Confined Cell Migration and Asymmetric Hydraulic Environments to Evaluate the Metastatic Potential of Cancer Cells.

Metastasis, a hallmark of cancer development, is also the leading reason for most cancer-related deaths. Furthermore, cancer cells are highly adaptable to micro-environments and can migrate along pre-existing channel-like tracks of anatomical structures. However, more representative three-dimensional models are required to reproduce the heterogeneity of metastatic cell migration in vivo to further understand the metastasis mechanism and develop novel therapeutic strategies against it. Here, we designed and fabricated different microfluidic-based devices that recreate confined migration and diverse environments with asymmetric hydraulic resistances. Our results show different migratory potential between metastatic and nonmetastatic cancer cells in confined environments. Moreover, although nonmetastatic cells have not been tested against barotaxis due to their low migration capacity, metastatic cells present an enhanced preference to migrate through the lowest resistance path, being sensitive to barotaxis. This device, approaching the study of metastasis capability based on confined cell migration and barotactic cell decisions, may pave the way for the implementation of such technology to determine and screen the metastatic potential of certain cancer cells.

The role of nuclear mechanics in cell deformation under creeping flows.

Despite the relevant regulatory role that nuclear deformation plays in cell behaviour, a thorough understanding of how fluid flow modulates the deformation of the cell nucleus in non-confined environments is lacking. In this work, we investigated the dynamics of cell deformation under different creeping flows as a general simulation tool for predicting nuclear stresses and strains. Using this solid-fluid modelling interaction framework, we assessed the stress and strain levels that the cell nucleus experiences as a function of different microenvironmental conditions, such as physical constraints, fluid flows, cytosol properties, and nucleus properties and size. Therefore, the simulation methodology proposed here allows the design of deformability-based experiments involving fluid flow, such as real-time deformability cytometry and dynamic cell culture in bioreactors or microfluidic devices.

An Evaluation of Surgical Functional Reconstruction of the Foot Using Kinetic and Kinematic Systems: A Case Report.

Most pedobarographic studies of microsurgical foot reconstruction have been retrospective. In the present study, we report the results from a prospective pedobarographic study of a patient after microsurgical reconstruction of her foot with a latissimus dorsi flap and a cutaneous paddle, with a 42-month follow-up period. We describe the foot reconstruction plan and the pedobarographic measurements and analyzed its functional outcome. The goal of the present study was to demonstrate that pedobarography could have a role in the treatment of foot reconstruction from a quantitative perspective. The pedobarographic measurements were recorded after the initial coverage surgery and 2 subsequent foot remodeling procedures. A total of 4 pedobarographic measurements and 2 gait analyses were recorded and compared for both the noninvolved foot and the injured foot. Furthermore, the progress of the reconstructed foot was critically evaluated using this method. Both static and dynamic patterns were compared at subsequent follow-up visits after the foot reconstruction. The values and progression of the foot shape, peak foot pressure (kPa), average foot pressure (kPa), total contact surface (cm2), loading time (%), and step time (ms) were recorded. Initially, the pressure distribution of the reconstructed foot showed higher peak values at nonanatomic locations, revealing a greater ulceration risk. Over time, we found an improvement in the shape and values of these factors in the involved foot. To homogenize the pressure distribution and correct the imbalance between the 2 feet, patient-specific insoles were designed and fabricated. In our patient, pedobarography provided an objective, repeatable, and recordable method for the evaluation of the reconstructed foot. Pedobarography can therefore provide valuable insights into the prevention of pressure ulcers and optimization of rehabilitation.

An agent-based method to estimate 3D cell migration trajectories from 2D measurements: Quantifying and comparing T vs CAR-T 3D cell migration.

BACKGROUND AND OBJECTIVE: Immune cell migration is one of the key features that enable immune cells to find invading pathogens, control tissue damage, and eliminate primary developing tumors. Chimeric antigen receptor (CAR) T-cell therapy is a novel strategy in the battle against various cancers. It has been successful in treating hematological tumors, yet it still faces many challenges in the case of solid tumors. In this work, we evaluate the three-dimensional (3D) migration capacity of T and CAR-T cells within dense collagen-based hydrogels. Quantifying three-dimensional (3D) cell migration requires microscopy techniques that may not be readily accessible. Thus, we introduce a straightforward mathematical model designed to infer 3D trajectories of cells from two-dimensional (2D) cell trajectories. METHODS: We develop a 3D agent-based model (ABM) that simulates the temporal changes in the direction of migration with an inverse transform sampling method. Then, we propose an optimization procedure to accurately orient cell migration over time to reproduce cell migration from 2D experimental cell trajectories. With this model, we simulate cell migration assays of T and CAR-T cells in microfluidic devices conducted under hydrogels with different concentrations of type I collagen and validate our 3D cell migration predictions with light-sheet microscopy. RESULTS: Our findings indicate that CAR-T cell migration is more sensitive to collagen concentration increases than T cells, resulting in a more pronounced reduction in their invasiveness. Moreover, our computational model reveals significant differences in 3D movement patterns between T and CAR-T cells. T cells exhibit migratory behavior in 3D whereas that CAR-T cells predominantly move within the XY plane, with limited movement in the Z direction. However, upon the introduction of a CXCL12 chemical gradient, CAR-T cells present migration patterns that closely resemble those of T cells. CONCLUSIONS: This framework demonstrates that 2D projections of 3D trajectories may not accurately represent real migration patterns. Moreover, it offers a tool to estimate 3D migration patterns from 2D experimental data, which can be easily obtained with automatic quantification algorithms. This approach helps reduce the need for sophisticated and expensive microscopy equipment required in laboratories, as well as the computational burden involved in producing and analyzing 3D experimental data.

A hybrid physics-based and data-driven framework for cellular biological systems: Application to the morphogenesis of organoids.

How cells orchestrate their cellular functions remains a crucial question to unravel how they organize in different patterns. We present a framework based on artificial intelligence to advance the understanding of how cell functions are coordinated spatially and temporally in biological systems. It consists of a hybrid physics-based model that integrates both mechanical interactions and cell functions with a data-driven model that regulates the cellular decision-making process through a deep learning algorithm trained on image data metrics. To illustrate our approach, we used data from 3D cultures of murine pancreatic ductal adenocarcinoma cells (PDAC) grown in Matrigel as tumor organoids. Our approach allowed us to find the underlying principles through which cells activate different cell processes to self-organize in different patterns according to the specific microenvironmental conditions. The framework proposed here expands the tools for simulating biological systems at the cellular level, providing a novel perspective to unravel morphogenetic patterns.

Tumour growth: An approach to calibrate parameters of a multiphase porous media model based on in vitro observations of Neuroblastoma spheroid growth in a hydrogel microenvironment.

To unravel processes that lead to the growth of solid tumours, it is necessary to link knowledge of cancer biology with the physical properties of the tumour and its interaction with the surrounding microenvironment. Our understanding of the underlying mechanisms is however still imprecise. We therefore developed computational physics-based models, which incorporate the interaction of the tumour with its surroundings based on the theory of porous media. However, the experimental validation of such models represents a challenge to its clinical use as a prognostic tool. This study combines a physics-based model with in vitro experiments based on microfluidic devices used to mimic a three-dimensional tumour microenvironment. By conducting a global sensitivity analysis, we identify the most influential input parameters and infer their posterior distribution based on Bayesian calibration. The resulting probability density is in agreement with the scattering of the experimental data and thus validates the proposed workflow. This study demonstrates the huge challenges associated with determining precise parameters with usually only limited data for such complex processes and models, but also demonstrates in general how to indirectly characterise the mechanical properties of neuroblastoma spheroids that cannot feasibly be measured experimentally.

A 3D multi-agent-based model for lumen morphogenesis: the role of the biophysical properties of the extracellular matrix.

The correct function of many organs depends on proper lumen morphogenesis, which requires the orchestration of both biological and mechanical aspects. However, how these factors coordinate is not yet fully understood. Here, we focus on the development of a mechanistic model for computationally simulating lumen morphogenesis. In particular, we consider the hydrostatic pressure generated by the cells' fluid secretion as the driving force and the density of the extracellular matrix as regulators of the process. For this purpose, we develop a 3D agent-based-model for lumen morphogenesis that includes cells' fluid secretion and the density of the extracellular matrix. Moreover, this computer-based model considers the variation in the biological behavior of cells in response to the mechanical forces that they sense. Then, we study the formation of the lumen under different-mechanical scenarios and conclude that an increase in the matrix density reduces the lumen volume and hinders lumen morphogenesis. Finally, we show that the model successfully predicts normal lumen morphogenesis when the matrix density is physiological and aberrant multilumen formation when the matrix density is excessive. Supplementary Information: The online version contains supplementary material available at 10.1007/s00366-022-01654-1.

A Stiff Extracellular Matrix Favors the Mechanical Cell Competition that Leads to Extrusion of Bacterially-Infected Epithelial Cells.

Cell competition refers to the mechanism whereby less fit cells ("losers") are sensed and eliminated by more fit neighboring cells ("winners") and arises during many processes including intracellular bacterial infection. Extracellular matrix (ECM) stiffness can regulate important cellular functions, such as motility, by modulating the physical forces that cells transduce and could thus modulate the output of cellular competitions. Herein, we employ a computational model to investigate the previously overlooked role of ECM stiffness in modulating the forceful extrusion of infected "loser" cells by uninfected "winner" cells. We find that increasing ECM stiffness promotes the collective squeezing and subsequent extrusion of infected cells due to differential cell displacements and cellular force generation. Moreover, we discover that an increase in the ratio of uninfected to infected cell stiffness as well as a smaller infection focus size, independently promote squeezing of infected cells, and this phenomenon is more prominent on stiffer compared to softer matrices. Our experimental findings validate the computational predictions by demonstrating increased collective cell extrusion on stiff matrices and glass as opposed to softer matrices, which is associated with decreased bacterial spread in the basal cell monolayer in vitro. Collectively, our results suggest that ECM stiffness plays a major role in modulating the competition between infected and uninfected cells, with stiffer matrices promoting this battle through differential modulation of cell mechanics between the two cell populations.

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.

Unravelling cell migration: defining movement from the cell surface.

Cell motility is essential for life and development. Unfortunately, cell migration is also linked to several pathological processes, such as cancer metastasis. Cells' ability to migrate relies on many actors. Cells change their migratory strategy based on their phenotype and the properties of the surrounding microenvironment. Cell migration is, therefore, an extremely complex phenomenon. Researchers have investigated cell motility for more than a century. Recent discoveries have uncovered some of the mysteries associated with the mechanisms involved in cell migration, such as intracellular signaling and cell mechanics. These findings involve different players, including transmembrane receptors, adhesive complexes, cytoskeletal components , the nucleus, and the extracellular matrix. This review aims to give a global overview of our current understanding of cell migration.

Borrelia burgdorferi modulates the physical forces and immunity signaling in endothelial cells.

Borrelia burgdorferi (Bb), a vector-borne bacterial pathogen and the causative agent of Lyme disease, can spread to distant tissues in the human host by traveling in and through monolayers of endothelial cells (ECs) lining the vasculature. To examine whether Bb alters the physical forces of ECs to promote its dissemination, we exposed ECs to Bb and observed a sharp and transient increase in EC traction and intercellular forces, followed by a prolonged decrease in EC motility and physical forces. All variables returned to baseline at 24 h after exposure. RNA sequencing analysis revealed an upregulation of innate immune signaling pathways during early but not late Bb exposure. Exposure of ECs to heat-inactivated Bb recapitulated only the early weakening of EC mechanotransduction. The differential responses to live versus heat-inactivated Bb indicate a tight interplay between innate immune signaling and physical forces in host ECs and suggest their active modulation by Bb.

Down-regulation of EVI1 is associated with epigenetic alterations and good prognosis in patients with acute myeloid leukemia.

BACKGROUND: The EVI1 gene (3q26) codes for a zinc finger transcription factor with important roles in both mammalian development and leukemogenesis. Over-expression of EVI1 through either 3q26 rearrangements, MLL fusions, or other unknown mechanisms confers a poor prognosis in acute myeloid leukemia. DESIGN AND METHODS: We analyzed the prevalence and prognostic impact of EVI1 over-expression in a series of 476 patients with acute myeloid leukemia, and investigated the epigenetic modifications of the EVI1 locus which could be involved in the transcriptional regulation of this gene. RESULTS: Our data provide further evidence that EVI1 over-expression is a poor prognostic marker in acute myeloid leukemia patients less than 65 years old. Moreover, we found that patients with no basal expression of EVI1 had a better prognosis than patients with expression/over-expression (P=0.036). We also showed that cell lines with over-expression of EVI1 had no DNA methylation in the promoter region of the EVI1 locus, and had marks of active histone modifications: H3 and H4 acetylation, and trimethylation of histone H3 lysine 4. Conversely, cell lines with no expression of EVI1 have DNA hypermethylation and are marked by repressive trimethylation of histone H3 lysine 27 at the EVI1 promoter. CONCLUSIONS: Our results identify EVI1 over-expression as a poor prognostic marker in a large, independent cohort of acute myeloid leukemia patients less than 65 years old, and show that the total absence of EVI1 expression has a prognostic impact on the outcome of such patients. Furthermore, we demonstrated for the first time that an aberrant epigenetic pattern involving DNA methylation, H3 and H4 acetylation, and trimethylation of histone H3 lysine 4 and histone H3 lysine 27 might play a role in the transcriptional regulation of EVI1 in acute myeloid leukemia. This study opens new avenues for a better understanding of the regulation of EVI1 expression at a transcriptional level.

Time-dependent in silico modelling of orthognathic surgery to support the design of biodegradable bone plates.

Orthognathic surgery is performed to realign the jaws of a patient through several osteotomies. The state-of-the-art bone plates used to maintain the bone fragments in place are made of titanium. The presence of these non-degradable plates can have unwanted side effects on the long term (e.g. higher infection risk) if they are not removed. Using a biodegradable material such as magnesium may be a possible solution to this problem. However, biodegradation leads to a decrease of mechanical strength, therefore a time-dependent computational approach can help to evaluate the performance of such plates. In the present work, a computational framework has been developed to include biodegradation and bone healing algorithms in a finite element model. It includes bone plates and the mandible, which are submitted to masticatory loads during the early healing period (two months following the surgery). Two different bone plate designs with different stiffnesses have been tested. The stiff design exhibited good mechanical stability, with maximum Von Mises stress being less than 40% of the yield strength throughout the simulation. The flexible design shows high stresses when the bone healing has not started in the fracture gaps, indicating possible failure of the plate. However, this design leads to a higher bone healing quality after two months, as more cartilage is formed due to higher strains exerted in fracture gaps. We therefore conclude that in silico modelling can support tuning of the design parameters to ensure mechanical stability and while promoting bone healing.

Cell biophysical stimuli in lobopodium formation: a computer based approach.

Different cell migration modes have been identified in 3D environments, e.g., modes incorporating lamellopodia or blebs. Recently, a new type of cellular migration has been investigated: lobopodia-based migration, which appears only in three-dimensional matrices under certain conditions. The cell creates a protrusion through which the nucleus slips, dividing the cell into two parts (front and rear) with different hydrostatic pressures. In this work, we elucidate the mechanical conditions that favour this type of migration.One of the hypotheses about this type of migration is that it depends on the mechanical properties of the extracellular matrix. That is, lobopodia-based migration is dependent on whether the extracellular matrix is linearly elastic or non-linearly elastic.To determine whether the mechanical properties of the extracellular matrix are crucial in the choice of cell migration mode and which mechanotransduction mechanism the cell might use, we develop a finite element model. From our simulations, we identify two different possible mechanotransduction mechanisms that could regulate the cell to switch from a lobopodial to a lamellipodial migration mode. The first relies on a differential pressure increase inside the cytoplasm while the cell contracts, and the second relies on a change in the fluid flow direction in non-linearly elastic extracellular matrices but not in linearly elastic matrices. The biphasic nature of the cell has been determined to mediate this mechanism and the different behaviours of cells in linearly elastic and non-linearly elastic matrices.

A new 3D finite element-based approach for computing cell surface tractions assuming nonlinear conditions.

Advances in methods for determining the forces exerted by cells while they migrate are essential for attempting to understand important pathological processes, such as cancer or angiogenesis, among others. Precise data from three-dimensional conditions are both difficult to obtain and manipulate. For this purpose, it is critical to develop workflows in which the experiments are closely linked to the subsequent computational postprocessing. The work presented here starts from a traction force microscopy (TFM) experiment carried out on microfluidic chips, and this experiment is automatically joined to an inverse problem solver that allows us to extract the traction forces exerted by the cell from the displacements of fluorescent beads embedded in the extracellular matrix (ECM). Therefore, both the reconstruction of the cell geometry and the recovery of the ECM displacements are used to generate the inputs for the resolution of the inverse problem. The inverse problem is solved iteratively by using the finite element method under the hypothesis of finite deformations and nonlinear material formulation. Finally, after mathematical postprocessing is performed, the traction forces on the surface of the cell in the undeformed configuration are obtained. Therefore, in this work, we demonstrate the robustness of our computational-based methodology by testing it under different conditions in an extreme theoretical load problem and then by applying it to a real case based on experimental results. In summary, we have developed a new procedure that adds value to existing methodologies for solving inverse problems in 3D, mainly by allowing for large deformations and not being restricted to any particular material formulation. In addition, it automatically bridges the gap between experimental images and mechanical computations.

Multiscale modeling of bone tissue mechanobiology.

Mechanical environment has a crucial role in our organism at the different levels, ranging from cells to tissues and our own organs. This regulatory role is especially relevant for bones, given their importance as load-transmitting elements that allow the movement of our body as well as the protection of vital organs from load impacts. Therefore bone, as living tissue, is continuously adapting its properties, shape and repairing itself, being the mechanical loads one of the main regulatory stimuli that modulate this adaptive behavior. Here we review some key results of bone mechanobiology from computational models, describing the effect that changes associated to the mechanical environment induce in bone response, implant design and scaffold-driven bone regeneration.

Mechanical competition triggered by innate immune signaling drives the collective extrusion of bacterially infected epithelial cells.

Intracellular pathogens alter their host cells' mechanics to promote dissemination through tissues. Conversely, host cells may respond to the presence of pathogens by altering their mechanics to limit infection. Here, we monitored epithelial cell monolayers infected with intracellular bacterial pathogens, Listeria monocytogenes or Rickettsia parkeri, over days. Under conditions in which these pathogens trigger innate immune signaling through NF-κB and use actin-based motility to spread non-lytically intercellularly, we found that infected cell domains formed three-dimensional mounds. These mounds resulted from uninfected cells moving toward the infection site, collectively squeezing the softer and less contractile infected cells upward and ejecting them from the monolayer. Bacteria in mounds were less able to spread laterally in the monolayer, limiting the growth of the infection focus, while extruded infected cells underwent cell death. Thus, the coordinated forceful action of uninfected cells actively eliminates large domains of infected cells, consistent with this collective cell response representing an innate immunity-driven process.

Mechanism of apoptosis induced by IFN-alpha in human myeloma cells: role of Jak1 and Bim and potentiation by rapamycin.

Interferon-alpha (IFN-alpha) has been used for the last 20 years in the maintenance therapy of multiple myeloma (MM), though it is only effective in some patients. Congruent with this, IFN-alpha induces apoptosis in some MM cell lines. Understanding the mechanism of IFN-alpha-induced apoptosis could be useful in establishing criteria of eligibility for therapy. Here we show that IFN-alpha-induced apoptosis in the MM cell lines U266 and H929 was completely blocked by a specific inhibitor of Jak1. The mTOR inhibitor rapamycin mitigated apoptosis in U266 but potentiated it in H929 cells. IFN-alpha induced PS exposure, DeltaPsi(m) loss and pro-apoptotic conformational changes of Bak, but not of Bax, and was fully prevented by Mcl-1 overexpression in U266 cells. IFN-alpha treatment caused the release of cytochrome c from mitochondria to cytosol and consequently, a limited proteolytic processing of caspases. Apoptosis induced by IFN-alpha was only slightly prevented by caspase inhibitors. Levels of the BH3-only proteins PUMA and Bim increased during IFN-alpha treatment. Bim increase and apoptosis was prevented by transfection with the siRNA for Bim. PUMA-siRNA transfection reduced electroporation-induced apoptosis but had no effect on apoptosis triggered by IFN-alpha. The potentiating effect of rapamycin on apoptosis in H929 cells was associated to an increase in basal and IFN-alpha-induced Bim levels. Our results indicate that IFN-alpha causes apoptosis in myeloma cells through a moderate triggering of the mitochondrial route initiated by Bim and that mTOR inhibitors may be useful in IFN-alpha maintenance therapy of certain MM patients.

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.

Computational comparison of reamed versus unreamed intramedullary tibial nails.

We compared, via a computational model, the biomechanical performance of reamed versus unreamed intramedullary tibial nails to treat fractures in three different locations: proximal, mid-diaphyseal, and distal. Two finite element models were analyzed for the two nail types and the three kinds of fractures. Several biomechanical variables were determined: interfragmentary strains in the fracture site, von Mises stresses in nails and bolts, and strain distributions in the tibia and fibula. Although good mechanical stabilization was achieved in all the simulated fractures, the best results were obtained in the proximal fracture for the unreamed nail and in the mid-diaphyseal and distal fractures for the reamed nail. The interlocking bolts, in general, were subjected to higher stresses in the unreamed tibial nail than in the reamed one; thus the former stabilization technique is more likely to fail due to fatigue.