Advanced in silico validation framework for three-dimensional traction force microscopy and application to an in vitro model of sprouting angiogenesis

Extracellular Matrix as a Driver of Chronic Lung Diseases

The extracellular matrix (ECM) is not just a three-dimensional scaffold that provides stable support for all cells in the lungs, but also an important component of chronic fibrotic airway, vascular, and interstitial diseases. It is a bioactive entity that is dynamically modulated during tissue homeostasis and disease, that controls structural and immune cell functions and drug responses, and that can release fragments that have biological activity and that can be used to monitor disease activity. There is a growing recognition of the importance of considering ECM changes in chronic airway, vascular, and interstitial diseases, including 1) compositional changes, 2) structural and organizational changes, and 3) mechanical changes and how these affect disease pathogenesis. As altered ECM biology is an important component of many lung diseases, disease models must incorporate this factor to fully recapitulate disease-driver pathways and to study potential novel therapeutic interventions. Although novel models are evolving that capture some or all of the elements of the altered ECM microenvironment in lung diseases, opportunities exist to more fully understand cell-ECM interactions that will help devise future therapeutic targets to restore function in chronic lung diseases. In this perspective article, we review evolving knowledge about the ECM's role in homeostasis and disease in the lung.

SGABU computational platform for multiscale modeling: Bridging the gap between education and research

BACKGROUND AND OBJECTIVE

In accordance with the latest aspirations in the field of bioengineering, there is a need to create a web accessible, but powerful cloud computational platform that combines datasets and multiscale models related to bone modeling, cancer, cardiovascular diseases and tissue engineering. The SGABU platform may become a powerful information system for research and education that can integrate data, extract information, and facilitate knowledge exchange with the goal of creating and developing appropriate computing pipelines to provide accurate and comprehensive biological information from the molecular to organ level.

METHODS

The datasets integrated into the platform are obtained from experimental and/or clinical studies and are mainly in tabular or image file format, including metadata. The implementation of multiscale models, is an ambitious effort of the platform to capture phenomena at different length scales, described using partial and ordinary differential equations, which are solved numerically on complex geometries with the use of the finite element method. The majority of the SGABU platform's simulation pipelines are provided as Common Workflow Language (CWL) workflows. Each of them requires creating a CWL implementation on the backend and a user-friendly interface using standard web technologies. Platform is available at https://sgabu-test.unic.kg.ac.rs/login.

RESULTS

The main dashboard of the SGABU platform is divided into sections for each field of research, each one of which includes a subsection of datasets and multiscale models. The datasets can be presented in a simple form as tabular data, or using technologies such as Plotly.js for 2D plot interactivity, Kitware Paraview Glance for 3D view. Regarding the models, the usage of Docker containerization for packing the individual tools and CWL orchestration for describing inputs with validation forms and outputs with tabular views for output visualization, interactive diagrams, 3D views and animations.

CONCLUSIONS

In practice, the structure of SGABU platform means that any of the integrated workflows can work equally well on any other bioengineering platform. The key advantage of the SGABU platform over similar efforts is its versatility offered with the use of modern, modular, and extensible technology for various levels of architecture.

An Inverse Modeling Approach to Estimate Three-Dimensional Aortic Valve Interstitial Cell Stress Fiber Force Levels

Within the aortic valve (AV) leaflet exists a population of interstitial cells (AVICs) that maintain the constituent tissues by extracellular matrix (ECM) secretion, degradation, and remodeling. AVICs can transition from a quiescent, fibroblast-like phenotype to an activated, myofibroblast phenotype in response to growth or disease. AVIC dysfunction has been implicated in AV disease processes, yet our understanding of AVIC function remains quite limited. A major characteristic of the AVIC phenotype is its contractile state, driven by contractile forces generated by the underlying stress fibers (SF). However, direct assessment of the AVIC SF contractile state and structure within physiologically mimicking three-dimensional environments remains technically challenging, as the size of single SFs are below the resolution of light microscopy. Therefore, in the present study, we developed a three-dimensional (3D) computational approach of AVICs embedded in 3D hydrogels to estimate their SF local orientations and contractile forces. One challenge with this approach is that AVICs will remodel the hydrogel, so that the gel moduli will vary spatially. We thus utilized our previous approach (Khang et al. 2023, "Estimation of Aortic Valve Interstitial Cell-Induced 3D Remodeling of Poly (Ethylene Glycol) Hydrogel Environments Using an Inverse Finite Element Approach," Acta Biomater., 160, pp. 123-133) to define local hydrogel mechanical properties. The AVIC SF model incorporated known cytosol and nucleus mechanical behaviors, with the cell membrane assumed to be perfectly bonded to the surrounding hydrogel. The AVIC SFs were first modeled as locally unidirectional hyperelastic fibers with a contractile force component. An adjoint-based inverse modeling approach was developed to estimate local SF orientation and contractile force. Substantial heterogeneity in SF force and orientations were observed, with the greatest levels of SF alignment and contractile forces occurring in AVIC protrusions. The addition of a dispersed SF orientation to the modeling approach did not substantially alter these findings. To the best of our knowledge, we report the first fully 3D computational contractile cell models which can predict locally varying stress fiber orientation and contractile force levels.

2.5D Traction Force Microscopy: Imaging three-dimensional cell forces at interfaces and biological applications

The forces that cells, tissues, and organisms exert on the surface of a soft substrate can be measured using Traction Force Microscopy (TFM), an important and well-established technique in Mechanobiology. The usual TFM technique (two-dimensional, 2D TFM) treats only the in-plane component of the traction forces and omits the out-of-plane forces at the substrate interfaces (2.5D) that turn out to be important in many biological processes such as tissue migration and tumour invasion. Here, we review the imaging, material, and analytical tools to perform "2.5D TFM" and explain how they are different from 2D TFM. Challenges in 2.5D TFM arise primarily from the need to work with a lower imaging resolution in the z-direction, track fiducial markers in three-dimensions, and reliably and efficiently reconstruct mechanical stress from substrate deformation fields. We also discuss how 2.5D TFM can be used to image, map, and understand the complete force vectors in various important biological events of various length-scales happening at two-dimensional interfaces, including focal adhesions forces, cell diapedesis across tissue monolayers, the formation of three-dimensional tissue structures, and the locomotion of large multicellular organisms. We close with future perspectives including the use of new materials, imaging and machine learning techniques to continuously improve the 2.5D TFM in terms of imaging resolution, speed, and faithfulness of the force reconstruction procedure.

A mechanobiological model for tumor spheroid evolution with application to glioblastoma: A continuum multiphysics approach

BACKGROUND

Spheroids are in vitro quasi-spherical structures of cell aggregates, eventually cultured within a hydrogel matrix, that are used, among other applications, as a technological platform to investigate tumor formation and evolution. Several interesting features can be replicated using this methodology, such as cell communication mechanisms, the effect of gradients of nutrients, or the creation of realistic 3D biological structures. The main objective of this work is to link the spheroid evolution with the mechanical activity of cells, coupled with nutrient consumption and the subsequent cell dynamics.

METHOD

We propose a continuum mechanobiological model which accounts for the most relevant phenomena that take place in tumor spheroid evolution under in vitro suspension, namely, nutrient diffusion in the spheroid, kinetics of cellular growth and death, and mechanical interactions among the cells. The model is qualitatively validated, after calibration of the model parameters, versus in vitro experiments of spheroids of different glioblastoma cell lines.

RESULTS

Our model is able to explain in a novel way quite different setups, such as spheroid growth (up to six times the initial configuration for U-87 MG cell line) or shrinking (almost half of the initial configuration for U-251 MG cell line); as the result of the mechanical interplay of cells driven by cellular evolution.

CONCLUSIONS

Glioblastoma tumor spheroid evolution is driven by mechanical interactions of the cell aggregate and the dynamical evolution of the cell population. All this information can be used to further investigate mechanistic effects in the evolution of tumors and their role in cancer disease.

Estimation of aortic valve interstitial cell-induced 3D remodeling of poly(ethylene glycol) hydrogel environments using an inverse finite element approach

Aortic valve interstitial cells (AVICs) reside within the leaflet tissues of the aortic valve and maintain and remodel its extracellular matrix components. Part of this process is a result of AVIC contractility brought about by underlying stress fibers whose behaviors can change in various disease states. Currently, it is challenging to directly investigate AVIC contractile behaviors within dense leaflet tissues. As a result, optically clear poly (ethylene glycol) hydrogel matrices have been used to study AVIC contractility via 3D traction force microscopy (3DTFM). However, the local stiffness of the hydrogel is difficult to measure directly and is further confounded by the remodeling activity of the AVIC. Ambiguity in hydrogel mechanics can lead to large errors in computed cellular tractions. Herein, we developed an inverse computational approach to estimate AVIC-induced remodeling of the hydrogel material. The model was validated with test problems comprised of an experimentally measured AVIC geometry and prescribed modulus fields containing unmodified, stiffened, and degraded regions. The inverse model estimated the ground truth data sets with high accuracy. When applied to AVICs assessed via 3DTFM, the model estimated regions of significant stiffening and degradation in the vicinity of the AVIC. We observed that stiffening was largely localized at AVIC protrusions, likely a result of collagen deposition as confirmed by immunostaining. Degradation was more spatially uniform and present in regions further away from the AVIC, likely a result of enzymatic activity. Looking forward, this approach will allow for more accurate computation of AVIC contractile force levels. STATEMENT OF SIGNIFICANCE: The aortic valve (AV), positioned between the left ventricle and the aorta, prevents retrograde flow into the left ventricle. Within the AV tissues reside a resident population of aortic valve interstitial cells (AVICs) that replenish, restore, and remodel extracellular matrix components. Currently, it is technically challenging to directly investigate AVIC contractile behaviors within the dense leaflet tissues. As a result, optically clear hydrogels have been used to study AVIC contractility through means of 3D traction force microscopy. Herein, we developed a method to estimate AVIC-induced remodeling of PEG hydrogels. This method was able to accurately estimate regions of significant stiffening and degradation induced by the AVIC and allows a deeper understanding of AVIC remodeling activity, which can differ in normal and disease conditions.

Adhesive peptide and polymer density modulate 3D cell traction forces within synthetic hydrogels

Cell-extracellular matrix forces provide pivotal signals regulating diverse physiological and pathological processes. Although mechanobiology has been widely studied in two-dimensional configurations, limited research has been conducted in three-dimensional (3D) systems due to the complex nature of mechanics and cellular behaviors. In this study, we established a platform integrating a well-defined synthetic hydrogel system (PEG-4MAL) with 3D traction force microscopy (TFM) methodologies to evaluate deformation and force responses within synthetic microenvironments, providing insights that are not tractable using biological matrices because of the interdependence of biochemical and biophysical properties and complex mechanics. We dissected the contributions of adhesive peptide density and polymer density, which determines hydrogel stiffness, to 3D force generation for fibroblasts. A critical threshold of adhesive peptide density at a constant matrix elasticity is required for cells to generate 3D forces. Furthermore, matrix displacements and strains decreased with matrix stiffness whereas stresses, and tractions increased with matrix stiffness until reaching constant values at higher stiffness values. Finally, Rho-kinase-dependent contractility and vinculin expression are required to generate significant 3D forces in both collagen and synthetic hydrogels. This research establishes a tunable platform for the study of mechanobiology and provides new insights into how cells sense and transmit forces in 3D.

Comparison of direct and inverse methods for 2.5D traction force microscopy

Essential cellular processes such as cell adhesion, migration and division strongly depend on mechanical forces. The standard method to measure cell forces is traction force microscopy (TFM) on soft elastic substrates with embedded marker beads. While in 2D TFM one only reconstructs tangential forces, in 2.5D TFM one also considers normal forces. Here we present a systematic comparison between two fundamentally different approaches to 2.5D TFM, which in particular require different methods to deal with noise in the displacement data. In the direct method, one calculates strain and stress tensors directly from the displacement data, which in principle requires a divergence correction. In the inverse method, one minimizes the difference between estimated and measured displacements, which requires some kind of regularization. By calculating the required Green's functions in Fourier space from Boussinesq-Cerruti potential functions, we first derive a new variant of 2.5D Fourier Transform Traction Cytometry (FTTC). To simulate realistic traction patterns, we make use of an analytical solution for Hertz-like adhesion patches. We find that FTTC works best if only tangential forces are reconstructed, that 2.5D FTTC is more precise for small noise, but that the performance of the direct method approaches the one of 2.5D FTTC for larger noise, before both fail for very large noise. Moreover we find that a divergence correction is not really needed for the direct method and that it profits more from increased resolution than the inverse method.