Living Systems Institute, University of Exeter, Exeter, United Kingdom; Mathematics and Statistics, University of Exeter, Exeter, United Kingdom; Biosciences, University of Exeter, Exeter, United Kingdom
Living Systems Institute, University of Exeter, Exeter, United Kingdom; Mathematics and Statistics, University of Exeter, Exeter, United Kingdom
Vasileios Anagnostidis
Living Systems Institute, University of Exeter, Exeter, United Kingdom; Biosciences, University of Exeter, Exeter, United Kingdom; Physics and Astronomy, University of Exeter, Exeter, United Kingdom
Interdisciplinary Centre for Mathematical Modelling and Department of Mathematical Sciences, Loughborough University, Loughborough, United Kingdom; Max Planck Institute for Dynamics and Self-Organization (MPIDS), Göttingen, Germany
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 aneural microorganisms adapt their locomotor patterns in real-time.