title: Irreversibility of T-Cell Specification: Insights from Computational Modelling of a Minimal Network Architecture.
abstract: OBJECTIVE
  A cascade of gene activations under the control of Notch signalling is required during T-cell specification, when T-cell precursors gradually lose the potential to undertake other fates and become fully committed to the T-cell lineage. We elucidate how the gene/protein dynamics for a core transcriptional module governs this important process by computational means.
  
  
  METHODS
  We first assembled existing knowledge about transcription factors known to be important for T-cell specification to form a minimal core module consisting of TCF-1, GATA-3, BCL11B, and PU.1 aiming at dynamical modeling. Model architecture was based on published experimental measurements of the effects on each factor when each of the others is perturbed. While several studies provided gene expression measurements at different stages of T-cell development, pure time series are not available, thus precluding a straightforward study of the dynamical interactions among these genes. We therefore translate stage dependent data into time series. A feed-forward motif with multiple positive feed-backs can account for the observed delay between BCL11B versus TCF-1 and GATA-3 activation by Notch signalling. With a novel computational approach, all 32 possible interactions among Notch signalling, TCF-1, and GATA-3 are explored by translating combinatorial logic expressions into differential equations for BCL11B production rate.
  
  
  RESULTS
  Our analysis reveals that only 3 of 32 possible configurations, where GATA-3 works as a dimer, are able to explain not only the time delay, but very importantly, also give rise to irreversibility. The winning models explain the data within the 95% confidence region and are consistent with regard to decay rates.
  
  
  CONCLUSIONS
  This first generation model for early T-cell specification has relatively few players. Yet it explains the gradual transition into a committed state with no return. Encoding logics in a rate equation setting allows determination of binding properties beyond what is possible in a Boolean network.
authors.affiliation: Computational Biology and Biological Physics, Department of Astronomy and Theoretical Physics, Lund University, SE-223 62 Lund, Sweden.
authors.forename: Erica
authors.initials: E
authors.lastname: Manesso
authors.affiliation: Division of Biology, California Institute of Technology, Pasadena, CA 91125, United States of America.
authors.forename: Hao Yuan
authors.initials: HY
authors.lastname: Kueh
authors.affiliation: Division of Biology, California Institute of Technology, Pasadena, CA 91125, United States of America.
authors.forename: George
authors.initials: G
authors.lastname: Freedman
authors.affiliation: Division of Biology, California Institute of Technology, Pasadena, CA 91125, United States of America.
authors.forename: Ellen V
authors.initials: EV
authors.lastname: Rothenberg
authors.affiliation: Computational Biology and Biological Physics, Department of Astronomy and Theoretical Physics, Lund University, SE-223 62 Lund, Sweden.
authors.forename: Carsten
authors.identifier: http://orcid.org/0000-0001-7362-2191
authors.initials: C
authors.lastname: Peterson
mesh_terms: D000818:Animals; D002454:Cell Differentiation / Q000235:genetics*; D019070:Cell Lineage / Q000235:genetics*; D019295:Computational Biology; D053263:Gene Regulatory Networks / Q000235:genetics; D008954:Models, Biological; D051880:Receptors, Notch / Q000235:genetics; D015398:Signal Transduction; D013601:T-Lymphocytes / Q000166:cytology* / Q000378:metabolism
chemical_list: D051880:Receptors, Notch