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Depletion interactions are thought to significantly contribute to the organization of intracellular structures in the crowded cytosol. The strength of depletion interactions depends on physical parameters like the depletant number density and the depletant size ratio. Cells are known to dynamically regulate these two parameters by varying the copy number of proteins of a wide distribution of sizes. However, mammalian cells are also known to keep the total protein mass density remarkably constant, to within 0.5% throughout the cell cycle. We thus ask how the strength of depletion interactions varies when the total depletant mass is held fixed, a.k.a. fixed-mass depletion. We answer this question via scaling arguments, as well as by studying depletion effects on networks of reconstituted semiflexible actin $\textit{in silico}$ and $\textit{in vitro}$. We examine the maximum strength of the depletion interaction potential $U^*$ as a function of $q$, the size ratio between the depletant and the matter being depleted. We uncover a scaling relation $U^* \sim q^{-\zeta}$ for two cases: fixed volume fraction $\phi$ and fixed mass density $\rho$. For fixed volume fraction, we report $\zeta < 0$. For the fixed mass density case, we report $\zeta > 0$, which suggests the depletion interaction strength increases as the depletant size ratio is increased. To test this prediction, we prepared our filament networks at fixed mass concentrations with varying sizes of the depletant molecule poly(ethylene glycol) (PEG). We characterize the depletion interaction strength in our simulations via the mesh size. In experiments, we observe two distinct actin network morphologies, which we call weakly bundled and strongly bundled. We identify a mass concentration where different PEG depletant sizes leads to weakly bundled or strongly bundled morphologies...[more in main text]., Comment: 21 pages, 5 figures. arXiv admin note: substantial text overlap with arXiv:2205.01864

The effect of the presence of two probe waveguides on the dynamics of hyper-Raman processes is studied in terms of quantum Zeno and anti-Zeno effects. Specifically, the enhancement (diminution) of the evolution of the hyper-Raman processes due to interaction with the probe waveguides via evanescent waves is viewed as quantum Zeno (anti-Zeno) effect. We considered the two probe waveguides interacting with only one of the optical modes at a time. For instance, as a specific scenario, it is considered that the two non-degenerate pump modes interact with each probe waveguide linearly while Stokes and anti-Stokes modes do not interact with the probes. Similarly, in another scenario, we assumed both the probe waveguides interact with Stokes (anti-Stokes) mode simultaneously. The present results show that quantum Zeno (anti-Zeno) effect is associated with phase-matching (mismatching). However, we did not find any relation between the presence of the quantum Zeno effect and antibunching in the bosonic modes present in the hyper-Raman processes., Comment: Dynamics of hyper-Raman processes is studied in terms of quantum Zeno and anti-Zeno effects

Active biological molecules present a powerful, yet largely untapped, opportunity to impart autonomous regulation to materials. Because these systems can function robustly to regulate when and where chemical reactions occur, they have the ability to bring complex, life-like behavior to synthetic materials. Here, we achieve this design feat by using functionalized circadian clock proteins, KaiB and KaiC, to engineer time-dependent crosslinking of colloids. The resulting material self-assembles with programmable kinetics, producing macroscopic changes in material properties, via molecular assembly of KaiB-KaiC complexes. We show that colloid crosslinking depends strictly on the phosphorylation state of KaiC, with kinetics that are synced with KaiB-KaiC complexing. Our microscopic image analyses and computational models indicate that the stability of colloidal super-structures depends sensitively on the number of Kai complexes per colloid connection. Consistent with our model predictions, a high concentration stabilizes the material against dissolution after a robust self-assembly phase, while a low concentration allows circadian oscillation of material structure. This work introduces the concept of harnessing biological timers to control synthetic materials; and, more generally, opens the door to using protein-based reaction networks to endow synthetic systems with life-like functional properties., Comment: 5 figures + SI

The actin cytoskeleton is a semiflexible biopolymer network whose morphology is controlled by a wide range of biochemical and physical factors. Actin is known to undergo a phase transition from a single-filament state to a bundled state by the addition of polyethylene glycol (PEG) molecules in sufficient concentration. While the depletion interaction experienced by these biopolymers is well-known, the effect of changing the molecular weight of the depletant is less well understood. Here, we experimentally identify a phase transition in solutions of actin from networks of filaments to networks of bundles by varying the molecular weight of PEG polymers, while holding the concentration of these PEG polymers constant. We examine the states straddling the phase transition in terms of micro and macroscale properties. We find that the mesh size, bundle diameter, persistence length, and intra-bundle spacing between filaments across the line of criticality do not show significant differences, while the relaxation time, storage modulus, and degree of bundling change between the two states do show significant differences. Our results demonstrate the ability to tune actin network morphology and mechanics by controlling depletant size, a property which could be exploited to develop actin-based materials with switchable rigidity., Comment: 22 pages, 10 figures. Authors James Clarke and Francis Cavanna contributed equally; Changes: Added modeling work, extended dynamic light scattering analysis

Many biological tissues feature a heterogeneous network of fibers whose tensile and bending rigidity contribute substantially to these tissues' elastic properties. Rigidity percolation has emerged as a important paradigm for relating these filamentous tissues' mechanics to the concentrations of their constituents. Past studies have generally considered tuning of networks by spatially homogeneous variation in concentration, while ignoring structural correlation. We here introduce a model in which dilute fiber networks are built in a correlated manner that produces alternating sparse and dense regions. Our simulations indicate that structural correlation consistently allows tissues to attain rigidity with less material. We further find that the percolation threshold varies non-monotonically with the degree of correlation, such that it decreases with moderate correlation and once more increases for high correlation. We explain the eventual reentrance in the dependence of the rigidity percolation threshold on correlation as the consequence of large, stiff clusters that are too poorly coupled to transmit forces across the network. Our study offers deeper understanding of how spatial heterogeneity may enable tissues to robustly adapt to different mechanical contexts., Comment: This article contains 10 pages and 5 figures

The cytoskeleton relies on diverse populations of motors, filaments, and binding proteins acting in concert to enable non-equilibrium processes ranging from mitosis to chemotaxis. Its versatile reconfigurability, programmed by interactions between its constituents, make the cytoskeleton foundational active matter. Yet, current active matter endeavors are limited largely to single force-generating components acting on a single substrate, far from the composite cytoskeleton in cells. Here, we engineer actin-microtubule double-networks, driven by kinesin and myosin motors and tuned by crosslinkers, to ballistically restructure and flow with speeds that span three orders of magnitude depending on the composite formulation and time relative to the onset of motor activity. Differential dynamic microscopy analyses reveal that kinesin and myosin compete to delay the onset of acceleration and suppress discrete restructuring events, while passive crosslinking of either actin or microtubules has an opposite effect. Our minimal advection-diffusion model and spatial correlation analyses correlate these dynamics to structure, with motor antagonism suppressing reconfiguration and de-mixing, while crosslinking enhances clustering. Despite the rich formulation space and emergent formulation-dependent structures, the non-equilibrium dynamics across all networks and timescales can be organized into three classes: slow isotropic reorientation, fast directional flow, and multimode restructuring. Moreover, our mathematical model demonstrates that diverse structural motifs can arise simply from the interplay between motor-driven advection and frictional drag. These general features of our platform facilitate applicability to other active matter systems, and shed light on diverse ways that cytoskeletal components can cooperate or compete to enable wide-ranging cellular processes.

Biological systems have the unique ability to self-organize and generate autonomous motion and work. Motivated by this, we investigate a 2D model colloidal network that can repeatedly transition between disordered states of low connectivity and ordered states of high connectivity via rhythmic binding and unbinding of biomimetic crosslinkers. We use Langevin dynamics to investigate the time-dependent changes in structure and collective properties of this system as a function of colloidal packing fractions and crosslinker oscillation periods and characterize the degree of order in the system by using network connectivity, bond length distributions, and collective motion. Our simulations suggest that we can achieve distinct states of this colloidal system with pronounced differences in microstructural order and large residence times in the ordered state when crosslinker kinetics and lifetimes depend directly on the oscillation period and this oscillation period is much larger than the colloidal diffusion time. Our results will provide insights into the rational design of smart active materials that can independently cycle between ordered and disordered states with desired material properties on a programmed schedule.