A unicellular walker controlled by a microtubule-based finite-state machine

Bioelectric control of locomotor gaits in the walking ciliate Euplotes

Diverse animal species exhibit highly stereotyped behavioral actions and locomotor sequences as they explore their natural environments. In many such cases, the neural basis of behavior is well established, where dedicated neural circuitry contributes to the initiation and regulation of certain response sequences. At the microscopic scale, single-celled eukaryotes (protists) also exhibit remarkably complex behaviors and yet are completely devoid of nervous systems. Here, to address the question of how single cells control behavior, we study locomotor patterning in the exemplary hypotrich ciliate Euplotes, a highly polarized cell, which actuates a large number of leg-like appendages called cirri (each a bundle of ∼25-50 cilia) to swim in fluids or walk on surfaces. As it navigates its surroundings, a walking Euplotes cell is routinely observed to perform side-stepping reactions, one of the most sophisticated maneuvers ever observed in a single-celled organism. These are spontaneous and stereotyped reorientation events involving a transient and fast backward motion followed by a turn. Combining high-speed imaging with simultaneous time-resolved electrophysiological recordings, we show that this complex coordinated motion sequence is tightly regulated by rapid membrane depolarization events, which orchestrate the activity of different cirri on the cell. Using machine learning and computer vision methods, we map detailed measurements of cirri dynamics to the cell's membrane bioelectrical activity, revealing a differential response in the front and back cirri. We integrate these measurements with a minimal model to understand how Euplotes-a unicellular organism-manipulates its membrane potential to achieve real-time control over its motor apparatus.

Cell motility: Bioelectrical control of behavior without neurons

Single cells are capable of remarkably sophisticated, sometimes animal-like, behaviors. New work 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.

Perspectives on Principles of Cellular Behavior from the Biophysics of Protists

Cells are the fundamental unit of biological organization. Although it may be easy to think of them as little more than the simple building blocks of complex organisms such as animals, single cells are capable of behaviors of remarkable apparent sophistication. This is abundantly clear when considering the diversity of form and function among the microbial eukaryotes, the protists. How might we navigate this diversity in the search for general principles of cellular behavior? Here, we review cases in which the intensive study of protists from the perspective of cellular biophysics has driven insight into broad biological questions of morphogenesis, navigation and motility, and decision making. We argue that applying such approaches to questions of evolutionary cell biology presents rich, emerging opportunities. Integrating and expanding biophysical studies across protist diversity, exploiting the unique characteristics of each organism, will enrich our understanding of general underlying principles.

Methods and Measures for Investigating Microscale Motility

Motility is an essential factor for an organism's survival and diversification. With the advent of novel single-cell technologies, analytical frameworks, and theoretical methods, we can begin to probe the complex lives of microscopic motile organisms and answer the intertwining biological and physical questions of how these diverse lifeforms navigate their surroundings. Herein, we summarize the main mechanisms of microscale motility and give an overview of different experimental, analytical, and mathematical methods used to study them across different scales encompassing the molecular-, individual-, to population-level. We identify transferable techniques, pressing challenges, and future directions in the field. This review can serve as a starting point for researchers who are interested in exploring and quantifying the movements of organisms in the microscale world.

What is it like to be a choanoflagellate? Sensation, processing and behavior in the closest unicellular relatives of animals

All animals evolved from a single lineage of unicellular precursors more than 600 million years ago. Thus, the biological and genetic foundations for animal sensation, cognition and behavior must necessarily have arisen by modifications of pre-existing features in their unicellular ancestors. Given that the single-celled ancestors of the animal kingdom are extinct, the only way to reconstruct how these features evolved is by comparing the biology and genomic content of extant animals to their closest living relatives. Here, we reconstruct the Umwelt (the subjective, perceptive world) inhabited by choanoflagellates, a group of unicellular (or facultatively multicellular) aquatic microeukaryotes that are the closest living relatives of animals. Although behavioral research on choanoflagellates remains patchy, existing evidence shows that they are capable of chemosensation, photosensation and mechanosensation. These processes often involve specialized sensorimotor cellular appendages (cilia, microvilli, and/or filopodia) that resemble those that underlie perception in most animal sensory cells. Furthermore, comparative genomics predicts an extensive "sensory molecular toolkit" in choanoflagellates, which both provides a potential basis for known behaviors and suggests the existence of a largely undescribed behavioral complexity that presents exciting avenues for future research. Finally, we discuss how facultative multicellularity in choanoflagellates might help us understand how evolution displaced the locus of decision-making from a single cell to a collective, and how a new space of behavioral complexity might have become accessible in the process.

Openly available illustrations as tools to describe eukaryotic microbial diversity

Microbial life maintains nearly all the support systems that keep the Earth habitable, yet the diversity of this vast microbial world is greatly understudied, misrepresented, and misunderstood. Even what we do know is difficult to communicate broadly because an intuitive grasp of what these tiny organisms are like is abstract, and we lack tools that would help to describe them. In this Essay, we present a series of openly available technical diagrams that illustrate the diverse range of complex body plans of microbial eukaryotes (or "protists"), as well as an illustrated tree to show the vast diversity they encompass and how they are related to the more familiar macroscopic animals, fungi, and plants. These sorts of tools are desperately needed for teaching and communication about the microbial world, which is a pressingly important problem where much improvement is needed.

Active oscillations in microscale navigation

Living organisms routinely navigate their surroundings in search of better conditions, more food, or to avoid predators. Typically, animals do so by integrating sensory cues from the environment with their locomotor apparatuses. For single cells or small organisms that possess motility, fundamental physical constraints imposed by their small size have led to alternative navigation strategies that are specific to the microscopic world. Intriguingly, underlying these myriad exploratory behaviours or sensory functions is the onset of periodic activity at multiple scales, such as the undulations of cilia and flagella, the vibrations of hair cells, or the oscillatory shape modes of migrating neutrophils. Here, I explore oscillatory dynamics in basal microeukaryotes and hypothesize that these active oscillations play a critical role in enhancing the fidelity of adaptive sensorimotor integration.

The evolution and diversity of actin-dependent cell migration

Many eukaryotic cells, including animal cells and unicellular amoebae, use dynamic-actin networks to crawl across solid surfaces. Recent discoveries of actin-dependent crawling in additional lineages have sparked interest in understanding how and when this type of motility evolved. Tracing the evolution of cell crawling requires understanding the molecular mechanisms underlying motility. Here we outline what is known about the diversity and evolution of the molecular mechanisms that drive cell motility, with a focus on actin-dependent crawling. Classic studies and recent work have revealed a surprising number of distinct mechanical modes of actin-dependent crawling used by different cell types and species to navigate different environments. The overlap in actin network regulators driving multiple types of actin-dependent crawling, along with cortical-actin networks that support the plasma membrane in these cells, suggest that actin motility and cortical actin networks might have a common evolutionary origin. The rapid development of additional evolutionarily diverse model systems, advanced imaging technologies, and CRISPR-based genetic tools, is opening the door to testing these and other new ideas about the evolution of actin-dependent cell crawling.

Comparative profiling of cellular gait on adhesive micropatterns defines statistical patterns of activity that underlie native and cancerous cell dynamics

Cell dynamics are powered by patterns of activity, but it is not straightforward to quantify these patterns or compare them across different environmental conditions or cell-types. Here we digitize the long-term shape fluctuations of metazoan cells grown on micropatterned fibronectin islands to define and extract statistical features of cell dynamics without the need for genetic modification or fluorescence imaging. These shape fluctuations generate single-cell morphological signals that can be decomposed into two major components: a continuous, slow-timescale meandering of morphology about an average steady-state shape; and short-lived "events" of rapid morphology change that sporadically occur throughout the timecourse. By developing statistical metrics for each of these components, we used thousands of hours of single-cell data to quantitatively define how each axis of cell dynamics was impacted by environmental conditions or cell-type. We found the size and spatial complexity of the micropattern island modulated the statistics of morphological events-lifetime, frequency, and orientation-but not its baseline shape fluctuations. Extending this approach to profile a panel of triple negative breast cancer cell-lines, we found that different cell-types could be distinguished from one another along specific and unique statistical axes of their behavior. Our results suggest that micropatterned substrates provide a generalizable method to build statistical profiles of cell dynamics to classify and compare emergent cell behaviors.

Mitochondrial networks through the lens of mathematics

Mitochondria serve a wide range of functions within cells, most notably via their production of ATP. Although their morphology is commonly described as bean-like, mitochondria often form interconnected networks within cells that exhibit dynamic restructuring through a variety of physical changes. Further, though relationships between form and function in biology are well established, the extant toolkit for understanding mitochondrial morphology is limited. Here, we emphasize new and established methods for quantitatively describing mitochondrial networks, ranging from unweighted graph-theoretic representations to multi-scale approaches from applied topology, in particular persistent homology. We also show fundamental relationships between mitochondrial networks, mathematics, and physics, using ideas of graph planarity and statistical mechanics to better understand the full possible morphological space of mitochondrial network structures. Lastly, we provide suggestions for how examination of mitochondrial network form through the language of mathematics can inform biological understanding, and vice versa.

Emergent programmable behavior and chaos in dynamically driven active filaments

How the behavior of cells emerges from their constituent subcellular biochemical and physical parts is an outstanding challenge at the intersection of biology and physics. A remarkable example of single-cell behavior occurs in the ciliate Lacrymaria olor, which hunts for its prey via rapid movements and protrusions of a slender neck, many times the size of the original cell body. The dynamics of this cell neck is powered by a coat of cilia across its length and tip. How a cell can program this active filamentous structure to produce desirable behaviors like search and homing to a target remains unknown. Here, we present an active filament model that allows us to uncover how a "program" (time sequence of active forcing) leads to "behavior" (filament shape dynamics). Our model captures two key features of this system-time-varying activity patterns (extension and compression cycles) and active stresses that are uniquely aligned with the filament geometry-a "follower force" constraint. We show that active filaments under deterministic, time-varying follower forces display rich behaviors including periodic and aperiodic dynamics over long times. We further show that aperiodicity occurs due to a transition to chaos in regions of a biologically accessible parameter space. We also identify a simple nonlinear iterated map of filament shape that approximately predicts long-term behavior suggesting simple, artificial "programs" for filament functions such as homing and searching space. Last, we directly measure the statistical properties of biological programs in L. olor, enabling comparisons between model predictions and experiments.

Embodied cognitive morphogenesis as a route to intelligent systems

The embryological view of development is that coordinated gene expression, cellular physics and migration provides the basis for phenotypic complexity. This stands in contrast with the prevailing view of embodied cognition, which claims that informational feedback between organisms and their environment is key to the emergence of intelligent behaviours. We aim to unite these two perspectives as embodied cognitive morphogenesis, in which morphogenetic symmetry breaking produces specialized organismal subsystems which serve as a substrate for the emergence of autonomous behaviours. As embodied cognitive morphogenesis produces fluctuating phenotypic asymmetry and the emergence of information processing subsystems, we observe three distinct properties: acquisition, generativity and transformation. Using a generic organismal agent, such properties are captured through models such as tensegrity networks, differentiation trees and embodied hypernetworks, providing a means to identify the context of various symmetry-breaking events in developmental time. Related concepts that help us define this phenotype further include concepts such as modularity, homeostasis and 4E (embodied, enactive, embedded and extended) cognition. We conclude by considering these autonomous developmental systems as a process called connectogenesis, connecting various parts of the emerged phenotype into an approach useful for the analysis of organisms and the design of bioinspired computational agents.

There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines

The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., a tendency to oversimplify) and prior technological limitations in favor of a more continuous view, necessitated by the study of evolution, developmental biology, and intelligent machines. Form and function are tightly entwined in nature, and in some cases, in robotics as well. Thus, efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as “polycomputing”—the ability of the same substrate to simultaneously compute different things, and make those computational results available to different observers. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of their computational materials, as reported in the rapidly growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of mesoscale events, as it has already done at quantum and relativistic scales. To develop our understanding of how life performs polycomputing, and how it can be convinced to alter one or more of those functions, we can first create technologies that polycompute and learn how to alter their functions. Here, we review examples of biological and technological polycomputing, and develop the idea that the overloading of different functions on the same hardware is an important design principle that helps to understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as to evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.

Phenotyping single-cell motility in microfluidic confinement

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.