Science fiction author Arthur C. Clarke’s Third Law states: “Any sufficiently advanced technology is indistinguishable from magic.”
Indika Rajapakse, Ph.D., is a believer. The engineer and mathematician now finds himself as a biologist. And he believes the beauty of merging these three disciplines is crucial to unraveling how cells work.
His latest development is a new mathematical technique to understand how a cell nucleus is structured. The technique, which Rajapakse and co-workers tested on multiple cell types, revealed what the researchers termed self-sustaining transcription clusters, a subset of proteins that play a key role in maintaining cell identity.
They hope this understanding will uncover vulnerabilities that can be targeted to reprogram a cell to stop cancer or other diseases.
“More and more cancer biologists believe that the organization of the genome plays a big role in understanding uncontrollable cell division and whether we can reprogram a cancer cell. That means we need to understand more details about what’s happening in the nucleus,” said Rajapakse, associate professor of computational medicine and bioinformatics, mathematics and biomedical engineering at the University of Michigan. He is also a member of the UM Rogel Cancer Center.
Rajapakse is senior author of the paper, published in nature communication. The project was led by a trio of PhD students with an interdisciplinary research team.
The team improved an older technology for studying chromatin called Hi-C, which maps which parts of the genome are close together. It can identify chromosomal translocations that occur in some types of cancer. However, its limitation is that it only sees these contiguous genomic regions.
The new technology, called Pore-C, uses much more data to visualize how all parts in the nucleus interact. The researchers used a mathematical technique called hypergraphs. Think: three-dimensional Venn diagram. It allows researchers to see not just pairs of interacting genomic regions, but the entirety of the complex and overlapping genome-wide relationships within cells.
“We can clearly understand this multidimensional relationship. It gives us a more detailed way of understanding the organizing principles within the core. If you understand that, you can also understand where these organizing principles diverge, like in cancer,” Rajapakse said. “It’s like putting three worlds together – technology, mathematics and biology – to examine more details inside the core.”
The researchers tested their approach on neonatal fibroblasts, biopsied adult fibroblasts and B lymphocytes. They identified organizations of transcription clusters that are specific to each cell type. They also found so-called self-sustaining transcription clusters, which serve as important transcription signatures for a cell type.
Rajapakse describes this as the first step into a larger picture.
“My goal is to create such a picture of the cell cycle in order to understand how a cell goes through different stages. Cancer is uncontrollable cell division,” said Rajapakse. If we understand how a normal cell changes over time, we can begin to study controlled and uncontrolled systems and find ways to reprogram that system.”