Ke Xu, Luca Miglietta, Piyanate Kesakomol, Alison Holmes, Pantelis Georgiou, Nicolas Moser and Jesus Rodriguez-Manzano*,
{"title":"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。","authors":"Ke Xu, Luca Miglietta, Piyanate Kesakomol, Alison Holmes, Pantelis Georgiou, Nicolas Moser and Jesus Rodriguez-Manzano*, ","doi":"10.1021/acs.analchem.5c01181","DOIUrl":null,"url":null,"abstract":"<p >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.</p>","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"97 27","pages":"14311–14320"},"PeriodicalIF":6.7000,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.analchem.5c01181","citationCount":"0","resultStr":"{\"title\":\"Smart-Plexer 2.0: Leveraging New Features of Amplification Curves to Enhance the Selection of Multiplex PCR Assays in Multi-Target Identification\",\"authors\":\"Ke Xu, Luca Miglietta, Piyanate Kesakomol, Alison Holmes, Pantelis Georgiou, Nicolas Moser and Jesus Rodriguez-Manzano*, \",\"doi\":\"10.1021/acs.analchem.5c01181\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >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.</p>\",\"PeriodicalId\":27,\"journal\":{\"name\":\"Analytical Chemistry\",\"volume\":\"97 27\",\"pages\":\"14311–14320\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://pubs.acs.org/doi/pdf/10.1021/acs.analchem.5c01181\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.analchem.5c01181\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.analchem.5c01181","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
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.
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.