Genomic Decoding of Neuronal Depolarization by Stimulus-Specific NPAS4 Heterodimers.

Cells regulate gene expression in response to salient external stimuli. In neurons, depolarization leads to the expression of inducible transcription factors (ITFs) that direct subsequent gene regulation. Depolarization encodes both a neuron's action potential (AP) output and synaptic inputs, via excitatory postsynaptic potentials (EPSPs). However, it is unclear if distinct types of electrical activity can be transformed by an ITF into distinct modes of genomic regulation. Here, we show that APs and EPSPs in mouse hippocampal neurons trigger two spatially segregated and molecularly distinct induction mechanisms that lead to the expression of the ITF NPAS4. These two pathways culminate in the formation of stimulus-specific NPAS4 heterodimers that exhibit distinct DNA binding patterns. Thus, NPAS4 differentially communicates increases in a neuron's spiking output and synaptic inputs to the nucleus, enabling gene regulation to be tailored to the type of depolarizing activity along the somato-dendritic axis of a neuron.

Transcription Elongation Can Affect Genome 3D Structure.

How transcription affects genome 3D organization is not well understood. We found that during influenza A (IAV) infection, rampant transcription rapidly reorganizes host cell chromatin interactions. These changes occur at the ends of highly transcribed genes, where global inhibition of transcription termination by IAV NS1 protein causes readthrough transcription for hundreds of kilobases. In these readthrough regions, elongating RNA polymerase II disrupts chromatin interactions by inducing cohesin displacement from CTCF sites, leading to locus decompaction. Readthrough transcription into heterochromatin regions switches them from the inert (B) to the permissive (A) chromatin compartment and enables transcription factor binding. Data from non-viral transcription stimuli show that transcription similarly affects cohesin-mediated chromatin contacts within gene bodies. Conversely, inhibition of transcription elongation allows cohesin to accumulate at previously transcribed intragenic CTCF sites and to mediate chromatin looping and compaction. Our data indicate that transcription elongation by RNA polymerase II remodels genome 3D architecture.

Liver-Derived Signals Sequentially Reprogram Myeloid Enhancers to Initiate and Maintain Kupffer Cell Identity.

Tissue environment plays a powerful role in establishing and maintaining the distinct phenotypes of resident macrophages, but the underlying molecular mechanisms remain poorly understood. Here, we characterized transcriptomic and epigenetic changes in repopulating liver macrophages following acute Kupffer cell depletion as a means to infer signaling pathways and transcription factors that promote Kupffer cell differentiation. We obtained evidence that combinatorial interactions of the Notch ligand DLL4 and transforming growth factor-b (TGF-ß) family ligands produced by sinusoidal endothelial cells and endogenous LXR ligands were required for the induction and maintenance of Kupffer cell identity. DLL4 regulation of the Notch transcriptional effector RBPJ activated poised enhancers to rapidly induce LXRα and other Kupffer cell lineage-determining factors. These factors in turn reprogrammed the repopulating liver macrophage enhancer landscape to converge on that of the original resident Kupffer cells. Collectively, these findings provide a framework for understanding how macrophage progenitor cells acquire tissue-specific phenotypes.

Longitudinal Human Milk miRNA Composition over the First 3 mo of Lactation in a Cohort of Healthy Mothers Delivering Term Infants.

BACKGROUND: MicroRNAs (miRNAs) are small noncoding RNAs involved in posttranscriptional regulation. miRNAs can be secreted and found in many body fluids, and although they are particularly abundant in breastmilk, their functions remain elusive. Human milk (HM) miRNAs start to raise considerable interest, but a comprehensive understanding of the repertoire and expression profiles along lactation has not been well characterized. OBJECTIVES: This study aimed to characterize the longitudinal profile of HM miRNA between the second week and third month postpartum. METHODS: We used a new sensitive technology to measure HM miRNAs in a cohort of 44 French mothers [mean ± SD age: 31 ± 3.5; BMI (in kg/m2) 21.8 ± 2.3] who delivered at term and provided HM samples at 3 time points (17 ± 3 d, 60 ± 3 d, and 90 ± 3 d) during follow-up visits. RESULTS: We detected 685 miRNAs, of which 35 showed a high and stable expression along the lactation period analyzed. We also described for the first time a set of 11 miRNAs with a dynamic expression profile. To gain insight into the potential functional relevance of this set of miRNAs, we selected miR-3126 and miR-3184 to treat undifferentiated Caco-2 human intestinal cells and then assessed differentially expressed genes and modulation of related biological pathways. CONCLUSIONS: Overall, our study provides new insights into HM miRNA composition and, to our knowledge, the first description of its longitudinal dynamics in mothers who delivered at term. Our in vitro results obtained in undifferentiated Caco-2 human intestinal cells transfected with HM miRNAs also provide further support to the hypothesized mother-to-neonate signaling role of HM miRNAs. This trial was registered at clinicaltrials.gov as NCT01894893.

The nuclear pore regulates GAL1 gene transcription by controlling the localization of the SUMO protease Ulp1.

Transcription activation of some yeast genes correlates with their repositioning to the nuclear pore complex (NPC). The NPC-bound Mlp1 and Mlp2 proteins have been shown to associate with the GAL1 gene promoter and to maintain Ulp1, a key SUMO protease, at the NPC. Here, we show that the release of Ulp1 from the NPC increases the kinetics of GAL1 derepression, whereas artificial NPC anchoring of Ulp1 in the Δmlp1/2 strain restores normal GAL1 regulation. Moreover, artificial tethering of the Ulp1 catalytic domain to the GAL1 locus enhances the derepression kinetics. Our results also indicate that Ulp1 modulates the sumoylation state of Tup1 and Ssn6, two regulators of glucose-repressed genes, and that a loss of Ssn6 sumoylation correlates with an increase in GAL1 derepression kinetics. Altogether, our data highlight a role for the NPC-associated SUMO protease Ulp1 in regulating the sumoylation of gene-bound transcription regulators, positively affecting transcription kinetics in the context of the NPC.

MEIRLOP: improving score-based motif enrichment by incorporating sequence bias covariates.

BACKGROUND: Motif enrichment analysis (MEA) identifies over-represented transcription factor binding (TF) motifs in the DNA sequence of regulatory regions, enabling researchers to infer which transcription factors can regulate transcriptional response to a stimulus, or identify sequence features found near a target protein in a ChIP-seq experiment. Score-based MEA determines motifs enriched in regions exhibiting extreme differences in regulatory activity, but existing methods do not control for biases in GC content or dinucleotide composition. This lack of control for sequence bias, such as those often found in CpG islands, can obscure the enrichment of biologically relevant motifs. RESULTS: We developed Motif Enrichment In Ranked Lists of Peaks (MEIRLOP), a novel MEA method that determines enrichment of TF binding motifs in a list of scored regulatory regions, while controlling for sequence bias. In this study, we compare MEIRLOP against other MEA methods in identifying binding motifs found enriched in differentially active regulatory regions after interferon-beta stimulus, finding that using logistic regression and covariates improves the ability to call enrichment of ISGF3 binding motifs from differential acetylation ChIP-seq data compared to other methods. Our method achieves similar or better performance compared to other methods when quantifying the enrichment of TF binding motifs from ENCODE TF ChIP-seq datasets. We also demonstrate how MEIRLOP is broadly applicable to the analysis of numerous types of NGS assays and experimental designs. CONCLUSIONS: Our results demonstrate the importance of controlling for sequence bias when accurately identifying enriched DNA sequence motifs using score-based MEA. MEIRLOP is available for download from https://github.com/npdeloss/meirlop under the MIT license.

Sumoylation and transcription regulation at nuclear pores.

Increasing evidence indicates that besides promoters, enhancers, and epigenetic modifications, nuclear organization is another parameter contributing to optimal control of gene expression. Although differences between species exist, the influence of gene positioning on expression seems to be a conserved feature from yeast to Drosophila and mammals. The nuclear periphery is one of the nuclear compartments implicated in gene regulation. It consists of the nuclear envelope (NE) and the nuclear pore complexes (NPC), which have distinct roles in the control of gene expression. The NPC has recently been shown to tether proteins involved in the sumoylation pathway. Here, we will focus on the importance of gene positioning and NPC-linked sumoylation/desumoylation in transcription regulation. We will mainly discuss observations made in the yeast Saccharomyces cerevisiae model system and highlight potential parallels in metazoan species.

An optimized protocol for rapid, sensitive and robust on-bead ChIP-seq from primary cells.

Integrative analysis of next-generation sequencing data can help understand disease mechanisms. Specifically, ChIP-seq can illuminate where transcription regulators bind to regulate transcription. A major obstacle to performing this assay on primary cells is the low numbers obtained from tissues. The extensively validated ChIP-seq protocol presented here uses small volumes and single-pot on-bead library preparation to generate diverse high-quality ChIP-seq data. This protocol allows for medium-to-high-throughput ChIP-seq of low-abundance cells and can also be applied to other mammalian cells. For complete details on the use and execution of this protocol, please refer to Brigidi et al. (2019), Carlin et al. (2018), Heinz et al. (2018), Nott et al. (2019), Sakai et al. (2019), and Seidman et al. (2020).