The dynamics of growth cone morphology

Goodhill, Geoffrey J., Faville, Richard A., Sutherland, Daniel J., Bicknell, Brendan A., Thompson, Andrew W., Pujic, Zac, Sun, Biao, Kita, Elizabeth M. and Scott, Ethan K. (2015) The dynamics of growth cone morphology. BMC Biology, 13 10: 1-16. doi:10.1186/s12915-015-0115-7

Author Goodhill, Geoffrey J.
Faville, Richard A.
Sutherland, Daniel J.
Bicknell, Brendan A.
Thompson, Andrew W.
Pujic, Zac
Sun, Biao
Kita, Elizabeth M.
Scott, Ethan K.
Title The dynamics of growth cone morphology
Journal name BMC Biology   Check publisher's open access policy
ISSN 1741-7007
Publication date 2015-02-11
Year available 2015
Sub-type Article (original research)
DOI 10.1186/s12915-015-0115-7
Open Access Status DOI
Volume 13
Issue 10
Start page 1
End page 16
Total pages 16
Place of publication London, United Kingdom
Publisher BioMed Central
Collection year 2016
Language eng
Formatted 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 intrinsic periodicity in cytoskeletal rearrangements.


Intrinsically driven shape oscillations are an important component of growth cone shape dynamics. More generally, eigenshape analysis has the potential to provide new quantitative information about differences in growth cone behaviour in different conditions.
Keyword Axon guidance
Neurite growth
Neural development
Eigenshape analysis
Shape analysis
Brain morphometry
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

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