ABSTRACT
TrkC and NGFR neurotrophin receptors are associated with cell death, cancer and differentiation. TrkC-miR2, which is located in TrkC gene, is known to regulate Wnt signalling pathway, and its influence on other signalling pathways is under investigation. Here, through RT-qPCR, dual-luciferase assay and Western blotting we reveal that TrkC-miR2 targets NGFR. Overexpression of TrkC-miR2 also affected TrkA, TrkC, NFKB, BCL2 and Akt2 expressions involved in neurotrophin signalling pathway, and elevated survival rate of HEK293t and U87 cells was distinguished by flow cytometry and MTT assay. Consistently, an opposite expression correlation was obtained between TrkC-miR2 and NGFR or TrkC for the duration of NT2 differentiation. Meanwhile, TrkC-miR2 down-regulation attenuated NT2 differentiation into neural-like cells. Overall, here we present in silico and experimental evidence showing TrkC-miR2 as a new controller in regulation of neurotrophin signalling pathway.
Subject(s)
MicroRNAs/metabolism , Nerve Growth Factors/metabolism , Nerve Tissue Proteins/genetics , Receptor, trkC/genetics , Receptors, Nerve Growth Factor/genetics , Signal Transduction , HEK293 Cells , HeLa Cells , Hep G2 Cells , Humans , MicroRNAs/genetics , Nerve Tissue Proteins/metabolism , Receptor, trkC/metabolism , Receptors, Nerve Growth Factor/metabolismABSTRACT
Type 2 diabetes mellitus (T2DM), nonalcoholic fatty liver disease (NAFLD), obesity (OB) and hypertension (HT) are categorized as metabolic disorders (MDs), which develop independently without distinct borders. Herein, we examined the gut microbiota (GM) and Saururus chinensis (SC) to confirm their therapeutic effects via integrated pharmacology. The overlapping targets from the four diseases were determined to be key protein coding genes. The protein-protein interaction (PPI) networks, and the SC, GM, signalling pathway, target and metabolite (SGSTM) networks were analysed via RPackage. Additionally, molecular docking tests (MDTs) and density functional theory (DFT) analysis were conducted to determine the affinity and stability of the conformer(s). TNF was the main target in the PPI analysis, and equol derived from Lactobacillus paracasei JS1 was the most effective agent for the formation of the TNF complex. The SC agonism (PPAR signalling pathway), and antagonism (neurotrophin signalling pathway) by SC were identified as agonistic bioactives (aromadendrane, stigmasta-5,22-dien-3-ol, 3,6,6-trimethyl-3,4,5,7,8,9-hexahydro-1H-2-benzoxepine, 4α-5α-epoxycholestane and kinic acid), and antagonistic bioactives (STK734327 and piclamilast), respectively, via MDT. Finally, STK734327-MAPK1 was the most favourable conformer according to DFT. Overall, the seven bioactives from SC and equol that can be produced by Lactobacillus paracasei JS1 can exert synergistic effects on these four diseases.