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Open AccessFeature PaperArticle

Droplet-Based Screening for the Investigation of Microbial Nonlinear Dose–Response Characteristics System, Background and Examples

1
Institute for Chemistry and Biotechnologies, Department of Physical Chemistry and Microreaction Technologies, Technische Universität Ilmenau, 98693 Ilmenau, Germany
2
CETONI GmbH Automatisierung und Microsysteme, 07554 Korbussen, Germany
*
Author to whom correspondence should be addressed.
Micromachines 2020, 11(6), 577; https://doi.org/10.3390/mi11060577
Received: 12 May 2020 / Revised: 4 June 2020 / Accepted: 7 June 2020 / Published: 8 June 2020
(This article belongs to the Special Issue Microfluidic for High-Throughput Screening)
Droplet-based microfluidics is a versatile tool to reveal the dose–response relationship of different effectors on the microbial proliferation. Traditional readout parameter is the temporal development of the cell density for different effector concentrations. To determine nonlinear or unconventional dose–response relationships, data with high temporal resolution and dense concentration graduation are essential. If microorganisms with slow microbial growth kinetics are investigated, a sterile and evaporation-free long-term incubation technique is required. Here, we present a modular droplet-based screening system which was developed to solve these issues. Beside relevant technical aspects of the developed modules, the procedural workflow, and exemplary dose–response data for 1D and 2D dose–response screenings are presented. View Full-Text
Keywords: dose–response; droplet-based; segmented-flow; photo-fluorimetric; flow sensor; dynamic cultivation; screening; bacterial; microbial; proliferation; droplet generator dose–response; droplet-based; segmented-flow; photo-fluorimetric; flow sensor; dynamic cultivation; screening; bacterial; microbial; proliferation; droplet generator
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MDPI and ACS Style

Cao, J.; Richter, F.; Kastl, M.; Erdmann, J.; Burgold, C.; Dittrich, D.; Schneider, S.; Köhler, J.M.; Groß, G.A. Droplet-Based Screening for the Investigation of Microbial Nonlinear Dose–Response Characteristics System, Background and Examples. Micromachines 2020, 11, 577.

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