Hematopoietic differentiation: a coordinated dynamical process towards attractor stable states

BMC Syst Biol. 2010 Jun 16:4:85. doi: 10.1186/1752-0509-4-85.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antigens, CD34 / metabolism
  • Cell Culture Techniques
  • Cell Differentiation / genetics
  • Cell Differentiation / physiology*
  • Cell Lineage
  • Computational Biology / methods
  • Fetal Blood / cytology
  • Flow Cytometry
  • Gene Expression Profiling
  • Genome / genetics*
  • Hematopoietic Stem Cells / physiology*
  • Models, Biological*
  • Oligonucleotide Array Sequence Analysis
  • Signal Transduction / genetics
  • Signal Transduction / physiology*

Substances

  • Antigens, CD34