second option, manual marking of individual nuclei, is
extremely time consuming, especially if one wants to perform
triangulation at multiple time points for multiple explants to
assess the dynamics of dispersion. A typical explant has between
100 and 200 cells. If one wants to perform triangulation on
20 explants at 5 time points each, it means marking manually
between 10,000–20,000 nuclei. This increases exponentially if
one needs to do experiments in triplicate and has to compare
multiple experimental conditions. Thus, if one absolutely
needs to use triangulation (e.g., local differences in terms of
distance between neighbors within each explant are important), we recommend using the automated detection of nuclei.
However, it is important to bear in mind that some nuclei will
not be detected regardless of the technique used to mark them,
or to detect them. It is important to first establish the conditions for automated detection on a small subset of data and to
compare the overall output with the one obtained when marking nuclei manually. A difference of more than 5% should not
be considered acceptable and image acquisition and nuclei
detection would need to be improved before embarking on
large-scale automated detection of nuclei.
Acknowledgements
Eric Theveneau and Christian Rouviere are permanent CNRS staff.
Work in the Theveneau lab is supported by the Region MidiPyrenees (Installation Grants for Excellent Researchers,
13053025), the Fondation pour la Recherche Medicale
(AJE201224), the CNRS and the Universite ´ Paul Sabatier. Nade `ge
Gouignard is the recipient of an individual fellowship from FRM
(ARF20150934153) and the Marie Curie Prestiges Program
(PRESTIGES 2015-4-007).
References
1. Hay ED (1995) An overview of epitheliomesenchymal transformation. Acta Anat 154
(1):8–20.
https://doi.org/10.1159/
000147748
2. Hay ED, Zuk A (1995) Transformations
between epithelium and mesenchyme: normal,
pathological, and experimentally induced. Am
J Kidney Dis 26(4):678–690. https://doi.org/
10.1016/0272-6386(95)90610-x
3. Nieto MA (2011) The ins and outs of the
epithelial to mesenchymal transition in health
and disease. Annu Rev Cell Dev Biol
27:347–376.
https://doi.org/10.1146/
annurev-cellbio-092910-154036
4. Thiery JP, Acloque H, Huang RY, Nieto MA
(2009) Epithelial-mesenchymal transitions in
development
and
disease.
Cell
139
(5):871–890. https://doi.org/10.1016/j.cell.
2009.11.007
5. Thiery JP (2002) Epithelial-mesenchymal transitions in tumour progression. Nat Rev Cancer
2(6):442–454.
https://doi.org/10.1038/
nrc822
6. Gouignard N, Andrieu C, Theveneau E (2018)
Neural crest delamination and migration:
Looking forward to the next 150 years. Genesis
56:e23107. https://doi.org/10.1002/dvg.
23107
Using Xenopus Neural Crest to Study EMT
273
extremely time consuming, especially if one wants to perform
triangulation at multiple time points for multiple explants to
assess the dynamics of dispersion. A typical explant has between
100 and 200 cells. If one wants to perform triangulation on
20 explants at 5 time points each, it means marking manually
between 10,000–20,000 nuclei. This increases exponentially if
one needs to do experiments in triplicate and has to compare
multiple experimental conditions. Thus, if one absolutely
needs to use triangulation (e.g., local differences in terms of
distance between neighbors within each explant are important), we recommend using the automated detection of nuclei.
However, it is important to bear in mind that some nuclei will
not be detected regardless of the technique used to mark them,
or to detect them. It is important to first establish the conditions for automated detection on a small subset of data and to
compare the overall output with the one obtained when marking nuclei manually. A difference of more than 5% should not
be considered acceptable and image acquisition and nuclei
detection would need to be improved before embarking on
large-scale automated detection of nuclei.
Acknowledgements
Eric Theveneau and Christian Rouviere are permanent CNRS staff.
Work in the Theveneau lab is supported by the Region MidiPyrenees (Installation Grants for Excellent Researchers,
13053025), the Fondation pour la Recherche Medicale
(AJE201224), the CNRS and the Universite ´ Paul Sabatier. Nade `ge
Gouignard is the recipient of an individual fellowship from FRM
(ARF20150934153) and the Marie Curie Prestiges Program
(PRESTIGES 2015-4-007).
References
1. Hay ED (1995) An overview of epitheliomesenchymal transformation. Acta Anat 154
(1):8–20.
https://doi.org/10.1159/
000147748
2. Hay ED, Zuk A (1995) Transformations
between epithelium and mesenchyme: normal,
pathological, and experimentally induced. Am
J Kidney Dis 26(4):678–690. https://doi.org/
10.1016/0272-6386(95)90610-x
3. Nieto MA (2011) The ins and outs of the
epithelial to mesenchymal transition in health
and disease. Annu Rev Cell Dev Biol
27:347–376.
https://doi.org/10.1146/
annurev-cellbio-092910-154036
4. Thiery JP, Acloque H, Huang RY, Nieto MA
(2009) Epithelial-mesenchymal transitions in
development
and
disease.
Cell
139
(5):871–890. https://doi.org/10.1016/j.cell.
2009.11.007
5. Thiery JP (2002) Epithelial-mesenchymal transitions in tumour progression. Nat Rev Cancer
2(6):442–454.
https://doi.org/10.1038/
nrc822
6. Gouignard N, Andrieu C, Theveneau E (2018)
Neural crest delamination and migration:
Looking forward to the next 150 years. Genesis
56:e23107. https://doi.org/10.1002/dvg.
23107
Using Xenopus Neural Crest to Study EMT
273