Freeze-frame imaging of synaptic activity using SynTagMA
Information within the brain travels from neuron to neuron across billions of synapses. At any given moment, only a small subset of neurons and synapses are active, but finding the active synapses in brain tissue has been a technical challenge. Here we introduce SynTagMA to tag active synapses in a...
Saved in:
Published in | Nature communications Vol. 11; no. 1; p. 2464 |
---|---|
Main Authors | , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
18.05.2020
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Information within the brain travels from neuron to neuron across billions of synapses. At any given moment, only a small subset of neurons and synapses are active, but finding the active synapses in brain tissue has been a technical challenge. Here we introduce SynTagMA to tag active synapses in a user-defined time window. Upon 395–405 nm illumination, this genetically encoded marker of activity converts from green to red fluorescence if, and only if, it is bound to calcium. Targeted to presynaptic terminals, preSynTagMA allows discrimination between active and silent axons. Targeted to excitatory postsynapses, postSynTagMA creates a snapshot of synapses active just before photoconversion. To analyze large datasets, we show how to identify and track the fluorescence of thousands of individual synapses in an automated fashion. Together, these tools provide an efficient method for repeatedly mapping active neurons and synapses in cell culture, slice preparations, and in vivo during behavior.
Calcium imaging has been used to visualize the activity of individual synapses, but cannot be scaled up to monitor thousands of synapses in tissue. Here, the authors present genetic tools that can be photoconverted from green to red to create a map of active synapses. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-020-16315-4 |