Feng Guo, Keren Chen, Jiaru Yang, Yifan Wu, Jiageng Cheng, Qian Yang, Longjiao Zhu, Jun Li and Wentao Xu
{"title":"基于多分子识别元件的快速抗生素生物传感器。","authors":"Feng Guo, Keren Chen, Jiaru Yang, Yifan Wu, Jiageng Cheng, Qian Yang, Longjiao Zhu, Jun Li and Wentao Xu","doi":"10.1039/D4AY02212B","DOIUrl":null,"url":null,"abstract":"<p >The extensive use of antibiotics poses significant public health concerns, including the increase in drug-resistant bacteria and environmental pollution, underscoring the urgent need for rapid, sensitive, and specific antibiotic detection methods. Most current reviews on antibiotic detection primarily focus on categorizing antibiotics based on their types or the classification of sensors used, such as electrochemical, optical, or colorimetric sensors. In contrast, this review proposes a novel and systematic theoretical framework for the detection of antibiotics using sensors using seven popular molecular recognition elements-antibodies, aptamers, microorganisms, cells, peptides, molecularly imprinted polymers (MIPs), metal–organic frameworks (MOFs) and direct recognition modalities and briefly discusses the mechanism of molecular recognition elements and antibiotic recognition. Additionally, it explores biosensors developed using these elements, offering a detailed analysis of their strengths and limitations in terms of sensitivity, specificity, and practicality. The review concludes by addressing current challenges and future directions, providing a comprehensive perspective essential for enhancing food safety and protecting public health.</p>","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" 12","pages":" 2496-2514"},"PeriodicalIF":2.6000,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rapid antibiotic biosensors based on multiple molecular recognition elements\",\"authors\":\"Feng Guo, Keren Chen, Jiaru Yang, Yifan Wu, Jiageng Cheng, Qian Yang, Longjiao Zhu, Jun Li and Wentao Xu\",\"doi\":\"10.1039/D4AY02212B\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >The extensive use of antibiotics poses significant public health concerns, including the increase in drug-resistant bacteria and environmental pollution, underscoring the urgent need for rapid, sensitive, and specific antibiotic detection methods. Most current reviews on antibiotic detection primarily focus on categorizing antibiotics based on their types or the classification of sensors used, such as electrochemical, optical, or colorimetric sensors. In contrast, this review proposes a novel and systematic theoretical framework for the detection of antibiotics using sensors using seven popular molecular recognition elements-antibodies, aptamers, microorganisms, cells, peptides, molecularly imprinted polymers (MIPs), metal–organic frameworks (MOFs) and direct recognition modalities and briefly discusses the mechanism of molecular recognition elements and antibiotic recognition. Additionally, it explores biosensors developed using these elements, offering a detailed analysis of their strengths and limitations in terms of sensitivity, specificity, and practicality. The review concludes by addressing current challenges and future directions, providing a comprehensive perspective essential for enhancing food safety and protecting public health.</p>\",\"PeriodicalId\":64,\"journal\":{\"name\":\"Analytical Methods\",\"volume\":\" 12\",\"pages\":\" 2496-2514\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-02-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical Methods\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://pubs.rsc.org/en/content/articlelanding/2025/ay/d4ay02212b\",\"RegionNum\":3,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Methods","FirstCategoryId":"92","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2025/ay/d4ay02212b","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
Rapid antibiotic biosensors based on multiple molecular recognition elements
The extensive use of antibiotics poses significant public health concerns, including the increase in drug-resistant bacteria and environmental pollution, underscoring the urgent need for rapid, sensitive, and specific antibiotic detection methods. Most current reviews on antibiotic detection primarily focus on categorizing antibiotics based on their types or the classification of sensors used, such as electrochemical, optical, or colorimetric sensors. In contrast, this review proposes a novel and systematic theoretical framework for the detection of antibiotics using sensors using seven popular molecular recognition elements-antibodies, aptamers, microorganisms, cells, peptides, molecularly imprinted polymers (MIPs), metal–organic frameworks (MOFs) and direct recognition modalities and briefly discusses the mechanism of molecular recognition elements and antibiotic recognition. Additionally, it explores biosensors developed using these elements, offering a detailed analysis of their strengths and limitations in terms of sensitivity, specificity, and practicality. The review concludes by addressing current challenges and future directions, providing a comprehensive perspective essential for enhancing food safety and protecting public health.