What drives brain diseases


The brain is often referred to as a “black box”—one that’s difficult to peer inside and determine what’s happening at any given moment. This is part of the reason why it’s difficult to understand the complex interplay of molecules, cells and genes that underly neurological disorders. But a new CRISPR screen method has the potential to uncover new therapeutic targets and treatments for these conditions.

The method, outlined in a study published in Cell, provides a way to rapidly examine the brain cell types linked to key developmental genes at a scale never done before—helping unravel the genetic and cellular drivers of different neurological diseases.

“We know that certain genetic variations in our genome can make us vulnerable or resilient towards different diseases, but which specific cell types are behind a disease? Which brain regions are susceptible to the genome mutations in those cells? These are the kinds of questions we're trying to answer,” says the senior author. “With this new technology, we want to build a more dynamic picture across brain region, across cell type, across the timing of disease development, and really start understanding how the disease happened—and how to design interventions.”

Thanks to over a decade’s efforts in human genetics, scientists have had access to long lists of genetic changes that contribute to a range of human illnesses, but knowing how a gene causes a disease is very different than knowing how to treat the illness itself. Every risk gene may impact one or several different cell types. Comprehending how those cell types—and even individual cells—impact a gene and affect disease progression is key to understanding how to ultimately treat that disease.

This is the study’s first author, co-invented the new technique, named in vivo Perturb-seq. This method leverages CRISPR-Cas9 technology and a readout, single-cell transcriptomic analysis, to measure its impact on a cell: one cell at a time. Using CRISPR-Cas9, scientists can make precise changes to the genome during brain development, and then closely study how those changes affect individual cells using single-cell transcriptomic analysis—for tens of thousands of cells in parallel.

“Our new system can measure individual cells’ response after genetic perturbations, meaning that we can paint a picture of whether certain cell types are more susceptible than others and react differently when a particular mutation happens,” the author says.

Previously, the method for introducing the genetic perturbations into the brain tissue was very slow, often taking days or even weeks, which created suboptimal conditions for studying gene functions related to neurodevelopment. But the new screening method allows for rapid expression of perturbation agents in living cells within 48 hours—meaning scientists can quickly see how specific genes function in different types of cells in a very short amount of time.

The method also enables a level of scalability that was previously impossible—the research team was able to profile more than 30,000 cells in just one experiment, 10-20 times accelerated from the traditional approaches. In many of the brain regions they examined, such as the cerebellum, they were able to collect tens of thousands of cells that previous labeling methods could not reach.

In a pilot study using this new technology, the team’s interest was piqued when they saw a genetic perturbation elicit different effects when perturbed in different cell types. This is important because those impacted cell types are the sites of action for particular diseases or genetic variants. “Despite their smaller population representations, some low-abundant cell types may have a stronger impact than others by the genetic perturbation, and when we systematically look at other cell types across multiple genes, we see patterns. That’s why single-cell resolution—being able to study every cell and how each one behaves—can offer us a systematic view,” the author says.

With her new technology in hand, the authors plan to apply it to better understand neuropsychiatric conditions and how certain cell types correspond with various brain regions.

https://www.cell.com/cell/fulltext/S0092-8674(24)00476-8

http://sciencemission.com/site/index.php?page=news&type=view&id=protocols%2Fmassively-parallel-in&filter=25

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