Michael Mecklenburg , Qun Chen , Anneli Andersson , Bin Xie
{"title":"一种快速分析抗生素耐药性的生物传感策略","authors":"Michael Mecklenburg , Qun Chen , Anneli Andersson , Bin Xie","doi":"10.1016/j.protcy.2017.04.016","DOIUrl":null,"url":null,"abstract":"<div><p>Antibiotic resistance threatens global public health. Clinical methods that simplify and accelerate resistance diagnosis are urgently needed. Here we describe a function-based antibiotic resistance detection and classification strategy to improve diagnosis. The method identifies resistance enzymes by directly measuring the thermal signal generated when an antibiotic i enzymatically degraded. A substrate specificity profile is created by analyzing a panel of antibiotics. Here we show proof of principle by differentiating two antibiotic resistance enzymes based on their substrate specificities profiles. The method provides a fast, simple, cost effective alternative for diagnosing and classifying antibiotic resistance.</p></div>","PeriodicalId":101042,"journal":{"name":"Procedia Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.protcy.2017.04.016","citationCount":"2","resultStr":"{\"title\":\"A Biosensing Strategy for Fast Profiling of Antibiotic Resistance\",\"authors\":\"Michael Mecklenburg , Qun Chen , Anneli Andersson , Bin Xie\",\"doi\":\"10.1016/j.protcy.2017.04.016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Antibiotic resistance threatens global public health. Clinical methods that simplify and accelerate resistance diagnosis are urgently needed. Here we describe a function-based antibiotic resistance detection and classification strategy to improve diagnosis. The method identifies resistance enzymes by directly measuring the thermal signal generated when an antibiotic i enzymatically degraded. A substrate specificity profile is created by analyzing a panel of antibiotics. Here we show proof of principle by differentiating two antibiotic resistance enzymes based on their substrate specificities profiles. The method provides a fast, simple, cost effective alternative for diagnosing and classifying antibiotic resistance.</p></div>\",\"PeriodicalId\":101042,\"journal\":{\"name\":\"Procedia Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.protcy.2017.04.016\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Procedia Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212017317300178\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia Technology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212017317300178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Biosensing Strategy for Fast Profiling of Antibiotic Resistance
Antibiotic resistance threatens global public health. Clinical methods that simplify and accelerate resistance diagnosis are urgently needed. Here we describe a function-based antibiotic resistance detection and classification strategy to improve diagnosis. The method identifies resistance enzymes by directly measuring the thermal signal generated when an antibiotic i enzymatically degraded. A substrate specificity profile is created by analyzing a panel of antibiotics. Here we show proof of principle by differentiating two antibiotic resistance enzymes based on their substrate specificities profiles. The method provides a fast, simple, cost effective alternative for diagnosing and classifying antibiotic resistance.