as sensor design. One example is the large discrepancy indetection time between experimental demonstration of Si nanowire sensor and the theoreticaldiffusion-reaction model. The goal of this proposal is to resolve the puzzles of biomarkerdetection process at ultralow concentrations and explore possible contributions fromelectrokinetics to detection speed acceleration through a novel multiphysicscomputational model with verification by an ultrasensitive bio-FET sensor. The proposedresearch will not only advance the molecular-level understanding of the biomarker-nanosensorinterface, but also help design lab-on-chip devices for molecular transportation and diagnosis,e.g., early cancer diagnosis by detecting protein at ultralow concentrations. We will provide aphysical and statistical interpretation of fM nanosensor detection process and explain the threeorders of magnitude difference in experimental and theoretically predicted detection responsetime. The objectives of the proposed work are:(1) Develop a Brownian adhesion dynamics model for biomarker detection process and performstochastic analysis of real-time detection results.(2) Characterize how internal or external electrokinetics such as electroosmosis flow,electrophoretic and dielectrophoretic force can potentially change biomarker diffusiondynamics, and enhance biomarker detection at ultralow concentrations.(3) Benchmark four nanosensor platforms in terms of limits on detection sensitivity andresponse time and suggest new sensor designs for faster detection.(4) Validate the model prediction through designed biosensing experiments by novel bioFETnanosensors with single molecule detection capability.(5) Provide a prediction and evaluation tool to help design nanosensors for optimal performance.Intellectual merits:1. Statistical insights to the nanosensor detection process will be provided through a Brownianadhesion dynamics approach, which cannot be achieved by the commonly used continuumdiffusion-reaction approach.2. Multiphysics modeling are applied for the first time to study how various inner and externalfields might accelerate the detection process, thus provide new design guidance for fasterdetection. The new design and modeling results will be evaluated through novel Si nanowirebio-FETs, which have single molecule detection capability that enables accurate and stablequantification of binding dynamics at ultralow concentration for the first time.The ultimate goal of the proposed work is to help develop novel field-assisted approach toenhance detection capability: concentrate biomarkers near nanosensor, increase binding rate,improve sensitivity, and shorten response time. An optimized testing platform will be the finaloutcome of this research.Broader impacts:The proposed multiphysics simulation-based method will provide a rigorous mathematicalmodel of biosensing at ultralow concentration. Results of this work will pave the way toward newbiosensor design. The computational tools developed from the proposed research will be sharedwithin the research community and subsequently aid in addressing other important bio-sensingissues that cannot be explored systematically by experiments alone. The education plan willincrease the awareness among high school teachers and students of the potential biomedicalapplications of nanotechnology, to advance understanding of nano-bio interfacial phenomena forstudents at all levels, and to increase minority participation in science and engineering.

本课题旨在量化生物标志物的检测过程，解决生物传感器在超低浓度（毫摩尔或fM）下的检测难题，对疾病的早期诊断具有重要意义。尽管近年来生物传感器取得了重大进展，但对超低浓度下生物传感器检测过程和生物纳米界面相互作用的基本理解非常有限，这阻碍了实验结果的解释以及传感器的设计。其中一个例子是硅纳米线传感器的实验演示与理论扩散反应模型的检测时间存在较大差异。本提案的目标是解决在超低浓度下的生物标记检测过程的难题，并通过一个新的多物理场计算模型和一个超灵敏的生物场效应晶体管传感器验证，探索电动力学对检测速度加速的可能贡献。所提出的研究不仅将推进对生物标志物-纳米传感器界面的分子水平理解，而且还有助于设计用于分子运输和诊断的芯片实验室设备，例如：，通过检测超低浓度的蛋白质进行早期癌症诊断。我们将提供fM纳米传感器检测过程的物理和统计解释，并解释实验和理论预测的检测响应时间的三个数量级差异。提出的工作目标是：(1)建立生物标志物检测过程的布朗粘附动力学模型，并对实时检测结果进行随机分析。(2)表征内部或外部电动力学，如电渗透流，电泳和介电泳力如何潜在地改变生物标志物扩散动力学，并在超低浓度下增强生物标志物检测。(3)对四种纳米传感器平台的检测灵敏度和响应时间进行了基准测试，并提出了更快检测的新传感器设计。(4)通过设计具有单分子检测能力的新型生物场效应晶体管纳米传感器进行生物传感实验，验证模型预测。(5)为纳米传感器的优化设计提供预测和评估工具。知识的优点:1。对纳米传感器检测过程的统计见解将通过布朗粘附动力学方法提供，这是常用的连续扩散反应方法无法实现的。首次应用多物理场模型来研究不同的内外场如何加速探测过程，从而为更快的探测提供新的设计指导。新的设计和建模结果将通过新型硅纳米线生物场效应管进行评估，该场效应管具有单分子检测能力，首次能够在超低浓度下精确和稳定地量化结合动力学。这项工作的最终目标是帮助开发新的现场辅助方法来增强检测能力：将生物标志物集中在纳米传感器附近，提高结合率，提高灵敏度，缩短响应时间。优化后的测试平台将是本研究的最终成果。更广泛的影响：提出的基于多物理场模拟的方法将提供一个严格的超低浓度生物传感数学模型。这项工作的结果将为新的生物传感器设计铺平道路。从提议的研究中开发的计算工具将在研究社区内共享，并随后帮助解决其他重要的生物传感问题，这些问题不能单独通过实验系统地探索。该教育计划将提高高中教师和学生对纳米技术潜在生物医学应用的认识，促进各级学生对纳米生物界面现象的理解，并增加少数民族参与科学和工程。