Chromatin and Cytoskeletal Tethering Determine Nuclear Morphology in Progerin-Expressing Cells.

The nuclear morphology of eukaryotic cells is determined by the interplay between the lamina forming the nuclear skeleton, the chromatin inside the nucleus, and the coupling with the cytoskeleton. Nuclear alterations are often associated with pathological conditions as in Hutchinson-Gilford progeria syndrome, in which a mutation in the lamin A gene yields an altered form of the protein, named progerin, and an aberrant nuclear shape. Here, we introduce an inducible cellular model of Hutchinson-Gilford progeria syndrome in HeLa cells in which increased progerin expression leads to alterations in the coupling of the lamin shell with cytoskeletal or chromatin tethers as well as with polycomb group proteins. Furthermore, our experiments show that progerin expression leads to enhanced nuclear shape fluctuations in response to cytoskeletal activity. To interpret the experimental results, we introduce a computational model of the cell nucleus that explicitly includes chromatin fibers, the nuclear shell, and coupling with the cytoskeleton. The model allows us to investigate how the geometrical organization of the chromatin-lamin tether affects nuclear morphology and shape fluctuations. In sum, our findings highlight the crucial role played by lamin-chromatin and lamin-cytoskeletal alterations in determining nuclear shape morphology and in affecting cellular functions and gene regulation.

Physics in a time of COVID-19.

As the number of COVID-19 cases continues to grow around the world, physicists - many of whom rely on international travel and collaborations - are adapting.

Keeping the labs running.

A report from the UK's Science Council-supported Technician Commitment highlights the role played by technical staff in minimizing the disruption to research caused by COVID-19.

Metamaterial architecture from a self-shaping carnivorous plant.

As meticulously observed and recorded by Darwin, the leaves of the carnivorous plant Drosera capensis L. slowly fold around insects trapped on their sticky surface in order to ensure their digestion. While the biochemical signaling driving leaf closure has been associated with plant growth hormones, how mechanical forces actuate the process is still unknown. Here, we combine experimental tests of leaf mechanics with quantitative measurements of the leaf microstructure and biochemistry to demonstrate that the closure mechanism is programmed into the cellular architecture of D. capensis leaves, which converts a homogeneous biochemical signal into an asymmetric response. Inspired by the leaf closure mechanism, we devise and test a mechanical metamaterial, which curls under homogeneous mechanical stimuli. This kind of metamaterial could find possible applications as a component in soft robotics and provides an example of bio-inspired design.

Strain Modulation of Graphene by Nanoscale Substrate Curvatures: A Molecular View.

Spatially nonuniform strain is important for engineering the pseudomagnetic field and band structure of graphene. Despite the wide interest in strain engineering, there is still a lack of control on device-compatible strain patterns due to the limited understanding of the structure-strain relationship. Here, we study the effect of substrate corrugation and curvature on the strain profiles of graphene via combined experimental and theoretical studies of a model system: graphene on closely packed SiO2 nanospheres with different diameters (20-200 nm). Experimentally, via quantitative Raman analysis, we observe partial adhesion and wrinkle features and find that smaller nanospheres induce larger tensile strain in graphene; theoretically, molecular dynamics simulations confirm the same microscopic structure and size dependence of strain and reveal that a larger strain is caused by a stronger, inhomogeneous interaction force between smaller nanospheres and graphene. This molecular-level understanding of the strain mechanism is important for strain engineering of graphene and other two-dimensional materials.

Universal features of amorphous plasticity.

Plastic yielding of amorphous solids occurs by power-law distributed deformation avalanches whose universality is still debated. Experiments and molecular dynamics simulations are hampered by limited statistical samples, and although existing stochastic models give precise exponents, they require strong assumptions about fixed deformation directions, at odds with the statistical isotropy of amorphous materials. Here, we introduce a fully tensorial, stochastic mesoscale model for amorphous plasticity that links the statistical physics of plastic yielding to engineering mechanics. It captures the complex shear patterning observed for a wide variety of deformation modes, as well as the avalanche dynamics of plastic flow. Avalanches are described by universal size exponents and scaling functions, avalanche shapes, and local stability distributions, independent of system dimensionality, boundary and loading conditions, and stress state. Our predictions consistently differ from those of mean-field depinning models, providing evidence that plastic yielding is a distinct type of critical phenomenon.

Direct Observation of Percolation in the Yielding Transition of Colloidal Glasses.

When strained beyond the linear regime, soft colloidal glasses yield to steady-state plastic flow in a way that is similar to the deformation of conventional amorphous solids. Because of the much larger size of the colloidal particles with respect to the atoms comprising an amorphous solid, colloidal glasses allow us to obtain microscopic insight into the nature of the yielding transition, as we illustrate here combining experiments, atomistic simulations, and mesoscopic modeling. Our results unanimously show growing clusters of nonaffine deformation percolating at yielding. In agreement with percolation theory, the spanning cluster is fractal with a fractal dimension d_{f}≃2, and the correlation length diverges upon approaching the critical yield strain. These results indicate that percolation of highly nonaffine particles is the hallmark of the yielding transition in disordered glassy systems.

Temperature-Dependent Adhesion of Graphene Suspended on a Trench.

Graphene deposited over a trench has been studied in the context of nanomechanical resonators, where experiments indicate adhesion of the graphene sheet to the trench boundary and sidewalls leads to self-tensioning; however, this adhesion is not well understood. We use molecular dynamics to simulate graphene deposited on a trench and study how adhesion to the sidewalls depends on substrate interaction, temperature, and curvature of the edge of the trench. Over the range of parameters we study, the depth at the center of the sheet is approximately linear in substrate interaction strength and temperature but not trench width, and we explain this using a one-dimensional model for the sheet configuration.

Role of the Number of Microtubules in Chromosome Segregation during Cell Division.

Faithful segregation of genetic material during cell division requires alignment of chromosomes between two spindle poles and attachment of their kinetochores to each of the poles. Failure of these complex dynamical processes leads to chromosomal instability (CIN), a characteristic feature of several diseases including cancer. While a multitude of biological factors regulating chromosome congression and bi-orientation have been identified, it is still unclear how they are integrated so that coherent chromosome motion emerges from a large collection of random and deterministic processes. Here we address this issue by a three dimensional computational model of motor-driven chromosome congression and bi-orientation during mitosis. Our model reveals that successful cell division requires control of the total number of microtubules: if this number is too small bi-orientation fails, while if it is too large not all the chromosomes are able to congress. The optimal number of microtubules predicted by our model compares well with early observations in mammalian cell spindles. Our results shed new light on the origin of several pathological conditions related to chromosomal instability.

Navigation Strategies of Motor Proteins on Decorated Tracks.

Motor proteins display widely different stepping patterns as they move on microtubule tracks, from the deterministic linear or helical motion performed by the protein kinesin to the uncoordinated random steps made by dynein. How these different strategies produce an efficient navigation system needed to ensure correct cellular functioning is still unclear. Here, we show by numerical simulations that deterministic and random motor steps yield different outcomes when random obstacles decorate the microtubule tracks: kinesin moves faster on clean tracks but its motion is strongly hindered on decorated tracks, while dynein is slower on clean tracks but more efficient in avoiding obstacles. Further simulations indicate that dynein's advantage on decorated tracks is due to its ability to step backwards. Our results explain how different navigation strategies are employed by the cell to optimize motor driven cargo transport.

Wrinkle motifs in thin films.

On length scales from nanometres to metres, partial adhesion of thin films with substrates generates a fascinating variety of patterns, such as 'telephone cord' buckles, wrinkles, and labyrinth domains. Although these patterns are part of everyday experience and are important in industry, they are not completely understood. Here, we report simulation studies of a previously-overlooked phenomenon in which pairs of wrinkles form avoiding pairs, focusing on the case of graphene over patterned substrates. By nucleating and growing wrinkles in a controlled way, we characterize how their morphology is determined by stress fields in the sheet and friction with the substrate. Our simulations uncover the generic behaviour of avoiding wrinkle pairs that should be valid at all scales.

Protein accumulation in the endoplasmic reticulum as a non-equilibrium phase transition.

Several neurological disorders are associated with the aggregation of aberrant proteins, often localized in intracellular organelles such as the endoplasmic reticulum. Here we study protein aggregation kinetics by mean-field reactions and three dimensional Monte carlo simulations of diffusion-limited aggregation of linear polymers in a confined space, representing the endoplasmic reticulum. By tuning the rates of protein production and degradation, we show that the system undergoes a non-equilibrium phase transition from a physiological phase with little or no polymer accumulation to a pathological phase characterized by persistent polymerization. A combination of external factors accumulating during the lifetime of a patient can thus slightly modify the phase transition control parameters, tipping the balance from a long symptomless lag phase to an accelerated pathological development. The model can be successfully used to interpret experimental data on amyloid-ß clearance from the central nervous system.

Avalanche localization and crossover scaling in amorphous plasticity.

We perform large-scale simulations of a two-dimensional lattice model for amorphous plasticity with random local yield stresses and long-range quadrupolar elastic interactions. We show that as the external stress increases towards the yielding phase transition, the scaling behavior of the avalanches crosses over from mean-field theory to a different universality class. This behavior is associated with strain localization, which significantly depends on the short-range properties of the interaction kernel.

Disorder strength and field-driven ground state domain formation in artificial spin ice: experiment, simulation, and theory.

Quenched disorder affects how nonequilibrium systems respond to driving. In the context of artificial spin ice, an athermal system comprised of geometrically frustrated classical Ising spins with a twofold degenerate ground state, we give experimental and numerical evidence of how such disorder washes out edge effects and provide an estimate of disorder strength in the experimental system. We prove analytically that a sequence of applied fields with fixed amplitude is unable to drive the system to its ground state from a saturated state. These results should be relevant for other systems where disorder does not change the nature of the ground state.

Diversity enabling equilibration: disorder and the ground state in artificial spin ice.

We report a novel approach to the question of whether and how the ground state can be achieved in square artificial spin ices where frustration is incomplete. We identify two sources of randomness that affect the approach to ground state: quenched disorder in the island response to fields and randomness in the sequence of driving fields. Numerical simulations show that quenched disorder can lead to final states with lower energy, and randomness in the sequence of driving fields always lowers the final energy attained by the system. We use a network picture to understand these two effects: disorder in island responses creates new dynamical pathways, and a random sequence of driving fields allows more pathways to be followed.

Vertex dynamics in finite two-dimensional square spin ices.

Local magnetic ordering in artificial spin ices is discussed from the point of view of how geometrical frustration controls dynamics and the approach to steady state. We discuss the possibility of using a particle picture based on vertex configurations to interpret the time evolution of magnetic configurations. Analysis of possible vertex processes allows us to anticipate different behaviors for open and closed edges and the existence of different field regimes. Numerical simulations confirm these results and also demonstrate the importance of correlations and long-range interactions in understanding particle population evolution. We also show that a mean-field model of vertex dynamics gives important insights into finite size effects.