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.

项目摘要 蛋白质检测和生物标志物分析在许多疾病预后的许多领域具有广泛的意义， 诊断和治疗学。例如，各种癌症的发展和发展是 伴随着特定蛋白质表达的改变。不同生物流体中的这些变化是指示性的 类似疾病的疾病。现有方法的长期困难是检测A中多种蛋白 具有高灵敏度和广泛动态范围的复杂生物样品。另外，可伸缩蛋白 识别和量化技术通常是用牺牲的灵敏度创建的，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点，我们将发展， 优化并验证靶向蛋白生物标志物检测的下一代感应元素 单识别事件精度。这些拟议的研究旨在设计由 单型链链蛋白纳米结构。该蛋白质纳米结构包含膜蛋白 孔和可编程蛋白粘合剂。蛋白质孔是生成输出签名的记者， 取决于生物标志物的身份和数量。可编程粘合剂是一种小抗体 - 模拟型支架，例如单镜或杂物，对溶液中的靶向生物标志物进行采样。因此， 可以修改多种蛋白质分析物的通用粘合剂。这样，如此模块化的设计明显 扩大这些感应元素的效用，以确保许多生物标志物的高灵敏度 和使用电阻脉冲技术的特异性。遗传编码的促进了这种关键好处 这些传感器的性质，以便它们可以形成束缚粘合剂的组合库。这些操纵 以前尚未进行配备有抗体仿真粘合剂的模块化孔基于孔隙的检测器。 它们旨在用于挑战生物流体，在此特定的粘合剂生物标志物相互作用将是 明确区分了培养基成分的非特异性相互作用。进一步的优势 这种实时和无标签的技术包括保持广泛动态的放大信号噪声比率 由于时间分辨电记录的优越带宽，范围。预期的即时结果 在这些拟议的研究中，将有以下内容：（i）单向和验证单向和验证 基于蛋白质检测的基于附生的传感器； （ii）多路复用和高 - 吞吐量配方； （iii）异质溶液中的蛋白质生物标志物检测。这些结果将会 代表了生物流体中多种蛋白质靶标的指纹面板的平台，而不会损害 这些决定的敏感性。这项拟议的研究将影响定量蛋白质组学和生物传感器 通过为超敏感生物标志物检测提供基本基础和工具来技术。