Interaction Of Transcription Factors Research Articles

A comparative analysis of ENCODE and Cistrome in the context of TF binding signal

BackgroundWith the rise of publicly available genomic data repositories, it is now common for scientists to rely on computational models and preprocessed data, either as control or to discover new knowledge. However, different repositories adhere to the different principles and guidelines, and data processing plays a significant role in the quality of the resulting datasets. Two popular repositories for transcription factor binding sites data - ENCODE and Cistrome - process the same biological samples in alternative ways, and their results are not always consistent. Moreover, the output format of the processing (BED narrowPeak) exposes a feature, the signalValue, which is seldom used in consistency checks, but can offer valuable insight on the quality of the data.ResultsWe provide evidence that data points with high signalValue(s) (top 25% of values) are more likely to be consistent between ENCODE and Cistrome in human cell lines K562, GM12878, and HepG2. In addition, we show that filtering according to said high values improves the quality of predictions for a machine learning algorithm that detects transcription factor interactions based only on positional information. Finally, we provide a set of practices and guidelines, based on the signalValue feature, for scientists who wish to compare and merge narrowPeaks from ENCODE and Cistrome.ConclusionsThe signalValue feature is an informative feature that can be effectively used to highlight consistent areas of overlap between different sources of TF binding sites that expose it. Its applicability extends to downstream to positional machine learning algorithms, making it a powerful tool for performance tweaking and data aggregation.

Ripening and rot: How ripening processes influence disease susceptibility in fleshy fruits.

Fleshy fruits become more susceptible to pathogen infection when they ripen; for example, changes in cell wall properties related to softening make it easier for pathogens to infect fruits. The need for high-quality fruit has driven extensive research on improving pathogen resistance in important fruit crops such as tomato (Solanum lycopersicum). In this review, we summarize current progress in understanding how changes in fruit properties during ripening affect infection by pathogens. These changes affect physical barriers that limit pathogen entry, such as the fruit epidermis and its cuticle, along with other defenses that limit pathogen growth, such as preformed and induced defense compounds. The plant immune system also protects ripening fruit by recognizing pathogens and initiating defense responses involving reactive oxygen species production, mitogen-activated protein kinase signaling cascades, and jasmonic acid, salicylic acid, ethylene, and abscisic acid signaling. These phytohormones regulate an intricate web of transcription factors (TFs) that activate resistance mechanisms, including the expression of pathogenesis-related genes. In tomato, ripening regulators, such as RIPENING INHIBITOR and NON_RIPENING, not only regulate ripening but also influence fruit defenses against pathogens. Moreover, members of the ETHYLENE RESPONSE FACTOR (ERF) family play pivotal and distinct roles in ripening and defense, with different members being regulated by different phytohormones. We also discuss the interaction of ripening-related and defense-related TFs with the Mediator transcription complex. As the ripening processes in climacteric and non-climacteric fruits share many similarities, these processes have broad applications across fruiting crops. Further research on the individual contributions of ERFs and other TFs will inform efforts to diminish disease susceptibility in ripe fruit, satisfy the growing demand for high-quality fruit and decrease food waste and related economic losses.

RNA Binding Properties of SOX Family Members.

SOX proteins are a family of transcription factors (TFs) that play critical functions in sex determination, neurogenesis, and chondrocyte differentiation, as well as cardiac, vascular, and lymphatic development. There are 20 SOX family members in humans, each sharing a 79-residue L-shaped high mobility group (HMG)-box domain that is responsible for DNA binding. SOX2 was recently shown to interact with long non-coding RNA and large-intergenic non-coding RNA to regulate embryonic stem cell and neuronal differentiation. The RNA binding region was shown to reside within the HMG-box domain; however, the structural details of this binding remain unclear. Here, we show that all SOX family members, except group H, interact with RNA. Our mutational experiments demonstrate that the disordered C-terminal region of the HMG-box domain plays an important role in RNA binding. Further, by determining a high-resolution structure of the HMG-box domain of the group H family member SOX30, we show that despite differences in RNA binding ability, SOX30 shares a very similar secondary structure with other SOX protein HMG-box domains. Together, our study provides insight into the interaction of SOX TFs with RNA.

Identification of Potential Biomarkers for Patients with DWI-Negative Ischemic Stroke

Ischemic stroke is the leading cause of long-term disability in adults, accounting for 80% of stroke cases. Diffusion weighted imaging (DWI) examination is the main test for acute ischemic stroke, but in recent years, several studies have shown that some patients show negative DWI examination after the onset of ischemic stroke with symptoms of significant neurological deficits. In this study, we investigated potential biomarkers related to immune metabolism in the peripheral blood of DWI-negative versus DWI-positive patients after ischemic stroke and explored their possible regulatory processes in ischemic stroke. The datasets related to ischemic stroke were downloaded from the GEO database, immune-related genes and metabolism-related genes were obtained from the ImmPort database and MSigDB database, respectively, and immune-related differential genes were obtained based on immune scores using the algorithm of the R software package “GSVA.” Candidate genes were selected based on intersections, hub genes were screened using the algorithm in Cytoscape software, and finally, GeneMANIA analysis, GSEA enrichment analysis, subcellular localization, gene transcription factor and gene-drug interaction networks, and disease correlation analyses were performed for the hub genes. Five hub genes (GART, TYMS, PPAT, CTPS1, and PAICS) were obtained by PPI network analysis and software analysis. Among them, PPAT and PAICS may be the real hub genes with consistent and significantly differentiated results from the discovery and validation sets. The functions of these hub genes may be related to pathways such as nucleotide biosynthetic processes. The constructed hub gene ceRNA network showed that hsa-10a-5p is the key miRNA connecting PAICS and multiple lncRNAs in this study. Differential genes related to immunity and metabolism in DWI-negative and DWI-positive patients after IS were identified using bioinformatics analysis, and their pathways and related TF-RNAs, miRNAs, and lncRNAs were identified. These genes may be considered effective targets for the diagnosis and treatment of ischemic stroke.

GET: a foundation model of transcription across human cell types.

Transcriptional regulation, involving the complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate in unseen cell types and conditions. Here, we introduce GET, an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types. Relying exclusively on chromatin accessibility data and sequence information, GET achieves experimental-level accuracy in predicting gene expression even in previously unseen cell types. GET showcases remarkable adaptability across new sequencing platforms and assays, enabling regulatory inference across a broad range of cell types and conditions, and uncovering universal and cell type specific transcription factor interaction networks. We evaluated its performance on prediction of regulatory activity, inference of regulatory elements and regulators, and identification of physical interactions between transcription factors. Specifically, we show GET outperforms current models in predicting lentivirus-based massive parallel reporter assay readout with reduced input data. In fetal erythroblasts, we identify distal (>1Mbp) regulatory regions that were missed by previous models. In B cells, we identified a lymphocyte-specific transcription factor-transcription factor interaction that explains the functional significance of a leukemia-risk predisposing germline mutation. In sum, we provide a generalizable and accurate model for transcription together with catalogs of gene regulation and transcription factor interactions, all with cell type specificity.

REEP3 is a potential diagnostic and prognostic biomarker correlated with immune infiltration in pancreatic cancer

Receptor Expression-Enhancing Protein 3 (REEP3) serves as a pivotal enzyme crucial for endoplasmic reticulum (ER) clearance during mitosis and is implicated in the advancement of diverse malignancies. Nonetheless, the biological role and mechanisms of REEP3 in pancreatic cancer patients, along with its interplay with immune infiltration, remain inadequately elucidated. In this study, we initially analyzed the differential expression of REEP3 between pancreatic cancer tissues and normal pancreas tissues using the Cancer Genome Atlas (TCGA), GTEx and Gene Expression Omnibus (GEO) databases. Subsequently, we utilized Kaplan–Meier analysis, Cox regression and ROC curve to determine the predictive value of REEP3 for the clinical outcomes of pancreatic cancer patients. Functional enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA), were conducted to explore the potential signaling pathways and biological functions associated with pancreatic cancer. Furthermore, we investigated the PPI network, miRNA, RBP and transcription factor interactions of REEP3 using databases such as GeneMania, STRING, StarBase, KnockTK, ENCODE, Jaspar and hTFtarget. Lastly, the “ssGSEA” algorithm and TIMER database were employed to investigate the correlation between REEP3 expression and immune infiltration as well as immune checkpoints. The expression of REEP3 in pancreatic cancer showed a significantly higher level compared to that in normal tissues. ROC curve analysis indicated that REEP3 holds substantial diagnostic potential for pancreatic cancer patients. Elevated REEP3 expression correlated with unfavorable outcomes in terms of both overall survival and relapse-free survival, establishing it as a notable adverse prognostic marker in pancreatic cancer. Moreover, both univariate and multivariate Cox regression analyses demonstrated that REEP3 maintained an independent association with overall survival. Functional enrichment analyses revealed pathways significantly linked to REEP3, including cytoplasmic translation, wound healing, viral processes, regulation of cellular component size and actin filament organization. Additionally, REEP3 expression displayed a significant positive correlation with CD8+ T cells, B cells, natural killer cells, dendritic cells and macrophages. REEP3 is a potential diagnostic, prognostic marker and immunotherapeutic target for pancreatic cancer.

Gene regulatory network topology governs resistance and treatment escape in glioma stem-like cells.

Poor prognosis and drug resistance in glioblastoma (GBM) can result from cellular heterogeneity and treatment-induced shifts in phenotypic states of tumor cells, including dedifferentiation into glioma stem-like cells (GSCs). This rare tumorigenic cell subpopulation resists temozolomide, undergoes proneural-to-mesenchymal transition (PMT) to evade therapy, and drives recurrence. Through inference of transcriptional regulatory networks (TRNs) of patient-derived GSCs (PD-GSCs) at single-cell resolution, we demonstrate how the topology of transcription factor interaction networks drives distinct trajectories of cell-state transitions in PD-GSCs resistant or susceptible to cytotoxic drug treatment. By experimentally testing predictions based on TRN simulations, we show that drug treatment drives surviving PD-GSCs along a trajectory of intermediate states, exposing vulnerability to potentiated killing by siRNA or a second drug targeting treatment-induced transcriptional programs governing nongenetic cell plasticity. Our findings demonstrate an approach to uncover TRN topology and use it to rationally predict combinatorial treatments that disrupt acquired resistance in GBM.

Mapping putative enhancers in mouse oocytes and early embryos reveals TCF3/12 as key folliculogenesis regulators.

Dynamic epigenomic reprogramming occurs during mammalian oocyte maturation and early development. However, the underlying transcription circuitry remains poorly characterized. By mapping cis-regulatory elements using H3K27ac, we identified putative enhancers in mouse oocytes and early embryos distinct from those in adult tissues, enabling global transitions of regulatory landscapes around fertilization and implantation. Gene deserts harbour prevalent putative enhancers in fully grown oocytes linked to oocyte-specific genes and repeat activation. Embryo-specific enhancers are primed before zygotic genome activation and are restricted by oocyte-inherited H3K27me3. Putative enhancers in oocytes often manifest H3K4me3, bidirectional transcription, Pol II binding and can drive transcription in STARR-seq and a reporter assay. Finally, motif analysis of these elements identified crucial regulators of oogenesis, TCF3 and TCF12, the deficiency of which impairs activation of key oocyte genes and folliculogenesis. These data reveal distinctive regulatory landscapes and their interacting transcription factors that underpin the development of mammalian oocytes and early embryos.

A first-in-human, phase 1/2 trial of FOG-001, a β-catenin:TCF antagonist, in patients with locally advanced or metastatic solid tumors.

TPS3175 Background: The Wnt/β-catenin pathway is a frequently activated oncogenic pathway and a well-described driver of many cancers. FOG-001 is designed to be a first-in-class direct inhibitor of β-catenin that blocks β-catenin’s interaction with the T-cell factor (TCF) family of transcription factors. Preclinical studies have indicated FOG-001 can cause tumor growth inhibition and regression by disrupting β-catenin-dependent signaling. FOG-001 is unique from previously reported Wnt/β-catenin pathway modulators as it is designed to directly inhibit TCF transcription factor and β-catenin interaction, the most downstream node in the Wnt pathway. It is hypothesized FOG-001 will abrogate the hyperactivation of the Wnt pathway that is driven by most known pathway mutations. Methods: This first-in-human, Phase 1/2, multicenter, open-label, dose escalation (Parts 1a and 1b) and dose-expansion (Part 2) study is evaluating the safety/tolerability, pharmacokinetics (PK), pharmacodynamics (PD), and antitumor activity of FOG-001 in patients with advanced or metastatic solid tumors. Patients with the following tumor types are eligible: microsatellite stable (MSS) colorectal cancer (CRC) or any solid tumor with documented Wnt pathway activating mutation (WPAM) (Part 1a), MSS CRC only (Part 1b) and MSS CRC, gastric/gastroesophageal (GEJ) cancer, non-small cell lung cancer (NSCLC), and any solid tumors with documented WPAM in Part 2. Patients must have received ≥1 prior systemic anticancer therapy(ies) and be ineligible for curative surgery or curative chemoradiation. In Part 1, FOG-001 is administered at escalating doses via intravenous (IV) infusion on Days 1, 8, 15, and 22 of each 4-week cycle; additional dosing regimens may be explored. After selection of the preliminary recommended Phase 2 dose(s) (pRP2D) and regimen(s) in Part 1, the following cohorts will be enrolled to receive FOG-001 at the pRP2D in Part 2: (2a) MSS CRC; (2b) NSCLC with documented WPAM in adenomatous polyposis coli (APC) or β-catenin; (2c) gastric/GEJ cancer with documented WPAM in APC or β-catenin; and (2d) solid tumors with ≥1 documented WPAM in any predefined Wnt pathway genes. The primary endpoints are safety/tolerability (Parts 1 and 2), and also preliminary antitumor activity (objective response rate) (Part 2). Secondary endpoints are PK, PD, and additional antitumor activity assessments. Enrollment in Part 1 is ongoing. Clinical trial information: NCT05919264 .

The developmental and evolutionary characteristics of transcription factor binding site clustered regions based on an explainable machine learning model.

Gene expression is temporally and spatially regulated by the interaction of transcription factors (TFs) and cis-regulatory elements (CREs). The uneven distribution of TF binding sites across the genome poses challenges in understanding how this distribution evolves to regulate spatio-temporal gene expression and consequent heritable phenotypic variation. In this study, chromatin accessibility profiles and gene expression profiles were collected from several species including mammals (human, mouse, bovine), fish (zebrafish and medaka), and chicken. Transcription factor binding sites clustered regions (TFCRs) at different embryonic stages were characterized to investigate regulatory evolution. The study revealed dynamic changes in TFCR distribution during embryonic development and species evolution. The synchronization between TFCR complexity and gene expression was assessed across species using RegulatoryScore. Additionally, an explainable machine learning model highlighted the importance of the distance between TFCR and promoter in the coordinated regulation of TFCRs on gene expression. Our results revealed the developmental and evolutionary dynamics of TFCRs during embryonic development from fish, chicken to mammals. These data provide valuable resources for exploring the relationship between transcriptional regulation and phenotypic differences during embryonic development.

Characterization of PANoptosis-related genes in Crohn's disease by integrated bioinformatics, machine learning and experiments.

Currently, the biological understanding of Crohn's disease (CD) remains limited. PANoptosis is a revolutionary form of cell death reported to participate in numerous diseases, including CD. In our study, we aimed to uncover the roles of PANoptosis in CD. Differentially expressed PANoptosis-related genes (DE-PRGs) were identified by overlapping PANoptosis-related genes and differentially expressed genes between CD and normal samples in a combined microarray dataset. Three machine learning algorithms were adopted to detect hub DE-PRGs. To stratify the heterogeneity within CD patients, nonnegative matrix factorization clustering was conducted. In terms of immune landscape analysis, the "ssGSEA" method was applied. qRT-PCR was performed to examine the expression levels of the hub DE-PRGs in CD patients and colitis model mice. Ten hub DE-PRGs with satisfactory diagnostic performance were identified and validated: CD44, CIDEC, NDRG1, NUMA1, PEA15, RAG1, S100A8, S100A9, TIMP1 and XBP1. These genes displayed significant associations with certain immune cell types and CD-related genes. We also constructed gene‒microRNA, gene‒transcription factor and drug‒gene interaction networks. CD samples were classified into two PANoptosis patterns according to the expression levels of the hub DE-PRGs. Our results suggest that PANoptosis plays a nonnegligible role in CD by modulating the immune system and interacting with CD-related genes.

A dynamic role for transcription factors in restoring transcription through mitosis.

Mitosis involves intricate steps, such as DNA condensation, nuclear membrane disassembly, and phosphorylation cascades that temporarily halt gene transcription. Despite this disruption, daughter cells remarkably retain the parent cell's gene expression pattern, allowing for efficient transcriptional memory after division. Early studies in mammalian cells suggested that transcription factors (TFs) mark genes for swift reactivation, a phenomenon termed 'mitotic bookmarking', but conflicting data emerged regarding TF presence on mitotic chromosomes. Recent advancements in live-cell imaging and fixation-free genomics challenge the conventional belief in universal formaldehyde fixation, revealing dynamic TF interactions during mitosis. Here, we review recent studies that provide examples of at least four modes of TF-DNA interaction during mitosis and the molecular mechanisms that govern these interactions. Additionally, we explore the impact of these interactions on transcription initiation post-mitosis. Taken together, these recent studies call for a paradigm shift toward a dynamic model of TF behavior during mitosis, underscoring the need for incorporating dynamics in mechanistic models for re-establishing transcription post-mitosis.

YAP/TEAD involvement in resistance to paclitaxel chemotherapy in lung cancer.

The Yes-associated protein (YAP) oncoprotein has been linked to both metastases and resistance to targeted therapy of lung cancer cells. We aimed to investigate the effect of YAP pharmacological inhibition, using YAP/TEA domain (TEAD) transcription factor interaction inhibitors in chemo-resistant lung cancer cells. YAP subcellular localization, as a readout for YAP activation, cell migration, and TEAD transcription factor functional transcriptional activity were investigated in cancer cell lines with up-regulated YAP, with and without YAP/TEAD interaction inhibitors. Parental (A549) and paclitaxel-resistant (A549R) cell transcriptomes were analyzed. The half-maximal inhibitory concentration (IC50) of paclitaxel or trametinib, which are Mitogen-Activated protein kinase and Erk Kinase (MEK) inhibitors, combined with a YAP/TEAD inhibitor (IV#6), was determined. A three-dimensional (3D) microfluidic culture device enabled us to study the effect of IV#6/paclitaxel combination on cancer cells isolated from fresh resected lung cancer samples. YAP activity was significantly higher in paclitaxel-resistant cell lines. The YAP/TEAD inhibitor induced a decreased YAP activity in A549, PC9, and H2052 cells, with reduced YAP nuclear staining. Wound healing assays upon YAP inhibition revealed impaired cell motility of lung cancer A549 and mesothelioma H2052 cells. Combining YAP pharmacological inhibition with trametinib in K-Ras mutated A549 cells recapitulated synthetic lethality, thereby sensitizing these cells to MEK inhibition. The YAP/TEAD inhibitor lowered the IC50 of paclitaxel in A549R cells. Differential transcriptomic analysis of parental and A549R cells revealed an increased YAP/TEAD transcriptomic signature in resistant cells, downregulated upon YAP inhibition. The YAP/TEAD inhibitor restored paclitaxel sensitivity of A549R cells cultured in a 3D microfluidic system, with lung cancer cells from a fresh tumor efficiently killed by YAP/TEAD inhibitor/paclitaxel doublet. Evidence of the YAP/TEAD transcriptional program's role in chemotherapy resistance paves the way for YAP therapeutic targeting.

Investigation of two-pore K+ (TPK) channels in Triticum aestivum L. suggests their role in stress response

Two-pore K+ (TPK) channels are voltage-independent and involved in stress response in plants. Herein, we identified 12 TaTPK genes located on nine chromosomes in the Triticum aestivum genome. The majority of TaTPK genes comprised two exons. Each TaTPK channel comprised four transmembrane (TM) helices, N- and C-terminal ion-channel domains, two EF-hand domains and one 14-3-3 binding site. Additionally, highly conserved ‘GYGD’ motif responsible for K+ ion specificity, was found in between the TMs in both the ion-channel domains. Nine TaTPK channels were predicted to be localised at the plasma membrane, while three were vacuolar. The protein-protein and protein-chemical interactions indicated the coordinated functioning of the TaTPK channels with the other K+ transporters and their possible interaction with the Ca2+-signaling pathway. Expression studies suggested their importance in both vegetative and reproductive tissues development. Significantly modulated expression of various TaTPK genes during heat, drought, combined heat and drought and salt stresses, and after fungal infestation, depicted their function in stress responses. The miRNAs and transcription factors interaction analyses suggested their role in the hormone, light, growth and development-related, and stress-responsive signaling cascades. The current study suggested vital functions of various TaTPK genes, especially in stress response, and would provide an opportunity for their detailed characterization in future studies.

Causal effect of gut microbiota of Defluviitaleaceae on the clinical pathway of "Influenza-Subacute Thyroiditis-Hypothyroidism".

Hypothyroidism has been found to be influenced by gut microbiota. However, it remains unclear which a taxon of gut microbiota plays a key role in this function. Identifying the key bacteria affects hypothyroidism and through what mechanism will be helpful for the prevention of hypothyroidism through specific clinical pathways. In Study A, 35 families and 130 genera of gut microbiota are used as exposures, with hypothyroidism as the outcome. The causal effect of the gut microbiota on hypothyroidism is estimated through two-sample Mendelian randomization. Combining the results of the two taxonomical levels, key taxa are selected, which in Study B are investigated for their causal association with multiple generally admitted causes of hypothyroidism and their more upstream factors. For validating and revealing the potential mechanism, enrichment analyses of the related genes and interacting transcription factors were performed. In Study A, Defluviitaleaceae (OR: 0.043, 95% CI: 0.005-0.363, P = 0.018)/Defluviitaleaceae_UCG_011 (OR: 0.385, 95% CI: 0.172-0.865, P = 0.021) are significantly causally associated with hypothyroidism at both taxonomical levels. In Study B, Defluviitaleaceae family and Defluviitaleaceae_UCG_011 genus show the causal association with decreased thyroiditis (Family: OR: 0.174, 95% CI: 0.046-0.653, P = 0.029; Genus: OR: 0.139, 95% CI: 0.029-0.664, P = 0.043), decreased subacute thyroiditis (Family: OR: 0.028, 95% CI: 0.004-0.213, P = 0.007; Genus: OR: 0.018, 95% CI: 0.002-0.194, P = 0.013), decreased influenza (Family: OR: 0.818, 95% CI: 0.676-0.989, P = 0.038; Genus: OR: 0.792, 95% CI: 0.644-0.974, P = 0.027), and increased anti-influenza H3N2 IgG levels (Family: OR: 1.934, 95% CI: 1.123-3.332, P = 0.017; Genus: OR: 1.675, 95% CI: 0.953-2.943, P = 0.073). The results of the enrichment analysis are consistent with the findings and the suggested possible mechanisms. Defluviitaleaceae of the gut microbiota displays the probability of causally inhibiting the clinical pathway of "Influenza-Subacute Thyroiditis-Hypothyroidism" and acts as the potential probiotics to prevent influenza, subacute thyroiditis, and hypothyroidism.

Myocardin regulates fibronectin expression and secretion from human pleural mesothelial cells.

During the progression of pleural fibrosis, pleural mesothelial cells (PMCs) undergo a phenotype switching process known as mesothelial-mesenchymal transition (MesoMT). During MesoMT, transformed PMCs become myofibroblasts that produce increased extracellular matrix (ECM) proteins, including collagen and fibronectin (FN1) that is critical to develop fibrosis. Here, we studied the mechanism that regulates FN1 expression in myofibroblasts derived from human pleural mesothelial cells (HPMCs). We found that myocardin (Myocd), a transcriptional coactivator of serum response factor (SRF) and a master regulator of smooth muscle and cardiac muscle differentiation, strongly controls FN1 gene expression. Myocd gene silencing markedly inhibited FN1 expression. FN1 promoter analysis revealed that deletion of the Smad3-binding element diminished FN1 promoter activity, whereas deletion of the putative SRF-binding element increased FN1 promoter activity. Smad3 gene silencing decreased FN1 expression, whereas SRF gene silencing increased FN1 expression. Moreover, SRF competes with Smad3 for binding to Myocd. These results indicate that Myocd activates FN1 expression through Smad3, whereas SRF inhibits FN1 expression in HPMCs. In HPMCs, TGF-β induced Smad3 nuclear localization, and the proximity ligation signal between Myocd and Smad3 was markedly increased after TGF-β stimulation at nucleus, suggesting that TGF-β facilitates nuclear translocation of Smad3 and interaction between Smad3 and Myocd. Moreover, Myocd and Smad3 were coimmunoprecipitated and isolated Myocd and Smad3 proteins directly bound each other. Chromatin immunoprecipitation assays revealed that Myocd interacts with the FN1 promoter at the Smad3-binding consensus sequence. The results indicate that Myocd regulates FN1 gene activation through interaction and activation of the Smad3 transcription factor.NEW & NOTEWORTHY During phenotype switching from mesothelial to mesenchymal, pleural mesothelial cells (PMCs) produce extracellular matrix (ECM) proteins, including collagen and fibronectin (FN1), critical components in the development of fibrosis. Here, we found that myocardin, a transcriptional coactivator of serum response factor (SRF), strongly activates FN1 expression through Smad3, whereas SRF inhibits FN1 expression. This study provides insights about the regulation of FN1 that could lead to the development of novel interventional approaches to prevent pleural fibrosis.

Cell-free genomics: transcription factor interactions in reconstituted naïve embryonic chromatin.

Extracts from Drosophila preblastoderm embryos (DREX) form the basis of a powerful in vitro chromatin reconstitution system that assembles entire genomes into complex chromatin with physiological nucleosome spacing and polymer condensation. As the zygotic genome has not yet been activated in preblastoderm embryos, the reconstitution extract lacks endogenous transcription factors (TFs) and the RNA polymerase machinery. At the same time, it contains high levels of ATP-dependent nucleosome sliding enzymes that render the reconstituted chromatin dynamic. The naïve chromatin can be used to determine the intrinsic DNA binding properties of exogenous, usually recombinant TFs (or DNA binding proteins in general) in a complex chromatin context. Recent applications of the system include the description of cooperation and competition of Drosophila pioneer TFs for composite binding sites, and the characterization of nucleosome interactions of mammalian pioneer TFs in the heterologous system.

Structure and interactions of prion-like domains in transcription factor Efg1 phase separation

Candida albicans, a prominent member of the human microbiome, can make an opportunistic switch from commensal coexistence to pathogenicity accompanied by an epigenetic shift between the white and opaque cell states. This transcriptional switch is under precise regulation by a set of transcription factors (TFs), with Enhanced Filamentous Growth Protein 1 (Efg1) playing a central role. Previous research has emphasized the importance of Efg1’s prion-like domain (PrLD) and the protein’s ability to undergo phase separation for the white-to-opaque transition of C. albicans. However, the underlying molecular mechanisms of Efg1 phase separation have remained underexplored. In this study, we delved into the biophysical basis of Efg1 phase separation, revealing the significant contribution of both N-terminal (N) and C-terminal (C) PrLDs. Through NMR structural analysis, we found that Efg1 N-PrLD and C-PrLD are mostly disordered but have prominent partial α-helical secondary structures in both domains. NMR titration experiments suggest that the partially helical structures in N-PrLD act as hubs for self-interaction as well as Efg1 interaction with RNA. Using condensed-phase NMR spectroscopy, we uncovered diverse amino acid interactions underlying Efg1 phase separation. Particularly, we highlight the indispensable role of tyrosine residues within the transient α-helical structures of PrLDs particularly in the N-PrLD compared to the C-PrLD in stabilizing phase separation. Our study provides evidence that the transient α-helical structure is present in the phase-separated state and highlights the particular importance of aromatic residues within these structures for phase separation. Together, these results enhance the understanding of C. albicans transcription factor interactions that lead to virulence and provide a crucial foundation for potential antifungal therapies targeting the transcriptional switch.

Identification of potential regulatory mechanisms and therapeutic targets for lung cancer

Lung cancer poses a significant health threat globally, especially in regions like India, with 5-year survival rates remain alarmingly low. Our study aimed to uncover key markers for effective treatment and early detection. We identified specific genes related to lung cancer using the BioXpress database and delved into their roles through DAVID enrichment analysis. By employing network theory, we explored the intricate interactions within lung cancer networks, identifying ASPM and MKI67 as crucial regulator genes. Predictions of microRNA and transcription factor interactions provided additional insights. Examining gene expression patterns using GEPIA and KM Plotter revealed the clinical relevance of these key genes. In our pursuit of targeted therapies, Drug Bank pointed to methotrexate as a potential drug for the identified key regulator genes. Confirming this, molecular docking studies through Swiss Dock showed promising binding interactions. To ensure stability, we conducted molecular dynamics simulations using the AMBER 16 suite. In summary, our study pinpoints ASPM and MKI67 as vital regulators in lung cancer networks. The identification of hub genes and functional pathways enhances our understanding of molecular processes, offering potential therapeutic targets. Importantly, methotrexate emerged as a promising drug candidate, supported by robust docking and simulation studies. These findings lay a solid foundation for further experimental validations and hold promise for advancing personalized therapeutic strategies in lung cancer. Communicated by Ramaswamy H. Sarma

ENPP1 inhibits the transcription activity of the hepatitis B virus pregenomic promoter by upregulating the acetylation of LMNB1.

Current therapies for hepatitis B virus (HBV) infection can slow disease progression but cannot cure the infection, as it is difficult to eliminate or permanently silence HBV covalently closed circular DNA (cccDNA). The interaction between host factors and cccDNA is essential for their formation, stability, and transcriptional activity. Here, we focused on the regulatory role of the host factor ENPP1 and its interacting transcription factor LMNB1 in HBV replication and transcription to better understand the network of host factors that regulate HBV, which may facilitate the development of new antiviral drugs. Overexpression of ectonucleotide pyrophosphatase/phosphodiesterase 1(ENPP1) in Huh7 cells decreased HBV pregenomic RNA (pgRNA) and hepatitis B core antigen (HBcAg) expression levels, whereas knockdown of ENPP1 increased them. A series of HBV promoter and mutant plasmids were constructed, and a luciferase reporter assay showed that overexpression of ENPP1 caused inhibition of the HBV promoter and its mutants. A DNA pull-down assay showed that lamin B1 (LMNB1), but not ENPP1, interacts directly with the HBV enhancer II/basic core promoter(EnhII/BCP). ZDOCK and PyMOL software were used to predict the interaction of ENPP1 with LMNB1. Overexpression of LMNB1 inhibited the activity of the HBV promoter and its mutant. The acetylation levels at the amino acids 111K, 261K, and 483K of LMNB1 were reduced compared to the control, and an LMNB1 acetylation mutant containing 111R, 261Q, 261R, 483Q, and 483R showed increased promoter activity. In summary, ENPP1 together with LMNB1 increased the acetylation level at 111K and 261K, and LMNB1 inhibited the activity of HBV promoter and downregulated the expression of pregenomic RNA and HBcAg. Our follow-up studies will investigate the expression, clinical significance, and relevance of ENPP1 and LMNB1 in HBV patient tissues, explore the effect of LMNB1 on post-transcriptional progression, and examine whether ENPP1 can reduce cccDNA levels in the nucleus.