Biology subjects

Drasdo, D.

Publications and source records attributed to Drasdo, D..

6 recordsLinked to original sources

bioRxiv2025

The interplay between biomechanics and cell kinetics explains the spatial pattern in liver fibrosis

The formation of liver fibrosis patterns, characterized by excess extracellular matrix (ECM), is a complex process that is difficult to investigate experimentally. To complement experimental approaches, we developed a digital twin (DT) model to simulate the pattern formation of septal and biliary fibrosis, the two common forms of liver fibrosis. This model is based on iterative calibration with experiments from animal models treated with the hepatotoxic substance CCl4 (septal form) and Abcb4-knockout mice (biliary form). Septal fibrosis is characterized by ECM accumulation along the connective line between the central veins of neighboring liver lobules, while biliary fibrosis is marked by a scattered ECM pattern within the portal fields. This mechanistic DT model includes the components of hepatocytes (Heps{spadesuit}), hepatic stellate cells (HSCs), macrophages (Mphs), bile duct (BD) cells, collagen fibers secreted by activated HSCs, blood vessels, and cell-cell communication. It allows for the integration and simultaneous modulation of multiple hypothesized mechanisms underlying fibrotic wall formation. The model simulates the formation of liver fibrosis pattern and demonstrates that ECM distribution results from the pattern of cell death zones and biomechanical compression due to cell proliferation. "Healthy" Heps proliferate to compensate for cell loss. In septal fibrosis, where the cell death zones are several cells thick, the proliferating Heps surrounding a zone mechanically compress the deposited collagen network. After a transient phase of collagen scattered between/around Heps, the ECM eventually adopts a sharp, "wall"-like structure. Whereas, in biliary fibrosis, the pattern of cell death is more scattered, leading to a corresponding scattered ECM pattern. In this case, a pattern of scattered distributed collagen forms without transitioning to a sharp wall. Notably, the failure of fibrotic wall formation in endothelial cell-specific GATA4LSEC-KO mice, due to the disrupted pattern of CYP2E1-expressing Heps, validates our DT model. In conclusion, the DT model provided a deeper understanding of liver fibrosis pattern formation. It enabled comparison between simulated outcomes of hypothesized mechanisms and experimental data. Additionally, it guided the design of validation experiments and enabled the identification of optimal strategies for drug testing and extrapolation to humans.

systems biology↗

bioRxiv2025

Open Benchmarking for Cell-Based Multiscale Models: Lessons from a Community Initiative

The emergence of virtual human twins (VHT) in biomedical research has sparked interest in multiscale in silico modelling frameworks, particularly in their application bridging cellular to tissue levels. Among the diverse array of multiscale modelling tools, off-lattice center-based agent-based models (CBM) offer a promising approach due to their depiction of cells in 3D space, closely resembling biological reality. Despite the proliferation of CBM tools addressing various biomedical challenges, a comprehensive and systematic comparison among them has been elusive. This paper presents a community-driven benchmark initiative aimed at evaluating and comparing CBM for biomedical applications, akin to successful efforts in other scientific domains such as the Critical Assessment of Protein Structure Prediction (CASP). Enlisting developers from leading tools like BioDynaMo, Chaste, PhysiCell,TiSim, and CompuTiX, we devised a benchmark scope, defined metrics, and established reference datasets to ensure a meaningful and equitable evaluation. Unit tests targeting different solvers within these tools were designed, ranging from diffusion and mechanics to cell cycle simulations and growth scenarios. Results from these tests demonstrate varying tool implementations in handling diffusion, mechanics, and cell cycle equations, emphasising the need for standardised benchmarks and interoperability. Discussions among the community underscore the necessity for defining gold standards, fostering interoperability, and drawing lessons from analogous benchmarking experiences. The outcomes, disseminated through a public platform in collaboration with OpenEBench, aim to catalyse advancements in computational biology, offering a comprehensive resource for tool evaluation and guiding future developments in cell-level simulations. This initiative endeavours to strengthen and expand the computational biology simulation community through continued dissemination and performance-oriented benchmarking efforts to enable the use of VHT in biomedicine.

systems biology↗

bioRxiv2023

Extracellular Matrix Protein 1 Attenuates Hepatic Fibrosis by Inhibiting TSP-, ADAMTS-, and MMP-Mediated Latent TGF-β1 Activation

ObjectiveExtracellular Matrix Protein 1 (ECM1) serves as a gatekeeper of hepatic fibrosis by maintaining transforming growth factor-{beta}1 (TGF-{beta}1) in its latent form. ECM1 knockout (KO) causes latent (L) TGF-{beta}1 activation, resulting in hepatic fibrosis with rapid mortality. In chronic liver disease (CLD), ECM1 decreases with increasing CLD severity. We investigate the regulatory role of ECM1 in TGF-{beta}1 bioavailability and its impact on CLD progression. DesignRNAseq was performed to analyze hepatic gene expression. Functional assays were performed using hepatic stellate cells (HSCs), Ecm1-KO and Fxr-KO mice, patient liver tissue, and computer simulations. ResultsExpression of LTGF-{beta}1 activators, including thrombospondins (TSPs), ADAMTS proteases, and matrix metalloproteinases (MMPs) increased along with pro-fibrotic gene expression in liver tissue of Ecm1-KO mice. In HSCs, overexpression of ECM1 prevented TSP-1-, ADAMTS1-, and MMP-2/9-mediated LTGF-{beta}1 activation. In vitro interaction assays demonstrated that ECM1 inhibited LTGF-{beta}1 activation by interacting with TSP-1 and ADAMTS1 via their respective, intrinsic KRFK or KTFR amino acid sequences, and by suppressing MMP-2/9 proteolytic activity. In mice, ECM1 overexpression attenuated KRFK-induced LTGF-{beta}1 activation, while KTFR treatment reversed Ecm1-KO- and Fxr-KO-mediated liver injury. In patients with CLD, ECM1 expression was inversely correlated with TSP-1, ADAMTS1, MMP-2/9 expression and LTGF-{beta}1 activation. And these results were complemented by a computational compartment model representing the key network of cellular phenotypes and predicted interactions in liver fibrogenesis. ConclusionOur findings underscore the hepatoprotective effect of ECM1, which interferes with mediators of LTGF-{beta}1 activation, suggesting ECM1 or its representative peptide as potential anti-fibrotic therapies in CLD. What is already known on this topic?[tpltrtarr] ECM1 expression is negatively correlated with CLD progression. [tpltrtarr]ECM1 maintains liver homeostasis by keeping TGF-{beta}1 latency. What this study adds?[tpltrtarr] ECM1 inhibits LTGF-{beta}1 activation through interfering with key activators, including TSP-1, ADAMTS1, MMP-2, and MMP-9. [tpltrtarr]ECM1 interacts with TSP-1 and ADAMTS1 via their respective, intrinsic KRFK or KTFR amino acid motifs, and suppresses MMP-2/9 proteolytic activity. [tpltrtarr]In vivo, ECM1 overexpression mitigates KRFK peptide-induced LTGF-{beta}1 activation, while KTFR peptide rescues Ecm1-KO- and Fxr-KO-induced liver injury. [tpltrtarr]ECM1 expression inversely correlates with TSP-1, ADAMTS1, MMP-2/9 expression and LTGF-{beta}1 activation in CLD patients. How might this study affect research, practice or policy?[tpltrtarr] Considering severe adverse effects associated with anti-fibrotic treatments utilizing TGF-{beta}1 receptor inhibitors, our findings indicate that restoration of ECM1 expression or phenocopying peptides might represent a novel and safe route to urgently needed anti-fibrotic therapies in CLD.

cell biology↗

bioRxiv2019

Intravital multi-modal flux analysis reveals the transport mechanism of bile acids through hepatic microconduits

Small-molecule flux in tissue-microdomains is essential for organ function, but knowledge of this process is scant due to the lack of suitable methods. We developed two independent techniques that allow the quantification of advection (flow) and diffusion in individual bile canaliculi and in interlobular bile ducts of intact livers in living mice, namely Fluorescence Loss After Photoactivation (FLAP) and Intravital Arbitrary Region Image Correlation Spectroscopy (IVARICS). The results challenge the prevailing ‘mechano-osmotic’ theory of canalicular bile flow. After active transport across hepatocyte membranes bile acids are transported in the canaliculi primarily by diffusion. Only in the interlobular ducts, diffusion is augmented by regulatable advection. Photoactivation of fluorescein bis-(5-carboxymethoxy-2-nitrobenzyl)-ether (CMNB-caged fluorescein) in entire lobules demonstrated the establishment of diffusive gradients in the bile canalicular network and the sink function of interlobular ducts. In contrast to the bile canalicular network, vectorial transport was detected and quantified in the mesh of interlobular bile ducts. In conclusion, the liver consists of a diffusion dominated canalicular domain, where hepatocytes secrete small molecules and generate a concentration gradient and a flow-augmented ductular domain, where regulated water influx creates unidirectional advection that augments the diffusive flux.One Sentence Summary/Keywords Bile flux proceeds by diffusion in canaliculi, augmented by advection in ducts.Competing Interest StatementThe authors have declared no competing interest.View Full Text

physiology↗

bioRxiv2018

Quantifying the mechanics and growth of cells and tissues in 3D using high resolution computational models.

Mathematical models are increasingly designed to guide experiments in biology, biotechnology, as well as to assist in medical decision making. They are in particular important to understand emergent collective cell behavior. For this purpose, the models, despite still abstractions of reality, need to be quantitative in all aspects relevant for the question of interest. The focus in this paper is to study the regeneration of liver after drug-induced depletion of hepatocytes, in which surviving dividing and migrating hepatocytes must squeeze through a blood vessel network to fill the emerged lesions. Here, the cells response to mechanical stress might significantly impact on the regeneration process. We present a 3D high-resolution cell-based model integrating information from measurements in order to obtain a refined quantitative understanding of the cell-biomechanical impact on the closure of drug-induced lesions in liver. Our model represents each cell individually, constructed as a physically scalable network of viscoelastic elements, capable of mimicking realistic cell deformation and supplying information at subcellular scales. The cells have the capability to migrate, grow and divide, and infer the nature of their mechanical elements and their parameters from comparisons with optical stretcher experiments. Due to triangulation of the cell surface, interactions of cells with arbitrarily shaped (triangulated) structures such as blood vessels can be captured naturally. Comparing our simulations with those of so-called center-based models, in which cells have a rigid shape and forces are exerted between cell centers, we find that the migration forces a cell needs to exert on its environment to close a tissue lesion, is much smaller than predicted by center-based models. This effect is expected to be even more present in chronic liver disease, where tissue stiffens and excess collagen narrows pores for cells to squeeze through.

bioengineering↗

bioRxiv2017

Quantitative hybrid modeling reveals predictable mechanical stress response of growing tumor spheroids

Model simulations indicate that the response of growing cell populations on mechanical stress follows the same functional relationship and is predictable over different cell lines and growth conditions despite the response curves look largely different. We develop a hybrid model strategy in which cells are represented by coarse-grained individual units calibrated with a high resolution cell model and parameterized measurable biophysical and cell-biological parameters. Cell cycle progression in our model is controlled by volumetric strain, the latter being derived from a bio-mechanical relation between applied pressure and cell compressibility. After parameter calibration from experiments with mouse colon carcinoma cells growing against the resistance of an elastic alginate capsule, the model adequately predicts the growth curve in i) soft and rigid capsules, ii) in different experimental conditions where the mechanical stress is generated by osmosis via a high molecular weight dextran solution, and iii) for other cell types with varying doubling times. Our model simulation results suggest that the growth response of cell population upon externally applied mechanical stress is the same, as it can be quantitatively predicted using the same growth progression function.\n\nAuthor summaryThe effect of mechanical resistance on the growth of tumor cells remains today largely unquantified. We studied data from two different experimental setups that monitor the growth of tumor cells under mechanical compression. The existing data in the first experiment examined growing CT26 cells in an elastic permeable capsule. In the second experiment, growth of tumor cells under osmotic stress of the same cell line as well as other cell lines were studied. We have developed and agent-based model with measurable biophysical and cell-biological parameters that can simulate both experiments. Cell cycle progression in our model is a Hill function of cell volumetric strain, derived from a bio-mechanical relation between applied pressure and cell compressibility. After calibration of the model parameters within the data of the first experiment, we are able predict the growth rates in the second experiment. We show that that the growth response of cell populations upon externally applied mechanical stress in the two different experiments and over different cell lines can be predicted using the same growth progression function once the growth kinetics of the cell lines in abscence of mechanical stress is known.

biophysics↗