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Rewriting Life

DNA Sequencing Could Map the Brain’s Wiring

A fast, cheap way to identify neuron-to-neuron connections could shed light on disorders including autism and schizophrenia.

Many brain disorders, such as autism and schizophrenia, are likely caused by abnormal connections in the brain. Better understanding of these abnormalities could provide clues to ways to treat these problems.

Neuroscientists plan to use a virus that carries DNA from neuron to neuron, combined with DNA sequencing technology, to understand how the brain of the mouse is wired, cell by cell.

The project proposed by Anthony Zador and others at Cold Spring Harbor Laboratory in New York, however, offers a cheaper and faster way to map neuron-to-neuron conversations happening in the brain and could shed light on disorders including autism or schizophrenia.

The effort would be an exciting addition to the burgeoning field of “connectome” projects—research efforts to map the neural connections in the brain—says Amy Bernard, director of Structured Science at the Allen Institute for Brain Science in Seattle. “Fundamental to understanding any foundation of disease or function is first understanding your parts list: what all the cells are, and how they fit together,” says Bernard.

The symptoms of many brain disorders and diseases, especially poorly understood conditions such autism or schizophrenia, could arise from abnormal connections in the brain. “It’s largely thought that these diseases might impact the wiring diagram of the brain. Understanding the normal version will help us to understand when it is not connected correctly and what might be wrong,” says Bernard. 

Most connectome projects rely on visual inspection of the brain’s structure with the aide of neuron-tracing dyes and microscopes. These methods let scientists see how major neuronal roadways connect one area of the brain to another, but they don’t allow a close-up view of the synapses (the intersection of two neurons where information is exchanged). More intensive microscopy methods do allow for high-precision views of synapses, but the process is time-consuming and expensive. Given the estimated billions of synapses in a mouse brain, a faster, high-throughput method could accelerate our understanding of how neurons talk to one another in the mammalian brain.

In PLOS Biology this week, the team describes a method in which small snippets of DNA are passed from one neuron to the next as part of a virus. Each neuron is labeled with a unique DNA barcode—a handful of DNA letters or bases in a specific order that will be unique to each neuron. With just 20 letters, the team can uniquely label a trillion neurons—many more than exist in the brain of a mouse.

“We engineer the virus to move the barcodes across synapses, so now, each neuron becomes a bag of barcodes, containing copies of its own barcode and copies of all the neurons that talk to it,” says Zador.

Once the virus has carried the barcodes from one neuron to another, another modern biology trick will be used to map the connections. The team will harvest DNA from the brain and sequence the combined barcodes. Computers will then sort out which neurons exchanged barcodes with one another. 

“This strategy is really nice, particularly as the cost of sequencing is going down,” says Bernard. “It’s not going to give you the whole-brain, whole-structure information that some of the other connectome projects are focusing on,” but instead will provide a more up-close view of the brain’s connections.

Zador hopes that the data from his team’s connectome will help scientists tune their hypothesis about how the brain works by providing them with data of how it is wired.

“Right now, our knowledge of circuitry is so rudimentary that [hypotheses are] largely unconstrained,” says Zador. When researchers have an idea about how the brain works, they have no way to easily check whether the wiring of the brain is compatible with their hypothesis. “One of my major hopes has been that we can [improve] our understanding of the circuitry to a point where we could then make much faster progress in understanding how brains compute.”

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