Faculty Bibliography

Whereas human dendritic cells (DCs) are largely resistant to productive infection with HIV-1, they have a unique ability to take up the virus and transmit it efficiently to T lymphocytes through a process of trans-infection or trans-enhancement. To elucidate the molecular and cell biological mechanism for trans-enhancement, we performed an shRNA screen of several hundred genes involved in organelle and membrane trafficking in immature human monocyte-derived dendritic cells (MDDCs). We identified TSPAN7 and DNM2, which control actin nucleation and stabilization, as having important and distinct roles in limiting HIV-1 endocytosis and in maintaining virus particles on dendrites, which is required for efficient transfer to T lymphocytes. Further characterization of this process may provide insights not only into the role of DCs in transmission and dissemination of HIV-1 but also more broadly into mechanisms controlling capture and internalization of pathogens.

RORgammat+ Th17 cells are important for mucosal defenses but also contribute to autoimmune disease. They accumulate in the intestine in response to microbiota and produce IL-17 cytokines. Segmented filamentous bacteria (SFB) are Th17-inducing commensals that potentiate autoimmunity in mice. RORgammat+ T cells were induced in mesenteric lymph nodes early after SFB colonization and distributed across different segments of the gastrointestinal tract. However, robust IL-17A production was restricted to the ileum, where SFB makes direct contact with the epithelium and induces serum amyloid A proteins 1 and 2 (SAA1/2), which promote local IL-17A expression in RORgammat+ T cells. We identified an SFB-dependent role of type 3 innate lymphoid cells (ILC3), which secreted IL-22 that induced epithelial SAA production in a Stat3-dependent manner. This highlights the critical role of tissue microenvironment in activating effector functions of committed Th17 cells, which may have important implications for how these cells contribute to inflammatory disease.

This year's Lasker approximately DeBakey Clinical Research Award goes to James Allison for discovering that antibody blockade of the T cell molecule CTLA-4 unleashes the body's immune response against malignant tumors. This has led to development of multiple "immune checkpoint therapies" that are prolonging and saving the lives of thousands of cancer patients.

During development, progenitor cells with binary potential give rise to daughter cells that have distinct functions. Heritable epigenetic mechanisms then lock in gene-expression programs that define lineage identity. Regulation of the gene encoding the T cell-specific coreceptor CD4 in helper and cytotoxic T cells exemplifies this process, with enhancer- and silencer-regulated establishment of epigenetic memory for stable gene expression and repression, respectively. Using a genetic screen, we identified the DNA-methylation machinery as essential for maintaining silencing of Cd4 in the cytotoxic lineage. Furthermore, we found a requirement for the proximal enhancer in mediating the removal of DNA-methylation marks from Cd4, which allowed stable expression of Cd4 in helper T cells. Our findings suggest that stage-specific methylation and demethylation events in Cd4 regulate its heritable expression in response to the distinct signals that dictate lineage 'choice' during T cell development.

PURPOSE OF REVIEW: This review will highlight recent advances functionally linking the gut microbiome with mucosal and systemic immune cell activation underlying autoimmunity. RECENT FINDINGS: Dynamic interactions between the gut microbiome and environmental cues (including diet and medicines) shape the effector potential of the microbial organ. Key bacteria and viruses have emerged that, in defined microenvironments, play a critical role in regulating effector lymphocyte functions. The coordinated interactions between these different microbial kingdoms - including bacteria, helminths, and viruses (termed transkingdom interactions) - play a key role in shaping immunity. Emerging strategies to identify immunologically relevant microbes with the potential to regulate immune cell functions both at mucosal sites and systemically will likely define diagnostic and therapeutic targets. SUMMARY: The microbiome constitutes a critical microbial organ with coordinated interactions that shape host immunity.

The role of the microenvironment in T cell acute lymphoblastic leukemia (T-ALL), or any acute leukemia, is poorly understood. Here we demonstrate that T-ALL cells are in direct, stable contact with CXCL12-producing bone marrow stroma. Cxcl12 deletion from vascular endothelial, but not perivascular, cells impeded tumor growth, suggesting a vascular niche for T-ALL. Moreover, genetic targeting of Cxcr4 in murine T-ALL after disease onset led to rapid, sustained disease remission, and CXCR4 antagonism suppressed human T-ALL in primary xenografts. Loss of CXCR4 targeted key T-ALL regulators, including the MYC pathway, and decreased leukemia initiating cell activity in vivo. Our data identify a T-ALL niche and suggest targeting CXCL12/CXCR4 signaling as a powerful therapeutic approach for T-ALL.

The balance of effector and regulatory T cell function, dependent on multiple signals and epigenetic regulators, is critical to immune self-tolerance. Dysregulation of T helper 17 (Th17) effector cells is associated with multiple autoimmune diseases, including multiple sclerosis. Here, we report that Sirtuin 1 (SIRT1), a protein deacetylase previously reported to have an antiinflammatory function, in fact promotes autoimmunity by deacetylating RORgammat, the signature transcription factor of Th17 cells. SIRT1 increases RORgammat transcriptional activity, enhancing Th17 cell generation and function. Both T cell-specific Sirt1 deletion and treatment with pharmacologic SIRT1 inhibitors suppress Th17 differentiation and are protective in a mouse model of multiple sclerosis. Moreover, analysis of infiltrating cell populations during disease induction in mixed hematopoietic chimeras shows a marked bias against Sirt1-deficient Th17 cells. These findings reveal an unexpected proinflammatory role of SIRT1 and, importantly, support the possible therapeutic use of SIRT1 inhibitors against autoimmunity.

16S ribosomal RNA (rRNA) gene and other environmental sequencing techniques provide snapshots of microbial communities, revealing phylogeny and the abundances of microbial populations across diverse ecosystems. While changes in microbial community structure are demonstrably associated with certain environmental conditions (from metabolic and immunological health in mammals to ecological stability in soils and oceans), identification of underlying mechanisms requires new statistical tools, as these datasets present several technical challenges. First, the abundances of microbial operational taxonomic units (OTUs) from amplicon-based datasets are compositional. Counts are normalized to the total number of counts in the sample. Thus, microbial abundances are not independent, and traditional statistical metrics (e.g., correlation) for the detection of OTU-OTU relationships can lead to spurious results. Secondly, microbial sequencing-based studies typically measure hundreds of OTUs on only tens to hundreds of samples; thus, inference of OTU-OTU association networks is severely under-powered, and additional information (or assumptions) are required for accurate inference. Here, we present SPIEC-EASI (SParse InversE Covariance Estimation for Ecological Association Inference), a statistical method for the inference of microbial ecological networks from amplicon sequencing datasets that addresses both of these issues. SPIEC-EASI combines data transformations developed for compositional data analysis with a graphical model inference framework that assumes the underlying ecological association network is sparse. To reconstruct the network, SPIEC-EASI relies on algorithms for sparse neighborhood and inverse covariance selection. To provide a synthetic benchmark in the absence of an experimentally validated gold-standard network, SPIEC-EASI is accompanied by a set of computational tools to generate OTU count data from a set of diverse underlying network topologies. SPIEC-EASI outperforms state-of-the-art methods to recover edges and network properties on synthetic data under a variety of scenarios. SPIEC-EASI also reproducibly predicts previously unknown microbial associations using data from the American Gut project.