Deciphering synergistic regulatory networks of microRNAs in hESCs and fibroblasts

Modeling ncRNA Synergistic Regulation in Cancer

Cancer seriously threatens human life and health, and the structure and function of genes within cancer cells have changed relative to normal cells. Essentially, cancer is a polygenic disorder, and the core of its occurrence and development is caused by polygenic synergy. Non-coding RNAs (ncRNAs) act as regulators to modulate gene expression levels, and they provide theoretical basis and new technology for the diagnosis and preventive treatment of cancer. However, the study of ncRNA regulation and its role as biomarkers in cancer remain largely unearthed. Driven by multi-omics data, an abundance of computational methods, tools, and databases have been developed for predicting ncRNA-cancer association/causality, inferring ncRNA regulation, and modeling ncRNA synergistic regulation. This chapter aims to provide a comprehensive perspective of modeling ncRNA synergistic regulation. Since the ncRNAs involved in cancer contribute to modeling cancer-associated ncRNA synergistic regulation, we first review the databases and tools of cancer-related ncRNAs. Then we investigate the existing tools or methods for modeling ncRNA-directed and ncRNA-mediated regulation. In addition, we survey the available computational tools or methods for modeling ncRNA synergistic regulation, including synergistic interaction and synergistic competition. Finally, we discuss the future directions and challenges in modeling ncRNA synergistic regulation.

Tryptophan As a New Member of RNA-Induced Silencing Complexes Prevents Colon Cancer Liver Metastasis

Essential amino acids (EAA) and microRNAs (miRs) control biological activity of a cell. Whether EAA regulates the activity of miR has never been demonstrated. Here, as proof-of-concept, a tryptophan (Trp, an EAA) complex containing Argonaute 2 (Ago2) and miRs including miR-193a (Trp/Ago2/miR-193a) is identified. Trp binds miR-193a-3p and interacts with Ago2. Trp/Ago2/miR-193a increases miR-193a-3p activity via enhancing Argonaute 2 (Ago2) RNase activity. Other miRs including miR-103 and miR-107 in the Trp complex enhance miR-193a activity by targeting the same genes. Mechanistically, the Trp/Ago2/miR-193a complex interacts with Trp-binding pockets of the PIWI domain of Ago2 to enhance Ago2 mediated miR activity. This newly formed Ago2/Trp/miR-193a-3p complex is more efficient than miR-193a-3p alone in inhibiting the expression of targeted genes and inhibiting colon cancer liver metastasis. The findings show that Trp regulates miR activity through communication with the RNA-induced silencing complexes (RISC), which provides the basis for tryptophan based miR therapy.

Genome-wide profiling of dysregulated piRNAs and their target genes implicated in oncogenicity of Tongue Squamous Cell Carcinoma

PIWI-interacting RNAs (piRNAs) are single-stranded, 23-36 nucleotide long RNAs that regulate gene expression in the germline but are also detected in some cancers. However, there are no reports yet on piRNA expression in tongue squamous cell carcinoma (TSCC), the most common oral cancer (80-90% percent of all oral cancers). We performed small RNA and whole transcriptome sequencing in H357 tongue cancer and HOK cells (GEO database accession numbers: GSE196674 and GSE196688). We also examined nine published sets of gene expression array data of TSCC tissues from the GEO database to decode piRNAs and their putative targets that may be involved in tumorigenesis. We identified a pool of 16058 and 25677 piRNAs in H357 and HOK, respectively, among which 406 are differentially expressed. We also found that 2094 protein-coding genes are differentially expressed in either TSCC tissues or cell lines. We performed target predictions for these piRNA, pathway and disease function (DF) analyses, as well as qRT-PCR validation of piRNA-target pairs. These experiments revealed one up-regulated (FDFT1) and four down-regulated (OGA, BDH1, TAT, HYAL4) target genes that are enriched in 11 canonical pathways (CPs), with postulated roles in the initiation and progression of TSCC. Downregulation of piR-33422 is predicted to upregulate the FDFT1 gene, which encodes a mevalonate/cholesterol-pathway related farnesyl-diphosphate farnesyltransferase. The FDFT1 appears to be involved in the largest number of oncogenesis-related processes and is interacting with statins, which is a classical cancer drug. This study provides the first evidence of the piRNome of TSCC, which could be investigated further to decode piRNA-mediated gene regulations in malignancy and potential drug targets, such as FDFT1.

Immunomodulatory Properties of Human Breast Milk: MicroRNA Contents and Potential Epigenetic Effects

Infants who are exclusively breastfed in the first six months of age receive adequate nutrients, achieving optimal immune protection and growth. In addition to the known nutritional components of human breast milk (HBM), i.e., water, carbohydrates, fats and proteins, it is also a rich source of microRNAs, which impact epigenetic mechanisms. This comprehensive work presents an up-to-date overview of the immunomodulatory constituents of HBM, highlighting its content of circulating microRNAs. The epigenetic effects of HBM are discussed, especially those regulated by miRNAs. HBM contains more than 1400 microRNAs. The majority of these microRNAs originate from the lactating gland and are based on the remodeling of cells in the gland during breastfeeding. These miRNAs can affect epigenetic patterns by several mechanisms, including DNA methylation, histone modifications and RNA regulation, which could ultimately result in alterations in gene expressions. Therefore, the unique microRNA profile of HBM, including exosomal microRNAs, is implicated in the regulation of the genes responsible for a variety of immunological and physiological functions, such as FTO, INS, IGF1, NRF2, GLUT1 and FOXP3 genes. Hence, studying the HBM miRNA composition is important for improving the nutritional approaches for pregnancy and infant's early life and preventing diseases that could occur in the future. Interestingly, the composition of miRNAs in HBM is affected by multiple factors, including diet, environmental and genetic factors.

LncRNA-ATB regulates epithelial-mesenchymal transition progression in pulmonary fibrosis via sponging miR-29b-2-5p and miR-34c-3p

Dysregulation of non‐coding RNAs (ncRNAs) has been proved to play pivotal roles in epithelial‐mesenchymal transition (EMT) and fibrosis. We have previously demonstrated the crucial function of long non‐coding RNA (lncRNA) ATB in silica‐induced pulmonary fibrosis‐related EMT progression. However, the underlying molecular mechanism has not been fully elucidated. Here, we verified miR‐29b‐2‐5p and miR‐34c‐3p as two vital downstream targets of lncRNA‐ATB. As opposed to lncRNA‐ATB, a significant reduction of both miR‐29b‐2‐5p and miR‐34c‐3p was observed in lung epithelial cells treated with TGF‐β1 and a murine silicosis model. Overexpression miR‐29b‐2‐5p or miR‐34c‐3p inhibited EMT process and abrogated the pro‐fibrotic effects of lncRNA‐ATB in vitro. Further, the ectopic expression of miR‐29b‐2‐5p and miR‐34c‐3p with chemotherapy attenuated silica‐induced pulmonary fibrosis in vivo. Mechanistically, TGF‐β1‐induced lncRNA‐ATB accelerated EMT as a sponge of miR‐29b‐2‐5p and miR‐34c‐3p and shared miRNA response elements with MEKK2 and NOTCH2, thus relieving these two molecules from miRNA‐mediated translational repression. Interestingly, the co‐transfection of miR‐29b‐2‐5p and miR‐34c‐3p showed a synergistic suppression effect on EMT in vitro. Furthermore, the co‐expression of these two miRNAs by using adeno‐associated virus (AAV) better alleviated silica‐induced fibrogenesis than single miRNA. Approaches aiming at lncRNA‐ATB and its downstream effectors may represent new effective therapeutic strategies in pulmonary fibrosis.

Prediction and Boolean logical modelling of synergistic microRNA regulatory networks during reprogramming of male germline pluripotent stem cells

Unipotent male germline stem (GS) cells can undergo spontaneous reprogramming to germline pluripotent stem (GPS) cells during in vitro culture. In our previous study, we proposed a Boolean logical model of gene regulatory network (GRN) during reprogramming of GS cells to GPS cells. This study was designed to predict and model synergistic microRNA (miRNA) regulatory network during reprogramming of GS cells into GPS cells. The miRNAs targeting differentially expressed genes (DEGs) among GS and GPS cells were predicted by a novel Gene Ontology (GO) enrichment analysis to construct miRNA synergistic networks (MSN) and identify regulatory miRNA modules. Qualitative Boolean logical model of synergistic miRNAs and its regulated genes was then constructed by considering discrete, asynchronous, multivalued logical formalism using the GINsim modeling and simulation tools. Topology, functional and community overlap studies revealed that mmu-miR-200b-3p, mmu-miR-429-3p and mmu-miR-141-3p, mmu-miR-200a-3p and mmu-miR-200c-3p in MSN belongs to the family of miR-200/429/141 and conjectured to control the pluripotency and reprogramming by promoting Mesenchymal to Epithelial Transition (MET). Synergistic network involving mmu-miR-20b-5p, mmu-miR-20a-5p, mmu-miR-106a-5p, mmu-miR-106b-5p, and mmu-miR-17-5p were found to be essential for the maintenance of GS cells. Logical miRNA regulatory network modelling showed that synergistic miRNAs regulates the gene dynamics of MET during GS-GPS reprogramming, as confirmed by perturbation analysis. Taken together, our study predicted novel synergistic miRNAs involved in the regulation of reprogramming and pluripotency in GPS cells. The Boolean logical model of synergistic miRNAs regulatory network further confirms our previous study that gene dynamics of MET regulates GS-GPS reprogramming.

The impact of microRNAs on alterations of gene regulatory networks in allergic diseases

Allergic diseases including asthma are worldwide on the rise and contribute significantly to health expenditures. Allergic diseases are prototypic diseases with a strong gene by environment interaction component and epigenetic mechanisms might mediate the effects of the environment on the disease phenotype. MicroRNAs, small non-coding RNAs (miRNAs), regulate gene expression post-transcriptionally. Functional single-stranded miRNAs are generated in multiple steps of enzymatic processing from their precursors and mature miRNAs are included into the RNA-induced silencing complex (RISC). They imperfectly base-pair with the 3'UTR region of targeted genes leading to translational repression or mRNA decay. The cellular context and microenvironment as well the isoform of the mRNA control the dynamics and complexity of the regulatory circuits induced by miRNAs that regulate cell fate decisions and function. MiR-21, miR-146a/b and miR-155 are among the best understood miRNAs of the immune system and implicated in different diseases including allergic diseases. MiRNAs are implicated in the induction of the allergy reinforcing the Th2 phenotype (miR-19a, miR-24, miR-27), while other miRNAs promote regulatory T cells associated with allergen tolerance or unresponsiveness. In the current chapter we describe in detail the biogenesis and regulatory function of miRNAs and summarize current knowledge on miRNAs in allergic diseases and allergy relevant cell fate decisions focusing mainly on immune cells. Furthermore, we evoke the principles of regulatory loops and feedback mechanisms involving miRNAs on examples with relevance for allergic diseases. Finally, we show the potential of miRNAs and exosomes containing miRNAs present in several biological fluids that can be exploited with non-invasive procedures for diagnostic and potentially therapeutic purposes.

Identifying miRNA synergism using multiple-intervention causal inference

BACKGROUND

Studying multiple microRNAs (miRNAs) synergism in gene regulation could help to understand the regulatory mechanisms of complicated human diseases caused by miRNAs. Several existing methods have been presented to infer miRNA synergism. Most of the current methods assume that miRNAs with shared targets at the sequence level are working synergistically. However, it is unclear if miRNAs with shared targets are working in concert to regulate the targets or they individually regulate the targets at different time points or different biological processes. A standard method to test the synergistic activities is to knock-down multiple miRNAs at the same time and measure the changes in the target genes. However, this approach may not be practical as we would have too many sets of miRNAs to test.

RESULTS

n this paper, we present a novel framework called miRsyn for inferring miRNA synergism by using a causal inference method that mimics the multiple-intervention experiments, e.g. knocking-down multiple miRNAs, with observational data. Our results show that several miRNA-miRNA pairs that have shared targets at the sequence level are not working synergistically at the expression level. Moreover, the identified miRNA synergistic network is small-world and biologically meaningful, and a number of miRNA synergistic modules are significantly enriched in breast cancer. Our further analyses also reveal that most of synergistic miRNA-miRNA pairs show the same expression patterns. The comparison results indicate that the proposed multiple-intervention causal inference method performs better than the single-intervention causal inference method in identifying miRNA synergistic network.

CONCLUSIONS

Taken together, the results imply that miRsyn is a promising framework for identifying miRNA synergism, and it could enhance the understanding of miRNA synergism in breast cancer.

MicroRNA-98-5p prevents bone regeneration by targeting high mobility group AT-Hook 2

MicroRNAs (mRNAs or miRs) serve an important role in the regulation of gene expression. In the present study, the role of miR-98-5p in bone regeneration was determined. Three osteoblast cell models were established, including primary human stem cells (BMMSC), mouse BMMSC's and MC3T3-E1 cells. miR-98-5p expression was determined using reverse transcription-quantitative (RT-q)PCR. Osteoblast markers, including alkaline phosphatase, runt related transcription factor 2 and transcription factor Sp7, were determined using RT-qPCR and western blot analysis, respectively. Alkaline phosphatase activity was determined in the present study and cell proliferation and apoptosis assays were performed. Furthermore, an association between miR-98-5p and high mobility group AT-Hook 2 (HMGA2) was revealed. This association was determined using TargetScan and a dual luciferase reporter assay. The current study demonstrated that miR-98-5p was downregulated during osteogenic differentiation and further demonstrated that HMGA2 may be a direct target of miR-98-5p. The results also demonstrated that miR-98-5p upregulation significantly inhibited the osteogenic differentiation of MC3T3-E1 cells, an effect that was reversed by an increased HMGA2 expression. Additionally, the results revealed that miR-98-5p upregulation inhibited MC3T3-E1 cell viability and induced cell apoptosis and these effects were eliminated by HMGA2 overexpression. In conclusion, miR-98-5p may prevent bone regeneration through inhibiting osteogenic differentiation and osteoblast growth by targeting HMGA2.

Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation

MicroRNAs (miRNAs) are a class of non-coding RNAs that play important roles in regulating gene expression. The majority of miRNAs are transcribed from DNA sequences into primary miRNAs and processed into precursor miRNAs, and finally mature miRNAs. In most cases, miRNAs interact with the 3' untranslated region (3' UTR) of target mRNAs to induce mRNA degradation and translational repression. However, interaction of miRNAs with other regions, including the 5' UTR, coding sequence, and gene promoters, have also been reported. Under certain conditions, miRNAs can also activate translation or regulate transcription. The interaction of miRNAs with their target genes is dynamic and dependent on many factors, such as subcellular location of miRNAs, the abundancy of miRNAs and target mRNAs, and the affinity of miRNA-mRNA interactions. miRNAs can be secreted into extracellular fluids and transported to target cells via vesicles, such as exosomes, or by binding to proteins, including Argonautes. Extracellular miRNAs function as chemical messengers to mediate cell-cell communication. In this review, we provide an update on canonical and non-canonical miRNA biogenesis pathways and various mechanisms underlying miRNA-mediated gene regulations. We also summarize the current knowledge of the dynamics of miRNA action and of the secretion, transfer, and uptake of extracellular miRNAs.

Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation

MicroRNAs (miRNAs) are a class of non-coding RNAs that play important roles in regulating gene expression. The majority of miRNAs are transcribed from DNA sequences into primary miRNAs and processed into precursor miRNAs, and finally mature miRNAs. In most cases, miRNAs interact with the 3' untranslated region (3' UTR) of target mRNAs to induce mRNA degradation and translational repression. However, interaction of miRNAs with other regions, including the 5' UTR, coding sequence, and gene promoters, have also been reported. Under certain conditions, miRNAs can also activate translation or regulate transcription. The interaction of miRNAs with their target genes is dynamic and dependent on many factors, such as subcellular location of miRNAs, the abundancy of miRNAs and target mRNAs, and the affinity of miRNA-mRNA interactions. miRNAs can be secreted into extracellular fluids and transported to target cells via vesicles, such as exosomes, or by binding to proteins, including Argonautes. Extracellular miRNAs function as chemical messengers to mediate cell-cell communication. In this review, we provide an update on canonical and non-canonical miRNA biogenesis pathways and various mechanisms underlying miRNA-mediated gene regulations. We also summarize the current knowledge of the dynamics of miRNA action and of the secretion, transfer, and uptake of extracellular miRNAs.