SIAM News Blog

Computational Algorithm Improves Cell Reprogramming Techniques

By Lina Sorg

Because cells are not permanently static, the addition of certain cellular factors can reprogram and transform one type of cell into a completely different type. Nobel prizewinner Shinya Yamanaka’s research with induced pluripotent stem (iPS) cells (adult stem cells that are reprogrammed to an embryonic—or pluripotent—state) publicized this tactic. However, the intermediate step of reprogramming the cells raises safety concerns, because the reprogrammed cells run the risk of accruing cancerous mutations and thus behaving unpredictably.

Additionally, the experimental process necessary to prepare cells for manipulation is both costly and time-consuming, as manipulation demands the exact identification of a unique set of transcription factors needed for reprogramming. Because of the time, expense, and trial and error involved when identifying the necessary cellular factors, most researchers and doctors do not have the means to pursue this path, making transcription via iPS nearly impossible.

However, a team of researchers from Duke-NUS Medical School, Monash University, the University of Bristol, and RIKEN are perfecting a computational algorithm meant to surmount the present cell reprogramming challenge. Dr. Owen Rackham, a Senior Research Fellow and member of the Systems Genetics of Complex Disease Laboratory at Duke-NUS, spent five years creating the predictive algorithm, which is called Mogrify. By combining regulatory network information with gene expression data, Mogrify determines the ideal set of cellular factors required for a successful human cell conversion. It has the potential to improve regenerative medicine and advance the field of transdifferentiation, or the conversion of cells from one type to another while bypassing the high-risk pluripotent state.

The research team applied the algorithm to 134 tissues and 173 types of human cells. When tested against previously-successful cell conversions, Mogrify accurately predicted the necessary cell factors. The team also successfully executed two new human cell conversions, using only Mogrify’s predictions.

Rackham describes Mogrify as a “world atlas” for a cell, in that it enables researchers and doctors to map the development of human cell conversions. He hopes to apply Mogrify in a clinical setting to reprogram so-called ‘defective’ cells into healthy functioning cells, skipping over the expensive and potentially-risky middle iPS stage. The healthy cells would then be reinserted into patients. Read more of Rackham’s thoughts here.

Additionally, because Mogrify is wholly data-driven, its accuracy and predictive strength will continue to advance with use, as the system will continually record and store data in its framework.  With its use of a unique combination of systems biology and big data, the program has the potential to inspire future clinical applications. Mogrify is currently available online to other scientists and researchers. The researchers plan to apply the algorithm to the field of translational medicine to possibly create potential treatments for diseases such as cancer.

A paper about Mogrify was recently published in Nature Genetics.

Lina Sorg is the associate editor of SIAM News.
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