Controlling microalgae populations by phototactic memory

TL;DR

It is shown that structured light landscapes can guide microalgae populations and localise them in defined spatial regions and reveal new aspects of phototactic behaviour, highlighting gradient-aligned steering together with temporal integration as central mechanisms for navigation in structured environments.

Abstract

Understanding how microorganisms navigate in complex environments is a central question in active matter and biological physics. Phototaxis - the ability to use light as a navigation cue - is a widespread strategy in motile microalgae to optimise photosynthesis and avoid light-induced stress. The microalga Chlamydomonas reinhardtii is a model system for studying this behaviour, where navigation is classically attributed to a photosensitive organelle named eyespot. While this mechanism enables cells to sense the direction of incoming light, their response to light intensity gradients remains less understood. Here we show that structured light landscapes can guide microalgae populations and localise them in defined spatial regions. By analysing single-cell trajectories, we find that cells actively steer relative to the local light gradient, and a comparison with a minimal theoretical model shows that a short-time memory of light exposure acting on the transition between positive and negative phototaxis is necessary to reproduce the observed accumulation. At longer times, we observe a gradual decrease in cell number density within the trapping region, consistent with phototactic adaptation. Beyond controlling population dynamics, our results reveal new aspects of phototactic behaviour, highlighting gradient-aligned steering together with temporal integration as central mechanisms for navigation in structured environments.

Figures (14)

• Figure 1: Light-controlled spatial organisation of microalgae.a) Schematic of the experimental setup. Chlamydomonas reinhardtii cells ($\sim$10µm) are confined in a quasi-two-dimensional microfluidic chamber ($\sim$20µm thick) and illuminated with a ring-shaped blue light pattern generated by an axicon lens and a microscope objective. b) Energy density profiles of two ring illuminations with same inner radius ($r_{in} =$150µm) and peak intensity, but different outer radii ($r_{out}$): 245µm (magenta) and 420µm (green). c–d) Bright-field images of the microalgae suspension without illumination (c) and after 1 hour of exposure to the ring-shaped pattern (d). In the absence of light, cells are uniformly distributed and display run-and-tumble motility. Upon illumination, they actively migrate towards the ring and accumulate within it, demonstrating light-guided spatial organisation.
• Figure 2: Dynamics of microalgae accumulation under ring-shaped illumination. Comparison of the accumulation dynamics under illuminations with the same inner radius (150µm) but different outer radii, 245µm and 420µm, shown in pink and green, respectively. a) Temporal evolution of the normalised cell number density inside (solid lines) and outside (dotted lines) the illuminated region. In both cases, the density inside the ring rises sharply following illumination. The density outside the ring also increases, indicating active migration of cells toward the illuminated region from areas beyond the field of view. Accumulation is faster and more pronounced in the thinner ring. b) Spatial density profiles measured one hour into the experiment. The shaded regions indicate the spatial extent of the illumination, corresponding to the central peak and extending across the full width at half maximum of the intensity profile. As the ring thickness increases, the density distribution transitions from a pronounced central peak to a broader, plateau-like profile.
• Figure 3: Statistics of single-cell phototaxis.a) Microalgae located outside the ring-shaped illumination (distance from centre $>$ 300µm) exhibit biased swimming towards the high-intensity region. The run duration is maximised when cells are aligned with the light gradient ($\theta = 0$), indicating active steering towards the ring. b) Probability distribution of the swimming angle relative to the local light gradient (P$(\theta)$) as a function of the distance from the ring centre. Two distinct phototactic regimes emerge: outside the ring, cells preferentially swim along the light gradient ($\theta = 0$), indicating positive phototaxis; inside the ring, the response switches to negative phototaxis, with a preference for swimming away from the gradient ($\theta = \pi$). Data were obtained from averaging at least 100 trajectories, each lasting 2 minutes, and an illumination with $r_{in} = 150µm$ and $r_{out} = 250µm$.
• Figure 4: Role of short-time memory in microalgal accumulation.a–b) Numerical modelling demonstrates that a short-time memory is needed for effective accumulation, illustrated through schematic (left) and simulation snapshots (right) panels. a) Without memory ($\tau_m = 0$), cells switch phototactic behaviour instantaneously upon crossing the intensity threshold ($d_{\text{thr}}$), leading to prolonged residence near the threshold rather than accumulation inside the ring. b) When memory is present ($\tau_m = 16s$), cells integrate past light exposure, enabling them to cross the threshold and reach the location of maximum intensity (at $d_{\rm max}$) before switching to negative phototaxis and entering the ring. In the schematics, orange arrows indicate positive phototaxis, green arrows negative. Simulation snapshots show the spatial distribution of the cells after one hour. c) The ratio of cell number density inside versus outside the ring, $\rho_{\text{in}}/\rho_{\text{out}}$, increases over time in a memory-dependent manner, with longer memory times leading to stronger accumulation. d) The corresponding steady-state spatial profiles, measured after one hour of illumination, show that for short memory durations, cells predominantly accumulate near the intensity threshold $d = d_{\text{thr}}$; as memory increases, this peak decreases and the density within the ring becomes more pronounced. Calculations were run using a ring illumination with $r_{in} = 150µm$ and $r_{out} = 420µm$.
• Figure S1: Experimental setup. A laser and an axicon are used to generate a ring-shaped illumination for the microalgae. The laser is directed to the sample via two mirrors (M1, M2) and an axicon illuminating the back aperture of an objective (obj. 1). Microalgae are imaged via a second objective (obj. 2), a tube lens and a camera (CMOS). The trajectories are then reconstructed using a custom software. The ring size can be adjusted by changing the beam size and the position of the axicon with respect to the sample. The laser power is controlled by a half-waveplate ($\lambda$/2) and a polarising beamsplitter (PBS).