Characterisation and correction of polarisation effects in fluorescently labelled fibres.

Many biological structures take the form of fibres and filaments, and quantitative analysis of fibre organisation is important for understanding their functions in both normal physiological conditions and disease. In order to visualise these structures, fibres can be fluorescently labelled and imaged, with specialised image analysis methods available for quantifying the degree and strength of fibre alignment. Here we show that fluorescently labelled fibres can display polarised emission, with the strength of this effect varying depending on structure and fluorophore identity. This can bias automated analysis of fibre alignment and mask the true underlying structural organisation. We present a method for quantifying and correcting these polarisation effects without requiring polarisation-resolved microscopy and demonstrate its efficacy when applied to images of fluorescently labelled collagen gels, allowing for more reliable characterisation of fibre microarchitecture.

Imaging actin organisation and dynamics in 3D.

The actin cytoskeleton plays a critical role in cell architecture and the control of fundamental processes including cell division, migration and survival. The dynamics and organisation of F-actin have been widely studied in a breadth of cell types on classical two-dimensional (2D) surfaces. Recent advances in optical microscopy have enabled interrogation of these cytoskeletal networks in cells within three-dimensional (3D) scaffolds, tissues and in vivo. Emerging studies indicate that the dimensionality experienced by cells has a profound impact on the structure and function of the cytoskeleton, with cells in 3D environments exhibiting cytoskeletal arrangements that differ to cells in 2D environments. However, the addition of a third (and fourth, with time) dimension leads to challenges in sample preparation, imaging and analysis, necessitating additional considerations to achieve the required signal-to-noise ratio and spatial and temporal resolution. Here, we summarise the current tools for imaging actin in a 3D context and highlight examples of the importance of this in understanding cytoskeletal biology and the challenges and opportunities in this domain.

Extracellular matrix stiffness activates mechanosensitive signals but limits breast cancer cell spheroid proliferation and invasion.

Breast cancer is characterized by physical changes that occur in the tumor microenvironment throughout growth and metastasis of tumors. Extracellular matrix stiffness increases as tumors develop and spread, with stiffer environments thought to correlate with poorer disease prognosis. Changes in extracellular stiffness and other physical characteristics are sensed by integrins which integrate these extracellular cues to intracellular signaling, resulting in modulation of proliferation and invasion. However, the co-ordination of mechano-sensitive signaling with functional changes to groups of tumor cells within 3-dimensional environments remains poorly understood. Here we provide evidence that increasing the stiffness of collagen scaffolds results in increased activation of ERK1/2 and YAP in human breast cancer cell spheroids. We also show that ERK1/2 acts upstream of YAP activation in this context. We further demonstrate that YAP, matrix metalloproteinases and actomyosin contractility are required for collagen remodeling, proliferation and invasion in lower stiffness scaffolds. However, the increased activation of these proteins in higher stiffness 3-dimensional collagen gels is correlated with reduced proliferation and reduced invasion of cancer cell spheroids. Our data collectively provide evidence that higher stiffness 3-dimensional environments induce mechano-signaling but contrary to evidence from 2-dimensional studies, this is not sufficient to promote pro-tumorigenic effects in breast cancer cell spheroids.

Autocrine IL-6 drives cell and extracellular matrix anisotropy in scar fibroblasts.

Fibrosis is associated with dramatic changes in extracellular matrix (ECM) architecture of unknown etiology. Here we exploit keloid scars as a paradigm to understand fibrotic ECM organization. We reveal that keloid patient fibroblasts uniquely produce a globally aligned ECM network in 2-D culture as observed in scar tissue. ECM anisotropy develops after rapid initiation of a fibroblast supracellular actin network, suggesting that cell alignment initiates ECM patterning. Keloid fibroblasts produce elevated levels of IL-6, and autocrine IL-6 production is both necessary and sufficient to induce cell and ECM alignment, as evidenced by ligand stimulation of normal dermal fibroblasts and treatment of keloid fibroblasts with the function blocking IL-6 receptor monoclonal antibody, tocilizumab. Downstream of IL-6, supracellular organization of keloid fibroblasts is controlled by activation of cell-cell adhesion. Adhesion formation inhibits contact-induced cellular overlap leading to nematic organization of cells and an alignment of focal adhesions. Keloid fibroblasts placed on isotropic ECM align the pre-existing matrix, suggesting that focal adhesion alignment leads to active anisotropic remodeling. These results show that IL-6-induced fibroblast cooperativity can control the development of a nematic ECM, highlighting both IL-6 signaling and cell-cell adhesions as potential therapeutic targets to inhibit this common feature of fibrosis.

Bridging imaging users to imaging analysis - A community survey.

The 'Bridging Imaging Users to Imaging Analysis' survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), BioImaging North America (BINA) and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multichoice and open-ended questions, the survey inquired about demographics, image analysis experiences, future needs and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross-community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents' overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user-friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarise themselves with the fundamentals of image analysis, provide constant feedback and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for 'written tutorials' to acquire knowledge on image analysis. We also observed that the interest in having 'office hours' to get an expert opinion on their image analysis methods has increased over the years. The results also showed less-than-expected usage of online discussion forums in the imaging community for solving image analysis problems. Surprisingly, we also observed a decreased interest among the survey respondents in deep/machine learning despite the increasing adoption of artificial intelligence in biology. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly.

Bridging Imaging Users to Imaging Analysis - A community survey.

The "Bridging Imaging Users to Imaging Analysis" survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), Bioimaging North America (BINA), and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multi-choice and open-ended questions, the survey inquired about demographics, image analysis experiences, future needs, and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross-community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents' overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user-friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarize themselves with the fundamentals of image analysis, provide constant feedback, and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for 'written tutorials' to acquire knowledge on image analysis. We also observed that the interest in having 'office hours' to get an expert opinion on their image analysis methods has increased over the years. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly.

Extracellular matrix assembly stress initiates Drosophila central nervous system morphogenesis.

Forces controlling tissue morphogenesis are attributed to cellular-driven activities, and any role for extracellular matrix (ECM) is assumed to be passive. However, all polymer networks, including ECM, can develop autonomous stresses during their assembly. Here, we examine the morphogenetic function of an ECM before reaching homeostatic equilibrium by analyzing de novo ECM assembly during Drosophila ventral nerve cord (VNC) condensation. Asymmetric VNC shortening and a rapid decrease in surface area correlate with the exponential assembly of collagen IV (Col4) surrounding the tissue. Concomitantly, a transient developmentally induced Col4 gradient leads to coherent long-range flow of ECM, which equilibrates the Col4 network. Finite element analysis and perturbation of Col4 network formation through the generation of dominant Col4 mutations that affect assembly reveal that VNC morphodynamics is partially driven by a sudden increase in ECM-driven surface tension. These data suggest that ECM assembly stress and associated network instabilities can actively participate in tissue morphogenesis.

A method for reproducible high-resolution imaging of 3D cancer cell spheroids.

Multicellular tumour cell spheroids embedded within three-dimensional (3D) hydrogels or extracellular matrices (ECM) are widely used as models to study cancer growth and invasion. Standard methods to embed spheroids in 3D matrices result in random placement in space which limits the use of inverted fluorescence microscopy techniques, and thus the resolution that can be achieved to image molecular detail within the intact spheroid. Here, we leverage UV photolithography to microfabricate PDMS (polydimethylsiloxane) stamps that allow for generation of high-content, reproducible well-like structures in multiple different imaging chambers. Addition of multicellular tumour spheroids into stamped collagen structures allows for precise positioning of spheroids in 3D space for reproducible high-/super-resolution imaging. Embedded spheroids can be imaged live or fixed and are amenable to immunostaining, allowing for greater flexibility of experimental approaches. We describe the use of these spheroid imaging chambers to analyse cell invasion, cell-ECM interaction, ECM alignment, force-dependent intracellular protein dynamics and extension of fine actin-based protrusions with a variety of commonly used inverted microscope platforms. This method enables reproducible, high-/super-resolution live imaging of multiple tumour spheroids, that can be potentially extended to visualise organoids and other more complex 3D in vitro systems.

GliaMorph: a modular image analysis toolkit to quantify Müller glial cell morphology.

Cell morphology is crucial for all cell functions. This is particularly true for glial cells as they rely on complex shape to contact and support neurons. However, methods to quantify complex glial cell shape accurately and reproducibly are lacking. To address this, we developed the image analysis pipeline 'GliaMorph'. GliaMorph is a modular analysis toolkit developed to perform (1) image pre-processing, (2) semi-automatic region-of-interest selection, (3) apicobasal texture analysis, (4) glia segmentation, and (5) cell feature quantification. Müller glia (MG) have a stereotypic shape linked to their maturation and physiological status. Here, we characterized MG on three levels: (1) global image-level, (2) apicobasal texture, and (3) regional apicobasal vertical-to-horizontal alignment. Using GliaMorph, we quantified MG development on a global and single-cell level, showing increased feature elaboration and subcellular morphological rearrangement in the zebrafish retina. As proof of principle, we analysed expression changes in a mouse glaucoma model, identifying subcellular protein localization changes in MG. Together, these data demonstrate that GliaMorph enables an in-depth understanding of MG morphology in the developing and diseased retina.

The glycocalyx affects the mechanotransductive perception of the topographical microenvironment.

The cell/microenvironment interface is the starting point of integrin-mediated mechanotransduction, but many details of mechanotransductive signal integration remain elusive due to the complexity of the involved (extra)cellular structures, such as the glycocalyx. We used nano-bio-interfaces reproducing the complex nanotopographical features of the extracellular matrix to analyse the glycocalyx impact on PC12 cell mechanosensing at the nanoscale (e.g., by force spectroscopy with functionalised probes). Our data demonstrates that the glycocalyx configuration affects spatio-temporal nanotopography-sensitive mechanotransductive events at the cell/microenvironment interface. Opposing effects of major glycocalyx removal were observed, when comparing flat and specific nanotopographical conditions. The excessive retrograde actin flow speed and force loading are strongly reduced on certain nanotopographies upon strong reduction of the native glycocalyx, while on the flat substrate we observe the opposite trend. Our results highlight the importance of the glycocalyx configuration in a molecular clutch force loading-dependent cellular mechanism for mechanosensing of microenvironmental nanotopographical features.

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.

Nance-Horan Syndrome-like 1 protein negatively regulates Scar/WAVE-Arp2/3 activity and inhibits lamellipodia stability and cell migration.

Cell migration is important for development and its aberrant regulation contributes to many diseases. The Scar/WAVE complex is essential for Arp2/3 mediated lamellipodia formation during mesenchymal cell migration and several coinciding signals activate it. However, so far, no direct negative regulators are known. Here we identify Nance-Horan Syndrome-like 1 protein (NHSL1) as a direct binding partner of the Scar/WAVE complex, which co-localise at protruding lamellipodia. This interaction is mediated by the Abi SH3 domain and two binding sites in NHSL1. Furthermore, active Rac binds to NHSL1 at two regions that mediate leading edge targeting of NHSL1. Surprisingly, NHSL1 inhibits cell migration through its interaction with the Scar/WAVE complex. Mechanistically, NHSL1 may reduce cell migration efficiency by impeding Arp2/3 activity, as measured in cells using a Arp2/3 FRET-FLIM biosensor, resulting in reduced F-actin density of lamellipodia, and consequently impairing the stability of lamellipodia protrusions.

Protocol for intervention-free quantification of protein turnover rate by steady-state modeling.

Protein turnover rate is difficult to obtain experimentally. This protocol shows how to mathematically model turnover rates in an intervention-free manner given the ability to quantify mRNA and protein expression from initiation to homeostasis. This approach can be used to calculate production and degradation rates and to infer protein half-life. This model was successfully employed to quantify turnover during Drosophila embryogenesis, and we hypothesize that it will be applicable to diverse in vivo or in vitro systems. For complete details on the use and execution of this protocol, please refer to Matsubayashi et al. (2020).

Rapid Homeostatic Turnover of Embryonic ECM during Tissue Morphogenesis.

The extracellular matrix (ECM) is a polymer network hypothesized to form a stable cellular scaffold. While the ECM can undergo acute remodeling during embryogenesis, it is experimentally difficult to determine whether basal turnover is also important. Most studies of homeostatic turnover assume an initial steady-state balance of production and degradation and measure half-life by quantifying the rate of decay after experimental intervention (e.g., pulse labeling). Here, we present an intervention-free approach to mathematically model basal ECM turnover during embryogenesis by exploiting our ability to live image de novo ECM development in Drosophila to quantify production from initiation to homeostasis. This reveals rapid turnover (half-life ∼7-10 h), which we confirmed by in vivo pulse-chase experiments. Moreover, ECM turnover is partially dependent on proteolysis and network interactions, and slowing turnover affects tissue morphogenesis. These data demonstrate that embryonic ECM undergoes constant replacement, which is likely necessary to maintain network plasticity to accommodate growth and morphogenesis.

Comparative Study of Contact Repulsion in Control and Mutant Macrophages Using a Novel Interaction Detection.

In this paper, a novel method for interaction detection is presented to compare the contact dynamics of macrophages in the Drosophila embryo. The study is carried out by a framework called macrosight, which analyses the movement and interaction of migrating macrophages. The framework incorporates a segmentation and tracking algorithm into analysing the motion characteristics of cells after contact. In this particular study, the interactions between cells is characterised in the case of control embryos and Shot mutants, a candidate protein that is hypothesised to regulate contact dynamics between migrating cells. Statistical significance between control and mutant cells was found when comparing the direction of motion after contact in specific conditions. Such discoveries provide insights for future developments in combining biological experiments with computational analysis.

Persistent and polarized global actin flow is essential for directionality during cell migration.

Cell migration is hypothesized to involve a cycle of behaviours beginning with leading edge extension. However, recent evidence suggests that the leading edge may be dispensable for migration, raising the question of what actually controls cell directionality. Here, we exploit the embryonic migration of Drosophila macrophages to bridge the different temporal scales of the behaviours controlling motility. This approach reveals that edge fluctuations during random motility are not persistent and are weakly correlated with motion. In contrast, flow of the actin network behind the leading edge is highly persistent. Quantification of actin flow structure during migration reveals a stable organization and asymmetry in the cell-wide flowfield that strongly correlates with cell directionality. This organization is regulated by a gradient of actin network compression and destruction, which is controlled by myosin contraction and cofilin-mediated disassembly. It is this stable actin-flow polarity, which integrates rapid fluctuations of the leading edge, that controls inherent cellular persistence.

Effect of cell sample size in atomic force microscopy nanoindentation.

Single-cell technologies are powerful tools to evaluate cell characteristics. In particular, Atomic Force Microscopy (AFM) nanoindentation experiments have been widely used to study single cell mechanical properties. One important aspect related to single cell techniques is the need for sufficient statistical power to obtain reliable results. This aspect is often overlooked in AFM experiments were sample sizes are arbitrarily set. The aim of the present work was to propose a tool for sample size estimation in the context of AFM nanoindentation experiments of single cell. To this aim, a retrospective approach was used by acquiring a large dataset of experimental measurements on four bone cell types and by building saturation curves for increasing sample sizes with a bootstrap resampling method. It was observed that the coefficient of variation (CV%) decayed with a function of the form y = axb with similar parameters for all samples tested and that sample sizes of 21 and 83 cells were needed for the specific cells and protocol employed if setting a maximum threshold on CV% of 10% or 5%, respectively. The developed tool is made available as an open-source repository and guidelines are provided for its use for AFM nanoindentation experimental design.

Hyaluronic acid selective anchoring to the cytoskeleton: An atomic force microscopy study.

The hyaluronic acid component of the glycocalyx plays a role in cell mechanotransduction by selectively transmitting mechanical signals to the cell cytoskeleton or to the cell membrane. The aim of this study was to evaluate the mechanical link between the hyaluronic acid molecule and the cell cytoskeleton by means of atomic force microscopy single molecule force spectroscopy. Hyaluronic acid molecules on live cells were targeted with probes coated with hyaluronic acid binding protein. Two different types of events were observed when the detachment of the target molecule from the probe occurred, suggesting the presence of cytoskeleton- and membrane-anchored molecules. Membrane-anchored molecules facilitated the formation of tethers when pulled. About 15% of the tested hyaluronic acid molecules were shown to be anchored to the cytoskeleton. When multiple molecules bonded to the probe, specific detachment patterns were observed, suggesting that a cytoskeletal bond needed to be broken to improve the ability to pull tethers from the cell membrane. This likely resulted in the formation of tethering structures maintaining a cytoskeletal core similar to the ones observed for cells over-expressing HA synthases. The different observed rupture events were associated with separate mechanotransductive mechanisms in an analogous manner to that previously proposed for the endothelial glycocalyx. Single cytoskeleton anchored rupture events represent HA molecules linked to the cytoskeleton and therefore transmitting mechanical stimuli into the inner cell compartments. Single membrane tethers would conversely represent the glycocalyx molecules connected to areas of the membrane where an abundance of signalling molecules reside.

An anatomy-based lumped parameter model of cerebrospinal venous circulation: can an extracranial anatomical change impact intracranial hemodynamics?

BACKGROUND: The relationship between extracranial venous system abnormalities and central nervous system disorders has been recently theorized. In this paper we delve into this hypothesis by modeling the venous drainage in brain and spinal column areas and simulating the intracranial flow changes due to extracranial morphological stenoses. METHODS: A lumped parameter model of the cerebro-spinal venous drainage was created based on anatomical knowledge and vessels diameters and lengths taken from literature. Each vein was modeled as a hydraulic resistance, calculated through Poiseuille's law. The inputs of the model were arterial flow rates of the intracranial, vertebral and lumbar districts. The effects of the obstruction of the main venous outflows were simulated. A database comprising 112 Multiple Sclerosis patients (Male/Female = 42/70; median age ± standard deviation = 43.7 ± 10.5 years) was retrospectively analyzed. RESULTS: The flow rate of the main veins estimated with the model was similar to the measures of 21 healthy controls (Male/Female = 10/11; mean age ± standard deviation = 31 ± 11 years), obtained with a 1.5 T Magnetic Resonance scanner. The intracranial reflux topography predicted with the model in cases of internal jugular vein diameter reduction was similar to those observed in the patients with internal jugular vein obstacles. CONCLUSIONS: The proposed model can predict physiological and pathological behaviors with good fidelity. Despite the simplifications introduced in cerebrospinal venous circulation modeling, the key anatomical feature of the lumped parameter model allowed for a detailed analysis of the consequences of extracranial venous impairments on intracranial pressure and hemodynamics.