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.

项目总结 蛋白质检测和生物标志物分析在疾病预后的许多领域具有广泛的意义， 诊断学和治疗学。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。这些在不同生物体液中的变化是指示性的 类似疾病的情况。现有方法的一个长期的困难是检测一种 复杂的生物样品，灵敏度高，动态范围大。此外，可伸缩蛋白质 识别和量化技术通常是以牺牲敏感性为代价创建的，因此它们在 临床环境仍然有限。为了克服这些根本和技术上的缺陷，我们将开发， 优化并验证用于靶向蛋白质生物标记物检测的下一代传感元件类别 单一识别事件精确度。这些拟议的研究旨在设计合成传感器，由 单链多肽链蛋白质纳米结构。这种蛋白质纳米结构包含一种膜蛋白。 毛孔和可编程蛋白质粘合剂。蛋白质孔是产生输出信号的报告器， 这取决于生物标志物的身份和数量。可编程结合剂是一种小抗体- 模拟支架，如单体或仿生体，在溶液中采样目标生物标记物。因此，一个 通用结合剂可以针对多种蛋白质分析物进行修饰。这样，这样的模块化设计显著地 扩展了这些传感元件在众多生物标志物中的应用，同时保持了它们的高灵敏度 以及使用阻性脉冲技术的特异性。这一关键的好处是由基因编码的 这些传感器的性质，以便它们可以形成系链绑定剂的组合库。这些操纵 以前还没有进行过配备模拟抗体结合剂的模块化孔基检测器的研究。 它们旨在用于具有挑战性的生物流体，其中特定的结合剂-生物标记物相互作用将是 明确区别于介质成分的非特定相互作用。更多的优势 这种实时且无标签的技术包括在广泛的动态范围内保持放大的信噪比 由于时间分辨电子记录具有超高的带宽，因此可提供更高的传输范围。预期的直接结果 这些拟议的研究将如下：(I)开发、优化和验证单体--以及 用于蛋白质检测的基于仿生体的传感器；(Ii)多路和高密度的蛋白质生物标志物的检测 产量配方；(Iii)异质溶液中蛋白质生物标记物的检测。这些结果将 为生物体液中多个蛋白质目标的指纹图谱面板提供了一个平台，而不会损害 这些测定的灵敏度。这项拟议的研究将对定量蛋白质组学和生物传感器产生影响 通过为超灵敏生物标志物检测提供基本的基础和工具。