TF-binding Motifs Research Articles

Genome-wide epigenetic dynamics of tea leaves under mechanical wounding stress during oolong tea postharvest processing

Understanding the epigenetic responses to mechanical wounding stress during the postharvest processing of oolong tea provides insight into the reprogramming of the tea genome and its impact on tea quality. Here, we characterized the 5mC DNA methylation and chromatin accessibility landscapes of tea leaves subjected to mechanical wounding stress during the postharvest processing of oolong tea. Analysis of the differentially methylated regions and preferentially accessible promoters revealed many overrepresented TF-binding motifs, highlighting sets of TFs that are likely important for the quality of oolong tea. Within these sets, we constructed a chromatin accessibility-mediated gene regulatory network specific to mechanical wounding stress. In combination with the results of the TF-centred yeast one-hybrid assay, we identified potential binding sites of CsMYC2 and constructed a gene regulatory network centred on CsMYC2, clarifying the potential regulatory role of CsMYC2 in the postharvest processing of oolong tea. Interestingly, highly accessible chromatin and hypomethylated cytosine were found to coexist in the promoter region of the indole biosynthesis gene (tryptophan synthase β-subunit, CsTSB) under wounding stress, which indicates that these two important epigenetic regulatory mechanisms are jointly involved in regulating the synthesis of indole during the postharvest processing of oolong tea. These findings improve our understanding of the epigenetic regulatory mechanisms involved in quality formation during the postharvest processing of oolong tea.

Secretome from iPSC-derived MSCs exerts proangiogenic and immunosuppressive effects to alleviate radiation-induced vascular endothelial cell damage

BackgroundRadiation therapy is the standard of care for central nervous system tumours. Despite the success of radiation therapy in reducing tumour mass, irradiation (IR)-induced vasculopathies and neuroinflammation contribute to late-delayed complications, neurodegeneration, and premature ageing in long-term cancer survivors. Mesenchymal stromal cells (MSCs) are adult stem cells that facilitate tissue integrity, homeostasis, and repair. Here, we investigated the potential of the iPSC-derived MSC (iMSC) secretome in immunomodulation and vasculature repair in response to radiation injury utilizing human cell lines.MethodsWe generated iPSC-derived iMSC lines and evaluated the potential of their conditioned media (iMSC CM) to treat IR-induced injuries in human monocytes (THP1) and brain vascular endothelial cells (hCMEC/D3). We further assessed factors in the iMSC secretome, their modulation, and the molecular pathways they elicit.ResultsIncreasing doses of IR disturbed endothelial tube and spheroid formation in hCMEC/D3. When IR-injured hCMEC/D3 (IR ≤ 5 Gy) were treated with iMSC CM, endothelial cell viability, adherence, spheroid compactness, and proangiogenic sprout formation were significantly ameliorated, and IR-induced ROS levels were reduced. iMSC CM augmented tube formation in cocultures of hCMEC/D3 and iMSCs. Consistently, iMSC CM facilitated angiogenesis in a zebrafish model in vivo. Furthermore, iMSC CM suppressed IR-induced NFκB activation, TNF-α release, and ROS production in THP1 cells. Additionally, iMSC CM diminished NF-kB activation in THP1 cells cocultured with irradiated hCMEC/D3, iMSCs, or HMC3 microglial lines. The cytokine array revealed that iMSC CM contains the proangiogenic and immunosuppressive factors MCP1/CCL2, IL6, IL8/CXCL8, ANG (Angiogenin), GROα/CXCL1, and RANTES/CCL5. Common promoter regulatory elements were enriched in TF-binding motifs such as androgen receptor (ANDR) and GATA2. hCMEC/D3 phosphokinome profiling revealed increased expression of pro-survival factors, the PI3K/AKT/mTOR modulator PRAS40 and β-catenin in response to CM. The transcriptome analysis revealed increased expression of GATA2 in iMSCs and the enrichment of pathways involved in RNA metabolism, translation, mitochondrial respiration, DNA damage repair, and neurodevelopment.ConclusionsThe iMSC secretome is a comodulated composite of proangiogenic and immunosuppressive factors that has the potential to alleviate radiation-induced vascular endothelial cell damage and immune activation.

Overexpression of a pearl millet WRKY transcription factor gene, PgWRKY74, in Arabidopsis retards shoot growth under dehydration and salinity-stressed conditions

Pearl millet (Cenchrus americanus) is a cereal crop that can tolerate high temperatures, drought, and low-fertility conditions where other crops lose productivity. However, genes regulating this ability are largely unknown. Transcription factors (TFs) regulate transcription of their target genes, regulate downstream biological processes, and thus are candidates for regulators of such tolerance of pearl millet. PgWRKY74 encodes a group IIc WRKY TF in pearl millet and is downregulated by drought. PgWRKY74 may have a role in drought tolerance. The objective of this study was to gain insights into the physiological and biochemical functions of PgWRKY74. Yeast one-hybrid and gel shift assays were performed to examine transcriptional activation potential and deoxyribonucleic acid (DNA)-binding ability, respectively. Transgenic Arabidopsis thaliana plants overexpressing PgWRKY74-green fluorescent protein (GFP) fusion gene were generated and tested for growth and stress-responsive gene expression under mannitol and NaCl-stressed conditions. A construct with PgWRKY74 enabled yeast reporter cells to survive on test media in the yeast one-hybrid assays. The electrophoretic mobility of DNA with putative WRKY TF-binding motifs was lower in the presence of a recombinant PgWRKY74 protein than its absence. The PgWRKY74-GFP-overexpressing Arabidopsis plants exhibited smaller rosette areas than did wild-type plants under mannitol-stressed and NaCl-stressed conditions, and exhibited weaker expression of RD29B, which is induced by the stress-related phytohormone abscisic acid (ABA), under the mannitol-stressed condition. PgWRKY74 have transcriptional activation potential and DNA-binding ability, and can negatively regulate plant responses to mannitol and NaCl stresses, possibly by decreasing ABA levels or ABA sensitivity.

ZIP Code to Genomic Code: Neighborhood Disadvantage, Aggressive Breast Cancer Biology, and Breast Cancer Outcomes.

To determine the association between objective (geospatial) and subjective (perceived) measures of neighborhood disadvantage (ND) and aggressive breast cancer (BCa) tumor biology, defined using validated social adversity-associated transcription factor (TF) activity and clinical outcomes. ND is associated with shorter BCa recurrence-free survival (RFS), independent of individual, tumor, and treatment characteristics, suggesting potential unaccounted biological mechanisms by which ND influences RFS. We quantified TF-binding motif prevalence within promoters of differentially expressed genes for 147 tissue samples prospectively collected on protocol. Covariate-adjusted multivariable regression analyzed objective and subjective ND scores with 5 validated TFs of social adversity and aggressive biology-pro-inflammatory activity (NF-kB, AP-1), sympathetic nervous system (SNS) activity (CREB), and protective cellular responses (IRF, STAT). To clinically validate these TFs as prognostic biomarkers of aggressive biology, logistic regression and multivariable Cox proportional-hazards models analyzed their association with Oncotype DX scores and RFS, respectively. Increasing objective ND was associated with aggressive tumor biology (up-regulated NF-kB, AP-1, down-regulated IRF, STAT) and SNS activation (up-regulated CREB). Increasing subjective ND (e.g., threat to safety), was associated with up-regulated NF-kB and CREB and down-regulated IRF. These TF patterns were associated with high-risk Oncotype DX scores and shorter RFS. In the largest human social genomics study, objective and subjective ND were significantly associated with TFs of aggressive biology and SNS activation. These TFs also correlated with worse clinical outcomes, implicating SNS activation as one potential mechanism behind ND survival disparities. These findings remain to be validated in a national cohort.

Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS.

The molecular identity of a cell results from a complex interplay between heterogeneous molecular layers. Recent advances in single-cell sequencing technologies have opened the possibility to measure such molecular layers of regulation. Here, we present HuMMuS, a new method for inferring regulatory mechanisms from single-cell multi-omics data. Differently from the state-of-the-art, HuMMuS captures cooperation between biological macromolecules and can easily include additional layers of molecular regulation. We benchmarked HuMMuS with respect to the state-of-the-art on both paired and unpaired multi-omics datasets. Our results proved the improvements provided by HuMMuS in terms of transcription factor (TF) targets, TF binding motifs and regulatory regions prediction. Finally, once applied to snmC-seq, scATAC-seq and scRNA-seq data from mouse brain cortex, HuMMuS enabled to accurately cluster scRNA profiles and to identify potential driver TFs. HuMMuS is available at https://github.com/cantinilab/HuMMuS.

Species-Specific Transcription Factors Associated with Long Terminal Repeat Promoters of Endogenous Retroviruses: A Comprehensive Review.

Endogenous retroviruses (ERVs) became a part of the eukaryotic genome through endogenization millions of years ago. Moreover, they have lost their innate capability of virulence or replication. Nevertheless, in eukaryotic cells, they actively engage in various activities that may be advantageous or disadvantageous to the cells. The mechanisms by which transcription is triggered and implicated in cellular processes are complex. Owing to the diversity in the expression of transcription factors (TFs) in cells and the TF-binding motifs of viruses, the comprehensibility of ERV initiation and its impact on cellular functions are unclear. Currently, several factors are known to be related to their initiation. TFs that bind to the viral long-terminal repeat (LTR) are critical initiators. This review discusses the TFs shown to actively associate with ERV stimulation across species such as humans, mice, pigs, monkeys, zebrafish, Drosophila, and yeast. A comprehensive summary of the expression of previously reported TFs may aid in identifying similarities between animal species and endogenous viruses. Moreover, an in-depth understanding of ERV expression will assist in elucidating their physiological roles in eukaryotic cell development and in clarifying their relationship with endogenous retrovirus-associated diseases.

MethMotif.Org 2024: a database integrating context-specific transcription factor-binding motifs with DNA methylation patterns.

MethMotif (https://methmotif.org) is a publicly available database that provides a comprehensive repository of transcription factor (TF)-binding profiles, enriched with DNA methylation patterns. In this release, we have enhanced the platform, expanding our initial collection to over 700 position weight matrices (PWM), all of which include DNA methylation profiles. One of the key advancements in this release is the segregation of TF-binding motifs based on their cofactors and DNA methylation status. We have previously demonstrated that gene ontology (GO) enriched terms associated with TF target genes may differ based on their association with alternative cofactors and DNA methylation status. MethMotif provides precomputed GO annotations for each human TF of interest, as well as for TF-co-TF complexes, enabling a comprehensive analysis of TF functions in the context of their co-factors. Additionally, MethMotif has been updated to encompass data for two new species, Mus musculus and Arabidopsis thaliana, widening its applicability to a broader community. MethMotif stands out as the first and only TF-binding motifs database to incorporate context-specific PWM coupled with epigenetic information, thereby enlightening context-specific TF functions. This enhancement allows the community to explore and gain deeper insights into the regulatory mechanisms governing transcriptional processes.

Identification of potential ferroptosis-associated biomarkers in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by inflammation and gradual joint degeneration, resulting in function disability. Recently, ferroptosis, a novel form of regulated cell death that involves iron-dependent lipid peroxidation, has been implicated in the pathogenesis of RA. However, the underlying molecular mechanisms and key genes involved in ferroptosis in RA remain largely unknown. The GSE134420 and GSE77298 datasets were downloaded and DEGs were identified using R software. The DEGs were then mapped to the dataset of 619 ferroptosis-related genes obtained from the GeneCards database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to investigate the possible biological functions. Protein-protein interaction (PPI) networks were constructed to identify the hub genes. The relationship between hub genes and immune infiltration was estimated using the CIBERSORT algorithms. Gene Set Enrichment Analysis (GSEA) was used to explore the underlying signaling pathways of hub genes. Genome-wide association studies (GWAS) analysis was performed to confirm the pathogenic regions of the hub genes. RcisTarget and Gene-motif ranking databases were used to identify transcription factors (TFs) associated with the hub genes. The miRcode databases were utilized to construct the microRNA (miRNA)-messenger RNA (mRNA) network. Single-cell analysis was utilized to cluster cells and display the expression of hub genes in cell clusters. Finally, the expression and potential mechanism of hub genes were investigated in human and experimental samples. Three hub genes PTGS2, ENO1, and GRN highly associated with ferroptosis were identified. Four pathogenic genes HLA-B, MIF, PSTPIP, TLR1 were identified that were significantly and positively correlated with the expression levels of hub genes. The results of the GSEA showed that the hub genes were significantly enriched in pathways related to immunity, lysosome, phagocytosis and infection. ENO1 and PTGS2 were enriched in the TF-binding motif of cisbp_M5493. The hub genes were validated in experimental and patient samples and highly level of ENO1 expression was found to inhibit ACO1, which reduces ferroptosis in proliferating fibroblast-like synoviocytes (FLS). PTGS2, ENO1 and GRN were identified and validated as potential ferroptosis-related biomarkers. Our work first revealed that ENO1 is highly expressed in RA synovium and that ferroptosis may be regulated by the ENO1-ACO1 axis, advancing the understanding of the underlying ferroptosis-related mechanisms of synovial proliferation and providing potential diagnostic and therapeutic targets for RA.

Characterization of chromatin accessibility and gene expression reveal the key genes involved in cotton fiber elongation.

Cotton (Gossypium hirsutum L.) is an important economic crop, and cotton fiber is one of the longest plant cells, which provides an ideal model for the study of cell elongation and secondary cell wall synthesis. Cotton fiber length is regulated by a variety of transcription factors (TF) and their target genes; however, the mechanism of fiber elongation mediated by transcriptional regulatory networks is still unclear to a large extent. Here, we used a comparative assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) assay and RNA-seq analysis to identify fiber elongation transcription factors and genes using the short-fiber mutant ligon linless-2 (Li2 ) and wild type (WT). A total of 499 differential target genes were identified and GO analysis shows that differential genes are mainly involved in plant secondary wall synthesis and microtubule-binding processes. Analysis of the genomic regions preferentially accessible (Peak) has identified a number of overrepresented TF-binding motifs, highlighting sets of TFs that are important for cotton fiber development. Using ATAC-seq and RNA-seq data, we have constructed a functional regulatory network of each TF regulatory target gene and also the network pattern of TF regulating differential target genes. Further, to obtain the genes related to fiber length, the differential target genes were combined with FLGWAS data to identify the genes highly related to fiber length. Our work provides new insights into cotton fiber elongation.

Evaluation of MYBL1 as the master regulator for pachytene spermatocyte genes dysregulated in interspecific hybrid dzo

Misregulation of spermatogenesis transcription factors (TF) in hybrids can lead to misexpression, which is a mechanism for hybrid male sterility (HMS). We used dzo (male offspring of Bos taurus ♂ × Bos grunniens ♀) in bovines to investigate the relationship of the key TF with HMS via RNA sequencing and assay for transposase-accessible chromatin with high-throughput sequencing analyses. RNA sequencing showed that the widespread misexpression in dzo was associated with spermatogenesis-related genes and somatic or progenitor genes. The transition from leptotene or zygotene spermatocytes to pachytene spermatocytes may be the key stage for meiosis arrest in dzo. The analysis of TF-binding motif enrichment revealed that the male meiosis-specific master TF MYB proto-oncogene like 1 (MYBL1, known as A-MYB) motif was enriched on the promoters of downregulated pachytene spermatocyte genes in dzo. Assay for transposase-accessible chromatin with high-throughput sequencing revealed that TF-binding sites for MYBL1, nuclear transcription factor Y, and regulatory factor X were enriched in the low-chromatin accessibility region of dzo. The target genes of the MYBL1-binding motif were associated with meiosis-specific genes and significantly downregulated in dzo testis. The transcription factor MYBL1 may be the candidate master regulator for pachytene spermatocyte genes dysregulated in interspecific HMS dzo. This study reported that a few upstream TF regulation changes might exert a cascading effect downstream in a regulatory network as a mechanism for HMS.

Genome-Wide Identification and Analysis of DOF Gene Family in Eugenia uniflora L. (Myrtaceae)

Eugenia uniflora is a Brazilian native plant species with great ecological and economic importance. It is distributed throughout the Atlantic forest, where two distinct populations show local adaptation to the contrasting conditions of restinga and riparian forest. Among various TFs described in plants, the DOF TF family has been reported to affect flowering and vascular development, making them promising candidates for characterization in E. uniflora. In this study, 28 DOF genes were identified by a genome-wide analysis, of which 20 were grouped into 11 MCOGs by Bayesian phylogeny, suggesting a shared functionallity between members. Based on RNA-seq experiments, we have detected eight drought responsive genes, and SNPs identification revealed population unique polymorphisms, implying a role in local adapatation mechanisms. Finally, analysis of conserved motifs through MEME revealed 15 different protein motifs, and a promoter region analysis returned 40 enriched TF binding motifs, both reporting novel biological functions circa the DOF gene family. In general, the DOF family is found to be conserved both in sequence and expression. Furthermore, this study contributes to both DOF literature and the genetic exploration of native species, elucidating their genetic potential and bringing to light new research topics, paving the way to future studies.

Characterizing collaborative transcription regulation with a graph-based deep learning approach.

Human epigenome and transcription activities have been characterized by a number of sequence-based deep learning approaches which only utilize the DNA sequences. However, transcription factors interact with each other, and their collaborative regulatory activities go beyond the linear DNA sequence. Therefore leveraging the informative 3D chromatin organization to investigate the collaborations among transcription factors is critical. We developed ECHO, a graph-based neural network, to predict chromatin features and characterize the collaboration among them by incorporating 3D chromatin organization from 200-bp high-resolution Micro-C contact maps. ECHO predicted 2,583 chromatin features with significantly higher average AUROC and AUPR than the best sequence-based model. We observed that chromatin contacts of different distances affected different types of chromatin features' prediction in diverse ways, suggesting complex and divergent collaborative regulatory mechanisms. Moreover, ECHO was interpretable via gradient-based attribution methods. The attributions on chromatin contacts identify important contacts relevant to chromatin features. The attributions on DNA sequences identify TF binding motifs and TF collaborative binding. Furthermore, combining the attributions on contacts and sequences reveals important sequence patterns in the neighborhood which are relevant to a target sequence's chromatin feature prediction.

Abc4pwm: affinity based clustering for position weight matrices in applications of DNA sequence analysis

BackgroundTranscription factor (TF) binding motifs are identified by high throughput sequencing technologies as means to capture Protein-DNA interactions. These motifs are often represented by consensus sequences in form of position weight matrices (PWMs). With ever-increasing pool of TF binding motifs from multiple sources, redundancy issues are difficult to avoid, especially when every source maintains its own database for collection. One solution can be to cluster biologically relevant or similar PWMs, whether coming from experimental detection or in silico predictions. However, there is a lack of efficient tools to cluster PWMs. Assessing quality of PWM clusters is yet another challenge. Therefore, new methods and tools are required to efficiently cluster PWMs and assess quality of clusters.ResultsA new Python package Affinity Based Clustering for Position Weight Matrices (abc4pwm) was developed. It efficiently clustered PWMs from multiple sources with or without using DNA-Binding Domain (DBD) information, generated a representative motif for each cluster, evaluated the clustering quality automatically, and filtered out incorrectly clustered PWMs. Additionally, it was able to update human DBD family database automatically, classified known human TF PWMs to the respective DBD family, and performed TF motif searching and motif discovery by a new ensemble learning approach.ConclusionThis work demonstrates applications of abc4pwm in the DNA sequence analysis for various high throughput sequencing data using ~ 1770 human TF PWMs. It recovered known TF motifs at gene promoters based on gene expression profiles (RNA-seq) and identified true TF binding targets for motifs predicted from ChIP-seq experiments. Abc4pwm is a useful tool for TF motif searching, clustering, quality assessment and integration in multiple types of sequence data analysis including RNA-seq, ChIP-seq and ATAC-seq.

Functional noncoding SNPs in human endothelial cells fine-map vascular trait associations.

Functional consequences of genetic variation in the noncoding human genome are difficult to ascertain despite demonstrated associations to common, complex disease traits. To elucidate properties of functional noncoding SNPs with effects in human endothelial cells (ECs), we utilized our previous molecular quantitative trait locus (molQTL) analysis for transcription factor binding, chromatin accessibility, and H3K27 acetylation to nominate a set of likely functional noncoding SNPs. Together with information from genome-wide association studies (GWASs) for vascular disease traits, we tested the ability of 34,344 variants to perturb enhancer function in ECs using the highly multiplexed STARR-seq assay. Of these, 5711 variants validated, whose enriched attributes included: (1) mutations to TF binding motifs for ETS or AP-1 that are regulators of the EC state; (2) location in accessible and H3K27ac-marked EC chromatin; and (3) molQTL associations whereby alleles associate with differences in chromatin accessibility and TF binding across genetically diverse ECs. Next, using pro-inflammatory IL1B as an activator of cell state, we observed robust evidence (>50%) of context-specific SNP effects, underscoring the prevalence of noncoding gene-by-environment (GxE) effects. Lastly, using these cumulative data, we fine-mapped vascular disease loci and highlighted evidence suggesting mechanisms by which noncoding SNPs at two loci affect risk for pulse pressure/large artery stroke and abdominal aortic aneurysm through respective effects on transcriptional regulation of POU4F1 and LDAH. Together, we highlight the attributes and context dependence of functional noncoding SNPs and provide new mechanisms underlying vascular disease risk.

A systematic study of motif pairs that may facilitate enhancer-promoter interactions.

Pairs of interacting transcription factors (TFs) have previously been shown to bind to enhancers and promoters and contribute to their physical interactions. However, to date, we have limited knowledge about such TF pairs. To fill this void, we systematically studied the co-occurrence of TF-binding motifs in interacting enhancer–promoter (EP) pairs in seven human cell lines. We discovered 423 motif pairs that significantly co-occur in enhancers and promoters of interacting EP pairs. We demonstrated that these motif pairs are biologically meaningful and significantly enriched with motif pairs of known interacting TF pairs. We also showed that the identified motif pairs facilitated the discovery of the interacting EP pairs. The developed pipeline, EPmotifPair, together with the predicted motifs and motif pairs, is available at https://doi.org/10.6084/m9.figshare.14192000. Our study provides a comprehensive list of motif pairs that may contribute to EP physical interactions, which facilitate generating meaningful hypotheses for experimental validation.

Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue

Understanding the contributions of transcription factor DNA binding sites to transcriptional enhancers is a significant challenge. We developed Quantitative enhancer-FACS-Seq for highly parallel quantification of enhancer activities from a genomically integrated reporter in Drosophila melanogaster embryos. We investigate the contributions of the DNA binding motifs of four poorly characterized TFs to the activities of twelve embryonic mesodermal enhancers. We measure quantitative changes in enhancer activity and discover a range of epistatic interactions among the motifs, both synergistic and alleviating. We find that understanding the regulatory consequences of TF binding motifs requires that they be investigated in combination across enhancer contexts.

Transcriptomic analyses of black women in neighborhoods with high levels of violence

Chronic stress threatens an individual's capacity to maintain psychological and physiological homeostasis, but the molecular processes underlying the biological embedding of these experiences are not well understood. This is particularly true for marginalized groups, presenting a fundamental challenge to decreasing racial, economic, and gender-based health disparities. Physical and social environments influence genome function, including the transcriptional activity of core stress responsive genes. We studied the relationship between social experiences that are associated with systemic inequality (e.g., racial segregation, poverty, and neighborhood violence) and blood cell (leukocytes) gene expression, focusing on the activation of transcription factors (TF) critical to stress response pathways. The study used data from 68 women collected from a convenience sample in 2013 from the Southside of Chicago. Comparing single, low-income Black mothers living in neighborhoods with high levels of violence (self-reported and assessed using administrative police records) to those with low levels of violence we found no significant differences in expression of 51 genes associated with the Conserved Transcriptional Response to Adversity (CTRA). Using TELiS analysis of promoter TF-binding motif prevalence we found that mothers who self-reported higher levels of neighborhood stress showed greater expression of genes regulated by the glucocorticoid receptor (GR). These findings may reflect increased cortisol output from the hypothalamic-pituitary-adrenal (HPA) axis, or increased GR transcriptional sensitivity. Transcript origin analyses identified monocytes and dendritic cells as the primary cellular sources of gene transcripts up-regulated in association with neighborhood stress. The prominence of GR-related transcripts and the absence of sympathetic nervous system-related CTRA transcripts suggest that a subjective perception of elevated chronic neighborhood stress may be associated with an HPA-related defeat-withdrawal phenotype rather than a fight-or-flight phenotype. The defeat-withdrawal phenotype has been previously observed in animal models of severe, overwhelming threat. These results demonstrate the importance of studying biological embedding in diverse environments and communities, specifically marginalized populations such as low-income Black women.

Abstract 16406: Epigenetic Regulation of Myofibroblast Differentiation and Persistence is Mediated by Enhanced Glutaminolysis

Cardiac fibrosis is mediated by the activation and differentiation of resident cardiac fibroblasts. While initially reparative, chronic activation leads to progressive cardiac dysfunction. Associated with myofibroblast formation are changes in metabolites directly linked to the activity of epigenetic-modifying enzymes. To define the signaling linking fibroblast activation with changes to the epigenetic landscape, we treated primary adult murine cardiac fibroblasts (CFs) with the pro-fibrotic agonist, TGFβ, and subjected them to next-gen sequencing techniques (RNA-seq, ATAC-seq). Following activation, we observed alterations in chromatin accessibility corresponding to the transcriptional activation and suppression of key fibrotic genes. Intriguingly, increased chromatin accessibility was strongly associated with both transcriptional activation and suppression, while decreased accessibility correlated with neither transcriptional repression or activation. Regions of increased accessibility were enriched for canonical fibrotic TF binding motifs (e.g. SMADs, NFAT). We recently reported that αKG-dependent lysine demethylases may be required for myofibroblast formation, so we made correlative comparisons between chromatin remodeling and the synthesis and utilization of metabolites critical for (de)methylation by applying unbiased, stable isotope metabolomics. These studies indicated enhanced glutaminolysis as the driver of increased αKG abundance. In the presence of TGFβ, pharmacologic inhibition (CB-839) or genetic deletion ( Gls1 -/- ) of glutaminolysis prevented myofibroblast formation as indicated by αSMA positivity, fibrotic gene program activation, and collagen contraction assays. Following myofibroblast formation, inhibition of glutaminolysis was sufficient to revert activated myofibroblasts to a non-fibrotic phenotype, during sustained stress. Remarkably, these results were recapitulated in CFs from human heart failure patients. Collectively, these findings suggest that metabolic remodeling is necessary for the epigenetic modifications that underlie myofibroblast formation and persistence, providing substantial rationale to evaluate several new therapeutic targets to treat fibrosis.

Learning and interpreting the gene regulatory grammar in a deep learning framework.

Deep neural networks (DNNs) have achieved state-of-the-art performance in identifying gene regulatory sequences, but they have provided limited insight into the biology of regulatory elements due to the difficulty of interpreting the complex features they learn. Several models of how combinatorial binding of transcription factors, i.e. the regulatory grammar, drives enhancer activity have been proposed, ranging from the flexible TF billboard model to the stringent enhanceosome model. However, there is limited knowledge of the prevalence of these (or other) sequence architectures across enhancers. Here we perform several hypothesis-driven analyses to explore the ability of DNNs to learn the regulatory grammar of enhancers. We created synthetic datasets based on existing hypotheses about combinatorial transcription factor binding site (TFBS) patterns, including homotypic clusters, heterotypic clusters, and enhanceosomes, from real TF binding motifs from diverse TF families. We then trained deep residual neural networks (ResNets) to model the sequences under a range of scenarios that reflect real-world multi-label regulatory sequence prediction tasks. We developed a gradient-based unsupervised clustering method to extract the patterns learned by the ResNet models. We demonstrated that simulated regulatory grammars are best learned in the penultimate layer of the ResNets, and the proposed method can accurately retrieve the regulatory grammar even when there is heterogeneity in the enhancer categories and a large fraction of TFBS outside of the regulatory grammar. However, we also identify common scenarios where ResNets fail to learn simulated regulatory grammars. Finally, we applied the proposed method to mouse developmental enhancers and were able to identify the components of a known heterotypic TF cluster. Our results provide a framework for interpreting the regulatory rules learned by ResNets, and they demonstrate that the ability and efficiency of ResNets in learning the regulatory grammar depends on the nature of the prediction task.

Determinants of correlated expression of transcription factors and their target genes

While transcription factors (TFs) are known to regulate the expression of their target genes (TGs), only a weak correlation of expression between TFs and their TGs has generally been observed. As lack of correlation could be caused by additional layers of regulation, the overall correlation distribution may hide the presence of a subset of regulatory TF–TG pairs with tight expression coupling. Using reported regulatory pairs in the plant Arabidopsis thaliana along with comprehensive gene expression information and testing a wide array of molecular features, we aimed to discern the molecular determinants of high expression correlation of TFs and their TGs. TF-family assignment, stress-response process involvement, short genomic distances of the TF-binding sites to the transcription start site of their TGs, few required protein-protein-interaction connections to establish physical interactions between the TF and polymerase-II, unambiguous TF-binding motifs, increased numbers of miRNA target-sites in TF-mRNAs, and a young evolutionary age of TGs were found particularly indicative of high TF–TG correlation. The modulating roles of post-transcriptional, post-translational processes, and epigenetic factors have been characterized as well. Our study reveals that regulatory pairs with high expression coupling are associated with specific molecular determinants.