Multi-scale Dynamical Modeling of T Cell Development from an Early Thymic Progenitor State to Lineage Commitment

• Published in: Cell reports (Cambridge) 2021-01, Vol.34 (2), p.108622-108622, Article 108622
• Main Authors: Olariu, Victor, Yui, Mary A., Krupinski, Pawel, Zhou, Wen, Deichmann, Julia, Andersson, Emil, Rothenberg, Ellen V., Peterson, Carsten
• Format: Article
• Language: English
• Subjects: Annan fysik; Basic Medicine; Bioinformatics and Systems Biology; Bioinformatik och systembiologi; Biologi; Biological Sciences; Cell and Molecular Biology; Cell Biology; Cell Differentiation; Cell Lineage - genetics; Cell- och molekylärbiologi; Cellbiologi; epigenetic modeling; experimental validations; Fysik; Humans; kinetic measurements; Medical and Health Sciences; Medicin och hälsovetenskap; Medicinska och farmaceutiska grundvetenskaper; Natural Sciences; Naturvetenskap; Other Physics Topics; Physical Sciences; population modeling; proliferation measurements; single-cell measurements; Stem Cells - metabolism; stochastic simulations; T cell development; T-Lymphocytes - physiology; Thymus Gland - metabolism; transcriptional modeling
• ISSN: 2211-1247; 2211-1247
• DOI: 10.1016/j.celrep.2020.108622

Intrathymic development of committed progenitor (pro)-T cells from multipotent hematopoietic precursors offers an opportunity to dissect the molecular circuitry establishing cell identity in response to environmental signals. This transition encompasses programmed shutoff of stem/progenitor genes, upregulation of T cell specification genes, proliferation, and ultimately commitment. To explain these features in light of reported cis-acting chromatin effects and experimental kinetic data, we develop a three-level dynamic model of commitment based upon regulation of the commitment-linked gene Bcl11b. The levels are (1) a core gene regulatory network (GRN) architecture from transcription factor (TF) perturbation data, (2) a stochastically controlled chromatin-state gate, and (3) a single-cell proliferation model validated by experimental clonal growth and commitment kinetic assays. Using RNA fluorescence in situ hybridization (FISH) measurements of genes encoding key TFs and measured bulk population dynamics, this single-cell model predicts state-switching kinetics validated by measured clonal proliferation and commitment times. The resulting multi-scale model provides a mechanistic framework for dissecting commitment dynamics. [Display omitted] •A multi-level dynamical model is developed for the commitment of T cell precursors•It links gene networks, single-cell RNA analysis, chromatin changes, and cell division•It provides quantitative understanding of commitment kinetic requirements•The model predictions are verified against new clonal and real-time imaging data Olariu et al. use computational modeling and live-cell developmental imaging to explain the kinetics of early T cell lineage commitment. An integrated computational multi-scale model incorporating gene network architecture, single-cell RNA levels, chromatin state shifts, and proliferation is developed, explored, and validated.