An agent-based model for cell microenvironment simulation using FLAMEGPU2.

This work presents an advanced agent-based model developed within the FLAMEGPU2 framework, aimed at simulating the intricate dynamics of cell microenvironments. Our primary objective is to showcase FLAMEGPU2's potential in modelling critical features such as cell-cell and cell-ECM interactions, species diffusion, vascularisation, cell migration, and/or cell cycling. By doing so, we provide a versatile template that serves as a foundational platform for researchers to model specific biological mechanisms or processes. We highlight the utility of our approach as a microscale component within multiscale frameworks. Through four example applications, we demonstrate the model's versatility in capturing phenomena such as strain-stiffening behaviour of hydrogels, cell migration patterns within hydrogels, spheroid formation and fibre reorientation, and the simulation of diffusion processes within a vascularised and deformable domain. This work aims to bridge the gap between computational efficiency and biological fidelity, offering a scalable and flexible platform to advance our understanding of tissue biology and engineering.

Brain tissue mechanics is governed by microscale relations of the tissue constituents.

Local mechanical tissue properties are a critical regulator of cell function in the central nervous system (CNS) during development and disorder. However, we still don't fully understand how the mechanical properties of individual tissue constituents, such as cell nuclei or myelin, determine tissue mechanics. Here we developed a model predicting local tissue mechanics, which induces non-affine deformations of the tissue components. Using the mouse hippocampus and cerebellum as model systems, we show that considering individual tissue components alone, as identified by immunohistochemistry, is not sufficient to reproduce the local mechanical properties of CNS tissue. Our results suggest that brain tissue shows a universal response to applied forces that depends not only on the amount and stiffness of the individual tissue constituents but also on the way how they assemble. Our model may unify current incongruences between the mechanics of soft biological tissues and the underlying constituents and facilitate the design of better biomedical materials and engineered tissues. To this end, we provide a freely-available platform to predict local tissue elasticity upon providing immunohistochemistry images and stiffness values for the constituents of the tissue.

A multiscale orchestrated computational framework to reveal emergent phenomena in neuroblastoma.

Neuroblastoma is a complex and aggressive type of cancer that affects children. Current treatments involve a combination of surgery, chemotherapy, radiotherapy, and stem cell transplantation. However, treatment outcomes vary due to the heterogeneous nature of the disease. Computational models have been used to analyse data, simulate biological processes, and predict disease progression and treatment outcomes. While continuum cancer models capture the overall behaviour of tumours, and agent-based models represent the complex behaviour of individual cells, multiscale models represent interactions at different organisational levels, providing a more comprehensive understanding of the system. In 2018, the PRIMAGE consortium was formed to build a cloud-based decision support system for neuroblastoma, including a multi-scale model for patient-specific simulations of disease progression. In this work we have developed this multi-scale model that includes data such as patient's tumour geometry, cellularity, vascularization, genetics and type of chemotherapy treatment, and integrated it into an online platform that runs the simulations on a high-performance computation cluster using Onedata and Kubernetes technologies. This infrastructure will allow clinicians to optimise treatment regimens and reduce the number of costly and time-consuming clinical trials. This manuscript outlines the challenging framework's model architecture, data workflow, hypothesis, and resources employed in its development.

From individual to collective 3D cancer dissemination: roles of collagen concentration and TGF-ß.

Cancer cells have the ability to migrate from the primary (original) site to other places in the body. The extracellular matrix affects cancer cell migratory capacity and has been correlated with tissue-specific spreading patterns. However, how the matrix orchestrates these behaviors remains unclear. Here, we investigated how both higher collagen concentrations and TGF-ß regulate the formation of H1299 cell (a non-small cell lung cancer cell line) spheroids within 3D collagen-based matrices and promote cancer cell invasive capacity. We show that at low collagen concentrations, tumor cells move individually and have moderate invasive capacity, whereas when the collagen concentration is increased, the formation of cell clusters is promoted. In addition, when the concentration of TGF-ß in the microenvironment is lower, most of the clusters are aggregates of cancer cells with a spheroid-like morphology and poor migratory capacity. In contrast, higher concentrations of TGF-ß induced the formation of clusters with a notably higher invasive capacity, resulting in clear strand-like collective cell migration. Our results show that the concentration of the extracellular matrix is a key regulator of the formation of tumor clusters that affects their development and growth. In addition, chemical factors create a microenvironment that promotes the transformation of idle tumor clusters into very active, invasive tumor structures. These results collectively demonstrate the relevant regulatory role of the mechano-chemical microenvironment in leading the preferential metastasis of tumor cells to specific tissues with high collagen concentrations and TFG-ß activity.

A web-based application for automated quantification of chemical gradients induced in microfluidic devices.

Advances in microfabrication have allowed the development and popularization of microfluidic devices, which are powerful tools to recreate three-dimensional (3-D) biologically relevant in vitro models. These microenvironments are usually generated by using hydrogels and induced chemical gradients. Going further, computational models enable, after validation, the simulation of such conditions without the necessity of real experiments, thus saving costs and time. In this work we present a web-based application that allows, based on a previous numerical model, the assessment of different chemical gradients induced within a 3-D extracellular matrix. This application enables the estimation of the spatio-temporal chemical distribution inside microfluidic devices, by defining a first set of parameters characterizing the chip geometry, and a second set characterizing the diffusion properties of the hydrogel-based matrix. The simulated chemical concentration profiles generated within a synthetic hydrogel are calculated remotely on a server and returned to the website in less than 3 min, thus offering a quick automatic quantification to any user. To ensure the day-to-day applicability, user requirements were investigated prior to tool development, pre-selecting some of the most common geometries. The tool is freely available online, after user registration, on http://m2be.unizar.es/insilico_cell under the software tab. Four different microfluidic device geometries were defined to study the dependence of the geometrical parameters onto the gradient formation processes. The numerical predictions demonstrate that growth factor diffusion within 3-D matrices strongly depends not only on the physics of diffusion, but also on the geometrical parameters that characterizes these complex devices. Additionally, the effect of the combination of different hydrogels inside a microfluidic device was studied. The automatization of microfluidic device geometries generation provide a powerful tool which facilitates to any user the possibility to automatically create its own microfluidic device, greatly reducing the experimental validation processes and advancing in the understanding of in vitro 3-D cell responses without the necessity of using commercial software or performing real testing experiments.

Degradation of extracellular matrix regulates osteoblast migration: A microfluidic-based study.

Bone regeneration is strongly dependent on the capacity of cells to move in a 3D microenvironment, where a large cascade of signals is activated. To improve the understanding of this complex process and to advance in the knowledge of the role of each specific signal, it is fundamental to analyze the impact of each factor independently. Microfluidic-based cell culture is an appropriate technology to achieve this objective, because it allows recreating realistic 3D local microenvironments by taking into account the extracellular matrix, cells and chemical gradients in an independent or combined scenario. The main aim of this work is to analyze the impact of extracellular matrix properties and growth factor gradients on 3D osteoblast movement, as well as the role of cell matrix degradation. For that, we used collagen-based hydrogels, with and without crosslinkers, under different chemical gradients, and eventually inhibiting metalloproteinases to tweak matrix degradation. We found that osteoblast's 3D migratory patterns were affected by the hydrogel properties and the PDGF-BB gradient, although the strongest regulatory factor was determined by the ability of cells to remodel the matrix.

Quantifying 3D chemotaxis in microfluidic-based chips with step gradients of collagen hydrogel concentrations.

Cell migration is an essential process involved in crucial stages of tissue formation, regeneration or immune function as well as in pathological processes including tumor development or metastasis. During the last few years, the effect of gradients of soluble molecules on cell migration has been widely studied, and complex systems have been used to analyze cell behavior under simultaneous mechano-chemical stimuli. Most of these chemotactic assays have, however, focused on specific substrates in 2D. The aim of the present work is to develop a novel microfluidic-based chip that allows the long-term chemoattractant effect of growth factors (GFs) on 3D cell migration to be studied, while also providing the possibility to analyze the influence of the interface generated between different adjacent hydrogels. Namely, 1.5, 2, 2.5 and 4 mg ml-1 concentrations of collagen type I were alternatively combined with 5, 10 or 50 ng ml-1 concentrations of PDGF and VEGF (as a negative control). To achieve this goal, we have designed a new microfluidic device including three adjacent chambers to introduce hydrogels that allow the generation of a collagen concentration step gradient. This versatile and simple platform was tested by using dermal human fibroblasts embedded in 3D collagen matrices. Images taken over a week were processed to quantify the number of cells in each zone. We found, in terms of cell distribution, that the presence of PDGF, especially in small concentrations, was a strong chemoattractant for dermal human fibroblasts across the gels regardless of their collagen concentration and step gradient direction, whereas the effects of VEGF or collagen step gradient concentrations alone were negligible.

Fibroblast Migration in 3D is Controlled by Haptotaxis in a Non-muscle Myosin II-Dependent Manner.

Cell migration in 3D is a key process in many physiological and pathological processes. Although valuable knowledge has been accumulated through analysis of various 2D models, some of these insights are not directly applicable to migration in 3D. In this study, we have confined biomimetic hydrogels within microfluidic platforms in the presence of a chemoattractant (platelet-derived growth factor-BB). We have characterized the migratory responses of human fibroblasts within them, particularly focusing on the role of non-muscle myosin II. Our results indicate a prominent role for myosin II in the integration of chemotactic and haptotactic migratory responses of fibroblasts in 3D confined environments.

Mechano-sensing and cell migration: a 3D model approach.

Cell migration is essential for tissue development in different physiological and pathological conditions. It is a complex process orchestrated by chemistry, biological factors, microstructure and surrounding mechanical properties. Focusing on the mechanical interactions, cells do not only exert forces on the matrix that surrounds them, but they also sense and react to mechanical cues in a process called mechano-sensing. Here, we hypothesize the involvement of mechano-sensing in the regulation of directional cell migration through a three-dimensional (3D) matrix. For this purpose, we develop a 3D numerical model of individual cell migration, which incorporates the mechano-sensing process of the cell as the main mechanism regulating its movement. Consistent with this hypothesis, we found that factors, such as substrate stiffness, boundary conditions and external forces, regulate specific and distinct cell movements.