Neuropathic pain resulting from nerve lesions or dysfunction represents one of the most challenging neurological diseases to treat. A better understanding of the molecular mechanisms responsible for causing these maladaptive responses can help develop novel therapeutic strategies and biomarkers for neuropathic pain. We performed a miRNA expression profiling study of dorsal root ganglion (DRG) tissue from rats four weeks post spinal nerve ligation (SNL), a model of neuropathic pain. TaqMan low density arrays identified 63 miRNAs whose level of expression was significantly altered following SNL surgery. Of these, 59 were downregulated and the ipsilateral L4 DRG, not the injured L5 DRG, showed the most significant downregulation suggesting that miRNA changes in the uninjured afferents may underlie the development and maintenance of neuropathic pain. TargetScan was used to predict mRNA targets for these miRNAs and it was found that the transcripts with multiple predicted target sites belong to neurologically important pathways. By employing different bioinformatic approaches we identified neurite remodeling as a significantly regulated biological pathway, and some of these predictions were confirmed by siRNA knockdown for genes that regulate neurite growth in differentiated Neuro2A cells. In vitro validation for predicted target sites in the 3′-UTR of voltage-gated sodium channel Scn11a, alpha 2/delta1 subunit of voltage-dependent Ca-channel, and purinergic receptor P2rx ligand-gated ion channel 4 using luciferase reporter assays showed that identified miRNAs modulated gene expression significantly. Our results suggest the potential for miRNAs to play a direct role in neuropathic pain.
Systematic analysis of literature- and experimentally-derived datasets using text mining with ontological enrichment and network modeling revealed global trends in the microRNA (miRNA) interactome. A total of 756 unique miRNAs were resolved from PubMed abstracts and 1165 direct relationships between 270 miRNAs and 581 genes were identified as phrase groups using semantic search techniques. These miRNA:gene interactions were built into a bipartite network (the miRNAome) which displays scale-free degree distribution. Functional classification of miRNA-target genes using PANTHER revealed 189 distinct molecular functions, with significant enrichment of nucleic acid binding, transcription and protein phosphorylation. Pathway analysis revealed a network of 176 miRNAs linked to 368 OMIM disorders via their target genes, which are enriched (p = 0.0047) for disease-associated SNP variations. Reference to a database of drug targets revealed that 24.8% of all published miRNA-targets are targets for drug development programs, while a sub-set (18.2%) are targets for FDA-approved drugs. Consistent with topological analysis of the miRNA-disease network, the most prevalent class of FDA-approved drugs is anti-neoplastic agents against published miRNA-target genes. Linking miRNAs to biological process and diseases reveals distinct co-regulation of phenotypes that could aid in understanding the role miRNA-based gene regulation plays in biological phenomena.
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