Neuroscientists’ new process reveals single-cell secrets for novel therapeutic targets.
Neuroscientists investigating the gene changes behind Alzheimer’s disease have developed a process of making a “meta-cell” that overcomes the challenges of studying a single cell; this technique has already revealed important new information and can also be used to study other diseases throughout the body [1].
Details about the meta-cell – which was created by researchers with the UC Irvine Institute for Memory Impairments and Neurological Disorders, known as UCI MIND – have been published in the journal Cell Press.
Longevity.Technology: Technologies called transcriptomics that study sets of RNA within organisms enable scientists to understand what each cell does. However, the question of how particular genes work within a solo cell, a process known as single-cell genomics, has not been widely studied, and as a result, it has still been difficult to determine which genes are associated with disease or carrying out normal functions.
Single-cell genomic could plays a pivotal role in advancing longevity research; by scrutinizing individual cells and unraveling the intricate mechanisms that underlie aging at the cellular level, this powerful technology can enable scientists to examine the genomic and epigenomic variations that occur within a diverse population of cells, and decipher the molecular changes associated with aging, such as accumulated DNA damage, altered gene expression patterns and cellular senescence. Single-cell genomics also facilitates the identification of rare cell populations, including stem cells or rejuvenated cells, which hold immense potential for rejuvenation therapies. Moreover, by comparing the genomes of healthy long-lived individuals with those with shorter lifespans, single-cell genomics aids in the identification of genetic factors and regulatory networks that impact lifespan. But getting the technology to a point where it can be useful is tricky, as the UCI team found out.
“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 [2].”
However, single-cell genomics is a powerful tool in the search for disease prevention and cures, so the research team took up the gauntlet.
“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 [2].”
The team has now devised a way to eliminate this obstacle. “In working with an individual cell, we looked for others that are the most similar in terms of transcriptomics,” Swarup said. “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 process is named hdWGCNA (don’t even attempt to pronounce it). It improves on a method called RNA bulk sequencing that is widely used but does not address single-cell genomes. Instead, the researchers used their lab’s own data and information from two other published studies to devise the process, examining microglia, the brain’s primary immune cells, which carry most of the common Alzheimer’s genetic risk factors. Their findings revealed important insights and key areas to investigate further.
“We found it’s not easy to distinguish between good microglia that are doing their normal job and bad microglia that damage neurons,” Swarup explained. “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 even stopped – through therapeutics.
While the researchers are focusing on neurological disorders, hdWGCNA is a versatile computational approach that can identify patterns of gene expression and gene modules associated with specific diseases, regardless of the organ or tissue involved. This means it could have a bright future ahead when it comes to helping to shape longevity therapeutics.
[1] https://www.cell.com/cell-reports-methods/fulltext/S2667-2375(23)00127-3
[2] https://bit.ly/3pk2ajJ
