Literature DB >> 28464521

On-chip spectroscopic assessment of microbial susceptibility to antibiotics within 3.5 hours.

Ulrich-Christian Schröder1,2, Johanna Kirchhoff1,2, Uwe Hübner1, Günter Mayer1, Uwe Glaser1,2, Thomas Henkel1, Wolfgang Pfister3, Wolfgang Fritzsche1, Jürgen Popp1,2,4,5, Ute Neugebauer1,2,3,5.   

Abstract

In times of rising antibiotic resistances, there is a high need for fast, sensitive and specific methods to determine antibiotic susceptibilities of bacterial pathogens. Here, we present an integrated microfluidic device in which bacteria from diluted suspensions are captured in well-defined regions using on-chip dielectrophoresis and further analyzed in a label-free and non-destructive manner using Raman spectroscopy. Minimal sample preparation and automated sample processing ensure safe handling of infectious material with minimal hands-on time for the operator. Clinical applicability of the presented device is demonstrated by antibiotic susceptibility testing of Escherichia coli towards the commonly prescribed second generation fluoroquinolone ciprofloxacin. Ciprofloxacin resistant E. coli were differentiated from sensitive E. coli with high accuracy within roughly three hours total analysis time paving the way for future point-of-care devices. Spectral changes leading to the discrimination between sensitive and resistant bacteria are in excellent agreement with expected metabolic changes in the bacteria due to the mode of action of the drug. The robustness of the method was confirmed with experiments involving different chip devices with different designs, both electrode as well as microfluidics design, and material. Furthermore, general applicability was demonstrated with different operators over an extended time period of half a year.
© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  E. coli, ciprofloxacin; Raman spectroscopy; antibiotic resistance; antibiotic susceptibility testing; device-independent classification; dielectrophoresis (DEP); microfluidic

Mesh:

Substances:

Year:  2017        PMID: 28464521     DOI: 10.1002/jbio.201600316

Source DB:  PubMed          Journal:  J Biophotonics        ISSN: 1864-063X            Impact factor:   3.207


  6 in total

1.  Discriminating cell line specific features of antibiotic-resistant strains of Escherichia coli from Raman spectra via machine learning analysis.

Authors:  Jessica Zahn; Arno Germond; Alice Y Lundgren; Marcus T Cicerone
Journal:  J Biophotonics       Date:  2022-04-06       Impact factor: 3.390

2.  Microfluidic Cultivation and Laser Tweezers Raman Spectroscopy of E. coli under Antibiotic Stress.

Authors:  Zdeněk Pilát; Silvie Bernatová; Jan Ježek; Johanna Kirchhoff; Astrid Tannert; Ute Neugebauer; Ota Samek; Pavel Zemánek
Journal:  Sensors (Basel)       Date:  2018-05-18       Impact factor: 3.576

3.  Detection of multi-resistant clinical strains of E. coli with Raman spectroscopy.

Authors:  Amir Nakar; Aikaterini Pistiki; Oleg Ryabchykov; Thomas Bocklitz; Petra Rösch; Jürgen Popp
Journal:  Anal Bioanal Chem       Date:  2022-01-04       Impact factor: 4.142

4.  Rapid, Label-Free Prediction of Antibiotic Resistance in Salmonella typhimurium by Surface-Enhanced Raman Spectroscopy.

Authors:  Ping Zhang; Xi-Hao Wu; Lan Su; Hui-Qin Wang; Tai-Feng Lin; Ya-Ping Fang; Hui-Min Zhao; Wen-Jing Lu; Meng-Jia Liu; Wen-Bo Liu; Da-Wei Zheng
Journal:  Int J Mol Sci       Date:  2022-01-25       Impact factor: 5.923

5.  Raman spectral signature reflects transcriptomic features of antibiotic resistance in Escherichia coli.

Authors:  Arno Germond; Taro Ichimura; Takaaki Horinouchi; Hideaki Fujita; Chikara Furusawa; Tomonobu M Watanabe
Journal:  Commun Biol       Date:  2018-07-02

Review 6.  Recent Development of Rapid Antimicrobial Susceptibility Testing Methods through Metabolic Profiling of Bacteria.

Authors:  Chen Chen; Weili Hong
Journal:  Antibiotics (Basel)       Date:  2021-03-17
  6 in total

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