Methods for detecting and quantifying disease biomarkers in biofluids with high specificity and sensitivity play a pivotal role in enabling clinical diagnostics, including point-of-care tests. The most widely used molecular biomarkers include proteins, nucleic acids, hormones, metabolites, and other small molecules. While numerous methods have been developed for analyzing biomarkers, most techniques are challenging to implement for clinical use due to insufficient analytical performance, high cost, and/or other practical shortcomings. For instance, the detection of cell-free nucleic acid (cfNA) biomarkers by digital PCR and next-generation sequencing (NGS) requires time-consuming nucleic acid extraction steps, often introduces enzymatic amplification bias, and can be costly when high specificity is required. While several amplification-free methods for detecting cfNAs have been reported, these techniques generally suffer from low specificity and sensitivity. Meanwhile, the quantification of protein biomarkers is generally performed using immunoassays such as enzyme-linked immunosorbent assay (ELISA); the analytical performance of these methods is often limited by the availability of antibodies with high affinity and specificity as well as the significant nonspecific binding of antibodies to assay surfaces. To address the drawbacks of existing biomarker detection methods and establish a universal diagnostics platform capable of detecting different types of analytes, we have developed an amplification-free approach, named single-molecule recognition through equilibrium Poisson sampling (SiMREPS), for the detection of diverse biomarkers with arbitrarily high specificity and single-molecule sensitivity. SiMREPS utilizes the transient, reversible binding of fluorescent detection probes to immobilized target molecules to generate kinetic fingerprints that are detected by single-molecule fluorescence microscopy. The analysis of these kinetic fingerprints enables nearly perfect discrimination between specific binding to target molecules and any nonspecific binding. Early proof-of-concept studies demonstrated the in vitro detection of miRNAs with a limit of detection (LOD) of approximately 1 fM and >500-fold selectivity for single-nucleotide polymorphisms. The SiMREPS approach was subsequently expanded to the detection of rare mutant DNA alleles from biofluids at mutant allele fractions of as low as 1 in 1 million, corresponding to a specificity of >99.99999%. Recently, SiMREPS was generalized to protein quantification using dynamically binding antibody probes, permitting LODs in the low-femtomolar to attomolar range. Finally, SiMREPS has been demonstrated to be suitable for the in situ detection of miRNAs in cultured cells, the quantification of small-molecule toxins and drugs, and the monitoring of telomerase activity at the single-molecule level. In this Account, we discuss the principles of SiMREPS for the highly specific and sensitive detection of molecular analytes, including considerations for assay design. We discuss the generality of SiMREPS for the detection of very disparate analytes and provide an overview of data processing methods, including the expansion of the dynamic range using super-resolution analysis and the improvement of performance using deep learning algorithms. Finally, we describe current challenges, opportunities, and future directions for the SiMREPS approach.

中文翻译：

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用于多种疾病生物标志物的高精度单分子计数的直接动力学指纹图谱

以高特异性和灵敏度检测和量化生物流体中疾病生物标志物的方法在实现临床诊断（包括即时检测）方面发挥着关键作用。最广泛使用的分子生物标志物包括蛋白质、核酸、激素、代谢物和其他小分子。虽然已经开发了许多用于分析生物标志物的方法，但由于分析性能不足、成本高和/或其他实际缺点，大多数技术在临床应用中实施起来具有挑战性。例如，通过数字 PCR 和下一代测序 (NGS) 检测无细胞核酸 (cfNA) 生物标志物需要耗时的核酸提取步骤，通常会引入酶促扩增偏差，并且在需要高特异性时成本可能会很高. 虽然已经报道了几种检测 cfNA 的无扩增方法，但这些技术通常具有低特异性和敏感性。同时，蛋白质生物标志物的定量一般采用酶联免疫吸附试验（ELISA）等免疫分析方法进行；这些方法的分析性能通常受到具有高亲和力和特异性的抗体的可用性以及抗体与测定表面的显着非特异性结合的限制。为了解决现有生物标志物检测方法的缺陷并建立能够检测不同类型分析物的通用诊断平台，我们开发了一种无扩增方法，称为平衡泊松采样单分子识别（SiMREPS），用于检测具有任意高特异性和单分子灵敏度的多种生物标志物。SiMREPS 利用荧光检测探针与固定目标分子的瞬时、可逆结合来生成动力学指纹，该指纹可通过单分子荧光显微镜检测。对这些动力学指纹的分析几乎可以完美区分与靶分子的特异性结合和任何非特异性结合。早期的概念验证研究表明 对这些动力学指纹的分析几乎可以完美区分与靶分子的特异性结合和任何非特异性结合。早期的概念验证研究表明 对这些动力学指纹的分析几乎可以完美区分与靶分子的特异性结合和任何非特异性结合。早期的概念验证研究表明体外检测 miRNA，检测限 (LOD) 约为 1 fM，对单核苷酸多态性的选择性 > 500 倍。SiMREPS 方法随后扩展到检测来自生物流体的罕见突变 DNA 等位基因，突变等位基因分数低至百万分之一，对应于 >99.99999% 的特异性。最近，SiMREPS 被推广到使用动态结合抗体探针进行蛋白质定量，允许低飞摩尔到阿托摩尔范围内的 LOD。最后，SiMREPS 已被证明适用于原位培养细胞中 miRNA 的检测，小分子毒素和药物的定量，以及单分子水平的端粒酶活性监测。在本文中，我们讨论了 SiMREPS 用于分子分析物的高度特异性和灵敏检测的原理，包括分析设计的考虑因素。我们讨论了 SiMREPS 用于检测非常不同的分析物的一般性，并概述了数据处理方法，包括使用超分辨率分析扩展动态范围和使用深度学习算法提高性能。最后，我们描述了 SiMREPS 方法的当前挑战、机遇和未来方向。