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News

Billions of neuronal junctions make up new ‘synaptome’ map

by  /  15 November 2017
Mind the gap: Abnormalities in proteins at synapses are implicated in autism.

Science Picture Co / Science Source

Researchers have charted billions of synapses in the mouse brain and sorted them by type, according to unpublished findings presented today at the 2017 Society for Neuroscience annual meeting in Washington, D.C.

They used a new technique that captures and categorizes these tiny gaps between neurons by labeling and sorting the proteins that line them. The method involves a new way to illuminate the proteins at synapses and a machine-learning method to analyze them. The resulting ‘synaptome’ is a comprehensive catalog of synapses in the mouse brain.

The technique could be used to map synapses in mouse models of conditions such as autism.

“We can apply this method to any disease model, in principle,” says Zhen Qiu, a postdoctoral researcher in Seth Grant’s lab at the University of Edinburgh in Scotland.

Synapses are junctions between neurons, and they mediate the transfer of information between the cells. Abnormalities in proteins at synapses have been implicated in autism and other neurodevelopmental disorders.

Some of these proteins are on the neuronal branch that sends the signal, and others are on the neuron that receives it. The researchers injected into the brains of mice florescent markers that attach to proteins at the receiving end. The markers reveal the number of parts, or subunits, that make up the protein by the intensity of the light emitted. And the pattern of fluorescence indicates each protein’s shape.

Sorting synapses:

The researchers used a spinning disk confocal microscope to capture the fluorescence. The result is a detailed picture of the location, size, shape and other features of these proteins.

The method is fast: Imaging an entire mouse brain took just half a day, Qiu says.

“That is feasible and practical for our study because we are doing hundreds of brains in our experiments,” he says.

The researchers wound up with terabytes of data. So they developed a machine-learning technique that automatically detects and categorizes the proteins based on the pattern of florescence. For instance, the software could determine how round or oblong the proteins are. It could decipher the proteins’ size and pinpoint the number of synapses within various brain regions.

The program then used the characteristics of proteins at each synapse to sort the junctions into categories. For instance, it revealed that the hippocampus has several synapse subtypes.

The team plans to test the effect of drugs such as ketamine on synapse organization and characteristics. They also hope to generate mouse synaptomes across all stages of development, from pup to adult.

For more reports from the 2017 Society for Neuroscience annual meeting, please click here.


  • Sharwan Kumar

    People who could benefit from such type of work should collaborate with. These people to facilitate their work.

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