TY - JOUR
T1 - Automated profiling of growth cone heterogeneity defines relations between morphology and motility
AU - Bagonis, Maria M.
AU - Fusco, Ludovico
AU - Pertz, Olivier
AU - Danuser, Gaudenz
N1 - Funding Information:
The project was funded by the Human Frontier Science Program (HFSP RGP0037_2010 to O. Pertz and G. Danuser) and grants from the International Foundation for Research in Paraplegia (to O. Pertz) and the National Institutes of Health (R01 GM067230 to G. Danuser). The authors declare no competing financial interests.
Publisher Copyright:
© 2018 Bagonis et al.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Growth cones are complex, motile structures at the tip of an outgrowing neurite. They often exhibit a high density of filopodia (thin actin bundles), which complicates the unbiased quantification of their morphologies by software. Contemporary image processing methods require extensive tuning of segmentation parameters, require significant manual curation, and are often not sufficiently adaptable to capture morphology changes associated with switches in regulatory signals. To overcome these limitations, we developed Growth Cone Analyzer (GCA). GCA is designed to quantify growth cone morphodynamics from time-lapse sequences imaged both in vitro and in vivo, but is sufficiently generic that it may be applied to nonneuronal cellular structures. We demonstrate the adaptability of GCA through the analysis of growth cone morphological variation and its relation to motility in both an unperturbed system and in the context of modified Rho GTPase signaling. We find that perturbations inducing similar changes in neurite length exhibit underappreciated phenotypic nuance at the scale of the growth cone.
AB - Growth cones are complex, motile structures at the tip of an outgrowing neurite. They often exhibit a high density of filopodia (thin actin bundles), which complicates the unbiased quantification of their morphologies by software. Contemporary image processing methods require extensive tuning of segmentation parameters, require significant manual curation, and are often not sufficiently adaptable to capture morphology changes associated with switches in regulatory signals. To overcome these limitations, we developed Growth Cone Analyzer (GCA). GCA is designed to quantify growth cone morphodynamics from time-lapse sequences imaged both in vitro and in vivo, but is sufficiently generic that it may be applied to nonneuronal cellular structures. We demonstrate the adaptability of GCA through the analysis of growth cone morphological variation and its relation to motility in both an unperturbed system and in the context of modified Rho GTPase signaling. We find that perturbations inducing similar changes in neurite length exhibit underappreciated phenotypic nuance at the scale of the growth cone.
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U2 - 10.1083/jcb.201711023
DO - 10.1083/jcb.201711023
M3 - Article
C2 - 30523041
AN - SCOPUS:85059929887
SN - 0021-9525
VL - 218
SP - 350
EP - 379
JO - Journal of Cell Biology
JF - Journal of Cell Biology
IS - 1
ER -