Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi

PLoS One. 2016 Jan 11;11(1):e0146947. doi: 10.1371/journal.pone.0146947. eCollection 2016.

Abstract

Due to recent advances in reprogramming cell phenotypes, many efforts have been dedicated to developing reverse engineering procedures for the identification of gene regulatory networks that emulate dynamical properties associated with the cell fates of a given biological system. In this work, we propose a systems biology approach for the reconstruction of the gene regulatory network underlying the dynamics of the Trypanosoma cruzi's life cycle. By means of an optimisation procedure, we embedded the steady state maintenance, and the known phenotypic transitions between these steady states in response to environmental cues, into the dynamics of a gene network model. In the resulting network architecture we identified a small subnetwork, formed by seven interconnected nodes, that controls the parasite's life cycle. The present approach could be useful for better understanding other single cell organisms with multiple developmental stages.

MeSH terms

  • Algorithms
  • Cluster Analysis
  • Computational Biology
  • Data Mining
  • Databases, Genetic
  • Environment
  • Gene Expression Profiling
  • Gene Regulatory Networks
  • Humans
  • Life Cycle Stages*
  • Markov Chains
  • Models, Statistical
  • Oligonucleotide Array Sequence Analysis
  • Phenotype
  • Principal Component Analysis
  • Systems Biology*
  • Trypanosoma cruzi / genetics*
  • Trypanosoma cruzi / physiology*

Grants and funding

The authors have no support or funding to report.