Ultrastructural analysis reveals mitochondrial placement independent of synapse placement in fine caliber C. elegans neurons.

Neurons rely on mitochondria for an efficient supply of ATP and other metabolites. However, while neurons are highly elongated, mitochondria are discrete and limited in number. Due to the slow rates of diffusion over long distances it follows that neurons would benefit from an ability to control the distribution of mitochondria to sites of high metabolic activity, such as synapses. It is assumed that neurons' possess this capacity, but ultrastructural data over substantial portions of a neuron's extent that would allow for tests of such hypotheses are scarce. Here, we mined the Caenorhabditis elegans electron micrographs of John White and Sydney Brenner and found systematic differences in average mitochondrial length (ranging from 1.3 to 2.4 µm), volume density (3.7% to 6.5%) and diameter (0.18 to 0.24 µm) between neurons of different neurotransmitter type and function, but found limited differences in mitochondrial morphometrics between axons and dendrites of the same neurons. Analyses of distance intervals found mitochondria to be distributed randomly with respect to presynaptic specializations, and an indication that mitochondria were displaced from postsynaptic specializations. Presynaptic specializations were primarily localized to varicosities, but mitochondria were no more likely to be found in synaptic varicosities than non-synaptic varicosities. Consistently, mitochondrial volume density was no greater in varicosities with synapses. Therefore, beyond the capacity to disperse mitochondria throughout their length, at least in C. elegans, fine caliber neurons manifest limited sub-cellular control of mitochondrial size and distribution.

Mitochondrial phosphagen kinases support the volatile power demands of motor nerve terminals.

Motor neurons are the longest neurons in the body, with axon terminals separated from the soma by as much as a meter. These terminals are largely autonomous with regard to their bioenergetic metabolism and must burn energy at a high rate to sustain muscle contraction. Here, through computer simulation and drawing on previously published empirical data, we determined that motor neuron terminals in Drosophila larvae experience highly volatile power demands. It might not be surprising then, that we discovered the mitochondria in the motor neuron terminals of both Drosophila and mice to be heavily decorated with phosphagen kinases - a key element in an energy storage and buffering system well-characterized in fast-twitch muscle fibres. Knockdown of arginine kinase 1 (ArgK1) in Drosophila larval motor neurons led to several bioenergetic deficits, including mitochondrial matrix acidification and a faster decline in the cytosol ATP to ADP ratio during axon burst firing. KEY POINTS: Neurons commonly fire in bursts imposing highly volatile demands on the bioenergetic machinery that generates ATP. Using a computational approach, we built profiles of presynaptic power demand at the level of single action potentials, as well as the transition from rest to sustained activity. Phosphagen systems are known to buffer ATP levels in muscles and we demonstrate that phosphagen kinases, which support such phosphagen systems, also localize to mitochondria in motor nerve terminals of fruit flies and mice. By knocking down phosphagen kinases in fruit fly motor nerve terminals, and using fluorescent reporters of the ATP:ADP ratio, lactate, pH and Ca2+ , we demonstrate a role for phosphagen kinases in stabilizing presynaptic ATP levels. These data indicate that the maintenance of phosphagen systems in motor neurons, and not just muscle, could be a beneficial initiative in sustaining musculoskeletal health and performance.

Changes in local interaction rules during ontogeny underlie the evolution of collective behavior.

Collective motion emerges from individual interactions which produce group-wide patterns in behavior. While adaptive changes to collective motion are observed across animal species, how local interactions change when these collective behaviors evolve is poorly understood. Here, we use the Mexican tetra, Astyanax mexicanus, which exists as a schooling surface form and a non-schooling cave form, to study differences in how fish alter their swimming in response to neighbors across ontogeny and between evolutionarily diverged populations. We find that surface fish undergo a transition to schooling mediated by changes in the way fish modulate speed and turning relative to neighbors. This transition begins with the tendency to align to neighbors emerging by 28 days post-fertilization and ends with the emergence of robust attraction by 70 days post-fertilization. Cavefish exhibit neither alignment nor attraction at any stage of development. These results reveal how evolution alters local interactions to produce striking differences in collective behavior.

Changes in local interaction rules during ontogeny underlie the evolution of collective behavior.

Collective motion emerges from individual interactions which produce groupwide patterns in behavior. While adaptive changes to collective motion are observed across animal species, how local interactions change when these collective behaviors evolve is poorly understood. Here, we use the Mexican tetra, A. mexicanus, which exists as a schooling surface form and a non-schooling cave form, to study differences in how fish alter their swimming in response to neighbors across ontogeny and between evolutionarily diverged populations. We find that surface fish undergo a transition to schooling during development that occurs through increases in inter-individual alignment and attraction mediated by changes in the way fish modulate speed and turning relative to neighbors. Cavefish, which have evolved loss of schooling, exhibit neither of these schooling-promoting interactions at any stage of development. These results reveal how evolution alters local interaction rules to produce striking differences in collective behavior.

Characterizing the genetic basis of trait evolution in the Mexican cavefish.

Evolution in response to a change in ecology often coincides with various morphological, physiological, and behavioral traits. For most organisms little is known about the genetic and functional relationship between evolutionarily derived traits, representing a critical gap in our understanding of adaptation. The Mexican tetra, Astyanax mexicanus, consists of largely independent populations of fish that inhabit at least 30 caves in Northeast Mexico, and a surface fish population, that inhabit the rivers of Mexico and Southern Texas. The recent application of molecular genetic approaches combined with behavioral phenotyping have established A. mexicanus as a model for studying the evolution of complex traits. Cave populations of A. mexicanus are interfertile with surface populations and have evolved numerous traits including eye degeneration, insomnia, albinism, and enhanced mechanosensory function. The interfertility of different populations from the same species provides a unique opportunity to define the genetic relationship between evolved traits and assess the co-evolution of behavioral and morphological traits with one another. To define the relationships between morphological and behavioral traits, we developed a pipeline to test individual fish for multiple traits. This pipeline confirmed differences in locomotor activity, prey capture, and startle reflex between surface and cavefish populations. To measure the relationship between traits, individual F2 hybrid fish were characterized for locomotor behavior, prey-capture behavior, startle reflex, and morphological attributes. Analysis revealed an association between body length and slower escape reflex, suggesting a trade-off between increased size and predator avoidance in cavefish. Overall, there were few associations between individual behavioral traits, or behavioral and morphological traits, suggesting independent genetic changes underlie the evolution of the measured behavioral and morphological traits. Taken together, this approach provides a novel system to identify genetic underpinnings of naturally occurring variation in morphological and behavioral traits.

Kinematic analysis of social interactions deconstructs the evolved loss of schooling behavior in cavefish.

Fish display a remarkable diversity of social behaviors, both within and between species. While social behaviors are likely critical for survival, surprisingly little is known about how they evolve in response to changing environmental pressures. With its highly social surface form and multiple populations of a largely asocial, blind, cave-dwelling form, the Mexican tetra, Astyanax mexicanus, provides a powerful model to study the evolution of social behavior. Here we use motion tracking and analysis of swimming kinematics to quantify social swimming in four Astyanax mexicanus populations. In the light, surface fish school, maintaining both close proximity and alignment with each other. In the dark, surface fish no longer form coherent schools, however, they still show evidence of an attempt to align and maintain proximity when they find themselves near another fish. In contrast, cavefish from three independently-evolved populations (Pachón, Molino, Tinaja) show little preference for proximity or alignment, instead exhibiting behaviors that suggest active avoidance of each other. Two of the three cave populations we studied also slow down when more fish are present in the tank, a behavior which is not observed in surface fish in light or the dark, suggesting divergent responses to conspecifics. Using data-driven computer simulations, we show that the observed reduction in swimming speed is sufficient to alter the way fish explore their environment: it can increase time spent exploring away from the walls. Thus, the absence of schooling in cavefish is not merely a consequence of their inability to see, but may rather be a genuine behavioral adaptation that impacts the way they explore their environment.

Cavefish brain atlases reveal functional and anatomical convergence across independently evolved populations.

Environmental perturbation can drive behavioral evolution and associated changes in brain structure and function. The Mexican fish species, Astyanax mexicanus, includes eyed river-dwelling surface populations and multiple independently evolved populations of blind cavefish. We used whole-brain imaging and neuronal mapping of 684 larval fish to generate neuroanatomical atlases of surface fish and three different cave populations. Analyses of brain region volume and neural circuits associated with cavefish behavior identified evolutionary convergence in hindbrain and hypothalamic expansion, and changes in neurotransmitter systems, including increased numbers of catecholamine and hypocretin/orexin neurons. To define evolutionary changes in brain function, we performed whole-brain activity mapping associated with behavior. Hunting behavior evoked activity in sensory processing centers, while sleep-associated activity differed in the rostral zone of the hypothalamus and tegmentum. These atlases represent a comparative brain-wide study of intraspecies variation in vertebrates and provide a resource for studying the neural basis of behavioral evolution.

Buckling instabilities and spatio-temporal dynamics of active elastic filaments.

Biological filaments driven by molecular motors tend to experience tangential propulsive forces also known as active follower forces. When such a filament encounters an obstacle, it deforms, which reorients its follower forces and alters its entire motion. If the filament pushes a cargo, the friction on the cargo can be enough to deform the filament, thus affecting the transport properties of the cargo. Motivated by cytoskeletal filament motility assays, we study the dynamic buckling instabilities of a two-dimensional slender elastic filament driven through a dissipative medium by tangential propulsive forces in the presence of obstacles or cargo. We observe two distinct instabilities. When the filament's head is pinned or experiences significant translational but little rotational drag from its cargo, it buckles into a steadily rotating coiled state. When it is clamped or experiences both significant translational and rotational drag from its cargo, it buckles into a periodically beating, overall translating state. Using minimal analytically tractable models, linear stability theory and fully nonlinear computations, we study the onset of each buckling instability, characterize each buckled state, and map out the phase diagram of the system. Finally, we use particle-based Brownian dynamics simulations to show our main results are robust to moderate noise and steric repulsion. Overall, our results provide a unified framework to understand the dynamics of tangentially propelled filaments and filament-cargo assemblies.

Self-propelled particle in a nonconvex external potential: Persistent limit in one dimension.

Equilibrium mapping techniques for nonaligning self-propelled particles have made it possible to predict the density profile of an active ideal gas in a wide variety of external potentials. However, they fail when the self-propulsion is very persistent and the potential is nonconvex, which is precisely when the most uniquely active phenomena occur. Here, we show how to predict the density profile of a 1D active Ornstein-Uhlenbeck particle in an arbitrary external potential in the persistent limit and discuss the consequences of the potential's nonconvexity on the structure of the solution, including the central role of the potential's inflection points and the nonlocal dependence of the density profile on the potential.

Equilibrium mappings in polar-isotropic confined active particles.

Despite their fundamentally nonequilibrium nature, the individual and collective behavior of active systems with polar propulsion and isotropic interactions (polar-isotropic active systems) are remarkably well captured by equilibrium mapping techniques. Here we examine two signatures of equilibrium systems --the existence of a local free energy function and the independence of the coarse-grained behavior on the details of the microscopic dynamics-- in polar-isotropic active particles confined by hard walls of arbitrary geometry at the one-particle level. We find that boundaries that possess concave regions make the density profile strongly dynamics-dependent and give it a nonlocal dependence on the geometry of the confining box. This in turn constrains the scope of equilibrium mapping techniques in polar-isotropic active systems.

Rigid Cluster Decomposition Reveals Criticality in Frictional Jamming.

We study the nature of the frictional jamming transition within the framework of rigidity percolation theory. Slowly sheared frictional packings are decomposed into rigid clusters and floppy regions with a generalization of the pebble game including frictional contacts. Our method suggests a second-order transition controlled by the emergence of a system-spanning rigid cluster accompanied by a critical cluster size distribution. Rigid clusters also correlate with common measures of rigidity. We contrast this result with frictionless jamming, where the rigid cluster size distribution is noncritical.

Dynamics and density distribution of strongly confined noninteracting nonaligning self-propelled particles in a nonconvex boundary.

We study the dynamics of nonaligning, noninteracting self-propelled particles confined to a box in two dimensions. In the strong confinement limit, when the persistence length of the active particles is much larger than the size of the box, particles stay on the boundary and align with the local boundary normal. It is then possible to derive the steady-state density on the boundary for arbitrary box shapes. In nonconvex boxes, the nonuniqueness of the boundary normal results in hysteretic dynamics and the density is nonlocal, i.e., it depends on the global geometry of the box. These findings establish a general connection between the geometry of a confining box and the behavior of an ideal active gas it confines, thus providing a powerful tool to understand and design such confinements.

Dynamics of self-propelled particles under strong confinement.

We develop a statistical theory for the dynamics of non-aligning, non-interacting self-propelled particles confined in a convex box in two dimensions. We find that when the size of the box is small compared to the persistence length of a particle's trajectory (strong confinement), the steady-state density is zero in the bulk and proportional to the local curvature on the boundary. Conversely, the theory may be used to construct the box shape that yields any desired density distribution on the boundary, thus offering a general tool to understand and design such confinements. When the curvature variations are small, we also predict the distribution of orientations at the boundary and the exponential decay of pressure as a function of box size recently observed in simulations in a spherical box.

Freezing and phase separation of self-propelled disks.

We study numerically a model of soft polydisperse and non-aligning self-propelled particles interacting through elastic repulsion, which was recently shown to exhibit active phase separation in two dimensions in the absence of any attractive interaction or breaking of the orientational symmetry. We construct a phase diagram in terms of activity and packing fraction and identify three distinct regimes: a homogeneous liquid with anomalous cluster size distribution, a phase-separated state both at high and at low density, and a frozen phase. We provide a physical interpretation of the various regimes and develop scaling arguments for the boundaries separating them.

Athermal phase separation of self-propelled particles with no alignment.

We study numerically and analytically a model of self-propelled polar disks on a substrate in two dimensions. The particles interact via isotropic repulsive forces and are subject to rotational noise, but there is no aligning interaction. As a result, the system does not exhibit an ordered state. The isotropic fluid phase separates well below close packing and exhibits the large number fluctuations and clustering found ubiquitously in active systems. Our work shows that this behavior is a generic property of systems that are driven out of equilibrium locally, as for instance by self-propulsion.

Active jamming: self-propelled soft particles at high density.

We study numerically the phases and dynamics of a dense collection of self-propelled particles with soft repulsive interactions in two dimensions. The model is motivated by recent in vitro experiments on confluent monolayers of migratory epithelial and endothelial cells. The phase diagram exhibits a liquid phase with giant number fluctuations at low packing fraction φ and high self-propulsion speed v(0) and a jammed phase at high φ and low v(0). The dynamics of the jammed phase is controlled by the low-frequency modes of the jammed packing.