Identification of a novel distal regulatory element of the human Neuroglobin gene by the chromosome conformation capture approach

Exploration of key drug target proteins highlighting their related regulatory molecules, functional pathways and drug candidates associated with delirium: evidence from meta-data analyses

BACKGROUND

Delirium is a prevalent neuropsychiatric medical phenomenon that causes serious emergency outcomes, including mortality and morbidity. It also increases the suffering and the economic burden for families and carers. Unfortunately, the pathophysiology of delirium is still unknown, which is a major obstacle to therapeutic development. The modern network-based system biology and multi-omics analysis approach has been widely used to recover the key drug target biomolecules and signaling pathways associated with disease pathophysiology. This study aimed to identify the major drug target hub-proteins associated with delirium, their regulatory molecules with functional pathways, and repurposable drug candidates for delirium treatment.

METHODS

We used a comprehensive proteomic seed dataset derived from a systematic literature review and the Comparative Toxicogenomics Database (CTD). An integrated multi-omics network-based bioinformatics approach was utilized in this study. The STRING database was used to construct the protein-protein interaction (PPI) network. The gene set enrichment and signaling pathways analysis, the regulatory transcription factors and microRNAs were conducted using delirium-associated genes. Finally, hub-proteins associated repurposable drugs were retrieved from CMap database.

RESULTS

We have distinguished 11 drug targeted hub-proteins (MAPK1, MAPK3, TP53, JUN, STAT3, SRC, RELA, AKT1, MAPK14, HSP90AA1 and DLG4), 5 transcription factors (FOXC1, GATA2, YY1, TFAP2A and SREBF1) and 6 microRNA (miR-375, miR-17-5, miR-17-5p, miR-106a-5p, miR-125b-5p, and miR-125a-5p) associated with delirium. The functional enrichment and pathway analysis revealed the cytokines, inflammation, postoperative pain, oxidative stress-associated pathways, developmental biology, shigellosis and cellular senescence which are closely connected with delirium development and the hallmarks of aging. The hub-proteins associated computationally identified repurposable drugs were retrieved from database. The predicted drug molecules including aspirin, irbesartan, ephedrine-(racemic), nedocromil, and guanidine were characterized as anti-inflammatory, stimulating the central nervous system, neuroprotective medication based on the existing literatures. The drug molecules may play an important role for therapeutic development against delirium if they are investigated more extensively through clinical trials and various wet lab experiments.

CONCLUSION

This study could possibly help future research on investigating the delirium-associated therapeutic target biomarker hub-proteins and repurposed drug compounds. These results will also aid understanding of the molecular mechanisms that underlie the pathophysiology of delirium onset and molecular function.

Molecular crosstalk between COVID-19 and Alzheimer's disease using microarray and RNA-seq datasets: A system biology approach

Objective

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The clinical and epidemiological analysis reported the association between SARS-CoV-2 and neurological diseases. Among neurological diseases, Alzheimer's disease (AD) has developed as a crucial comorbidity of SARS-CoV-2. This study aimed to understand the common transcriptional signatures between SARS-CoV-2 and AD.

Materials and methods

System biology approaches were used to compare the datasets of AD and COVID-19 to identify the genetic association. For this, we have integrated three human whole transcriptomic datasets for COVID-19 and five microarray datasets for AD. We have identified differentially expressed genes for all the datasets and constructed a protein-protein interaction (PPI) network. Hub genes were identified from the PPI network, and hub genes-associated regulatory molecules (transcription factors and miRNAs) were identified for further validation.

Results

A total of 9,500 differentially expressed genes (DEGs) were identified for AD and 7,000 DEGs for COVID-19. Gene ontology analysis resulted in 37 molecular functions, 79 cellular components, and 129 biological processes were found to be commonly enriched in AD and COVID-19. We identified 26 hub genes which includes AKT1, ALB, BDNF, CD4, CDH1, DLG4, EGF, EGFR, FN1, GAPDH, INS, ITGB1, ACTB, SRC, TP53, CDC42, RUNX2, HSPA8, PSMD2, GFAP, VAMP2, MAPK8, CAV1, GNB1, RBX1, and ITGA2B. Specific miRNA targets associated with Alzheimer's disease and COVID-19 were identified through miRNA target prediction. In addition, we found hub genes-transcription factor and hub genes-drugs interaction. We also performed pathway analysis for the hub genes and found that several cell signaling pathways are enriched, such as PI3K-AKT, Neurotrophin, Rap1, Ras, and JAK-STAT.

Conclusion

Our results suggest that the identified hub genes could be diagnostic biomarkers and potential therapeutic drug targets for COVID-19 patients with AD comorbidity.

CRISPR Activator Approaches to Study Endogenous Androglobin Gene Regulation

Androglobin (ADGB), the most recently identified member of the mammalian globin family, is a chimeric protein with an unusual, embedded globin domain that is circularly permutated and exhibits hallmarks of a hexacoordinated heme-binding scheme. Whereas abundant expression of ADGB was initially found to be mainly restricted to cells in the postmeiotic stages of spermatogenesis, more recent RNA-Seq-based expression analysis data revealed that ADGB is detectable in cells carrying motile cilia or flagella. This very tight regulation of ADGB gene expression urges the need for alternative techniques to study endogenous expression in classical mammalian cell models, which do not express ADGB. We describe here the use of CRISPR activation (CRISPRa) technology to induce endogenous ADGB gene expression in HEK293T, MCF-7, and HeLa cells from its promoter and illustrate how this method can be employed to validate putative regulatory DNA elements of ADGB in promoter and enhancer regions.

Functional characterization of ABCA4 genetic variants related to Stargardt disease

The ATP-binding cassette subfamily 4 (ABCA4), a transporter, is localized within the photoreceptors of the retina, and its genetic variants cause retinal dystrophy. Despite the clinical importance of the ABCA4 transporter, a few studies have investigated the function of each variant. In this study, we functionally characterized ABCA4 variants found in Korean patients with Stargardt disease or variants of the ABCA4 promoter region. We observed that four missense variants-p.Arg290Gln, p.Thr1117Ala, p.Cys1140Trp, and p.Asn1588Tyr-significantly decreased ABCA4 expression on the plasma membrane, which could be due to intracellular degradation. There are four major haplotypes in the ABCA4 proximal promoter. We observed that the H1 haplotype (c.-761C>A) indicated significantly increased luciferase activity compared to that of the wild-type, whereas the H3 haplotype (c.-1086A>C) indicated significantly decreased luciferase activity (P < 0.01 and 0.001, respectively). In addition, c.-900A>T in the H2 haplotype exhibited significantly increased luciferase activity compared with that of the wild-type. Two transcription factors, GATA-2 and HLF, were found to function as enhancers of ABCA4 transcription. Our findings suggest that ABCA4 variants in patients with Stargardt disease affect ABCA4 expression. Furthermore, common variants of the ABCA4 proximal promoter alter the ABCA4 transcriptional activity, which is regulated by GATA-2 and HLF transcription factors.

Key Genes and Biochemical Networks in Various Brain Regions Affected in Alzheimer's Disease

Alzheimer’s disease (AD) is one of the most complicated progressive neurodegenerative brain disorders, affecting millions of people around the world. Ageing remains one of the strongest risk factors associated with the disease and the increasing trend of the ageing population globally has significantly increased the pressure on healthcare systems worldwide. The pathogenesis of AD is being extensively investigated, yet several unknown key components remain. Therefore, we aimed to extract new knowledge from existing data. Ten gene expression datasets from different brain regions including the hippocampus, cerebellum, entorhinal, frontal and temporal cortices of 820 AD cases and 626 healthy controls were analyzed using the robust rank aggregation (RRA) method. Our results returned 1713 robust differentially expressed genes (DEGs) between five brain regions of AD cases and healthy controls. Subsequent analysis revealed pathways that were altered in each brain region, of which the GABAergic synapse pathway and the retrograde endocannabinoid signaling pathway were shared between all AD affected brain regions except the cerebellum, which is relatively less sensitive to the effects of AD. Furthermore, we obtained common robust DEGs between these two pathways and predicted three miRNAs as potential candidates targeting these genes; hsa-mir-17-5p, hsa-mir-106a-5p and hsa-mir-373-3p. Three transcription factors (TFs) were also identified as the potential upstream regulators of the robust DEGs; ELK-1, GATA1 and GATA2. Our results provide the foundation for further research investigating the role of these pathways in AD pathogenesis, and potential application of these miRNAs and TFs as therapeutic and diagnostic targets.

Yin-Yang 1 and HBx protein activate HBV transcription by mediating the spatial interaction of cccDNA minichromosome with cellular chromosome 19p13.11

HBV cccDNA stably exists in the nuclei of infected cells as an episomal munichromosome which is responsible for viral persistence and failure of current antiviral treatments. However, the regulatory mechanism of cccDNA transcription by viral and host cellular factors is not well understood. In this study, we investigated whether cccDNA could be recruited into a specific region of the nucleus via specific interaction with a cellular chromatin to regulate its transcription activity. To investigate this hypothesis, we used chromosome conformation capture (3C) technology to search for the potential interaction of cccDNA and cellular chromatin through rcccDNA transfection in hepatoma cells and found that cccDNA is specifically associated with human chromosome 19p13.11 region, which contains a highly active enhancer element. We also confirmed that cellular transcription factor Yin-Yang 1 (YY1) and viral protein HBx mediated the spatial regulation of HBV cccDNA transcription by 19p13.11 enhancer. Thus, These findings indicate that YY1 and HBx mediate the recruitment of HBV cccDNA minichromosomes to 19p13.11 region for transcription activation, and YY1 may present as a novel therapeutic target against HBV infection.

Genetic Variants and Oxidative Stress in Alzheimer's Disease

In an aging society, the number of people suffering from Alzheimer's Disease (AD) is still growing. Currently, intensive research is being carried out on the pathogenesis of AD. The results of these studies indicated that oxidative stress plays an important role in the onset and development of this disease. Moreover, in AD oxidative stress is generated by both genetic and biochemical factors as well as the functioning of the systems responsible for their formation and removal. The genetic factors associated with the regulation of the redox system include TOMM40, APOE, LPR, MAPT, APP, PSEN1 and PSEN2 genes. The most important biochemical parameters related to the formation of oxidative species in AD are p53, Homocysteine (Hcy) and a number of others. The formation of Reactive Oxygen Species (ROS) is also related to the efficiency of the DNA repair system, the effectiveness of the apoptosis, autophagy and mitophagy processes as well as the antioxidant potential. However, these factors are responsible for the development of many disorders, often with similar clinical symptoms, especially in the early stages of the disease. The discovery of markers of the early diagnosis of AD may contribute to the introduction of pharmacotherapy and slow down the progression of this disease.

A regulatory element in the 3'-untranslated region of CEBPA is associated with myeloid/NK/T-cell leukemia

OBJECTIVES

CCAAT/enhancer-binding protein α (CEBPA) is an essential transcription factor for myeloid differentiation. Not only mutation of the CEBPA gene, but also promoter methylation, which results in silencing of CEBPA, contributes to the pathogenesis of acute myeloid leukemia (AML). We sought for another differentially methylated region (DMR) that associates with the CEBPA silencing and disease phenotype.

METHODS

Using databases, we identified a conserved DMR in the CEBPA 3'-untranslated region (UTR).

RESULTS

Methylation-specific PCR analysis of 231 AML cases showed that hypermethylation of the 3'-UTR was associated with AML that had a myeloid/NK/T-cell phenotype and downregulated CEBPA. Most of these cases were of an immature phenotype with CD7/CD56 positivity. These cases were significantly associated with lower hemoglobin levels than the others. Furthermore, we discovered that the CEBPA 3'-UTR DMR can enhance transcription from the CEBPA native promoter. In vitro experiments identified IKZF1-binding sites in the 3'-UTR that are responsible for this increased transcription of CEBPA.

CONCLUSIONS

These results indicate that the CEBPA 3'-UTR DMR is a novel regulatory element of CEBPA related to myeloid/NK/T-cell lineage leukemogenesis. Transcriptional regulation of CEBPA by IKZF1 may provide a clue for understanding the fate determination of myeloid vs. NK/T-lymphoid progenitors.

Network Medicine Approach for Analysis of Alzheimer's Disease Gene Expression Data

Alzheimer’s disease (AD) is the most widespread diagnosed cause of dementia in the elderly. It is a progressive neurodegenerative disease that causes memory loss as well as other detrimental symptoms that are ultimately fatal. Due to the urgent nature of this disease, and the current lack of success in treatment and prevention, it is vital that different methods and approaches are applied to its study in order to better understand its underlying mechanisms. To this end, we have conducted network-based gene co-expression analysis on data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. By processing and filtering gene expression data taken from the blood samples of subjects with varying disease states and constructing networks based on that data to evaluate gene relationships, we have been able to learn about gene expression correlated with the disease, and we have identified several areas of potential research interest.

Shaping the nebulous enhancer in the era of high-throughput assays and genome editing

Since the 1st discovery of transcriptional enhancers in 1981, their textbook definition has remained largely unchanged in the past 37 years. With the emergence of high-throughput assays and genome editing, which are switching the paradigm from bottom-up discovery and testing of individual enhancers to top-down profiling of enhancer activities genome-wide, it has become increasingly evidenced that this classical definition has left substantial gray areas in different aspects. Here we survey a representative set of recent research articles and report the definitions of enhancers they have adopted. The results reveal that a wide spectrum of definitions is used usually without the definition stated explicitly, which could lead to difficulties in data interpretation and downstream analyses. Based on these findings, we discuss the practical implications and suggestions for future studies.

Network-based approach to identify molecular signatures and therapeutic agents in Alzheimer's disease

Alzheimer's disease (AD) is a dynamic degeneration of the brain with progressive dementia. Considering the uncertainties in its molecular mechanism, in the present study, we employed network-based integrative analyses, and aimed to explore the key molecules and their associations with small drugs to identify potential biomarkers and therapeutic agents for the AD. First of all, we studied a transcriptome dataset and identified 1521 differentially expressed genes (DEGs). Integration of transcriptome data with protein-protein and transcriptional regulatory interactions resulted with central (hub) proteins (UBA52, RAC1, CREBBP, AR, RPS11, SMAD3, RPS6, RPL12, RPL15, and UBC), regulatory transcription factors (FOXC1, GATA2, YY1, FOXL1, NFIC, E2F1, USF2, SRF, PPARG, and JUN) and microRNAs (mir-335-5p, mir-26b-5p, mir-93-5p, mir-124-3p, mir-17-5p, mir-16-5p, mir-20a-5p, mir-92a-3p, mir-106b-5p, and mir-192-5p) as key signaling and regulatory molecules associated with transcriptional changes for the AD. Considering these key molecules as potential therapeutic targets and Connectivity Map (CMap) architecture, candidate small molecular agents (such as STOCK1N-35696) were identified as novel potential therapeutics for the AD. This study presents molecular signatures at RNA and protein levels which might be useful in increasing discernment of the molecular mechanisms, and potential drug targets and therapeutics to design effective treatment strategies for the AD.

17β-estradiol Induces MMP-9 and MMP-13 in TMJ Fibrochondrocytes via Estrogen Receptor α

Temporomandibular joint (TMJ) disorders, including degenerative TMJ disease, occur primarily in women of reproductive age. Previous studies showed elevated estrogen levels in subjects with TMJ disorders relative to controls and the presence of estrogen receptors α and β (ERα and ERβ) in TMJ fibrocartilage. Additionally, estrogen-induced overexpression of specific matrix metalloproteinases (MMPs), including MMP-9 and MMP-13, in TMJ fibrocartilage is accompanied by loss of extracellular matrices. However, the contribution of ERα and ERβ in estrogen-mediated induction of MMP-9 and MMP-13 and the signaling cascade leading to the upregulation of these MMPs have not been elucidated. Here, we show that specific siRNAs and selective ER antagonists effectively block ERα or ERβ expression in primary mouse TMJ fibrochondrocytes, but that only blockage of ERα suppresses MMP-9 and MMP-13 levels induced by 17β-estradiol (E2). Overexpression of ERα but not ERβ enhances E2-induced MMP-9. Using the same loss-of-function and gain-of-function approaches, we demonstrate that E2 stimulates ERK activation through ERα and that inhibition of ERK phosphorylation reduces E2-induced MMP-9. Furthermore, we reveal that E2 promotes NF-κB and ELK-1 activation through ERα/ERK signaling and that knockdown of either one decreases the respective activity of these signaling mediators and MMP-9 expression induced by E2, indicating that both contribute to E2/ERα/ERK-mediated MMP-9 upregulation. This is supported by findings in which mutated binding sites of either NF-κB or ELK-1 in the MMP-9 promoter lead to a significant reduction of E2-stimulated promoter activity. Our findings provide novel molecular mechanisms for the understanding of E2-mediated upregulation of MMPs, having implications to pathophysiologic TMJ cartilage matrix turnover that may yield therapeutic intervention targets for TMJ disorders.

CRISPR-based strategies for studying regulatory elements and chromatin structure in mammalian gene control

The development of high-throughput methods has enabled the genome-wide identification of putative regulatory elements in a wide variety of mammalian cells at an unprecedented resolution. Extensive genomic studies have revealed the important role of regulatory elements and genetic variation therein in disease formation and risk. In most cases, there is only correlative evidence for the roles of these elements and non-coding changes within these elements in pathogenesis. With the advent of genome- and epigenome-editing tools based on the CRISPR technology, it is now possible to test the functional relevance of the regulatory elements and alterations on a genomic scale. Here, we review the various CRISPR-based strategies that have been developed to functionally validate the candidate regulatory elements in mammals as well as the non-coding genetic variants found to be associated with human disease. We also discuss how these synthetic biology tools have helped to elucidate the role of three-dimensional nuclear architecture and higher-order chromatin organization in shaping functional genome and controlling gene expression.

Hill functions for stochastic gene regulatory networks from master equations with split nodes and time-scale separation

The deterministic Hill function depends only on the average values of molecule numbers. To account for the fluctuations in the molecule numbers, the argument of the Hill function needs to contain the means, the standard deviations, and the correlations. Here we present a method that allows for stochastic Hill functions to be constructed from the dynamical evolution of stochastic biocircuits with specific topologies. These stochastic Hill functions are presented in a closed analytical form so that they can be easily incorporated in models for large genetic regulatory networks. Using a repressive biocircuit as an example, we show by Monte Carlo simulations that the traditional deterministic Hill function inaccurately predicts time of repression by an order of two magnitudes. However, the stochastic Hill function was able to capture the fluctuations and thus accurately predicted the time of repression.

VariFunNet, an integrated multiscale modeling framework to study the effects of rare non-coding variants in Genome-Wide Association Studies: applied to Alzheimer's Disease

It is a grand challenge to reveal the causal effects of DNA variants in complex phenotypes. Although statistical techniques can establish correlations between genotypes and phenotypes in Genome-Wide Association Studies (GWAS), they often fail when the variant is rare. The emerging Network-based Association Studies aim to address this shortcoming in statistical analysis, but are mainly applied to coding variations. Increasing evidences suggest that non-coding variants play critical roles in the etiology of complex diseases. However, few computational tools are available to study the effect of rare non-coding variants on phenotypes. Here we have developed a multiscale modeling variant-to-function-to-network framework VariFunNet to address these challenges. VariFunNet first predict the functional variations of molecular interactions, which result from the non-coding variants. Then we incorporate the genes associated with the functional variation into a tissue-specific gene network, and identify subnetworks that transmit the functional variation to molecular phenotypes. Finally, we quantify the functional implication of the subnetwork, and prioritize the association of the non-coding variants with the phenotype. We have applied VariFunNet to investigating the causal effect of rare non-coding variants on Alzheimer's disease (AD). Among top 21 ranked causal non-coding variants, 16 of them are directly supported by existing evidences. The remaining 5 novel variants dysregulate multiple downstream biological processes, all of which are associated with the pathology of AD. Furthermore, we propose potential new drug targets that may modulate diverse pathways responsible for AD. These findings may shed new light on discovering new biomarkers and therapies for the prevention, diagnosis, and treatment of AD. Our results suggest that multiscale modeling is a potentially powerful approach to studying causal genotype-phenotype associations.