α-catenin middle- and actin-binding domain unfolding mutants differentially impact epithelial strength and sheet migration.

α-catenin (α-cat) displays force-dependent unfolding and binding to actin filaments through direct and indirect means, but features of adherens junction structure and function most vulnerable to loss of these allosteric mechanisms have not been directly compared. By reconstituting an α-cat F-actin-binding domain unfolding mutant known to exhibit enhanced binding to actin (α-cat-H0-FABD+) into α-cat knockout Madin Darby Canine Kidney (MDCK) cells, we show that partial loss of the α-cat catch bond mechanism (via an altered H0 α-helix) leads to stronger epithelial sheet integrity with greater colocalization between the α-cat-H0-FABD+ mutant and actin. α-cat-H0-FABD+ -expressing cells are less efficient at closing scratch-wounds, suggesting reduced capacity for more dynamic cell-cell coordination. Evidence that α-cat-H0-FABD+ is equally accessible to the conformationally sensitive α18 antibody epitope as WT α-cat and shows similar vinculin recruitment suggests this mutant engages lower tension cortical actin networks, as its M-domain is not persistently open. Conversely, α-cat-M-domain salt-bridge mutants with persistent recruitment of vinculin and phosphorylated myosin light chain show only intermediate monolayer adhesive strengths, but display less directionally coordinated and thereby slower migration speeds during wound-repair. These data show α-cat M- and FABD-unfolding mutants differentially impact cell-cell cohesion and migration properties, and suggest signals favoring α-cat-cortical actin interaction without persistent M-domain opening may improve epithelial monolayer strength through enhanced coupling to lower tension actin networks.

Local monomer levels and established filaments potentiate non-muscle myosin 2 assembly.

The ability to dynamically assemble contractile networks is required throughout cell physiology, yet direct biophysical mechanisms regulating non-muscle myosin 2 filament assembly in living cells are lacking. Here, we use a suite of dynamic, quantitative imaging approaches to identify deterministic factors that drive myosin filament appearance and amplification. We find that actin dynamics regulate myosin assembly, but that the static actin architecture plays a less clear role. Instead, remodeling of actin networks modulates the local myosin monomer levels and facilitates assembly through myosin:myosin-driven interactions. Using optogenetically controlled myosin, we demonstrate that locally concentrating myosin is sufficient to both form filaments and jump-start filament amplification and partitioning. By counting myosin monomers within filaments, we demonstrate a myosin-facilitated assembly process that establishes filament stacks prior to partitioning into clusters that feed higher-order networks. Together, these findings establish the biophysical mechanisms regulating the assembly of non-muscle contractile structures that are ubiquitous throughout cell biology.

Machine learning interpretable models of cell mechanics from protein images.

Cellular form and function emerge from complex mechanochemical systems within the cytoplasm. Currently, no systematic strategy exists to infer large-scale physical properties of a cell from its molecular components. This is an obstacle to understanding processes such as cell adhesion and migration. Here, we develop a data-driven modeling pipeline to learn the mechanical behavior of adherent cells. We first train neural networks to predict cellular forces from images of cytoskeletal proteins. Strikingly, experimental images of a single focal adhesion (FA) protein, such as zyxin, are sufficient to predict forces and can generalize to unseen biological regimes. Using this observation, we develop two approaches-one constrained by physics and the other agnostic-to construct data-driven continuum models of cellular forces. Both reveal how cellular forces are encoded by two distinct length scales. Beyond adherent cell mechanics, our work serves as a case study for integrating neural networks into predictive models for cell biology.

Limiting pool and actin architecture controls myosin cluster sizes in adherent cells.

The actomyosin cytoskeleton generates mechanical forces that power important cellular processes, such as cell migration, cell division, and mechanosensing. Actomyosin self-assembles into contractile networks and bundles that underlie force generation and transmission in cells. A central step is the assembly of the myosin II filament from myosin monomers, regulation of which has been extensively studied. However, myosin filaments are almost always found as clusters within the cell cortex. While recent studies characterized cluster nucleation dynamics at the cell periphery, how myosin clusters grow on stress fibers remains poorly characterized. Here, we utilize a U2OS osteosarcoma cell line with endogenously tagged myosin II to measure the myosin cluster size distribution in the lamella of adherent cells. We find that myosin clusters can grow with Rho-kinase (ROCK) activity alone in the absence of myosin motor activity. Time-lapse imaging reveals that myosin clusters grow via increased myosin association to existing clusters, which is potentiated by ROCK-dependent myosin filament assembly. Enabling myosin motor activity allows further myosin cluster growth through myosin association that is dependent on F-actin architecture. Using a toy model, we show that myosin self-affinity is sufficient to recapitulate the experimentally observed myosin cluster size distribution, and that myosin cluster sizes are determined by the pool of myosin available for cluster growth. Together, our findings provide new insights into the regulation of myosin cluster sizes within the lamellar actomyosin cytoskeleton.

T cells Use Focal Adhesions to Pull Themselves Through Confined Environments.

Immune cells are highly dynamic and able to migrate through environments with diverse biochemical and mechanical composition. Their migration has classically been defined as amoeboid under the assumption that it is integrin-independent. Here we show that activated primary Th1 T cells require both confinement and extracellular matrix protein to migrate efficiently. This migration is mediated through small and dynamic focal adhesions that are composed of the same proteins associated with canonical mesenchymal focal adhesions, such as integrins, talin, and vinculin. These focal adhesions, furthermore, localize to sites of contractile traction stresses, enabling T cells to pull themselves through confined spaces. Finally, we show that Th1 T cell preferentially follows tracks of other T cells, suggesting that these adhesions are modifying the extracellular matrix to provide additional environmental guidance cues. These results demonstrate not only that the boundaries between amoeboid and mesenchymal migration modes are ambiguous, but that integrin-mediated adhesions play a key role in T cell motility.

Measuring response functions of active materials from data.

From flocks of birds to biomolecular assemblies, systems in which many individual components independently consume energy to perform mechanical work exhibit a wide array of striking behaviors. Methods to quantify the dynamics of these so-called active systems generally aim to extract important length or time scales from experimental fields. Because such methods focus on extracting scalar values, they do not wring maximal information from experimental data. We introduce a method to overcome these limitations. We extend the framework of correlation functions by taking into account the internal headings of displacement fields. The functions we construct represent the material response to specific types of active perturbation within the system. Utilizing these response functions we query the material response of disparate active systems composed of actin filaments and myosin motors, from model fluids to living cells. We show we can extract critical length scales from the turbulent flows of an active nematic, anticipate contractility in an active gel, distinguish viscous from viscoelastic dissipation, and even differentiate modes of contractility in living cells. These examples underscore the vast utility of this method which measures response functions from experimental observations of complex active systems.

Atypical peripheral actin band formation via overactivation of RhoA and nonmuscle myosin II in mitofusin 2-deficient cells.

Cell spreading and migration play central roles in many physiological and pathophysiological processes. We have previously shown that MFN2 regulates the migration of human neutrophil-like cells via suppressing Rac activation. Here, we show that in mouse embryonic fibroblasts, MFN2 suppresses RhoA activation and supports cell polarization. After initial spreading, the wild-type cells polarize and migrate, whereas the Mfn2-/- cells maintain a circular shape. Increased cytosolic Ca2+ resulting from the loss of Mfn2 is directly responsible for this phenotype, which can be rescued by expressing an artificial tether to bring mitochondria and endoplasmic reticulum to close vicinity. Elevated cytosolic Ca2+ activates Ca2+/calmodulin-dependent protein kinase II, RhoA, and myosin light-chain kinase, causing an overactivation of nonmuscle myosin II, leading to a formation of a prominent F-actin ring at the cell periphery and increased cell contractility. The peripheral actin band alters cell physics and is dependent on substrate rigidity. Our results provide a novel molecular basis to understand how MFN2 regulates distinct signaling pathways in different cells and tissue environments, which is instrumental in understanding and treating MFN2-related diseases.

Limiting Pool and Actin Architecture Controls Myosin Cluster Sizes in Adherent Cells.

The actomyosin cytoskeleton generates mechanical forces that power important cellular processes, such as cell migration, cell division, and mechanosensing. Actomyosin self-assembles into contractile networks and bundles that underlie force generation and transmission in cells. A central step is the assembly of the myosin II filament from myosin monomers, regulation of which has been extensively studied. However, myosin filaments are almost always found as clusters within the cell cortex. While recent studies characterized cluster nucleation dynamics at the cell periphery, how myosin clusters grow on stress fibers remains poorly characterized. Here, we utilize a U2OS osteosarcoma cell line with endogenously tagged myosin II to measure the myosin cluster size distribution in the lamella of adherent cells. We find that myosin clusters can grow with Rho-kinase (ROCK) activity alone in the absence of myosin motor activity. Time-lapse imaging reveals that myosin clusters grow via increased myosin association to existing clusters, which is potentiated by ROCK-dependent myosin filament assembly. Enabling myosin motor activity allows further myosin cluster growth through myosin association that is dependent on F-actin architecture. Using a toy model, we show that myosin self-affinity is sufficient to recapitulate the experimentally observed myosin cluster size distribution, and that myosin cluster sizes are determined by the pool of myosin available for cluster growth. Together, our findings provide new insights into the regulation of myosin cluster sizes within the lamellar actomyosin cytoskeleton.

Repair of noise-induced damage to stereocilia F-actin cores is facilitated by XIRP2 and its novel mechanosensor domain.

Prolonged exposure to loud noise has been shown to affect inner ear sensory hair cells in a variety of deleterious manners, including damaging the stereocilia core. The damaged sites can be visualized as 'gaps' in phalloidin staining of F-actin, and the enrichment of monomeric actin at these sites, along with an actin nucleator and crosslinker, suggests that localized remodeling occurs to repair the broken filaments. Herein, we show that gaps in mouse auditory hair cells are largely repaired within 1 week of traumatic noise exposure through the incorporation of newly synthesized actin. We provide evidence that Xin actin binding repeat containing 2 (XIRP2) is required for the repair process and facilitates the enrichment of monomeric γ-actin at gaps. Recruitment of XIRP2 to stereocilia gaps and stress fiber strain sites in fibroblasts is force-dependent, mediated by a novel mechanosensor domain located in the C-terminus of XIRP2. Our study describes a novel process by which hair cells can recover from sublethal hair bundle damage and which may contribute to recovery from temporary hearing threshold shifts and the prevention of age-related hearing loss.

Shining a light on RhoA: Optical control of cell contractility.

In addition to biochemical and electrochemical signaling, cells also rely extensively on mechanical signaling to regulate their behavior. While a number of tools have been adapted from physics and engineering to manipulate cell mechanics, they typically require specialized equipment or lack spatiotemporal precision. Alternatively, a recent, more elegant approach is to use light itself to modulate the mechanical equilibrium inside the cell. This approach leverages the power of optogenetics, which can be controlled in a fully reversible manner in both time and space, to tune RhoA signaling, the master regulator of cellular contractility. We review here the fundamentals of this approach, including illustrating the tunability and flexibility that optogenetics offers, and demonstrate how this tool can be used to modulate both internal cytoskeletal flows and contractile force generation. Together these features highlight the advantages that optogenetics offers for investigating mechanical interactions in cells.

LIM domain proteins.

Sala and Oakes introduce LIM domain proteins and discuss their roles in transcription, cytokinesis, adhesion, motility and mechanosignaling.

Local Monomer Levels and Established Filaments Potentiate Non-Muscle Myosin 2 Assembly.

The ability to dynamically assemble contractile networks is required throughout cell physiology, yet the biophysical mechanisms regulating non-muscle myosin 2 filament assembly in living cells are lacking. Here we use a suite of dynamic, quantitative imaging approaches to identify deterministic factors that drive myosin filament appearance and amplification. We find that actin dynamics regulate myosin assembly, but that the actin architecture plays a minimal direct role. Instead, remodeling of actin networks modulates the local myosin monomer levels and facilitates assembly through myosin:myosin driven interactions. Using optogenetically controlled myosin, we demonstrate that locally concentrating myosin is sufficient to both form filaments and jump-start filament amplification and partitioning. By counting myosin monomers within filaments, we demonstrate a myosin-facilitated assembly process that establishes sub-resolution filament stacks prior to partitioning into clusters that feed higher-order networks. Together these findings establish the biophysical mechanisms regulating the assembly of non-muscle contractile structures that are ubiquitous throughout cell biology.

Nonmuscle myosin 2 filaments are processive in cells.

Directed transport of cellular components is often dependent on the processive movements of cytoskeletal motors. Myosin 2 motors predominantly engage actin filaments of opposing orientation to drive contractile events and are therefore not traditionally viewed as processive. However, recent in vitro experiments with purified nonmuscle myosin 2 (NM2) demonstrated myosin 2 filaments could move processively. Here, we establish processivity as a cellular property of NM2. Processive runs in central nervous system-derived CAD cells are most apparent on bundled actin in protrusions that terminate at the leading edge. We find that processive velocities in vivo are consistent with in vitro measurements. NM2 makes these processive runs in its filamentous form against lamellipodia retrograde flow, though anterograde movement can still occur in the absence of actin dynamics. Comparing the processivity of NM2 isoforms, we find that NM2A moves slightly faster than NM2B. Finally, we demonstrate that this is not a cell-specific property, as we observe processive-like movements of NM2 in the lamella and subnuclear stress fibers of fibroblasts. Collectively, these observations further broaden NM2 functionality and the biological processes in which the already ubiquitous motor can contribute.

ST3GAL1 and ßII-spectrin pathways control CAR T cell migration to target tumors.

Adoptive transfer of genetically engineered chimeric antigen receptor (CAR) T cells is becoming a promising treatment option for hematological malignancies. However, T cell immunotherapies have mostly failed in individuals with solid tumors. Here, with a CRISPR-Cas9 pooled library, we performed an in vivo targeted loss-of-function screen and identified ST3 ß-galactoside α-2,3-sialyltransferase 1 (ST3GAL1) as a negative regulator of the cancer-specific migration of CAR T cells. Analysis of glycosylated proteins revealed that CD18 is a major effector of ST3GAL1 in activated CD8+ T cells. ST3GAL1-mediated glycosylation induces the spontaneous nonspecific tissue sequestration of T cells by altering lymphocyte function-associated antigen-1 (LFA-1) endocytic recycling. Engineered CAR T cells with enhanced expression of ßII-spectrin, a central LFA-1-associated cytoskeleton molecule, reversed ST3GAL1-mediated nonspecific T cell migration and reduced tumor growth in mice by improving tumor-specific homing of CAR T cells. These findings identify the ST3GAL1-ßII-spectrin axis as a major cell-intrinsic program for cancer-targeting CAR T cell migration and as a promising strategy for effective T cell immunotherapy.

Non-muscle myosin 2 filaments are processive in cells.

Directed transport of cellular components is often dependent on the processive movements of cytoskeletal motors. Myosin 2 motors predominantly engage actin filaments of opposing orientation to drive contractile events, and are therefore not traditionally viewed as processive. However, recent in vitro experiments with purified non-muscle myosin 2 (NM2) demonstrated myosin 2 filaments could move processively. Here, we establish processivity as a cellular property of NM2. Processive runs in central nervous system-derived CAD cells are most apparent as processive movements on bundled actin in protrusions that terminate at the leading edge. We find that processive velocities in vivo are consistent with in vitro measurements. NM2 makes these processive runs in its filamentous form against lamellipodia retrograde flow, though anterograde movement can still occur in the absence of actin dynamics. Comparing the processivity of NM2 isoforms, we find that NM2A moves slightly faster than NM2B. Finally, we demonstrate that this is not a cell-specific property, as we observe processive-like movements of NM2 in the lamella and subnuclear stress fibers of fibroblasts. Collectively, these observations further broaden NM2 functionality and the biological processes in which the already ubiquitous motor can contribute.

Zyxin is all you need: machine learning adherent cell mechanics.

Cellular form and function emerge from complex mechanochemical systems within the cytoplasm. No systematic strategy currently exists to infer large-scale physical properties of a cell from its many molecular components. This is a significant obstacle to understanding biophysical processes such as cell adhesion and migration. Here, we develop a data-driven biophysical modeling approach to learn the mechanical behavior of adherent cells. We first train neural networks to predict forces generated by adherent cells from images of cytoskeletal proteins. Strikingly, experimental images of a single focal adhesion protein, such as zyxin, are sufficient to predict forces and generalize to unseen biological regimes. This protein field alone contains enough information to yield accurate predictions even if forces themselves are generated by many interacting proteins. We next develop two approaches - one explicitly constrained by physics, the other more agnostic - that help construct data-driven continuum models of cellular forces using this single focal adhesion field. Both strategies consistently reveal that cellular forces are encoded by two different length scales in adhesion protein distributions. Beyond adherent cell mechanics, our work serves as a case study for how to integrate neural networks in the construction of predictive phenomenological models in cell biology, even when little knowledge of the underlying microscopic mechanisms exist.

Quantifying Strain-Sensing Protein Recruitment During Stress Fiber Repair.

A family of proteins have been identified that recognize damaged, strained actin filaments in stress fibers. These proteins are often referred to as strain- or force-sensing and trigger downstream signaling mechanisms that can facilitate repair at these strain sites. Here we describe a method using high-resolution microscopy to screen and quantify the mechanosensitive recruitment of proteins to these stress fiber strain sites. Strain sites are induced using spatially controlled illumination of UV light to locally damage actin stress fibers. Recruitment of potential strain-sensing proteins can then either be compared to (Blanchoin, Physiol Rev 94, 235-263, 2014) a known control (e.g., zyxin-GFP) or (Hoffman, Mol Biol Cell 23, 1846-1859, 2012) the pre-damaged stress fiber protein distribution. With this method, strain-sensing proteins and their dynamic association with stress fiber strain sites can be reproducibly measured and compared.

Meeting report - the ever-fascinating world of septins.

Septins are GTP-binding proteins that assemble into hetero-oligomers. They can interact with each other end-to-end to form filaments, making them the fourth element of the cytoskeleton. To update the current knowledge on the ever-increasing implications of these fascinating proteins in cellular functions, a hundred expert scientists from across the globe gathered from 12 to 15 October 2021 in Berlin for the first hybrid-format (on site and virtual) EMBO workshop Molecular and Cell Biology of Septins.

A workflow for rapid unbiased quantification of fibrillar feature alignment in biological images.

Measuring the organisation of the cellular cytoskeleton and the surrounding extracellular matrix (ECM) is currently of wide interest as changes in both local and global alignment can highlight alterations in cellular functions and material properties of the extracellular environment. Different approaches have been developed to quantify these structures, typically based on fibre segmentation or on matrix representation and transformation of the image, each with its own advantages and disadvantages. Here we present AFT-Alignment by Fourier Transform, a workflow to quantify the alignment of fibrillar features in microscopy images exploiting 2D Fast Fourier Transforms (FFT). Using pre-existing datasets of cell and ECM images, we demonstrate our approach and compare and contrast this workflow with two other well-known ImageJ algorithms to quantify image feature alignment. These comparisons reveal that AFT has a number of advantages due to its grid-based FFT approach. 1) Flexibility in defining the window and neighbourhood sizes allows for performing a parameter search to determine an optimal length scale to carry out alignment metrics. This approach can thus easily accommodate different image resolutions and biological systems. 2) The length scale of decay in alignment can be extracted by comparing neighbourhood sizes, revealing the overall distance that features remain anisotropic. 3) The approach is ambivalent to the signal source, thus making it applicable for a wide range of imaging modalities and is dependent on fewer input parameters than segmentation methods. 4) Finally, compared to segmentation methods, this algorithm is computationally inexpensive, as high-resolution images can be evaluated in less than a second on a standard desktop computer. This makes it feasible to screen numerous experimental perturbations or examine large images over long length scales. Implementation is made available in both MATLAB and Python for wider accessibility, with example datasets for single images and batch processing. Additionally, we include an approach to automatically search parameters for optimum window and neighbourhood sizes, as well as to measure the decay in alignment over progressively increasing length scales.