Bioactive lipids are critical regulators of inflammation. Over the last 75 years, these diverse compounds have emerged as clinically-relevant mediators of allergic disease pathophysiology. Animal and human studies have demonstrated the importance of lipid mediators in the development of asthma, allergic rhinitis, urticaria, anaphylaxis, atopic dermatitis, and food allergy. Lipids are critical participants in cell signaling events which influence key physiologic (bronchoconstriction) and immune phenomena (degranulation, chemotaxis, sensitization). Lipid-mediated cellular mechanisms including: (1) formation of structural support platforms (lipid rafts) for receptor signaling complexes, (2) activation of a diverse family of G-protein coupled receptors, and (3) mediating intracellular signaling cascades by acting as second messengers. Here, we review four classes of bioactive lipids (platelet activating factor, the leukotrienes, the prostanoids, and the sphingolipids) with special emphasis on lipid synthesis pathways and signaling, atopic disease pathology, and the ongoing development of atopy treatments targeting lipid mediator pathways.

Genome-wide association studies of Systemic Lupus Erythematosus (SLE) nominate 3073 genetic variants at 91 risk loci. To systematically screen these variants for allelic transcriptional enhancer activity, we construct a massively parallel reporter assay (MPRA) library comprising 12,396 DNA oligonucleotides containing the genomic context around every allele of each SLE variant. Transfection into the Epstein-Barr virus-transformed B cell line GM12878 reveals 482 variants with enhancer activity, with 51 variants showing genotype-dependent (allelic) enhancer activity at 27 risk loci. Comparison of MPRA results in GM12878 and Jurkat T cell lines highlights shared and unique allelic transcriptional regulatory mechanisms at SLE risk loci. In-depth analysis of allelic transcription factor (TF) binding at and around allelic variants identifies one class of TFs whose DNA-binding motif tends to be directly altered by the risk variant and a second class of TFs that bind allelically without direct alteration of their motif by the variant. Collectively, our approach provides a blueprint for the discovery of allelic gene regulation at risk loci for any disease and offers insight into the transcriptional regulatory mechanisms underlying SLE.

Background: Kabuki syndrome (KS) is commonly caused by mutations in the histone-modifying enzyme lysine methyltransferase 2D (KMT2D). Immune dysfunction is frequently observed in individuals with KS, but the role of KMT2D in immune system function has not been identified. Objective: We sought to understand the mechanisms driving KS-associated immune deficiency (hypogammaglobulinemia [low IgA], splenomegaly, and diminished immunization responses). Methods: We performed a comprehensive evaluation of humoral immunity and secondary lymphoid tissues in an established KS (Kmt2d 1/bGeo) mouse model and validated select findings in a patient with KS. Results: Compared with wild-type littermates, Kmt2d 1/bGeo mice demonstrated deficiencies in multiple B-cell lineages and reduced serum IgA and elevated IgM levels across multiple ages. The bone marrow, spleen, and intestine of Kmt2d 1/bGeo mice contained diminished numbers of IgA-secreting cells, while elevated germinal center B cells were found in the mesenteric lymph node and Peyer patches. Kmt2d 1/bGeo mice have decreased size and numbers of Peyer patches, a finding confirmed in human samples. We identified deficiency of Itgb7 RNA and protein expression, a gene encoding an adhesion protein that mediates intestinal homing, and we demonstrated KMT2D-dependent control of ITGB7 expression in a human cell line. Conclusions: Kmt2d haploinsufficiency has broad deleterious effects on B-cell differentiation, specifically hampering gut lymphocyte homing and IgA 1 plasma cell differentiation. Intestinal lymphoid defects caused by ITGB7 deficiency have not previously been recognized in KS, and these results provide new mechanistic insights into the pathogenesis of KS-associated immune deficiency.

Aging profoundly affects immune system function, rendering the elderly more susceptible to pathogens, cancers and chronic inflammation. We previously identified a population of IL-10-producing, T follicular helper-like cells ("Tfh10"), linked to suppressed vaccine responses in aged mice. Here, we use the power of single-cell (sc)genomics and genome-scale modeling to characterize Tfh10 — and the full CD4+memory T cell (CD4+TM) compartment — in young and old mice. Unprecedented scRNA-seq coverage of the CD4+TM compartment and parallel chromatin accessibility measurements (scATAC-seq) enabled identification of 13 CD4+TM populations, which we validated as a reference through comprehensive cross-comparison to aging cell atlases and scRNA-seq studies reporting Tfh10 in other contexts. Beyond robust characterization of age- and cell-type-dependent transcriptional landscapes, we used integrative computational modeling to predict the underlying regulatory mechanisms: We inferred gene regulatory networks (GRNs) that describe transcription-factor control of gene expression in each T-cell population and how these circuits change with age. Furthermore, we integrated our data with prior, pan-cell scRNA-seq studies to identify intercellular-signaling networks driving age-dependent changes in CD4+TM. Our atlas of finely resolved CD4+TM subsets, GRNs and cell-cell communication networks is a critical resource for analysis of biologic processes operative in memory T cells in youth and old age. The resource presents new opportunities to manipulate regulatory circuits in CD4+TM, which, long-term, could improve immune responses in the elderly.

Transcription factors read the genome, fundamentally connecting DNA sequence to gene expression across diverse cell types. Determining how, where, and when TFs bind chromatin will advance our understanding of gene regulatory networks and cellular behavior. The 2017 ENCODE-DREAM in vivo Transcription-Factor Binding Site (TFBS) Prediction Challenge highlighted the value of chromatin accessibility data to TFBS prediction, establishing state-of-the- art methods. Yet, while Assay-for-Transposase-Accessible-Chromatin (ATAC)-seq datasets grow exponentially, suboptimal motif scanning is commonly used for TFBS prediction from ATAC-seq. Here, we present "maxATAC", a suite of user-friendly, deep neural network models for genome- wide TFBS prediction from ATAC-seq in any cell type. With models available for 127 human TFs, maxATAC is the largest collection of state-of-the-art TFBS models to date. maxATAC performance extends to primary cells and single-cell ATAC-seq, enabling state-of-the-art TFBS prediction in vivo. We demonstrate maxATAC's capabilities by identifying TFBS associated with allele-dependent chromatin accessibility at atopic dermatitis genetic risk loci.

Genome-wide association studies of Systemic Lupus Erythematosus (SLE) nominate 3,073 genetic variants at 91 risk loci. To systematically screen these variants for allelic transcriptional enhancer activity, we constructed a massively parallel reporter assay (MPRA) library comprising 12,396 DNA oligonucleotides containing the genomic context around every allele of each SLE variant. Transfection into EBV-infected B cells revealed 482 variants with enhancer activity, with 51 variants showing genotype-dependent (allelic) enhancer activity at 27 risk loci. In-depth analysis of allelic transcription factor (TF) binding at and around these 51 variants identified one class of TFs whose DNA-binding motif tends to be directly altered by the risk variant and a second, larger class of TFs that also bind allelically but do not have their motifs directly altered by the variant. Collectively, our approach provides a blueprint for the discovery of allelic gene regulation at risk loci for any disease and offers insight into the transcriptional regulatory mechanisms underlying SLE.

Transcription factors read the genome, fundamentally connecting DNA sequence to gene expression across diverse cell types. Determining how, where, and when TFs bind chromatin will advance our understanding of gene regulatory networks and cellular behavior. The 2017 ENCODE-DREAM in vivo Transcription-Factor Binding Site (TFBS) Prediction Challenge highlighted the value of chromatin accessibility data to TFBS prediction, establishing state-of-the-art methods for TFBS prediction from DNase-seq. However, the more recent Assay-for-Transposase-Accessible-Chromatin (ATAC)-seq has surpassed DNase-seq as the most widely-used chromatin accessibility profiling method. Furthermore, ATAC-seq is the only such technique available at single-cell resolution from standard commercial platforms. While ATAC-seq datasets grow exponentially, suboptimal motif scanning is unfortunately the most common method for TFBS prediction from ATAC-seq. To enable community access to state-of-the-art TFBS prediction from ATAC-seq, we (1) curated an extensive benchmark dataset (127 TFs) for ATAC-seq model training and (2) built “maxATAC”, a suite of user-friendly, deep neural network models for genome-wide TFBS prediction from ATAC-seq in any cell type. With models available for 127 human TFs, maxATAC is the largest collection of high-performance TFBS prediction models for ATAC-seq. maxATAC performance extends to primary cells and single-cell ATAC-seq, enabling improved TFBS prediction in vivo. We demonstrate maxATAC’s capabilities by identifying TFBS associated with allele-dependent chromatin accessibility at atopic dermatitis genetic risk loci.

Innate lymphoid cells (ILCs) are rare tissue-resident “helper” lymphocytes that do not express diversified antigen receptors. Type 3 ILCs (ILC3s) are an important class of these cells enriched in the respiratory and intestinal mucosa, where they regulate inflammation and mucosal homeostasis. To gain insight into the cis-regulatory circuitries underlying ILC3 function, we used high-resolution Capture Hi-C to profile promoter-anchored chromosomal contacts in human primary ILC3s. Combining significant interaction detection with the Activity-By-Contact approach adapted to Capture Hi-C, we reveal a multitude of contacts between promoters and distal regulatory elements and obtain evidence for distinct regulatory wiring of alternative promoters. We find that promoter-interacting regions in ILC3s are enriched for genetic variants associated with multiple immune diseases. Focusing on Crohn’s disease (CD), in which ILC3s are established mediators, we used a Bayesian approach that incorporates multivariate fine-mapping to link CD-associated genetic variants with putative target genes. We identify known and previously unimplicated genes in conferring genetic risk of CD through activity in ILC3s. This includes the CLN3gene that is mutated in the neurodegenerative disorder Batten disease. UsingCln3mutant mice, we show thatCLN3is a putative negative regulator of IL-17 production in an inflammatory subset of ILC3s. This finding suggests a functional role forCLN3in ILC3 biology, with mechanistic implications for both Crohn’s and Batten diseases.