SAN DIEGO—Using a new artificial intelligence identifying method, researchers at the University of California–San Diego (UCSD) and their collaborators have taken a potentially significant leap forward in understanding human cells, according to a report published in the Nov. 24 issue of “Nature.”
The pilot study—which combines microscopy, biochemistry techniques, and artificial intelligence in a technique known as Multi-Scale Integrated Cell (MuSIC)—revealed around 70 components contained within a human kidney cell line, half of which had never been seen before.
“If you imagine a cell, you probably picture the colorful diagram in your cell biology textbook, with mitochondria, endoplasmic reticulum, and nucleus. But is that the whole story? Definitely not,” said Trey Ideker, a professor at UCSD’s School of Medicine and Moores Cancer Center. “Scientists have long realized there’s more that we don’t know than we know, but now we finally have a way to look deeper.”
In one example, the researchers spotted a group of proteins forming an unfamiliar structure.
Working with UCSD colleague Gene Yeo, they determined the structure to be a new complex of proteins that binds RNA. The complex is likely involved in splicing—a cellular event that enables the translation of genes to proteins—and helps determine which genes are activated at which times.
For many years, the scientists had been interested in mapping the inner workings of cells. What’s different about MuSIC is the use of deep learning to map the cell directly from cellular microscopy images.
“The combination of these technologies is unique and powerful because it’s the first time measurements at vastly different scales have been brought together,” said the study’s first author Yue Qin, a bioinformatics and systems biology graduate student in Ideker’s lab.
Microscopes allow scientists to see down to the level of a single micron—about the size of some organelles, such as mitochondria.
Smaller elements, such as individual proteins and protein complexes, can’t be seen through a microscope. Thanks to biochemistry techniques, which start with a single protein, scientists can get down to the nanometer scale, or one-billionth of a meter.
The team trained the MuSIC artificial intelligence platform to construct a model of the cell. The system doesn’t yet map the cell contents to specific locations, like a textbook diagram, in part because their locations aren’t necessarily fixed, the researchers said.
Ideker noted this was a pilot study to test MuSIC. The team has only looked at 661 proteins and one cell type.
“The clear next step is to blow through the entire human cell and then move to different cell types, people, and species,” Ideker said. “Eventually we might be able to better understand the molecular basis of many diseases by comparing what’s different between healthy and diseased cells.”