Chromatin Immunoprecipitation to Investigate H2A.Z Dynamics in Response to Environmental Changes.

DNA methylation and posttranslational modifications of histones instruct gene expression in eukaryotes. Besides canonical histones, histone variants also play a critical role in transcriptional regulation. One of the best studied histone variants in plants is H2A.Z whose removal from gene bodies correlates with increased transcriptional activity. The eviction of H2A.Z is regulated by environmental cues such as increased ambient temperatures, and current models suggest that H2A.Z functions as a transcriptional buffer preventing environmentally responsive genes from undesired activation. To monitor temperature-dependent H2A.Z dynamics, chromatin immunoprecipitation (ChIP) of H2A.Z-occupied DNA can be performed. The following protocol describes a quick and easy ChIP approach to study in vivo H2A.Z occupancy.

Using Cleavage Under Targets and Tagmentation (CUT&Tag) Assay in Mouse Myoblast Research.

This protocol paper aims to provide the new researchers with the full details of using Cleavage Under Targets and Tagmentation (CUT&Tag) to profile the genomic locations of chromatin binding factors, histone marks, and histone variants. CUT&Tag protocols function very well with mouse myoblasts and freshly isolated muscle stem cells (MuSCs). They can easily be applied to many other cell types as long as the cells can be immobilized by Concanavalin-A beads. Compared to CUT&Tag, chromatin immunoprecipitation (ChIP) assays are time-consuming experiments. ChIP assays require the pre-treatment of chromatin before the chromatic material can be used for immunoprecipitation. In cross-linking ChIP (X-ChIP), pre-treatment of chromatin involves cross-linking and sonication to fragment the chromatin. In the case of native ChIP (N-ChIP), the fragmented chromatins are normally achieved by Micrococcal nuclease (MNase) digestion. Both sonication and MNase digestion introduce some bias to the ChIP experiments. CUT&Tag assays can be finished within fewer steps and require much fewer cells compared to ChIPs but provide more unbiased information on transcription factors or histone marks at various genomic locations. CUT&Tag can function with as few as 5,000 cells. Due to its higher sensitivity and lower background signal than ChIPs, researchers can expect to obtain reliable peak data from merely several millions of reads after sequencing.

BIOMAPP::CHIP: large-scale motif analysis.

BACKGROUND: Discovery biological motifs plays a fundamental role in understanding regulatory mechanisms. Computationally, they can be efficiently represented as kmers, making the counting of these elements a critical aspect for ensuring not only the accuracy but also the efficiency of the analytical process. This is particularly useful in scenarios involving large data volumes, such as those generated by the ChIP-seq protocol. Against this backdrop, we introduce BIOMAPP::CHIP, a tool specifically designed to optimize the discovery of biological motifs in large data volumes. RESULTS: We conducted a comprehensive set of comparative tests with state-of-the-art algorithms. Our analyses revealed that BIOMAPP::CHIP outperforms existing approaches in various metrics, excelling both in terms of performance and accuracy. The tests demonstrated a higher detection rate of significant motifs and also greater agility in the execution of the algorithm. Furthermore, the SMT component played a vital role in the system's efficiency, proving to be both agile and accurate in kmer counting, which in turn improved the overall efficacy of our tool. CONCLUSION: BIOMAPP::CHIP represent real advancements in the discovery of biological motifs, particularly in large data volume scenarios, offering a relevant alternative for the analysis of ChIP-seq data and have the potential to boost future research in the field. This software can be found at the following address: (https://github.com/jadermcg/biomapp-chip).

IFI16 Is Indispensable for Promoting HIF-1α-Mediated APOL1 Expression in Human Podocytes under Hypoxic Conditions.

Genetic variants in the protein-coding regions of APOL1 are associated with an increased risk and progression of chronic kidney disease (CKD) in African Americans. Hypoxia exacerbates CKD progression by stabilizing HIF-1α, which induces APOL1 transcription in kidney podocytes. However, the contribution of additional mediators to regulating APOL1 expression under hypoxia in podocytes is unknown. Here, we report that a transient accumulation of HIF-1α in hypoxia is sufficient to upregulate APOL1 expression in podocytes through a cGAS/STING/IRF3-independent pathway. Notably, IFI16 ablation impedes hypoxia-driven APOL1 expression despite the nuclear accumulation of HIF-1α. Co-immunoprecipitation assays indicate no direct interaction between IFI16 and HIF-1α. Our studies identify hypoxia response elements (HREs) in the APOL1 gene enhancer/promoter region, showing increased HIF-1α binding to HREs located in the APOL1 gene enhancer. Luciferase reporter assays confirm the role of these HREs in transcriptional activation. Chromatin immunoprecipitation (ChIP)-qPCR assays demonstrate that IFI16 is not recruited to HREs, and IFI16 deletion reduces HIF-1α binding to APOL1 HREs. RT-qPCR analysis indicates that IFI16 selectively affects APOL1 expression, with a negligible impact on other hypoxia-responsive genes in podocytes. These findings highlight the unique contribution of IFI16 to hypoxia-driven APOL1 gene expression and suggest alternative IFI16-dependent mechanisms regulating APOL1 gene expression under hypoxic conditions.

Aberrant H3K4me3 modification of immune response genes in CD4+ T cells of patients with systemic lupus erythematosus.

BACKGROUND: Increasing evidence has highlighted the significant role of histone modifications in pathogenesis of systemic lupus erythematosus (SLE). However, few studies have comprehensively analyzed trimethylation of histone H3 lysine 4 (H3K4me3) features at specific immune gene loci in SLE patients. METHODS: We conducted H3K4me3 chromatin immunoprecipitation sequencing (ChIP-seq) on CD4+ T cells from SLE patients and healthy controls (HC). Differential H3K4me3 peaks were identified, followed by enrichment analysis. We integrated online RNA-seq and DNA methylation datasets to explore the relationship between H3K4me3 modification, DNA methylation and gene expression. We validated several upregulated peak regions by ChIP-qPCR and confirmed their impact on gene expression using RT-qPCR. Finally, we investigated the impact of H3K4 methyltransferases KMT2A on the expression of immune response genes. RESULTS: we identified 147 downregulated and 2701 upregulated H3K4me3 peaks in CD4+ T cells of SLE. The upregulated peaks primarily classified as gained peaks and enriched in immune response genes such as FCGR2A, C5AR1, SERPING1 and OASL. Genes with upregulated H3K4me3 and downregulated DNA methylations in the promoter were highly expressed in SLE patients. These genes, including OAS1, IFI27 and IFI44L, were enriched in immune response pathways. The IFI44L locus also showed increased H3K27ac modification, chromatin accessibility and chromatin interactions in SLE. Moreover, knockdown of KMT2A can downregulate the expression of immune response genes in T cells. CONCLUSION: Our study uncovers dysregulated H3K4me3 modification patterns in immune response genes loci, which also exhibit downregulated DNA methylation and higher mRNA expression in CD4+ T cells of SLE patients.

E2F1 promotes cell migration in hepatocellular carcinoma via FNDC3B.

FNDC3B (fibronectin type III domain containing 3B) is highly expressed in hepatocellular carcinoma (HCC) and other cancer types, and fusion genes involving FNDC3B have been identified in HCC and leukemia. Growing evidence suggests the significance of FNDC3B in tumorigenesis, particularly in cell migration and tumor metastasis. However, its regulatory mechanisms remain elusive. In this study, we employed bioinformatic, gene regulation, and protein-DNA interaction screening to investigate the transcription factors (TFs) involved in regulating FNDC3B. Initially, 338 candidate TFs were selected based on previous chromatin immunoprecipitation (ChIP)-seq experiments available in public domain databases. Through TF knockdown screening and ChIP coupled with Droplet Digital PCR assays, we identified that E2F1 (E2F transcription factor 1) is crucial for the activation of FNDC3B. Overexpression or knockdown of E2F1 significantly impacts the expression of FNDC3B. In conclusion, our study elucidated the mechanistic link between FNDC3B and E2F1. These findings contribute to a better understanding of FNDC3B in tumorigenesis and provide insights into potential therapeutic targets for cancer treatment.

A low-input high resolution sequential chromatin immunoprecipitation method captures genome-wide dynamics of bivalent chromatin.

BACKGROUND: Bivalent chromatin is an exemplar of epigenetic plasticity. This co-occurrence of active-associated H3K4me3 and inactive-associated H3K27me3 histone modifications on opposite tails of the same nucleosome occurs predominantly at promoters that are poised for future transcriptional upregulation or terminal silencing. We know little of the dynamics, resolution, and regulation of this chromatin state outside of embryonic stem cells where it was first described. This is partly due to the technical challenges distinguishing bone-fide bivalent chromatin, where both marks are on the same nucleosome, from allelic or sample heterogeneity where there is a mix of H3K4me3-only and H3K27me3-only mononucleosomes. RESULTS: Here, we present a robust and sensitive method to accurately map bivalent chromatin genome-wide, along with controls, from as little as 2 million cells. We optimized and refined the sequential ChIP protocol which uses two sequential overnight immunoprecipitation reactions to robustly purify nucleosomes that are truly bivalent and contain both H3K4me3 and H3K27me3 modifications. Our method generates high quality genome-wide maps with strong peak enrichment and low background, which can be analyzed using standard bioinformatic packages. Using this method, we detect 8,789 bivalent regions in mouse embryonic stem cells corresponding to 3,918 predominantly CpG rich and developmentally regulated gene promoters. Furthermore, profiling Dppa2/4 knockout mouse embryonic stem cells, which lose both H3K4me3 and H3K27me3 at approximately 10% of bivalent promoters, demonstrated the ability of our method to capture bivalent chromatin dynamics. CONCLUSIONS: Our optimized sequential reChIP method enables high-resolution genome-wide assessment of bivalent chromatin together with all required controls in as little as 2 million cells. We share a detailed protocol and guidelines that will enable bivalent chromatin landscapes to be generated in a range of cellular contexts, greatly enhancing our understanding of bivalent chromatin and epigenetic plasticity beyond embryonic stem cells.

Pycallingcards: an integrated environment for visualizing, analyzing, and interpreting Calling Cards data.

MOTIVATION: Unraveling the transcriptional programs that control how cells divide, differentiate, and respond to their environments requires a precise understanding of transcription factors' (TFs) DNA-binding activities. Calling cards (CC) technology uses transposons to capture transient TF binding events at one instant in time and then read them out at a later time. This methodology can also be used to simultaneously measure TF binding and mRNA expression from single-cell CC and to record and integrate TF binding events across time in any cell type of interest without the need for purification. Despite these advantages, there has been a lack of dedicated bioinformatics tools for the detailed analysis of CC data. RESULTS: We introduce Pycallingcards, a comprehensive Python module specifically designed for the analysis of single-cell and bulk CC data across multiple species. Pycallingcards introduces two innovative peak callers, CCcaller and MACCs, enhancing the accuracy and speed of pinpointing TF binding sites from CC data. Pycallingcards offers a fully integrated environment for data visualization, motif finding, and comparative analysis with RNA-seq and ChIP-seq datasets. To illustrate its practical application, we have reanalyzed previously published mouse cortex and glioblastoma datasets. This analysis revealed novel cell-type-specific binding sites and potential sex-linked TF regulators, furthering our understanding of TF binding and gene expression relationships. Thus, Pycallingcards, with its user-friendly design and seamless interface with the Python data science ecosystem, stands as a critical tool for advancing the analysis of TF functions via CC data. AVAILABILITY AND IMPLEMENTATION: Pycallingcards can be accessed on the GitHub repository: https://github.com/The-Mitra-Lab/pycallingcards.

ROS in diabetic atria regulate SK2 degradation by Atrogin-1 through the NF-κB signaling pathway.

One of the independent risk factors for atrial fibrillation is diabetes mellitus (DM); however, the underlying mechanisms causing atrial fibrillation in DM are unknown. The underlying mechanism of Atrogin-1-mediated SK2 degradation and associated signaling pathways are unclear. The aim of this study was to elucidate the relationship among reactive oxygen species (ROS), the NF-κB signaling pathway, and Atrogin-1 protein expression in the atrial myocardia of DM mice. We found that SK2 expression was downregulated comitant with increased ROS generation and enhanced NF-κB signaling activation in the atrial cardiomyocytes of DM mice. These observations were mimicked by exogenously applicating H2O2 and by high glucose culture conditions in HL-1 cells. Inhibition of ROS production by diphenyleneiodonium chloride or silencing of NF-κB by siRNA decreased the protein expression of NF-κB and Atrogin-1 and increased that of SK2 in HL-1 cells with high glucose culture. Moreover, chromatin immunoprecipitation assay demonstrated that NF-κB/p65 directly binds to the promoter of the FBXO32 gene (encoding Atrogin-1), regulating the FBXO32 transcription. Finally, we evaluated the therapeutic effects of curcumin, known as a NF-κB inhibitor, on Atrogin-1 and SK2 expression in DM mice and confirmed that oral administration of curcumin for 4 weeks significantly suppressed Atrogin-1 expression and protected SK2 expression against hyperglycemia. In summary, the results from this study indicated that the ROS/NF-κB signaling pathway participates in Atrogin-1-mediated SK2 regulation in the atria of streptozotocin-induced DM mice.

ChIP-GPT: a managed large language model for robust data extraction from biomedical database records.

Increasing volumes of biomedical data are amassing in databases. Large-scale analyses of these data have wide-ranging applications in biology and medicine. Such analyses require tools to characterize and process entries at scale. However, existing tools, mainly centered on extracting predefined fields, often fail to comprehensively process database entries or correct evident errors-a task humans can easily perform. These tools also lack the ability to reason like domain experts, hindering their robustness and analytical depth. Recent advances with large language models (LLMs) provide a fundamentally new way to query databases. But while a tool such as ChatGPT is adept at answering questions about manually input records, challenges arise when scaling up this process. First, interactions with the LLM need to be automated. Second, limitations on input length may require a record pruning or summarization pre-processing step. Third, to behave reliably as desired, the LLM needs either well-designed, short, 'few-shot' examples, or fine-tuning based on a larger set of well-curated examples. Here, we report ChIP-GPT, based on fine-tuning of the generative pre-trained transformer (GPT) model Llama and on a program prompting the model iteratively and handling its generation of answer text. This model is designed to extract metadata from the Sequence Read Archive, emphasizing the identification of chromatin immunoprecipitation (ChIP) targets and cell lines. When trained with 100 examples, ChIP-GPT demonstrates 90-94% accuracy. Notably, it can seamlessly extract data from records with typos or absent field labels. Our proposed method is easily adaptable to customized questions and different databases.

NOTCH localizes to mitochondria through the TBC1D15-FIS1 interaction and is stabilized via blockade of E3 ligase and CDK8 recruitment to reprogram tumor-initiating cells.

The P53-destabilizing TBC1D15-NOTCH protein interaction promotes self-renewal of tumor-initiating stem-like cells (TICs); however, the mechanisms governing the regulation of this pathway have not been fully elucidated. Here, we show that TBC1D15 stabilizes NOTCH and c-JUN through blockade of E3 ligase and CDK8 recruitment to phosphodegron sequences. Chromatin immunoprecipitation (ChIP-seq) analysis was performed to determine whether TBC1D15-dependent NOTCH1 binding occurs in TICs or non-TICs. The TIC population was isolated to evaluate TBC1D15-dependent NOTCH1 stabilization mechanisms. The tumor incidence in hepatocyte-specific triple knockout (Alb::CreERT2;Tbc1d15Flox/Flox;Notch1Flox/Flox;Notch2Flox/Flox;HCV-NS5A) Transgenic (Tg) mice and wild-type mice was compared after being fed an alcohol-containing Western diet (WD) for 12 months. The NOTCH1-TBC1D15-FIS1 interaction resulted in recruitment of mitochondria to the perinuclear region. TBC1D15 bound to full-length NUMB and to NUMB isoform 5, which lacks three Ser phosphorylation sites, and relocalized NUMB5 to mitochondria. TBC1D15 binding to NOTCH1 blocked CDK8- and CDK19-mediated phosphorylation of the NOTCH1 PEST phosphodegron to block FBW7 recruitment to Thr-2512 of NOTCH1. ChIP-seq analysis revealed that TBC1D15 and NOTCH1 regulated the expression of genes involved in mitochondrial metabolism-related pathways required for the maintenance of TICs. TBC1D15 inhibited CDK8-mediated phosphorylation to stabilize NOTCH1 and protect it from degradation The NUMB-binding oncoprotein TBC1D15 rescued NOTCH1 from NUMB-mediated ubiquitin-dependent degradation and recruited NOTCH1 to the mitochondrial outer membrane for the generation and expansion of liver TICs. A NOTCH-TBC1D15 inhibitor was found to inhibit NOTCH-dependent pathways and exhibited potent therapeutic effects in PDX mouse models. This unique targeting of the NOTCH-TBC1D15 interaction not only normalized the perinuclear localization of mitochondria but also promoted potent cytotoxic effects against TICs to eradicate patient-derived xenografts through NOTCH-dependent pathways.

ChIP-Seq analysis reveals PRKACB as a target gene of HOXC13 involved in rabbit hair follicle development.

Dermal papilla cells (DPCs) are key regulators of hair follicle (HF) development and growth, which not only regulate HF growth and cycling but play a role in the pathogenesis of hair loss. The transcription factor Homeobox C13 (HOXC13) can modulate the growth and development of HFs. Nevertheless, the specific genes and pathways regulated by HOXC13 in DPCs have yet to be determined. Thus, to gain a better understanding of genomic binding sites involved in HOXC13-regulated HF development, chromatin immunoprecipitation followed by high throughput sequencing (ChIP-Seq) was performed on rabbit DPCs with pcDNA3.1-3 × Flag-HOXC13 overexpression. A complete set of 9670 enrichment peaks was acquired by applying HOXC13-Flag ChIP. Subsequently, the peak sequence was annotated to the rabbit genome, revealing that 6.1 % of the peaks were identified within in the promoter region. Thereafter, five annotated genes were verified using RT-qPCR. The peak-associated genes were mainly enriched in signaling pathways related to HF development, such as MAPK and PI3K-Akt. Furthermore, by using a dual-luciferase reporter assay, we found that HOXC13 can target the protein kinase cAMP­dependent catalytic ß (PRKACB) promoter region (-1596 âˆ¼ -1107 bp) and inhibit its transcription, which was consistent with data obtained from ChIP-seq analysis. Overexpression of PRKACB gene significantly modulated the expression of BCL2, WNT2, LEF1, and SFRP2 genes related to HF development as determined by RT-qPCR (P < 0.01, P < 0.05). The CCK-8 and flow cytometry assays showed that PRKACB significantly inhibited the proliferation of DPCs and promoted apoptosis (P < 0.01). In conclusion, our research revealed that PRKACB has the potential to serve as a novel target gene of HOXC13, contributing to the regulation of the proliferation and apoptosis of DPCs. The process of identifying global target genes can contribute to the understanding of the intricate pathways that HOXC13 regulates in the growth of HFs.

Transcriptional programming of translation by BCL6 controls skeletal muscle proteostasis.

Skeletal muscle is dynamically controlled by the balance of protein synthesis and degradation. Here we discover an unexpected function for the transcriptional repressor B cell lymphoma 6 (BCL6) in muscle proteostasis and strength in mice. Skeletal muscle-specific Bcl6 ablation in utero or in adult mice results in over 30% decreased muscle mass and force production due to reduced protein synthesis and increased autophagy, while it promotes a shift to a slower myosin heavy chain fibre profile. Ribosome profiling reveals reduced overall translation efficiency in Bcl6-ablated muscles. Mechanistically, tandem chromatin immunoprecipitation, transcriptomic and translational analyses identify direct BCL6 repression of eukaryotic translation initiation factor 4E-binding protein 1 (Eif4ebp1) and activation of insulin-like growth factor 1 (Igf1) and androgen receptor (Ar). Together, these results uncover a bifunctional role for BCL6 in the transcriptional and translational control of muscle proteostasis.

Less-is-more: selecting transcription factor binding regions informative for motif inference.

Numerous statistical methods have emerged for inferring DNA motifs for transcription factors (TFs) from genomic regions. However, the process of selecting informative regions for motif inference remains understudied. Current approaches select regions with strong ChIP-seq signal for a given TF, assuming that such strong signal primarily results from specific interactions between the TF and its motif. Additionally, these selection approaches do not account for non-target motifs, i.e. motifs of other TFs; they presume the occurrence of these non-target motifs infrequent compared to that of the target motif, and thus assume these have minimal interference with the identification of the target. Leveraging extensive ChIP-seq datasets, we introduced the concept of TF signal 'crowdedness', referred to as C-score, for each genomic region. The C-score helps in highlighting TF signals arising from non-specific interactions. Moreover, by considering the C-score (and adjusting for the length of genomic regions), we can effectively mitigate interference of non-target motifs. Using these tools, we find that in many instances, strong ChIP-seq signal stems mainly from non-specific interactions, and the occurrence of non-target motifs significantly impacts the accurate inference of the target motif. Prioritizing genomic regions with reduced crowdedness and short length markedly improves motif inference. This 'less-is-more' effect suggests that ChIP-seq region selection warrants more attention.

LINC01852 inhibits the tumorigenesis and chemoresistance in colorectal cancer by suppressing SRSF5-mediated alternative splicing of PKM.

BACKGROUND: Colorectal cancer (CRC) is a major cause of cancer-related deaths worldwide, and chemoresistance is a major obstacle in its treatment. Despite advances in therapy, the molecular mechanism underlying chemoresistance in CRC is not fully understood. Recent studies have implicated the key roles of long noncoding RNAs (lncRNAs) in the regulation of CRC chemoresistance. METHODS: In this study, we investigated the role of the lncRNA LINC01852 in CRC chemoresistance. LINC01852 expression was evaluated in multiple CRC cohorts using quantitative reverse transcription PCR. We conducted in vitro and in vivo functional experiments using cell culture and mouse models. RNA pull-down, RNA immunoprecipitation, chromatin immunoprecipitation, and dual luciferase assays were used to investigate the molecular mechanism of LINC01852 in CRC. RESULTS: Our findings revealed that a lncRNA with tumor-inhibiting properties, LINC01852, was downregulated in CRC and inhibited cell proliferation and chemoresistance both in vitro and in vivo. Further mechanistic investigations revealed that LINC01852 increases TRIM72-mediated ubiquitination and degradation of SRSF5, inhibiting SRSF5-mediated alternative splicing of PKM and thereby decreasing the production of PKM2. Overexpression of LINC01852 induces a metabolic switch from aerobic glycolysis to oxidative phosphorylation, which attenuates the chemoresistance of CRC cells by inhibiting PKM2-mediated glycolysis. CONCLUSIONS: Our results demonstrate that LINC01852 plays an important role in repressing CRC malignancy and chemoresistance by regulating SRSF5-mediated alternative splicing of PKM, and that targeting the LINC01852/TRIM72/SRSF5/PKM2 signaling axis may represent a potential therapeutic strategy for CRC.

MMCT-Loop: a mix model-based pipeline for calling targeted 3D chromatin loops.

Protein-specific Chromatin Conformation Capture (3C)-based technologies have become essential for identifying distal genomic interactions with critical roles in gene regulation. The standard techniques include Chromatin Interaction Analysis by Paired-End Tag (ChIA-PET), in situ Hi-C followed by chromatin immunoprecipitation (HiChIP) also known as PLAC-seq. To identify chromatin interactions from these data, a variety of computational methods have emerged. Although these state-of-art methods address many issues with loop calling, only few methods can fit different data types simultaneously, and the accuracy as well as the efficiency these approaches remains limited. Here we have generated a pipeline, MMCT-Loop, which ensures the accurate identification of strong loops as well as dynamic or weak loops through a mixed model. MMCT-Loop outperforms existing methods in accuracy, and the detected loops show higher activation functionality. To highlight the utility of MMCT-Loop, we applied it to conformational data derived from neural stem cell (NSCs) and uncovered several previously unidentified regulatory regions for key master regulators of stem cell identity. MMCT-Loop is an accurate and efficient loop caller for targeted conformation capture data, which supports raw data or pre-processed valid pairs as input, the output interactions are formatted and easily uploaded to a genome browser for visualization.

GSDMD suppresses keratinocyte differentiation by inhibiting FLG expression and attenuating KCTD6-mediated HDAC1 degradation in atopic dermatitis.

Background: Recent studies have shown that activated pyroptosis in atopic dermatitis (AD) switches inflammatory processes and causes abnormal cornification and epidermal barrier dysfunction. Little research has focused on the interaction mechanism between pyroptosis-related genes and human keratinocyte differentiation. Methods: The AD dataset from the Gene Expression Omnibus (GEO) was used to identify differently expressed pyroptosis-related genes (DEPRGs). Hub genes were identified and an enrichment analysis was performed to select epithelial development-related genes. Lesions of AD patients were detected via immunohistochemistry (IHC) to verify the hub gene. Human keratinocytes cell lines, gasdermin D (GSDMD) overexpression, Caspase1 siRNA, Histone Deacetylase1 (HDAC1) siRNA, and HDAC1 overexpression vectors were used for gain-and-loss-of-function experiments. Regulation of cornification protein was determined by qPCR, western blot (WB), immunofluorescence (IF), dual-luciferase reporter assay, co-immunoprecipitation (Co-IP), and chromatin immunoprecipitation (ChIP). Results: A total of 27 DEPRGs were identified between either atopic dermatitis non-lesional skin (ANL) and healthy control (HC) or atopic dermatitis lesional skin (AL) and HC. The enrichment analysis showed that these DEPRGs were primarily enriched in the inflammatory response and keratinocytes differentiation. Of the 10 hub genes identified via the protein-protein interaction network, only GSDMD was statistically and negatively associated with the expression of epithelial tight junction core genes. Furthermore, GSDMD was upregulated in AD lesions and inhibited human keratinocyte differentiation by reducing filaggrin (FLG) expression. Mechanistically, GSDMD activated by Caspase1 reduced FLG expression via HDAC1. HDAC1 decreased FLG expression by reducing histone acetylation at the FLG promoter. In addition, GSDMD blocked the interaction of Potassium Channel Tetramerization Domain Containing 6 (KCTD6) and HDAC1 to prohibit HDAC1 degradation. Conclusion: This study revealed that GSDMD was upregulated in AD lesions and that GSDMD regulated keratinocytes via epigenetic modification, which might provide potential therapeutic targets for AD.

Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks.

Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) is a central genome-wide method for in vivo analyses of DNA-protein interactions in various cellular conditions. Numerous studies have demonstrated the complex contextual organization of ChIP-seq peak sequences and the presence of binding sites for transcription factors in them. We assessed the dependence of the ChIP-seq peak score on the presence of different contextual signals in the peak sequences by analyzing these sequences from several ChIP-seq experiments using our fully enumerative GPU-based de novo motif discovery method, Argo_CUDA. Analysis revealed sets of significant IUPAC motifs corresponding to the binding sites of the target and partner transcription factors. For these ChIP-seq experiments, multiple regression models were constructed, demonstrating a significant dependence of the peak scores on the presence in the peak sequences of not only highly significant target motifs but also less significant motifs corresponding to the binding sites of the partner transcription factors. A significant correlation was shown between the presence of the target motifs FOXA2 and the partner motifs HNF4G, which found experimental confirmation in the scientific literature, demonstrating the important contribution of the partner transcription factors to the binding of the target transcription factor to DNA and, consequently, their important contribution to the peak score.

The promotive role of lncRNA MIR205HG in proliferation, invasion, and migration of melanoma cells via the JMJD2C/ALKBH5 axis.

Melanoma is a highly malignant skin cancer. This study aimed to investigate the role of long non-coding RNA MIR205 host gene (lncRNA MIR205HG) in proliferation, invasion, and migration of melanoma cells via jumonji domain containing 2C (JMJD2C) and ALKB homolog 5 (ALKBH5). Real-time quantitative polymerase chain reaction or Western blot assay showed that MIR205HG, JMJD2C, and ALKBH5 were increased in melanoma cell lines. Cell counting kit-8, colony formation, and Transwell assays showed that silencing MIR205HG inhibited proliferation, invasion, and migration of melanoma cells. RNA immunoprecipitation, actinomycin D treatment, and chromatin immunoprecipitation showed that MIR205HG may bind to human antigen R (HuR, ELAVL1) and stabilized JMJD2C expression, and JMJD2C may increase the enrichment of H3K9me3 in the ALKBH5 promotor region to promote ALKBH5 transcription. The tumor xenograft assay based on subcutaneous injection of sh-MIR205HG-treated melanoma cells showed that silencing MIR205HG suppressed tumor growth and reduced Ki67 positive rate by inactivating the JMJD2C/ALKBH5 axis. Generally, MIR205HG facilitated proliferation, invasion, and migration of melanoma cells through HuR-mediated stabilization of JMJD2C and increasing ALKBH5 transcription by erasing H3K9me3.

Combinatorial single-cell profiling of major chromatin types with MAbID.

Gene expression programs result from the collective activity of numerous regulatory factors. Studying their cooperative mode of action is imperative to understand gene regulation, but simultaneously measuring these factors within one sample has been challenging. Here we introduce Multiplexing Antibodies by barcode Identification (MAbID), a method for combinatorial genomic profiling of histone modifications and chromatin-binding proteins. MAbID employs antibody-DNA conjugates to integrate barcodes at the genomic location of the epitope, enabling combined incubation of multiple antibodies to reveal the distributions of many epigenetic markers simultaneously. We used MAbID to profile major chromatin types and multiplexed measurements without loss of individual data quality. Moreover, we obtained joint measurements of six epitopes in single cells of mouse bone marrow and during mouse in vitro differentiation, capturing associated changes in multifactorial chromatin states. Thus, MAbID holds the potential to gain unique insights into the interplay between gene regulatory mechanisms, especially for low-input samples and in single cells.