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: 1067502
• 负责人: Yaling Liu
• 金额: $ 20.01万
• 依托单位: Lehigh University
• 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=1067502&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.

1067502/1064574 Liu/Huu该建议旨在量化生物标志物的检测过程，解决超低浓度(飞摩尔或FM)生物传感器检测的难题，这对疾病的早期诊断至关重要。尽管近年来生物传感器取得了长足的进步，但对超低浓度生物传感器的检测过程和生物-纳米界面相互作用的基本了解还很有限，这阻碍了对实验结果的解释和传感器的设计。一个例子是硅纳米线传感器的实验验证与理论扩散-反应模型的检测时间相差很大。这项建议的目的是解决超低浓度生物标志物检测过程中的难题，并通过一种新的多物理计算模型和超灵敏生物FET传感器的验证来探索电动力学对检测速度加速的可能贡献。这项研究不仅将促进对生物标记物-纳米传感器界面的分子水平的理解，还将有助于设计用于分子传输和诊断的芯片实验室设备，例如通过检测超低浓度蛋白质来进行早期癌症诊断。我们将提供调频纳米传感器检测过程的形而上学和统计解释，并解释在实验和理论预测的检测响应时间上的三个数量级的差异。这项工作的目标是：(1)建立生物标志物检测过程的布朗附着动力学模型，并对实时检测结果进行随机分析。(2)表征电渗流、电泳力和电泳力等内部或外部电动力学如何潜在地改变生物标志物的扩散动力学，(3)在检测灵敏度和响应时间方面对四个纳米传感器平台进行基准测试，并为更快的检测提出新的传感器设计。(4)通过设计具有单分子检测能力的新型生物FET纳米传感器的生物传感实验来验证模型预测。(5)提供预测和评估工具，帮助设计最佳性能的纳米传感器。智力优势：1.通过布朗附着动力学方法提供对纳米传感器检测过程的统计洞察，这是通常使用的连续扩散-反应方法无法实现的。首次应用多物理模型来研究各种内外电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。新的设计和模拟结果将通过新型的硅纳米管生物场效应管进行评估，这种新型的生物场效应管具有单分子检测能力，首次实现了超低浓度下结合动力学的准确和稳定的均衡化。拟议工作的最终目标是帮助开发新的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，改善灵敏度，并缩短响应时间。优化的测试平台将是这项研究的最终结果。广泛的影响：所提出的基于多物理模拟的方法将为超低浓度生物传感提供严格的数学模型。这项工作的结果将为新的生物传感器的设计铺平道路。根据拟议研究开发的计算工具将在研究界内共享，并随后帮助解决仅靠实验无法系统探索的其他重要生物传感问题。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，增进各级学生对纳米生物界面现象的理解，并增加少数人对科学和工程的参与。