Development of Modular Synthetic Sensors for Protein Biomarker Detection

用于蛋白质生物标志物检测的模块化合成传感器的开发

• 批准号: 10659642
• 负责人: LIVIU MOVILEANU
• 金额: $ 39.18万
• 依托单位: SYRACUSE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10659642
• 关键词: Address; Affinity; Anisotropy; Architecture; Area; Binding; Binding Proteins; Biological; Biological Assay; Biological Markers; Biosensor; Cells; Clinical; Complex; Crowding; Detection; Deterioration; Development; Diagnostic; Disease; Elements; Engineering; Epidermal Growth Factor Receptor; Event; Fingerprint; Fluorescence Polarization; Formulation; Goals; Healthcare; Human; Impairment; Kinetics; Knowledge; Label; Libraries; Liquid substance; Malignant Neoplasms; Mammalian Cell; Masks; Measurement; Membrane Proteins; Methods; Microelectrodes; Modification; Molecular; Names; Nanostructures; Nature; Noise; Outcome; Output; Performance; Physiologic pulse; Pore Proteins; Property; Protein Engineering; Proteins; Proteome; Proteomics; Reading; Reagent; Reporter; Research; Resolution; Sampling; Sensitivity and Specificity; Serum; Signal Transduction; Structure; Surface; Techniques; Technology; Therapeutic; Time; Validation; Variant; Work; antibody mimetics; biomarker discovery; biomarker performance; combinatorial; design; detection limit; detector; disease prognostic; high throughput technology; improved; next generation; operation; polypeptide; preservation; protein biomarkers; protein expression; scaffold; sensor; sensor technology; targeted biomarker; time use; tool; trait

Project summary Protein detection and biomarker profiling have wide-ranging significance in many areas of disease prognostics, diagnostics, and therapeutics. For example, the progression and development of various cancers are accompanied by alterations in specific protein expressions. These variations in different biofluids are indicative of disease-like conditions. A long-standing difficulty of existing methods is the detection of multiple proteins in a complex biological sample with high sensitivity and a broad dynamic range. In addition, scalable protein identification and quantification techniques are usually created with sacrificed sensitivity, so their applicability in clinical settings remains limited. To overcome these fundamental and technical shortcomings, we will develop, optimize, and validate a next-generation class of sensing elements for targeted protein biomarker detection at single-recognition event precision. These proposed studies aim to engineer synthetic sensors made of a single-polypeptide chain protein nanostructure. This protein nanostructure encompasses a membrane protein pore and a programmable protein binder. The protein pore is a reporter that generates an output signature, which depends on the identity and quantity of the biomarker. A programmable binder is a small antibody- mimetic scaffold, such as a monobody or an affibody, sampling the targeted biomarker in solution. Hence, a generic binder can be modified for multiple protein analytes. This way, such a modular design significantly expands the utility of these sensing elements for numerous biomarkers while preserving their high sensitivity and specificity using the resistive-pulse technique. This critical benefit is facilitated by the genetically encoded nature of these sensors so that they can form combinatorial libraries of tethered binders. These manipulations of modular pore-based detectors equipped with antibody-mimetic binders have not been conducted previously. They are intended for use in challenging biofluids, where specific binder-biomarker interactions will be unambiguously distinguished from nonspecific interactions of the medium constituents. Further advantages of this real-time and label-free technology include maintaining an amplified signal-to-noise ratio in a wide dynamic range due to the superior bandwidth of time-resolved electrical recordings. The expected immediate outcomes of these proposed studies will be the following: (i) development, optimization, and validation of monobody- and affibody-based sensors for protein detection; (ii) protein biomarker detection in multiplexed and high- throughput formulations; (iii) protein biomarker detection in heterogeneous solutions. These results will represent a platform for fingerprinting panels of multiple protein targets in biofluids without impairing the sensitivity of these determinations. This proposed research will impact quantitative proteomics and biosensor technology by providing a fundamental basis and tools for ultrasensitive biomarker detection.

项目概要 蛋白质检测和生物标志物分析在疾病预测的许多领域具有广泛的意义， 诊断和治疗。例如，各种癌症的进展和发展是 伴随着特定蛋白质表达的改变。不同生物体液中的这些差异具有指示性 类似疾病的情况。现有方法的一个长期存在的困难是检测一个蛋白质中的多种蛋白质。 具有高灵敏度和宽动态范围的复杂生物样品。此外，可扩展的蛋白质 识别和定量技术通常是在牺牲灵敏度的情况下创建的，因此它们的适用性 临床环境仍然有限。为了克服这些基本和技术缺陷，我们将开发， 优化并验证下一代传感元件，用于目标蛋白质生物标志物检测 单次识别事件精度。这些拟议的研究旨在设计由 单多肽链蛋白质纳米结构。这种蛋白质纳米结构包含膜蛋白 孔和可编程蛋白质结合剂。蛋白质孔是一个生成输出签名的报告者， 这取决于生物标志物的特性和数量。可编程结合物是一种小型抗体 模拟支架，例如单体或亲和体，对溶液中的目标生物标志物进行采样。因此，一个 通用结合剂可针对多种蛋白质分析物进行修改。这样一来，这样的模块化设计就显着 扩展了这些传感元件对众多生物标志物的实用性，同时保持了它们的高灵敏度 和使用电阻脉冲技术的特异性。基因编码促进了这一关键益处 这些传感器的性质，使它们可以形成系留结合物的组合库。这些操纵 之前尚未进行过配备抗体模拟结合物的基于模块化孔的探测器的研究。 它们旨在用于具有挑战性的生物流体，其中特定的结合物-生物标志物相互作用将被 与介质成分的非特异性相互作用明确区分。进一步的优点 这种实时且无标记的技术包括在宽动态范围内保持放大的信噪比 由于时间分辨电记录的优越带宽，范围很广。预期的直接结果 这些拟议的研究将包括以下内容：（i）单体和单体的开发、优化和验证 用于蛋白质检测的基于亲和体的传感器； (ii) 多重和高通量中的蛋白质生物标志物检测 吞吐量公式； (iii) 异质溶液中的蛋白质生物标志物检测。这些结果将 代表了一个平台，用于生物流体中多个蛋白质目标的指纹识别面板，而不损害 这些测定的敏感性。这项拟议的研究将影响定量蛋白质组学和生物传感器 技术，为超灵敏生物标志物检测提供基础基础和工具。