Neuroscience Led ‘Meta-Cell’ Fight Alzheimer’s

Neuroscientists at the University of California, Irvine have found a method for creating a “meta-cell” , a major discovery in neuroscience, that overcomes the difficulties of examining a single cell. Their method has already yielded valuable new knowledge and can be used to the study of various diseases across the body. Details of the meta-cell, developed by researchers at the University of California, Irvine’s Institute for Memory Impairments and Neurological Disorders (UCI MIND), are published in the online journal Cell Reports Methods.

Transcriptomics, which studies sets of RNA within organisms, allows scientists to understand what each cell performs. However, little is known about how specific genes function within a single cell, a technique known as single-cell genomics. As a result, determining whether genes are related with disease or performing normal duties remains difficult.

“The challenge is that a single cell does not contain much RNA,” said first author Samuel Morabito, a UCI graduate student researcher in the mathematical, computational and systems biology program. “This sparsity makes it hard to study. Even if a gene is present, technology might miss it.”

Single-cell genomics, on the other hand, is a potent neuroscience tool in the hunt for disease prevention and therapies.

“If we know that a gene process is degrading cells, we can potentially intervene,” said lead author Vivek Swarup, UCI assistant professor of neurobiology and behavior. We can devise therapeutics and target hundreds of genes to stop disease from developing.

The team has now devised a solution to this problem. “When we worked with a single cell, we looked for others that were the most similar in terms of transcriptomics,” Swarup explained. “By taking an average of 50 such cells, we developed a meta-cell that represents an individual cell but without the scarcity problems.”

The new method, known as hdWGCNA, improves on an existing method known as RNA bulk sequencing, which is extensively used but does not address single-cell genomes. The approach was devised using data from their laboratory as well as information from two other published investigations. They looked at microglia, which are the brain’s primary immune cells and carry the majority of the prevalent Alzheimer’s genetic risk factors. Their findings highlighted critical insights and key areas for further investigation.

“We found it’s not easy to distinguish between good microglia that are doing their normal job and bad microglia that damage neurons,” Swarup said. “Normal brains have good microglia, but a large proportion of microglia in people with Alzheimer’s is altered to be reactive microglia. Also, the bad kind specific to Alzheimer’s has different types, and we discovered microglia states that were not previously known.” The team plans to next look at how genes regulate microglia and whether gene activity can be moderated or stopped through therapeutics.

hdWGCNA is a versatile computational approach that may discover patterns of gene expression and gene modules related with certain diseases, independent of the organ or tissue involved.

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