Dynamics of pattern formation and emergence of swarming in Caenorhabditis elegans

Kin-recognition and predation shape collective behaviors in the cannibalistic nematode Pristionchus pacificus

Kin-recognition is observed across diverse species forming an important behavioral adaptation influencing organismal interactions. In many species, the molecular mechanisms involved are difficult to characterize, but in the nematode Pristionchus pacificus molecular components regulating its kin-recognition system have been identified. These determine its predatory behaviors towards other con-specifics which prevents the killing and cannibalization of kin. Importantly, their impact on other interactions including collective behaviors is unknown. Here, we explored a high altitude adapted clade of this species which aggregates abundantly under laboratory conditions, to investigate the influence of the kin-recognition system on their group behaviours. By utilizing pairwise aggregation assays between distinct strains of P. pacificus with differing degrees of genetic relatedness, we observe aggregation between kin but not distantly related strains. In assays between distantly related strains, the aggregation ratio is frequently reduced. Furthermore, abolishing predation behaviors through CRISPR/Cas9 induced mutations in Ppa-nhr-40 result in rival strains successfully aggregating together. Finally, as Caenorhabditis elegans are found naturally occurring with P. pacificus, we also explored aggregation events between these species. Here, aggregates were dominated by P. pacificus with the presence of only a small number of predators proving sufficient to disrupt C. elegans aggregation dynamics. Thus, aggregating strains of P. pacificus preferentially group with kin, revealing competition and nepotism as previously unknown components influencing collective behaviors in nematodes.

Gigapixel imaging with a novel multi-camera array microscope

The dynamics of living organisms are organized across many spatial scales. However, current cost-effective imaging systems can measure only a subset of these scales at once. We have created a scalable multi-camera array microscope (MCAM) that enables comprehensive high-resolution recording from multiple spatial scales simultaneously, ranging from structures that approach the cellular scale to large-group behavioral dynamics. By collecting data from up to 96 cameras, we computationally generate gigapixel-scale images and movies with a field of view over hundreds of square centimeters at an optical resolution of 18 µm. This allows us to observe the behavior and fine anatomical features of numerous freely moving model organisms on multiple spatial scales, including larval zebrafish, fruit flies, nematodes, carpenter ants, and slime mold. Further, the MCAM architecture allows stereoscopic tracking of the z-position of organisms using the overlapping field of view from adjacent cameras. Overall, by removing the bottlenecks imposed by single-camera image acquisition systems, the MCAM provides a powerful platform for investigating detailed biological features and behavioral processes of small model organisms across a wide range of spatial scales.

Synchronized oscillations in swarms of nematode Turbatrix aceti

There is a recent surge of interest in the behavior of active particles that can at the same time align their direction of movement and synchronize their oscillations, known as swarmalators. While theoretical and numerical models of such systems are now abundant, no real-life examples have been shown to date. We present an experimental investigation of the collective motion of the nematode Turbatrix aceti that self-propel by body undulation. We discover that these nematodes can synchronize their body oscillations, forming striking traveling metachronal waves, which produces strong fluid flows. We uncover that the location and strength of this collective state can be controlled through the shape of the confining structure; in our case the contact angle of a droplet. This opens a way for producing controlled work such as on-demand flows or displacement of objects. We illustrate this by showing that the force generated by this state is sufficient to change the physics of evaporation of fluid droplets, by counteracting the surface-tension force, which allow us to estimate its strength. The relatively large size and ease of culture make Turbatrix aceti a promising model organism for experimental investigation of swarming and oscillating active matter capable of producing controllable work.

Phase-ordering kinetics in the Allen-Cahn (Model A) class: Universal aspects elucidated by electrically induced transition in liquid crystals

The two-dimensional (2D) Ising model is the statistical physics textbook example for phase transitions and their kinetics. Quenched through the Curie point with Glauber rates, the late-time description of the ferromagnetic domain coarsening finds its place at the scalar sector of the Allen-Cahn (or Model A) class, which encompasses phase-ordering kinetics endowed with a nonconserved order parameter. Resisting exact results sought for theoreticians since Lifshitz's first account in 1962, the central quantities of 2D Model A-most scaling exponents and correlation functions-remain known up to approximate theories whose disparate outcomes urge experimental assessment. Here we perform such assessment based on a comprehensive study of the coarsening of 2D twisted nematic liquid crystals whose kinetics is induced by a superfast electrical switching from a spatiotemporally chaotic (disordered) state to a two-phase concurrent, equilibrium one. Tracking the dynamics via optical microscopy, we first show the sharp evidence of well-established Model A aspects, such as the dynamic exponent z=2 and the dynamic scaling hypothesis, to then move forward. We confirm the Bray-Humayun theory for Porod's regime describing intradomain length scales of the two-point spatial correlators and show that their nontrivial decay beyond the Porod's scale can be captured in a free-from-parameter fashion by Gaussian theories, namely the Ohta-Jasnow-Kawasaki (OJK) and Mazenko theories. Regarding time-related statistics, we corroborate the aging hypothesis in Model A systems, which includes the collapse of two-time correlators into a master curve whose format is, actually, best accounted for by a solution of the local scaling invariance theory: the same solution that fits the 2D nonconserved Ising model correlator along with the Fisher-Huse conjecture. We also suggest the true value for the local persistence exponent in Model A class, in disfavor of the exact outcome for the diffusion and OJK equations. Finally, we observe a fractal morphology for persistence clusters and extract their universal dimension. Given its accuracy and possibilities, this experimental setup may work as a prototype to address further universality issues in the realm of nonequilibrium systems.

The Dynamics of Aerotaxis in a Simple Eukaryotic Model

In aerobic organisms, oxygen is essential for efficient energy production, and it acts as the last acceptor of the mitochondrial electron transport chain and as regulator of gene expression. However, excessive oxygen can lead to production of deleterious reactive oxygen species. Therefore, the directed migration of single cells or cell clumps from hypoxic areas toward a region of optimal oxygen concentration, named aerotaxis, can be considered an adaptive mechanism that plays a major role in biological and pathological processes. One relevant example is the development of O₂ gradients when tumors grow beyond their vascular supply, leading frequently to metastasis. In higher eukaryotic organisms, aerotaxis has only recently begun to be explored, but genetically amenable model organisms suitable to dissect this process remain an unmet need. In this regard, we sought to assess whether Dictyostelium cells, which are an established model for chemotaxis and other motility processes, could sense oxygen gradients and move directionally in their response. By assessing different physical parameters, our findings indicate that both growing and starving Dictyostelium cells under hypoxic conditions migrate directionally toward regions of higher O₂ concentration. This migration is characterized by a specific pattern of cell arrangement. A thickened circular front of high cell density (corona) forms in the cell cluster and persistently moves following the oxygen gradient. Cells in the colony center, where hypoxia is more severe, are less motile and display a rounded shape. Aggregation-competent cells forming streams by chemotaxis, when confined under hypoxic conditions, undergo stream or aggregate fragmentation, giving rise to multiple small loose aggregates that coordinately move toward regions of higher O₂ concentration. By testing a panel of mutants defective in chemotactic signaling, and a catalase-deficient strain, we found that the latter and the pkbR1^null exhibited altered migration patterns. Our results suggest that in Dictyostelium, like in mammalian cells, an intracellular accumulation of hydrogen peroxide favors the migration toward optimal oxygen concentration. Furthermore, differently from chemotaxis, this oxygen-driven migration is a G protein-independent process.

Foraging behaviours lead to spatiotemporal self-similar dynamics in grazing ecosystems

Biological behaviour‐driven self‐organized patterns have recently been confirmed to play a key role in ecosystem functioning. Here, we develop a theoretical phase‐separation model to describe spatiotemporal self‐similar dynamics, which is a consequence of behaviour‐driven trophic interactions in short‐time scales. Our framework integrates scale‐dependent feedback and density‐dependent movement into grazing ecosystems. This model derives six types of selective foraging behaviours that trigger pattern formation for top‐down grazing ecosystems, and one of which is consistent with existing foraging theories. Self‐organized patterns nucleate under moderate grazing intensity and are destroyed by overgrazing, which suggests ecosystem degradation. Theoretical results qualitatively agree with observed grazing ecosystems that display spatial heterogeneities under variable grazing intensity. Our findings potentially provide new insights into self‐organized patterns as an indicator of ecosystem transitions under a stressful environment.

Ice needles weave patterns of stones in freezing landscapes

Patterned ground, defined by the segregation of stones in soil according to size, is one of the most strikingly self-organized characteristics of polar and high-alpine landscapes. The presence of such patterns on Mars has been proposed as evidence for the past presence of surface liquid water. Despite their ubiquity, the dearth of quantitative field data on the patterns and their slow dynamics have hindered fundamental understanding of the pattern formation mechanisms. Here, we use laboratory experiments to show that stone transport is strongly dependent on local stone concentration and the height of ice needles, leading effectively to pattern formation driven by needle ice activity. Through numerical simulations, theory, and experiments, we show that the nonlinear amplification of long wavelength instabilities leads to self-similar dynamics that resemble phase separation patterns in binary alloys, characterized by scaling laws and spatial structure formation. Our results illustrate insights to be gained into patterns in landscapes by viewing the pattern formation through the lens of phase separation. Moreover, they may help interpret spatial structures that arise on diverse planetary landscapes, including ground patterns recently examined using the rover Curiosity on Mars.

C. elegans colony formation as a condensation phenomenon

Phase separation at the molecular scale affects many biological processes. The theoretical requirements for phase separation are fairly minimal, and there is growing evidence that analogous phenomena occur at other scales in biology. Here we examine colony formation in the nematode C. elegans as a possible example of phase separation by a population of organisms. The population density of worms determines whether a colony will form in a thresholded fashion, and a simple two-compartment ordinary differential equation model correctly predicts the threshold. Furthermore, small, round colonies sometimes fuse to form larger, round colonies, and a phenomenon akin to Ostwald ripening – a coarsening process seen in many systems that undergo phase separation – also occurs. These findings support the emerging view that the principles of microscopic phase separation can also apply to collective behaviors of living organisms.

Phase separation phenomena have emerged as being of critical importance in biology. Here, using colony formation in C. elegans as model, the authors demonstrate that the basic concepts that underpin phase separation at a molecular level also apply to collective phenomena at the level of a population of organisms.

Capillary Interfacial Tension in Active Phase Separation

In passive fluid-fluid phase separation, a single interfacial tension sets both the capillary fluctuations of the interface and the rate of Ostwald ripening. We show that these phenomena are governed by two different tensions in active systems, and compute the capillary tension σ_{cw} which sets the relaxation rate of interfacial fluctuations in accordance with capillary wave theory. We discover that strong enough activity can cause negative σ_{cw}. In this regime, depending on the global composition, the system self-organizes, either into a microphase-separated state in which coalescence is highly inhibited, or into an "active foam" state. Our results are obtained for Active Model B+, a minimal continuum model which, although generic, admits significant analytical progress.

A Keller-Segel model for C elegans L1 aggregation

We describe a mathematical model for the aggregation of starved first-stage C elegans larvae (L1s). We propose that starved L1s produce and respond chemotactically to two labile diffusible chemical signals, a short-range attractant and a longer range repellent. This model takes the mathematical form of three coupled partial differential equations, one that describes the movement of the worms and one for each of the chemical signals. Numerical solution of these equations produced a pattern of aggregates that resembled that of worm aggregates observed in experiments. We also describe the identification of a sensory receptor gene, srh-2, whose expression is induced under conditions that promote L1 aggregation. Worms whose srh-2 gene has been knocked out form irregularly shaped aggregates. Our model suggests this phenotype may be explained by the mutant worms slowing their movement more quickly than the wild type.

Collective dynamics in entangled worm and robot blobs

Living systems at all scales aggregate in large numbers for a variety of functions including mating, predation, and survival. The majority of such systems consist of unconnected individuals that collectively flock, school, or swarm. However, some aggregations involve physically entangled individuals, which can confer emergent mechanofunctional material properties to the collective. Here, we study in laboratory experiments and rationalize in theoretical and robophysical models the dynamics of physically entangled and motile self-assemblies of 1-cm-long California blackworms (Lumbriculus variegatus, Annelida: Clitellata: Lumbriculidae). Thousands of individual worms form braids with their long, slender, and flexible bodies to make a three-dimensional, soft, and shape-shifting "blob." The blob behaves as a living material capable of mitigating damage and assault from environmental stresses through dynamic shape transformations, including minimizing surface area for survival against desiccation and enabling transport (negative thermotaxis) from hazardous environments (like heat). We specifically focus on the locomotion of the blob to understand how an amorphous entangled ball of worms can break symmetry to move across a substrate. We hypothesize that the collective blob displays rudimentary differentiation of function across itself, which when combined with entanglement dynamics facilitates directed persistent blob locomotion. To test this, we develop a robophysical model of the worm blobs, which displays emergent locomotion in the collective without sophisticated control or programming of any individual robot. The emergent dynamics of the living functional blob and robophysical model can inform the design of additional classes of adaptive mechanofunctional living materials and emergent robotics.