This title appears in the Scientific Report :
2019
Please use the identifier:
http://dx.doi.org/10.1016/j.jmb.2019.04.025 in citations.
Analyzing Microbial Population Heterogeneity—Expanding the Toolbox of Microfluidic Single-Cell Cultivations
Analyzing Microbial Population Heterogeneity—Expanding the Toolbox of Microfluidic Single-Cell Cultivations
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 re...
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Personal Name(s): | Leygeber, Markus |
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Lindemann, Dorina / Sachs, Christian Carsten / Kaganovitch, Eugen / Wiechert, Wolfgang / Nöh, Katharina / Kohlheyer, Dietrich (Corresponding author) | |
Contributing Institute: |
Biotechnologie; IBG-1 |
Published in: | Journal of molecular biology, 431 (2019) 23, S. 4569-4588 |
Imprint: |
Amsterdam [u.a.]
Elsevier
2019
|
PubMed ID: |
31034885 |
DOI: |
10.1016/j.jmb.2019.04.025 |
Document Type: |
Journal Article |
Research Program: |
Biotechnology |
Publikationsportal JuSER |
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 |