A single cell-based computational platform to identify chemical compounds targeting desired sets of transcription factors for cellular conversion

Menglin Zheng, Bingqing Xie, Satoshi Okawa, Soon Yi Liew, Hongkui Deng, Antonio Del Sol*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

Cellular conversion can be induced by perturbing a handful of key transcription factors (TFs). Replacement of direct manipulation of key TFs with chemical compounds offers a less laborious and safer strategy to drive cellular conversion for regenerative medicine. Nevertheless, identifying optimal chemical compounds currently requires large-scale screening of chemical libraries, which is resource intensive. Existing computational methods aim at predicting cell conversion TFs, but there are no methods for identifying chemical compounds targeting these TFs. Here, we develop a single cell-based platform (SiPer) to systematically prioritize chemical compounds targeting desired TFs to guide cellular conversions. SiPer integrates a large compendium of chemical perturbations on non-cancer cells with a network model and predicted known and novel chemical compounds in diverse cell conversion examples. Importantly, we applied SiPer to develop a highly efficient protocol for human hepatic maturation. Overall, SiPer provides a valuable resource to efficiently identify chemical compounds for cell conversion.

Original languageEnglish
Pages (from-to)131-144
Number of pages14
JournalStem Cell Reports
Volume18
Issue number1
Early online date8 Nov 2022
DOIs
Publication statusPublished - 10 Jan 2023

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