A universal algorithm that directly reprograms any human cell type into any other type has been developed. It is described in a paper published yesterday in the Proceedings of the National Academy of Sciences.
The concept, developed by a team of University of Michigan scientists together with colleagues from the University of Maryland and Harvard University, combines biological information on genome structure and gene expression with mathematics, using an approach called data-guided control. The paper's authors include Roger Brockett, Ph.D. of Harvard and U-M mathematics department chair Anthony Bloch, Ph.D.
"Cells in our body always self-specialize," says Indika Rajapakse, Ph.D., the U-M bioinformatics and mathematics researcher who is senior author of the new paper. "What we propose could provide a shortcut to doing the same, to help any cell become a targeted cell type."
Rajapakse notes that the idea of direct reprogramming is not new. In the late 1980s, a team led by the late scientist Harold Weintraub turned skin cells directly into muscle cells by bathing the cells in transcription factors that encouraged certain genes in the cells' DNA to be "read". The new model builds on that idea, by also harnessing the power of transcription factors or TFs.
But instead of bathing the whole cell culture in one TF, the scientists aim to target cells with specific TFs at specific crucial times in their lifespan. They lay out a mathematical control model for harnessing all the information that can now be learned about cells at the molecular level, and combining it to map out the timing and sequence for injecting TFs to get the desired cell type.
"We have so much data now from RNA and transcription factor activity, and from Hi-C data of chromosome configuration that tells us how often two pieces of chromatin are near one another, that we believe we can go from the cell's initial configuration to the desired configuration," says Rajapakse.
The Hi-C technique lets scientists track the location of, and contact between, portions of chromatin. So even if two genes sit far apart on a long strand of DNA, they may come in close contact with one another when those looping, folding strands end up next to one another. If one of those genes gets "read", it may produce a transcription factor that then sets in motion the "reading" of the other gene, and the production of a certain protein that plays a key role in transforming the cell in some way.
The amount of data that would come out of analyzing these "topologically associating domains" in just one type of cell is huge. But modern bioinformatics techniques make it easier to make sense of it all.