Original Research ARTICLE
Systems Biology-Based Analysis Indicates Global Transcriptional Impairment in Lead-Treated Human Neural Progenitor Cells
- 1Bioinformatics Multidisciplinary Environment, Federal University of Rio Grande do Norte, Brazil
- 2Federal University of Rio Grande do Sul, Brazil
- 3Federal University of Rio Grande do Norte, Brazil
Lead poisoning effects are wide and include nervous system impairment, peculiarly during development, leading to neural damage. Lead interaction with calcium and zinc-containing metalloproteins broadly affects cellular metabolism since these proteins are related to intracellular ion balance, activation of signaling transduction cascades, and gene expression regulation. In spite of lead being recognized as a neurotoxin, there are gaps in knowledge about the global effect of lead in modulating the transcription of entire cellular systems in neural cells. In order to investigate the effects of lead poisoning in a systemic perspective, we applied the transcriptogram methodology in a RNA-seq dataset of human embryonic-derived neural progenitor cells (ES-NP Cells) treated with 30 μM lead acetate for 26 days. We observed early downregulation of several cellular systems involved with cell differentiation, such as cytoskeleton organization, RNA and protein biosynthesis. The downregulated cellular systems presented big and tightly connected networks. For long treatment times (12 to 26 days) it was possible to observe a massive impairment in cell transcription profile. Taking the enriched terms together, we observed interference in all layers of gene expression regulation, from chromatin remodeling to vesicle transport. Considering ES-NP Cells are progenitor cells which can originate other neural cell types, our results suggest that lead-induced gene expression disturbance might impair cells ability to differentiate, therefore influencing ES-NP cells fate.
Keywords: Lead (Pb) exposure, lead (Pb) poisoning, transcriptogramer, RNA-Seq, transcriptome analysis, Network Inference, data integration, network visualization
Received: 26 Mar 2019;
Accepted: 26 Jul 2019.
Copyright: © 2019 Reis, Souza, MORAIS, Oliveira, Imparato, De Almeida and Dalmolin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mx. Rodrigo J. Dalmolin, Federal University of Rio Grande do Norte, Natal, Brazil, firstname.lastname@example.org