A MicroRNA-Based Network Provides Potential Predictive Signatures and Reveals the Crucial Role of PI3K/AKT Signaling for Hepatic Lineage Maturation

Abstract

BackgroundFunctions of miRNAs involved in tumorigenesis are well reported, yet, their roles in normal cell lineage commitment remain ambiguous. Here, we investigated a specific “transcription factor (TF)-miRNA-Target” regulatory network during the lineage maturation of biliary tree stem cells (BTSCs) into adult hepatocytes (hAHeps).MethodBioinformatic analysis was conducted based on our RNA-seq and microRNA-seq datasets with four human hepatic-lineage cell lines, including hBTSCs, hepatic stem cells (hHpSCs), hepatoblasts (hHBs), and hAHeps. Short time-series expression miner (STEM) analysis was performed to reveal the time-dependent dynamically changed miRNAs and mRNAs. GO and KEGG analyses were applied to reveal the potential function of key miRNAs and mRNAs. Then, the miRDB, miRTarBase, TargetScan, miRWalk, and DIANA-microT-CDS databases were adopted to predict the potential targets of miRNAs while the TransmiR v2.0 database was used to obtain the experimentally supported TFs that regulate miRNAs. The TCGA, Kaplan–Meier Plotter, and human protein atlas (HPA) databases and more than 10 sequencing data, including bulk RNA-seq, microRNA-seq, and scRNA-seq data related to hepatic development or lineage reprogramming, were obtained from both our or other published studies for validation.ResultsSTEM analysis showed that during the maturation from hBTSCs to hAHeps, 52 miRNAs were downwardly expressed and 928 mRNA were upwardly expressed. Enrichment analyses revealed that those 52 miRNAs acted as pluripotency regulators for stem cells and participated in various novel signaling pathways, including PI3K/AKT, MAPK, and etc., while 928 mRNAs played important roles in liver-functional metabolism. With an extensive sorting of those key miRNAs and mRNAs based on the target prediction results, 23 genes were obtained which not only functioned as the targets of 17 miRNAs but were considered critical for the hepatic lineage commitment. A “TF-miRNA-Target” regulatory network for hepatic lineage commitment was therefore established and had been well validated by various datasets. The network revealed that the PI3K/AKT pathway was gradually suppressed during the hepatic commitment.ConclusionA total of 17 miRNAs act as suppressors during hepatic maturation mainly by regulating 23 targets and modulating the PI3K/AKT signaling pathway. The regulatory network uncovers possible signatures and guidelines enabling us to identify or obtain the functional hepatocytes for future study.

A postnatal network of co-hepato/pancreatic stem/progenitors in the biliary trees of pigs and humans

“…We prepared cell suspensions of the neonatal piglet tissues of the gallbladder, cystic duct, and common duct, and then from them isolated the porcine biliary tree stem cells (pBTSCs) for the analyses by RNAseq. Prior extensive characterizations of the human biliary tree, liver, gallbladder, duodenum, and pancreatic tissue included both immunohistochemistry and RNAseq 5 , 29 , 30 , 32 , 33 , 36 , 49 , 56 . The findings revealed distinctions in genetic expression between cells within the biliary tree versus the duodenum and stomach.…”

A passage-dependent network for estimating the in vitro senescence of mesenchymal stromal/stem cells using microarray, bulk and single cell RNA sequencing

“…Previously, we established a specific “TF-miRNA-Target” regulatory network to investigate the underlying mechanisms of the lineage maturation of hepatic stem cells into mature cells ( Wang X. et al, 2021 ). This “TF-miRNA-Target” was proved to be validated to predict the genes or the signaling pathways which are related to the maturation of hepatocytes from various sources.…”

“…Previously, by comparing the genetic signature of four stages of hepatic lineages, including human biliary tree stem cells (BTSCs), human hepatic stem cells (hHPSCs), human hepatoblasts (hHBs) and adult hepatocytes (AHEPs), we developed a “TF-miRNA-target” network, which can be used to determine the hepatic differentiation or maturation of stem cells or progenitors ( Wang X. et al, 2021 ) ( Yang et al, 2018 ). Using a large amount of sequencing data generated in the public domain by different groups conducting basic, transformation and clinical research or application of MSCs, a general model can be built for quality control and status evaluation of MSCs prepared by different procedures.…”