Identification of an inter-transcription factor regulatory network in human hepatoma cells by Matrix RNAi

Role of ONECUT family transcription factors in cancer and other diseases

Members of ONECUT transcription factor play an essential role in several developmental processes, however, the atypical expression of ONECUT proteins lead to numerous diseases, including cancer. ONECUT family proteins promote cell proliferation, progression, invasion, metastasis, angiogenesis, and stemness. This family of proteins interacts with other proteins such as KLF4, TGF-β, VEGFA, PRC2, SMAD3 and alters their expression involved in the regulation of various signaling pathways including Jak/Stat3, Akt/Erk, TGF-β, Smad2/3, and HIF-1α. Furthermore, ONECUT proteins are proposed as predictive biomarkers for pancreatic and gastric cancers. The present review summarizes the involvement of ONECUT family proteins in the development and progression of various human cancers and other diseases.

A reference single-cell regulomic and transcriptomic map of cynomolgus monkeys

Non-human primates are attractive laboratory animal models that accurately reflect both developmental and pathological features of humans. Here we present a compendium of cell types across multiple organs in cynomolgus monkeys (Macaca fascicularis) using both single-cell chromatin accessibility and RNA sequencing data. The integrated cell map enables in-depth dissection and comparison of molecular dynamics, cell-type compositions and cellular heterogeneity across multiple tissues and organs. Using single-cell transcriptomic data, we infer pseudotime cell trajectories and cell-cell communications to uncover key molecular signatures underlying their cellular processes. Furthermore, we identify various cell-specific cis-regulatory elements and construct organ-specific gene regulatory networks at the single-cell level. Finally, we perform comparative analyses of single-cell landscapes among mouse, monkey and human. We show that cynomolgus monkey has strikingly higher degree of similarities in terms of immune-associated gene expression patterns and cellular communications to human than mouse. Taken together, our study provides a valuable resource for non-human primate cell biology.

Non-human primates are attractive laboratory animal models that can accurately reflect some developmental and pathological features of humans. Here the authors chart a reference cell map of cynomolgus monkeys using both scATAC-seq and scRNA-seq data across multiple organs, providing insights into the molecular dynamics and cellular heterogeneity of this organism.

SimiC enables the inference of complex gene regulatory dynamics across cell phenotypes

Single-cell RNA-Sequencing has the potential to provide deep biological insights by revealing complex regulatory interactions across diverse cell phenotypes at single-cell resolution. However, current single-cell gene regulatory network inference methods produce a single regulatory network per input dataset, limiting their capability to uncover complex regulatory relationships across related cell phenotypes. We present SimiC, a single-cell gene regulatory inference framework that overcomes this limitation by jointly inferring distinct, but related, gene regulatory dynamics per phenotype. We show that SimiC uncovers key regulatory dynamics missed by previously proposed methods across a range of systems, both model and non-model alike. In particular, SimiC was able to uncover CAR T cell dynamics after tumor recognition and key regulatory patterns on a regenerating liver, and was able to implicate glial cells in the generation of distinct behavioral states in honeybees. SimiC hence establishes a new approach to quantitating regulatory architectures between distinct cellular phenotypes, with far-reaching implications for systems biology.

Human Glial Progenitor Cells Effectively Remyelinate the Demyelinated Adult Brain

Neonatally transplanted human glial progenitor cells (hGPCs) can myelinate the brains of myelin-deficient shiverer mice, rescuing their phenotype and survival. Yet, it has been unclear whether implanted hGPCs are similarly able to remyelinate the diffusely demyelinated adult CNS. We, therefore, ask if hGPCs could remyelinate both congenitally hypomyelinated adult shiverers and normal adult mice after cuprizone demyelination. In adult shiverers, hGPCs broadly disperse and differentiate as myelinating oligodendrocytes after subcortical injection, improving both host callosal conduction and ambulation. Implanted hGPCs similarly remyelinate denuded axons after cuprizone demyelination, whether delivered before or after demyelination. RNA sequencing (RNA-seq) of hGPCs back from cuprizone-demyelinated brains reveals their transcriptional activation of oligodendrocyte differentiation programs, while distinguishing them from hGPCs not previously exposed to demyelination. These data indicate the ability of transplanted hGPCs to disperse throughout the adult CNS, to broadly myelinate regions of dysmyelination, and also to be recruited as myelinogenic oligodendrocytes later in life, upon demyelination-associated demand.

A computer-guided design tool to increase the efficiency of cellular conversions

Human cell conversion technology has become an important tool for devising new cell transplantation therapies, generating disease models and testing gene therapies. However, while transcription factor over-expression-based methods have shown great promise in generating cell types in vitro, they often endure low conversion efficiency. In this context, great effort has been devoted to increasing the efficiency of current protocols and the development of computational approaches can be of great help in this endeavor. Here we introduce a computer-guided design tool that combines a computational framework for prioritizing more efficient combinations of instructive factors (IFs) of cellular conversions, called IRENE, with a transposon-based genomic integration system for efficient delivery. Particularly, IRENE relies on a stochastic gene regulatory network model that systematically prioritizes more efficient IFs by maximizing the agreement of the transcriptional and epigenetic landscapes between the converted and target cells. Our predictions substantially increased the efficiency of two established iPSC-differentiation protocols (natural killer cells and melanocytes) and established the first protocol for iPSC-derived mammary epithelial cells with high efficiency.

Peretinoin, an Acyclic Retinoid, for the Secondary Prevention of Hepatocellular Carcinoma

The high rates of hepatocellular carcinoma (HCC) recurrence after initially successful curative therapy emphasize ongoing unmet needs to prevent or reduce HCC recurrence. Retinoid acid (RA), a metabolite of vitamin A and its related analogues (termed retinoids) has been suggested as a promising chemotherapeutic agent in cancer treatment. The synthetic oral retinoid peretinoin is the only agent for the secondary chemoprevention of HCC after curative therapy that is currently well applied into clinical development. Here we present an updated summary of the molecular pathogenesis of HCC and of preclinical and clinical findings with peretinoin, including its clinical characteristics, safety and tolerability profile and future perspectives for clinical use.

Early Transcriptional Changes within Liver, Adrenal Gland, and Lymphoid Tissues Significantly Contribute to Ebola Virus Pathogenesis in Cynomolgus Macaques

Ebola virus (EBOV) continues to pose a significant threat to human health, as evidenced by the 2013-2016 epidemic in West Africa and the ongoing outbreak in the Democratic Republic of the Congo. EBOV causes hemorrhagic fever, organ damage, and shock culminating in death, with case fatality rates as high as 90%. This high lethality combined with the paucity of licensed medical countermeasures makes EBOV a critical human pathogen. Although EBOV infection results in significant damage to the liver and the adrenal glands, little is known about the molecular signatures of injury in these organs. Moreover, while changes in peripheral blood cells are becoming increasingly understood, the host responses within organs and lymphoid tissues remain poorly characterized. To address this knowledge gap, we tracked longitudinal transcriptional changes in tissues collected from EBOV-Makona-infected cynomolgus macaques. Following infection, both liver and adrenal glands exhibited significant and early downregulation of genes involved in metabolism, coagulation, hormone synthesis, and angiogenesis; upregulated genes were associated with inflammation. Analysis of lymphoid tissues showed early upregulation of genes that play a role in innate immunity and inflammation and downregulation of genes associated with cell cycle and adaptive immunity. Moreover, transient activation of innate immune responses and downregulation of humoral immune responses in lymphoid tissues were confirmed with flow cytometry. Together, these data suggest that the liver, adrenal gland, and lymphatic organs are important sites of EBOV infection and that dysregulating the function of these vital organs contributes to the development of Ebola virus disease.IMPORTANCE Ebola virus (EBOV) remains a high-priority pathogen since it continues to cause outbreaks with high case fatality rates. Although it is well established that EBOV results in severe organ damage, our understanding of tissue injury in the liver, adrenal glands, and lymphoid tissues remains limited. We begin to address this knowledge gap by conducting longitudinal gene expression studies in these tissues, which were collected from EBOV-infected cynomolgus macaques. We report robust and early gene expression changes within these tissues, indicating they are primary sites of EBOV infection. Furthermore, genes involved in metabolism, coagulation, and adaptive immunity were downregulated, while inflammation-related genes were upregulated. These results indicate significant tissue damage consistent with the development of hemorrhagic fever and lymphopenia. Our study provides novel insight into EBOV-host interactions and elucidates how host responses within the liver, adrenal glands, and lymphoid tissues contribute to EBOV pathogenesis.

The role of lineage specifiers in pancreatic ductal adenocarcinoma

Over the last decade, multiple genomics studies have led to the identification of discrete molecular subtypes of pancreatic ductal adenocarcinoma. A general theme has emerged that most pancreatic ductal adenocarcinoma (PDAC) can be grouped into two major subtypes based on cancer cell autonomous properties: classical/pancreatic progenitor and basal-like/squamous. The classical/progenitor subtype expresses higher levels of lineage specifiers that regulate endodermal differentiation than the basal-like/squamous subtype. The basal-like/squamous subtype confers a worse prognosis, raising the possibility that loss of these lineage specifiers might enhance the malignant potential of PDAC. Here, we discuss several of these differentially expressed lineage specifiers and examine the evidence that they might play a functional role in PDAC biology.

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions.

Forkhead box protein A2, a pioneer factor for hepatogenesis, is involved in the expression of hepatic phenotype of alpha-fetoprotein-producing adenocarcinoma

Alpha-fetoprotein (AFP)-producing adenocarcinoma is a high-malignant variant of adenocarcinoma with a hepatic or fetal-intestinal phenotype. The number of cases of AFP-producing adenocarcinomas is increasing, but the molecular mechanism underlying the aberrant production of AFP is unclear. Here we sought to assess the role of Forkhead box A (FoxA)2, which is a pioneer transcription factor in the differentiation of hepatoblasts. FoxA2 expression was investigated in five cases of AFP-producing gastric adenocarcinomas by immunohistochemistry, and all cases showed FoxA2 expression. Chromatin immunoprecipitation revealed the DNA binding of FoxA2 on the regulatory element of AFP gene in AFP-producing adenocarcinoma cells. The inhibition of FoxA2 expression with siRNA reduced the mRNA expression of liver-specific proteins, including AFP, albumin, and transferrin. The inhibition of FoxA2 also reduced the expressions of liver-enriched nuclear factors, i.e., hepatocyte nuclear factor (HNF) 4α and HNF6, although the expressions of HNF1α and HNF1β were not affected. The same effect as FoxA2 knockdown in AFP producing adenocarcinoma cells was also observed in hepatocellular carcinoma cells. Our results suggest that FoxA2 plays a key role in the expression of hepatic phenotype of AFP-producing adenocarcinomas.

The activity of the carbamoyl phosphate synthase 1 promoter in human liver-derived cells is dependent on hepatocyte nuclear factor 3-beta

Carbamoyl phosphate synthase 1 (CPS1) is the rate‐limiting enzyme in the first step of the urea cycle and an indispensable enzyme in the metabolism of human liver. However, CPS1 epigenetic regulation involves promoter analysis and the role of liver‐enriched transcription factors (LETFs), which is not fully elucidated. In this work, the promoter region of hCPS1 gene was cloned, and its activity was investigated. An LETF, hepatocyte nuclear factor 3‐beta (HNF3β), was found to promote the transcriptional expression of CPS1 in liver‐derived cell lines. In addition, dual‐luciferase reporter assay shows that the essential binding sites of the HNF3β may exist in the oligonucleotide −70 nt to +73 nt. Two putative binding sites are available for HNF3β. Mutation analysis results show that the binding site 2 of HNF3β was effective, and the transcriptional activity of CPS1 promoter significantly decreased after mutation. Electrophoretic mobile shift assay (EMSA) and ChIP assay confirmed that HNF3β can interact with the binding site in the CPS1 promoter region of −70 nt to +73 nt promoter region in vivo and in vitro to regulate the transcription of CPS1. Moreover, HNF3β overexpression enhanced the transcription of CPS1 and consequently improved the mRNA and protein levels of CPS1, whereas the knockdown of HNF3β showed the opposite effects. Finally, urea production in cells was measured, and ammonia detoxification improved significantly in cells after transfection with HNF3β. HNF3β plays a vital role in regulation of CPS1 gene and could promote the metabolism of ammonia by regulating CPS1 expression.

DNA methylation alters transcriptional rates of differentially expressed genes and contributes to pathophysiology in mice fed a high fat diet

OBJECTIVE

Overnutrition can alter gene expression patterns through epigenetic mechanisms that may persist through generations. However, it is less clear if overnutrition, for example a high fat diet, modifies epigenetic control of gene expression in adults, or by what molecular mechanisms, or if such mechanisms contribute to the pathology of the metabolic syndrome. Here we test the hypothesis that a high fat diet alters hepatic DNA methylation, transcription and gene expression patterns, and explore the contribution of such changes to the pathophysiology of obesity.

METHODS

RNA-seq and targeted high-throughput bisulfite DNA sequencing were used to undertake a systematic analysis of the hepatic response to a high fat diet. RT-PCR, chromatin immunoprecipitation and in vivo knockdown of an identified driver gene, Phlda1, were used to validate the results.

RESULTS

A high fat diet resulted in the hypermethylation and decreased transcription and expression of Phlda1 and several other genes. A subnetwork of genes associated with Phlda1 was identified from an existing Bayesian gene network that contained numerous hepatic regulatory genes involved in lipid and body weight homeostasis. Hepatic-specific depletion of Phlda1 in mice decreased expression of the genes in the subnetwork, and led to increased oil droplet size in standard chow-fed mice, an early indicator of steatosis, validating the contribution of this gene to the phenotype.

CONCLUSIONS

We conclude that a high fat diet alters the epigenetics and transcriptional activity of key hepatic genes controlling lipid homeostasis, contributing to the pathophysiology of obesity.

Oncoprotein HBXIP Modulates Abnormal Lipid Metabolism and Growth of Breast Cancer Cells by Activating the LXRs/SREBP-1c/FAS Signaling Cascade

Abnormal lipid metabolism is a hallmark of tumorigenesis. Accumulating evidence demonstrates that fatty acid synthase (FAS, FASN) is a metabolic oncogene that supports the growth and survival of tumor cells and is highly expressed in many cancers. Here, we report that the oncoprotein, hepatitis B X-interacting protein (HBXIP, LAMTOR5) contributes to abnormal lipid metabolism. We show that high expression of HBXIP in 236 breast cancer patients was significantly associated with decreased overall survival and progression-free survival. Interestingly, the expression of HBXIP was positively related to that of FAS in clinical breast cancer tissues, and HBXIP overexpression in breast cancer cells resulted in FAS upregulation. Mechanistically, HBXIP upregulated SREBP-1c (SREBF1), which activates the transcription of FAS, by directly interacting with and coactivating nuclear receptor (NR) liver X receptors (LXR). Physiologically, LXRs are activated via a coactivator containing NR motif in a ligand-dependent manner. However, in breast cancer cells, HBXIP containing the corepressor/nuclear receptor motif with special flanking sequence could coactivate LXRs independent of ligand. Moreover, overexpressed SREBP-1c was able to activate the transcription of HBXIP, forming a positive-feedback loop. Functionally, HBXIP enhanced lipogenesis, resulting in the growth of breast cancer cells in vitro and in vivo Thus, we conclude that the oncoprotein HBXIP contributes to the abnormal lipid metabolism in breast cancer through LXRs/SREBP-1c/FAS signaling, providing new insights into the mechanisms by which cancer cells reprogram lipid metabolism in their favor. Cancer Res; 76(16); 4696-707. ©2016 AACR.

Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method

BACKGROUND

Inference of gene regulation from expression data may help to unravel regulatory mechanisms involved in complex diseases or in the action of specific drugs. A challenging task for many researchers working in the field of systems biology is to build up an experiment with a limited budget and produce a dataset suitable to reconstruct putative regulatory modules worth of biological validation.

RESULTS

Here, we focus on small-scale gene expression screens and we introduce a novel experimental set-up and a customized method of analysis to make inference on regulatory modules starting from genetic perturbation data, e.g. knockdown and overexpression data. To illustrate the utility of our strategy, it was applied to produce and analyze a dataset of quantitative real-time RT-PCR data, in which interferon-α (IFN-α) transcriptional response in endothelial cells is investigated by RNA silencing of two candidate IFN-α modulators, STAT1 and IFIH1. A putative regulatory module was reconstructed by our method, revealing an intriguing feed-forward loop, in which STAT1 regulates IFIH1 and they both negatively regulate IFNAR1. STAT1 regulation on IFNAR1 was object of experimental validation at the protein level.

CONCLUSIONS

Detailed description of the experimental set-up and of the analysis procedure is reported, with the intent to be of inspiration for other scientists who want to realize similar experiments to reconstruct gene regulatory modules starting from perturbations of possible regulators. Application of our approach to the study of IFN-α transcriptional response modulators in endothelial cells has led to many interesting novel findings and new biological hypotheses worth of validation.

Telomerase reverse transcriptase regulates microRNAs

MicroRNAs are small non-coding RNAs that inhibit the translation of target mRNAs. In humans, most microRNAs are transcribed by RNA polymerase II as long primary transcripts and processed by sequential cleavage of the two RNase III enzymes, DROSHA and DICER, into precursor and mature microRNAs, respectively. Although the fundamental functions of microRNAs in RNA silencing have been gradually uncovered, less is known about the regulatory mechanisms of microRNA expression. Here, we report that telomerase reverse transcriptase (TERT) extensively affects the expression levels of mature microRNAs. Deep sequencing-based screens of short RNA populations revealed that the suppression of TERT resulted in the downregulation of microRNAs expressed in THP-1 cells and HeLa cells. Primary and precursor microRNA levels were also reduced under the suppression of TERT. Similar results were obtained with the suppression of either BRG1 (also called SMARCA4) or nucleostemin, which are proteins interacting with TERT and functioning beyond telomeres. These results suggest that TERT regulates microRNAs at the very early phases in their biogenesis, presumably through non-telomerase mechanism(s).

Foxa1 and Foxa2 regulate α-cell differentiation, glucagon biosynthesis, and secretion

The Forkhead box A transcription factors are major regulators of glucose homeostasis. They show both distinct and redundant roles during pancreas development and in adult mouse β-cells. In vivo ablation studies have revealed critical implications of Foxa1 on glucagon biosynthesis and requirement of Foxa2 in α-cell terminal differentiation. In order to examine the respective role of these factors in mature α-cells, we used small interfering RNA (siRNA) directed against Foxa1 and Foxa2 in rat primary pancreatic α-cells and rodent α-cell lines leading to marked decreases in Foxa1 and Foxa2 mRNA levels and proteins. Both Foxa1 and Foxa2 control glucagon gene expression specifically through the G2 element. Although we found that Foxa2 controls the expression of the glucagon, MafB, Pou3f4, Pcsk2, Nkx2.2, Kir6.2, and Sur1 genes, Foxa1 only regulates glucagon gene expression. Interestingly, the Isl1 and Gipr genes were not controlled by either Foxa1 or Foxa2 alone but by their combination. Foxa1 and Foxa2 directly activate and bind the promoter region the Nkx2.2, Kir6.2 and Sur1, Gipr, Isl1, and Pou3f4 genes. We also demonstrated that glucagon secretion is affected by the combined effects of Foxa1 and Foxa2 but not by either one alone. Our results indicate that Foxa1 and Foxa2 control glucagon biosynthesis and secretion as well as α-cell differentiation with both common and unique target genes.

Temporal dynamics and transcriptional control using single-cell gene expression analysis

Background

Changes in environmental conditions lead to expression variation that manifest at the level of gene regulatory networks. Despite a strong understanding of the role noise plays in synthetic biological systems, it remains unclear how propagation of expression heterogeneity in an endogenous regulatory network is distributed and utilized by cells transitioning through a key developmental event.

Results

Here we investigate the temporal dynamics of a single-cell transcriptional network of 45 transcription factors in THP-1 human myeloid monocytic leukemia cells undergoing differentiation to macrophages. We systematically measure temporal regulation of expression and variation by profiling 120 single cells at eight distinct time points, and infer highly controlled regulatory modules through which signaling operates with stochastic effects. This reveals dynamic and specific rewiring as a cellular strategy for differentiation. The integration of both positive and negative co-expression networks further identifies the proto-oncogene MYB as a network hinge to modulate both the pro- and anti-differentiation pathways.

Conclusions

Compared to averaged cell populations, temporal single-cell expression profiling provides a much more powerful technique to probe for mechanistic insights underlying cellular differentiation. We believe that our approach will form the basis of novel strategies to study the regulation of transcription at a single-cell level.

A transient disruption of fibroblastic transcriptional regulatory network facilitates trans-differentiation

Transcriptional Regulatory Networks (TRNs) coordinate multiple transcription factors (TFs) in concert to maintain tissue homeostasis and cellular function. The re-establishment of target cell TRNs has been previously implicated in direct trans-differentiation studies where the newly introduced TFs switch on a set of key regulatory factors to induce de novo expression and function. However, the extent to which TRNs in starting cell types, such as dermal fibroblasts, protect cells from undergoing cellular reprogramming remains largely unexplored. In order to identify TFs specific to maintaining the fibroblast state, we performed systematic knockdown of 18 fibroblast-enriched TFs and analyzed differential mRNA expression against the same 18 genes, building a Matrix-RNAi. The resulting expression matrix revealed seven highly interconnected TFs. Interestingly, suppressing four out of seven TFs generated lipid droplets and induced PPARG and CEBPA expression in the presence of adipocyte-inducing medium only, while negative control knockdown cells maintained fibroblastic character in the same induction regime. Global gene expression analyses further revealed that the knockdown-induced adipocytes expressed genes associated with lipid metabolism and significantly suppressed fibroblast genes. Overall, this study reveals the critical role of the TRN in protecting cells against aberrant reprogramming, and demonstrates the vulnerability of donor cell's TRNs, offering a novel strategy to induce transgene-free trans-differentiations.

A bayesian framework that integrates heterogeneous data for inferring gene regulatory networks

Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein-protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances.

An integrated approach for the identification of USF1-centered transcriptional regulatory networks during liver regeneration

Liver regeneration after partial hepatectomy (PH) is a synchronized process that is precisely controlled by system-wide transcriptional regulatory networks. To clarify the transcriptional changes and regulatory networks that involve transcription factors (TFs) and their target genes during the priming phase, an advanced mouse oligonucleotide array-based transcription factor assay (MOUSE OATFA), mRNA microarray analysis, bioinformatic analysis and ChIP-on-chip experiments were used. A total of 774 genes were upregulated or downregulated in PH liver samples compared with the sham operation (SH) group. Seventeen TFs showed significant changes in activity in the regenerating livers, some of which have not been extensively studied in previous reports, including upstream stimulatory transcription factor 1 (USF1). The TF signatures from MOUSE OATFA were combined with mRNA expression profiles and ChIP-on-chip analyses to construct experimental transcriptional regulatory networks in regenerating livers. USF1-centered regulatory networks were further confirmed by ChIP assays, revealing some of its target genes and novel coregulatory networks. The combination of MOUSE OATFA with transcriptome profiling and bioinformatic analysis represents a novel paradigm for the comprehensive prediction of transcriptional coregulatory networks during the early phase of liver regeneration.

ISMARA: automated modeling of genomic signals as a democracy of regulatory motifs

Accurate reconstruction of the regulatory networks that control gene expression is one of the key current challenges in molecular biology. Although gene expression and chromatin state dynamics are ultimately encoded by constellations of binding sites recognized by regulators such as transcriptions factors (TFs) and microRNAs (miRNAs), our understanding of this regulatory code and its context-dependent read-out remains very limited. Given that there are thousands of potential regulators in mammals, it is not practical to use direct experimentation to identify which of these play a key role for a particular system of interest. We developed a methodology that models gene expression or chromatin modifications in terms of genome-wide predictions of regulatory sites and completely automated it into a web-based tool called ISMARA (Integrated System for Motif Activity Response Analysis). Given only gene expression or chromatin state data across a set of samples as input, ISMARA identifies the key TFs and miRNAs driving expression/chromatin changes and makes detailed predictions regarding their regulatory roles. These include predicted activities of the regulators across the samples, their genome-wide targets, enriched gene categories among the targets, and direct interactions between the regulators. Applying ISMARA to data sets from well-studied systems, we show that it consistently identifies known key regulators ab initio. We also present a number of novel predictions including regulatory interactions in innate immunity, a master regulator of mucociliary differentiation, TFs consistently disregulated in cancer, and TFs that mediate specific chromatin modifications.

Overexpression of miR-122 promotes the hepatic differentiation and maturation of mouse ESCs through a miR-122/FoxA1/HNF4a-positive feedback loop

BACKGROUND & AIMS

microRNA-122 is the only identified liver-specific miRNA and plays a crucial role in liver development, maintenance of hepatic homeostasis as well as tumourigenesis. In our previous differentiation of ESCs into hepatocytes, microRNA-122 (miR-122) was expressed at a relatively low level. Here, we aim to elucidate the effect and underlying mechanisms of miR-122 during differentiation of ESCs into hepatocytes.

METHODS

Mouse ESCs were initially induced towards HPCs by activin A, FGF-4 and sodium butyrate and were subsequently transfected with a recombinant adenovirus expressing vector pAV.Ex1d-CMV>miR-122/IRES/eGFP 9 days after induction. Cells were analysed by real-time PCR, immunofluorescence, flow cytometry, microscopy and functional assays. Furthermore, microarray analysis was performed.

RESULTS

We demonstrated that overexpression of miR-122 could effectively promote hepatic differentiation and maturation, as assessed by morphological and functional tests. The microarray analysis revealed that 323 genes were down-regulated, whereas 59 were up-regulated. Particularly, two liver-specific transcription factors, FoxA1 and HNF4a, were significantly up-regulated. Moreover, the expression of E-cadherin was dramatically increased and the proliferation of HPCs was suppressed, whereas knockdown of FoxA1 reduced E-cadherin expression and increased the proliferation of HPCs. In addition, the expression levels of FoxA1, HNF4a and E-cadherin in time-course transfection experiments with miR-122 were not significantly increased except in cells in which transfection with miR-122 occurred 9 days after induction.

CONCLUSION

Overexpression of miR-122 at an appropriate stage could promote hepatic differentiation and maturation by regulating the balance between proliferation and differentiation, as well as the balance between EMT and MET, partially through a miR-122/FoxA1/HNF4a-positive feedback loop.

Deep resequencing of GWAS loci identifies rare variants in CARD9, IL23R and RNF186 that are associated with ulcerative colitis

Genome-wide association studies and follow-up meta-analyses in Crohn's disease (CD) and ulcerative colitis (UC) have recently identified 163 disease-associated loci that meet genome-wide significance for these two inflammatory bowel diseases (IBD). These discoveries have already had a tremendous impact on our understanding of the genetic architecture of these diseases and have directed functional studies that have revealed some of the biological functions that are important to IBD (e.g. autophagy). Nonetheless, these loci can only explain a small proportion of disease variance (~14% in CD and 7.5% in UC), suggesting that not only are additional loci to be found but that the known loci may contain high effect rare risk variants that have gone undetected by GWAS. To test this, we have used a targeted sequencing approach in 200 UC cases and 150 healthy controls (HC), all of French Canadian descent, to study 55 genes in regions associated with UC. We performed follow-up genotyping of 42 rare non-synonymous variants in independent case-control cohorts (totaling 14,435 UC cases and 20,204 HC). Our results confirmed significant association to rare non-synonymous coding variants in both IL23R and CARD9, previously identified from sequencing of CD loci, as well as identified a novel association in RNF186. With the exception of CARD9 (OR = 0.39), the rare non-synonymous variants identified were of moderate effect (OR = 1.49 for RNF186 and OR = 0.79 for IL23R). RNF186 encodes a protein with a RING domain having predicted E3 ubiquitin-protein ligase activity and two transmembrane domains. Importantly, the disease-coding variant is located in the ubiquitin ligase domain. Finally, our results suggest that rare variants in genes identified by genome-wide association in UC are unlikely to contribute significantly to the overall variance for the disease. Rather, these are expected to help focus functional studies of the corresponding disease loci.

Peretinoin, an acyclic retinoid, improves the hepatic gene signature of chronic hepatitis C following curative therapy of hepatocellular carcinoma

Background

The acyclic retinoid, peretinoin, has been shown to be effective for suppressing hepatocellular carcinoma (HCC) recurrence after definitive treatment in a small-scale randomized clinical trial. However, little has been documented about the mechanism by which peretinoin exerts its inhibitory effects against recurrent HCC in humans in vivo.

Methods

Twelve hepatitis C virus-positive patients whose HCC had been eradicated through curative resection or ablation underwent liver biopsy at baseline and week 8 of treatment with either a daily dose of 300 or 600 mg peretinoin. RNA isolated from biopsy samples was subjected to gene expression profile analysis.

Results

Peretinoin treatment elevated the expression levels of IGFBP6, RBP1, PRB4, CEBPA, G0S2, TGM2, GPRC5A, CYP26B1, and many other retinoid target genes. Elevated expression was also observed for interferon-, Wnt-, and tumor suppressor-related genes. By contrast, decreased expression levels were found for mTOR- and tumor progression-related genes. Interestingly, gene expression profiles for week 8 of peretinoin treatment could be classified into two groups of recurrence and non-recurrence with a prediction accuracy rate of 79.6% (P<0.05). In the liver of patients with non-recurrence, expression of PDGFC and other angiogenesis genes, cancer stem cell marker genes, and genes related to tumor progression was down-regulated, while expression of genes related to hepatocyte differentiation, tumor suppression genes, and other genes related to apoptosis induction was up-regulated.

Conclusions

Gene expression profiling at week 8 of peretinoin treatment could successfully predict HCC recurrence within 2 years. This study is the first to show the effect of peretinoin in suppressing HCC recurrence in vivo based on gene expression profiles and provides a molecular basis for understanding the efficacy of peretinoin.

Reconstruction of monocyte transcriptional regulatory network accompanies monocytic functions in human fibroblasts

Transcriptional regulatory networks (TRN) control the underlying mechanisms behind cellular functions and they are defined by a set of core transcription factors regulating cascades of peripheral genes. Here we report SPI1, CEBPA, MNDA and IRF8 as core transcription factors of monocyte TRN and demonstrate functional inductions of phagocytosis, inflammatory response and chemotaxis activities in human dermal fibroblasts. The Gene Ontology and KEGG pathway analyses also revealed notable representation of genes involved in immune response and endocytosis in fibroblasts. Moreover, monocyte TRN-inducers triggered multiple monocyte-specific genes based on the transcription factor motif response analysis and suggest that complex cellular TRNs are uniquely amenable to elicit cell-specific functions in unrelated cell types.

Human liver fatty acid binding protein (hFABP1) gene is regulated by liver-enriched transcription factors HNF3β and C/EBPα

The human liver fatty acid binding protein (hFABP1) participates in cellular long-chain fatty acid trafficking and regulation of lipid metabolism and changes in hFABP1 are associated with an increased risk for type 2 diabetes, cardiovascular disease (CVD), and metabolic syndromes. Gene regulation of hFABP1 is not fully understood. Therefore, in the present study, the full length hFABP1 promoter (nucleotides -2125 to +51) and a series of truncated promoter regions were cloned. A luciferase reporter assay revealed that nucleotides -255 to +50 in the promoter region contained full of maximum hFABP1 promoter activity compared with the full length promoter. Furthermore high activity was shown when the plasmid was transfected into liver-derived cells such as the human hepatoblastoma cell line HepG2 and the hepatoma cell line Huh7. TFSEARCH and TESS programs were used to predict potential transcription factor binding sites. Two putative binding sites for the liver-enriched transcription factors hepatocyte nuclear factor 3β (HNF3β) and CCAAT/enhancer binding protein α (C/EBPα) were identified in the -255 nt to -155 nt hFABP1 promoter region. Site-directed mutagenesis of these two sites reduced dramatically hFABP1 promoter activity. In addition, the electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation assay (ChIP) revealed that these binding sites were recognized by HNF3β and C/EBPα respectively. Overexpression of HNF3β and C/EBPα enhanced the transcription of hFABP1 and consequently improved the protein level of hFABP1 in HepG2 cells, while knockdown of HNF3β and C/EBPα showed the inverse effects. Taken together, the hFABP1 gene is highly transcribed in liver-derived cells, and regulated predominantly by liver-enriched transcription factors HNF3β and C/EBPα.

A comprehensive survey of 3' animal miRNA modification events and a possible role for 3' adenylation in modulating miRNA targeting effectiveness

Animal microRNA sequences are subject to 3' nucleotide addition. Through detailed analysis of deep-sequenced short RNA data sets, we show adenylation and uridylation of miRNA is globally present and conserved across Drosophila and vertebrates. To better understand 3' adenylation function, we deep-sequenced RNA after knockdown of nucleotidyltransferase enzymes. The PAPD4 nucleotidyltransferase adenylates a wide range of miRNA loci, but adenylation does not appear to affect miRNA stability on a genome-wide scale. Adenine addition appears to reduce effectiveness of miRNA targeting of mRNA transcripts while deep-sequencing of RNA bound to immunoprecipitated Argonaute (AGO) subfamily proteins EIF2C1-EIF2C3 revealed substantial reduction of adenine addition in miRNA associated with EIF2C2 and EIF2C3. Our findings show 3' addition events are widespread and conserved across animals, PAPD4 is a primary miRNA adenylating enzyme, and suggest a role for 3' adenine addition in modulating miRNA effectiveness, possibly through interfering with incorporation into the RNA-induced silencing complex (RISC), a regulatory role that would complement the role of miRNA uridylation in blocking DICER1 uptake.

Molecular interactions between HNF4a, FOXA2 and GABP identified at regulatory DNA elements through ChIP-sequencing

Gene expression is regulated by combinations of transcription factors, which can be mapped to regulatory elements on a genome-wide scale using ChIP experiments. In a previous ChIP-chip study of USF1 and USF2 we found evidence also of binding of GABP, FOXA2 and HNF4a within the enriched regions. Here, we have applied ChIP-seq for these transcription factors and identified 3064 peaks of enrichment for GABP, 7266 for FOXA2 and 18783 for HNF4a. Distal elements with USF2 signal was frequently bound also by HNF4a and FOXA2. GABP peaks were found at transcription start sites, whereas 94% of FOXA2 and 90% of HNF4a peaks were located at other positions. We developed a method to accurately define TFBS within peaks, and found the predicted sites to have an elevated conservation level compared to peak centers; however the majority of bindings were not evolutionary conserved. An interaction between HNF4a and GABP was seen at TSS, with one-third of the HNF4a positive promoters being bound also by GABP, and this interaction was verified by co-immunoprecipitations.

Regulatory interdependence of myeloid transcription factors revealed by Matrix RNAi analysis

The knockdown of 78 transcription factors in differentiating human THP-1 cells using matrix RNAi reveals their interdependence

Background

With the move towards systems biology, we need sensitive and reliable ways to determine the relationships between transcription factors and their target genes. In this paper we analyze the regulatory relationships between 78 myeloid transcription factors and their coding genes by using the matrix RNAi system in which a set of transcription factor genes are individually knocked down and the resultant expression perturbation is quantified.

Results

Using small interfering RNAs we knocked down the 78 transcription factor genes in monocytic THP-1 cells and monitored the perturbation of the expression of the same 78 transcription factors and 13 other transcription factor genes as well as 5 non-transcription factor genes by quantitative real-time RT-PCR, thereby building a 78 × 96 matrix of perturbation and measurement. This approach identified 876 cases where knockdown of one transcription factor significantly affected the expression of another (from a potential 7,488 combinations). Our study also revealed cell-type-specific transcriptional regulatory networks in two different cell types.

Conclusions

By considering whether the targets of a given transcription factor are naturally up- or downregulated during phorbol 12-myristate 13-acetate-induced differentiation, we could classify these edges as pro-differentiative (229), anti-differentiative (76) or neither (571) using expression profiling data obtained in the FANTOM4 study. This classification analysis suggested that several factors could be involved in monocytic differentiation, while others such as MYB and the leukemogenic fusion MLL-MLLT3 could help to maintain the initial undifferentiated state by repressing the expression of pro-differentiative factors or maintaining expression of anti-differentiative factors.