PuSH - Publication Server of Helmholtz Zentrum München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
Marr, C. ; Strasser, M. ; Schwarzfischer, M. ; Schroeder, T. ; Theis, F.J.

Multi-scale modeling of GMP differentiation based on single-cell genealogies.

FEBS J. 279, 3488-3500 (2012)
Publ. Version/Full Text Volltext DOI PMC
Closed
Open Access Green as soon as Postprint is submitted to ZB.
Hematopoiesis is often pictured as a hierarchy of branching decisions, giving rise to all mature blood cell types from stepwise differentiation of a single cell, the hematopoietic stem cell. Various aspects of this process have been modeled using various experimental and theoretical techniques on different scales. Here we integrate the more common population-based approach with a single-cell resolved molecular differentiation model to study the possibility of inferring mechanistic knowledge of the differentiation process. We focus on a sub-module of hematopoiesis: differentiation of granulocyte-monocyte progenitors GMPs) to granulocytes or monocytes. Within a branching process model, we infer the differentiation probability of GMPs from the experimentally quantified heterogeneity of colony assays under permissive conditions where both granulocytes and monocytes can emerge. We compare the predictions with the differentiation probability in genealogies determined from single-cell time-lapse microscopy. In contrast to the branching process model, we found that the differentiation probability as determined by differentiation marker onset increases with the generation of the cell within the genealogy. To study this feature from a molecular perspective, we established a stochastic toggle switch model, in which the intrinsic lineage decision is executed using two antagonistic transcription factors. We identified parameter regimes that allow for both time-dependent and time-independent differentiation probabilities. Finally, we infer parameters for which the model matches experimentally observed differentiation probabilities via approximate Bayesian computing. These parameters suggest different timescales in the dynamics of granulocyte and monocyte differentiation. Thus we provide a multi-scale picture of cell differentiation in murine GMPs, and illustrate the need for single-cell time-resolved observations of cellular decisions.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Scopus
Cited By
Altmetric
3.790
0.890
15
16
Tags
Icb_qscd
Annotations
Special Publikation
Hide on homepage

Edit extra information
Edit own tags
Private
Edit own annotation
Private
Hide on publication lists
on hompage
Mark as special
publikation
Publication type Article: Journal article
Document type Scientific Article
Keywords Approximate Bayesian Computing ; Branching Process ; Differentiation ; Hematopoiesis ; Stochastic Gene Expression Model; Hematopoietic Stem-Cells; Approximate Bayesian Computation; Stochastic Gene-Expression; Lineage Specification; Interaction Networks; Stability; Dynamics; Switch; Fates; Pu.1
Language english
Publication Year 2012
HGF-reported in Year 2012
ISSN (print) / ISBN 1742-464X
e-ISSN 1742-4658
Journal FEBS Journal, The
Quellenangaben Volume: 279, Issue: 18, Pages: 3488-3500 Article Number: , Supplement: ,
Publisher Wiley
Reviewing status Peer reviewed
Institute(s) Institute of Bioinformatics and Systems Biology (IBIS)
Research Unit Stem Cell Dynamics (SCD)
POF-Topic(s) 30505 - New Technologies for Biomedical Discoveries
30504 - Mechanisms of Genetic and Environmental Influences on Health and Disease
Research field(s) Enabling and Novel Technologies
Stem Cell and Neuroscience
PSP Element(s) G-503700-004
G-501200-001
PubMed ID 22708849
DOI 10.1111/j.1742-4658.2012.08664.x
WOS ID WOS:000308299200015
Scopus ID 84865970286
Erfassungsdatum 2012-10-26
[➜Report correction]