ORCID Profile
0000-0002-5509-402X
Current Organisation
University of Melbourne
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Biological Mathematics | Applied Mathematics |
Publisher: Cold Spring Harbor Laboratory
Date: 24-02-2021
DOI: 10.1101/2021.02.23.432578
Abstract: Adherens junctions (AJs) physically link two cells at their contact interface via extracellular homophilic interactions between cadherin molecules and intracellular connections between cadherins and the actomyosin cortex. Both cadherin and actomyosin cytoskeletal dynamics are reciprocally regulated by mechanical and chemical signals, which subsequently determine the strength of cell-cell adhesions and the emergent organization and stiffness of the tissues they form. However, an understanding of the integrated system is lacking. We present a new mechanistic computational model of intercellular junction maturation in a cell doublet to investigate the mechano-chemical crosstalk that regulates AJ formation and homeostasis. The model couples a 2D lattice-based model of cadherin dynamics with a continuum, reaction-diffusion model of the reorganizing actomyosin network through its regulation by Rho signaling at the intercellular junction. We demonstrate that local immobilization of cadherin induces cluster formation in a cis less dependent manner. We further investigate how cadherin and actin regulate and cooperate. By considering the force balance during AJ maturation and the force-sensitive property of the cadherin/F-actin linking molecules, we show that cortical tension applied on the contact rim can explain the ring distribution of cadherin and F-actin on the cell-cell contact of the cell-doublet. Meanwhile, the positive feedback loop between cadherin and F-actin is necessary for maintenance of the ring. Different patterns of cadherin distribution can be observed as an emergent property of disturbances of this feedback loop. We discuss these findings in light of available experimental observations on underlying mechanisms related to cadherin/F-actin binding and the mechanical environment. The formation, maintenance and disassembly of adherens junctions (AJs) is fundamental to organ development, tissue integrity as well as tissue function. E-cadherins and F-actin are two major players of the adherens junctions (AJs). Although it is well known that cadherins and F-actin affect each other, how these two players work together to maintain the intercellular contact is unclear. Using a novel mechano-chemical model of E-cadherin and F-actin remodeling, we demonstrate that a positive feedback loop between cadherins and F-actin allows them to stabilize each other locally. Mechanical and chemical stimuli applied to the cell adhesion change E-cadherin and F-actin distribution by consolidating or interrupting the feedback loop locally. Our study mechanistically links mechanical force to E-cadherin patterning at cell-cell junctions.
Publisher: Springer Science and Business Media LLC
Date: 14-11-2018
DOI: 10.1007/S00380-018-1303-5
Abstract: Multi-beat end-systolic elastance (E
Publisher: Cold Spring Harbor Laboratory
Date: 25-04-2023
DOI: 10.1101/2023.04.23.537337
Abstract: BondGraphs.jl is a Julia implementation of bond graphs. Bond graphs provide a modelling framework that describes energy flow through a physical system and by construction enforce thermodynamic constraints. The framework is widely used in engineering and has recently been shown to be a powerful approach for modelling biology. Models are mutable, hierarchical, multi-scale, multi-physics, and BondGraphs.jl is compatible with the Julia modelling ecosystem. BondGraphs.jl is freely available under the MIT license. Source code and documentation can be found at edforrest/BondGraphs.jl . pan.m@unimelb.edu.au , mstumpf@unimelb.edu.au Supplementary data are available at Bioinformatics online.
Publisher: SPIE
Date: 14-04-2005
DOI: 10.1117/12.596178
Publisher: IOP Publishing
Date: 12-2020
Publisher: Wiley
Date: 16-02-2011
DOI: 10.1002/CNM.1429
Publisher: Elsevier BV
Date: 02-2022
Publisher: Cold Spring Harbor Laboratory
Date: 22-09-2020
DOI: 10.1101/2020.09.21.307306
Abstract: Mitochondria are the powerhouse of the cell and owing to their unique energetic demands, heart muscles contain a high density of mitochondria. In conditions such as heart failure and diabetes-induced heart disease, changes in the organization of cardiac mitochondria are common. While recent studies have also shown that cardiac mitochondria split and fuse throughout the cell, a mechanistic understanding of how mitochondrial dynamics may affect energy output is lacking. Using a mathematical model that has been fitted to experimental data, we test if briefly altering fission or fusion rates improves ATP production and supply in cardiomyocytes. Unexpectedly, we found that cardiac bioenergetics, e.g., the ADP/ATP ratio, were robust to changes in fusion and fission rates and consequently mitochondria organization. Our study highlights complex nonlinear feedback loops that are at play in the cross-talk between mitochondrial dynamics and bioenergetics. The study motivate further in-silico and experimental investigations to determine the mechanistic basis for new therapies that target mitochondrial dynamics.
Publisher: Elsevier BV
Date: 10-2011
DOI: 10.1016/J.PBIOMOLBIO.2011.06.015
Abstract: The VPH/Physiome Project is developing the model encoding standards CellML (cellml.org) and FieldML (fieldml.org) as well as web-accessible model repositories based on these standards (models.physiome.org). Freely available open source computational modelling software is also being developed to solve the partial differential equations described by the models and to visualise results. The OpenCMISS code (opencmiss.org), described here, has been developed by the authors over the last six years to replace the CMISS code that has supported a number of organ system Physiome projects. OpenCMISS is designed to encompass multiple sets of physical equations and to link subcellular and tissue-level biophysical processes into organ-level processes. In the Heart Physiome project, for ex le, the large deformation mechanics of the myocardial wall need to be coupled to both ventricular flow and embedded coronary flow, and the reaction-diffusion equations that govern the propagation of electrical waves through myocardial tissue need to be coupled with equations that describe the ion channel currents that flow through the cardiac cell membranes. In this paper we discuss the design principles and distributed memory architecture behind the OpenCMISS code. We also discuss the design of the interfaces that link the sets of physical equations across common boundaries (such as fluid-structure coupling), or between spatial fields over the same domain (such as coupled electromechanics), and the concepts behind CellML and FieldML that are embodied in the OpenCMISS data structures. We show how all of these provide a flexible infrastructure for combining models developed across the VPH/Physiome community.
Publisher: Cold Spring Harbor Laboratory
Date: 14-08-2020
DOI: 10.1101/2020.08.13.249144
Abstract: Calcium (Ca 2+ ) plays a critical role in the excitation contraction coupling (ECC) process that governs the contraction of cardiomyocytes during each heartbeat. While ryanodine receptors (RyRs) are the primary Ca 2+ channels responsible for mediating cell-wide Ca 2+ transients during ECC, Ca 2+ release via inositol 1,4,5-trisphosphate (IP 3 ) receptors (IP 3 Rs) have been reported to elicit ECC-modulating effects. Recent studies suggest that the proximal localization of IP 3 Rs at dyads grants their ability to modify the occurrence of Ca 2+ sparks (elementary Ca 2+ release events that constitute ECC-associated Ca 2+ transients) which may underlie the modulatory effects on ECC. Here, we aim to uncover the mechanism by which IP 3 Rs affect Ca 2+ spark dynamics. To this end, we developed a mathematical model of the dyad that incorporates IP 3 Rs to reveal their impact on local Ca 2+ handling and corresponding Ca 2+ spark formation. Consistent with published experimental data, our model predicts that the propensity for Ca 2+ spark formation increases with IP 3 R activity. Our simulations support the hypothesis that IP 3 R activity elevates Ca 2+ within the dyad, sensitizing proximal RyRs for future release. However, this lowers Ca 2+ in the JSR available for release and thus results in Ca 2+ sparks with the same duration but lower litudes.
Publisher: Elsevier BV
Date: 10-2020
Publisher: Cold Spring Harbor Laboratory
Date: 02-04-2020
DOI: 10.1101/2020.04.01.020289
Abstract: Migratory cells are known to adapt to environments that contain wide-ranging levels of chemoattractant. While biochemical models of adaptation have been previously proposed, here we discuss a different mechanism based on mechanosensing, where the interaction between biochemical signaling and cell tension facilitates adaptation. We describe and analyze a model of mechanochemical-based adaptation coupling a mechanics-based physical model of cell tension coupled with the wave-pinning reaction-diffusion model for Rac activity. Mathematical analysis of this model, simulations of a simplified 1D cell geometry, and 2D finite element simulations of deforming cells reveal that as a cell protrudes under the influence of high stimulation levels, tension mediated inhibition of GTPase signaling causes the cell to polarize even when initially over-stimulated. Specifically, tension mediated inhibition of GTPase activation, which has been experimentally observed in recent years, facilitates this adaptation by countering the high levels of environmental stimulation. These results demonstrate how tension related mechanosensing may provide an alternative (and potentially complementary) mechanism for cell adaptation. Migratory cells such as human neutrophils encounter environments that contain wide-ranging levels of chemoattractant. In order to move, these cells must maintain an organized front-rear signaling polarity despite this wide variation in environmental stimuli. Past research has demonstrated a number of biochemical based mechanisms by which cells adapt to variable signal levels. Here we demonstrate that the interplay between Rho GTPase signaling and tension mediated feedbacks may provide an alternative mechanochemical mechanism for adaptation to high levels of signaling.
Publisher: SPIE
Date: 26-02-2009
DOI: 10.1117/12.811789
Publisher: Oxford University Press (OUP)
Date: 03-0003
Publisher: Hindawi Limited
Date: 07-10-2020
DOI: 10.1111/CMI.13270
Publisher: Elsevier BV
Date: 2023
DOI: 10.1016/J.MBS.2022.108923
Abstract: Calcium (Ca
Publisher: Oxford University Press (OUP)
Date: 19-09-2023
Publisher: Elsevier BV
Date: 08-2021
Publisher: Cold Spring Harbor Laboratory
Date: 04-01-2018
DOI: 10.1101/242701
Abstract: This paper presents a new algorithm to automatically segment the myofibrils, mitochondria and nuclei within single adult cardiac cells that are part of a large serial-block-face scanning electron microscopy (SBF-SEM) dataset. The algorithm only requires a set of manually drawn contours that roughly demarcate the cell boundary at routine slice intervals (every 50 th , for ex le). The algorithm correctly classified pixels within the single cell with 97% accuracy when compared to manual segmentations. One entire cell and the partial volumes of two cells were segmented. Analysis of segmentations within these cells showed that myofibrils and mitochondria occupied 47.5% and 51.6% on average respectively, while the nuclei occupy 0.7% of the cell for which the entire volume was captured in the SBF-SEM dataset. Mitochondria clustering increased at the periphery of the nucleus region and branching points of the cardiac cell. The segmentations also showed high area fraction of mitochondria (up to 70% of the 2D image slice) in the sub-sarcolemmal region, whilst it was closer to 50% in the intermyofibrillar space. We finally demonstrate that our segmentations can be turned into 3D finite element meshes for cardiac cell computational physiology studies. We offer our large dataset and MATLAB implementation of the algorithm for research use at www.github.com/CellSMB/sbfsem-cardiac-cell-segmenter/ . We anticipate that this timely tool will be of use to cardiac computational and experimental physiologists alike who study cardiac ultrastructure and its role in heart function.
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: IEEE
Date: 12-2018
Publisher: IEEE
Date: 10-01-2020
Publisher: Cold Spring Harbor Laboratory
Date: 11-07-2020
DOI: 10.1101/2020.07.11.191494
Abstract: The remarkable deformability of red blood cells (RBCs) depends on the viscoelasticity of the plasma membrane and cell contents and the surface area to volume (SA:V) ratio however, it remains unclear which of these factors is the key determinant for passage through small capillaries. We used a microfluidic device to examine the traversal of normal, stiffened, swollen, parasitised and immature RBCs. We show that dramatic stiffening of RBCs had no measurable effect on their ability to traverse small channels. By contrast, a moderate decrease in the SA:V ratio had a marked effect on the equivalent cylinder diameter that is traversable by RBCs of similar stiffness. We developed a finite element model that provides a coherent rationale for the experimental observations, based on the nonlinear mechanical behaviour of the RBC membrane skeleton. We conclude that the SA:V ratio should be given more prominence in studies of RBC pathologies.
Publisher: Cold Spring Harbor Laboratory
Date: 12-02-2023
DOI: 10.1101/2023.02.12.528212
Abstract: One of the best known ways bacteria cells understand and respond to the environment are through Two-Component Systems (TCS). These signalling systems are highly erse in function and can detect a range of physical stimuli including molecular concentrations and temperature, with a range of responses including chemotaxis and anaerobic energy production. TCS exhibit a range of different molecular structures and energy costs, and multiple types co-exist in the same cell. TCSs that incur relatively high energy cost are abundant in biology, despite strong evolutionary pressure to efficiently spend energy. We are motivated to discern what benefits, if any, the more energetically expensive variants had for a cell. We seek to answer this question by modelling energy flow through two variants of TCS. This was accomplished using bond graphs, a physics-based modelling framework that accurately models energy transfer through different physical domains. Our analysis demonstrates that energy availability can affect a cell’s signal sensitivity, noise filtering effectiveness, and the stimulus level where cell response is maximal. We also found that these properties are determined not by the molecular parameters themselves, but the reaction rate parameters that govern the reaction systems as a whole. This suggests possible connections between the molecular structure and evolutionary purpose of any two-component system. This opens the door to new synthetic circuit design in systems biology, and we propose new hypotheses about this link between structure and purpose that could be experimentally verified. Two-component systems are the main way many bacteria sense and respond to their environment. They exist in such well-studied bacteria as E. coli where they have been shown to detect a range of stimuli including nutrients, temperature, acidity, and pressure. Two-component systems are ubiquitous in bacteria yet have a deceptively simple structure. Knowing how they operate and the purpose of variations in signalling structure is helpful to our understanding of cellular biology and the design of synthetic biological circuits. Critical unanswered questions remain about the energy usage and functional benefits of these systems. We sought to improve our understanding of two-component systems by applying a physics-based modelling framework. We found that tracking energy flow through the cell reveals new energy-dependent behaviour in signalling sensitivity, noise filtering, and maximal cell response. We also found that these properties are not strictly dependent on the molecular properties themselves, but from the configuration of the reaction system as a whole.
Publisher: Elsevier BV
Date: 2008
DOI: 10.1016/J.JBIOMECH.2007.07.016
Abstract: Mammography is currently the most widely used screening and diagnostic tool for breast cancer. Because X-ray images are 2D projections of a 3D object, it is not trivial to localise features identified in mammogram pairs within the breast volume. Furthermore, mammograms represent highly deformed configurations of the breast under compression, thus the tumour localisation process relies on the clinician's experience. Biomechanical models of the breast undergoing mammographic compressions have been developed to overcome this limitation. In this study, we present the development of a modelling framework that implements Coulomb's frictional law with a finite element analysis using a C(1)-continuous Hermite mesh. We compared two methods of this contact mechanics implementation: the penalty method, and the augmented Lagrangian method, the latter of which is more accurate but computationally more expensive compared to the former. Simulation results were compared with experimental data from a soft silicon gel phantom in order to evaluate the modelling accuracy of each method. Both methods resulted in surface-deformation root-mean-square errors of less than 2mm, whilst the maximum internal marker prediction error was less than 3mm when simulating two mammographic-like compressions. Simulation results were confirmed using the augmented Lagrangian method, which provided similar accuracy. We conclude that contact mechanics on soft elastic materials using the penalty method with an appropriate choice of the penalty parameters provides sufficient accuracy (with contact constraints suitably enforced), and may thus be useful for tracking breast tumours between clinical images.
Publisher: Cold Spring Harbor Laboratory
Date: 22-05-2018
DOI: 10.1101/327254
Abstract: Recent electron microscopy data have revealed that cardiac mitochondria are not arranged in crystalline columns, but are organised with several mitochondria aggregated into columns of varying sizes often spanning the cell cross-section. This raises the question - how does the mitochondrial arrangement affect the metabolite distributions within cardiomyocytes and their impact on force dynamics? Here we employed finite element modelling of cardiac bioenergetics, using computational meshes derived from electron microscope images, to address this question. Our results indicate that heterogeneous mitochondrial distributions can lead to significant spatial variation across the cell in concentrations of inorganic phosphate, creatine (Cr) and creatine phosphate (PCr). However, our model predicts that sufficient activity of the creatine kinase (CK) system, coupled with rapid diffusion of Cr and PCr, maintains near uniform ATP and ADP ratios across the cell cross sections. This homogenous distribution of ATP and ADP should also evenly distribute force production and twitch duration with contraction. These results suggest that the PCr shuttle, and associated enzymatic reactions, act to maintain uniform force dynamics in the cell despite the heterogeneous mitochondrial organization. However, our model also predicts that under hypoxia - activity of mitochondrial CK enzyme and diffusion of high-energy phosphate compounds may be insufficient to sustain uniform ATP/ADP distribution and hence force generation.
Publisher: The Royal Society
Date: 03-10-2022
Abstract: Advances in electron microscopy (EM) such as electron tomography and focused ion-beam scanning electron microscopy provide unprecedented, three-dimensional views of cardiac ultrastructures within s le volumes ranging from hundreds of nanometres to hundreds of micrometres. The datasets from these s les are typically large, with file sizes ranging from gigabytes to terabytes and the number of image slices within the three-dimensional stack in the hundreds. A significant bottleneck with these large datasets is the time taken to extract and statistically analyse three-dimensional changes in cardiac ultrastructures. This is because of the inherently low contrast and the significant amount of structural detail that is present in EM images. These datasets often require manual annotation, which needs substantial person-hours and may result in only partial segmentation that makes quantitative analysis of the three-dimensional volumes infeasible. We present CardioVinci, a deep learning workflow to automatically segment and statistically quantify the morphologies and spatial assembly of mitochondria, myofibrils and Z-discs with minimal manual annotation. The workflow encodes a probabilistic model of the three-dimensional cardiomyocyte using a generative adversarial network. This generative model can be used to create new models of cardiomyocyte architecture that reflect variations in morphologies and cell architecture found in EM datasets. This article is part of the theme issue ‘The cardiomyocyte: new revelations on the interplay between architecture and function in growth, health, and disease’.
Publisher: Springer Berlin Heidelberg
Date: 2007
DOI: 10.1007/978-3-540-75757-3_79
Abstract: Breast cancer detection, diagnosis and treatment increasingly involves images of the breast taken with different degrees of breast deformation. We introduce a new biomechanical modelling framework for predicting breast deformation and thus aiding the combination of information derived from the various images. In this paper, we focus on MR images of the breast under different loading conditions, and consider methods to map information between the images. We generate subject-specific finite element models of the breast by semi-automatically fitting geometrical models to segmented data from breast MR images, and characterizing the subject-specific mechanical properties of the breast tissues. We identified the unloaded reference configuration of the breast by acquiring MR images of the breast under neutral buoyancy (immersed in water). Such imaging is clearly not practical in the clinical setting, however this previously unavailable data provides us with important data with which to validate models of breast biomechanics, and provides a common configuration with which to refer and interpret all breast images. We demonstrate our modelling framework using a pilot study that was conducted to assess the mechanical performance of a subject-specific homogeneous biomechanical model in predicting deformations of the breast of a volunteer in a prone gravity-loaded configuration. The model captured the gross characteristics of the breast deformation with an RMS error of 4.2 mm in predicting the skin surface of the gravity-loaded shape, which included tissue displacements of over 20 mm. Internal tissue features identified from the MR images were tracked from the reference state to the prone gravity-loaded configuration with a mean error of 3.7 mm. We consider the modelling assumptions and discuss how the framework could be refined in order to further improve the tissue tracking accuracy.
Publisher: Cold Spring Harbor Laboratory
Date: 23-08-2021
DOI: 10.1101/2021.08.22.457257
Abstract: Recent advances in high-throughput microscopy imaging have made it easier to acquire large volumes of cell images. Thanks to electron microscopy (EM) imaging, they provide a high-resolution and sufficient field of view that suits imaging large cell types, including cardiomyocytes. A significant bottleneck with these large datasets is the time taken to collect, extract and statistically analyse 3D changes in cardiac ultrastructures. We address this bottleneck with CardioVinci.
Publisher: Wiley
Date: 09-04-2010
DOI: 10.1002/WSBM.58
Abstract: Biomechanical modeling of the breast is a burgeoning research field that has potential uses across a wide range of healthcare applications. This review describes recent developments regarding multi-modal breast image analysis, and outlines some of the key challenges that researchers face in introducing the models into the clinical arena. Deformable breast models have demonstrated capabilities across a wide range of breast cancer diagnoses and treatments. Specific applications include magnetic resonance (MR) image guided surgery, registration of x-ray and MR images, and breast reduction/augmentation surgery planning. Challenges lie in improving the fidelity of these models, which are presently simplistic and use many unverified parameters. Specific challenges include characterization of in idual-specific mechanical properties of breast tissues, precise representation of loading and boundary constraints during different clinical procedures, and validation of modeling techniques used to represent key mechanical aspects such as the suspensory Cooper's ligaments. Scientists must also work towards translating their research tools into the clinical setting by developing efficient tools with user-friendly interactivity. Widespread adoption of such techniques has the potential to significantly reduce the numbers of misdiagnosed breast cancers and enhance surgical planning for patient treatment.
Publisher: Elsevier BV
Date: 12-2013
DOI: 10.1016/J.MEDIA.2013.05.011
Abstract: This paper presents a novel X-ray and MR image registration technique based on in idual-specific biomechanical finite element (FE) models of the breasts. Information from 3D magnetic resonance (MR) images was registered to X-ray mammographic images using non-linear FE models subject to contact mechanics constraints to simulate the large compressive deformations between the two imaging modalities. A physics-based perspective ray-casting algorithm was used to generate 2D pseudo-X-ray projections of the FE-warped 3D MR images. Unknown input parameters to the FE models, such as the location and orientation of the compression plates, were optimised to provide the best match between the pseudo and clinical X-ray images. The methods were validated using images taken before and during compression of a breast-shaped phantom, for which 12 inclusions were tracked between imaging modalities. These methods were then applied to X-ray and MR images from six breast cancer patients. Error measures (such as centroid and surface distances) of segmented tumours in simulated and actual X-ray mammograms were used to assess the accuracy of the methods. Sensitivity analysis of the lesion co-localisation accuracy to rotation about the anterior-posterior axis was then performed. For 10 of the 12 X-ray mammograms, lesion localisation accuracies of 14 mm and less were achieved. This analysis on the rotation about the anterior-posterior axis indicated that, in cases where the lesion lies in the plane parallel to the mammographic compression plates, that cuts through the nipple, such rotations have relatively minor effects.This has important implications for clinical applicability of this multi-modality lesion registration technique, which will aid in the diagnosis and treatment of breast cancer.
Publisher: Elsevier BV
Date: 08-2009
Publisher: Cold Spring Harbor Laboratory
Date: 22-05-2022
DOI: 10.1101/2022.05.22.492785
Abstract: Diabetic cardiomyopathy is a leading cause of heart failure in diabetes. At the cellular level, diabetic cardiomyopathy leads to altered mitochondrial energy metabolism and cardiomyocyte ultrastructure. We combined electron microscopy and computational modelling to understand the impact of diabetes induced ultrastructural changes on cardiac bioenergetics. We collected transverse micrographs of multiple control and type I diabetic rat cardiomyocytes using electron microscopy. Micrographs were converted to finite element meshes, and bioenergetics was simulated over them using a biophysical model. The simulations also incorporated depressed mitochondrial capacity for oxidative phosphorylation and creatine kinase reactions to simulate diabetes induced mitochondrial dysfunction. Analysis of micrographs revealed a 14% decline in mitochondrial area fraction in diabetic cardiomyocytes, and an irregular arrangement of mitochondria and myofibrils. Simulations predicted that this irregular arrangement, coupled with depressed activity of mitochondrial creatine kinase enzymes, leads to large spatial variation in ADP/ATP profile of diabetic cardiomyocytes. However, when spatially averaged, myofibrillar ADP/ATP ratios of a cardiomyocyte do not change with diabetes. Instead, average concentration of inorganic phosphate rises by 40% due to lower mitochondrial area fraction and dysfunction in oxidative phosphorylation. These simulations indicate that a disorganized cellular ultrastructure negatively impacts metabolite transport in diabetic cardiomyopathy.
Publisher: IEEE
Date: 07-2017
Publisher: Public Library of Science (PLoS)
Date: 05-12-2018
Publisher: American Physical Society (APS)
Date: 15-10-2021
Publisher: Wiley
Date: 30-11-2018
DOI: 10.1002/WSBM.1407
Abstract: Cellular cytoskeletal mechanics plays a major role in many aspects of human health from organ development to wound healing, tissue homeostasis and cancer metastasis. We summarize the state‐of‐the‐art techniques for mathematically modeling cellular stiffness and mechanics and the cytoskeletal components and factors that regulate them. We highlight key experiments that have assisted model parameterization and compare the advantages of different models that have been used to recapitulate these experiments. An overview of feed‐forward mechanisms from signaling to cytoskeleton remodeling is provided, followed by a discussion of the rapidly growing niche of encapsulating feedback mechanisms from cytoskeletal and cell mechanics to signaling. We discuss broad areas of advancement that could accelerate research and understanding of cellular mechanobiology. A precise understanding of the molecular mechanisms that affect cell and tissue mechanics and function will underpin innovations in medical device technologies of the future. WIREs Syst Biol Med 2018, 10:e1407. doi: 10.1002/wsbm.1407 This article is categorized under: Models of Systems Properties and Processes Mechanistic Models Physiology Mammalian Physiology in Health and Disease Models of Systems Properties and Processes Cellular Models
Publisher: Cold Spring Harbor Laboratory
Date: 15-02-2019
DOI: 10.1101/549683
Abstract: In cardiomyocytes, the coordinated release of calcium ions from intracellular stores through ryanodine receptor (RyR) clusters is key to the generation of a calcium transient and induction of contraction. Recently, a deconvolution algorithm from radio astronomy was adapted and applied to analysis of calcium fluorescence imaging of cardiomyocytes. The algorithm, CaCLEAN, showed potential in revealing both the spatial locations of RyR clusters and their functional response in living cells. However, whether the RyR clusters identified by CaCLEAN analysis of the imaging data were true or false positives remained unvalidated in the absence of ground truth values. In this work, a structurally realistic finite element model was developed to simulate reaction-diffusion of calcium emanating from RyR clusters during the rising phase (first 30 ms) of the calcium transient. The effect of two sets of factors were examined with the model: (1) the number and spacing of simulated RyR clusters and (2) the effect of mitochondria acting as barriers to diffusion. Confocal fluorescence microscopy images were simulated from the model results and analysed using CaCLEAN. The performance of CaCLEAN was found to be sensitive to cluster spacing and distance from the imaging plane. In a case with sparsely-packed clusters, detection recall and precision were 0.82 for clusters up to 610 nm from the imaging plane in a densely-packed cluster case, recall and precision were 0.69 for clusters up to 280 nm from the imaging plane. Users interested in applying CaCLEAN to their data should therefore consider the likely density of cluster distributions and the trade-off between precision and recall when determining the maximum relevant depth of RyR clusters in their application.
Publisher: Springer New York
Date: 2010
Publisher: Springer New York
Date: 2010
Publisher: Oxford University Press (OUP)
Date: 2021
DOI: 10.1093/BIOINFORMATICS/BTAA1094
Abstract: The inherent low contrast of electron microscopy (EM) datasets presents a significant challenge for rapid segmentation of cellular ultrastructures from EM data. This challenge is particularly prominent when working with high-resolution big-datasets that are now acquired using electron tomography and serial block-face imaging techniques. Deep learning (DL) methods offer an exciting opportunity to automate the segmentation process by learning from manual annotations of a small s le of EM data. While many DL methods are being rapidly adopted to segment EM data no benchmark analysis has been conducted on these methods to date. We present EM-stellar, a platform that is hosted on Google Colab that can be used to benchmark the performance of a range of state-of-the-art DL methods on user-provided datasets. Using EM-stellar we show that the performance of any DL method is dependent on the properties of the images being segmented. It also follows that no single DL method performs consistently across all performance evaluation metrics. EM-stellar (code and data) is written in Python and is freely available under MIT license on GitHub (ellsmb/em-stellar). Supplementary data are available at Bioinformatics online.
Publisher: Wiley
Date: 14-02-2020
DOI: 10.1002/CNM.3313
Abstract: Models of cardiac mechanics require a well-defined reference geometry from which deformations and hence myocardial strain and stress can be calculated. In the in vivo beating heart, the load-free (LF) geometry generally cannot be measured directly, since, in many cases, there is no stage at which the lumen pressures and contractile state are all zero. Therefore, there is a need for an efficient method to estimate the LF geometry, which is essential for an accurate mechanical simulation of left ventricular (LV) mechanics, and for estimations of passive and contractile constitutive parameters of the heart muscle. In this paper, we present a novel method for estimating both the LF geometry and the passive stiffness of the myocardium. A linear combination of principal components from a population of diastolic displacements is used to construct the LF geometry. For each estimate of the LF geometry and tissue stiffness, LV inflation is simulated, and the model predictions are compared with surface data at multiple stages during passive diastolic filling. The feasibility of this method was demonstrated using synthetically deformation data that were generated using LV models derived from clinical magnetic resonance image data, and the identifiability of the LF geometry and passive stiffness parameters were analysed using Hessian metrics. Applications of this method to clinical data would improve the accuracy of constitutive parameter estimation and allow a better simulation of LV wall strains and stresses.
Publisher: SPIE
Date: 06-03-2008
DOI: 10.1117/12.769945
Publisher: The Royal Society
Date: 03-10-2022
Publisher: MyJove Corporation
Date: 18-04-2018
DOI: 10.3791/56817
Publisher: Royal Society of Chemistry (RSC)
Date: 2021
DOI: 10.1039/D1LC00378J
Abstract: We highlight recent acoustofluidic advances that demonstrate versatility for activities beyond periodic patterning in pressure nodes.
Publisher: Elsevier BV
Date: 11-2008
DOI: 10.1016/J.ACRA.2008.07.017
Abstract: Anatomically realistic biomechanical models of the breast potentially provide a reliable way of mapping tissue locations across medical images, such as mammograms, magnetic resonance imaging (MRI), and ultrasound. This work presents a new modeling framework that enables us to create biomechanical models of the breast that are customized to the in idual. We demonstrate the framework's capabilities by creating models of the left breasts of two volunteers and tracking their deformations across MRIs. We generate customized finite element models by automatically fitting geometrical models to segmented data from breast MRIs, and characterizing the in vivo mechanical properties (assuming homogeneity) of the breast tissues. For each volunteer, we identified the unloaded configuration by acquiring MRIs of the breast under neutral buoyancy (immersed in water). Such imaging is clearly not practical in the clinical setting however, these previously unavailable data provide us with important data with which to validate models of breast biomechanics. Internal tissue features were identified in the neutral buoyancy images and tracked to the prone gravity-loaded state using the modeling framework. The models predicted deformations with root-mean-square errors of 4.2 and 3.6 mm in predicting the skin surface of the gravity-loaded state for each volunteer. Internal tissue features were tracked with a mean error of 3.7 and 4.7 mm for each volunteer. The models capture breast shape and internal deformations across the images with clinically acceptable accuracy. Further refinement of the framework and incorporation of more anatomic detail will make these models useful for breast cancer diagnosis.
Publisher: Cold Spring Harbor Laboratory
Date: 15-07-2020
DOI: 10.1101/2020.07.15.203836
Abstract: The inherent low contrast of electron microscopy (EM) datasets presents a significant challenge for rapid segmentation of cellular ultrastructures from EM data. This challenge is particularly prominent when working with high resolution big-datasets that are now acquired using electron tomography and serial block-face imaging techniques. Deep learning (DL) methods offer an exciting opportunity to automate the segmentation process by learning from manual annotations of a small s le of EM data. While many DL methods are being rapidly adopted to segment EM data no benchmark analysis has been conducted on these methods to date. We present EM-stellar, a Jupyter Notebook platform that is hosted on google Colab that can be used to benchmark the performance of a range of state-of-the-art DL methods on user-provided datasets. Using EM-Stellar we show that the performance of any DL method is dependent on the properties of the images being segmented. It also follows that no single DL method performs consistently across all performance evaluation metrics.
Publisher: Annual Reviews
Date: 10-08-2022
DOI: 10.1146/ANNUREV-BIODATASCI-072018-021246
Abstract: Modern biology and biomedicine are undergoing a big data explosion, needing advanced computational algorithms to extract mechanistic insights on the physiological state of living cells. We present the motivation for the Cell Physiome Project: a framework and approach for creating, sharing, and using biophysics-based computational models of single-cell physiology. Using ex les in calcium signaling, bioenergetics, and endosomal trafficking, we highlight the need for spatially detailed, biophysics-based computational models to uncover new mechanisms underlying cell biology. We review progress and challenges to date toward creating cell physiome models. We then introduce bond graphs as an efficient way to create cell physiome models that integrate chemical, mechanical, electromagnetic, and thermal processes while maintaining mass and energy balance. Bond graphs enhance modularization and reusability of computational models of cells at scale. We conclude with a look forward at steps that will help fully realize this exciting new field of mechanistic biomedical data science.
Publisher: Hindawi Limited
Date: 11-02-2019
DOI: 10.1111/CMI.13005
Publisher: American Physiological Society
Date: 02-2017
DOI: 10.1152/AJPCELL.00298.2016
Abstract: Diabetic cardiomyopathy is accompanied by metabolic and ultrastructural alterations, but the impact of the structural changes on metabolism itself is yet to be determined. Morphometric analysis of mitochondrial shape and spatial organization within transverse sections of cardiomyocytes from control and streptozotocin-induced type I diabetic Sprague-Dawley rats revealed that mitochondria are 20% smaller in size while their spatial density increases by 53% in diabetic cells relative to control myocytes. Diabetic cells formed larger clusters of mitochondria (60% more mitochondria per cluster) and the effective surface-to-volume ratio of these clusters increased by 22.5%. Using a biophysical computational model we found that this increase can have a moderate compensatory effect by increasing the availability of ATP in the cytosol when ATP synthesis within the mitochondrial matrix is compromised.
Publisher: Public Library of Science (PLoS)
Date: 08-07-2022
DOI: 10.1371/JOURNAL.PCBI.1010257
Abstract: Cadherins build up clusters to maintain intercellular contact through trans and cis (lateral) bindings. Meanwhile, interactions between cadherin and the actin cytoskeleton through cadherin/F-actin linkers can affect cadherin dynamics by corralling and tethering cadherin molecules locally. Despite many experimental studies, a quantitative, mechanistic understanding of how cadherin and actin cytoskeleton interactions regulate cadherin clustering does not exist. To address this gap in knowledge, we developed a coarse-grained computational model of cadherin dynamics and their interaction with the actin cortex underlying the cell membrane. Our simulation predictions suggest that weak cis binding affinity between cadherin molecules can facilitate large cluster formation. We also found that cadherin movement inhibition by actin corralling is dependent on the concentration and length of actin filaments. This results in changes in cadherin clustering behaviors, as reflected by differences in cluster size and distribution as well as cadherin monomer trajectory. Strong cadherin/actin binding can enhance trans and cis interactions as well as cadherin clustering. By contrast, with weak cadherin/actin binding affinity, a competition between cadherin-actin binding and cis binding for a limited cadherin pool leads to temporary and unstable cadherin clusters.
Publisher: Acoustical Society of America (ASA)
Date: 09-2021
DOI: 10.1121/10.0006235
Abstract: Both the scarcity and environmental impact of disposable face masks, as in the COVID-19 pandemic, have instigated the recent development of reusable masks. Such face masks reduce transmission of infectious agents and particulates, but often impact a user's ability to be understood when materials, such as silicone or hard polymers, are used. In this work, we present a numerical optimisation approach to optimise waveguide topology, where a waveguide is used to transmit and direct sound from the interior of the mask volume to the outside air. This approach allows acoustic energy to be maximised according to specific frequency bands, including those most relevant to human speech. We employ this method to convert a resuscitator mask, made of silicone, into respiration personal protective equipment (PPE) that maximises the speech intelligibility index (SII). We validate this approach experimentally as well, showing improved SII when using the fabricated device. Together, this design represents a unique and effective approach to utilize and adapt available apparatus to filter air while improving the ability to communicate effectively, including in healthcare settings.
Publisher: Springer Science and Business Media LLC
Date: 09-01-2008
DOI: 10.1007/S10237-006-0074-6
Abstract: A number of biomechanical models have been proposed to improve nonrigid registration techniques for multimodal breast image alignment. A deformable breast model may also be useful for overcoming difficulties in interpreting 2D X-ray projections (mammograms) of 3D volumes (breast tissues). If a deformable model could accurately predict the shape changes that breasts undergo during mammography, then the model could serve to localize suspicious masses (visible in mammograms) in the unloaded state, or in any other deformed state required for further investigations (such as biopsy or other medical imaging modalities). In this paper, we present a validation study that was conducted in order to develop a biomechanical model based on the well-established theory of continuum mechanics (finite elasticity theory with contact mechanics) and demonstrate its use for this application. Experimental studies using gel phantoms were conducted to test the accuracy in predicting mammographic-like deformations. The material properties of the gel phantom were estimated using a nonlinear optimization process, which minimized the errors between the experimental and the model-predicted surface data by adjusting the parameter associated with the neo-Hookean constitutive relation. Two compressions (the equivalent of cranio-caudal and medio-lateral mammograms) were performed on the phantom, and the corresponding deformations were recorded using a MRI scanner. Finite element simulations were performed to mimic the experiments using the estimated material properties with appropriate boundary conditions. The simulation results matched the experimental recordings of the deformed phantom, with a sub-millimeter root-mean-square error for each compression state. Having now validated our finite element model of breast compression, the next stage is to apply the model to clinical images.
Publisher: Public Library of Science (PLoS)
Date: 03-09-2015
Publisher: Springer Berlin Heidelberg
Date: 2008
DOI: 10.1007/978-3-540-85990-1_91
Abstract: We have developed a biomechanical model of the breast to simulate compression during mammographic imaging. The modelling framework was applied to a set of MR images of the breasts of a volunteer. Images of the uncompressed breast were segmented into skin and pectoral muscle, from which a finite element (FE) mesh of the left breast was generated using a nonlinear geometric fitting process. The compression plates within the breast MR coil were used to compress the volunteer's breasts by 32% in the latero-medial direction and the compressed breasts were subsequently imaged using MRI. The FE geometry of the uncompressed left breast was used to numerically simulate compression based on finite deformation elasticity coupled with contact mechanics, and in idual-specific tissue properties. Accuracy of the simulated FE model was analysed by comparing the predicted surface data, and locations of three internal features within the compressed breast, with the equivalent experimental observations. Model predictions of the surface deformation yielded a RMS error of 1.5 mm. The Euclidean errors in predicting the locations of three internal features were 4.1 mm, 4.1 mm and 6.5 mm. Whilst the model reliably reproduced the compressive deformation, further investigations are required in order to test the validity of the underlying modelling assumptions. A reliable biomechanical model will provide a multi-modality imaging registration tool to help identify potential tumours observed between mammograms and other imaging modalities such as MRI or ultrasound.
Publisher: Wiley
Date: 25-03-2011
DOI: 10.1002/CNM.1441
Publisher: Springer New York
Date: 2012
Publisher: MDPI AG
Date: 10-03-2021
Abstract: Reticulocalbin 1 (RCN1) is an endoplasmic reticulum (ER)-residing protein, involved in promoting cell survival during pathophysiological conditions that lead to ER stress. However, the key upstream receptor tyrosine kinase that regulates RCN1 expression and its potential role in cell survival in the glioblastoma setting have not been determined. Here, we demonstrate that RCN1 expression significantly correlates with poor glioblastoma patient survival. We also demonstrate that glioblastoma cells with expression of EGFRvIII receptor also have high RCN1 expression. Over-expression of wildtype EGFR also correlated with high RCN1 expression, suggesting that EGFR and EGFRvIII regulate RCN1 expression. Importantly, cells that expressed EGFRvIII and subsequently showed high RCN1 expression displayed greater cell viability under ER stress compared to EGFRvIII negative glioblastoma cells. Consistently, we also demonstrated that RCN1 knockdown reduced cell viability and exogenous introduction of RCN1 enhanced cell viability following induction of ER stress. Mechanistically, we demonstrate that the EGFRvIII-RCN1-driven increase in cell survival is due to the inactivation of the ER stress markers ATF4 and ATF6, maintained expression of the anti-apoptotic protein Bcl-2 and reduced activity of caspase 3/7. Our current findings identify that EGFRvIII regulates RCN1 expression and that this novel association promotes cell survival in glioblastoma cells during ER stress.
Publisher: Springer Science and Business Media LLC
Date: 02-2022
DOI: 10.1007/S12551-022-00937-7
Abstract: In the Carboniferous, insects evolved flight. Intense selection drove for high performance and approximately 100 million years later, Hymenoptera (bees, wasps and ants) emerged. Some species had proportionately small wings, with apparently impossible aerodynamic challenges including a need for high frequency flight muscles (FMs), powered exclusively off aerobic pathways and resulting in extreme aerobic capacities. Modern insect FMs are the most refined and form large dense blocks that occupy 90% of the thorax. These can beat wings at 200 to 230 Hz, more than double that achieved by standard neuromuscular systems. To do so, rapid repolarisation was circumvented through evolution of asynchronous stimulation, stretch activation, elastic recoil and a paradoxically slow Ca 2+ reuptake. While the latter conserves ATP, considerable ATP is demanded at the myofibrils. FMs have diminished sarcoplasmic volumes, and ATP is produced solely by mitochondria, which pack myocytes to maximal limits and have very dense cristae. Gaseous oxygen is supplied directly to mitochondria. While FMs appear to be optimised for function, several unusual paradoxes remain. FMs lack any significant equivalent to the creatine kinase shuttle, and myofibrils are twice as wide as those of within cardiomyocytes. The mitochondrial electron transport systems also release large amounts of reactive oxygen species (ROS) and respiratory complexes do not appear to be present at any exceptional level. Given that the loss of the creatine kinase shuttle and elevated ROS impairs heart function, we question how do FM shuttle adenylates at high rates and tolerate oxidative stress conditions that occur in diseased hearts?
Publisher: The Royal Society
Date: 03-10-2022
Abstract: Diabetic cardiomyopathy is a leading cause of heart failure in diabetes. At the cellular level, diabetic cardiomyopathy leads to altered mitochondrial energy metabolism and cardiomyocyte ultrastructure. We combined electron microscopy (EM) and computational modelling to understand the impact of diabetes-induced ultrastructural changes on cardiac bioenergetics. We collected transverse micrographs of multiple control and type I diabetic rat cardiomyocytes using EM. Micrographs were converted to finite-element meshes, and bioenergetics was simulated over them using a biophysical model. The simulations also incorporated depressed mitochondrial capacity for oxidative phosphorylation (OXPHOS) and creatine kinase (CK) reactions to simulate diabetes-induced mitochondrial dysfunction. Analysis of micrographs revealed a 14% decline in mitochondrial area fraction in diabetic cardiomyocytes, and an irregular arrangement of mitochondria and myofibrils. Simulations predicted that this irregular arrangement, coupled with the depressed activity of mitochondrial CK enzymes, leads to large spatial variation in adenosine diphosphate (ADP)/adenosine triphosphate (ATP) ratio profile of diabetic cardiomyocytes. However, when spatially averaged, myofibrillar ADP/ATP ratios of a cardiomyocyte do not change with diabetes. Instead, average concentration of inorganic phosphate rises by 40% owing to lower mitochondrial area fraction and dysfunction in OXPHOS. These simulations indicate that a disorganized cellular ultrastructure negatively impacts metabolite transport in diabetic cardiomyopathy. This article is part of the theme issue ‘The cardiomyocyte: new revelations on the interplay between architecture and function in growth, health, and disease’.
Publisher: American Society of Hematology
Date: 12-12-2017
DOI: 10.1182/BLOODADVANCES.2017009274
Abstract: Mutations in β spectrin cause microcytosis, resulting in increased clearance of erythrocytes and enhanced resistance to malaria in mice. A homozygous CRISPR/Cas9-induced mutation in the binding site between β spectrin and ankyrin-1 increases mouse survival during malaria.
Publisher: Frontiers Media SA
Date: 02-10-2019
Publisher: IEEE
Date: 08-2010
Publisher: Springer Berlin Heidelberg
Date: 2011
DOI: 10.1007/8415_2011_92
Publisher: Elsevier BV
Date: 2022
Publisher: Elsevier BV
Date: 09-2020
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: Springer Science and Business Media LLC
Date: 12-2019
DOI: 10.1186/S12911-019-0962-1
Abstract: With the advent of new high-throughput electron microscopy techniques such as serial block-face scanning electron microscopy (SBF-SEM) and focused ion-beam scanning electron microscopy (FIB-SEM) biomedical scientists can study sub-cellular structural mechanisms of heart disease at high resolution and high volume. Among several key components that determine healthy contractile function in cardiomyocytes are Z-disks or Z-lines, which are located at the lateral borders of the sarcomere, the fundamental unit of striated muscle. Z-disks play the important role of anchoring contractile proteins within the cell that make the heartbeat. Changes to their organization can affect the force with which the cardiomyocyte contracts and may also affect signaling pathways that regulate cardiomyocyte health and function. Compared to other components in the cell, such as mitochondria, Z-disks appear as very thin linear structures in microscopy data with limited difference in contrast to the remaining components of the cell. In this paper, we propose to generate a 3D model of Z-disks within single adult cardiac cells from an automated segmentation of a large serial-block-face scanning electron microscopy (SBF-SEM) dataset. The proposed fully automated segmentation scheme is comprised of three main modules including “pre-processing”, “segmentation” and “refinement”. We represent a simple, yet effective model to perform segmentation and refinement steps. Contrast stretching, and Gaussian kernels are used to pre-process the dataset, and well-known “Sobel operators” are used in the segmentation module. We have validated our model by comparing segmentation results with ground-truth annotated Z-disks in terms of pixel-wise accuracy. The results show that our model correctly detects Z-disks with 90.56% accuracy. We also compare and contrast the accuracy of the proposed algorithm in segmenting a FIB-SEM dataset against the accuracy of segmentations from a machine learning program called Ilastik and discuss the advantages and disadvantages that these two approaches have. Our validation results demonstrate the robustness and reliability of our algorithm and model both in terms of validation metrics and in terms of a comparison with a 3D visualisation of Z-disks obtained using immunofluorescence based confocal imaging.
Publisher: IEEE
Date: 08-2006
Publisher: Elsevier BV
Date: 06-2018
DOI: 10.1016/J.JSB.2018.02.005
Abstract: This paper presents a new algorithm to automatically segment the myofibrils, mitochondria and nuclei within single adult cardiac cells that are part of a large serial-block-face scanning electron microscopy (SBF-SEM) dataset. The algorithm only requires a set of manually drawn contours that roughly demarcate the cell boundary at routine slice intervals (every 50th, for ex le). The algorithm correctly classified pixels within the single cell with 97% accuracy when compared to manual segmentations. One entire cell and the partial volumes of two cells were segmented. Analysis of segmentations within these cells showed that myofibrils and mitochondria occupied 47.5% and 51.6% on average respectively, while the nuclei occupy 0.7% of the cell for which the entire volume was captured in the SBF-SEM dataset. Mitochondria clustering increased at the periphery of the nucleus region and branching points of the cardiac cell. The segmentations also showed high area fraction of mitochondria (up to 70% of the 2D image slice) in the sub-sarcolemmal region, whilst it was closer to 50% in the intermyofibrillar space. We finally demonstrate that our segmentations can be turned into 3D finite element meshes for cardiac cell computational physiology studies. We offer our large dataset and MATLAB implementation of the algorithm for research use at www.github.com/CellSMB/sbfsem-cardiac-cell-segmenter/. We anticipate that this timely tool will be of use to cardiac computational and experimental physiologists alike who study cardiac ultrastructure and its role in heart function.
Publisher: Wiley
Date: 2007
DOI: 10.1002/NME.2045
Publisher: Cold Spring Harbor Laboratory
Date: 04-02-2020
DOI: 10.1101/2020.02.03.933127
Abstract: Recent high-throughput electron microscopy techniques such as focused ion-beam scanning electron microscopy (FIB-SEM) provide thousands of serial sections which assist the biologists in studying sub-cellular structures at high resolution and large volume. Low contrast of such images hinder image segmentation and 3D visualisation of these datasets. With recent advances in computer vision and deep learning, such datasets can be segmented and reconstructed in 3D with greater ease and speed than with previous approaches. However, these methods still rely on thousands of ground-truth s les for training and electron microscopy datasets require significant amounts of time for carefully curated manual annotations. We address these bottlenecks with EM-net, a scalable deep convolutional neural network for EM image segmentation. We have evaluated EM-net using two datasets, one of which belongs to an ongoing competition on EM stack segmentation since 2012. We show that EM-net variants achieve better performances than current deep learning methods using small- and medium-sized ground-truth datasets. We also show that the ensemble of top EM-net base classifiers outperforms other methods across a wide variety of evaluation metrics.
Publisher: Oxford University Press (OUP)
Date: 08-2019
Publisher: Springer New York
Date: 2011
Publisher: Elsevier BV
Date: 08-2014
DOI: 10.1016/J.PBIOMOLBIO.2014.07.003
Abstract: A major motivation for the use of super-resolution imaging methods in the investigation of cardiac biophysics has been the insight from biophysical considerations and detailed mathematical modeling that the spatial structure and protein organisation at the scale of nanometres can have enormous implications for calcium signalling in cardiac muscle. We illustrate the use of dSTORM based super-resolution in optically thick (∼10 μm) tissue slices of rat ventricular tissue to visualize proteins at the cardiac Z-disk and compare those images with confocal (diffraction-limited) as well as electron microscopy (EM) data which still provides a benchmark in terms of resolution. α-actinin is an abundant protein target that effectively defines the Z-disk in striated muscle and provides a reference structure for other proteins at the Z-line and the transverse tubules. Using super-resolution imaging α-actinin labelling provides very detailed outlines of the contractile machinery which we have used to study the properties of Z-disks and the distribution of α-actinin itself. We determined the local diameters of the myo-fibrillar and non-myofibrillar space using α-actinin labelling. Comparison between confocal and super-resolution based myofibrillar masks suggested that super-resolution data was able to segment myofibrils accurately while confocal approaches were not always able to distinguish neighbouring myofibrillar bundles which resulted in overestimated diameters. The increased resolution of super-resolution methods provides qualitatively new information to improve our understanding of cardiac biophysics. Nevertheless, conventional diffraction-limited imaging still has an important role to play which we illustrate with correlative confocal and super-resolution data.
Location: New Zealand
Start Date: 2009
End Date: 2012
Funder: Marsden Fund
View Funded ActivityStart Date: 2010
End Date: 2014
Funder: Health Research Council of New Zealand
View Funded ActivityStart Date: 02-2017
End Date: 06-2020
Amount: $316,000.00
Funder: Australian Research Council
View Funded Activity