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A Biosensing Strategy for Fast Profiling of Antibiotic Resistance

Mecklenburg, Michael ; Chen, Qun LU ; Andersson, Anneli LU and Xie, Bin LU (2017) In Procedia Technology 27. p.33-34
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.
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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
β-lactamase, Antibiotics, Antibiotic resistance, Profiling, Thermal biosensor
in
Procedia Technology
volume
27
pages
2 pages
publisher
Elsevier
ISSN
2212-0173
DOI
10.1016/j.protcy.2017.04.016
language
English
LU publication?
yes
id
6574fd14-e824-4883-bac2-defd5ca731c0
date added to LUP
2021-10-26 12:53:22
date last changed
2025-04-04 15:12:13
@article{6574fd14-e824-4883-bac2-defd5ca731c0,
  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.}},
  author       = {{Mecklenburg, Michael and Chen, Qun and Andersson, Anneli and Xie, Bin}},
  issn         = {{2212-0173}},
  keywords     = {{β-lactamase; Antibiotics; Antibiotic resistance; Profiling; Thermal biosensor}},
  language     = {{eng}},
  pages        = {{33--34}},
  publisher    = {{Elsevier}},
  series       = {{Procedia Technology}},
  title        = {{A Biosensing Strategy for Fast Profiling of Antibiotic Resistance}},
  url          = {{http://dx.doi.org/10.1016/j.protcy.2017.04.016}},
  doi          = {{10.1016/j.protcy.2017.04.016}},
  volume       = {{27}},
  year         = {{2017}},
}