Super resolution imaging of genetically labeled synapses in drosophila brain tissue
-
Spühler, Isabelle A.
Department of Physics, University of Fribourg, Fribourg, Switzerland - Department of Biology, University of Fribourg, Fribourg, Switzerland
-
Conley, Gaurasundar M.
Department of Physics, University of Fribourg, Fribourg, Switzerland
-
Scheffold, Frank
Department of Physics, University of Fribourg, Fribourg, Switzerland
-
Sprecher, Simon G.
Department of Biology, University of Fribourg, Fribourg, Switzerland
Show more…
Published in:
- Frontiers in Cellular Neuroscience. - 2016, p. 142
English
Understanding synaptic connectivity and plasticity within brain circuits and their relationship to learning and behavior is a fundamental quest in neuroscience. Visualizing the fine details of synapses using optical microscopy remains however a major technical challenge. Super resolution microscopy opens the possibility to reveal molecular features of synapses beyond the diffraction limit. With direct stochastic optical reconstruction microscopy, dSTORM, we image synaptic proteins in the brain tissue of the fruit fly, Drosophila melanogaster. Super resolution imaging of brain tissue harbors difficulties due to light scattering and the density of signals. In order to reduce out of focus signal, we take advantage of the genetic tools available in the Drosophila and have fluorescently tagged synaptic proteins expressed in only a small number of neurons. These neurons form synapses within the calyx of the mushroom body, a distinct brain region involved in associative memory formation. Our results show that super resolution microscopy, in combination with genetically labeled synaptic proteins, is a powerful tool to investigate synapses in a quantitative fashion providing an entry point for studies on synaptic plasticity during learning and memory formation.
-
Faculty
- Faculté des sciences et de médecine
-
Department
- Département de Biologie, Département de Physique
-
Language
-
-
Classification
-
Biological sciences
-
License
-
License undefined
-
Identifiers
-
-
Persistent URL
-
https://folia.unifr.ch/unifr/documents/305050
Statistics
Document views: 33
File downloads: