Literature DB >> 27577009

Single-cell level methods for studying the effect of antibiotics on bacteria during infection.

Karin Kogermann1, Marta Putrinš2, Tanel Tenson3.   

Abstract

Considerable evidence about phenotypic heterogeneity among bacteria during infection has accumulated during recent years. This heterogeneity has to be considered if the mechanisms of infection and antibiotic action are to be understood, so we need to implement existing and find novel methods to monitor the effects of antibiotics on bacteria at the single-cell level. This review provides an overview of methods by which this aim can be achieved. Fluorescence label-based methods and Raman scattering as a label-free approach are discussed in particular detail. Other label-free methods that can provide single-cell level information, such as impedance spectroscopy and surface plasmon resonance, are briefly summarized. The advantages and disadvantages of these different methods are discussed in light of a challenging in vivo environment. Copyright Â
© 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Antibacterial susceptibility; Antibiotics; Fluorescence; In vivo animal infection models; Phenotypic heterogeneity; Raman spectroscopy; Single-cell level methods

Mesh:

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Year:  2016        PMID: 27577009     DOI: 10.1016/j.ejps.2016.08.042

Source DB:  PubMed          Journal:  Eur J Pharm Sci        ISSN: 0928-0987            Impact factor:   4.384


  2 in total

1.  Fingerprinting Bacterial Metabolic Response to Erythromycin by Raman-Integrated Mid-Infrared Photothermal Microscopy.

Authors:  Jiabao Xu; Xiaojie Li; Zhongyue Guo; Wei E Huang; Ji-Xin Cheng
Journal:  Anal Chem       Date:  2020-10-22       Impact factor: 6.986

2.  Classification of M1/M2-polarized human macrophages by label-free hyperspectral reflectance confocal microscopy and multivariate analysis.

Authors:  Francesca R Bertani; Pamela Mozetic; Marco Fioramonti; Michele Iuliani; Giulia Ribelli; Francesco Pantano; Daniele Santini; Giuseppe Tonini; Marcella Trombetta; Luca Businaro; Stefano Selci; Alberto Rainer
Journal:  Sci Rep       Date:  2017-08-21       Impact factor: 4.379

  2 in total

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