The dynamics of growth cone morphology

BMC Biology
Geoffrey J GoodhillEthan K Scott

Abstract

Normal brain function depends on the development of appropriate patterns of neural connections. A critical role in guiding axons to their targets during neural development is played by neuronal growth cones. These have a complex and rapidly changing morphology; however, a quantitative understanding of this morphology, its dynamics and how these are related to growth cone movement, is lacking. Here we use eigenshape analysis (principal components analysis in shape space) to uncover the set of five to six basic shape modes that capture the most variance in growth cone form. By analysing how the projections of growth cones onto these principal modes evolve in time, we found that growth cone shape oscillates with a mean period of 30 min. The variability of oscillation periods and strengths between different growth cones was correlated with their forward movement, such that growth cones with strong, fast shape oscillations tended to extend faster. A simple computational model of growth cone shape dynamics based on dynamic microtubule instability was able to reproduce quantitatively both the mean and variance of oscillation periods seen experimentally, suggesting that the principal driver of growth cone shape oscillations may be intr...Continue Reading

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Citations

Mar 2, 2016·Trends in Neurosciences·Geoffrey J Goodhill
Jan 25, 2018·Journal of Neural Engineering·Yuan RenDaniel M Suter
Apr 20, 2018·Proceedings. Biological Sciences·Pranesh Padmanabhan, Geoffrey J Goodhill
Dec 14, 2018·The Journal of Cell Biology·Maria M BagonisGaudenz Danuser
Aug 2, 2018·Frontiers in Cellular Neuroscience·Alexa KissFriedrich Propst
Sep 23, 2020·Pharmacology & Therapeutics·Krzysztof RogowskiSiem van der Laan
Mar 11, 2020·Developmental Cell·Dani L BodorEwa K Paluch

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Methods Mentioned

BETA
dissection
PCA

Software Mentioned

autocorr
pchip
Mathworks
FastICA
Matlab
fft

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