BMPER is upregulated in obesity and seems to have a role in pericardial adipose stem cells

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

BMPER is a marker of adipose progenitors and adipocytes and a positive modulator of adipogenesis

Autocrine and paracrine signaling regulating adipogenesis in white adipose tissue remains largely unclear. Here we used single-cell RNA-sequencing (RNA-seq) and single nuclei RNA-sequencing (snRNA-seq) to identify markers of adipose progenitor cells (APCs) and adipogenic modulators in visceral adipose tissue (VAT) of humans and mice. Our study confirmed the presence of major cellular clusters in humans and mice and established important sex and diet-specific dissimilarities in cell proportions. Here we show that bone morphogenetic protein (BMP)-binding endothelial regulator (BMPER) is a conserved marker for APCs and adipocytes in VAT in humans and mice. Further, BMPER is highly enriched in lineage negative stromal vascular cells and its expression is significantly higher in visceral compared to subcutaneous APCs in mice. BMPER expression and release peaked by day four post-differentiation in 3T3-L1 preadipocytes. We reveal that BMPER is required for adipogenesis both in 3T3-L1 preadipocytes and in mouse APCs. Together, this study identified BMPER as a positive modulator of adipogenesis.

The whole profiling and competing endogenous RNA network analyses of noncoding RNAs in adipose-derived stem cells from diabetic, old, and young patients

Background

Mesenchymal stem cells including adipose-derived stem cells (ASCs) have a considerable potential in the field of translational medicine. Unfortunately, multiple factors (e.g., older age, co-existing diabetes, and obesity) may impair cellular function, which hinders the overall effectiveness of autologous stem cell therapy. Noncoding RNAs—including microRNAs (miRNAs), long ncRNAs (lncRNAs), and circular RNAs (circRNAs)—have been shown to play important roles in stem cell biology. However, the overall diabetes-related and aging-related expression patterns and interactions of these RNAs in ASCs remain unknown.

Method

The phenotypes and functions of ASCs isolated from diabetic (D-ASCs), old (O-ASCs), and young (Y-ASCs) donors were evaluated by in vitro assays. We conducted high-throughput RNA sequencing (RNA-seq) in these ASCs to identify the differentially expressed (DE) RNAs. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) analyses were performed to investigate mRNAs with significant differences among groups. The lncRNA- or circRNA-associated competing endogenous RNA (ceRNA) networks were constructed based on bioinformatics analyses and real-time polymerase chain reaction (RT-PCR) results. The miR-145-5p mimics were transfected into O-ASCs and verified by PCR.

Results

ASCs from diabetic and old donors showed inferior migration ability and increased cellular senescence. Furthermore, O-ASCs have decreased capacities for promoting endothelial cell angiogenesis and fibroblast migration, compared with Y-ASCs. The DE miRNAs, mRNAs, lncRNAs, and circRNAs were successfully identified by RNA-seq in O-ASCs vs. Y-ASCs and D-ASCs vs. O-ASCs. GO and KEGG analyses demonstrated that DE mRNAs were significantly enriched in aging and cell senescence terms separately. PPI networks revealed critical DE mRNAs in the above groups. RNAs with high fold changes and low p values were validated by PCR. ceRNA networks were constructed based on bioinformatics analyses and validated RNAs. Additionally, the lncRNA RAET1E-AS1–miR-145-5p–WNT11/BMPER axis was validated by PCR and correlation analyses. Finally, the overexpression of miR-145-5p was found to rejuvenate O-ASCs phenotype and augment the functionality of these cells.

Conclusion

Our research may provide insights regarding the underlying mechanisms of ASC dysfunction; it may also offer novel targets for restoring therapeutic properties in ASCs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-021-02388-5.