Cell cycle and developmental control of cortical excitability in Xenopus laevis

Abstract

Interest in cortical excitability – the ability of the cell cortex to generate traveling waves of protein activity – has grown considerably over the past twenty years. Attributing biological functions to cortical excitability requires an understanding of the natural behavior of excitable waves and the ability to accurately quantify wave properties. Here we have investigated and quantified the onset of cortical excitability in X. laevis eggs and embryos, and the changes in cortical excitability throughout early development. We found that cortical excitability begins to manifest shortly after egg activation. Further, we identified a close relationship between wave properties – such as wave frequency and amplitude – and cell cycle progression as well as cell size. Finally, we identified quantitative differences between cortical excitability in the cleavage furrow relative to non-furrow cortical excitability and showed that these wave regimes are mutually exclusive.

A versatile cortical pattern-forming circuit based on Rho, F-actin, Ect2, and RGA-3/4

“…The oocyte system overcomes several limitations of the natural excitability evident in embryos. First, immature oocytes are arrested in an interphase-like state and thus are not subject to the rapid cell-cycle and developmental changes intrinsic to early embryos, greatly reducing cell-to-cell variation and analysis complexity ( Bement et al, 2015 ; Swider et al, 2022 ). Second, capturing cortical waves in the fleeting embryonic furrow is extremely challenging, especially as cells become smaller.…”

“…Histograms, averages, and SDs of periods, shifts between the signals, temporal amplitudes, and temporal widths were computed using all boxes. For the final analysis used in the paper, a custom Python workflow described in Swider et al (2022) was used. Briefly, each maximum projection video was divided up into a grid of uniform boxes.…”

A versatile pattern-forming cortical circuit based on Rho, F-actin, Ect2, and RGA-3/4

“…Histograms, averages and standard deviations of periods, shifts between the signals, temporal amplitudes and temporal widths were computed using all boxes. For the final analysis used in the paper, a custom Python workflow described in (Swider et al, 2022) was used. Briefly, each maximum projection movie was divided up into a grid of uniform boxes.…”

“…For the final analysis used in the paper, a custom Python workflow described in (Swider et al, 2022) was used. Briefly, each maximum projection movie was divided up into a grid of uniform boxes.…”