UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Computational Modeling of the Hematopoietic Erythroid-Myeloid Switch Reveals Insights into Cooperativity, Priming, and Irreversibility

Chickarmane, V; Enver, T; Peterson, C; (2009) Computational Modeling of the Hematopoietic Erythroid-Myeloid Switch Reveals Insights into Cooperativity, Priming, and Irreversibility. PLOS COMPUT BIOL , 5 (1) , Article e1000268. 10.1371/journal.pcbi.1000268. Green open access

[img]
Preview
PDF
1336622.pdf

Download (343kB)

Abstract

Hematopoietic stem cell lineage choices are decided by genetic networks that are turned ON/OFF in a switch-like manner. However, prior to lineage commitment, genes are primed at low expression levels. Understanding the underlying molecular circuitry in terms of how it governs both a primed state and, at the other extreme, a committed state is of relevance not only to hematopoiesis but also to developmental systems in general. We develop a computational model for the hematopoietic erythroid-myeloid lineage decision, which is determined by a genetic switch involving the genes PU.1 and GATA-1. Dynamical models based upon known interactions between these master genes, such as mutual antagonism and autoregulation, fail to make the system bistable, a desired feature for robust lineage determination. We therefore suggest a new mechanism involving a cofactor that is regulated as well as recruited by one of the master genes to bind to the antagonistic partner that is necessary for bistability and hence switch-like behavior. An interesting fallout from this architecture is that suppression of the cofactor through external means can lead to a loss of cooperativity, and hence to a primed state for PU.1 and GATA-1. The PU. 1-GATA-1 switch also interacts with another mutually antagonistic pair, C/EBP alpha-FOG-1. The latter pair inherits the state of its upstream master genes and further reinforces the decision due to several feedback loops, thereby leading to irreversible commitment. The genetic switch, which handles the erythroid-myeloid lineage decision, is an example of a network that implements both a primed and a committed state by regulating cooperativity through recruitment of cofactors. Perturbing the feedback between the master regulators and downstream targets suggests potential reprogramming strategies. The approach points to a framework for lineage commitment studies in general and could aid the search for lineage-determining genes.

Type: Article
Title: Computational Modeling of the Hematopoietic Erythroid-Myeloid Switch Reveals Insights into Cooperativity, Priming, and Irreversibility
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pcbi.1000268
Publisher version: http://dx.doi.org/10.1371/journal.pcbi.1000268
Language: English
Additional information: © 2009 Chickarmane et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This research was in part supported by the Swedish Foundation for Strategic Research through a Senior Individual Grant, the National Science Foundation FIBR Award EF-0330786, the UK Medical Research Council, the Leukemia Research Fund UK, and the EU EuroSyStem and Estools projects.
Keywords: TRANSCRIPTION FACTORS GATA-1, PROGENITOR CELLS, GENE-EXPRESSION, REGULATORY NETWORKS, LINEAGE-COMMITMENT, POSITIVE-FEEDBACK, ESCHERICHIA-COLI, STEM-CELLS, C/EBP-ALPHA, DIFFERENTIATION
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > Research Department of Cancer Bio
URI: https://discovery.ucl.ac.uk/id/eprint/1336622
Downloads since deposit
117Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item