Cell motility: Bioelectrical control of behavior without neurons

Summary:

Single cells are capable of remarkably sophisticated, sometimes animal-like, behaviors. New work highlighted here demonstrates bioelectric control of motility through the differential regulation of appendage movements in a unicellular organism that walks across surfaces using leg-like bundles of cilia.

Anyone who has had the pleasure of looking through a microscope at a water sample from a pond or tidepool has likely been mesmerized by the diverse, intricate forms and movements of microorganisms. Often accompanying this sense of wonder is the uncanny feeling that these “cavorting wee beasties”¹ are up to something, displaying apparently purposeful behavior. Indeed, unicellular organisms exhibit behaviors more commonly associated with animals with nervous systems including hunting, avoiding predators, and even solving mazes and learning^2–5. Careful observation of these behaviors inspired work beginning in the late 19^th century on the “psychology” of protists (microbial eukaryotes)^6,7. Although much of the intellectual scaffolding supporting this work, such as the identification of supposed rudimentary nervous systems in cells⁸, has not held up to scientific progress, many fundamental observations have and are currently experiencing a resurgence of interest. One fascinating parallel between the molecular basis of behavior in animals and some cells is the bioelectric control of movement. While action potentials in neurons that control locomotor activity in animals are familiar to biologists, action potential-like electrical activity associated with cellular locomotion is less widely known, although ubiquitous across the tree of life and long-studied. Electrophysiological studies of Paramecium, a large pond-dwelling ciliate, starting the in the 1960’s revealed an important role for stereotyped cell depolarizations in dictating cell movement^9,10. Early physiological work on Paramecium even clarified detailed mechanistic roles of voltage-gated Ca²⁺ channels, which were shown decades later to function identically in animal neurons⁹. Deep similarities in the ways ciliates encode sensory stimuli as intracellular electrical activity has even led some to refer to them as “swimming neurons”¹¹. In addition to the large sizes of many species facilitating experimental manipulation, including electrophysiology, easily observable and evocable stereotyped behavioral complexity, in conjunction with their highly stereotyped cell morphologies, makes ciliates attractive experimental systems for rigorous studies of cellular behavior, which may serve to reveal more general principles. Despite a long history of study, much remains to be discovered about how ciliates and other protists coordinate and control complex behaviors. Recent work on long-studied ciliates, including Paramecium, the trumpet-shaped Stentor, the long-necked Lacrymaria, and the unicellular walker Euplotes, highlights the opportunity for new insights into cellular behavior owing to modern advances in microscopy, physics, and computation^2,11–13. In this issue of Current Biology, Laeverenz-Schlogelhofer and Wan provide new insights into the control of complex locomotion in single cells by using experiments and theory to map patterns of electrical activity to differential control of ciliary appendages underlying different cell movement patterns in Euplotes vannus.

Ciliates of the genus Euplotes have been appreciated since the earliest days of microscopy for their distinctly animal-like form of motility, walking across surfaces underwater using leg-like appendages called cirri, which are composed of bundles of cilia. Each Euplotes vannus cell has 15 of these leg-like appendages arranged in a highly stereotyped, asymmetric configuration on its ventral surface (Fig. 1A). Laeverenz-Schlogelhofer and Wan isolated and cultured cells from coral larvae cultures. They first used video microscopy to characterized cell motility patterns, which were found to be highly stereotyped consistent with prior observations. Motility patterns included three distinct motility states: swimming, walking (Fig 1B), and the side-stepping reaction (SSR; Fig. 1C). Swimming involves steady helical motion of cells in the bulk fluid. Walking and the SSR involve motility in association with a solid substrate (the coverslip in the case of this work), with walking displaying intermittent pauses and wide ranges of fluctuating velocities driven by stepping-like movements of cirri and the SSR corresponding to rapid cell reversal and reorientation driven by a complex sequence of different cirral movements. The SSR was shown to be particularly highly stereotyped in terms of duration and cell trajectory. Discrete, stereotyped motility transitions are a feature of the behavioral repertoires of many cells, perhaps most famously in the form of “run-and-tumble” motility in the model bacterium Escherichia coli¹⁴. Animal behavior is also often organized in terms modular discrete behavior or movement states, and substantial work is revealing the genetic and physiological basis of this modularity and that dictating behavioral transitions, often involving activity of specific neural circuits. Besides a few intensively studied cases (notably E. coli), comparatively less is known about the genetic and physiological basis of cellular behavior and locomotor coordination.

Figure 1.

Bioelectric control of motility in Euplotes vannus. A) Morphology of E. vannus includes 15 cirri, leg-like appendages composed of bundles of cilia used for walking and swimming locomotion, on the ventral surface of the cell in an asymmetric configuration, falling into two functionally distinct groups: frontoventral and transverse. Cells also have prominent membranelles, also composed of bundles of cilia, arranged in a membranellar band, which cells beat in a coordinated fashion to generate feeding currents and also for propulsion during swimming. During surface-associated locomotion, cells exhibit two distinct movement patterns B) forward walking and C) a side-stepping reaction (SSR). Cell movement has been exaggerated in panels B and C to illustrate cirral movements associated with these cell movements. D) A bioelectric state of membrane potential held at a constant baseline level corresponds to forward walking and associated Type I beat pattern of frontoventral cirri. E) Cellular depolarization corresponds to the SSR and associated Type III movements of transverse cirri during rapid backward cellular movement and Type II movements of frontoventral cirri during cell reorientation.

To investigate the physiological basis of locomotor coordination, Laeverenz-Schlogelhofer and Wan next performed simultaneous high-speed imaging and electrophysiological recordings of cells. By holding immobilized cells that had been pierced by a recording electrode, they were able to observe the relationship between changes in membrane potential and cirral activity. Although membrane potential was variable and noisy across cells, depolarization events were stereotyped and correlated with similarly stereotyped cirral dynamics. Indeed, membrane potential displayed a bimodal character, with extended “baseline” potential corresponding to forward-walking-like cirral activity, and transient depolarizations corresponding to SSR-like cirral activity (Fig. 1D,E). Different cirri displayed differential changes in beat frequency and orientation, with transverse cirri showing an especially divergent response during depolarization events. Careful spatiotemporal analysis of the dynamics of individual cirri revealed some variability within and across cirri. However, cirral beat frequency and amplitude had a clear causal dependence on bioelectric state of the cell (baseline or depolarized), with changes in cirral activity consistently lagging changes in membrane potential by a small time delay. Further, different cirri with different characteristic beat frequencies and amplitudes showed the same functional dependencies between frequency, amplitude, and membrane potential.

The authors’ work complements previous studies on bioelectric control of cell motility in ciliates, including unicellular walkers. Prior work on E. vannus involving electrode pierced but not otherwise immobilized cells also reported that depolarizations exceeding a voltage and temporal threshold caused SSRs¹⁵. Prior measurements of baseline and depolarization threshold voltages are consistent with those reported in the present work¹⁵. Interestingly, the prior work reported periodic depolarizations in the majority of cells, and Laeverenz-Schlogelhofer and Wan suggest that this discrepancy may be due to the mechanoresponse of cells being held for their electrophysiological measurements. Cells are sometimes viewed as executing computational processes, and the earlier reports of highly periodic voltage pulses were clearly reminiscent of clock signals used in digital circuits to coordinate sequential computations. In the present study, the fact that voltage pulses are not periodic, and correlate with the type of motility pattern currently displayed, and not with transitions between states, tends to argue against a clock-like function for the membrane potential changes.

Careful analysis of spatiotemporal cirral dynamics allowed Laeverenz-Schlogelhofer and Wan to take an important step beyond previous studies. They were able to address quantitatively how cirral activity, controlled by bioelectric cell state, drives different cell movements. Using resistive force theory, a powerful mathematical formalism that allows one to estimate forces acting on a filament based on geometry alone, they estimated forces produced by cirri while executing different types of movement. Cirral movements fell into three main types of waveforms (Fig. 1D,E), and the authors used these waveforms to estimate net propulsive forces generated by cirri during locomotion. Like most microorganisms, Euplotes experiences a low-Reynolds number environment, where viscous effects dominate. Under such conditions, cell velocity is directly proportional to propulsive forces, with drag on the cell body exactly balancing propulsive forces and torques generated by cirri and neglecting adhesive interactions with the substrate. Under this mechanical model, cell movement is determined by the number of active cirri and their waveforms. Putting it all together, the authors used cirral waveforms from held cells with known bioelectric states to predict cirral activity associated with cell movements during forward walking and SSRs. Predicted numbers and types of active cirri agreed reasonably well with actual measurements of freely behaving cells. These results provide new insight into how discrete bioelectric states control locomotory cellular behavior by regulating complex ciliary dynamics.

Despite a rich history of study and recent modern advances, much about how cells control complex behaviors awaits discovery. How do cells integrate information from their surroundings and across their bodies to make decisions and reliably execute functional outputs? Attempts to answer this question will undoubtedly teach us new cell biology, both in terms of conserved and derived mechanisms as well as different types of general principles involving molecular and physical mechanisms. Future work could aim at broader integrative understanding. For example, work has shown that sensory stimuli such as pheromones that evoke behavioral changes can change electrical activity in Euplotes¹⁷, but how such sensory stimuli are transduced into sensorimotor activity is generally not known. Where and/or how are these kinds of behavioral decisions made? What role might mechanical feedback play in behavioral control? Recent work implicated microtubule-based cytoskeletal elements associated with cirri in mechanically dictating proper coordination among cirri during forward walking in a different species of Euplotes¹³. How might bioelectric control interface with this other aspect of control? Perhaps bioelectric activity sets the disposition of cirri to beat with particular waveforms and frequencies while mechanisms involving the microtubule cytoskeleton modulate beat frequencies, together coordinating proper sequences of ciliary movements. Similar mechanisms may be at play in other ciliates and perhaps other eukaryotes as well. Expanding in scope, the structure of motile eukaryotic cilia is deeply conserved, but how control of ciliary dynamics has evolved in different lineages is not well understood. Furthermore, the bioelectric control of cellular behavior likely arose early in the evolution of eukaryotes¹⁶. Comparative approaches mapping molecular mechanisms of cellular behavior to their phylogenetic contexts presents an exciting, expanding frontier of evolutionary cell biology. Extending our appreciation of diverse, complex cellular behaviors may also bolster our ability to engineer cellular behaviors or life-like properties in non-living systems.