Michael Mecklenburg , Qun Chen , Anneli Andersson , Bin Xie
{"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}
引用次数: 2
Abstract
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.