Rational reprogramming of cellular states by combinatorial perturbation

BioRxiv : the Preprint Server for Biology
Jialei DuanGary Hon

Abstract

Ectopic expression of transcription factors (TFs) can reprogram cell state. However, due to the large combinatorial space of possible TF cocktails, it remains difficult to identify TFs that reprogram specific cell types. Here, we develop Reprogram-Seq to experimentally screen thousands of TF cocktails for reprogramming performance. Reprogram-Seq leverages organ-specific cell atlas data with single-cell perturbation and computational analysis to predict, evaluate, and optimize TF combinations that reprogram a cell type of interest. Focusing on the cardiac system, we perform Reprogram-Seq on MEFs using an undirected library of 48 cardiac factors and separately on a directed library of 10 epicardial-related TFs. We identify a novel combination of 3 TFs which efficiently reprogram MEFs to epicardial-like cells that are transcriptionally, molecularly, morphologically, and functionally similar to primary epicardial cells. Reprogram-Seq holds promise to accelerate the generation of specific cell types for regenerative medicine.

Related Concepts

Heart
Transcription Factor
Organ
Evaluation
Anatomical Space Structure
Fluorouracil/Methotrexate Protocol
Sendai cocktail
Protein Expression
Regenerative Medicine
Elf4 protein, mouse

Related Feeds

Allogenic & Autologous Therapies

Allogenic therapies are generated in large batches from unrelated donor tissues such as bone marrow. In contrast, autologous therapies are manufactures as a single lot from the patient being treated. Here is the latest research on allogenic and autologous therapies.

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.

CZI Human Cell Atlas Seed Network

The aim of the Human Cell Atlas (HCA) is to build reference maps of all human cells in order to enhance our understanding of health and disease. The Seed Networks for the HCA project aims to bring together collaborators with different areas of expertise in order to facilitate the development of the HCA. Find the latest research from members of the HCA Seed Networks here.