Mapping Cell Diversity Using a Text-Mining Technique

Inspired by text-mining methods, a new bioinformatics method called cisTopic helps scientists gain insight into the mechanisms underlying the differences in gene regulation across cells by looking for common “topics.” The paper, published yesterday in Nature Methods, demonstrates a broad range of applications for this method.

“All the cells in our body essentially contain the same DNA,” says senior author Stein Aerts of VIB–KU Leuven. “What makes every cell type unique is which genes are active at any given time.”

Recent advances in single-cell technology have enabled scientists to look at gene activity and the accessibility of regulatory DNA regions for thousands of individual cells. But this information has not yet solved the challenge of reverse-engineering the genomic regulatory code. To tackle this problem, the researchers borrowed a computational technique from the text-mining field called topic modeling.

“In text mining, computers can discover ‘topics’ from large collections of text, as well as terms that are important for each topic,” says co–first author Carmen Bravo González-Blas. “When applied to our problem of gene control, the computer discovers topics that are important for each cell type in our body. It also allowed us to identify regulatory regions for each topic.”

The researchers applied cisTopic to cell populations that are biologically complex, such as the cells present in the mammalian brain. Not only did cisTopic allow them to recover the major cell types in the brain but also the team was able to identify new subpopulations and master regulators of neuronal cell types.

“In addition to the brain, we also used cisTopic to investigate dynamic changes in gene accessibility in melanoma cell cultures from patients,” says Aerts. “When we modulated one of the known important modulators in these cancer cells, we could for the first time track changes in the accessibility of different DNA regions over time. Such approaches will finally allow us to better understand what these master regulators actually do in cancer cells and which genes they control.”

These different applications illustrate the value of the team’s new method for studying the players and mechanism that orchestrate gene regulation in our cells. According to computational biologists like Aerts, this is an important step towards real-time and personalized monitoring of cell states in health and disease.