Exploring the potential of predicted miRNAs on the genes involved in the expansion of hematopoietic stem cells.

A major challenge in therapeutic approaches applying hematopoietic stem cells (HSCs) is the cell quantity. The primary objective of this study was to predict the miRNAs and anti-miRNAs using bioinformatics tools and investigate their effects on the expression levels of key genes predicted in the improvement of proliferation, and the inhibition of differentiation in HSCs isolated from Human umbilical cord blood (HUCB). A network including genes related to the differentiation and proliferation stages of HSCs was constructed by enriching data of text (PubMed) and StemChecker server with KEGG signaling pathways, and was improved using GEO datasets. Bioinformatics tools predicted a profile from miRNAs containing miR-20a-5p, miR-423-5p, and chimeric anti-miRNA constructed from 5'-miR-340/3'-miR-524 for the high-score genes (RB1, SMAD4, STAT1, CALML4, GNG13, and CDKN1A/CDKN1B genes) in the network. The miRNAs and anti-miRNA were transferred into HSCs using polyethylenimine (PEI). The gene expression levels were estimated using the RT-qPCR technique in the PEI + (miRNA/anti-miRNA)-contained cell groups (n = 6). Furthermore, CD markers (90, 16, and 45) were evaluated using flow cytometry. Strong relationships were found between the high-score genes, miRNAs, and chimeric anti-miRNA. The RB1, SMAD4, and STAT1 gene expression levels were decreased by miR-20a-5p (P < 0.05). Additionally, the anti-miRNA increased the gene expression level of GNG13 (P < 0.05), whereas the miR-423-5p decreased the CDKN1A gene expression level (P < 0.01). The cellular count also increased significantly (P < 0.05) but the CD45 differentiation marker did not change in the cell groups. The study revealed the predicted miRNA/anti-miRNA profile expands HSCs isolated from HUCB. While miR-20a-5p suppressed the RB1, SMAD4, and STAT1 genes involved in cellular differentiation, the anti-miRNA promoted the GNG13 gene related to the proliferation process. Notably, the mixed miRNA/anti-miRNA group exhibited the highest cellular expansion. This approach could hold promise for enhancing the cell quantity in HSC therapy.

Step by step analysis on gene datasets of growth phases in hematopoietic stem cells.

Background: Umbilical cord blood hematopoietic stem cells (UCB-HSCs) have important roles in the treatment of illnesses based on their self-renewal and potency characteristics. Knowing the gene profiles and signaling pathways involved in each step of the cell cycle could improve the therapeutic approaches of HSCs. The aim of this study was to predict the gene profiles and signaling pathways involved in the G0, G1, and differentiation stages of HSCs. Methods: Interventional (n = 8) and non-interventional (n = 3) datasets were obtained from the Gene Expression Omnibus (GEO) database, and were crossed and analyzed to determine the high- and low-express genes related to each of the G0, G1, and differentiation stages of HSCs. Then, the scores of STRING were annotated to the gene data. The gene networks were constructed using Cytoscape software, and enriched with the KEGG and GO databases. Results: The high- and low-express genes were determined due to inter and intra intersections of the interventional and non-interventional data. The non-interventional data were applied to construct the gene networks (n = 6) with the nodes improved using the interventional data. Several important signaling pathways were suggested in each of the G0, G1, and differentiation stages. Conclusion: The data revealed that the different signaling pathways are activated in each of the G0, G1, and differentiation stages so that their genes may be targeted to improve the HSC therapy.

NF-kB affects migration of vascular smooth muscle cells after treatment with heparin and ibrutinib.

The migration of vascular smooth muscle cells (VSMCs) is one of the most important events in the remodeling of atherosclerosis plaque. The aim of study was to investigate the role of Heparin in the VSMC migration and its association with the NF-kB, collagen 1 and collagen 3 expression levels. Moreover, the incorporation of Heparin was studied in the VSMC cultures including Betulinic acid and Ibrutinib. Twelve cell groups were cultured and treated with the Heparin, Betulinic acid and Ibrutinib based on the viability and toxicity in 24-h and 48-h periods. The gene and protein expression levels were measured by RT-qPCR and western blotting techniques. The VSMC migration was determined by scratch test. In contrast with Ibrutinib (2 µM), Heparin (30 IU) increased significantly (P < 0.05) the NF-kB gene and protein expression levels and the VSMC migration during the exposure periods. Heparin (15 IU and 30 IU) also increased the collagen 1 gene expression level in the 48-h period while Heparin (5 IU and 15 IU) increased the collagen 3 gene expression levels in both periods. Incorporating Heparin into the cultures including Betulinic acid and Ibrutinib affected the collagen 1 and collagen 3 expression levels. The data suggested that the cell migration relates to NF-kB in the VSMCs treated with Heparin and Ibrutinib. Furthermore, the Heparin doses (5 IU and 15 IU) were safe for VSMCs based on the NF-kB, and collagen 3 expression levels.

Differential gene expression patterns in ST-elevation Myocardial Infarction and Non-ST-elevation Myocardial Infarction.

The ST-elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI) might occur because of coronary artery stenosis. The gene biomarkers apply to the clinical diagnosis and therapeutic decisions in Myocardial Infarction. The aim of this study was to introduce, enrich and estimate timely the blood gene profiles based on the high-throughput data for the molecular distinction of STEMI and NSTEMI. The text mining data (50 genes) annotated with DisGeNET data (144 genes) were merged with the GEO gene expression data (5 datasets) using R software. Then, the STEMI and NSTEMI networks were primarily created using the STRING server, and improved using the Cytoscape software. The high-score genes were enriched using the KEGG signaling pathways and Gene Ontology (GO). Furthermore, the genes were categorized to determine the NSTEMI and STEMI gene profiles. The time cut-off points were identified statistically by monitoring the gene profiles up to 30 days after Myocardial Infarction (MI). The gene heatmaps were clearly created for the STEMI (high-fold genes 69, low-fold genes 45) and NSTEMI (high-fold genes 68, low-fold genes 36). The STEMI and NSTEMI networks suggested the high-score gene profiles. Furthermore, the gene enrichment suggested the different biological conditions for STEMI and NSTEMI. The time cut-off points for the NSTEMI (4 genes) and STEMI (13 genes) gene profiles were established up to three days after Myocardial Infarction. The study showed the different pathophysiologic conditions for STEMI and NSTEMI. Furthermore, the high-score gene profiles are suggested to measure up to 3 days after MI to distinguish the STEMI and NSTEMI.

Beta arrestin-related signalling axes are influenced by dexamethasone and metformin in vascular smooth muscle cells cultured in high glucose condition.

BACKGROUND: Metformin (Met) and dexamethasone (Dexa) are known to reduce blood sugar levels and anti-inflammatory effects, respectively. Based on the acceleration of atherosclerosis process in diabetes, the ß-arrestin 2 (BARR2) gene and protein expression levels were evaluated in vascular smooth muscle cells (VSMCs) treated with Met and Dexa in high glucose conditions in this study. METHODS AND MATERIALS: Human VSMCs were cultured in Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 (DMEM-F12) medium and, were treated with different values of Met (1 mM, 5 mM and 7 mM) and Dexa (10-7 M, 10-6 M and 10-5 M) in 24- and 48-h periods. The BARR2 gene and protein expression levels were identified with RT-qPCR and western blotting techniques, respectively. The signalling axes were predicted from gene network made using Cytoscape software and, were annotated with Gene Ontology. RESULTS: The BARR2 gene and protein expression levels reduced in VSMCs treated with Dexa and Met after 24- and 48-h periods. These results were more changed after 48 h. Furthermore, many BARR2-related signalling axes were found from the network genes. CONCLUSION: Met and Dexa suppressed the BARR2 protein and gene expression levels in the VSMCs. Moreover, the gene network suggested some the cellular signalling axes related to BARR2 that may be affected by Met and Dexa.