Publications by authors named "Emma Lejeune"

13 Publications

  • Page 1 of 1

Sarc-Graph: Automated segmentation, tracking, and analysis of sarcomeres in hiPSC-derived cardiomyocytes.

PLoS Comput Biol 2021 10 6;17(10):e1009443. Epub 2021 Oct 6.

Department of Mechanical Engineering, Boston University, Boston, Massachusetts, United States of America.

A better fundamental understanding of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) has the potential to advance applications ranging from drug discovery to cardiac repair. Automated quantitative analysis of beating hiPSC-CMs is an important and fast developing component of the hiPSC-CM research pipeline. Here we introduce "Sarc-Graph," a computational framework to segment, track, and analyze sarcomeres in fluorescently tagged hiPSC-CMs. Our framework includes functions to segment z-discs and sarcomeres, track z-discs and sarcomeres in beating cells, and perform automated spatiotemporal analysis and data visualization. In addition to reporting good performance for sarcomere segmentation and tracking with little to no parameter tuning and a short runtime, we introduce two novel analysis approaches. First, we construct spatial graphs where z-discs correspond to nodes and sarcomeres correspond to edges. This makes measuring the network distance between each sarcomere (i.e., the number of connecting sarcomeres separating each sarcomere pair) straightforward. Second, we treat tracked and segmented components as fiducial markers and use them to compute the approximate deformation gradient of the entire tracked population. This represents a new quantitative descriptor of hiPSC-CM function. We showcase and validate our approach with both synthetic and experimental movies of beating hiPSC-CMs. By publishing Sarc-Graph, we aim to make automated quantitative analysis of hiPSC-CM behavior more accessible to the broader research community.
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http://dx.doi.org/10.1371/journal.pcbi.1009443DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8523047PMC
October 2021

Extracellular Matrix Alignment Directs Provisional Matrix Assembly and Three Dimensional Fibrous Tissue Closure.

Tissue Eng Part A 2021 12 12;27(23-24):1447-1457. Epub 2021 May 12.

Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA.

Gap closure is a dynamic process in wound healing, in which a wound contracts and a provisional matrix is laid down, to restore structural integrity to injured tissues. The efficiency of wound closure has been found to depend on the shape of a wound, and this shape dependence has been echoed in various studies. While wound shape itself appears to contribute to this effect, it remains unclear whether the alignment of the surrounding extracellular matrix (ECM) may also contribute. In this study, we investigate the role both wound curvature and ECM alignment have on gap closure in a 3D culture model of fibrous tissue. Using microfabricated flexible micropillars positioned in rectangular and octagonal arrangements, seeded 3T3 fibroblasts embedded in a collagen matrix formed microtissues with different ECM alignments. Wounding these microtissues with a microsurgical knife resulted in wounds with different shapes and curvatures that closed at different rates. Observing different regions around the wounds, we noted local wound curvature did not impact the rate of production of provisional fibronectin matrix assembled by the fibroblasts. Instead, the rate of provisional matrix assembly was lowest emerging from regions of high fibronectin alignment and highest in the areas of low matrix alignment. Our data suggest that the underlying ECM structure affects the shape of the wound as well as the ability of fibroblasts to build provisional matrix, an important step in the process of tissue closure and restoration of tissue architecture. The study highlights an important interplay between ECM alignment, wound shape, and tissue healing that has not been previously recognized and may inform approaches to engineer tissues. Impact statement Current models of tissue growth have identified a role for curvature in driving provisional matrix assembly. However, most tissue repair occurs in fibrous tissues with different levels of extracellular matrix (ECM) alignment. Here, we show how this underlying ECM alignment may affect the ability of fibroblasts to build new provisional matrix, with implications for wound healing and providing insight for engineering of new tissues.
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http://dx.doi.org/10.1089/ten.tea.2020.0332DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8742281PMC
December 2021

On the Three-Dimensional Correlation Between Myofibroblast Shape and Contraction.

J Biomech Eng 2021 09;143(9)

James T. Willerson Center for Cardiovascular Modeling and Simulation, The Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712; Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712.

Myofibroblasts are responsible for wound healing and tissue repair across all organ systems. In periods of growth and disease, myofibroblasts can undergo a phenotypic transition characterized by an increase in extracellular matrix (ECM) deposition rate, changes in various protein expression (e.g., alpha-smooth muscle actin (αSMA)), and elevated contractility. Cell shape is known to correlate closely with stress-fiber geometry and function and is thus a critical feature of cell biophysical state. However, the relationship between myofibroblast shape and contraction is complex, even as well in regards to steady-state contractile level (basal tonus). At present, the relationship between myofibroblast shape and basal tonus in three-dimensional (3D) environments is poorly understood. Herein, we utilize the aortic valve interstitial cell (AVIC) as a representative myofibroblast to investigate the relationship between basal tonus and overall cell shape. AVICs were embedded within 3D poly(ethylene glycol) (PEG) hydrogels containing degradable peptide crosslinkers, adhesive peptide sequences, and submicron fluorescent microspheres to track the local displacement field. We then developed a methodology to evaluate the correlation between overall AVIC shape and basal tonus induced contraction. We computed a volume averaged stretch tensor ⟨U⟩ for the volume occupied by the AVIC, which had three distinct eigenvalues (λ1,2,3=1.08,0.99, and 0.89), suggesting that AVIC shape is a result of anisotropic contraction. Furthermore, the direction of maximum contraction correlated closely with the longest axis of a bounding ellipsoid enclosing the AVIC. As gel-imbedded AVICs are known to be in a stable state by 3 days of incubation used herein, this finding suggests that the overall quiescent AVIC shape is driven by the underlying stress-fiber directional structure and potentially contraction level.
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http://dx.doi.org/10.1115/1.4050915DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8299802PMC
September 2021

Right ventricular myocardial mechanics: Multi-modal deformation, microstructure, modeling, and comparison to the left ventricle.

Acta Biomater 2021 03 15;123:154-166. Epub 2020 Dec 15.

Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX 78712, USA; Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA; Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, 78712, USA. Electronic address:

The right ventricular myocardium, much like the rest of the right side of the heart, has been consistently understudied. Presently, little is known about its mechanics, its microstructure, and its constitutive behavior. In this work, we set out to provide the first data on the mechanics of the mature right ventricular myocardium in both simple shear and uniaxial loading and to compare these data to the mechanics of the left ventricular myocardium. To this end, we tested ovine tissue samples of the right and left ventricle under a comprehensive mechanical testing protocol that consisted of six simple shear modes and three tension/compression modes. After mechanical testing, we conducted a histology-based microstructural analysis on each right ventricular sample that yielded high resolution fiber distribution maps across the entire samples. Equipped with this detailed mechanical and histological data, we employed an inverse finite element framework to determine the optimal form and parameters for microstructure-based constitutive models. The results of our study show that right ventricular myocardium is less stiff then the left ventricular myocardium in the fiber direction, but similarly exhibits non-linear, anisotropic, and tension/compression asymmetric behavior with direction-dependent Poynting effect. In addition, we found that right ventricular myocardial fibers change angles transmurally and are dispersed within the sheet plane and normal to it. Through our inverse finite element analysis, we found that the Holzapfel model successfully fits these data, even when selectively informed by rudimentary microstructural information. And, we found that the inclusion of higher-fidelity microstructural data improved the Holzapfel model's predictive ability. Looking forward, this investigation is a critical step towards understanding the fundamental mechanical behavior of right ventricular myocardium and lays the groundwork for future whole-organ mechanical simulations.
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http://dx.doi.org/10.1016/j.actbio.2020.12.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7946450PMC
March 2021

FM-Track: A fiducial marker tracking software for studying cell mechanics in a three-dimensional environment.

SoftwareX 2020 Jan-Jun;11. Epub 2020 Feb 19.

James T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, Austin TX, United States.

Tracking the deformation of fiducial markers in the vicinity of living cells embedded in compliant synthetic or biological gels is a powerful means to study cell mechanics and mechanobiology in three-dimensional environments. However, current approaches to track and quantify three-dimensional (3D) fiducial marker displacements remain ad-hoc, can be difficult to implement, and may not produce reliable results. Herein, we present a compact software package entitled "FM-Track," written in the popular Python language, to facilitate feature-based particle tracking tailored for 3D cell micromechanical environment studies. FM-Track contains functions for pre-processing images, running fiducial marker tracking, and post-processing and visualization. FM-Track can thus aid the study of cellular mechanics and mechanobiology by providing an extensible software platform to more reliably extract complex local 3D cell contractile information in transparent compliant gel systems.
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http://dx.doi.org/10.1016/j.softx.2020.100417DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291167PMC
February 2020

Analyzing valve interstitial cell mechanics and geometry with spatial statistics.

J Biomech 2019 Aug 17;93:159-166. Epub 2019 Jul 17.

James T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, United States. Electronic address:

Understanding cell geometric and mechanical properties is crucial to understanding how cells sense and respond to their local environment. Moreover, changes to cell mechanical properties under varied micro-environmental conditions can both influence and indicate fundamental changes to cell behavior. Atomic Force Microscopy (AFM) is a well established, powerful tool to capture geometric and mechanical properties of cells. We have previously demonstrated substantial functional and behavioral differences between aortic and pulmonary valve interstitial cells (VIC) using AFM and subsequent models of VIC mechanical response. In the present work, we extend these studies by demonstrating that to best interpret the spatially distributed AFM data, the use of spatial statistics is required. Spatial statistics includes formal techniques to analyze spatially distributed data, and has been used successfully in the analysis of geographic data. Thus, spatially mapped AFM studies of cell geometry and mechanics are analogous to more traditional forms of geospatial data. We are able to compare the spatial autocorrelation of stiffness in aortic and pulmonary valve interstitial cells, and more accurately capture cell geometry from height recordings. Specifically, we showed that pulmonary valve interstitial cells display higher levels of spatial autocorrelation of stiffness than aortic valve interstitial cells. This suggests that aortic VICs form different stress fiber structures than their pulmonary counterparts, in addition to being more highly expressed and stiffer on average. Thus, the addition of spatial statistics can contribute to our fundamental understanding of the differences between cell types. Moving forward, we anticipate that this work will be meaningful to enhance direct analysis of experimental data and for constructing high fidelity computational of VICs and other cell models.
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http://dx.doi.org/10.1016/j.jbiomech.2019.06.028DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858609PMC
August 2019

Quantifying heart valve interstitial cell contractile state using highly tunable poly(ethylene glycol) hydrogels.

Acta Biomater 2019 09 16;96:354-367. Epub 2019 Jul 16.

James T. Willerson Center for Cardiovascular Modeling and Simulation, The Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, 240 East 24th Street, Austin, TX 78712, United States. Electronic address:

Valve interstitial cells (VIC) are the primary cell type residing within heart valve tissues. In many valve pathologies, VICs become activated and will subsequently profoundly remodel the valve tissue extracellular matrix (ECM). A primary indicator of VIC activation is the upregulation of α-smooth muscle actin (αSMA) stress fibers, which in turn increase VIC contractility. Thus, contractile state reflects VIC activation and ECM biosynthesis levels. In general, cell contraction studies have largely utilized two-dimensional substrates, which are a vastly different micro mechanical environment than 3D native leaflet tissue. To address this limitation, hydrogels have been a popular choice for studying cells in a three-dimensional environment due to their tunable properties and optical transparency, which allows for direct cell visualization. In the present study, we extended the use of hydrogels to study the active contractile behavior of VICs. Aortic VICs (AVIC) were encapsulated within poly(ethylene glycol) (PEG) hydrogels and were subjected to flexural-deformation tests to assess the state of AVIC contraction. Using a finite element model of the experimental setup, we determined the effective shear modulus μ of the constructs. An increase in μ resulting from AVIC active contraction was observed. Results further indicated that AVIC contraction had a more pronounced effect on μ in softer gels (72 ± 21% increase in μ within 2.5 kPa gels) and was dependent upon the availability of adhesion sites (0.5-1 mM CRGDS). The transparency of the gel allowed us to image AVICs directly within the hydrogel, where we observed a time-dependent decrease in volume (time constant τ=3.04 min) when the AVICs were induced into a hypertensive state. Our results indicated that AVIC contraction was regulated by both the intrinsic (unseeded) gel stiffness and the CRGDS peptide concentrations. This finding suggests that AVIC contractile state can be profoundly modulated through their local micro environment using modifiable PEG gels in a 3D micromechanical-emulating environment. Moving forward, this approach has the potential to be used towards delineating normal and diseased VIC biomechanical properties using highly tunable PEG biomaterials. STATEMENT OF SIGNIFICANCE.
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http://dx.doi.org/10.1016/j.actbio.2019.07.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717677PMC
September 2019

Understanding the mechanical link between oriented cell division and cerebellar morphogenesis.

Soft Matter 2019 Mar;15(10):2204-2215

Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA.

The cerebellum is a tightly folded structure located at the back of the head. Unlike the folds of the cerebrum, the folds of the cerebellum are aligned such that the external surface appears to be covered in parallel grooves. Experiments have shown that anchoring center initiation drives cerebellar foliation. However, the mechanism guiding the location of these anchoring centers, and subsequently cerebellar morphology, remains poorly understood. In particular, there is no definitive mechanistic explanation for the preferential emergence of parallel folds instead of an irregular folding pattern like in the cerebral cortex. Here we use mechanical modeling on the cellular and tissue scales to show that the oriented granule cell division observed in the experimental setting leads to the characteristic parallel folding pattern of the cerebellum. Specifically, we propose an agent-based model of cell clones, a strategy for propagating information from our in silico cell clones to the tissue scale, and an analytical solution backed by numerical results to understand how differential growth between the cerebellar layers drives geometric instability in three dimensional space on the tissue scale. This proposed mechanical model provides further insight into the process of anchoring center initiation and establishes a framework for future multiscale mechanical analysis of developing organs.
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http://dx.doi.org/10.1039/c8sm02231cDOI Listing
March 2019

Modeling mechanical inhomogeneities in small populations of proliferating monolayers and spheroids.

Biomech Model Mechanobiol 2018 Jun 2;17(3):727-743. Epub 2017 Dec 2.

Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, 94305, USA.

Understanding the mechanical behavior of multicellular monolayers and spheroids is fundamental to tissue culture, organism development, and the early stages of tumor growth. Proliferating cells in monolayers and spheroids experience mechanical forces as they grow and divide and local inhomogeneities in the mechanical microenvironment can cause individual cells within the multicellular system to grow and divide at different rates. This differential growth, combined with cell division and reorganization, leads to residual stress. Multiple different modeling approaches have been taken to understand and predict the residual stresses that arise in growing multicellular systems, particularly tumor spheroids. Here, we show that by using a mechanically robust agent-based model constructed with the peridynamic framework, we gain a better understanding of residual stresses in multicellular systems as they grow from a single cell. In particular, we focus on small populations of cells (1-100 s) where population behavior is highly stochastic and prior investigation has been limited. We compare the average strain energy density of cells in monolayers and spheroids using different growth and division rules and find that, on average, cells in spheroids have a higher strain energy density than cells in monolayers. We also find that cells in the interior of a growing spheroid are, on average, in compression. Finally, we demonstrate the importance of accounting for stochastic fluctuations in the mechanical environment, particularly when the cellular response to mechanical cues is nonlinear. The results presented here serve as a starting point for both further investigation with agent-based models, and for the incorporation of major findings from agent-based models into continuum scale models when explicit representation of individual cells is not computationally feasible.
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http://dx.doi.org/10.1007/s10237-017-0989-0DOI Listing
June 2018

Modeling tumor growth with peridynamics.

Biomech Model Mechanobiol 2017 08 26;16(4):1141-1157. Epub 2017 Jan 26.

Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, 94305, USA.

Computational models of tumors have the potential to connect observations made on the cellular and the tissue scales. With cellular scale models, each cell can be treated as a discrete entity, while tissue scale models typically represent tumors as a continuum. Though the discrete approach often enables a more mechanistic and biologically driven description of cellular behavior, it is often computationally intractable on the tissue scale. Here, we adapt peridynamics, a theoretical and computational approach designed to unify the mechanics of discrete and continuous media, for the growth of biological materials. The result is a computational model for tumor growth that can represent either individual cells or the tissue as a whole. We take advantage of the flexibility provided by the peridynamic framework to implement a cell division mechanism, motivated by the fact that cell division is the mechanism driving tumor growth. This paper provides a general framework for implementing a new tumor growth modeling technique.
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http://dx.doi.org/10.1007/s10237-017-0876-8DOI Listing
August 2017

Quantifying the relationship between cell division angle and morphogenesis through computational modeling.

J Theor Biol 2017 04 22;418:1-7. Epub 2017 Jan 22.

Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA. Electronic address:

When biological cells divide, they divide on a given angle. It has been shown experimentally that the orientation of cell division angle for a single cell can be described by a probability density function. However, the way in which the probability density function underlying cell division orientation influences population or tissue scale morphogenesis is unknown. Here we show that a computational approach, with thousands of stochastic simulations modeling growth and division of a population of cells, can be used to investigate this unknown. In this paper we examine two potential forms of the probability density function: a wrapped normal distribution and a binomial distribution. Our results demonstrate that for the wrapped normal distribution the standard deviation of the division angle, potentially interpreted as biological noise, controls the degree of tissue scale anisotropy. For the binomial distribution, we demonstrate a mechanism by which direction and degree of tissue scale anisotropy can be tuned via the probability of each division angle. We anticipate that the method presented in this paper and the results of these simulations will be a starting point for further investigation of this topic.
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http://dx.doi.org/10.1016/j.jtbi.2017.01.026DOI Listing
April 2017

Tri-layer wrinkling as a mechanism for anchoring center initiation in the developing cerebellum.

Soft Matter 2016 Jul 2;12(25):5613-20. Epub 2016 Jun 2.

Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA.

During cerebellar development, anchoring centers form at the base of each fissure and remain fixed in place while the rest of the cerebellum grows outward. Cerebellar foliation has been extensively studied; yet, the mechanisms that control anchoring center initiation and position remain insufficiently understood. Here we show that a tri-layer model can predict surface wrinkling as a potential mechanism to explain anchoring center initiation and position. Motivated by the cerebellar microstructure, we model the developing cerebellum as a tri-layer system with an external molecular layer and an internal granular layer of similar stiffness and a significantly softer intermediate Purkinje cell layer. Including a weak intermediate layer proves key to predicting surface morphogenesis, even at low stiffness contrasts between the top and bottom layers. The proposed tri-layer model provides insight into the hierarchical formation of anchoring centers and establishes an essential missing link between gene expression and evolution of shape.
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http://dx.doi.org/10.1039/c6sm00526hDOI Listing
July 2016

Understanding geometric instabilities in thin films via a multi-layer model.

Soft Matter 2016 Jan 4;12(3):806-16. Epub 2015 Nov 4.

Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA.

When a thin stiff film adhered to a compliant substrate is subject to compressive stresses, the film will experience a geometric instability and buckle out of plane. For high film/substrate stiffness ratios with relatively low levels of strain, the primary mode of instability will either be wrinkling or buckling delamination depending on the material and geometric properties of the system. Previous works approach these systems by treating the film and substrate as homogenous layers, either consistently perfectly attached, or perfectly unattached at interfacial flaws. However, this approach neglects systems where the film and substrate are uniformly weakly attached or where interfacial layers due to surface modifications in either the film or substrate are present. Here we demonstrate a method for accounting for these additional thin surface layers via an analytical solution verified by numerical results. The main outcome of this work is an improved understanding of how these layers influence global behavior. We demonstrate the utility of our model with applications ranging from buckling based metrology in ultrathin films, to an improved understanding of the formation of a novel surface in carbon nanotube bio-interface films. Moving forward, this model can be used to interpret experimental results, particularly for systems which deviate from traditional behavior, and aid in the evaluation and design of future film/substrate systems.
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http://dx.doi.org/10.1039/c5sm02082dDOI Listing
January 2016
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