Hepatocytes form bile canaliculi that dynamically respond to the signalling activity of bile acids and bile flow. Little is known about their responses to intraluminal pressure. During embryonic ...development, hepatocytes assemble apical bulkheads that increase the canalicular resistance to intraluminal pressure. Here, we investigate whether they also protect bile canaliculi against elevated pressure upon impaired bile flow in adult liver. Apical bulkheads accumulate upon bile flow obstruction in mouse models and patients with primary sclerosing cholangitis (PSC). Their loss under these conditions leads to abnormally dilated canaliculi, resembling liver cell rosettes described in other hepatic diseases. 3D reconstruction reveals that these structures are sections of cysts and tubes formed by hepatocytes. Mathematical modelling establishes that they positively correlate with canalicular pressure and occur in early PSC stages. Using primary hepatocytes and 3D organoids, we demonstrate that excessive canalicular pressure causes the loss of apical bulkheads and formation of rosettes. Our results suggest that apical bulkheads are a protective mechanism of hepatocytes against impaired bile flow, highlighting the role of canalicular pressure in liver diseases.
Endocytosis allows the import and distribution of cargo into a series of endosomes with distinct morphological and biochemical characteristics. Our current understanding of endocytic cargo ...trafficking is based on the kinetics of net cargo transport between endosomal compartments without considering individual endosomes. However, endosomes form a dynamic network of membranes undergoing fusion and fission, thereby continuously exchanging and redistributing cargo. The macroscopic kinetic properties, i.e., the properties of the endosomal network as a whole, result from the collective behaviors of many individual endosomes, a problem so far largely unaddressed.
Here, we developed a general theoretical framework to describe the dynamics of cargo distributions in the endosomal network. We combined the theory with quantitative experiments to study how the macroscopic kinetic properties of the endosomal network emerge from microscopic processes at the level of individual endosomes. We compared our theory predictions to experimental data in which dynamic distributions of endocytosed low-density lipoprotein (LDL) were quantified.
Our theory can quantitatively describe the observed cargo distributions as a function of time. Remarkably, the theory allows determining microscopic kinetic parameters such as the fusion rate between endosomes from still images of cargo distributions at different times of internalization. We show that this method is robust and sensitive because cargo distributions result from an average over many stochastic events in many cells. Our results provide theoretical and experimental support to the “funnel model” of endosome progression and suggest that the conversion of early to late endosomes is the major mode of LDL trafficking.
► Theory for the dynamics of endosomal network consisting of many interacting endosomes ► Cargo distributions are shaped by cargo influx, endosome fusion, and conversion ► Kinetic parameters of the endosomal network can be obtained from still images ► Changes of kinetic parameters by perturbations can be detected with high sensitivity
Bile, the central metabolic product of the liver, is transported by the bile canaliculi network. The impairment of bile flow in cholestatic liver diseases has urged a demand for insights into its ...regulation. Here, we developed a predictive 3D multi-scale model that simulates fluid dynamic properties successively from the subcellular to the tissue level. The model integrates the structure of the bile canalicular network in the mouse liver lobule, as determined by high-resolution confocal and serial block-face scanning electron microscopy, with measurements of bile transport by intravital microscopy. The combined experiment-theory approach revealed spatial heterogeneities of biliary geometry and hepatocyte transport activity. Based on this, our model predicts gradients of bile velocity and pressure in the liver lobule. Validation of the model predictions by pharmacological inhibition of Rho kinase demonstrated a requirement of canaliculi contractility for bile flow in vivo. Our model can be applied to functionally characterize liver diseases and quantitatively estimate biliary transport upon drug-induced liver injury.
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•The bile canaliculi network displays geometric heterogeneity within the liver lobule•Bile flow is driven by osmotic effects and bile canaliculi contractility•A multi-scale model reveals gradients of bile velocity and pressure within the lobule•The multi-scale model predicts drug-induced alterations of bile flow
Meyer et al. developed a 3D multi-scale model of biliary fluid dynamics in the mouse liver lobule to predict drug-induced alterations of bile flow. They demonstrate two inversely related gradients of bile velocity and pressure in the lobule and show that bile flow is driven by the osmotic effects of bile secretion and bile canaliculi contractility.
We study a model for a thin liquid film dewetting from a periodic heterogeneous substrate (template). The amplitude and periodicity of a striped template heterogeneity necessary to obtain a stable ...periodic stripe pattern, i.e., pinning, are computed. This requires a stabilization of the longitudinal and transversal modes driving the typical coarsening dynamics during dewetting of a thin film on a homogeneous substrate. If the heterogeneity has a larger spatial period than that of the critical dewetting mode, weak heterogeneities are sufficient for pinning. Our results imply a large region of coexistence between coarsening dynamics and pinning.
Replacement of dysfunctional β-cells in the islets of Langerhans by transdifferentiation of pancreatic acinar cells has been proposed as a regenerative therapy for diabetes. Adult acinar cells ...spontaneously revert to a multipotent state upon tissue dissociation in vitro and can be stimulated to redifferentiate into β-cells. Despite accumulating evidence that contact-mediated signals are involved, the mechanisms regulating acinar-to-islet cell transdifferentiation remain poorly understood.
In this study, we propose that the crosstalk between two contact-mediated signaling mechanisms, lateral inhibition and lateral stabilization, controls cell fate stability and transdifferentiation of pancreatic cells. Analysis of a mathematical model combining gene regulation with contact-mediated signaling reveals the multistability of acinar and islet cell fates. Inhibition of one or both modes of signaling results in transdifferentiation from the acinar to the islet cell fate, either by dedifferentiation to a multipotent state or by direct lineage switching.
This study provides a theoretical framework to understand the role of contact-mediated signaling in pancreatic cell fate control that may help to improve acinar-to-islet cell transdifferentiation strategies for β-cell neogenesis.
Many internal epithelial organs derive from cysts, which are tissues comprised of bent epithelial cell layers enclosing a lumen. Ion accumulation in the lumen drives water influx and consequently ...water accumulation and cyst expansion. Lumen-size recognition is important for the regulation of organ size. When lumen size and cyst size are not controlled, diseases can result; for instance, renal failure of the kidney. We develop a mechanistic mathematical model of lumen expansion in order to investigate the mechanisms for saturation of cyst growth. We include fluid accumulation in the lumen, osmotic and elastic pressure, ion transport and stretch-induced cell division. We find that the lumen volume increases in two phases: first, due to fluid accumulation stretching the cells, then in the second phase, the volume increase follows the increase in cell number until proliferation ceases as stretch forces relax. The model is quantitatively fitted to published data of
in vitro cyst growth and predicts steady state lumen size as a function of the model parameters.
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