In Silico Target Prediction of Overexpressed microRNAs from LPS-Challenged Zebrafish (<i>Danio rerio</i>) Treated with the Novel Anti-Inflammatory Peptide <i>Tn</i>P

Abstract

miRNAs regulate gene expression post-transcriptionally in various processes, e.g., immunity, development, and diseases. Since their experimental analysis is complex, in silico target prediction is important for directing investigations. TnP is a candidate peptide for anti-inflammatory therapy, first discovered in the venom of Thalassophryne nattereri, which led to miRNAs overexpression in LPS-inflamed zebrafish post-treatment. This work aimed to predict miR-21, miR-122, miR-731, and miR-26 targets using overlapped results of DIANA microT-CDS and TargetScanFish software. This study described 513 miRNAs targets using highly specific thresholds. Using Gene Ontology over-representation analysis, we identified their main roles in regulating gene expression, neurogenesis, DNA-binding, transcription regulation, immune system process, and inflammatory response. miRNAs act in post-transcriptional regulation, but we revealed that their targets are strongly related to expression regulation at the transcriptional level, e.g., transcription factors proteins. A few predicted genes participated concomitantly in many biological processes and molecular functions, such as foxo3a, rbpjb, rxrbb, tyrobp, hes6, zic5, smad1, e2f7, and npas4a. Others were particularly involved in innate immunity regulation: il17a/f2, pik3r3b, and nlrc6. Together, these findings not only provide new insights into the miRNAs mode of action but also raise hope for TnP therapy and may direct future experimental investigations.

Keywords

• <i>Tn</i>P
• inflammation
• preclinical toxicological studies
• epigenetic
• miRNAs
• bioinformatics