A clearer picture of a cell’s organization could help biologists learn how to reprogram a cell to stop cancer or other diseases


Science fiction writer Arthur C. Clarke’s Third Law states that “Any sufficiently advanced technology is indistinguishable from magic.”

Indika Rajapakse, Ph.D., is a believer. The engineer and mathematician now finds himself a biologist. And he thinks the beauty of blending these three disciplines is crucial to understanding how cells work.

His latest development is a new mathematical technique to begin to understand how a cell’s nucleus is organized. The technique, which Rajapakse and his collaborators tested on multiple cell types, revealed what the researchers called self-sustaining transcription clusters, a subset of proteins that play a key role in maintaining identity. cellular.

They hope this understanding will expose 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 huge role in understanding runaway cell division and whether we can reprogram a cancer cell. This means we need to understand in more detail what is going on. in the core,” said Rajapakse, an associate professor of computation. 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 the lead author of the article, published in Nature Communication. The project was led by a trio of graduate students with an interdisciplinary team of researchers.

The team improved on an older technology for looking at chromatin, called Hi-C, which maps parts of the genome close together. It can identify chromosomal translocations, such as those that occur in certain cancers. Its limitation, however, is that it only sees those adjacent genomic regions.

The new technology, called Pore-C, uses a lot more data to visualize how all the pieces of a cell’s 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 all of the complex, genome-wide overlapping relationships within cells.

“This multidimensional relationship that we can unambiguously understand. It gives us a more detailed way of understanding the organizing principles inside the core. If you understand that, you can also understand where those organizing principles diverge, like in the cancer,” Rajapakse said. “It’s like bringing three worlds together – technology, math and biology – to study inside the nucleus in more detail.”

The researchers tested their approach on neonatal fibroblasts, biopsied adult fibroblasts and B lymphocytes. They identified organizations of transcription clusters specific to each cell type. They also discovered what they called self-sustaining transcription clusters, which serve as key transcriptional signatures for a cell type.

Rajapakse describes this as the first step in a larger project.

“My goal is to build this kind of picture on the cell cycle to understand how a cell goes through different stages. Cancer is uncontrollable cell division,” Rajapakse said. If we understand how a normal cell changes over time, we can begin to look at controlled and uncontrolled systems and find ways to reprogram that system.”


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