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A computer-guided design tool to increase the efficiency of cellular conversions

Human cell conversion technology has become an important tool for devising new cell transplantation therapies, generating disease models and testing gene therapies. However, while transcription factor over-expression-based methods have shown great promise in generating cell types in vitro, they ofte...

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Autores principales: Jung, Sascha, Appleton, Evan, Ali, Muhammad, Church, George M., del Sol, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954801/
https://www.ncbi.nlm.nih.gov/pubmed/33712564
http://dx.doi.org/10.1038/s41467-021-21801-4
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author Jung, Sascha
Appleton, Evan
Ali, Muhammad
Church, George M.
del Sol, Antonio
author_facet Jung, Sascha
Appleton, Evan
Ali, Muhammad
Church, George M.
del Sol, Antonio
author_sort Jung, Sascha
collection PubMed
description Human cell conversion technology has become an important tool for devising new cell transplantation therapies, generating disease models and testing gene therapies. However, while transcription factor over-expression-based methods have shown great promise in generating cell types in vitro, they often endure low conversion efficiency. In this context, great effort has been devoted to increasing the efficiency of current protocols and the development of computational approaches can be of great help in this endeavor. Here we introduce a computer-guided design tool that combines a computational framework for prioritizing more efficient combinations of instructive factors (IFs) of cellular conversions, called IRENE, with a transposon-based genomic integration system for efficient delivery. Particularly, IRENE relies on a stochastic gene regulatory network model that systematically prioritizes more efficient IFs by maximizing the agreement of the transcriptional and epigenetic landscapes between the converted and target cells. Our predictions substantially increased the efficiency of two established iPSC-differentiation protocols (natural killer cells and melanocytes) and established the first protocol for iPSC-derived mammary epithelial cells with high efficiency.
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spelling pubmed-79548012021-03-28 A computer-guided design tool to increase the efficiency of cellular conversions Jung, Sascha Appleton, Evan Ali, Muhammad Church, George M. del Sol, Antonio Nat Commun Article Human cell conversion technology has become an important tool for devising new cell transplantation therapies, generating disease models and testing gene therapies. However, while transcription factor over-expression-based methods have shown great promise in generating cell types in vitro, they often endure low conversion efficiency. In this context, great effort has been devoted to increasing the efficiency of current protocols and the development of computational approaches can be of great help in this endeavor. Here we introduce a computer-guided design tool that combines a computational framework for prioritizing more efficient combinations of instructive factors (IFs) of cellular conversions, called IRENE, with a transposon-based genomic integration system for efficient delivery. Particularly, IRENE relies on a stochastic gene regulatory network model that systematically prioritizes more efficient IFs by maximizing the agreement of the transcriptional and epigenetic landscapes between the converted and target cells. Our predictions substantially increased the efficiency of two established iPSC-differentiation protocols (natural killer cells and melanocytes) and established the first protocol for iPSC-derived mammary epithelial cells with high efficiency. Nature Publishing Group UK 2021-03-12 /pmc/articles/PMC7954801/ /pubmed/33712564 http://dx.doi.org/10.1038/s41467-021-21801-4 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Jung, Sascha
Appleton, Evan
Ali, Muhammad
Church, George M.
del Sol, Antonio
A computer-guided design tool to increase the efficiency of cellular conversions
title A computer-guided design tool to increase the efficiency of cellular conversions
title_full A computer-guided design tool to increase the efficiency of cellular conversions
title_fullStr A computer-guided design tool to increase the efficiency of cellular conversions
title_full_unstemmed A computer-guided design tool to increase the efficiency of cellular conversions
title_short A computer-guided design tool to increase the efficiency of cellular conversions
title_sort computer-guided design tool to increase the efficiency of cellular conversions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954801/
https://www.ncbi.nlm.nih.gov/pubmed/33712564
http://dx.doi.org/10.1038/s41467-021-21801-4
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