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Systematic mapping of TF-mediated cell fate changes by a pooled inductioncoupled with scRNA-seq and multi-omics approaches

ABSTRACT: Transcriptional regulation controls various cellular functions via the interactionsbetween cell-type-specific transcription factors (TFs) and their chromosomaltargets. While multiple TFs capable of converting cell fates from one to anotherhave been reported, only a few systematic studies aiming to understand thefate conversion potential of numerous individual TFs have been reported. Here,we propose an iTF-seq method (pooled induction of individual TFs followed bysingle-cell RNA sequencing) to identify potent TFs capable of converting cellfates and elucidate their lineage specification potential at a single-cell level.Enabling metabolic biotinylation of TFs during the process, the method allowssubsequent multi-omics approaches to understand underlying actionmechanisms of TFs during cell fate changes. Our pilot iTF-seq of 80 TFs inmouse embryonic stem (ES) cells has identified multiple previously known andunknown TFs triggering transcriptome changes within one day of TF induction.Subsequent tests revealed that Gcm1 and Otx2 function as activators andpioneer factors, while they resulted in distinct cell fates and gene expressionprograms upon induction.

ORGANISM(S): Mus musculus

PROVIDER: GSE220724 | GEO | 2024/02/05

REPOSITORIES: GEO

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Project description:A network of transcription factors (TFs) determines cell identity, but identity can be altered by overexpressing a combination of TFs. In principle, this opens the possibility of achieving one of the goals of regenerative medicine generating the desired differentiated cells from pluripotent stem cells, such as embryonic stem (ES) cells and induced pluripotent stem (iPS) cells. However, choosing and verifying combinations of TFs for specific cell differentiation has been daunting due to a large number of possible combinations of ~2,000 TFs. Here we report an unbiased systematic approach identifying individual TFs that can direct efficient and rapid specific lineage differentiation. We start from a correlation matrix of global gene expression responses to the induction of single TFs and global gene expression profiles of a variety of tissues and organs. Based on the correlation matrix, we select TFs as examples and show that their overexpression differentiates ES cells into cells of specific organs, as predicted: Sfpi1 for blood cells, Hnf4a or Foxa1 for hepatocytes, and Ascl1 for neurons. Furthermore, we show that transfection of synthetic mRNAs of Sfpi1, Hnf4a, or Ascl1 generate correspondingly specific target cells. These results demonstrate both the wide-ranging utility of this approach to identify potent TFs for cell differentiation, and also the unanticipated capacity of single TFs to directly guide differentiation to specific lineage fates. Previously, we generated the global gene expression profiles obtained by overexpressing single TFs using the NIA mouse ES cell bank, which consists of 137 mouse ES cell lines carrying a doxycycline-regulatable TF. We then generated the correlation matrix by comparing TF-induced gene expression profiles and the expression profiles of a variety of cell types. TFs predicted by the correlation matrix for specific cell differentiation were selected and subjected to the detailed differentiation assays. ES cell lines were cultured in the GMEM with 1% FBS, 10% knockout serum (invitrogen), and LIF (Millipore). To induce differentiation, ES cell lines were cultured in the differentiation medium (DM) [(alpha minimal essential medium, aMEM) supplemented with 10% fetal calf serum and 5 × 10–5 M 2-mercaptoethanol] with or without doxycycline (1 g/ml). The following organ-specific cell culture media were also used: StemPro-34 Serum Free Media (invitrogen) for blood cells, Hepatocyte culture media kit (BD Biosciences) for hepatocytes, and NeuroCult differentiation kit (StemCell Technologies Inc) for neurons.

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Systematic mapping of TF-mediated cell fate changes by a pooled inductioncoupled with scRNA-seq and multi-omics approaches

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