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J Mol Biol. 2019 Apr 26. pii: S0022-2836(19)30232-3. doi: 10.1016/j.jmb.2019.04.025. [Epub ahead of print]

Analyzing Microbial Population Heterogeneity - Expanding the Toolbox of Microfluidic Single-Cell Cultivations.

Author information

1
IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany. Electronic address: m.leygeber@fz-juelich.de.
2
IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany. Electronic address: d.lindemann@fz-juelich.de.
3
IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany. Electronic address: c.sachs@fz-juelich.de.
4
IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany. Electronic address: e.kaganovitch@fz-juelich.de.
5
IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany; Aachener Verfahrenstechnik (AVT), RWTH Aachen University, Germany. Electronic address: w.wiechert@fz-juelich.de.
6
IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany. Electronic address: k.noeh@fz-juelich.de.
7
IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany; Aachener Verfahrenstechnik (AVT), RWTH Aachen University, Germany. Electronic address: d.kohlheyer@fz-juelich.de.

Abstract

Recent research on population heterogeneity revealed fascinating insights into microbial behavior. In particular emerging single-cell technologies, image-based microfluidics lab-on-chip systems generate insights with spatio-temporal resolution, which are inaccessible with conventional tools. This review reports recent developments and applications of microfluidic single-cell cultivation technology, highlighting fields of broad interest such as growth, gene expression and antibiotic resistance and susceptibility. Combining advanced microfluidic single-cell cultivation technology for environmental control with automated time-lapse imaging as well as smart computational image analysis offers tremendous potential for novel investigation at the single-cell level. We propose on-chip control of parameters like temperature, gas supply, pressure or a change in cultivation mode providing a versatile technology platform to mimic more complex and natural habitats. Digital analysis of the acquired images is a requirement for the extraction of biological knowledge and statistically reliable results demand for robust and automated solutions. Focusing on microbial cultivations, we compare prominent software systems that emerged during the last decade, discussing their applicability, opportunities and limitations. Next-generation microfluidic devices with a high degree of environmental control combined with time-lapse imaging and automated image analysis will be highly inspiring and beneficial for fruitful interdisciplinary cooperation between microbiologists and microfluidic engineers and image analysts in the field of microbial single-cell analysis.

KEYWORDS:

Computational image analysis; Environmental control; Microbial population heterogeneity; Single-cell microfluidics; Time-lapse imaging

PMID:
31034885
DOI:
10.1016/j.jmb.2019.04.025

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