H-ferritin-regulated microRNAs modulate gene expression in K562 cells

Abstract

In a previous study, we showed that the silencing of the heavy subunit (FHC) offerritin, the central iron storage molecule in the cell, is accompanied by a modification in global gene expression. In this work, we explored whether different FHC amounts might modulate miRNA expression levels in K562 cells and studied the impact of miRNAs in gene expression profile modifications. To this aim, we performed a miRNA-mRNA integrative analysis in K562 silenced for FHC (K562shFHC) comparing it with K562 transduced with scrambled RNA (K562shRNA). Four miRNAs, namely hsa-let-7g, hsa-let-7f, hsa-let-7i and hsa-miR-125b, were significantly up-regulated in silenced cells. The remarkable down-regulation of these miRNAs, following FHC expression rescue, supports a specific relation between FHC silencing and miRNA-modulation. The integration of target predictions with miRNA and gene expression profiles led to the identification of a regulatory network which includes the miRNAs up-regulated by FHC silencing, as well as91 down-regulated putative target genes. These genes were further classified in 9 networks; the highest scoring network, "Cell Death and Survival, Hematological System Development and Function, Hematopoiesis", is composed by 18 focus molecules including RAF1 and ERK1/2. We confirmed that, following FHC silencing, ERK1/2 phosphorylation is severely impaired and that RAF1 mRNA is significantly down-regulated. Taken all together, our data indicate that, in our experimental model, FHC silencing may affect RAF1/pERK1/2 levels through the modulation of a specific set of miRNAs and add new insights in to the relationship among iron homeostasis and miRNAs.

Fig 1. Four miRNAs are significantly modulated by FHC amounts.

A) Real-time PCR analysis of FHC mRNA performed on total RNA from K562 shRNA, K562 shFHC and K562^shFHC/pc3FHC. Results are representative of two different experiments. B) TaqMan analysis of hsa-miR-125b, hsa-let-7f, hsa-let-7g, hsa-let-7i in K562 shRNA, K562 shFHC and K562^shFHC/pc3FHC. Results are representative of two different experiments. N.S.: Not Significant

Fig 2. Transient silencing of FHC induce up-regulation of hsa-miR-125b, hsa-let-7f, hsa-let-7g, hsa-let-7i.

A transient silencing of FHC of about A) 20% and B) 40% is accompanied by the up-regulation of hsa-miR-125b, hsa-let-7f, hsa-let-7g, hsa-let-7i. Results are representative of two different experiments performed by TaqMan analysis. *p value<0.05

Fig 3. miRNA-mRNA interaction networks.

miRNA-mRNA interaction networks built by Cytoscape. We identified a total of 108 miRNA-mRNA significantly negatively correlated interaction. The four up-regulated miRNAs are colored in red and the 91 down-regulated target mRNAs are in green. let-7i is correlated with 13 transcripts; let-7f and let-7g with 20 and 25 transcripts, respectively; miR-125b negatively correlates with 50 transcripts. The majority of genes are supported targets of only one specific miRNA, whereas 15 genes are putatively regulated by two or more distinct up-regulated miRNAs.

Fig 4. The two highest scoring networks identified by IPA, that correlate genes target of the miRNAs differentially expressed after FHC silencing.

Ingenuity Pathway Analysis was used to investigate the networks potentially affected by the down-regulated genes. (A) Cell Death and Survival, Hematological System Development and Function, Hematopoiesis” is the highest scoring network with a significance score of 37 and 18 focus molecules (B) DNA Replication, Recombination and Repair, Cell Cycle, Cancer” has a significance score of 32 and 16 focus molecules. The target down-regulated genes are shaded in green. Intensity of shading correlates with the degree of down-regulation. A solid line represents a direct interaction between two genes, while a dotted line indicates an indirect interaction.

Fig 5. Pathway analysis performed using PANTHER.

Panther gene ontology (GO) analysis for the 91 down-regulated target genes. Several metabolic pathways are affected, the majority of them is represented by signalling pathways, shaded in blue.

Fig 6. FHC silencing in K562 cells reduces proliferation rate via RAF1/MAPK pathway inhibition and is associated with c-Mycdown-regulation.

A) Real-time PCR of RAF1 mRNA performed on K562 shRNA, K562 shFHC and K562^shFHC/pc3FHC. Results are representative of two different experiments B) Western Blot analysis for pERK1/2 was performed on 50μg of total protein extract from K562shRNA and K562shFHC cells. Total ERK1/2 was used as loading control. Results are representative of three different experiments. C) Western Blot analysis for pERK1/2 and FHC was performed on 50μg of total protein extract from K562shRNA and K562shRNA+FHC. Total ERK1/2 and γ-Tubulin were used as loading controls. Results are representative of two different experiments. D) Equal number of starved silenced and un-silenced cells were plated into a 96-well plate, incubated for 72 h and analysed by MTT assay. Proliferation of FHC-silenced cells is reduced of about 35% compared to controls. Data are presented as mean ±standard deviation. E) Real-time PCR of c-Myc mRNA performed on K562 shRNA, K562 shFHC and K562^shFHC/pc3FHC. Results are representative of two different experiments.