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HuC–eGFP mosaic labelling of neurons in zebrafish enables in vivo live cell imaging of growth cones

Overview of attention for article published in Journal of Molecular Histology, October 2012
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Title
HuC–eGFP mosaic labelling of neurons in zebrafish enables in vivo live cell imaging of growth cones
Published in
Journal of Molecular Histology, October 2012
DOI 10.1007/s10735-012-9462-7
Pubmed ID
Authors

James A. St John, Brian Key

Abstract

The field of axon guidance is taking advantage of the powerful genetic and imaging tools that are now available to visualise growth behaviour in living cells, both in vivo and in real time. We have developed a method to visualise individual neurons within the living zebrafish embryo which provides exceptional cellular resolution of growth cones and their filopodia. We generated a DNA construct in which the HuC promoter drives expression of eGFP. Injection of the plasmid into single cell fertilised zebrafish egg resulted in mosaic expression of eGFP in neurons throughout the developing embryo. By manipulating the concentration of injected plasmid, it was possible to optimise the numbers of neurons that expressed the construct so that individual growth cones could be easily visualised. We then used time-lapse high magnification widefield epifluorescence microscopy to visualise the growth cones as they were exploring their environment. Growth cones both near the surface of the embryo as well as deep within the developing brain of embryos at 20 h post fertilisation were clearly imaged. With time-lapse sequence imaging with intervals between frames as frequent as 1 s there was minimal loss of fluorescence intensity and the dynamic nature of the growth cones became evident. This method therefore provides high magnification, high resolution time-lapse imaging of living neurons in vivo and by use of widefield epifluorescence rather than confocal it is a relatively inexpensive microscopy method.

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Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 18%
Researcher 4 12%
Student > Master 4 12%
Student > Bachelor 3 9%
Professor 2 6%
Other 8 24%
Unknown 6 18%
Readers by discipline Count As %
Neuroscience 9 27%
Agricultural and Biological Sciences 8 24%
Biochemistry, Genetics and Molecular Biology 5 15%
Physics and Astronomy 1 3%
Medicine and Dentistry 1 3%
Other 1 3%
Unknown 8 24%