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Essential contributions of enhancer genomic regulatory elements to microglial cell identity and functions

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Abstract Microglia are the specialized macrophages of the brain and play essential roles in ensuring its proper functioning. Accumulating evidence suggests that these cells coordinate the inflammatory response that accompanies various clinical brain conditions, including neurodegenerative diseases and psychiatric disorders. Therefore, investigating the functions of these cells and how these are regulated have become important areas of research in neuroscience over the past decade. In this regards, recent efforts to characterize the epigenomic mechanisms underlying microglial gene transcription have provided significant insights into the mechanisms that control the ontogeny and the cellular competences of microglia. In particular, these studies have established that a substantial proportion of the microglial repertoire of promoter‐distal genomic regulatory elements, or enhancers, is relatively specific to these cells compared to other tissue‐resident macrophages. Notably, this specificity is under the regulation of factors present in the brain that modulate activity of target axes of signaling pathways—transcription factors in microglia. Thus, the microglial enhancer repertoire is highly responsive to perturbations in the cerebral tissue microenvironment and this responsiveness has profound implications on the activity of these cells in brain diseases. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Mechanistic Models Biological Mechanisms > Cell Fates Developmental Biology > Lineages
The microglial enhancer repertoire includes both primed and activated regulatory elements. H3K4me2 and H3K27ac ChIP‐seq data visualization in the vicinity of the mouse Ccr3, Ccr2, and Ccr5 gene loci. H3K4me2 peaks (top track) enables identification of regulatory elements, including promoters and enhancers, that are active or primed for activation. Transcriptional start sites (arrows) allows for identification of protein‐coding gene promoters. Alternatively, assessment of H3K27ac levels (bottom track) enables identification of active regulatory elements. Note that not all H3K4me2High regions are abundant for H3K27ac
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The hierarchal and collaborative model of macrophage enhancer selection. (a) In absence of macrophage lineage‐determining transcription factors (LDTFs), DNA interacts tightly with nucleosomes, which inhibits interactions of signal‐dependent transcription factors (SDTFs) like NF‐κB with their DNA motifs. (b) As macrophage progenitors develop and differentiate, gene encoding LDTFs, including Pu.1, C/ebp and AP‐1 factors, become up‐regulated. In turn, these factors recognize and interact with their DNA motifs, which causes local nucleosomal rearrangement and recruitment of methyltransferases that will modify nearby nucleosomes (e.g., H3K4me1), thus setting up enhancers. Note, however, that certain parameters influence the ability of LDTFs to select enhancers; for example, LDTF motifs that are too far apart will not favor local LDTF activity. (c) Activated SDTFs can bind their motifs at primed enhancers, and this leads to gains in acetylation at nearby nucleosomes (e.g., H3K27ac). Activated enhancers then relay regulatory input from SDTFs to the transcriptional machinery at transcriptional start site of protein‐coding genes (not depicted)
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Brain‐derived factors activate signal‐dependent transcription factors that collaborate with Pu.1 to configure the microglial enhancer landscape that underlies their transcriptional signature. (A) Factors present in the brain microenvironment regulate activity of SDTFs that activate pre‐established enhancers to promote a first wave of gene transcription (B). (C) These include, among others, transcription factors that in turn can also collaborate with Pu.1 to set‐up new enhancers which further refine the transcriptional output of the microglial cells (D)
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Combination of cellular origin and developmental history enables optimal microglia cell ontogeny. Putative microglia are derived from yolk‐sac progenitors that seed the developing brain early during embryonic development. Therefore, these progenitors/early microglia are necessarily exposed to all the factors that are required for brain development and functions. These factors act in combination to activate signaling pathways in the developing microglial cell population and this enables these cells to achieve their full canonical transcriptional signature. Similarly, cells derived from definitive hematopoiesis, including monocytes, can engraft in the parenchymal brain under defined conditions and acquire some phenotypic traits associated with microglia, including the deployment of an elaborate array of ramifications. However, although the gene expression program of these monocyte‐derived microglia exhibits similarities with that of microglia, it never achieves full duplication. Whether this limitation on transcriptional plasticity arises from timing of their engraftment in the brain, which occurs outside of the development period, or because of different cellular ontological process is currently not known
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Microglial gene signatures are coupled to brain physiological states. Under healthy brain condition, genes involved in microglial homeostatic cell activity are highly transcribed. Notably, many of those genes are relatively highly expressed compared to other tissue‐resident macrophage subsets and make‐up the microglial transcriptional signature. However, in contexts of lesions, this homeostatic gene signature diminishes. Alternatively, disease‐associated microglia, or DAM, up‐regulate genes that are intrinsically linked to inflammation which enable these cells to acquire new inflammatory functions. Depending upon the type of insult, the inflammatory activity of microglia may be beneficial (e.g., elimination of infectious agents) or detrimental (e.g., chronic inflammatory activity of microglia, as is the case with neurodegenerative diseases)
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Developmental Biology > Lineages
Models of Systems Properties and Processes > Mechanistic Models
Physiology > Mammalian Physiology in Health and Disease
Biological Mechanisms > Cell Fates

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