Search arXivSearch

arXiv · 1402.5258

Cytoskeletal turnover and Myosin contractility drive cell autonomous oscillations in a model of Drosophila Dorsal Closure

Abstract

Oscillatory behaviour in force-generating systems is a pervasive phenomenon in cell biology. In this work, we investigate how oscillations in the actomyosin cytoskeleton drive cell shape changes during the process of Dorsal Closure, a morphogenetic event in Drosophila embryo development whereby epidermal continuity is generated through the pulsatile apical area reduction of cells constituting the amnioserosa (AS) tissue. We present a theoretical model of AS cell dynamics by which the oscillatory behaviour arises due to a coupling between active Myosin-driven forces, actin turnover and cell deformation. Oscillations in our model are cell-autonomous and are modulated by neighbour coupling, and our model accurately reproduces the oscillatory dynamics of AS cells and their amplitude and frequency evolution. A key prediction arising from our model is that the rate of actin turnover and Myosin contractile force must increase during DC in order to reproduce the decrease in amplitude and period of cell area oscillations observed in vivo. This prediction opens up new ways to think about the molecular underpinnings of AS cell oscillations and their link to net tissue contraction and suggests the form of future experimental measurements.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Pedro F. Machado, Guy B. Blanchard, Julia Duque, Nicole Gorfinkiel. 2014-03-13. Cytoskeletal turnover and Myosin contractility drive cell autonomous oscillations in a model of Drosophila Dorsal Closure. https://doi.org/10.1140/epjst%2Fe2014-02197-7

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Local intercellular coupling is sufficient for long-range calcium signaling

Long-range intercellular calcium (Ca2+) signaling coordinates biological processes ranging from fertilization to contraction and cell death. The classical model attributes this long-range propagation to rapid diffusion of inositol 1,4,5-trisphosphate (IP3) through gap junctions. However, recent evidence that IP3 diffuses far more slowly than previously believed, and that Ca2+ oscillations persist even when gap junctions are disassembled, indicates that an alternative mechanism must sustain long-range communication. Here we develop a computational model showing that local coupling between neighboring cells is sufficient to generate and propagate regenerative Ca2+ oscillations across a cell population without fast molecular diffusion. Each cell is treated as an oscillator whose intrinsic frequency is set by its local IP3 concentration through an IP3-dependent refractory period, and neighboring cells are coupled using a Kuramoto nearest-neighbor framework. In a dual-stiffness regime, cells on a stiff extracellular matrix entrain their soft-matrix neighbors, producing an offset traveling wave of Ca2+ release. This reproduces the finite spatial range of influence (~8 cell lengths) observed experimentally. Our findings propose a diffusion-independent paradigm for calcium signaling in which local intercellular coupling drives long-range communication, offering insight into how localized ECM stiffening in asthma and fibrosis may produce systemic effects.

q-bio.CB

Fragmented uptake drives lipid accumulation in macrophage cannibalistic efferocytosis

Efferocytosis, the clearance of dying cells typically by macrophages, is essential for tissue homeostasis and the resolution of inflammation. Previous experiments by Ford et al. (Proc. R. Soc. B, 2019) showed that cannibalistic efferocytosis redistributes endogenous lipid from dying macrophages into the surviving population, but existing mathematical models do not reproduce the observed population dynamics and lipid distributions. Here, fifteen candidate models are compared, combining three mechanisms of apoptotic material uptake with five forms of the macrophage death rate. Model comparison is guided by the Akaike Information Criterion and qualitative agreement with the observed lipid distributions. Numerical solutions show that whole-cell uptake models predict internal maxima that are absent from the data, whereas nibbling uptake produces distributions that are too concentrated about their means. By contrast, intermediate "fragmented" uptake models provide substantially improved agreement when combined with either linear lipid-dependent or exponential time-dependent death rates. The fitted models predict that smaller fragments from dying cells are ingested at higher frequency than larger ones. This analysis provides new insight into how efferocytosis shapes the distribution of lipid within macrophage populations and highlights the importance of distribution-level data for distinguishing between mechanistic models that reproduce similar population-average dynamics.

q-bio.CB

SpCAST enables scalable and interpretable integration of single-cell RNA sequencing and single-cell-resolved spatial transcriptomics

Single-cell-resolution spatial transcriptomics (scST) preserves tissue architecture but often provides targeted or sparse transcriptomic measurements, whereas scRNA-seq offers broader coverage without spatial context. We present SpCAST, a scalable and interpretable framework that uses scRNA-seq references to transfer cell identity, reconstruct expression and expose gene-level decision evidence in scST. SpCAST jointly learns reference-cell classification, reference--query alignment and query reconstruction in mini-batches, avoiding the need for a global reference-by-query correspondence matrix. Spatially Aware Gene Attribution (SAGA) approximates the learned decision function with a sparse additive Kolmogorov--Arnold network. Across 53 sections comprising 413,404 spatial cells from five technologies, SpCAST achieved the highest aggregate annotation rank among seven methods and scaled to ten million simulated cells. Controlled masking recovered cell-type-associated expression signals and improved spatial marker concordance. SAGA further resolved expression-dependent gene evidence and distinguished evidence retained or attenuated across intra- and cross-species reference settings.

q-bio.CB