School of Physics and Astronomy, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
ACS Sens. 2023 Oct 27;8(10):3781-3792. doi: 10.1021/acssensors.3c01234. Epub 2023 Oct 4.
MicroRNAs (miRs) are small noncoding RNAs that regulate gene expression and are emerging as powerful indicators of diseases. MiRs are secreted in blood plasma and thus may report on systemic aberrations at an early stage via liquid biopsy analysis. We present a method for multiplexed single-molecule detection and quantification of a selected panel of miRs. The proposed assay does not depend on sequencing, requires less than 1 mL of blood, and provides fast results by direct analysis of native, unamplified miRs. This is enabled by a novel combination of compact spectral imaging and a machine learning-based detection scheme that allows simultaneous multiplexed classification of multiple miR targets per sample. The proposed end-to-end pipeline is extremely time efficient and cost-effective. We benchmark our method with synthetic mixtures of three target miRs, showcasing the ability to quantify and distinguish subtle ratio changes between miR targets.
微 RNA（miRs）是一种小的非编码 RNA，能够调控基因表达，并且正在成为疾病的有力指标。miRs 分泌在血浆中，因此通过液体活检分析，它们可能在早期报告系统性异常。我们提出了一种用于对选定的 miRs 进行多重单分子检测和定量的方法。该方法不依赖于测序，仅需要不到 1 毫升的血液，并且通过直接分析天然、未扩增的 miRs 提供快速的结果。这得益于紧凑的光谱成像和基于机器学习的检测方案的新颖组合，该方案允许每个样本同时对多个 miR 靶标进行多重分类。所提出的端到端管道非常高效和具有成本效益。我们使用三种靶标 miRs 的合成混合物对我们的方法进行了基准测试，展示了定量和区分 miR 靶标之间细微比例变化的能力。
