How Computational Analysis Can Reprogram Cells

By Jane Cook
October 6, 2021

Induced Pluripotent Stem Cells and Beyond

Determining how to reprogram cells from one type to another is an area of particular interest for regenerative medicine.

The classic example is the discovery of induced pluripotent stem cells (iPS), a Nobel-winning discovery by Shinya Yamanaka showing that mature, specialized cells could be reverted to immature cells that can then differentiate into any cell type in the body.

But the four genes needed to induce this transition back to a pluripotent state raises the question: is there a cocktail of genes or factors that can reprogram cells from one type to another, specific cell type instead of back to a naïve state?

Reprogram-Seq: Where Cellular Reprogramming Meets Bioinformatics

To answer this question, researchers at UT Southwestern developed a new scRNA-seq analysis workflow they termed “Reprogram-Seq,” published in Cell Reports in 2018 (Duan et.al.)

Their target was to learn how to reprogram fibroblasts (skin cells) to heart cells, so they performed scRNA-seq on heart tissue to first isolate their target cell type (epicardial cells), and then identify a group of transcription factors as unique to their cell type as possible.

Transcription factors are the key to cellular programming, and control gene expression at multiple points in a cell’s life. The researchers then infected fibroblasts with random combinations of the identified transcription factors and performed scRNA-seq again.

This is where this group’s unique approach paid off.

They developed computational tools to compare the state of cells infected with different cocktails of transcription factors to the transcriptome of their target epicardial cells. This allowed for extremely efficient identification of the exact combination of transcription factors that would reprogram a fibroblast to an epicardial-like cell.

The Promise of this Bioinformatic Pipeline

The Reprogram-Seq tools can be customized and applied to any target cell type, in theory, which provides huge research opportunities.

Understanding regulation of gene expression at the transcription factor level can provide insights for developing drug targets or understanding where a biological process goes wrong in disease.

Reprogramming cells is also extremely valuable for regenerative medicine and can be used to repair damaged tissue. Cells developed with Reprogram-Seq may even turn out to be faster and more specific than induced pluripotent stem cells.

The potential of scRNA-seq was harnessed by this research group’s bioinformatic pipeline development and is still only the beginning of what powerful sequencing techniques can do when custom computational analysis tools are developed in step with them.



Jane Cook, Journalist & Content Writer, Bridge Informatics

Jane is a Content Writer at Bridge Informatics, a professional services firm that helps biotech customers implement advanced techniques in management and analysis of genomic data. Bridge Informatics focuses on data mining, machine learning, and various bioinformatic techniques to discover biomarkers and companion diagnostics. If you’re interested in reaching out, please email daniel.dacey@old.bridgeinformatics.com or dan.ryder@old.bridgeinformatics.com.



Sources:

https://www.nobelprize.org/prizes/medicine/2012/press-release/

https://www.cell.com/cell-reports/pdf/S2211-1247(19)30708-9.pdf

https://github.com/jlduan/Reprogram-Seq

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