Biology subjects

Chubb, J. R.

Publications and source records attributed to Chubb, J. R..

4 recordsLinked to original sources

bioRxiv2024

Pattern formation along signaling gradients driven by active droplet behaviour of cell groups

Gradients of extracellular signals organise cells in tissues. Although there are several models for how gradients can pattern cell behaviour, it is not clear how cells react to gradients when the population is undergoing 3D morphogenesis, in which cell-cell and cell-signal interactions are continually changing. Dictyostelium cells follow gradients of their nutritional source to feed and maintain their undifferentiated state. Using light sheet imaging to simultaneously monitor signaling, single cell and population dynamics, we show that the cells migrate towards nutritional gradients in swarms. As swarms advance, they deposit clumps of cells at the rear, triggering differentiation. Clump deposition is explained by a physical model in which cell swarms behave as active droplets: cells proliferate within the swarm, with clump shedding occurring at a critical population size, at which cells at the rear no longer perceive the gradient and are not retained by the emergent surface tension of the swarm. The droplet model predicts vortex motion of the cells within the swarm emerging from the local transfer of propulsion forces, a prediction validated by 3D tracking of single cells. This active fluid behaviour reveals a developmental mechanism we term "musical chairs" decision-making, in which the decision to proliferate or differentiate is determined by the position of a cell within the group as it bifurcates.

biophysics↗

bioRxiv2023

Collective signalling drives rapid jumping between cell states

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. It is also not clear to what extent these rapid transitions represent developmental commitment. Here we address these issues using Dictyostelium cells undergoing development in their physiological niche. A continuous single cell transcriptomics time series reveals a sharp "jump" in global gene expression marking functionally different cell states. By simultaneously live imaging the physiological dynamics of transcription and signalling over millimetre length scales, we show that the jump coincides with the onset of collective oscillations of cAMP, the positive feedback signal for multicellular development. Different jump genes respond to distinct dynamic features of signalling. The late gene expression changes of the jump are almost completely dependent on cAMP. In contrast, transcript changes at the onset of the jump require additional input. The spatial boundary marking the jump divides cells separated by only a few minutes of developmental time, with cells missing a jump then waiting several hours for the onset of the next wave of cAMP oscillations. This timing variability contrasts the prevailing developmental paradigm of a timed synchronous process and is associated with substantial pre-jump transcriptome variability. 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.

developmental biology↗

bioRxiv2022

Signalling centre vortices coordinate collective behaviour in social amoebae

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 cell to relay the signal, causing further increase in the circulation rate. This implies that information driving a morphogenetic transition gradually unfolds due to positive feedback between cell signalling state and signalling pattern. This demonstrates how the coding properties of a long-range signal arise from self-organised wave dynamics at the signalling centre.

biophysics↗

bioRxiv2021

Content-aware frame interpolation (CAFI): Deep Learning-based temporal super-resolution for fast bioimaging

The development of high-resolution microscopes has made it possible to investigate cellular processes in 4D (3D over time). However, observing fast cellular dynamics remains challenging as a consequence of photobleaching and phototoxicity. These issues become increasingly problematic with the depth of the volume acquired and the speed of the biological events of interest. Here, we report the implementation of two content-aware frame interpolation (CAFI) deep learning networks, Zooming SlowMo (ZS) and Depth-Aware Video Frame Interpolation (DAIN), based on combinations of recurrent neural networks, that are highly suited for accurately predicting images in between image pairs, therefore improving the temporal resolution of image series as a post-acquisition analysis step. We show that CAFI predictions are capable of understanding the motion context of biological structures to perform better than standard interpolation methods. We benchmark CAFIs performance on six different datasets, obtained from three different microscopy modalities (point-scanning confocal, spinning-disk confocal and confocal brightfield microscopy). We demonstrate its capabilities for single-particle tracking methods applied to the study of lysosome trafficking. CAFI therefore allows for reduced light exposure and phototoxicity on the sample and extends the possibility of long-term live-cell imaging. Both DAIN and ZS as well as the training and testing data are made available for use by the wider community via the ZeroCostDL4Mic platform.

cell biology↗