SOAX: a software for quantification of 3D biopolymer networks

Design and Construction of a Multi-Tiered Minimal Actin Cortex for Structural Support in Lipid Bilayer Applications

Artificial lipid bilayers have revolutionized biochemical and biophysical research by providing a versatile interface to study aspects of cell membranes and membrane-bound processes in a controlled environment. Artificial bilayers also play a central role in numerous biosensing applications, form the foundational interface for liposomal drug delivery, and provide a vital structure for the development of synthetic cells. But unlike the envelope in many living cells, artificial bilayers can be mechanically fragile. Here, we develop prototype scaffolds for artificial bilayers made from multiple chemically linked tiers of actin filaments that can be bonded to lipid headgroups. We call the interlinked and layered assembly a multiple minimal actin cortex (multi-MAC). Construction of multi-MACs has the potential to significantly increase the bilayer's resistance to applied stress while retaining many desirable physical and chemical properties that are characteristic of lipid bilayers. Furthermore, the linking chemistry of multi-MACs is generalizable and can be applied almost anywhere lipid bilayers are important. This work describes a filament-by-filament approach to multi-MAC assembly that produces distinct 2D and 3D architectures. The nature of the structure depends on a combination of the underlying chemical conditions. Using fluorescence imaging techniques in model planar bilayers, we explore how multi-MACs vary with electrostatic charge, assembly time, ionic strength, and type of chemical linker. We also assess how the presence of a multi-MAC alters the underlying lateral diffusion of lipids and investigate the ability of multi-MACs to withstand exposure to shear stress.

In-Cell Association of a Bioorthogonal Tubulin

Studies of proteins from one organism in another organism's cells have shown that such exogenous proteins stick more, pointing toward coevolution of the cytoplasm and protein surface to minimize stickiness. Here we flip this question around by asking whether exogenous proteins can assemble efficiently into their target complexes in a non-native cytoplasm. We use as our model system the assembly of BtubA and BtubB from Prosthecobacter hosted in human U-2 OS cells. BtubA and B evolved from eukaryotic tubulins after horizontal gene transfer, but they have low surface sequence identity with the homologous human tubulins and do not respond to tubulin drugs such as nocodazole. In U-2 OS cells, BtubA and B assemble efficiently into dimers compared to in vitro, and the wild-type BtubA and B proteins subsequently are able to form microtubules as well. We find that generic crowding effects (Ficoll 70 in vitro) contribute significantly to efficient dimer assembly when compared to sticking interactions (U-2 OS cell lysate in vitro), consistent with the notion that a generic mechanism such as crowding can be effective at driving assembly of exogenous proteins, even when protein-cytoplasm quinary structure and sticking have been modified in a non-native cytoplasm. A simple Monte Carlo model of in vitro and in-cell interactions, treating BtubA and B as sticky dipoles in a matrix of sticky or nonsticky crowders, rationalizes all the experimental trends with two adjustable parameters and reveals nucleation as the likely mechanism for the time-scale separation between dimer- and tubule formation in-cell and in vitro.

Adhesion-induced cortical flows pattern E-cadherin-mediated cell contacts

Metazoan development relies on the formation and remodeling of cell-cell contacts. Dynamic reorganization of adhesion receptors and the actomyosin cell cortex in space and time plays a central role in cell-cell contact formation and maturation. Nevertheless, how this process is mechanistically achieved when new contacts are formed remains unclear. Here, by building a biomimetic assay composed of progenitor cells adhering to supported lipid bilayers functionalized with E-cadherin ectodomains, we show that cortical F-actin flows, driven by the depletion of myosin-2 at the cell contact center, mediate the dynamic reorganization of adhesion receptors and cell cortex at the contact. E-cadherin-dependent downregulation of the small GTPase RhoA at the forming contact leads to both a depletion of myosin-2 and a decrease of F-actin at the contact center. At the contact rim, in contrast, myosin-2 becomes enriched by the retraction of bleb-like protrusions, resulting in a cortical tension gradient from the contact rim to its center. This tension gradient, in turn, triggers centrifugal F-actin flows, leading to further accumulation of F-actin at the contact rim and the progressive redistribution of E-cadherin from the contact center to the rim. Eventually, this combination of actomyosin downregulation and flows at the contact determines the characteristic molecular organization, with E-cadherin and F-actin accumulating at the contact rim, where they are needed to mechanically link the contractile cortices of the adhering cells.

Quantifying cytoskeletal organization from optical microscopy data

The actin cytoskeleton plays a pivotal role in a broad range of physiological processes including directing cell shape and subcellular organization, determining cell mechanical properties, and sensing and transducing mechanical forces. The versatility of the actin cytoskeleton arises from the ability of actin filaments to assemble into higher order structures through their interaction with a vast set of regulatory proteins. Actin filaments assemble into bundles, meshes, and networks, where different combinations of these structures fulfill specific functional roles. Analyzing the organization and abundance of different actin structures from optical microscopy data provides a valuable metric for assessing cell physiological function and changes associated with disease. However, quantitative measurements of the size, abundance, orientation, and distribution of different types of actin structure remains challenging both from an experimental and image analysis perspective. In this review, we summarize image analysis methods for extracting quantitative values that can be used for characterizing the organization of actin structures and provide selected examples. We summarize the potential sample types and metric reported with different approaches as a guide for selecting an image analysis strategy.

MATLAB-Based Algorithm and Software for Analysis of Wavy Collagen Fibers

Knowledge of soft tissue fiber structure is necessary for accurate characterization and modeling of their mechanical response. Fiber configuration and structure informs both our understanding of healthy tissue physiology and of pathological processes resulting from diseased states. This study develops an automatic algorithm to simultaneously estimate fiber global orientation, abundance, and waviness in an investigated image. To our best knowledge, this is the first validated algorithm which can reliably separate fiber waviness from its global orientation for considerably wavy fibers. This is much needed feature for biological tissue characterization. The algorithm is based on incremental movement of local regions of interest (ROI) and analyzes two-dimensional images. Pixels belonging to the fiber are identified in the ROI, and ROI movement is determined according to local orientation of fiber within the ROI. The algorithm is validated with artificial images and ten images of porcine trachea containing wavy fibers. In each image, 80-120 fibers were tracked manually to serve as verification. The coefficient of determination R2 between curve lengths and histograms documenting the fiber waviness and global orientation were used as metrics for analysis. Verification-confirmed results were independent of image rotation and degree of fiber waviness, with curve length accuracy demonstrated to be below 1% of fiber curved length. Validation-confirmed median and interquartile range of R2, respectively, were 0.90 and 0.05 for curved length, 0.92 and 0.07 for waviness, and 0.96 and 0.04 for global orientation histograms. Software constructed from the proposed algorithm was able to track one fiber in about 1.1 s using a typical office computer. The proposed algorithm can reliably and accurately estimate fiber waviness, curve length, and global orientation simultaneously, moving beyond the limitations of prior methods.

Dynamic remodeling of actin networks by cyclase-associated protein and CAP-Abp1 complexes

How actin filaments are spatially organized and remodeled into diverse higher-order networks in vivo is still not well understood. Here, we report an unexpected F-actin "coalescence" activity driven by cyclase-associated protein (CAP) and enhanced by its interactions with actin-binding protein 1 (Abp1). We directly observe S. cerevisiae CAP and Abp1 rapidly transforming branched or linear actin networks by bundling and sliding filaments past each other, maximizing filament overlap, and promoting compaction into bundles. This activity does not require ATP and is conserved, as similar behaviors are observed for the mammalian homologs of CAP and Abp1. Coalescence depends on the CAP oligomerization domain but not the helical folded domain (HFD) that mediates its functions in F-actin severing and depolymerization. Coalescence by CAP-Abp1 further depends on interactions between CAP and Abp1 and interactions between Abp1 and F-actin. Our results are consistent with a mechanism in which the formation of energetically favorable sliding CAP and CAP-Abp1 crosslinks drives F-actin bundle compaction. Roles for CAP and CAP-Abp1 in actin remodeling in vivo are supported by strong phenotypes arising from deletion of the CAP oligomerization domain and by genetic interactions between sac6Δ and an srv2-301 mutant that does not bind Abp1. Together, these observations identify a new actin filament remodeling function for CAP, which is further enhanced by its direct interactions with Abp1.

Compressive forces stabilize microtubules in living cells

Microtubules are cytoskeleton components with unique mechanical and dynamic properties. They are rigid polymers that alternate phases of growth and shrinkage. Nonetheless, the cells can display a subset of stable microtubules, but it is unclear whether microtubule dynamics and mechanical properties are related. Recent in vitro studies suggest that microtubules have mechano-responsive properties, being able to stabilize their lattice by self-repair on physical damage. Here we study how microtubules respond to cycles of compressive forces in living cells and find that microtubules become distorted, less dynamic and more stable. This mechano-stabilization depends on CLASP2, which relocates from the end to the deformed shaft of microtubules. This process seems to be instrumental for cell migration in confined spaces. Overall, these results demonstrate that microtubules in living cells have mechano-responsive properties that allow them to resist and even counteract the forces to which they are subjected, being a central mediator of cellular mechano-responses.

Data driven and cell specific determination of nuclei-associated actin structure

Quantitative and volumetric assessment of filamentous actin fibers (F-actin) remains challenging due to their interconnected nature, leading researchers to utilize threshold based or qualitative measurement methods with poor reproducibility. Here we introduce a novel machine learning based methodology for accurate quantification and reconstruction of nuclei-associated F-actin. Utilizing a Convolutional Neural Network (CNN), we segment actin filaments and nuclei from 3D confocal microscopy images and then reconstruct each fiber by connecting intersecting contours on cross-sectional slices. This allowed measurement of the total number of actin filaments and individual actin filament length and volume in a reproducible fashion. Focusing on the role of F-actin in supporting nucleocytoskeletal connectivity, we quantified apical F-actin, basal F-actin, and nuclear architecture in mesenchymal stem cells (MSCs) following the disruption of the Linker of Nucleoskeleton and Cytoskeleton (LINC) Complexes. Disabling LINC in mesenchymal stem cells (MSCs) generated F-actin disorganization at the nuclear envelope characterized by shorter length and volume of actin fibers contributing a less elongated nuclear shape. Our findings not only present a new tool for mechanobiology but introduce a novel pipeline for developing realistic computational models based on quantitative measures of F-actin.

Exploring generic principles of compartmentalization in a developmental in vitro model

Self-organization of cells into higher-order structures is key for multicellular organisms, for example via repetitive replication of template-like founder cells or syncytial energids. Yet, very similar spatial arrangements of cell-like compartments ('protocells') are also seen in a minimal model system of Xenopus egg extracts in the absence of template structures and chromatin, with dynamic microtubule assemblies driving the self-organization process. Quantifying geometrical features over time, we show here that protocell patterns are highly organized with a spatial arrangement and coarsening dynamics similar to that of two-dimensional foams but without the long-range ordering expected for hexagonal patterns. These features remain invariant when enforcing smaller protocells by adding taxol, i.e. patterns are dominated by a single, microtubule-derived length scale. Comparing our data to generic models, we conclude that protocell patterns emerge by simultaneous formation of randomly assembling protocells that grow at a uniform rate towards a frustrated arrangement before fusion of adjacent protocells eventually drives coarsening. The similarity of protocell patterns to arrays of energids and cells in developing organisms, but also to epithelial monolayers, suggests generic mechanical cues to drive self-organized space compartmentalization.

3D Visualization of Microtubules in Epidermal Pavement Cells

The plant cytoskeleton is instrumental in cellular processes such as cell growth, differentiation, and immune response. Microtubules, in particular, play a crucial role in morphogenesis by governing the deposition of plant cell wall polysaccharides and, in consequence, the cell wall mechanics and cell shape. Scrutinizing the microtubule dynamics is therefore integral to understanding the spatiotemporal regulation of cellular activities. In this chapter, we outline steps to acquire 3D images of microtubules in epidermal pavement cells of Arabidopsis thaliana cotyledons using a confocal microscope. We introduce the steps to assess the microtubule distribution and organization using image processing software Bitplane Imaris and ImageJ. We also demonstrate how the interpretation of image material can be facilitated by post-processing with general-purpose image enhancement software using methods trained by artificial intelligence-based algorithms.

A systematic review and comparison of automated tools for quantification of fibrous networks

Fibrous networks are essential structural components of biological and engineered materials. Accordingly, many approaches have been developed to quantify their structural properties, which define their material properties. However, a comprehensive overview and comparison of methods is lacking. Therefore, we systematically searched for automated tools quantifying network characteristics in confocal, stimulated emission depletion (STED) or scanning electron microscopy (SEM) images and compared these tools by applying them to fibrin, a prototypical fibrous network in thrombi. Structural properties of fibrin such as fiber diameter and alignment are clinically relevant, since they influence the risk of thrombosis. Based on a systematic comparison of the automated tools with each other, manual measurements, and simulated networks, we provide guidance to choose appropriate tools for fibrous network quantification depending on imaging modality and structural parameter. These tools are often able to reliably measure relative changes in network characteristics, but absolute numbers should be interpreted with care. STATEMENT OF SIGNIFICANCE: Structural properties of fibrous networks define material properties of many biological and engineered materials. Many methods exist to automatically quantify structural properties, but an overview and comparison is lacking. In this work, we systematically searched for all publicly available automated analysis tools that can quantify structural properties of fibrous networks. Next, we compared them by applying them to microscopy images of fibrin networks. We also benchmarked the automated tools against manual measurements or synthetic images. As a result, we give advice on which automated analysis tools to use for specific structural properties. We anticipate that researchers from a large variety of fields, ranging from thrombosis and hemostasis to cancer research, and materials science, can benefit from our work.

Extracellular Cues Govern Shape and Cytoskeletal Organization in Giant Unilamellar Lipid Vesicles

Spontaneous and induced front-rear polarization and a subsequent asymmetric actin cytoskeleton is a crucial event leading to cell migration, a key process involved in a variety of physiological and pathological conditions such as tissue development, wound healing, and cancer. Migration of adherent cells relies on the balance between adhesion to the underlying matrix and cytoskeleton-driven front protrusion and rear retraction. A current challenge is to uncouple the effect of adhesion and shape from the contribution of the cytoskeleton in regulating the onset of front-rear polarization. Here, we present a minimal model system that introduces an asymmetric actin cytoskeleton in synthetic cells, which are resembled by giant unilamellar lipid vesicles (GUVs) adhering onto symmetric and asymmetric micropatterned surfaces. Surface micropatterning of streptavidin-coated regions with varying adhesion shape and area was achieved by maskless UV photopatterning. To further study the effects of GUV shape on the cytoskeletal organization, actin filaments were polymerized together with bundling proteins inside the GUVs. The micropatterns induce synthetic cell deformation upon adhesion to the surface, with the cell shape adapting to the pattern shape and size. As expected, asymmetric patterns induce an asymmetric deformation in adherent synthetic cells. Actin filaments orient along the long axis of the deformed GUV, when having a length similar to the size of the major axis, whereas short filaments exhibit random orientation. With this bottom-up approach we have laid the first steps to identify the relationship between cell front-rear polarization and cytoskeleton organization in the future. Such a minimal system will allow us to further study the major components needed to create a polarized cytoskeleton at the onset of migration.

Microtubules self-repair in living cells

Microtubule self-repair has been studied both in vitro and in vivo as an underlying mechanism of microtubule stability. The turnover of tubulin dimers along the microtubule has challenged the pre-existing dogma that only growing ends are dynamic. However, although there is clear evidence of tubulin incorporation into the shaft of polymerized microtubules in vitro, the possibility of such events occurring in living cells remains uncertain. In this study, we investigated this possibility by microinjecting purified tubulin dimers labeled with a red fluorophore into the cytoplasm of cells expressing GFP-tubulin. We observed the appearance of red dots along the pre-existing green microtubule within minutes. We found that the fluorescence intensities of these red dots were inversely correlated with the green signal, suggesting that the red dimers were incorporated into the microtubules and replaced the pre-existing green dimers. Lateral distance from the microtubule center was similar to that in incorporation sites and in growing ends. The saturation of the size and spatial frequency of incorporations as a function of injected tubulin concentration and post-injection delay suggested that the injected dimers incorporated into a finite number of damaged sites. By our low estimate, within a few minutes of the injections, free dimers incorporated into major repair sites every 70 μm of microtubules. Finally, we mapped the location of these sites in micropatterned cells and found that they were more concentrated in regions where the actin filament network was less dense and where microtubules exhibited greater lateral fluctuations.

Multiscale Label-Free Imaging of Fibrillar Collagen in the Tumor Microenvironment

With recent advances in cancer therapeutics, there is a great need for improved imaging methods for characterizing cancer onset and progression in a quantitative and actionable way. Collagen, the most abundant extracellular matrix protein in the tumor microenvironment (and the body in general), plays a multifaceted role, both hindering and promoting cancer invasion and progression. Collagen deposition can defend the tumor with immunosuppressive effects, while aligned collagen fiber structures can enable tumor cell migration, aiding invasion and metastasis. Given the complex role of collagen fiber organization and topology, imaging has been a tool of choice to characterize these changes on multiple spatial scales, from the organ and tumor scale to cellular and subcellular level. Macroscale density already aids in the detection and diagnosis of solid cancers, but progress is being made to integrate finer microscale features into the process. Here we review imaging modalities ranging from optical methods of second harmonic generation (SHG), polarized light microscopy (PLM), and optical coherence tomography (OCT) to the medical imaging approaches of ultrasound and magnetic resonance imaging (MRI). These methods have enabled scientists and clinicians to better understand the impact collagen structure has on the tumor environment, at both the bulk scale (density) and microscale (fibrillar structure) levels. We focus on imaging methods with the potential to both examine the collagen structure in as natural a state as possible and still be clinically amenable, with an emphasis on label-free strategies, exploiting intrinsic optical properties of collagen fibers.

A Beginner’s Guide to the Characterization of Hydrogel Microarchitecture for Cellular Applications

The extracellular matrix (ECM) is a three-dimensional, acellular scaffold of living tissues. Incorporating the ECM into cell culture models is a goal of cell biology studies and requires biocompatible materials that can mimic the ECM. Among such materials are hydrogels: polymeric networks that derive most of their mass from water. With the tuning of their properties, these polymer networks can resemble living tissues. The microarchitectural properties of hydrogels, such as porosity, pore size, fiber length, and surface topology can determine cell plasticity. The adequate characterization of these parameters requires reliable and reproducible methods. However, most methods were historically standardized using other biological specimens, such as 2D cell cultures, biopsies, or even animal models. Therefore, their translation comes with technical limitations when applied to hydrogel-based cell culture systems. In our current work, we have reviewed the most common techniques employed in the characterization of hydrogel microarchitectures. Our review provides a concise description of the underlying principles of each method and summarizes the collective data obtained from cell-free and cell-loaded hydrogels. The advantages and limitations of each technique are discussed, and comparisons are made. The information presented in our current work will be of interest to researchers who employ hydrogels as platforms for cell culture, 3D bioprinting, and other fields within hydrogel-based research.

Halogenation of tyrosine perturbs large-scale protein self-organization

Protein halogenation is a common non-enzymatic post-translational modification contributing to aging, oxidative stress-related diseases and cancer. Here, we report a genetically encodable halogenation of tyrosine residues in a reconstituted prokaryotic filamentous cell-division protein (FtsZ) as a platform to elucidate the implications of halogenation that can be extrapolated to living systems of much higher complexity. We show how single halogenations can fine-tune protein structures and dynamics of FtsZ with subtle perturbations collectively amplified by the process of FtsZ self-organization. Based on experiments and theories, we have gained valuable insights into the mechanism of halogen influence. The bending of FtsZ structures occurs by affecting surface charges and internal domain distances and is reflected in the decline of GTPase activities by reducing GTP binding energy during polymerization. Our results point to a better understanding of the physiological and pathological effects of protein halogenation and may contribute to the development of potential diagnostic tools.

Combining Image Restoration and Traction Force Microscopy to Study Extracellular Matrix-Dependent Keratin Filament Network Plasticity

Keratin intermediate filaments are dynamic cytoskeletal components that are responsible for tuning the mechanical properties of epithelial tissues. Although it is known that keratin filaments (KFs) are able to sense and respond to changes in the physicochemical properties of the local niche, a direct correlation of the dynamic three-dimensional network structure at the single filament level with the microenvironment has not been possible. Using conventional approaches, we find that keratin flow rates are dependent on extracellular matrix (ECM) composition but are unable to resolve KF network organization at the single filament level in relation to force patterns. We therefore developed a novel method that combines a machine learning-based image restoration technique and traction force microscopy to decipher the fine details of KF network properties in living cells grown on defined ECM patterns. Our approach utilizes Content-Aware Image Restoration (CARE) to enhance the temporal resolution of confocal fluorescence microscopy by at least five fold while preserving the spatial resolution required for accurate extraction of KF network structure at the single KF/KF bundle level. The restored images are used to segment the KF network, allowing numerical analyses of its local properties. We show that these tools can be used to study the impact of ECM composition and local mechanical perturbations on KF network properties and corresponding traction force patterns in size-controlled keratinocyte assemblies. We were thus able to detect increased curvature but not length of KFs on laminin-322 versus fibronectin. Photoablation of single cells in microprinted circular quadruplets revealed surprisingly little but still significant changes in KF segment length and curvature that were paralleled by an overall reduction in traction forces without affecting global network orientation in the modified cell groups irrespective of the ECM coating. Single cell analyses furthermore revealed differential responses to the photoablation that were less pronounced on laminin-332 than on fibronectin. The obtained results illustrate the feasibility of combining multiple techniques for multimodal monitoring and thereby provide, for the first time, a direct comparison between the changes in KF network organization at the single filament level and local force distribution in defined paradigms.

Measurement of the Persistence Length of Cytoskeletal Filaments using Curvature Distributions

Cytoskeletal filaments such as microtubules and actin filaments play important roles in the mechanical integrity of cells and the ability of cells to respond to their environment. Measuring the mechanical properties of cytoskeletal structures is crucial for gaining insight into intracellular mechanical stresses and their role in regulating cellular processes. One of the ways to characterize these mechanical properties is by measuring their persistence length, the average length over which filaments stay straight. There are several approaches in the literature for measuring filament deformations, such as Fourier analysis of images obtained using fluorescence microscopy. Here, we show how curvature distributions can be used as an alternative tool to quantify bio-filament deformations, and investigate how the apparent stiffness of filaments depends on the resolution and noise of the imaging system. We present analytical calculations of the scaling curvature distributions as a function of filament discretization, and test our predictions by comparing Monte Carlo simulations to results from existing techniques. We also apply our approach to microtubules and actin filaments obtained from in vitro gliding assay experiments with high densities of non-functional motors, and calculate the persistence length of these filaments. The presented curvature analysis is significantly more accurate compared to existing approaches for small data sets, and can be readily applied to both in vitro or in vivo filament data through the use of the open-source codes we provide.

Quantitative mapping of keratin networks in 3D

Mechanobiology requires precise quantitative information on processes taking place in specific 3D microenvironments. Connecting the abundance of microscopical, molecular, biochemical, and cell mechanical data with defined topologies has turned out to be extremely difficult. Establishing such structural and functional 3D maps needed for biophysical modeling is a particular challenge for the cytoskeleton, which consists of long and interwoven filamentous polymers coordinating subcellular processes and interactions of cells with their environment. To date, useful tools are available for the segmentation and modeling of actin filaments and microtubules but comprehensive tools for the mapping of intermediate filament organization are still lacking. In this work, we describe a workflow to model and examine the complete 3D arrangement of the keratin intermediate filament cytoskeleton in canine, murine, and human epithelial cells both, in vitro and in vivo. Numerical models are derived from confocal airyscan high-resolution 3D imaging of fluorescence-tagged keratin filaments. They are interrogated and annotated at different length scales using different modes of visualization including immersive virtual reality. In this way, information is provided on network organization at the subcellular level including mesh arrangement, density and isotropic configuration as well as details on filament morphology such as bundling, curvature, and orientation. We show that the comparison of these parameters helps to identify, in quantitative terms, similarities and differences of keratin network organization in epithelial cell types defining subcellular domains, notably basal, apical, lateral, and perinuclear systems. The described approach and the presented data are pivotal for generating mechanobiological models that can be experimentally tested.

Actin crosslinker competition and sorting drive emergent GUV size-dependent actin network architecture

The proteins that make up the actin cytoskeleton can self-assemble into a variety of structures. In vitro experiments and coarse-grained simulations have shown that the actin crosslinking proteins α-actinin and fascin segregate into distinct domains in single actin bundles with a molecular size-dependent competition-based mechanism. Here, by encapsulating actin, α-actinin, and fascin in giant unilamellar vesicles (GUVs), we show that physical confinement can cause these proteins to form much more complex structures, including rings and asters at GUV peripheries and centers; the prevalence of different structures depends on GUV size. Strikingly, we found that α-actinin and fascin self-sort into separate domains in the aster structures with actin bundles whose apparent stiffness depends on the ratio of the relative concentrations of α-actinin and fascin. The observed boundary-imposed effect on protein sorting may be a general mechanism for creating emergent structures in biopolymer networks with multiple crosslinkers.

Actin crosslinker competition and sorting drive emergent GUV size-dependent actin network architecture

The proteins that make up the actin cytoskeleton can self-assemble into a variety of structures. In vitro experiments and coarse-grained simulations have shown that the actin crosslinking proteins α-actinin and fascin segregate into distinct domains in single actin bundles with a molecular size-dependent competition-based mechanism. Here, by encapsulating actin, α-actinin, and fascin in giant unilamellar vesicles (GUVs), we show that physical confinement can cause these proteins to form much more complex structures, including rings and asters at GUV peripheries and centers; the prevalence of different structures depends on GUV size. Strikingly, we found that α-actinin and fascin self-sort into separate domains in the aster structures with actin bundles whose apparent stiffness depends on the ratio of the relative concentrations of α-actinin and fascin. The observed boundary-imposed effect on protein sorting may be a general mechanism for creating emergent structures in biopolymer networks with multiple crosslinkers.

By encapsulating proteins in giant unilamellar vesicles, Bashirzadeh et al find that actin crosslinkers, α-actinin and fascin, can self-assemble with actin into complex structures that depend on the degree of confinement. Further analysis and modeling show that α-actinin and fascin sort to separate domains of these structures. These insights may be generalizable to other biopolymer networks containing crosslinkers.

Fiber finding algorithm using stepwise tracing to identify biopolymer fibers in noisy 3D images

We present a novel fiber finding algorithm (FFA) that will permit researchers to detect and return traces of individual biopolymers. Determining the biophysical properties and structural cues of biopolymers can permit researchers to assess the progression and severity of disease. Confocal microscopy images are a useful method for observing biopolymer structures in three dimensions, but their utility for identifying individual biopolymers is impaired by noise inherent in the acquisition process, including convolution from the point spread function (PSF). The new, iterative FFA we present here 1) measures a microscope's PSF and uses it as a metric for identifying fibers against the background; 2) traces each fiber within a cone angle; and 3) blots out the identified trace before identifying another fiber. Blotting out the identified traces in each iteration allows the FFA to detect and return traces of single fibers accurately and efficiently-even within fiber bundles. We used the FFA to trace unlabeled collagen type I fibers-a biopolymer used to mimic the extracellular matrix in in vitro cancer assays-imaged by confocal reflectance microscopy in three dimensions, enabling quantification of fiber contour length, persistence length, and three-dimensional (3D) mesh size. Based on 3D confocal reflectance microscopy images and the PSF, we traced and measured the fibers to confirm that colder gelation temperatures increased fiber contour length, persistence length, and 3D mesh size-thereby demonstrating the FFA's use in quantifying biopolymers' structural and physical cues from noisy microscope images.

Oblique circle method for measuring the curvature and twist of mitotic spindle microtubule bundles

The highly ordered spatial organization of microtubule bundles in the mitotic spindle is crucial for its proper functioning. The recent discovery of twisted shapes of microtubule bundles and spindle chirality suggests that the bundles extend along curved paths in three dimensions, rather than being confined to a plane. This, in turn, implies that rotational forces, i.e., torques, exist in the spindle in addition to the widely studied linear forces. However, studies of spindle architecture and forces are impeded by a lack of a robust method for the geometric quantification of microtubule bundles in the spindle. In this work, we describe a simple method for measuring and evaluating the shapes of microtubule bundles by characterizing them in terms of their curvature and twist. By using confocal microscopy, we obtain three-dimensional images of spindles, which allows us to trace the entire microtubule bundle. For each traced bundle, we first fit a plane and then fit a circle lying in that plane. With this robust method, we extract the curvature and twist, which represent the geometric information characteristic for each bundle. As the bundle shapes reflect the forces within them, this method is valuable for the understanding of forces that act on chromosomes during mitosis.

Network organisation and the dynamics of tubules in the endoplasmic reticulum

The endoplasmic reticulum (ER) is a eukaryotic subcellular organelle composed of tubules and sheet-like areas of membrane connected at junctions. The tubule network is highly dynamic and undergoes rapid and continual rearrangement. There are currently few tools to evaluate network organisation and dynamics. We quantified ER network organisation in Vero and MRC5 cells, and developed an analysis workflow for dynamics of established tubules in live cells. The persistence length, tubule length, junction coordination number and angles of the network were quantified. Hallmarks of imbalances in ER tension, indications of interactions with microtubules and other subcellular organelles, and active dynamics were observed. Clear differences in dynamic behaviour were observed for established tubules at different positions within the cell using itemset mining. We found that tubules with activity-driven fluctuations were more likely to be located away from the cell periphery and a population of peripheral tubules with no signs of active motion was found.

A novel universal algorithm for filament network tracing and cytoskeleton analysis

The rapid development of advanced microscopy techniques over recent decades has significantly increased the quality of imaging and our understanding of subcellular structures, such as the organization of the filaments of the cytoskeleton using fluorescence and electron microscopy. However, these recent improvements in imaging techniques have not been matched by similar development of techniques for computational analysis of the images of filament networks that can now be obtained. Hence, for a wide range of applications, reliable computational analysis of such two-dimensional methods remains challenging. Here, we present a new algorithm for tracing of filament networks. This software can extract many important parameters from grayscale images of filament networks, including the mesh hole size, and filament length and connectivity (also known as Coordination Number). In addition, the method allows sub-networks to be distinguished in two-dimensional images using intensity thresholding. We show that the algorithm can be used to analyze images of cytoskeleton networks obtained using different advanced microscopy methods. We have thus developed a new improved method for computational analysis of two-dimensional images of filamentous networks that has wide applications for existing imaging techniques. The algorithm is available as open-source software.

Flow coupling between active and passive fluids across water-oil interfaces

Active fluid droplets surrounded by oil can spontaneously develop circulatory flows. However, the dynamics of the surrounding oil and their influence on the active fluid remain poorly understood. To investigate interactions between the active fluid and the passive oil across their interface, kinesin-driven microtubule-based active fluid droplets were immersed in oil and compressed into a cylinder-like shape. The droplet geometry supported intradroplet circulatory flows, but the circulation was suppressed when the thickness of the oil layer surrounding the droplet decreased. Experiments with tracers and network structure analyses and continuum models based on the dynamics of self-elongating rods demonstrated that the flow transition resulted from flow coupling across the interface between active fluid and oil, with a millimeter-scale coupling length. In addition, two novel millifluidic devices were developed that could trigger and suppress intradroplet circulatory flows in real time: one by changing the thickness of the surrounding oil layer and the other by locally deforming the droplet. This work highlights the role of interfacial dynamics in the active fluid droplet system and shows that circulatory flows within droplets can be affected by millimeter-scale flow coupling across the interface between the active fluid and the oil.

Automated and semi-automated enhancement, segmentation and tracing of cytoskeletal networks in microscopic images: A review

Cytoskeletal filaments are structures of utmost importance to biological cells and organisms due to their versatility and the significant functions they perform. These biopolymers are most often organised into network-like scaffolds with a complex morphology. Understanding the geometrical and topological organisation of these networks provides key insights into their functional roles. However, this non-trivial task requires a combination of high-resolution microscopy and sophisticated image processing/analysis software. The correct analysis of the network structure and connectivity needs precise segmentation of microscopic images. While segmentation of filament-like objects is a well-studied concept in biomedical imaging, where tracing of neurons and blood vessels is routine, there are comparatively fewer studies focusing on the segmentation of cytoskeletal filaments and networks from microscopic images. The developments in the fields of microscopy, computer vision and deep learning, however, began to facilitate the task, as reflected by an increase in the recent literature on the topic. Here, we aim to provide a short summary of the research on the (semi-)automated enhancement, segmentation and tracing methods that are particularly designed and developed for microscopic images of cytoskeletal networks. In addition to providing an overview of the conventional methods, we cover the recently introduced, deep-learning-assisted methods alongside the advantages they offer over classical methods.

Reconstitution of contractile actomyosin rings in vesicles

One of the grand challenges of bottom-up synthetic biology is the development of minimal machineries for cell division. The mechanical transformation of large-scale compartments, such as Giant Unilamellar Vesicles (GUVs), requires the geometry-specific coordination of active elements, several orders of magnitude larger than the molecular scale. Of all cytoskeletal structures, large-scale actomyosin rings appear to be the most promising cellular elements to accomplish this task. Here, we have adopted advanced encapsulation methods to study bundled actin filaments in GUVs and compare our results with theoretical modeling. By changing few key parameters, actin polymerization can be differentiated to resemble various types of networks in living cells. Importantly, we find membrane binding to be crucial for the robust condensation into a single actin ring in spherical vesicles, as predicted by theoretical considerations. Upon force generation by ATP-driven myosin motors, these ring-like actin structures contract and locally constrict the vesicle, forming furrow-like deformations. On the other hand, cortex-like actin networks are shown to induce and stabilize deformations from spherical shapes.

Cytoskeletal networks support and direct cell shape and guide intercellular transport, but relatively little is understood about the self-organization of cytoskeletal components on the scale of an entire cell. Here, authors use an in vitro system and observe the assembly of different types of actin networks and the condensation of membrane-bound actin into single rings.

Bil2 Is a Novel Inhibitor of the Yeast Formin Bnr1 Required for Proper Actin Cable Organization and Polarized Secretion

Cell growth in budding yeast depends on rapid and on-going assembly and turnover of polarized actin cables, which direct intracellular transport of post-Golgi vesicles to the bud tip. Saccharomyces cerevisiae actin cables are polymerized by two formins, Bni1 and Bnr1. Bni1 assembles cables in the bud, while Bnr1 is anchored to the bud neck and assembles cables that specifically extend filling the mother cell. Here, we report a formin regulatory role for YGL015c, a previously uncharacterized open reading frame, which we have named Bud6 Interacting Ligand 2 (BIL2). bil2Δ cells display defects in actin cable architecture and partially-impaired secretory vesicle transport. Bil2 inhibits Bnr1-mediated actin filament nucleation in vitro, yet has no effect on the rate of Bnr1-mediated filament elongation. This activity profile for Bil2 resembles that of another yeast formin regulator, the F-BAR protein Hof1, and we find that bil2Δ with hof1Δ are synthetic lethal. Unlike Hof1, which localizes exclusively to the bud neck, GFP-Bil2 localizes to the cytosol, secretory vesicles, and sites of polarized cell growth. Further, we provide evidence that Hof1 and Bil2 inhibitory effects on Bnr1 are overcome by distinct mechanisms. Together, our results suggest that Bil2 and Hof1 perform distinct yet genetically complementary roles in inhibiting the actin nucleation activity of Bnr1 to control actin cable assembly and polarized secretion.

Confinement Geometry Tunes Fascin-Actin Bundle Structures and Consequently the Shape of a Lipid Bilayer Vesicle

Depending on the physical and biochemical properties of actin-binding proteins, actin networks form different types of membrane protrusions at the cell periphery. Actin crosslinkers, which facilitate the interaction of actin filaments with one another, are pivotal in determining the mechanical properties and protrusive behavior of actin networks. Short crosslinkers such as fascin bundle F-actin to form rigid spiky filopodial protrusions. By encapsulation of fascin and actin in giant unilamellar vesicles (GUVs), we show that fascin-actin bundles cause various GUV shape changes by forming bundle networks or straight single bundles depending on GUV size and fascin concentration. We also show that the presence of a long crosslinker, α-actinin, impacts fascin-induced GUV shape changes and significantly impairs the formation of filopodia-like protrusions. Actin bundle-induced GUV shape changes are confirmed by light-induced disassembly of actin bundles leading to the reversal of GUV shape. Our study contributes to advancing the design of shape-changing minimal cells for better characterization of the interaction between lipid bilayer membranes and actin cytoskeleton.

QUANTIFYING ACTIN FILAMENTS IN MICROSCOPIC IMAGES USING KEYPOINT DETECTION TECHNIQUES AND A FAST MARCHING ALGORITHM

The actin filament plays a fundamental role in numerous cellular processes such as cell growth, proliferation, migration, division, and locomotion. The actin cytoskeleton is highly dynamical and can polymerize and depolymerize in a very short time under different stimuli. To study the mechanics of actin filament, quantifying the length and number of actin filaments in each time frame of microscopic images is fundamental. In this paper, we adopt a Convolutional Neural Network (CNN) to segment actin filaments first, and then we utilize a modified Resnet to detect junctions and endpoints of filaments. With binary segmentation and detected keypoints, we apply a fast marching algorithm to obtain the number and length of each actin filament in microscopic images. We have also collected a dataset of 10 microscopic images of actin filaments to test our method. Our experiments show that our approach outperforms other existing approaches tackling this problem regarding both accuracy and inference time.

A septin-Hof1 scaffold at the yeast bud neck binds and organizes actin cables

Cellular actin arrays are often highly organized, with characteristic patterns critical to their in vivo functions, yet the mechanisms for establishing these higher order geometries remain poorly understood. In Saccharomyces cerevisiae, formin-polymerized actin cables are spatially organized and aligned along the mother–bud axis to facilitate polarized vesicle traffic. Here, we show that the bud neck–associated F-BAR protein Hof1, independent of its functions in regulating the formin Bnr1, binds to actin filaments and organizes actin cables in vivo. Hof1 bundles actin filaments and links them to septins in vitro. F-actin binding is mediated by the “linker” domain of Hof1, and its deletion leads to cable organization defects in vivo. Using superresolution imaging, we show that Hof1 and septins are patterned at the bud neck into evenly spaced axial pillars (∼200 nm apart), from which actin cables emerge and grow into the mother cell. These results suggest that Hof1, while bound to septins at the bud neck, not only regulates Bnr1 activity, but also binds to actin cables and aligns them along the mother–bud axis. More broadly, these findings provide a strong example of how an actin regulatory protein can be spatially patterned at the cell cortex to govern actin network geometry.

Three-Dimensional Printing and Electrospinning Dual-Scale Polycaprolactone Scaffolds with Low-Density and Oriented Fibers to Promote Cell Alignment

Complex and hierarchically functionalized scaffolds composed of micro- and nanoscale structures are a key goal in tissue engineering. The combination of three-dimensional (3D) printing and electrospinning enables the fabrication of these multiscale structures. This study presents a polycaprolactone 3D-printed and electrospun scaffold with multiple mesh layers and fiber densities. The results show successful fabrication of a dual-scale scaffold with the 3D-printed scaffold acting as a gap collector with the printed microfibers as the electrodes and the pores a series of insulating gaps resulting in aligned nanofibers. The electrospun fibers are highly aligned perpendicular to the direction of the printed fiber and form aligned meshes within the pores of the scaffold. Mechanical testing showed no significant difference between the number of mesh layers whereas the hydrophobicity of the scaffold increased with increasing fiber density. Biological results indicate that increasing the number of mesh layers improves cell proliferation, migration, and adhesion. The aligned nanofibers within the microscale pores allowed enhanced cell bridging and cell alignment that was not observed in the 3D-printed only scaffold. These results demonstrate a facile method of incorporating low-density and aligned fibers within a 3D-printed scaffold that is a promising development in multiscale hierarchical scaffolds where alignment of cells can be desirable.

Intersection To Overpass: Instance Segmentation On Filamentous Structures With An Orientation-Aware Neural Network And Terminus Pairing Algorithm

Filamentous structures play an important role in biological systems. Extracting individual filaments is fundamental for analyzing and quantifying related biological processes. However, segmenting filamentous structures at an instance level is hampered by their complex architecture, uniform appearance, and image quality. In this paper, we introduce an orientation-aware neural network, which contains six orientation-associated branches. Each branch detects filaments with specific range of orientations, thus separating them at junctions, and turning intersections to overpasses. A terminus pairing algorithm is also proposed to regroup filaments from different branches, and achieve individual filaments extraction. We create a synthetic dataset to train our network, and annotate real full resolution microscopy images of microtubules to test our approach. Our experiments have shown that our proposed method outperforms most existing approaches for filaments extraction. We also show that our approach works on other similar structures with a road network dataset.

Progress and Opportunities in the Characterization of Cellulose - An Important Regulator of Cell Wall Growth and Mechanics

The plant cell wall is a dynamic network of several biopolymers and structural proteins including cellulose, pectin, hemicellulose and lignin. Cellulose is one of the main load bearing components of this complex, heterogeneous structure, and in this way, is an important regulator of cell wall growth and mechanics. Glucan chains of cellulose aggregate via hydrogen bonds and van der Waals forces to form long thread-like crystalline structures called cellulose microfibrils. The shape, size, and crystallinity of these microfibrils are important structural parameters that influence mechanical properties of the cell wall and these parameters are likely important determinants of cell wall digestibility for biofuel conversion. Cellulose-cellulose and cellulose-matrix interactions also contribute to the regulation of the mechanics and growth of the cell wall. As a consequence, much emphasis has been placed on extracting valuable structural details about cell wall components from several techniques, either individually or in combination, including diffraction/scattering, microscopy, and spectroscopy. In this review, we describe efforts to characterize the organization of cellulose in plant cell walls. X-ray scattering reveals the size and orientation of microfibrils; diffraction reveals unit lattice parameters and crystallinity. The presence of different cell wall components, their physical and chemical states, and their alignment and orientation have been identified by Infrared, Raman, Nuclear Magnetic Resonance, and Sum Frequency Generation spectroscopy. Direct visualization of cell wall components, their network-like structure, and interactions between different components has also been made possible through a host of microscopic imaging techniques including scanning electron microscopy, transmission electron microscopy, and atomic force microscopy. This review highlights advantages and limitations of different analytical techniques for characterizing cellulose structure and its interaction with other wall polymers. We also delineate emerging opportunities for future developments of structural characterization tools and multi-modal analyses of cellulose and plant cell walls. Ultimately, elucidation of the structure of plant cell walls across multiple length scales will be imperative for establishing structure-property relationships to link cell wall structure to control of growth and mechanics.

Automated Tracking of Biopolymer Growth and Network Deformation with TSOAX

Studies of how individual semi-flexible biopolymers and their network assemblies change over time reveal dynamical and mechanical properties important to the understanding of their function in tissues and living cells. Automatic tracking of biopolymer networks from fluorescence microscopy time-lapse sequences facilitates such quantitative studies. We present an open source software tool that combines a global and local correspondence algorithm to track biopolymer networks in 2D and 3D, using stretching open active contours. We demonstrate its application in fully automated tracking of elongating and intersecting actin filaments, detection of loop formation and constriction of tilted contractile rings in live cells, and tracking of network deformation under shear deformation.

Interactions of tropomyosin Tpm1.1 on a single actin filament: A method for extraction and processing of high resolution TIRF microscopy data

Skeletal muscle tropomyosin (Tpm1.1) is an elongated, rod-shaped, alpha-helical coiled-coil protein that forms continuous head-to-tail polymers along both sides of the actin filament. In this study we use single molecule fluorescence TIRF microscopy combined with a microfluidic device and fluorescently labelled proteins to measure Tpm1.1 association to and dissociation from single actin filaments. Our experimental setup allows us to clearly resolve Tpm1.1 interactions on both sides of the filaments. Here we provide a semi-automated method for the extraction and quantification of kymograph data for individual actin filaments bound at different Tpm1.1 concentrations. We determine boundaries on the kymograph on each side of the actin filament, based on intensity thresholding, performing fine manual editing of the boundaries (if needed) and extracting user defined kinetic properties of the system. Using our analytical tools we can determine (i) nucleation point(s) and rates, (ii) elongation rates of Tpm1.1, (iii) identify meeting points after the saturation of filament, and when dissociation occurs, (iv) initiation point(s), (v) the final dissociation point(s), as well as (vi) dissociation rates.

All of these measurements can be extracted from both sides of the filament, allowing for the determination of possible differences in behaviour on the two sides of the filament, and across concentrations. The robust and repeatable nature of the method allows quantitative, semi-automated analyses to be made of large studies of acto-tropomyosin interactions, as well as for other actin binding proteins or filamentous structures, opening the way for dissection of the dynamics underlying these interactions.

Light-Induced Printing of Protein Structures on Membranes in Vitro

Reconstituting functional modules of biological systems in vitro is an important yet challenging goal of bottom-up synthetic biology, in particular with respect to their precise spatiotemporal regulation. One of the most desirable external control parameters for the engineering of biological systems is visible light, owing to its specificity and ease of defined application in space and time. Here we engineered the PhyB-PIF6 system to spatiotemporally target proteins by light onto model membranes and thus sequentially guide protein pattern formation and structural assembly in vitro from the bottom up. We show that complex micrometer-sized protein patterns can be printed on time scales of seconds, and the pattern density can be precisely controlled by protein concentration, laser power, and activation time. Moreover, when printing self-assembling proteins such as the bacterial cytoskeleton protein FtsZ, the targeted assembly into filaments and large-scale structures such as artificial rings can be accomplished. Thus, light mediated sequential protein assembly in cell-free systems represents a promising approach to hierarchically building up the next level of complexity toward a minimal cell.

Architectural Dynamics of CaMKII-Actin Networks

Calcium-calmodulin-dependent kinase II (CaMKII) has an important role in dendritic spine remodeling upon synaptic stimulation. Using fluorescence video microscopy and image analysis, we investigated the architectural dynamics of rhodamine-phalloidin stabilized filamentous actin (F-actin) networks cross-linked by CaMKII. We used automated image analysis to identify F-actin bundles and crossover junctions and developed a dimensionless metric to characterize network architecture. Similar networks were formed by three different CaMKII species with a 10-fold length difference in the linker region between the kinase domain and holoenzyme hub, implying linker length is not a primary determinant of F-actin cross-linking. Electron micrographs showed that at physiological molar ratios, single CaMKII holoenzymes cross-linked multiple F-actin filaments at random, whereas at higher CaMKII/F-actin ratios, filaments bundled. Light microscopy established that the random network architecture resisted macromolecular crowding with polyethylene glycol and blocked ATP-powered compaction by myosin-II miniature filaments. Importantly, the networks disassembled after the addition of calcium-calmodulin and were then spaced within 3 min into compacted foci by myosin motors or more slowly (30 min) aggregated by crowding. Single-molecule total internal reflection fluorescence microscopy showed CaMKII dissociation from surface-immobilized globular actin exhibited a monoexponential dwell-time distribution, whereas CaMKII bound to F-actin networks had a long-lived fraction, trapped at crossover junctions. Release of CaMKII from F-actin, triggered by calcium-calmodulin, was too rapid to measure with flow-cell exchange (<20 s). The residual bound fraction was reduced substantially upon addition of an N-methyl-D-aspartate receptor peptide analog but not ATP. These results provide mechanistic insights to CaMKII-actin interactions at the collective network and single-molecule level. Our findings argue that CaMKII-actin networks in dendritic spines maintain spine size against physical stress. Upon synaptic stimulation, CaMKII is disengaged by calcium-calmodulin, triggering network disassembly, expansion, and subsequent compaction by myosin motors with kinetics compatible with the times recorded for the poststimulus changes in spine volume.

Direct induction of microtubule branching by microtubule nucleation factor SSNA1

Microtubules are central elements of the eukaryotic cytoskeleton that often function as part of branched networks. Current models for branching include nucleation of new microtubules from severed microtubule seeds or from gamma-tubulin recruited to the side of a pre-existing microtubule. Here, we found that microtubules can be directly remodeled into branched structures by the microtubule-remodeling factor SSNA1 (or also NA14/DIP13). The branching activity of SSNA1 relies on its ability to self-assemble into fibrils in a head-to-tail fashion. SSNA1 fibrils guide protofilaments of a microtubule to split apart to form daughter microtubules. We further found that SSNA1 localizes at axon branching sites and has a key role in neuronal development. SSNA1 mutants that abolish microtubule branching in vitro also fail to promote axon development and branching when overexpressed in neurons. We have therefore, discovered a mechanism for microtubule-branching and implicated its role in neuronal development.

Quantitative analysis of cell shape and the cytoskeleton in developmental biology

Computational approaches that enable quantification of microscopy data have revolutionized the field of developmental biology. Due to its inherent complexity, elucidating mechanisms of development requires sophisticated analysis of the structure, shape, and kinetics of cellular processes. This need has prompted the creation of numerous techniques to visualize, quantify, and merge microscopy data. These approaches have defined the order and structure of developmental events, thus, providing insight into the mechanisms that drive them. This review describes current computational approaches that are being used to answer developmental questions related to morphogenesis and describe how these approaches have impacted the field. Our intent is not to comprehensively review techniques, but to highlight examples of how different approaches have impacted our understanding of development. Specifically, we focus on methods to quantify cell shape and cytoskeleton structure and dynamics in developing tissues. Finally, we speculate on where the future of computational analysis in developmental biology might be headed. This article is categorized under: Technologies > Analysis of Cell, Tissue, and Animal Phenotypes Early Embryonic Development > Gastrulation and Neurulation Early Embryonic Development > Development to the Basic Body Plan.

Resonant soft X-ray scattering reveals cellulose microfibril spacing in plant primary cell walls

Cellulose microfibrils are crucial for many of the remarkable mechanical properties of primary cell walls. Nevertheless, many structural features of cellulose microfibril organization in cell walls are not yet fully described. Microscopy techniques provide direct visualization of cell wall organization, and quantification of some aspects of wall microstructure is possible through image processing. Complementary to microscopy techniques, scattering yields structural information in reciprocal space over large sample areas. Using the onion epidermal wall as a model system, we introduce resonant soft X-ray scattering (RSoXS) to directly quantify the average interfibril spacing. Tuning the X-ray energy to the calcium L-edge enhances the contrast between cellulose and pectin due to the localization of calcium ions to homogalacturonan in the pectin matrix. As a consequence, RSoXS profiles reveal an average center-to-center distance between cellulose microfibrils or microfibril bundles of about 20 nm.

Integrated control of formin-mediated actin assembly by a stationary inhibitor and a mobile activator

This study shows that in vivo actin nucleation by the yeast formin Bnr1 is controlled through the coordinated effects of two distinct regulators, a stationary inhibitor (the F-BAR protein Hof1) and a mobile activator (Bud6), establishing a positive feedback loop for precise spatial and temporal control of actin assembly.

Formins are essential actin assembly factors whose activities are controlled by a diverse array of binding partners. Until now, most formin ligands have been studied on an individual basis, leaving open the question of how multiple inputs are integrated to regulate formins in vivo. Here, we show that the F-BAR domain of Saccharomyces cerevisiae Hof1 interacts with the FH2 domain of the formin Bnr1 and blocks actin nucleation. Electron microscopy of the Hof1–Bnr1 complex reveals a novel dumbbell-shaped structure, with the tips of the F-BAR holding two FH2 dimers apart. Deletion of Hof1’s F-BAR domain in vivo results in disorganized actin cables and secretory defects. The formin-binding protein Bud6 strongly alleviates Hof1 inhibition in vitro, and bud6Δ suppresses hof1Δ defects in vivo. Whereas Hof1 stably resides at the bud neck, we show that Bud6 is delivered to the neck on secretory vesicles. We propose that Hof1 and Bud6 functions are intertwined as a stationary inhibitor and a mobile activator, respectively.

The Role of Network Architecture in Collagen Mechanics

Collagen forms fibrous networks that reinforce tissues and provide an extracellular matrix for cells. These networks exhibit remarkable strain-stiffening properties that tailor the mechanical functions of tissues and regulate cell behavior. Recent models explain this nonlinear behavior as an intrinsic feature of disordered networks of stiff fibers. Here, we experimentally validate this theoretical framework by measuring the elastic properties of collagen networks over a wide range of self-assembly conditions. We show that the model allows us to quantitatively relate both the linear and nonlinear elastic behavior of collagen networks to their underlying architecture. Specifically, we identify the local coordination number (or connectivity) 〈z〉 as a key architectural parameter that governs the elastic response of collagen. The network elastic response reveals that 〈z〉 decreases from 3.5 to 3 as the polymerization temperature is raised from 26 to 37°C while being weakly dependent on concentration. We furthermore infer a Young's modulus of 1.1 MPa for the collagen fibrils from the linear modulus. Scanning electron microscopy confirms that 〈z〉 is between three and four but is unable to detect the subtle changes in 〈z〉 with polymerization conditions that rheology is sensitive to. Finally, we show that, consistent with the model, the initial stress-stiffening response of collagen networks is controlled by the negative normal stress that builds up under shear. Our work provides a predictive framework to facilitate future studies of the regulatory effect of extracellular matrix molecules on collagen mechanics. Moreover, our findings can aid mechanobiological studies of wound healing, fibrosis, and cancer metastasis, which require collagen matrices with tunable mechanical properties.

Computational 3D imaging to quantify structural components and assembly of protein networks

Traditionally, protein structures have been described by the secondary structure architecture and fold arrangement. However, the relatively novel method of 3D confocal microscopy of fluorescent-protein-tagged networks in living cells allows resolving the detailed spatial organization of these networks. This provides new possibilities to predict network functionality, as structure and function seem to be linked at various scales. Here, we propose a quantitative approach using 3D confocal microscopy image data to describe protein networks based on their nano-structural characteristics. This analysis is constructed in four steps: (i) Segmentation of the microscopic raw data into a volume model and extraction of a spatial graph representing the protein network. (ii) Quantifying protein network gross morphology using the volume model. (iii) Quantifying protein network components using the spatial graph. (iv) Linking these two scales to obtain insights into network assembly. Here, we quantitatively describe the filamentous temperature sensitive Z protein network of the moss Physcomitrella patens and elucidate relations between network size and assembly details. Future applications will link network structure and functionality by tracking dynamic structural changes over time and comparing different states or types of networks, possibly allowing more precise identification of (mal) functions or the design of protein-engineered biomaterials for applications in regenerative medicine.

STATEMENT OF SIGNIFICANCE

Protein networks are highly complex and dynamic structures that play various roles in biological environments. Analyzing the detailed spatial structure of these networks may lead to new insight into biological functions and malfunctions. Here, we propose a tool set that extracts structural information at two scales of the protein network and allows therefore to address questions such as "how is the network built?" or "how networks grow?".

Stromule extension along microtubules coordinated with actin-mediated anchoring guides perinuclear chloroplast movement during innate immunity

Dynamic tubular extensions from chloroplasts called stromules have recently been shown to connect with nuclei and function during innate immunity. We demonstrate that stromules extend along microtubules (MTs) and MT organization directly affects stromule dynamics since stabilization of MTs chemically or genetically increases stromule numbers and length. Although actin filaments (AFs) are not required for stromule extension, they provide anchor points for stromules. Interestingly, there is a strong correlation between the direction of stromules from chloroplasts and the direction of chloroplast movement. Stromule-directed chloroplast movement was observed in steady-state conditions without immune induction, suggesting it is a general function of stromules in epidermal cells. Our results show that MTs and AFs may facilitate perinuclear clustering of chloroplasts during an innate immune response. We propose a model in which stromules extend along MTs and connect to AF anchor points surrounding nuclei, facilitating stromule-directed movement of chloroplasts to nuclei during innate immunity.

Transition from turbulent to coherent flows in confined three-dimensional active fluids

Transport of fluid through a pipe is essential for the operation of macroscale machines and microfluidic devices. Conventional fluids only flow in response to external pressure. We demonstrate that an active isotropic fluid, composed of microtubules and molecular motors, autonomously flows through meter-long three-dimensional channels. We establish control over the magnitude, velocity profile, and direction of the self-organized flows and correlate these to the structure of the extensile microtubule bundles. The inherently three-dimensional transition from bulk-turbulent to confined-coherent flows occurs concomitantly with a transition in the bundle orientational order near the surface and is controlled by a scale-invariant criterion related to the channel profile. The nonequilibrium transition of confined isotropic active fluids can be used to engineer self-organized soft machines.

Resliced image space construction for coronary artery collagen fibers

Collagen fibers play an important role in the biomechanics of the blood vessel wall. The objective of this study was to determine the 3D microstructure of collagen fibers in the media and adventitia of coronary arteries. We present a novel optimal angle consistence algorithm to reform image slices in the visualization and analysis of 3D collagen images. 3D geometry was reconstructed from resliced image space where the 3D skeleton was extracted as the primary feature for accurate reconstruction of geometrical parameters. Collagen fibers (range 80–200) were reconstructed from the porcine coronary artery wall for the measurement of various morphological parameters. Collagen waviness and diameters were 1.37 ± 0.19 and 2.61 ± 0.89 μm, respectively. The biaxial distributions of orientation had two different peaks at 110.7 ± 25.2° and 18.4 ± 19.3°. Results for width, waviness, and orientation were found to be in good agreement with manual measurements. In addition to accurately measuring 2D features more efficiently than the manual approach, the present method produced 3D features that could not be measured in the 2D manual approach. These additional parameters included the tilt angle (5.10 ± 2.95°) and cross-sectional area (CSA; 5.98 ± 3.79 μm²) of collagen fibers. These 3D collagen reconstructions provide accurate and reliable microstructure for biomechanical modeling of vessel wall mechanics.