Researchers say they have mapped the gene expression of each individual brain cell during aging in the fruit fly. Their study (“A Single-Cell Transcriptome Atlas of the Aging Drosophila Brain”), published in Cell, could lead to new insights on the workings of the brain as it ages, according to the scientists.
“The diversity of cell types and regulatory states in the brain, and how these change during aging, remains largely unknown. We present a single-cell transcriptome atlas of the entire adult Drosophila melanogaster brain sampled across its lifespan. Cell clustering identified 87 initial cell clusters that are further subclustered and validated by targeted cell-sorting. Our data show high granularity and identify a wide range of cell types,” write the investigators.
“Gene network analyses using SCENIC revealed regulatory heterogeneity linked to energy consumption. During aging, RNA content declines exponentially without affecting neuronal identity in old brains. This single-cell brain atlas covers nearly all cells in the normal brain and provides the tools to study cellular diversity alongside other Drosophila and mammalian single-cell datasets in our unique single-cell analysis platform: SCope. These results, together with SCope, allow comprehensive exploration of all transcriptional states of an entire aging brain.”
“All organs and tissues are composed of many different cells that communicate with each other to perform their specific functions,” says Stein Aerts, Ph.D., from the Flanders Institute of Biotechnology (VIB-KU Leuven). Although they share the same DNA, they all express a distinct set of genes, and to understand what is really going on, we need to know which cells are doing what and when.”
“There are about 15,000 genes and roughly 100,000 cells in the fly brain. So a quick calculation shows we are looking at more than a billion data points to analyze and map over time,” adds Kristofer Davie, research scientist, who notes that the only way to mine this enormous amount of data is with help from artificial intelligence.
The team used machine-learning methods to accurately predict the age of a cell, based on information gathered from brain cells of flies at different ages. Similar to our brain, the fly brain has distinct cells responsible for sleep, memory, smell, etc. The researchers catalogued more than 80 different cell type clusters and also found that not all of them age in the same way.
“Cells constantly change their role—as they age, in response to changes in the environment, upon disease,” explains Dr. Aerts. “The holy grail is to assess the molecular state of a patient's tissues and cells in real time, allowing for early diagnosis of any disease and effective, personalized treatments. But to get there we need to develop both the models and the tools to understand the dynamics of cellular changes.”
Developing biomedical applications will require more work and more collaboration, says Dr. Aerts.
“We have made all of our fly brain data freely available on a unique online analysis platform, where other scientists can deposit their data as well,” he points out.
Together with international colleagues who use single-cell technology to study different organs of the fruit fly, he founded the Fly Cell Atlas consortium. “It is a really exciting time for biomedical research. By looking at gene expression at single-cell resolution, we are uncovering so much information we can barely keep up,” says Dr. Aerts.