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

Cell morphology is critical 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 (i) image pre-processing, (ii) semi-automatic region-of-interest (ROI) selection, (iii) apicobasal texture analysis, (iv) glia segmentation, and (v) cell feature quantification. Müller Glia (MG) have a stereotypic shape linked to their maturation and physiological status. We here characterized MG on three levels, including (a) global image-level, (b) apicobasal texture, and (c) 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, GliaMorph enables an in-depth understanding of MG morphology in the developing and diseased retina

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

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

Persistent and polarised 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

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.</p

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

Derivation and simulation of a computational model of active cell populations:How overlap avoidance, deformability, cell-cell junctions and cytoskeletal forces affect alignment

Collective alignment of cell populations is a commonly observed phenomena in biology. An important example are aligning fibroblasts in healthy or scar tissue. In this work we derive and simulate a mechanistic agent-based model of the collective behaviour of actively moving and interacting cells, with a focus on understanding collective alignment. The derivation strategy is based on energy minimisation. The model ingredients are motivated by data on the behaviour of different populations of aligning fibroblasts and include: Self-propulsion, overlap avoidance, deformability, cell-cell junctions and cytoskeletal forces. We find that there is an optimal ratio of self-propulsion speed and overlap avoidance that maximises collective alignment. Further we find that deformability aids alignment, and that cell-cell junctions by themselves hinder alignment. However, if cytoskeletal forces are transmitted via cell-cell junctions we observe strong collective alignment over large spatial scales