1,556 research outputs found

    Collective signalling drives rapid jumping between cell states

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    Development can proceed in "fits and starts", with rapid transitions between cell states involving concerted transcriptome-wide changes in gene expression. However, it is not clear how these transitions are regulated in complex cell populations, in which cells receive multiple inputs. We address this issue using Dictyostelium cells undergoing development in their physiological niche. A continuous single cell transcriptomics time series identifies a sharp "jump" in global gene expression marking functionally different cell states. By simultaneously imaging the physiological dynamics of transcription and signalling, we show the jump coincides with the onset of collective oscillations of cAMP. Optogenetic control of cAMP pulses shows that different jump genes respond to distinct dynamic features of signalling. Late jump gene expression changes are almost completely dependent on cAMP, while transcript changes at the onset of the jump require additional input. The coupling of collective signalling with gene expression is a potentially powerful strategy to drive robust cell state transitions in heterogeneous signalling environments. Based on the context of the jump, we also conclude that sharp gene expression transitions may not be sufficient for commitment

    Controlling periodic long-range signalling to drive a morphogenetic transition

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    Cells use signal relay to transmit information across tissue scales. However, the production of information carried by signal relay remains poorly characterised. To determine how the coding features of signal relay are generated, we used the classic system for long-range signalling: the periodic cAMP waves that drive Dictyostelium collective migration. Combining imaging and optogenetic perturbation of cell signalling states, we find that migration is triggered by an increase in wave frequency generated at the signalling centre. Wave frequency is regulated by cAMP wave circulation, which organises the long-range signal. To determine the mechanisms modulating wave circulation, we combined mathematical modelling, the general theory of excitable media and mechanical perturbations to test competing models. Models in which cell density and spatial patterning modulate the wave frequency cannot explain the temporal evolution of signalling waves. Instead, our evidence leads to a model where wave circulation increases the ability for cells to relay the signal, causing further increase in the circulation rate. This positive feedback between cell state and signalling pattern regulates the long-range signal coding that drives morphogenesis

    Clearing the slate: RNA turnover to enable cell state switching?

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    The distribution of mRNA in tissue is determined by the balance between transcription and decay. Understanding the control of RNA decay during development has been somewhat neglected compared with transcriptional control. Here, we explore the potential for mRNA decay to trigger rapid cell state transitions during development, comparing a bistable switch model of cell state conversion with experimental evidence from different developmental systems. We also consider another potential role for large-scale RNA decay that has emerged from studies of stress-induced cell state transitions, in which removal of mRNA unblocks the translation machinery to prioritise the synthesis of proteins that establish the new cell state

    Slow Conduction in the Border Zones of Patchy Fibrosis Stabilizes the Drivers for Atrial Fibrillation: Insights from Multi-Scale Human Atrial Modeling

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    Introduction: The genesis of atrial fibrillation (AF) and success of AF ablation therapy have been strongly linked with atrial fibrosis. Increasing evidence suggests that patient-specific distributions of fibrosis may determine the locations of electrical drivers (rotors) sustaining AF, but the underlying mechanisms are incompletely understood. This study aims to elucidate a missing mechanistic link between patient-specific fibrosis distributions and AF drivers. Methods: 3D atrial models integrated human atrial geometry, rule-based fiber orientation, region-specific electrophysiology, and AF-induced ionic remodeling. A novel detailed model for an atrial fibroblast was developed, and effects of myocyte-fibroblast (M-F) coupling were explored at single-cell, 1D tissue and 3D atria levels. Left atrial LGE MRI datasets from 3 chronic AF patients were segmented to provide the patient-specific distributions of fibrosis. The data was non-linearly registered and mapped to the 3D atria model. Six distinctive fibrosis levels (0–healthy tissue, 5–dense fibrosis) were identified based on LGE MRI intensity and modeled as progressively increasing M-F coupling and decreasing atrial tissue coupling. Uniform 3D atrial model with diffuse (level 2) fibrosis was considered for comparison. Results: In single cells and tissue, the largest effect of atrial M-F coupling was on the myocyte resting membrane potential, leading to partial inactivation of sodium current and reduction of conduction velocity (CV). In the 3D atria, further to the M-F coupling, effects of fibrosis on tissue coupling greatly reduce atrial CV. AF was initiated by fast pacing in each 3D model with either uniform or patient-specific fibrosis. High variation in fibrosis distributions between the models resulted in varying complexity of AF, with several drivers emerging. In the diffuse fibrosis models, waves randomly meandered through the atria, whereas in each the patient-specific models, rotors stabilized in fibrotic regions. The rotors propagated slowly around the border zones of patchy fibrosis (levels 3–4), failing to spread into inner areas of dense fibrosis. Conclusion: Rotors stabilize in the border zones of patchy fibrosis in 3D atria, where slow conduction enable the development of circuits within relatively small regions. Our results can provide a mechanistic explanation for the clinical efficacy of ablation around fibrotic regions

    Polarization and wavelength diversities of Gulf Stream fronts imaged by AIRSAR

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    During the 1990 Gulf Stream Experiment, NASA/JPL AIRSAR imaged the north edge of the Gulf Stream near the coast of Virginia. Simultaneous in-situ measurements of currents, temperatures, salinities, etc. were made for several crossings of the north edge by the R/V Cape Henlopen. Measurements identified two fronts with shearing and converging flows. The polarimetric SAR images from the fronts showed two bright linear features. One of them corresponds to the temperature front, which separated the warm Gulf Stream water to the south from a cool, freshwater filament to the north. The other line, located about 8 km north of the temperature front, is believed to correspond to the velocity front between the filament and the slope water. At these fronts, wave-current interactions produced narrow bands of steep and breaking waves manifesting higher radar returns in polarimetric SAR images. In general, our AIRSAR imagery shows that the signal-to-clutter ratio of radar cross sections for the temperature front is higher than that of the velocity front. In this paper, we study the polarization and wavelength diversities of radar response of these two fronts using the P-, L-, and C-Band Polarimetric SAR data. The north-south flight path of the AIRSAR crossed the temperature front several times and provided valuable data for analysis. Three individual passes are investigated. We found that for the temperature front, the cross-pol (HV) responses are much higher than co-pol responses (VV and HH), and that P-Band HV has the highest signal to clutter ratio. For the velocity front, the ratio is the strongest in P-Band VV, and it is indistinguishable for all polarizations in C-Band. The radar cross sections for all three polarization (HH, HV, and VV) and for all three bands are modelled using an ocean wave model and a composite Bragg scattering model. In our initial investigations, the theoretical model agrees qualitatively with the AIRSAR observations
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