Biology subjects

Greenberg, M.

Publications and source records attributed to Greenberg, M..

18 recordsLinked to original sources

bioRxiv2026

Loss of TAFAZZIN leads to perturbation of amino acid metabolism and reduction of collagen synthesis

Barth syndrome is a life-threatening genetic disorder caused by mutations in the TAFAZZIN (TAZ) gene, which disrupt remodeling of cardiolipin in mitochondria. The disease is associated with cardiac and skeletal myopathy, neutropenia, fatigue, and metabolic dysfunction. Previous studies showed that loss of TAZ decreases pyruvate dehydrogenase activity, reduces glucose flux into the TCA cycle, and impairs fatty acid metabolism. To test the hypothesis that amino acid (AA) metabolism may be altered to compensate for these deficiencies, we characterized AA metabolism in TAZ-deficient mouse myoblasts (TAZ-KO). Levels of branched-chain amino acids (BCAAs) were reduced, while proline levels were increased in TAZ-KO cells. Levels of proline dehydrogenase and glutamate dehydrogenase, which convert proline to TCA cycle intermediates, were increased. 13C5-proline isotope tracing demonstrated elevated conversion of proline into glutamate and TCA cycle intermediates. SILAC analysis using [U-13C6, 15N2]-Lys and [U-13C6]-Arg revealed decreased synthesis of collagen and proteins associated with extracellular matrix (ECM). Gene expression and protein analyses revealed reduced collagen expression, lower total collagen content, decreased collagen crosslinking enzymes, decreased proline hydroxylation and reduced synthesis of new collagen and cell-adhesion proteins. SILAC analysis using [U-13C6, 15N2]-proline also showed diminished incorporation of proline into newly synthesized ECM proteins. Together, our findings reveal that loss of TAZ leads to increased proline catabolism to the TCA cycle, decreased incorporation of proline into collagen, and impaired collagen synthesis and ECM remodeling.

cell biology↗

bioRxiv2026

DNA methylation links lagging strand replication to transposable element control

DNA methylation is an essential epigenetic mark that silences transposable elements (TEs) in mammalian genomes1,2. Following DNA replication, methylation patterns must be faithfully restored3,4, yet how the two processes are coordinated remains unclear. Here, using strand-specific, genome-wide analyses5-7 in mouse embryonic stem cells, we show that DNA methylation maintenance is coupled to the lagging-strand synthesis in TE-rich regions. Paradoxically, despite this targeting, the lagging strand is more permissive for TE integration than the leading strand. Notably, insertions of full-length LINE-1s, SINEs, and satellite repeats are all enriched on the lagging strand over evolutionary time. Consequently, most TEs, particularly young elements, are oriented head-on relative to replication forks in the mouse genome, creating an unfavorable genomic configuration8 that is preferentially targeted by DNA methylation maintenance. Mechanistically, DNA methylation maintenance is coupled to the lagging-strand replication via UHRF1-LIG19 and PCNA-PAF1510 interactions, and the interference in this mechanism slows Okazaki fragment maturation, and thereby potentially may facilitate TE retention. Together, we show a mechanism of TE control during DNA replication with an unexpected evolutionary interplay in which DNA methylation may facilitate, rather than solely prevent, TE expansion.

Molecular Biology↗

bioRxiv2026

Dual profiling of DNA modifications with enhancer features during the exit of naive pluripotency

Cis-regulatory elements, such as enhancers, play an essential role in coordinating gene expression programs during cellular transitions. As such, substantial efforts have been made to characterize enhancer elements, e.g., chromatin accessibility, transcription factor (TF) binding sites, histone post-translational modifications (PTMs), and 5-cytosine DNA methylation and hydroxymethylation (5mC and 5hmC). Elevated 5mC levels are typically correlated with the inactive enhancer state. However, whether 5mC precludes TF binding or is simply a downstream consequence of enhancer decommissioning is difficult to determine. Bulk genomics assays from cell populations fail to fully capture cellular heterogeneity, and single-cell assays often suffer from limited read counts per cell. Here, we leveraged tagmentation-based technologies to assess chromatin features with 5mC simultaneously: Methyl-ATAC and Methyl-CUT&Tag. In addition, we modified the technique to interrogate 5hmC dynamics (hM-ATAC). We employed these techniques during the exit of naive pluripotency in mouse embryonic stem cells (mESCs), which recapitulates the embryonic DNA methylation establishment program. This system withstands the complete absence of DNA methylation and demethylation machinery, allowing us to further dissect the temporal contributions of 5mC and 5hmC. Given the affordability of these techniques, we were able to obtain robust, dynamic single-molecule 5mC/5hmC information during this cellular transition for chromatin accessibility and histone marks in wild-type and mutant conditions. The sum of these data allowed for unprecedented insight into the role that 5mC turnover plays at enhancers during a key window of mammalian embryonic development.

Molecular Biology↗

bioRxiv2024

Upregulation of the AMPK-FOXO1-PDK4 pathway is a primary mechanism of pyruvate dehydrogenase activity reduction and leads to increased glucose uptake in tafazzin-deficient cells

Barth syndrome (BTHS) is a rare disorder caused by mutations in the TAFAZZIN gene. Previous studies from both patients and model systems have established metabolic dysregulation as a core component of BTHS pathology. In particular, features such as lactic acidosis, pyruvate dehydrogenase (PDH) deficiency, and aberrant fatty acid and glucose oxidation have been identified. However, the lack of a mechanistic understanding of what causes these conditions in the context of BTHS remains a significant knowledge gap, and this has hindered the development of effective therapeutic strategies for treating the associated metabolic problems. In the current study, we utilized tafazzin-knockout C2C12 mouse myoblasts (TAZ-KO) and cardiac and skeletal muscle tissue from tafazzin-knockout mice to identify an upstream mechanism underlying impaired PDH activity in BTHS. This mechanism centers around robust upregulation of pyruvate dehydrogenase kinase 4 (PDK4), resulting from hyperactivation of AMP-activated protein kinase (AMPK) and subsequent transcriptional upregulation by forkhead box protein O1 (FOXO1). Upregulation of PDK4 in tafazzin-deficient cells causes direct phospho-inhibition of PDH activity accompanied by increased glucose uptake and elevated intracellular glucose concentration. Collectively, our findings provide a novel mechanistic framework whereby impaired tafazzin function ultimately results in robust PDK4 upregulation, leading to impaired PDH activity and likely linked to dysregulated metabolic substrate utilization. This mechanism may underlie previously reported findings of BTHS-associated metabolic dysregulation.

cell biology↗

bioRxiv2023

The Bias of Using Cross-Validation in Genomic Predictions and Its Correction

Cross-validation (CV) is a widely used technique in statistical learning for model evaluation and selection. Meanwhile, various of statistical learning methods, such as Generalized Least Square (GLS), Linear Mixed-Effects Models (LMM), and regularization methods are commonly used in genomic predictions, a field that utilizes DNA polymorphisms to predict phenotypic traits. However, due to high dimensionality, relatively small sample sizes, and data sparsity in genomic data, CV in these scenarios may lead to an underestimation of the generalization error. In this work, we analyzed the bias of CV in eight methods: Ordinary Least Square (OLS), GLS, LMM, Lasso, Ridge, elastic-net (ENET), and two hybrid methods: one combining GLS with Ridge regularization (GLS+Ridge), and the other combining LMM with Ridge regularization (LMM+Ridge). Leveraging genomics data from the 1,000 Genomes Project and simulated phenotypes, our investigation revealed the presence of bias in all these methods. To address this bias, we adapted a variance-structure method known as Cross-Validation Correction (CVc). This approach aims to rectify the cross-validation error by providing a more accurate estimate of the generalization error. To quantify the performance of our adapted CVc towards all these methods, we applied the trained model to an independently generated dataset, which served as a gold standard for validating the models and calculating the generalization error. The outcomes show that, by leveraging CVc, we corrected the CV bias for most of the methods mentioned above, with two exceptions that are unrectifiable methods: ENET and Lasso. Our work revealed the substantial bias in the use of CV in genomics, a phenomenon under-appreciated by the field of statistical genomics and medicine. Additionally, we demonstrated that bias-corrected models may be formed by adapting CVc, although more work is needed to cover the full spectrum.

bioinformatics↗

bioRxiv2023

Thyroid hormone rewires cortical circuits to coordinate body-wide metabolism and exploratory drive

Animals adapt to varying environmental conditions by modifying the function of their internal organs, including the brain. To be adaptive, alterations in behavior must be coordinated with the functional state of organs throughout the body. Here we find that thyroid hormone-- a prominent regulator of metabolism in many peripheral organs-- activates cell-type specific transcriptional programs in anterior regions of cortex of adult mice via direct activation of thyroid hormone receptors. These programs are enriched for axon-guidance genes in glutamatergic projection neurons, synaptic regulators across both astrocytes and neurons, and pro-myelination factors in oligodendrocytes, suggesting widespread remodeling of cortical circuits. Indeed, whole-cell electrophysiology recordings revealed that thyroid hormone induces local transcriptional programs that rewire cortical neural circuits via pre-synaptic mechanisms, resulting in increased excitatory drive with a concomitant sensitization of recruited inhibition. We find that thyroid hormone bidirectionally regulates innate exploratory behaviors and that the transcriptionally mediated circuit changes in anterior cortex causally promote exploratory decision-making. Thus, thyroid hormone acts directly on adult cerebral cortex to coordinate exploratory behaviors with whole-body metabolic state.

neuroscience↗

bioRxiv2023

Gradient-based implementation of linear model outperforms deep learning models

Deep learning has been widely considered more effective than traditional statistical models in modeling biological complex data such as single-cell omics. Here we show the devil is hidden in details: by adapting a modern gradient solver to a traditional linear mixed model, we showed that conventional models can outperform deep models in terms of both speed and accuracy. This work reveals the potential of re-implementing traditional models with modern solvers.

bioinformatics↗

bioRxiv2023

Decapping factor Dcp2 controls mRNA abundance and translation to adjust metabolism and filamentation to nutrient availability

Degradation of most yeast mRNAs involves decapping by Dcp1/Dcp2. DEAD-box protein Dhh1 has been implicated as an activator of decapping, in coupling codon non-optimality to enhanced degradation, and as a translational repressor, but its functions in cells are incompletely understood. RNA-Seq analyses coupled with CAGE sequencing of all capped mRNAs revealed increased abundance of hundreds of mRNAs in dcp2{Delta} cells that appears to result directly from impaired decapping rather than elevated transcription, which was confirmed by ChIP-Seq analysis of RNA Polymerase II occupancies genome-wide. Interestingly, only a subset of mRNAs requires Dhh1 for targeting by Dcp2, and also generally requires the other decapping activators Pat1, Lsm2, Edc3 or Scd6; whereas most of the remaining transcripts utilize NMD factors for Dcp2-mediated turnover. Neither inefficient translation initiation nor stalled elongation appears to be a major driver of Dhh1-enhanced mRNA degradation. Surprisingly, ribosome profiling revealed that dcp2{Delta} confers widespread changes in relative TEs that generally favor well-translated mRNAs. Because ribosome biogenesis is reduced while capped mRNA abundance is increased by dcp2{Delta}, we propose that an increased ratio of mRNA to ribosomes increases competition among mRNAs for limiting ribosomes to favor efficiently translated mRNAs in dcp2{Delta} cells. Interestingly, genes involved in respiration or utilization of alternative carbon or nitrogen sources are derepressed, and both mitochondrial function and cell filamentation (a strategy for nutrient foraging) are elevated by dcp2{Delta}, suggesting that mRNA decapping sculpts gene expression post-transcriptionally to fine-tune metabolic pathways and morphological transitions according to nutrient availability.

molecular biology↗

bioRxiv2022

Isoforms of the transcriptional cofactor SIN3 differentially regulate genes necessary for energy metabolism and cell survival

The SIN3 scaffolding protein is a conserved transcriptional regulator known to fine-tune gene expression. In Drosophila, there are two major isoforms of SIN3, SIN3 220 and SIN3 187, which each assemble into multi-subunit histone modifying complexes. The isoforms have distinct developmental expression patterns and non-redundant functions. Gene regulatory network analyses indicate that both isoforms affect genes encoding proteins in pathways such as the cell cycle and cell morphogenesis. Interestingly, the SIN3 187 isoform uniquely regulates a subset of pathways including post-embryonic development, phosphate metabolism and apoptosis. Target genes in the phosphate metabolism pathway include nuclear-encoded mitochondrial genes coding for proteins responsible for oxidative phosphorylation. Here, we investigate the physiological effects of SIN3 isoforms on energy metabolism and cell survival. We find that ectopic expression of SIN3 187 represses expression of several nuclear-encoded mitochondrial genes affecting production of ATP and generation of reactive oxygen species (ROS). Forced expression of SIN3 187 also activates several pro-apoptotic and represses a few anti-apoptotic genes. In the SIN3 187 expressing cells, these gene expression patterns are accompanied with an increased sensitivity to paraquat-mediated oxidative stress. These findings indicate that SIN3 187 influences the regulation of mitochondrial function, apoptosis and oxidative stress response in ways that are dissimilar from SIN3 220. The data suggest that the distinct SIN3 histone modifying complexes are deployed in different cellular contexts to maintain homeostasis.

molecular biology↗

bioRxiv2021

Predictive Modeling of Pseudomonas syringae Virulence on Bean using Gradient Boosted Decision Trees

Pseudomonas syringae is a genetically diverse bacterial species complex responsible for numerous agronomically important crop diseases. Individual P. syringae isolates are typically given pathovar designations based on their host of isolation and the associated disease symptoms, and these pathovar designations are often assumed to reflect host specificity although this assumption has rarely been rigorously tested. Here we developed a rapid seed infection assay to measure the virulence of 121 diverse P. syringae isolates on common bean (Phaseolus vulgaris). This collection includes P. syringae phylogroup 2 (PG2) bean isolates (pathovar syringae) that cause bacterial spot disease and P. syringae phylogroup 3 (PG3) bean isolates (pathovar phaseolicola) that cause the more serious halo blight disease. We found that bean isolates in general were significantly more virulent on bean than non-bean isolates and observed no significant virulence difference between the PG2 and PG3 bean isolates. However, when we compared virulence within PGs we found that PG3 bean isolates were significantly more virulent than PG3 non-bean isolates, while there was no significant difference in virulence between PG2 bean and non-bean isolates. These results indicate that PG3 strains have a higher level of host specificity than PG2 strains. We then employed machine learning to investigate if we could use genomic data to predict virulence on bean. We used gradient boosted decision trees to model the virulence using whole genome kmers, type III secreted effector kmers, and the presence/absence of type III effectors and phytotoxins. Our model performed best using whole genome data and was able to predict virulence with high accuracy (mean absolute error = 0.05). Finally, we functionally validated the model by predicting virulence for 16 strains and found that 15 (94%) had virulence levels within the bounds of estimated predictions. This study demonstrates the power of machine learning for predicting host specific adaptation and strengthens the hypothesis that P. syringae PG2 strains have evolved a different lifestyle than other P. syringae strains. AUTHOR SUMMARYPseudomonas syringae is a genetically diverse Gammaproteobacterial species complex responsible for numerous agronomically important crop diseases. Strains in the P. syringae species complex are frequently categorized into pathovars depending on pathogenic characteristics such as host of isolation and disease symptoms. Common bean pathogens from P. syringae are known to cause two major diseases: the halo blight disease, which is characterized by large necrotic lesions surrounded by a chlorotic zone or halo of yellow tissue; and the bacterial spot disease, which is characterized by brown leaf spots. While halo blight can cause serious crop losses, bacterial spot disease is generally of minor agronomic concern. The application of statistical genetic and machine learning approaches to genomic data has greatly increased our power to identify genes underlying traits of interest, such as host specificity. Machine learning models can be used to predict outcomes from new samples or to identify the genetic feature(s) that carry the most importance when predicting a particular phenotype. Here, we implemented a rapid method for screening a proxy of virulence for P. syringae isolates on common bean, and used this screen to assess virulence of P. syringae strains on bean. We found that halo blight pathogens display a stronger degree of host specificity compared to brown spot pathogens, and that genomic kmers and virulence factors can be used to predict the virulence of P. syringae isolates on bean using machine learning models.

genomics↗

bioRxiv2021

TNF Blockade Reduces Prostatic Hyperplasia and Inflammation while Limiting BPH Diagnosis in Patients with Autoimmune Disease

Benign prostatic hyperplasia (BPH) is ostensibly linked to autoimmune (AI) diseases, but whether the prostate is a target of systemic inflammation associated with AI conditions is unknown. Prostatic inflammation is linked to fibrosis, hyperplasia, and reduced responses to BPH-related medical therapies. This study was conducted to determine if AI disease correlates with BPH diagnosis and whether systemic targeting of an inflammatory mediator limits prostatic inflammation and hyperplasia. Patient medical records (n=112,152) were evaluated to determine BPH prevalence among different AI diseases. Inflammatory cells from human BPH tissues were analyzed by single-cell (sc)RNA-seq and the tumor necrosis factor (TNF)-antagonist etanercept was tested in two murine models of prostatic enlargement. BPH prevalence was significantly higher among patients with AI disease compared to unaffected individuals. However, AI patients treated with TNF-antagonists had a significantly reduced incidence of BPH. Data from scRNA- seq identified macrophages as a dominant source of TNF and in vitro assays confirmed that TNF stimulates BPH-derived fibroblast proliferation. In the AI patient cohort and murine models, systemic treatment with TNF-antagonists decreased prostatic epithelial proliferation, macrophage infiltration, and epithelial NF{kappa}B activation compared to control tissues. These studies are the first to show that patients with AI diseases have a heightened susceptibility to BPH and that the TNF-signaling axis is important for BPH pathogenesis. Macrophage-secreted TNF may mechanistically drive BPH via chronic activation of the signaling axis and NF{kappa}B. TNF blockade appears to be a promising new pharmacological approach to target inflammation and suppress BPH. One sentence summaryPatient data and mouse models suggest that repurposing tumor necrosis factor alpha blockade reduces inflammation-mediated prostatic hyperplasia.

cell biology↗

bioRxiv2020

PARprolink: a photoaffinity probe for identifying poly(ADP-ribose)-binding proteins

Post-translational modification of proteins with poly(ADP-ribose) (PAR) is an important component of the DNA damage response. Four PAR synthesis inhibitors have recently been approved for the treatment of breast, ovarian, and prostate cancers. Despite its clinical significance, a molecular understanding of PAR function, including its binding partners, remains incomplete. In this work, we synthesize a PAR photoaffinity probe that captures and isolates endogenous PAR binders. Our method identified dozens of known PAR-binding proteins and hundreds of novel binders involved in DNA repair, RNA processing, and metabolism. PAR binding by eight candidates was confirmed using pull-down and/or electrophoretic mobility shift assays. Using PAR probes of defined lengths, we detected proteins that preferentially bind to 40-mer over 8-mer PAR, indicating that polymer length may regulate the outcome and timing of PAR signaling pathways. This investigation produces the first census of PAR-binding proteins, provides a proteome-wide view of length-selective PAR binding, and associates PAR binding with RNA metabolism and the formation of biomolecular condensates.

molecular biology↗

bioRxiv2020

WgLink: reconstructing whole-genome viral haplotypes using L0+L1-regularization

Many tools can reconstruct viral sequences based on next generation sequencing reads. Although existing tools effectively recover local regions, their accuracy suffers when reconstructing the whole viral genomes (strains). Moreover, they consume significant memory when the sequencing coverage is high or when the genome size is large. We present WgLink to meet this challenge. WgLink takes local reconstructions produced by other tools as input and patches the resulting segments together into coherent whole-genome strains. We accomplish this using an L0 + L1-regularized regression synthesizing variant allele frequency data with physical linkage between multiple variants spanning multiple regions simultaneously. WgLink achieves higher accuracy than existing tools both on simulated and real data sets while using significantly less memory (RAM) and fewer CPU hours. Source code and binaries are freely available at https://github.com/theLongLab/wglink.

bioinformatics↗

bioRxiv2020

kTWAS: integrating kernel-machine with transcriptome-wide association studies improves statistical power and reveals novel genes

The power of genotype-phenotype association mapping studies increases greatly when contributions from multiple variants in a focal region are meaningfully aggregated. Currently, there are two popular categories of variant aggregation methods. Transcriptome-wide association studies (TWAS) represent a category of emerging methods that select variants based on their effect on gene expressions, providing pretrained linear combinations of variants for downstream association mapping. In contrast, kernel methods such as SKAT model genotypic and phenotypic variance using various kernel functions that capture genetic similarity between subjects, allowing non-linear effects to be included. From the perspective of machine learning, these two methods cover two complementary aspects of feature engineering: feature selection/pruning, and feature modeling. Thus far, no thorough comparison has been made between these categories, and no methods exist which incorporate the advantages of TWAS and kernel-based methods. In this work we developed a novel method called kTWAS that applies TWAS-like feature selection to a SKAT-like kernel association test, combining the strengths of both approaches. Through extensive simulations, we demonstrate that kTWAS has higher power than TWAS and multiple SKAT-based protocols, and we identify novel disease-associated genes in WTCCC genotyping array data and MSSNG (Autism) sequence data. The source code for kTWAS and our simulations are available in our GitHub repository (https://github.com/theLongLab/kTWAS).

bioinformatics↗

bioRxiv2020

De novo reconstruction of microbial haplotypes by integrating statistical and physical linkage

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or haplotypes. However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

bioinformatics↗

bioRxiv2019

Injection molded open microfluidic well plate inserts for user-friendly coculture and microscopy

Open microfluidic cell culture systems are powerful tools for interrogating biological mechanisms. We have previously presented a microscale cell culture system, based on spontaneous capillary flow of biocompatible hydrogels, that is integrated into a standard cell culture well plate, with flexible cell compartment geometries and easy pipet access. Here, we present two new injection molded open microfluidic devices that also easily insert into standard cell culture well plates and standard culture workflows, allowing seamless adoption by biomedical researchers. These platforms allow culture and study of soluble factor communication among multiple cell types, and the microscale dimensions are well-suited for rare primary cells. Unique advances include optimized evaporation control within the well, manufacture with reproducible and cost-effective rapid injection molding, and compatibility with sample preparation workflows for high resolution microscopy (following well-established coverslip mounting procedures). In this work, we present several use cases that highlight the usability and widespread utility of our platform including culture of limited primary testis cells from surgical patients, microscopy readouts including immunocytochemistry and single molecule fluorescence in situ hybridization (smFISH), and coculture to study interactions between adipocytes and prostate cancer cells.

bioengineering↗

bioRxiv2019

Discovery of tumoricidal DNA aptamers by effect-directed in-vitro evolution

Our current model of drug discovery is challenged by the relative ineffectiveness of drugs against highly variable and rapidly evolving diseases and their relatively high incidence of adverse effects due to poor selectivity. Here we describe a robust and reproducible platform which could potentially address these limitations. The platform enables rapid, de-novo discovery of DNA oligonucleotides evolved in-vitro to exert specific biological effects on target cells. Unlike aptamers, which are selected by their ligand binding capacity, this platform is driven directly by therapeutic effect and selectivity towards target vs negative target cells. The process could, therefore, operate without any a-priori knowledge (e.g. mutations, biomarker expression, or known drug resistance) of the target. We report the discovery of DNA oligonucleotides with direct and selective cytotoxicity towards several tumor cell lines as well as primary, patient-derived solid and hematological tumors, some with chemotherapy resistance. Oligonucleotides discovered by this platform exhibited favorable biodistribution in animals, persistence in target tumors up to 48 hours after injection, and safety in human blood. These oligonucleotides showed remarkable efficacy in-vivo as well as ex-vivo in freshly obtained, 3D cultured human tumors resistant to multiple chemotherapies. With further improvement, these findings could lead to a drug discovery model which is target-tailored, mechanism-flexible, and nearly on-demand.

synthetic biology↗

bioRxiv2018

Dynamic enhancer partitioning instructs activation of a growth regulator during exit from naïve pluripotency

During early mammalian development, the genome undergoes profound transitions in chromatin states, topological organization and recruitment of cis regulatory factors involved in transcriptional control. How these three layers of gene regulation interact is the matter of intense research. The Zdbf2 gene--which is involved in growth control--provides a valuable model to study this question: upon exit from naive pluripotency and prior to tissue differentiation, it undergoes a switch in usage from a distal to a proximal promoter, along with a switch in chromatin states, from polycomb to DNA methylation occupancy. Using an embryonic stem cell (ESC) culture system to mimic this period, we show here that four enhancers contribute to the Zdbf2 promoter switch, concomitantly with dynamic changes in chromosome architecture. Indeed, CTCF plays a key role in partitioning the locus in ESCs, to facilitate enhancer contact with the distal Zdbf2 promoter only. Partition relieving enhances proximal Zdbf2 promoter activity, as observed during differentiation or with mutants that lack local CTCF-based partition. Importantly, we show that CTCF-based regulation occurs independently of the polycomb and DNA methylation pathways. Our study reveals the importance of multi-layered regulatory frameworks to ensure proper spatio-temporal activation of developmentally important genes.

molecular biology↗