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Tobias Weise, Bettina Boettcher, Slavena Vylkova 2020. Bioflux Analyses: Modelling. protocols.io https://dx.doi.org/10.17504/protocols.io.bb7sirneCopy Citation Copied
URL: https://dx.doi.org/DOI:10.17504/protocols.io.bb7sirne
Authors: Tobias Weise, Bettina Boettcher, Slavena Vylkova
Summary: Biofilm formation under shear flow conditions was monitored using the Bioflux1000 device (Fluxion Biosciences, Inc.). In short, Candida albicans overnight cultures were washed in pre-warmed RPMI medium. Cells were seeded for 2-5 sec from the outlet well into the channels of Bioflux1000 flow chambers, which were primed before with warm medium. The cells were allowed to adhere to the channels for 90 min without any flow, followed by removal of non-adherent cells by flowing fresh, pre-warmed RPMI medium for 5 sec. Shear flow was set for time series experiments over 24 h biofilm formation and images were captured every 20 min. Two channels were investigated in parallel having a 10 × magnification to allow a direct comparison between a mutant and a reference (wild-type) strain. Image capturing and stacks to movies was performed using the MetaMorph® Software (Molecular Devices).An ODE model reflecting the logistic growth as well as the lag phase was fitted to the individual experiments. Fitting was carried out by minimising a cost function (unweighted least-squares-based) using the Nelder-Mead algorithm. Growth rate time series generated from the fitted model were used to compare wild type and mutant regarding the maximum observed growth rates at their respective time points.All computations were performed using the programming language python (version 3.6.9) and the additional packages numpy (version 1.16.2), pandas (version 0.25.0), and scipy (version 1.3.1).
Affiliations: BioControl Jena GmbH, Jena, Germany, Septomics Research Center, Friedrich Schiller University and Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute, Jena, Germany, Septomics Research Center, Friedrich Schiller University and Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute, Jena, Germany
Version: 2
Publication Date: 2020
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