Human microglia maturation is underpinned by specific gene regulatory networks.

Microglia phenotypes are highly regulated by the brain environment, but the transcriptional networks that specify the maturation of human microglia are poorly understood. Here, we characterized stage-specific transcriptomes and epigenetic landscapes of fetal and postnatal human microglia and acquired corresponding data in induced pluripotent stem cell (iPSC)-derived microglia, in cerebral organoids, and following engraftment into humanized mice. Parallel development of computational approaches that considered transcription factor (TF) co-occurrence and enhancer activity allowed prediction of shared and state-specific gene regulatory networks associated with fetal and postnatal microglia. Additionally, many features of the human fetal-to-postnatal transition were recapitulated in a time-dependent manner following the engraftment of iPSC cells into humanized mice. These data and accompanying computational approaches will facilitate further efforts to elucidate mechanisms by which human microglia acquire stage- and disease-specific phenotypes.

DNA methyltransferase 3 alpha and TET methylcytosine dioxygenase 2 restrain mitochondrial DNA-mediated interferon signaling in macrophages.

Deleterious somatic mutations in DNA methyltransferase 3 alpha (DNMT3A) and TET mehtylcytosine dioxygenase 2 (TET2) are associated with clonal expansion of hematopoietic cells and higher risk of cardiovascular disease (CVD). Here, we investigated roles of DNMT3A and TET2 in normal human monocyte-derived macrophages (MDM), in MDM isolated from individuals with DNMT3A or TET2 mutations, and in macrophages isolated from human atherosclerotic plaques. We found that loss of function of DNMT3A or TET2 resulted in a type I interferon response due to impaired mitochondrial DNA integrity and activation of cGAS signaling. DNMT3A and TET2 normally maintained mitochondrial DNA integrity by regulating the expression of transcription factor A mitochondria (TFAM) dependent on their interactions with RBPJ and ZNF143 at regulatory regions of the TFAM gene. These findings suggest that targeting the cGAS-type I IFN pathway may have therapeutic value in reducing risk of CVD in patients with DNMT3A or TET2 mutations.

Niche-Specific Reprogramming of Epigenetic Landscapes Drives Myeloid Cell Diversity in Nonalcoholic Steatohepatitis.

Tissue-resident and recruited macrophages contribute to both host defense and pathology. Multiple macrophage phenotypes are represented in diseased tissues, but we lack deep understanding of mechanisms controlling diversification. Here, we investigate origins and epigenetic trajectories of hepatic macrophages during diet-induced non-alcoholic steatohepatitis (NASH). The NASH diet induced significant changes in Kupffer cell enhancers and gene expression, resulting in partial loss of Kupffer cell identity, induction of Trem2 and Cd9 expression, and cell death. Kupffer cell loss was compensated by gain of adjacent monocyte-derived macrophages that exhibited convergent epigenomes, transcriptomes, and functions. NASH-induced changes in Kupffer cell enhancers were driven by AP-1 and EGR that reprogrammed LXR functions required for Kupffer cell identity and survival to instead drive a scar-associated macrophage phenotype. These findings reveal mechanisms by which disease-associated environmental signals instruct resident and recruited macrophages to acquire distinct gene expression programs and corresponding functions.

TIANA: transcription factors cooperativity inference analysis with neural attention.

BACKGROUND: Growing evidence suggests that distal regulatory elements are essential for cellular function and states. The sequences within these distal elements, especially motifs for transcription factor binding, provide critical information about the underlying regulatory programs. However, cooperativities between transcription factors that recognize these motifs are nonlinear and multiplexed, rendering traditional modeling methods insufficient to capture the underlying mechanisms. Recent development of attention mechanism, which exhibit superior performance in capturing dependencies across input sequences, makes them well-suited to uncover and decipher intricate dependencies between regulatory elements. RESULT: We present Transcription factors cooperativity Inference Analysis with Neural Attention (TIANA), a deep learning framework that focuses on interpretability. In this study, we demonstrated that TIANA could discover biologically relevant insights into co-occurring pairs of transcription factor motifs. Compared with existing tools, TIANA showed superior interpretability and robust performance in identifying putative transcription factor cooperativities from co-occurring motifs. CONCLUSION: Our results suggest that TIANA can be an effective tool to decipher transcription factor cooperativities from distal sequence data. TIANA can be accessed through: https://github.com/rzzli/TIANA .

Heterogeneity of HSCs in a Mouse Model of NASH.

BACKGROUND AND AIMS: In clinical and experimental NASH, the origin of the scar-forming myofibroblast is the HSC. We used foz/foz mice on a Western diet to characterize in detail the phenotypic changes of HSCs in a NASH model. APPROACH AND RESULTS: We examined the single-cell expression profiles (scRNA sequencing) of HSCs purified from the normal livers of foz/foz mice on a chow diet, in NASH with fibrosis of foz/foz mice on a Western diet, and in livers during regression of NASH after switching back to a chow diet. Selected genes were analyzed using immunohistochemistry, quantitative real-time PCR, and short hairpin RNA knockdown in primary mouse HSCs. Our analysis of the normal liver identified two distinct clusters of quiescent HSCs that correspond to their acinar position of either pericentral vein or periportal vein. The NASH livers had four distinct HSC clusters, including one representing the classic fibrogenic myofibroblast. The three other HSC clusters consisted of a proliferating cluster, an intermediate activated cluster, and an immune and inflammatory cluster. The livers with NASH regression had one cluster of inactivated HSCs, which was similar to, but distinct from, the quiescent HSCs. CONCLUSIONS: Analysis of single-cell RNA sequencing in combination with an interrogation of previous studies revealed an unanticipated heterogeneity of HSC phenotypes under normal and injured states.

Systematic analysis of naturally occurring insertions and deletions that alter transcription factor spacing identifies tolerant and sensitive transcription factor pairs.

Regulation of gene expression requires the combinatorial binding of sequence-specific transcription factors (TFs) at promoters and enhancers. Prior studies showed that alterations in the spacing between TF binding sites can influence promoter and enhancer activity. However, the relative importance of TF spacing alterations resulting from naturally occurring insertions and deletions (InDels) has not been systematically analyzed. To address this question, we first characterized the genome-wide spacing relationships of 73 TFs in human K562 cells as determined by ChIP-seq (chromatin immunoprecipitation sequencing). We found a dominant pattern of a relaxed range of spacing between collaborative factors, including 45 TFs exclusively exhibiting relaxed spacing with their binding partners. Next, we exploited millions of InDels provided by genetically diverse mouse strains and human individuals to investigate the effects of altered spacing on TF binding and local histone acetylation. These analyses suggested that spacing alterations resulting from naturally occurring InDels are generally tolerated in comparison to genetic variants directly affecting TF binding sites. To experimentally validate this prediction, we introduced synthetic spacing alterations between PU.1 and C/EBPß binding sites at six endogenous genomic loci in a macrophage cell line. Remarkably, collaborative binding of PU.1 and C/EBPß at these locations tolerated changes in spacing ranging from 5 bp increase to >30 bp decrease. Collectively, these findings have implications for understanding mechanisms underlying enhancer selection and for the interpretation of non-coding genetic variation.