Non-specific cargo-filament interactions slow down motor-driven transport.

Active, motor-based cargo transport is important for many cellular functions and cellular development. However, the cell interior is complex and crowded and could have many weak, non-specific interactions with the cargo being transported. To understand how cargo-environment interactions will affect single motor cargo transport and multi-motor cargo transport, we use an artificial quantum dot cargo bound with few (~ 1) to many (~ 5-10) motors allowed to move in a dense microtubule network. We find that kinesin-driven quantum dot cargo is slower than single kinesin-1 motors. Excitingly, there is some recovery of the speed when multiple motors are attached to the cargo. To determine the possible mechanisms of both the slow down and recovery of speed, we have developed a computational model that explicitly incorporates multi-motor cargos interacting non-specifically with nearby microtubules, including, and predominantly with the microtubule on which the cargo is being transported. Our model has recovered the experimentally measured average cargo speed distribution for cargo-motor configurations with few and many motors, implying that numerous, weak, non-specific interactions can slow down cargo transport and multiple motors can reduce these interactions thereby increasing velocity.

Range and strength of mechanical interactions of force dipoles in elastic fiber networks.

Mechanical forces generated by myosin II molecular motors drive diverse cellular processes, most notably shape change, division and locomotion. These forces may be transmitted over long range through the cytoskeletal medium - a disordered, viscoelastic network of biopolymers. The resulting cell size scale force chains can in principle mediate mechanical interactions between distant actomyosin units, leading to self-organized structural order in the cell cytoskeleton. Inspired by such force transmission through elastic structures in the cytoskeleton, we consider a percolated fiber lattice network, where fibers are represented as linear elastic elements that can both bend and stretch, and the contractile activity of myosin motors is represented by force dipoles. Then, by using a variety of metrics, we show how two such contractile force dipoles interact with each other through their mutual mechanical deformations of the elastic fiber network. As a prelude to two-dipole interactions, we quantify how forces propagate through the network from a single anisotropic force dipole by analyzing clusters of nodes connected by highly strained bonds, as well as through the decay rate of strain energy with distance from a force dipole. We show that predominant fiber bending screens out force propagation, resulting in reduced and strongly network configuration-dependent dipole interactions. On the other hand, stretching-dominated networks support longer-ranged inter-dipole interactions that recapitulate the predictions of linear elasticity theory. By characterizing the differences between tensile and compressive force propagation in the fiber network, we show how inter-dipole interaction depends on the dipoles' mutual separation and orientation. The resulting elastic interaction energy may mediate a force between multiple distant dipoles, leading to their self-organization into ordered configurations. This provides a potential pathway for active mechanical force-driven structural order in elastic biopolymer networks.

Optimal foraging strategies for mutually avoiding competitors.

Many animals are known to exhibit foraging patterns where the distances they travel in a given direction are drawn from a heavy-tailed Lévy distribution. Previous studies have shown that, under sparse and random resource conditions, solitary non-destructive (with regenerating resources) foragers perform a maximally efficient search with Lévy exponent µ equal to 2, while for destructive foragers, efficiency decreases with µ monotonically and there is no optimal µ. However, in nature, there also exist situations where multiple foragers, displaying avoidance behavior, interact with each other competitively. To understand the effects of such competition, we develop a stochastic agent-based simulation that models competitive foraging among mutually avoiding individuals by incorporating an avoidance zone, or territory, of a certain size around each forager which is not accessible for foraging by other competitors. For non-destructive foraging, our results show that with increasing size of the territory and number of agents the optimal Lévy exponent is still approximately 2 while the overall efficiency of the search decreases. At low values of the Lévy exponent, however, increasing territory size actually increases efficiency. For destructive foraging, we show that certain kinds of avoidance can lead to qualitatively different behavior from solitary foraging, such as the existence of an optimal search with 1<µ<2. Finally, we show that the variance among the efficiencies of the agents increases with increasing Lévy exponent for both solitary and competing foragers, suggesting that reducing variance might be a selective pressure for foragers adopting lower values of µ. Taken together, our results suggest that, for multiple foragers, mutual avoidance and efficiency variance among individuals can lead to optimal Lévy searches with exponents different from those for solitary foragers.

Using Genetically Encoded Fluorescent Biosensors for Quantitative In Vivo Imaging.

Fluorescent biosensors are powerful tools for tracking analytes or cellular processes in live organisms and allowing visualization of the spatial and temporal dynamics of cellular regulators. Fluorescent protein (FP)-based biosensors are extensively employed due to their high selectivity and low invasiveness. A variety of FP-based biosensors have been engineered and applied in plant research to visualize dynamic changes in pH, redox state, concentration of molecules (ions, sugars, peptides, ATP, reactive oxygen species, and phytohormones), and activity of transporters. In this chapter, we briefly summarize reported uses of FP-based biosensors in planta and show simple methods to monitor the dynamics of intracellular Ca2+ in Arabidopsis thaliana using a ratiometric genetically encoded Ca2+ indicator, MatryoshCaMP6s.

Chiral twisting in a bacterial cytoskeletal polymer affects filament size and orientation.

In many rod-shaped bacteria, the actin homolog MreB directs cell-wall insertion and maintains cell shape, but it remains unclear how structural changes to MreB affect its organization in vivo. Here, we perform molecular dynamics simulations for Caulobacter crescentus MreB to extract mechanical parameters for inputs into a coarse-grained biophysical polymer model that successfully predicts MreB filament properties in vivo. Our analyses indicate that MreB double protofilaments can exhibit left-handed twisting that is dependent on the bound nucleotide and membrane binding; the degree of twisting correlates with the length and orientation of MreB filaments observed in vitro and in vivo. Our molecular dynamics simulations also suggest that membrane binding of MreB double protofilaments induces a stable membrane curvature of similar magnitude to that observed in vivo. Thus, our multiscale modeling correlates cytoskeletal filament size with conformational changes inferred from molecular dynamics simulations, providing a paradigm for connecting protein filament structure and mechanics to cellular organization and function.

Membrane mediated motor kinetics in microtubule gliding assays.

Motor-based transport mechanisms are critical for a wide range of eukaryotic cell functions, including the transport of vesicle cargos over long distances. Our understanding of the factors that control and regulate motors when bound to a lipid substrate is however incomplete. We used microtubule gliding assays on a lipid bilayer substrate to investigate the role of membrane diffusion in kinesin-1 on/off binding kinetics and thereby transport velocity. Fluorescence imaging experiments demonstrate motor clustering on single microtubules due to membrane diffusion in the absence of ATP, followed by rapid ATP-induced dissociation during gliding. Our experimental data combined with analytical modeling show that the on/off binding kinetics of the motors are impacted by diffusion and, as a consequence, both the effective binding and unbinding rates for motors are much lower than the expected bare rates. Our results suggest that motor diffusion in the membrane can play a significant role in transport by impacting motor kinetics and can therefore function as a regulator of intracellular transport dynamics.

Cargo diffusion shortens single-kinesin runs at low viscous drag.

Molecular motors such as kinesin-1 drive active, long-range transport of cargos along microtubules in cells. Thermal diffusion of the cargo can impose a randomly directed, fluctuating mechanical load on the motor carrying the cargo. Recent experiments highlighted a strong asymmetry in the sensitivity of single-kinesin run length to load direction, raising the intriguing possibility that cargo diffusion may non-trivially influence motor run length. To test this possibility, here we employed Monte Carlo-based simulations to evaluate the transport of cargo by a single kinesin. Our simulations included physiologically relevant viscous drag on the cargo and interrogated a large parameter space of cytoplasmic viscosities, cargo sizes, and motor velocities that captures their respective ranges in living cells. We found that cargo diffusion significantly shortens single-kinesin runs. This diffusion-based shortening is countered by viscous drag, leading to an unexpected, non-monotonic variation in run length as viscous drag increases. To our knowledge, this is the first identification of a significant effect of cargo diffusion on motor-based transport. Our study highlights the importance of cargo diffusion and load-detachment kinetics on single-motor functions under physiologically relevant conditions.

The inflammasome adapter ASC assembles into filaments with integral participation of its two Death Domains, PYD and CARD.

The inflammasome is a multiprotein complex necessary for the onset of inflammation. The adapter protein ASC assembles inflammasome components by acting as a molecular glue between danger-signal sensors and procaspase-1. The assembly is mediated by ASC self-association and protein interactions via its two Death Domains, PYD and CARD. Truncated versions of ASC have been shown to form filaments, but information on the filaments formed by full-length ASC is needed to construct a meaningful model of inflammasome assembly. To gain insights into this system, we used a combination of transmission EM, NMR, and computational analysis to investigate intact ASC structures. We show that ASC forms ∼6-7-nm-wide filaments that stack laterally to form bundles. The structural characteristics and dimensions of the bundles indicate that both PYD and CARD are integral parts of the filament. A truncated version of ASC with only the CARD domain (ASCCARD) forms different filaments (∼3-4-nm width), providing further evidence that both domains work in concert in filament assembly. Ring-shaped protein particles bound to pre-existing filaments match the size of ASC dimer structures generated by NMR-based protein docking, suggesting that the ASC dimer could be a basic building block for filament formation. Solution NMR binding studies identified the protein surfaces involved in the ASCCARD-ASCCARD interaction. These data provide new insights into the structural underpinnings of the inflammasome and should inform future efforts to interrogate this important biological system.

Plasmon-actuated nano-assembled microshells.

We present three-dimensional microshells formed by self-assembly of densely-packed 5 nm gold nanoparticles (AuNPs). Surface functionalization of the AuNPs with custom-designed mesogenic molecules drives the formation of a stable and rigid shell wall, and these unique structures allow encapsulation of cargo that can be contained, virtually leakage-free, over several months. Further, by leveraging the plasmonic response of AuNPs, we can rupture the microshells using optical excitation with ultralow power (<2 mW), controllably and rapidly releasing the encapsulated contents in less than 5 s. The optimal AuNP packing in the wall, moderated by the custom ligands and verified using small angle x-ray spectroscopy, allows us to calculate the heat released in this process, and to simulate the temperature increase originating from the photothermal heating, with great accuracy. Atypically, we find the local heating does not cause a rise of more than 50 °C, which addresses a major shortcoming in plasmon actuated cargo delivery systems. This combination of spectral selectivity, low power requirements, low heat production, and fast release times, along with the versatility in terms of identity of the enclosed cargo, makes these hierarchical microshells suitable for wide-ranging applications, including biological ones.

Shape Selection of Surface-Bound Helical Filaments: Biopolymers on Curved Membranes.

Motivated to understand the behavior of biological filaments interacting with membranes of various types, we employ a theoretical model for the shape and thermodynamics of intrinsically helical filaments bound to curved membranes. We show that filament-surface interactions lead to a host of nonuniform shape equilibria, in which filaments progressively unwind from their native twist with increasing surface interaction and surface curvature, ultimately adopting uniform-contact curved shapes. The latter effect is due to nonlinear coupling between elastic twist and bending of filaments on anisotropically curved surfaces such as the cylindrical surfaces considered here. Via a combination of numerical solutions and asymptotic analysis of shape equilibria, we show that filament conformations are critically sensitive to the surface curvature in both the strong- and weak-binding limits. These results suggest that local structure of membrane-bound chiral filaments is generically sensitive to the curvature radius of the surface to which it is bound, even when that radius is much larger than the filament's intrinsic pitch. Typical values of elastic parameters and interaction energies for several prokaryotic and eukaryotic filaments indicate that biopolymers are inherently very sensitive to the coupling between twist, interactions, and geometry and that this could be exploited for regulation of a variety of processes such as the targeted exertion of forces, signaling, and self-assembly in response to geometric cues including the local mean and Gaussian curvatures.

Self-organized sorting limits behavioral variability in swarms.

Swarming is a phenomenon where collective motion arises from simple local interactions between typically identical individuals. Here, we investigate the effects of variability in behavior among the agents in finite swarms with both alignment and cohesive interactions. We show that swarming is abolished above a critical fraction of non-aligners who do not participate in alignment. In certain regimes, however, swarms above the critical threshold can dynamically reorganize and sort out excess non-aligners to maintain the average fraction close to the critical value. This persists even in swarms with a distribution of alignment interactions, suggesting a simple, robust and efficient mechanism that allows heterogeneously mixed populations to naturally regulate their composition and remain in a collective swarming state or even differentiate among behavioral phenotypes. We show that, for evolving swarms, this self-organized sorting behavior can couple to the evolutionary dynamics leading to new evolutionarily stable equilibrium populations set by the physical swarm parameters.

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.

Topologically induced swarming phase transition on a 2D percolated lattice.

The emergence of collective motion, or swarming, in groups of moving individuals who orient themselves using only information from their neighbors is a very general phenomenon that occurs at multiple spatio-temporal scales. Swarms that occur in natural environments typically have to contend with spatial disorder such as obstacles that can hinder an individual's motion or can disrupt communication with neighbors. We study swarming agents, possessing both aligning and mutually avoiding repulsive interactions, in a 2D percolated network representing a topologically disordered environment. We numerically find a phase transition from a collectively moving swarm to a disordered gas-like state above a critical value of the topological or environmental disorder. For agents that utilize only alignment interactions, we find that the swarming transition does not exist in the large system size limit, while the addition of a mutually repulsive interaction can restore the existence of the transition at a finite critical value of disorder. We find there is a finite range of topological disorder where swarming can occur and that this range can be maximized by an optimal amount of mutual repulsion.

Optimal cooperative searching using purely repulsive interactions.

Foraging, either solitarily or collectively, is a necessary behavior for survival that is demonstrated by many organisms. Foraging can be collectively optimized by utilizing communication between the organisms. Examples of such communication range from high level strategic foraging by animal groups to rudimentary signaling among unicellular organisms. Here we systematically study the simplest form of communication via long range repulsive interactions between multiple diffusing Brownian searchers on a one-dimensional lattice. We show that the mean first passage time for any one of them to reach a fixed target depends non-monotonically on the range of the interaction and can be optimized for a repulsive range that is comparable to the average spacing between searchers. Our results suggest that even the most rudimentary form of collective searching does in fact lower the search time for the foragers suggesting robust mechanisms for search optimization in cellular communities.