Skip to main navigation Skip to search Skip to main content

A Biosensing Strategy for Fast Profiling of Antibiotic Resistance

Michael Mecklenburg, Qun Chen, Anneli Andersson, Bin Xie

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Pages (from-to)33-34
Number of pages2
JournalProcedia Technology
Volume27
DOIs
Publication statusPublished - 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Subject classification (UKÄ)

  • Biological Sciences

Free keywords

  • β-lactamase
  • Antibiotics
  • Antibiotic resistance
  • Profiling
  • Thermal biosensor

Fingerprint

Dive into the research topics of 'A Biosensing Strategy for Fast Profiling of Antibiotic Resistance'. Together they form a unique fingerprint.

Cite this