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

Mathematical model of mechano-sensing and mechanically induced collective motility of cells on planar elastic substrates

Cells mechanically interact with their environment to sense, for example, topography, elasticity and mechanical cues from other cells. Mechano-sensing has profound effects on cellular behaviour, including motility. The current study aims to develop a mathematical model of cellular mechano-sensing on planar elastic substrates and demonstrate the model's predictive capabilities for the motility of individual cells in a colony. In the model, a cell is assumed to transmit an adhesion force, derived from a dynamic focal adhesion integrin density, that locally deforms a substrate, and to sense substrate deformation originating from neighbouring cells. The substrate deformation from multiple cells is expressed as total strain energy density with a spatially varying gradient. The magnitude and direction of the gradient at the cell location define the cell motion. Cell-substrate friction, partial motion randomness, and cell death and division are included. The substrate deformation by a single cell and the motility of two cells are presented for several substrate elasticities and thicknesses. The collective motility of 25 cells on a uniform substrate mimicking the closure of a circular wound of 200 µm is predicted for deterministic and random motion. Cell motility on substrates with varying elasticity and thickness is explored for four cells and 15 cells, the latter again mimicking wound closure. Wound closure by 45 cells is used to demonstrate the simulation of cell death and division during migration. The mathematical model can adequately simulate the mechanically induced collective cell motility on planar elastic substrates. The model is suitable for extension to other cell and substrates shapes and the inclusion of chemotactic cues, offering the potential to complement in vitro and in vivo studies.

A bone-on-a-chip collagen hydrogel-based model using pre-differentiated adipose-derived stem cells for personalized bone tissue engineering

Mesenchymal stem cells have contributed to the continuous progress of tissue engineering and regenerative medicine. Adipose-derived stem cells (ADSC) possess many advantages compared to other origins including easy tissue harvesting, self-renewal potential, and fast population doubling time. As multipotent cells, they can differentiate into osteoblastic cell linages. In vitro bone models are needed to carry out an initial safety assessment in the study of novel bone regeneration therapies. We hypothesized that 3D bone-on-a-chip models containing ADSC could closely recreate the physiological bone microenvironment and promote differentiation. They represent an intermedium step between traditional 2D-in vitro and in vivo experiments facilitating the screening of therapeutic molecules while saving resources. Herein, we have differentiated ADSC for 7 and 14 days and used them to fabricate in vitro bone models by embedding the pre-differentiated cells in a 3D collagen matrix placed in a microfluidic chip. Osteogenic markers such as alkaline phosphatase activity, calcium mineralization, changes on cell morphology, and expression of specific proteins (bone sialoprotein 2, dentin matrix acidic phosphoprotein-1, and osteocalcin) were evaluated to determine cell differentiation potential and evolution. This is the first miniaturized 3D-in vitro bone model created from pre-differentiated ADSC embedded in a hydrogel collagen matrix which could be used for personalized bone tissue engineering.

Characterization of mutant versions of the R-RAS2/TC21 GTPase found in tumors

The R-RAS2 GTP hydrolase (GTPase) (also known as TC21) has been traditionally considered quite similar to classical RAS proteins at the regulatory and signaling levels. Recently, a long-tail hotspot mutation targeting the R-RAS2/TC21 Gln⁷² residue (Q72L) was identified as a potent oncogenic driver. Additional point mutations were also found in other tumors at low frequencies. Despite this, little information is available regarding the transforming role of these mutant versions and their relevance for the tumorigenic properties of already-transformed cancer cells. Here, we report that many of the RRAS2 mutations found in human cancers are highly transforming when expressed in immortalized cell lines. Moreover, the expression of endogenous R-RAS2^Q72L is important for maintaining optimal levels of PI3K and ERK activities as well as for the adhesion, invasiveness, proliferation, and mitochondrial respiration of ovarian and breast cancer cell lines. Endogenous R-RAS2^Q72L also regulates gene expression programs linked to both cell adhesion and inflammatory/immune-related responses. Endogenous R-RAS2^Q72L is also quite relevant for the in vivo tumorigenic activity of these cells. This dependency is observed even though these cancer cell lines bear concurrent gain-of-function mutations in genes encoding RAS signaling elements. Finally, we show that endogenous R-RAS2, unlike the case of classical RAS proteins, specifically localizes in focal adhesions. Collectively, these results indicate that gain-of-function mutations of R-RAS2/TC21 play roles in tumor initiation and maintenance that are not fully redundant with those regulated by classical RAS oncoproteins.

A novel integrated experimental and computational approach to unravel fibroblast motility in response to chemical gradients in 3D collagen matrices

Fibroblasts play an essential role in tissue repair and regeneration as they migrate to wounded areas to secrete and remodel the extracellular matrix. Fibroblasts recognize chemical substances such as growth factors, which enhance their motility towards the wounded tissues through chemotaxis. Although several studies have characterized single-cell fibroblast motility before, the migration patterns of fibroblasts in response to external factors have not been fully explored in 3D environments. We present a study that combines experimental and computational efforts to characterize the effect of chemical stimuli on the invasion of 3D collagen matrices by fibroblasts. Experimentally, we used microfluidic devices to create chemical gradients using collagen matrices of distinct densities. We evaluated how cell migration patterns were affected by the presence of growth factors and the mechanical properties of the matrix. Based on these results, we present a discrete-based computational model to simulate cell motility, which we calibrated through the quantitative comparison of experimental and computational data via Bayesian optimization. By combining these approaches, we predict that fibroblasts respond to both the presence of chemical factors and their spatial location. Furthermore, our results show that the presence of these chemical gradients could be reproduced by our computational model through increases in the magnitude of cell-generated forces and enhanced cell directionality. Although these model predictions require further experimental validation, we propose that our framework can be applied as a tool that takes advantage of experimental data to guide the calibration of models and predict which mechanisms at the cellular level may justify the experimental findings. Consequently, these new insights may also guide the design of new experiments, tailored to validate the variables of interest identified by the model.

A microfluidic-based analysis of 3D macrophage migration after stimulation by Mycobacterium, Salmonella and Escherichia

Macrophages play an essential role in the process of recognition and containment of microbial infections. These immune cells are recruited to infectious sites to reach and phagocytose pathogens. Specifically, in this article, bacteria from the genus Mycobacterium, Salmonella and Escherichia, were selected to study the directional macrophage movement towards different bacterial fractions. We recreated a three-dimensional environment in a microfluidic device, using a collagen-based hydrogel that simulates the mechanical microarchitecture associated to the Extra Cellular Matrix (ECM). First, we showed that macrophage migration is affected by the collagen concentration of their environment, migrating greater distances at higher velocities with decreasing collagen concentrations. To recreate the infectious microenvironment, macrophages were exposed to lateral gradients of bacterial fractions obtained from the intracellular pathogens M. tuberculosis and S. typhimurium. Our results showed that macrophages migrated directionally, and in a concentration-dependent manner, towards the sites where bacterial fractions are located, suggesting the presence of attractants molecules in all the samples. We confirmed that purified M. tuberculosis antigens, as ESAT-6 and CFP-10, stimulated macrophage recruitment in our device. Finally, we also observed that macrophages migrate towards fractions from non-pathogenic bacteria, such as M. smegmatis and Escherichia coli. In conclusion, our microfluidic device is a useful tool which opens new perspectives to study the recognition of specific antigens by innate immune cells.

A mechanistic protrusive-based model for 3D cell migration

Cell migration is essential for a variety of biological processes, such as embryogenesis, wound healing, and the immune response. After more than a century of research-mainly on flat surfaces-, there are still many unknowns about cell motility. In particular, regarding how cells migrate within 3D matrices, which more accurately replicate in vivo conditions. We present a novel in silico model of 3D mesenchymal cell migration regulated by the chemical and mechanical profile of the surrounding environment. This in silico model considers cell's adhesive and nuclear phenotypes, the effects of the steric hindrance of the matrix, and cells ability to degradate the ECM. These factors are crucial when investigating the increasing difficulty that migrating cells find to squeeze their nuclei through dense matrices, which may act as physical barriers. Our results agree with previous in vitro observations where fibroblasts cultured in collagen-based hydrogels did not durotax toward regions with higher collagen concentrations. Instead, they exhibited an adurotactic behavior, following a more random trajectory. Overall, cell's migratory response in 3D domains depends on its phenotype, and the properties of the surrounding environment, that is, 3D cell motion is strongly dependent on the context.

Investigations on T cell transmigration in a human skin-on-chip (SoC) model

A microfluidics-based three-dimensional skin-on-chip (SoC) model is developed in this study to enable quantitative studies of transendothelial and transepithelial migration of human T lymphocytes in mimicked skin inflammatory microenvironments and to test new drug candidates. The keys results include 1) CCL20-dependent T cell transmigration is significantly inhibited by an engineered CCL20 locked dimer (CCL20LD), supporting the potential immunotherapeutic use of CCL20LD for treating skin diseases such as psoriasis; 2) transepithelial migration of T cells in response to a CXCL12 gradient mimicking T cell egress from the skin is significantly reduced by a sphingosine-1-phosphate (S1P) background, suggesting the role of S1P for T cell retention in inflamed skin tissues; and 3) T cell transmigration is induced by inflammatory cytokine stimulated epithelial cells in the SoC model. Collectively, the developed SoC model recreates a dynamic multi-cellular micro-environment that enables quantitative studies of T cell transmigration at a single cell level in response to physiological cutaneous inflammatory mediators and potential drugs.

Overview of Current Advances in Extrusion Bioprinting for Skin Applications

Bioprinting technologies, which have the ability to combine various human cell phenotypes, signaling proteins, extracellular matrix components, and other scaffold-like biomaterials, are currently being exploited for the fabrication of human skin in regenerative medicine. We performed a systematic review to appraise the latest advances in 3D bioprinting for skin applications, describing the main cell phenotypes, signaling proteins, and bioinks used in extrusion platforms. To understand the current limitations of this technology for skin bioprinting, we briefly address the relevant aspects of skin biology. This field is in the early stage of development, and reported research on extrusion bioprinting for skin applications has shown moderate progress. We have identified two major trends. First, the biomimetic approach uses cell-laden natural polymers, including fibrinogen, decellularized extracellular matrix, and collagen. Second, the material engineering line of research, which is focused on the optimization of printable biomaterials that expedite the manufacturing process, mainly involves chemically functionalized polymers and reinforcement strategies through molecular blending and postprinting interventions, i.e., ionic, covalent, or light entanglement, to enhance the mechanical properties of the construct and facilitate layer-by-layer deposition. Skin constructs manufactured using the biomimetic approach have reached a higher level of complexity in biological terms, including up to five different cell phenotypes and mirroring the epidermis, dermis and hypodermis. The confluence of the two perspectives, representing interdisciplinary inputs, is required for further advancement toward the future translation of extrusion bioprinting and to meet the urgent clinical demand for skin equivalents.

Primary Human Osteoblasts Cultured in a 3D Microenvironment Create a Unique Representative Model of Their Differentiation Into Osteocytes

Microengineered systems provide an in vitro strategy to explore the variability of individual patient response to tissue engineering products, since they prefer the use of primary cell sources representing the phenotype variability. Traditional in vitro systems already showed that primary human osteoblasts embedded in a 3D fibrous collagen matrix differentiate into osteocytes under specific conditions. Here, we hypothesized that translating this environment to the organ-on-a-chip scale creates a minimal functional unit to recapitulate osteoblast maturation toward osteocytes and matrix mineralization. Primary human osteoblasts were seeded in a type I collagen hydrogel, to establish the role of lower (2.5 × 10⁵ cells/ml) and higher (1 × 10⁶ cells/ml) cell density on their differentiation into osteocytes. A custom semi-automatic image analysis software was used to extract quantitative data on cellular morphology from brightfield images. The results are showing that cells cultured at a high density increase dendrite length over time, stop proliferating, exhibit dendritic morphology, upregulate alkaline phosphatase (ALP) activity, and express the osteocyte marker dental matrix protein 1 (DMP1). On the contrary, cells cultured at lower density proliferate over time, do not upregulate ALP and express the osteoblast marker bone sialoprotein 2 (BSP2) at all timepoints. Our work reveals that microengineered systems create unique conditions to capture the major aspects of osteoblast differentiation into osteocytes with a limited number of cells. We propose that the microengineered approach is a functional strategy to create a patient-specific bone tissue model and investigate the individual osteogenic potential of the patient bone cells.

Biofabrication Strategies and Engineered In Vitro Systems for Vascular Mechanobiology

The vascular system is integral for maintaining organ-specific functions and homeostasis. Dysregulation in vascular architecture and function can lead to various chronic or acute disorders. Investigation of the role of the vascular system in health and disease has been accelerated through the development of tissue-engineered constructs and microphysiological on-chip platforms. These in vitro systems permit studies of biochemical regulation of vascular networks and parenchymal tissue and provide mechanistic insights into the biophysical and hemodynamic forces acting in organ-specific niches. Detailed understanding of these forces and the mechanotransductory pathways involved is necessary to develop preventative and therapeutic strategies targeting the vascular system. This review describes vascular structure and function, the role of hemodynamic forces in maintaining vascular homeostasis, and measurement approaches for cell and tissue level mechanical properties influencing vascular phenomena. State-of-the-art techniques for fabricating in vitro microvascular systems, with varying degrees of biological and engineering complexity, are summarized. Finally, the role of vascular mechanobiology in organ-specific niches and pathophysiological states, and efforts to recapitulate these events using in vitro microphysiological systems, are explored. It is hoped that this review will help readers appreciate the important, but understudied, role of vascular-parenchymal mechanotransduction in health and disease toward developing mechanotherapeutics for treatment strategies.

An iterative finite element-based method for solving inverse problems in traction force microscopy

BACKGROUND AND OBJECTIVE

During the last years different model solutions were proposed for solving cell forces under different conditions. The solution relies on a deformation field that is obtained under cell relaxation with a chemical cocktail. Once the deformation field of the matrix is determined, cell forces can be computed by an inverse algorithm, given the mechanical properties of the matrix. Most of the Traction Force Microscopy (TFM) methods presented so far relied on a linear stress-strain response of the matrix. However, the mechanical response of some biopolymer networks, such as collagen gels is more complex. In this work, we present a numerical method for solving cell forces on non-linear materials.

METHODS

The proposed method relies on solving the inverse problem based on an iterative optimization. The objective function is defined by least-square minimization of the difference between the target and the current computed deformed configuration of the cell, and the iterative formulation is based on the solution of several direct mechanical problems. The model presents a well-posed discretized inverse elasticity problem in the absence of regularization. The algorithm can be easily implemented in any kind of Finite Element (FE) code as a sequence of different standard FE analysis.

RESULTS

To illustrate the proposed iterative formulation we apply the theoretical model to some illustrative examples by using real experimental data of Normal Human Dermal Fibroblast cells (NHDF) migrating inside a 2 mg/ml collagen-based gel. Different examples of application have been simulated to test the inverse numerical model proposed and to investigate the effect of introducing the correct cell properties onto the obtained cell forces. The algorithm converges after a small number of iterations, generating errors of around 5% for the tractions field in the cell contour domain. The resulting maximum traction values increased by 11% as a consequence of doubling the mechanical properties of the cell domain.

CONCLUSIONS

With the results generated from computations we demonstrate the application of the algorithm and explain how the mechanical properties of both, the cell and the gel, domains are important for arriving to the correct results when using inverse traction force reconstruction algorithms, however, have only a minor effect on the resulting traction values.

Topotactic Fibrillogenesis of Freeze-Cast Microridged Collagen Scaffolds for 3D Cell Culture

Type I collagen is the main component of the extracellular matrix (ECM). In vitro, under a narrow window of physicochemical conditions, type I collagen self-assembles to form complex supramolecular architectures reminiscent of those found in native ECM. Presently, a major challenge in collagen-based biomaterials is to couple the delicate collagen fibrillogenesis events with a controlled shaping process in non-denaturating conditions. In this work, an ice-templating approach promoting the structuration of collagen into macroporous monoliths is used. Instead of common solvent removal procedures, a new topotactic conversion approach yielding self-assembled ordered fibrous materials is implemented. These collagen-only, non-cross-linked scaffolds exhibit uncommon mechanical properties in the wet state, with a Young's modulus of 33 ± 12 kPa, an ultimate tensile stress of 33 ± 6 kPa, and a strain at failure of 105 ± 28%. With the help of the ice-patterned microridge features, normal human dermal fibroblasts and C2C12 murine myoblasts successfully migrate and form highly aligned populations within the resulting three-dimensional (3D) collagen scaffolds. These results open a new pathway to the development of new tissue engineering scaffolds ordered across various organization levels from the molecule to the macropore and are of particular interest for biomedical applications where large-scale 3D cell alignment is needed such as for muscular or nerve reconstruction.

Microfluidic modelling of the tumor microenvironment for anti-cancer drug development

Cancer is the leading cause of death worldwide. The complex and disorganized tumor microenvironment makes it very difficult to treat this disease. The most common in vitro drug screening method now is based on 2D culture models which poorly represent actual tumors. Therefore, many 3D tumor models which are more physiologically relevant have been developed to conduct in vitro drug screening and alleviate this situation. Among all these models, the microfluidic tumor model has the unique advantage of recapitulating the tumor microenvironment in a comparatively easier and representative fashion. While there are many review papers available on the related topic of microfluidic tumor models, in this review we aim to focus more on the possibility of generating "clinically actionable information" from these microfluidic systems, besides scientific insight. Our topics cover the tumor microenvironment, conventional 2D and 3D cultures, animal models, and microfluidic tumor models, emphasizing their link to anti-cancer drug discovery and personalized medicine.

Integration of in vitro and in silico Models Using Bayesian Optimization With an Application to Stochastic Modeling of Mesenchymal 3D Cell Migration

Cellular migration plays a crucial role in many aspects of life and development. In this paper, we propose a computational model of 3D migration that is solved by means of the tau-leaping algorithm and whose parameters have been calibrated using Bayesian optimization. Our main focus is two-fold: to optimize the numerical performance of the mechano-chemical model as well as to automate the calibration process of in silico models using Bayesian optimization. The presented mechano-chemical model allows us to simulate the stochastic behavior of our chemically reacting system in combination with mechanical constraints due to the surrounding collagen-based matrix. This numerical model has been used to simulate fibroblast migration. Moreover, we have performed in vitro analysis of migrating fibroblasts embedded in 3D collagen-based fibrous matrices (2 mg/ml). These in vitro experiments have been performed with the main objective of calibrating our model. Nine model parameters have been calibrated testing 300 different parametrizations using a completely automatic approach. Two competing evaluation metrics based on the Bhattacharyya coefficient have been defined in order to fit the model parameters. These metrics evaluate how accurately the in silico model is replicating in vitro measurements regarding the two main variables quantified in the experimental data (number of protrusions and the length of the longest protrusion). The selection of an optimal parametrization is based on the balance between the defined evaluation metrics. Results show how the calibrated model is able to predict the main features observed in the in vitro experiments.

3D Cell Migration Studies for Chemotaxis on Microfluidic-Based Chips: A Comparison between Cardiac and Dermal Fibroblasts

Fibroblast migration to damaged zones in different tissues is crucial to regenerate and recuperate their functional activity. However, fibroblast migration patterns have hardly been studied in disease terms. Here, we study this fundamental process in dermal and cardiac fibroblasts by means of microfluidic-based experiments, which simulate a three-dimensional matrix in which fibroblasts are found in physiological conditions. Cardiac fibroblasts show a higher mean and effective speed, as well as greater contractile force, in comparison to dermal fibroblasts. In addition, we generate chemical gradients to study fibroblast response to platelet derived growth factor (PDGF) and transforming growth factor beta (TGF-β) gradients. Dermal fibroblasts were attracted to PDGF, whereas cardiac fibroblasts are not. Notwithstanding, cardiac fibroblasts increased their mean and effective velocity in the presence of TGF-β. Therefore, given that we observe that the application of these growth factors does not modify fibroblasts’ morphology, these alterations in the migration patterns may be due to an intracellular regulation.

Combined experimental and computational characterization of crosslinked collagen-based hydrogels

Collagen hydrogels are widely used for in-vitro experiments and tissue engineering applications. Their use has been extended due to their biocompatibility with cells and their capacity to mimic biological tissues; nevertheless their mechanical properties are not always optimal for these purposes. Hydrogels are formed by a network of polymer filaments embedded on an aqueous substrate and their mechanical properties are mainly defined by the filament network architecture and the individual filament properties. To increase properties of native collagen, such as stiffness or strain-stiffening, these networks can be modified by adding crosslinking agents that alter the network architecture, increasing the unions between filaments. In this work, we have investigated the effect of one crosslinking agent, transglutaminase, in collagen hydrogels with varying collagen concentration. We have observed a linear dependency of the gel rigidity on the collagen concentration. Moreover, the addition of transglutaminase has induced an earlier strain-stiffening of the collagen gels. In addition, to better understand the mechanical implications of collagen concentration and crosslinkers inclusion, we have adapted an existing computational model, based on the worm-like chain model (WLC), to reproduce the mechanical behavior of the collagen gels. With this model we can estimate the parameters of the biopolymer networks without more sophisticated techniques, such as image processing or network reconstruction, or, inversely, predict the mechanical properties of a defined collagen network.

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.

A tuneable microfluidic system for long duration chemotaxis experiments in a 3D collagen matrix

In many cell types, migration can be oriented towards a chemical stimulus. In mammals, for example, embryonic cells migrate to follow developmental cues, immune cells migrate toward sites of inflammation, and cancer cells migrate away from the primary tumour and toward blood vessels during metastasis. Understanding how cells migrate in 3D environments in response to chemical cues is thus crucial to understanding directed migration in normal and disease states. To date, chemotaxis in mammalian cells has been primarily studied using 2D migration models. However, it is becoming increasingly clear that the mechanisms by which cells migrate in 2D and 3D environments dramatically differ, and cells in their native environments are confronted with a complex chemical milieu. To address these issues, we developed a microfluidic device to monitor the behaviour of cells embedded in a 3D collagen matrix in the presence of complex concentration fields of chemoattractants. This tuneable microsystem enables the generation of (1) homogeneous, stationary gradients set by a purely diffusive mechanism, or (2) spatially evolving, stationary gradients, set by a convection-diffusion mechanism. The device allows for stable gradients over several days and is large enough to study the behaviour of large cell aggregates. We observe that primary mature dendritic cells respond uniformly to homogeneous diffusion gradients, while cell behaviour is highly position-dependent in spatially variable convection-diffusion gradients. In addition, we demonstrate a directed response of cancer cells migrating away from tumour-like aggregates in the presence of soluble chemokine gradients. Together, this microfluidic device is a powerful system to observe the response of different cells and aggregates to tuneable chemical gradients.