PDF(Pubmed)
Abstract：
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.
摘要：
应用造血干细胞(HSC)的治疗方法的主要挑战是细胞数量。本研究的主要目的是使用生物信息学工具预测miRNAs和抗miRNAs，并研究它们对预测增殖改善的关键基因表达水平的影响。和抑制从人脐带血（HUCB）分离的HSC的分化。通过利用KEGG信号通路丰富文本（PubMed）和StemChecker服务器数据，构建了一个包含与HSC分化和增殖阶段相关基因的网络，并使用GEO数据集进行了改进。生物信息学工具预测了含有miR-20a-5p的miRNA的谱，miR-423-5p,和由5'-miR-340/3'-miR-524构建的嵌合抗miRNA，用于网络中的高分基因（RB1，SMAD4，STAT1，CALML4，GNG13和CDKN1A/CDKN1B基因）。使用聚乙烯亚胺(PEI)将miRNA和抗miRNA转移到HSC中。在含有PEI+(miRNA/抗miRNA)的细胞组中使用RT-qPCR技术估计基因表达水平(n=6)。此外，使用流式细胞术评估CD标志物(90、16和45)。发现高分基因之间有很强的关系，miRNA,和嵌合抗miRNA。miR-20a-5p可显著降低RB1、SMAD4和STAT1基因表达水平(P<0.05)。此外,抗miRNA提高了GNG13的基因表达水平(P<0.05),miR-423-5p降低了CDKN1A基因的表达水平(P<0.01)。细胞计数也显着增加（P<0.05），但CD45分化标记在细胞组中没有变化。该研究揭示了预测的miRNA/抗miRNA谱扩增了从HUCB分离的HSC。虽然miR-20a-5p抑制参与细胞分化的RB1，SMAD4和STAT1基因，抗-miRNA促进了GNG13基因的增殖过程。值得注意的是,混合miRNA/抗miRNA组表现出最高的细胞扩增。这种方法有望提高HSC治疗中的细胞数量。
