Literature DB >> 26163933

Fluorescence-based tools for single-cell approaches in food microbiology.

A Bridier1, F Hammes2, A Canette3, T Bouchez1, R Briandet4.   

Abstract

The better understanding of the functioning of microbial communities is a challenging and crucial issue in the field of food microbiology, as it constitutes a prerequisite to the optimization of positive and technological microbial population functioning, as well as for the better control of pathogen contamination of food. Heterogeneity appears now as an intrinsic and multi-origin feature of microbial populations and is a major determinant of their beneficial or detrimental functional properties. The understanding of the molecular and cellular mechanisms behind the behavior of bacteria in microbial communities requires therefore observations at the single-cell level in order to overcome "averaging" effects inherent to traditional global approaches. Recent advances in the development of fluorescence-based approaches dedicated to single-cell analysis provide the opportunity to study microbial communities with an unprecedented level of resolution and to obtain detailed insights on the cell structure, metabolism activity, multicellular behavior and bacterial interactions in complex communities. These methods are now increasingly applied in the field of food microbiology in different areas ranging from research laboratories to industry. In this perspective, we reviewed the main fluorescence-based tools used for single-cell approaches and their concrete applications with specific focus on food microbiology.
Copyright © 2015 Elsevier B.V. All rights reserved.

Keywords:  Bacterial pathogen; Flow cytometry; Food matrix; Laser scanning microscopy; Microfluidic; Single-cell fluorescence imaging

Mesh:

Year:  2015        PMID: 26163933     DOI: 10.1016/j.ijfoodmicro.2015.07.003

Source DB:  PubMed          Journal:  Int J Food Microbiol        ISSN: 0168-1605            Impact factor:   5.277


  10 in total

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7.  Rapid Detection of Escherichia coli Antibiotic Susceptibility Using Live/Dead Spectrometry for Lytic Agents.

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Review 8.  Colonial vs. planktonic type of growth: mathematical modeling of microbial dynamics on surfaces and in liquid, semi-liquid and solid foods.

Authors:  Panagiotis N Skandamis; Sophie Jeanson
Journal:  Front Microbiol       Date:  2015-10-29       Impact factor: 5.640

9.  Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes.

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10.  Use of flow cytometry and total viable count to determine the effects of orange juice composition on the physiology of Escherichia coli.

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  10 in total

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