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Open Access Highly Accessed Research article

Hematopoietic differentiation: a coordinated dynamical process towards attractor stable states

Nadia Felli1, Luciano Cianetti1, Elvira Pelosi1, Alessandra Carè1, Chang Gong Liu3, George A Calin3, Simona Rossi3, Cesare Peschle4, Giovanna Marziali1* and Alessandro Giuliani2*

Author Affiliations

1 Department of Hematology, Oncology and Molecular Medicine Istituto Superiore di Sanità, 00161 Rome, Italy

2 Department of Environment and Health, Istituto Superiore di Sanit, 00161 Rome, Italy

3 Department of Experimental Therapeutics and Cancer Genetics, University of Texas, M.D. Anderson Cancer Center, Houston, TX, USA

4 IRCCS MultiMedica, 20138 Milan, Italy

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BMC Systems Biology 2010, 4:85  doi:10.1186/1752-0509-4-85

Published: 16 June 2010

Abstract

Background

The differentiation process, proceeding from stem cells towards the different committed cell types, can be considered as a trajectory towards an attractor of a dynamical process. This view, taking into consideration the transcriptome and miRNome dynamics considered as a whole, instead of looking at few 'master genes' driving the system, offers a novel perspective on this phenomenon. We investigated the 'differentiation trajectories' of the hematopoietic system considering a genome-wide scenario.

Results

We developed serum-free liquid suspension unilineage cultures of cord blood (CB) CD34+ hematopoietic progenitor cells through erythroid (E), megakaryocytic (MK), granulocytic (G) and monocytic (Mo) pathways. These cultures recapitulate physiological hematopoiesis, allowing the analysis of almost pure unilineage precursors starting from initial differentiation of HPCs until terminal maturation. By analyzing the expression profile of protein coding genes and microRNAs in unilineage CB E, MK, G and Mo cultures, at sequential stages of differentiation and maturation, we observed a coordinated, fully interconnected and scalable character of cell population behaviour in both transcriptome and miRNome spaces reminiscent of an attractor-like dynamics. MiRNome and transcriptome space differed for a still not terminally committed behaviour of microRNAs.

Conclusions

Consistent with their roles, the transcriptome system can be considered as the state space of a cell population, while the continuously evolving miRNA space corresponds to the tuning system necessary to reach the attractor. The behaviour of miRNA machinery could be of great relevance not only for the promise of reversing the differentiated state but even for tumor biology.