Faculty Bibliography

Transcriptional programming of the innate immune response is pivotal for host protection. However, the transcriptional mechanisms that link pathogen sensing with innate activation remain poorly understood. During HIV-1 infection, human dendritic cells (DCs) can detect the virus through an innate sensing pathway, leading to antiviral interferon and DC maturation. Here, we develop an iterative experimental and computational approach to map the HIV-1 innate response circuitry in monocyte-derived DCs (MDDCs). By integrating genome-wide chromatin accessibility with expression kinetics, we infer a gene regulatory network that links 542 transcription factors with 21,862 target genes. We observe that an interferon response is required, yet insufficient, to drive MDDC maturation and identify PRDM1 and RARA as essential regulators of the interferon response and MDDC maturation, respectively. Our work provides a resource for interrogation of regulators of HIV replication and innate immunity, highlighting complexity and cooperativity in the regulatory circuit controlling the response to infection.

Lymphoid cells that produce interleukin (IL)-17 cytokines protect barrier tissues from pathogenic microbes but are also prominent effectors of inflammation and autoimmune disease. T helper 17 (Th17) cells, defined by RORγt-dependent production of IL-17A and IL-17F, exert homeostatic functions in the gut upon microbiota-directed differentiation from naive CD4⁺ T cells. In the non-pathogenic setting, their cytokine production is regulated by serum amyloid A proteins (SAA1 and SAA2) secreted by adjacent intestinal epithelial cells. However, Th17 cell behaviors vary markedly according to their environment. Here, we show that SAAs additionally direct a pathogenic pro-inflammatory Th17 cell differentiation program, acting directly on T cells in collaboration with STAT3-activating cytokines. Using loss- and gain-of-function mouse models, we show that SAA1, SAA2, and SAA3 have distinct systemic and local functions in promoting Th17-mediated inflammatory diseases. These studies suggest that T cell signaling pathways modulated by the SAAs may be attractive targets for anti-inflammatory therapies.

Bile acids are abundant in the mammalian gut, where they undergo bacteria-mediated transformation to generate a large pool of bioactive molecules. Although bile acids are known to affect host metabolism, cancer progression and innate immunity, it is unknown whether they affect adaptive immune cells such as T helper cells that express IL-17a (T_H17 cells) or regulatory T cells (T_reg cells). Here we screen a library of bile acid metabolites and identify two distinct derivatives of lithocholic acid (LCA), 3-oxoLCA and isoalloLCA, as T cell regulators in mice. 3-OxoLCA inhibited the differentiation of T_H17 cells by directly binding to the key transcription factor retinoid-related orphan receptor-γt (RORγt) and isoalloLCA increased the differentiation of T_reg cells through the production of mitochondrial reactive oxygen species (mitoROS), which led to increased expression of FOXP3. The isoalloLCA-mediated enhancement of T_reg cell differentiation required an intronic Foxp3 enhancer, the conserved noncoding sequence (CNS) 3; this represents a mode of action distinct from that of previously identified metabolites that increase T_reg cell differentiation, which require CNS1. The administration of 3-oxoLCA and isoalloLCA to mice reduced T_H17 cell differentiation and increased T_reg cell differentiation, respectively, in the intestinal lamina propria. Our data suggest mechanisms through which bile acid metabolites control host immune responses, by directly modulating the balance of T_H17 and T_reg cells.

Gut-dwelling Prevotella copri (P. copri), the most prevalent Prevotella species in the human gut, have been associated with diet and disease. However, our understanding of their diversity and function remains rudimentary because studies have been limited to 16S and metagenomic surveys and experiments using a single type strain. Here, we describe the genomic diversity of 83 P. copri isolates from 11 human donors. We demonstrate that genomically distinct isolates, which can be categorized into different P. copri complex clades, utilize defined sets of polysaccharides. These differences are exemplified by variations in susC genes involved in polysaccharide transport as well as polysaccharide utilization loci (PULs) that were predicted in part from genomic and metagenomic data. Functional validation of these PULs showed that P. copri isolates utilize distinct sets of polysaccharides from dietary plant, but not animal, sources. These findings reveal both genomic and functional differences in polysaccharide utilization across human intestinal P. copri strains.

Prevotella copri is a common human gut microbe that has been both positively and negatively associated with host health. In a cross-continent meta-analysis exploiting >6,500 metagenomes, we obtained >1,000 genomes and explored the genetic and population structure of P. copri. P. copri encompasses four distinct clades (>10% inter-clade genetic divergence) that we propose constitute the P. copri complex, and all clades were confirmed by isolate sequencing. These clades are nearly ubiquitous and co-present in non-Westernized populations. Genomic analysis showed substantial functional diversity in the complex with notable differences in carbohydrate metabolism, suggesting that multi-generational dietary modifications may be driving reduced prevalence in Westernized populations. Analysis of ancient metagenomes highlighted patterns of P. copri presence consistent with modern non-Westernized populations and a clade delineation time pre-dating human migratory waves out of Africa. These findings reveal that P. copri exhibits a high diversity that is underrepresented in Western-lifestyle populations.

Understanding the role of the microbiota components in either preventing or favoring enteric infections is critical. Here, we report the discovery of a Listeria bacteriocin, Lmo2776, which limits Listeria intestinal colonization. Oral infection of conventional mice with a Δlmo2776 mutant leads to a thinner intestinal mucus layer and higher Listeria loads both in the intestinal content and deeper tissues compared to WT Listeria. This latter difference is microbiota dependent, as it is not observed in germ-free mice. Strikingly, it is phenocopied by pre-colonization of germ-free mice before Listeria infection with Prevotella copri, an abundant gut-commensal bacteria, but not with the other commensals tested. We further show that Lmo2776 targets P. copri and reduces its abundance. Together, these data unveil a role for P.copri in exacerbating intestinal infection, highlighting that pathogens such as Listeria may selectively deplete microbiota bacterial species to avoid excessive inflammation.

Innate lymphoid cells (ILCs) promote tissue homeostasis and immune defense but also contribute to inflammatory diseases. ILCs exhibit phenotypic and functional plasticity in response to environmental stimuli, yet the transcriptional regulatory networks (TRNs) that control ILC function are largely unknown. Here, we integrate gene expression and chromatin accessibility data to infer regulatory interactions between transcription factors (TFs) and genes within intestinal type 1, 2, and 3 ILC subsets. We predicted the "core" TFs driving ILC identities, organized TFs into cooperative modules controlling distinct gene programs, and validated roles for c-MAF and BCL6 as regulators affecting type 1 and type 3 ILC lineages. The ILC network revealed alternative-lineage-gene repression, a mechanism that may contribute to reported plasticity between ILC subsets. By connecting TFs to genes, the TRNs suggest means to selectively regulate ILC effector functions, while our network approach is broadly applicable to identifying regulators in other in vivo cell populations.

The transcriptional repression of alternative lineage genes is critical for cell fate commitment. Mechanisms by which locus-specific gene silencing is initiated and heritably maintained during cell division are not clearly understood. To study the maintenance of silent gene states, we investigated how the Cd4 gene is stably repressed in CD8⁺ T cells. Through CRISPR and shRNA screening, we identified the histone chaperone CAF-1 as a critical component for Cd4 repression. We found that the large subunit of CAF-1, Chaf1a, requires the N-terminal KER domain to associate with the histone deacetylases HDAC1/2 and the histone demethylase LSD1, enzymes that also participate in Cd4 silencing. When CAF-1 was lacking, Cd4 derepression was markedly enhanced in the absence of the de novo DNA methyltransferase Dnmt3a but not the maintenance DNA methyltransferase Dnmt1. In contrast to Dnmt1, Dnmt3a deficiency did not significantly alter levels of DNA methylation at the Cd4 locus. Instead, Dnmt3a deficiency sensitized CD8⁺ T cells to Cd4 derepression mediated by compromised functions of histone-modifying factors, including the enzymes associated with CAF-1. Thus, we propose that the heritable silencing of the Cd4 gene in CD8⁺ T cells exploits cooperative functions among the DNA methyltransferases, CAF-1, and histone-modifying enzymes.

Transcriptional regulatory networks (TRNs) provide insight into cellular behavior by describing interactions between transcription factors (TFs) and their gene targets. The Assay for Transposase Accessible Chromatin (ATAC)-seq, coupled with transcription-factor motif analysis, provides indirect evidence of chromatin binding for hundreds of TFs genome-wide. Here, we propose methods for TRN inference in a mammalian setting, using ATAC-seq data to influence gene expression modeling. We rigorously test our methods in the context of T Helper Cell Type 17 (Th17) differentiation, generating new ATAC-seq data to complement existing Th17 genomic resources (gene expression data, TF knock-outs and ChIP-seq experiments). In this resource-rich mammalian setting, our extensive benchmarking provides quantitative, genome-scale evaluation of TRN inference combining ATAC-seq and RNA-seq data. We refine and extend our previous Th17 TRN, using our new TRN inference methods to integrate all Th17 data (gene expression, ATAC-seq, TF KO, ChIP-seq). We highlight newly discovered roles for individual TFs and groups of TFs ("TF-TF modules") in Th17 gene regulation. Given the popularity of ATAC-seq, which provides high-resolution with low sample input requirements, we anticipate that application of our methods will improve TRN inference in new mammalian systems, especially in vivo, for cells directly from humans and animal models.