A cheat sheet to help know your neurons

Not all neurons are equal, so researcher are building a “cheat sheet” to clarify things.

In the largest categorisation of mouse visual neurons to date, researchers from Allen Institute for Brain Science have devised an elegant three-trait system to sort and classify neurons. They found more than expected with 28 specific types, as described in their paper, published in Cell.

Fascinatingly, many of the types were restricted to certain locations in the brain, which means they can be used to identify sick cells and potentially trace where they should be and what they should be doing. 

“It’s becoming increasingly clear that in some disorders there’s a deficiency in a very particular type of neuron in a particular part of the brain,” says co-author Gabe Murphy.

“The more we understand the different types of neurons that exist and what makes them unique, the more we can understand what goes wrong if you have vulnerabilities in one or more of those types in disease.”

Much like how each animal looks different, neuron cells look and behave differently.  This means they can be categorised into different types based on three unique traits; their shape, their electrical properties, and the genes they use.

Based on these types, the “cheat sheet” can be used to fill in the gaps and identify a neuron when only some properties of the cell are known.

A highlight of this approach is the use of gene profiles. Each time a gene is “switched on” in a cell, the DNA is copied to a transcript. These transcripts – collectively called the transcriptome – make a genetic fruit salad that is beautifully unique to each neuron. 

As a result, when a problem in the brain arises, each individual cell can be compared back to the cheat sheet to see what is missing from the genetic fruit salad.

“With this approach, we’re now learning something new about the brain by adding transcriptomics to the method of studying neuron morphology that’s been around for more than 100 years,” says researcher Staci Sorensen.

“Using transcriptomics to label cell types has been revolutionary. When we sort cells in this way, we’re able to reveal patterns we hadn’t noticed before.”

They used a technique called Patch-seq to define the transcriptome in 4200 cells. This was then compared to the shape and electrical properties of the neurons, which has not been done before. This revealed a lot more diversity in the cells than they realised when looking at only shape and electrical properties, creating a much more holistic view of brain cells.

Not only this, but finding out the shape of a cell is very time consuming compared to Patch-seq. In fact, they had help constructing cell shapes from a citizen science project in the form of a game. Mozak Brainbuilder is a neuroscience game that encourages players to build models of brain cells, and 500 of these were used in the cheat sheet.

“This study has essentially provided a ‘lookup table’ for other neuroscientists, such that if you have information about only one property of a neuron, you can infer the other properties,” said Edward Callaway of the Salk Institute for Biological Studies, US.

“We need this kind of linking study to figure out what are the true cell types of the brain so we can begin to characterize them. This dataset enables that linking, and it will no doubt prove a great resource for future discovery.”