Probing cell identity hierarchies by fate titration and collision during direct reprogramming

Hersbach, Bob A. ; Fischer, David S. ; Masserdotti, Giacomo; Deeksha, Deeksha; Mojžišová, Karolina; Waltzhöni, Thomas; Rodriguez‐Terrones, Diego; Heinig, Matthias; Theis, Fabian J. ; Götz, Magdalena and Stricker, Stefan H. (2022): Probing cell identity hierarchies by fate titration and collision during direct reprogramming. In: Molecular Systems Biology, Vol. 18, e11129

Abstract

Despite the therapeutic promise of direct reprogramming, basic principles concerning fate erasure and the mechanisms to resolve cell identity conflicts remain unclear. To tackle these fundamental questions, we established a single-cell protocol for the simultaneous analysis of multiple cell fate conversion events based on combinatorial and traceable reprogramming factor expression: Collide-seq. Collide-seq revealed the lack of a common mechanism through which fibroblast-specific gene expression loss is initiated. Moreover, we found that the transcriptome of converting cells abruptly changes when a critical level of each reprogramming factor is attained, with higher or lower levels not contributing to major changes. By simultaneously inducing multiple competing reprogramming factors, we also found a deterministic system, in which titration of fates against each other yields dominant or colliding fates. By investigating one collision in detail, we show that reprogramming factors can disturb cell identity programs independent of their ability to bind their target genes. Taken together, Collide-seq has shed light on several fundamental principles of fate conversion that may aid in improving current reprogramming paradigms.

• Item Type: Journal article
• EU Funded Grant Agreement Number: 885382
• EU Projects: Horizon 2020 > ERC Grants > ERC Advanced Grant > ERC Grant 885382: NeuroCentro - Novel mechanisms of neurogenesis- from centrosome to engineering migration
• Faculties: Medicine > Institute of Physiology; Medicine > Munich Cluster for Systems Neurology (SyNergy)
• Subjects: 600 Technology > 610 Medicine and health
• ISSN: 1744-4292
• Language: English
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 491502892
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198