Mathematics enable scientists to understand organization within a cell's nucleus
Classes of transcription clusters. In a self-sustaining transcription cluster, a TF and the gene encoding that TF are both present. The inter- and intra-chromosomal examples in (a) and (b), respectively, illustrate this phenomenon where in a we see the TF of interest (orange triangle) circulating at the cluster, its binding motif present on the chromatin (orange portion), and its corresponding gene expressed (orange rectangle on Chromosome 6). The gray shapes represent additional TFs with binding motifs (gray portion of chromatin) at the cluster. Black rectangles on Chromosomes 3, 9, and 19 represent additional genes present in the cluster. c An analog-independent class of transcription clusters where we observe a TF (red square) bind at a transcription cluster (red cluster) and its corresponding gene expressed in a separate transcription cluster (gray cluster), yet not in the same cluster. d An analog-independent class of transcription clusters where we observe a TF (green circle) bind at a transcription cluster (green cluster) and its corresponding gene expressed but not within a transcription cluster. e Genome-wide cell type-specific self-sustaining transcription clusters extracted from multi-way contact data and decomposed into Hi-C contact matrices at 100 kb resolution. Contact frequencies are log-transformed for better visualization. Frequencies along the diagonal indicate interaction between two or more unique multi-way loci that fall within the same 100 kb bin. Axis labels are non-contiguous 100 kb bin coordinates in chromosomal order. Multi-way contacts that make up the self-sustaining transcription clusters are superimposed. Multi-way contacts with green-colored loci represent 'core' transcription clusters - transcription clusters containing a master regulator and its gene analog. An example read-level contact map for the inter-chromosomal FOXO3 self-sustaining transcription cluster is denoted by the orange highlighted box in the adult fibroblast contact matrix and a read-level contact map for the intra-chromosomal ZNF320 self-sustaining transcription cluster is denoted by the blue highlighted box. Values along the left axis of these read-level contact matrices are base-pair positions of the contacting loci in the genome. Credit: Nature Communications (2022). DOI: 10.1038/s41467-022-32980-z

Any sufficiently advanced technology is indistinguishable from magic.

Indika Raja pakse is a believer. A mathematician and engineer is now a Biologist. Blending these disciplines is important to unraveling how cells work.

A new mathematical technique is being used to understand how a cell's nucleus is arranged. The self-sustaining transcription clusters, a subset of proteins that play a key role in maintaining cell identity, were revealed by the technique.

They hope that this understanding will expose vulnerabilities that can be used to reprogram a cell.

Cancer biologists think genome organization plays a big part in understanding uncontrollable cell division and whether we can reprogram a cancer cell. Rajapakse said that we need to understand more about what's happening in the nucleus. The U-M has a cancer center.

The paper is in Nature Communications. A group of graduate students led the project.

The team improved upon an older technology to look at which parts of the genome are close together. It's possible to identify those that occur in cancer. It is only able to see the adjacent genomic regions.

The new technology, called Pore-C, uses more data to show how the nucleus of a cell interacts with other parts. Hypergraphs is a mathematical technique used by the researchers. Think of a diagram in three dimensions. It allows researchers to see more than just the pairs of genomic regions that interact.

We can comprehend this multi-dimensional relationship. We can understand organizational principles inside the nucleus with more detail. Rajapakse said that if you understand that, you can understand where the organization's principles deviate. It's like putting three worlds together to study something.

They tested their approach on fibroblasts, adult fibroblasts and B cells. The groups of transcription clusters were identified. They discovered self-sustaining transcription clusters, which are key genes for a cell type.

This is the first step in a larger picture.

To understand how a cell goes through different stages, I want to build a picture over the cell cycle. Rajapakse said that cancer is uncontrollable. We can reprogram systems if we understand how a normal cell changes over time.

More information: Gabrielle A. Dotson et al, Deciphering multi-way interactions in the human genome, Nature Communications (2022). DOI: 10.1038/s41467-022-32980-z Journal information: Nature Communications