Smart-Plexer 2.0:利用扩增曲线的新特性,在多靶点鉴定中增强多重PCR检测方法的选择。

IF 6.7 1区 化学 Q1 CHEMISTRY, ANALYTICAL
Ke Xu, Luca Miglietta, Piyanate Kesakomol, Alison Holmes, Pantelis Georgiou, Nicolas Moser and Jesus Rodriguez-Manzano*, 
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引用次数: 0

摘要

多重PCR通过在单一反应中检测多个靶标,在诊断中起着关键作用。然而,它的使用往往受到需要多个荧光通道的限制,这在标准PCR仪器中受到限制。扩增曲线分析(ACA)是一种数据驱动的多路复用(DDM)方法,它通过使用实时PCR数据和机器学习来区分单通道、单孔格式的目标,而无需修改仪器,从而克服了这一限制。作为DDM策略的一部分,我们之前介绍了Smart-Plexer 1.0,这是一种工具,可以使用经验单路数据模拟多路分析,以确定最佳的分析组合,最大化目标之间的动力学特征距离,以支持基于aca的区分。虽然Smart-Plexer 1.0在受控反应中表现可靠,并为ACA分析设计提供了强大的框架,但它依赖于单一的动力学特征和基于中值的距离度量,这限制了其在不同目标浓度或效率的反应中的准确性。在这里,我们提出了Smart-Plexer 2.0,一个更强大和准确的版本,旨在提高受这种可变性影响的扩增反应的性能。该版本引入了三个新的动力学特征,这些特征在不同的模板浓度下都是稳定的,并使用基于聚类的距离测量来更好地捕获目标之间的可变性。与其前身相比,Smart-Plexer 2.0将准确度方差降低了一个数量级,并在回顾性3-plex和7-plex分析中分别将ACA分类提高了1.5%和1%。在对新开发的7-plex测定法的多实验交叉浓度评估中,它达到了97.6%的ACA准确率,证实了其在复杂情况下的稳健性。Smart-Plexer 2.0提供了一种可靠和可扩展的方法来设计使用标准实时PCR仪器的高性能多重PCR分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart-Plexer 2.0: Leveraging New Features of Amplification Curves to Enhance the Selection of Multiplex PCR Assays in Multi-Target Identification

Multiplex PCR plays a critical role in diagnostics by enabling the detection of multiple targets in a single reaction. However, its use is often limited by the need for multiple fluorescent channels, which are restricted in standard PCR instrumentation. Amplification curve analysis (ACA) is a data-driven multiplexing (DDM) approach that overcomes this limitation by using real-time PCR data and machine learning to differentiate targets in a single-channel, single-well format, without requiring instrument modifications. As part of this DDM strategy, we previously introduced Smart-Plexer 1.0, a tool that simulates multiplex assays using empirical singleplex data to identify optimal assay combinations in silico, maximizing kinetic feature distances between targets to support ACA-based discrimination. While Smart-Plexer 1.0 performs reliably in controlled reactions and offers a strong framework for the ACA assay design, it relies on a single kinetic feature and a median-based distance metric, which limits its accuracy in reactions with variable target concentrations or efficiencies. Here, we present Smart-Plexer 2.0, a more robust and accurate version designed to improve the performance in amplification reactions affected by such variability. This version introduces three new kinetic features that are stable across different template concentrations and uses clustering-based distance measures to better capture the variability between targets. Compared to its predecessor, Smart-Plexer 2.0 reduces accuracy variance by an order of magnitude and improves ACA classification by 1.5 and 1% in retrospective 3-plex and 7-plex assays, respectively. In a multi-experiment, cross-concentration evaluation of a newly developed 7-plex assay, it achieved 97.6% ACA accuracy, confirming its robustness across complex scenarios. Smart-Plexer 2.0 offers a reliable and scalable way to design high-performance multiplex PCR assays using standard real-time PCR instruments.

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来源期刊
Analytical Chemistry
Analytical Chemistry 化学-分析化学
CiteScore
12.10
自引率
12.20%
发文量
1949
审稿时长
1.4 months
期刊介绍: Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.
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