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Tracking single-cell gene regulation in dynamically controlled environments using an integrated microfluidic and computational setup

Matthias Kaiser, Florian Jug, Olin Silander, Siddharth Deshpande, Thomas Pfohl, Thomas Julou, Gene Myers, Erik van Nimwegen
doi: https://doi.org/10.1101/076224
Matthias Kaiser
1Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, Basel, Switzerland
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Florian Jug
2Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
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Olin Silander
1Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, Basel, Switzerland
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Siddharth Deshpande
4Department of Chemistry, University of Basel, Basel, Switzerland
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Thomas Pfohl
4Department of Chemistry, University of Basel, Basel, Switzerland
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Thomas Julou
1Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, Basel, Switzerland
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  • For correspondence: thomas.julou@unibas.ch myers@mpi-cbg.de erik.vannimwegen@unibas.ch
Gene Myers
2Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
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  • For correspondence: thomas.julou@unibas.ch myers@mpi-cbg.de erik.vannimwegen@unibas.ch
Erik van Nimwegen
1Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, Basel, Switzerland
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  • For correspondence: thomas.julou@unibas.ch myers@mpi-cbg.de erik.vannimwegen@unibas.ch
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Abstract

Bacteria adapt to changes in their environment by regulating gene expression, often at the level of transcription. However, since the molecular processes underlying gene regulation are subject to thermodynamic and other stochastic fluctuations, gene expression is inherently noisy, and identical cells in a homogeneous environment can display highly heterogeneous expression levels. To study how stochasticity affects gene regulation at the single-cell level, it is crucial to be able to directly follow gene expression dynamics in single cells under changing environmental conditions. Recently developed microfluidic devices, used in combination with quantitative fluorescence time-lapse microscopy, represent a highly promising experimental approach, allowing tracking of lineages of single cells over long time-scales while simultaneously measuring their growth and gene expression. However, current devices do not allow controlled dynamical changes to the environmental conditions which are needed to study gene regulation. In addition, automated analysis of the imaging data from such devices is still highly challenging and no standard software is currently available. To address these challenges, we here present an integrated experimental and computational setup featuring, on the one hand, a new dual-input microfluidic chip which allows mixing and switching between two growth media and, on the other hand, a novel image analysis software which jointly optimizes segmentation and tracking of the cells and allows interactive user-guided fine-tuning of its results. To demonstrate the power of our approach, we study the lac operon regulation in E. coli cells grown in an environment that switches between glucose and lactose, and quantify stochastic lag times and memory at the single cell level.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted September 20, 2016.
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Tracking single-cell gene regulation in dynamically controlled environments using an integrated microfluidic and computational setup
Matthias Kaiser, Florian Jug, Olin Silander, Siddharth Deshpande, Thomas Pfohl, Thomas Julou, Gene Myers, Erik van Nimwegen
bioRxiv 076224; doi: https://doi.org/10.1101/076224
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Tracking single-cell gene regulation in dynamically controlled environments using an integrated microfluidic and computational setup
Matthias Kaiser, Florian Jug, Olin Silander, Siddharth Deshpande, Thomas Pfohl, Thomas Julou, Gene Myers, Erik van Nimwegen
bioRxiv 076224; doi: https://doi.org/10.1101/076224

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