Dataset Information

Intercellular communication induces glycolytic synchronization waves between individually oscillating cells.

ABSTRACT: Many organs have internal structures with spatially differentiated and sometimes temporally synchronized groups of cells. The mechanisms leading to such differentiation and coordination are not well understood. Here we design a diffusion-limited microfluidic system to mimic a multicellular organ structure with peripheral blood flow and test whether a group of individually oscillating yeast cells could form subpopulations of spatially differentiated and temporally synchronized cells. Upon substrate addition, the dynamic response at single-cell level shows glycolytic oscillations, leading to wave fronts traveling through the monolayered population and to synchronized communities at well-defined positions in the cell chamber. A detailed mechanistic model with the architectural structure of the flow chamber incorporated successfully predicts the spatial-temporal experimental data, and allows for a molecular understanding of the observed phenomena. The intricate interplay of intracellular biochemical reaction networks leading to the oscillations, combined with intercellular communication via metabolic intermediates and fluid dynamics of the reaction chamber, is responsible for the generation of the subpopulations of synchronized cells. This mechanism, as analyzed from the model simulations, is experimentally tested using different concentrations of cyanide stress solutions. The results are reproducible and stable, despite cellular heterogeneity, and the spontaneous community development is reminiscent of a zoned cell differentiation often observed in multicellular organs.

SUBMITTER: Mojica-Benavides M

PROVIDER: S-EPMC8017953 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Cell-to-cell communication is a fundamental process for development and maintenance of multicellular organisms. Diverse mechanisms for the exchange of molecular information between cells have been documented, such as the exchange of membrane fragments (trogocytosis), formation of tunneling nanotubes (TNTs) and release of microvesicles (MVs). In this study we assign to Fas signalling a pivotal role for intercellular communication in CD4+ T cells. Binding of membrane-bound FasL to Fas expressing target cells triggers a well-characterized pro-apoptotic signalling cascade. However, our results, pairing up flow cytometric studies with confocal microscopy data, highlight a new social dimension for Fas/FasL interactions between CD4+ T cells. Indeed, FasL enhances the formation of cell conjugates (8 fold of increase) in an early time-frame of stimulation (30 min), and this phenomenon appears to be a crucial step to prime intercellular communication. Our findings show that this communication mainly proceeds along a cytosolic material exchange (ratio of exchange >10, calculated as ratio of stimulated cells signal divided by that recorded in control cells) via TNTs and MVs release. In particular, inhibition of TNTs genesis by pharmacological agents (Latruculin A and Nocodazole) markedly reduced this exchange (inhibition percentage: >40% and >50% respectively), suggesting a key role for TNTs in CD4+ T cells communication. Although MVs are present in supernatants from PHA-activated T cells, Fas treatment also leads to a significant increase in the amount of released MVs. In fact, the co-culture performed between MVs and untreated cells highlights a higher presence of MVs in the medium (1.4 fold of increase) and a significant MVs uptake (6 fold of increase) by untreated T lymphocytes. We conclude that Fas signalling induces intercellular communication in CD4+ T cells by different mechanisms that seem to start concomitantly with the main pathway (programmed cell death) promoted by FasL.

Project description:Fibrogenic pathways in the liver are principally regulated by activation of hepatic stellate cells (HSC). Fibrosis is associated with chronic hepatitis C virus (HCV) infection, although the mechanism is poorly understood. HSC comprise the major population of nonparenchymal cells in the liver. Since HCV does not replicate in HSC, we hypothesized that exosomes secreted from HCV-infected hepatocytes activate HSC. Primary or immortalized human hepatic stellate (LX2) cells were exposed to exosomes derived from HCV-infected hepatocytes (HCV-exo), and the expression of fibrosis-related genes was examined. Our results demonstrated that HCV-exo internalized to HSC and increased the expression of profibrotic markers. Further analysis suggested that HCV-exo carry miR-19a and target SOCS3 in HSC, which in turn activates the STAT3-mediated transforming growth factor β (TGF-β) signaling pathway and enhances fibrosis marker genes. The higher expression of miR-19a in exosomes was also observed from HCV-infected hepatocytes and in sera of chronic HCV patients with fibrosis compared to healthy volunteers and non-HCV-related liver disease patients with fibrosis. Together, our results demonstrated that miR-19a carried through the exosomes from HCV-infected hepatocytes activates HSC by modulating the SOCS-STAT3 axis. Our results implicated a novel mechanism of exosome-mediated intercellular communication in the activation of HSC for liver fibrosis in HCV infection.IMPORTANCE HCV-associated liver fibrosis is a critical step for end-stage liver disease progression. However, the molecular mechanisms for hepatic stellate-cell activation by HCV-infected hepatocytes are underexplored. Here, we provide a role for miR-19a carried through the exosomes in intercellular communication between HCV-infected hepatocytes and HSC in fibrogenic activation. Furthermore, we demonstrate the role of exosomal miR-19a in activation of the STAT3-TGF-β pathway in HSC. This study contributes to the understanding of intercellular communication in the pathogenesis of liver disease during HCV infection.

Dataset Information

Intercellular communication induces glycolytic synchronization waves between individually oscillating cells.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets