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  Phenotyping single-cell motility in microfluidic confinement

Bentley, S. A., Laeverenz-Schlogelhofer, H., Anagnostidis, V., Cammann, J., Mazza, M. G., Gielen, F., et al. (2022). Phenotyping single-cell motility in microfluidic confinement. eLife, 11: e76519. doi:10.7554/eLife.76519.

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 Creators:
Bentley, Samuel A, Author
Laeverenz-Schlogelhofer, Hannah, Author
Anagnostidis, Vasileios, Author
Cammann, Jan, Author
Mazza, Marco G.1, Author           
Gielen, Fabrice, Author
Wan, Kirsty Y, Author
Affiliations:
1Group Non-equilibrium soft matter, Department of Dynamics of Complex Fluids, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063308              

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 Abstract: The movement trajectories of organisms serve as dynamic read-outs of their behaviour and physiology. For microorganisms this can be difficult to resolve due to their small size and fast movement. Here, we devise a novel droplet microfluidics assay to encapsulate single micron-sized algae inside closed arenas, enabling ultralong high-speed tracking of the same cell. Comparing two model species - Chlamydomonas reinhardtii (freshwater, 2 cilia), and Pyramimonas octopus (marine, 8 cilia), we detail their highly-stereotyped yet contrasting swimming behaviours and environmental interactions. By measuring the rates and probabilities with which cells transition between a trio of motility states (smooth-forward swimming, quiescence, tumbling or excitable backward swimming), we reconstruct the control network that underlies this gait switching dynamics. A simplified model of cell-roaming in circular confinement reproduces the observed long-term behaviours and spatial fluxes, including novel boundary circulation behaviour. Finally, we establish an assay in which pairs of droplets are fused on demand, one containing a trapped cell with another containing a chemical that perturbs cellular excitability, to reveal how a neural microorganisms adapt their locomotor patterns in real-time.

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Language(s): eng - English
 Dates: 2022-11-232022
 Publication Status: Issued
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 Identifiers: DOI: 10.7554/eLife.76519
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Title: eLife
Source Genre: Journal
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Pages: 28 Volume / Issue: 11 Sequence Number: e76519 Start / End Page: - Identifier: ISSN: 2050-084X