{"title":"Synergistic Inhibition of Nonspecific Binding for Accurate Detection of Escherichia coli O157:H7 and Multilevel Signal Discrimination","authors":"Yang Zhang, , , Feng Hu, , , Kaiyi Zheng, , , Haoran Li, , , Tianxi Yang, , , Chuping Zhao, , , Roujia Zhang, , , Xiaodong Zhai, , , Junjun Zhang, , , Ruiyun Zhou, , , Xiaowei Huang, , , Zhihua Li, , , Jiyong Shi, , , Zhiming Guo*, , , Shipeng Gao*, , and , Xiaobo Zou*, ","doi":"10.1021/acs.analchem.5c04495","DOIUrl":null,"url":null,"abstract":"<p >Pathogenic <i>Escherichia coli</i> (<i>E. coli</i>), particularly <i>E. coli</i> O157:H7, is a major foodborne pathogen with significant clinical relevance, necessitating accurate and rapid subtype identification. However, the high genetic variability and biological similarity among <i>E. coli</i> strains pose challenges for conventional signal-strain detection methods, often resulting in false-positive outcomes. In this study, we developed a novel biosensing strategy based on plasmonic nanostructures functionalized with heterogeneous recognition elements that target two distinct epitopes of <i>E. coli</i> O157:H7. The sensor incorporates biological silent Raman tags for ratiometric signal output and magnetic enrichment to improve selectivity and minimize interference from nontarget bacteria. This design ensures excellent reproducibility and operational stability. The biosensor demonstrated an impressive limit of detection (LOD) of 1.2 CFU/mL, outperforming most existing methods. Furthermore, a cutoff value of 0.32 for the signal ratio yielded a positive predictive value of 98% and a negative predictive value of 94%, demonstrating a clear signal boundary and high accuracy for various types of signals. These results highlight the potential of our plasmonic biosensor as a rapid, ultrasensitive, and reliable point-of-care diagnostic tool for pathogen detection in complex food matrices.</p>","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"97 40","pages":"22308–22317"},"PeriodicalIF":6.7000,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.analchem.5c04495","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Pathogenic Escherichia coli (E. coli), particularly E. coli O157:H7, is a major foodborne pathogen with significant clinical relevance, necessitating accurate and rapid subtype identification. However, the high genetic variability and biological similarity among E. coli strains pose challenges for conventional signal-strain detection methods, often resulting in false-positive outcomes. In this study, we developed a novel biosensing strategy based on plasmonic nanostructures functionalized with heterogeneous recognition elements that target two distinct epitopes of E. coli O157:H7. The sensor incorporates biological silent Raman tags for ratiometric signal output and magnetic enrichment to improve selectivity and minimize interference from nontarget bacteria. This design ensures excellent reproducibility and operational stability. The biosensor demonstrated an impressive limit of detection (LOD) of 1.2 CFU/mL, outperforming most existing methods. Furthermore, a cutoff value of 0.32 for the signal ratio yielded a positive predictive value of 98% and a negative predictive value of 94%, demonstrating a clear signal boundary and high accuracy for various types of signals. These results highlight the potential of our plasmonic biosensor as a rapid, ultrasensitive, and reliable point-of-care diagnostic tool for pathogen detection in complex food matrices.
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.