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Animal model studies highlight the role of innate-like lymphocyte populations in the early inflammatory response and subsequent parasite control following Plasmodium infection. IFN-γ production by these lymphocytes likely plays a key role in the early control of the parasite and disease severity. Analyzing human innate-like T cell and NK cell responses following infection with Plasmodium has been challenging because the early stages of infection are clinically silent. To overcome this limitation, we examined blood samples from a controlled human malaria infection (CHMI) study in a Tanzanian cohort, in which volunteers underwent CHMI with a low or high dose of Plasmodium falciparum sporozoites. The CHMI differentially affected NK, NKT (invariant NKT), and mucosal-associated invariant T cell populations in a dose-dependent manner, resulting in an altered composition of this innate-like lymphocyte compartment. Although these innate-like responses are typically thought of as short-lived, we found that changes persisted for months after the infection was cleared, leading to significantly increased frequencies of mucosal-associated invariant T cells 6 mo postinfection. We used single-cell RNA sequencing and TCR αβ-chain usage analysis to define potential mechanisms for this expansion. These single-cell data suggest that this increase was mediated by homeostatic expansion-like mechanisms. Together, these data demonstrate that CHMI leads to previously unappreciated long-lasting alterations in the human innate-like lymphocyte compartment. We discuss the consequences of these changes for recurrent parasite infection and infection-associated pathologies and highlight the importance of considering host immunity and infection history for vaccine design.

CCR5 is thought to play a central role in orchestrating migration of cells in response to inflammation. CCR5 antagonists can reduce inflammatory disease processes, which has led to an increased interest in using CCR5 antagonists in a wide range of inflammation-driven diseases. Paradoxically, these antagonists appear to function without negatively affecting host immunity at barrier sites. We reasoned that the resolution to this paradox may lie in the CCR5+ T cell populations that permanently reside in tissues. We used a single-cell analysis approach to examine the human CCR5+ T cell compartment in the blood, healthy, and inflamed mucosal tissues to resolve these seemingly contradictory observations. We found that 65% of the CD4 tissue-resident memory T (TRM) cell compartment expressed CCR5. These CCR5+ TRM cells were enriched in and near the epithelial layer and not only limited to TH1-type cells but also contained a large TH17-producing and a stable regulatory T cell population. The CCR5+ TRM compartment was stably maintained even in inflamed tissues including the preservation of TH17 and regulatory T cell populations. Further, using tissues from the CHARM-03 clinical trial, we found that CCR5+ TRM are preserved in human mucosal tissue during treatment with the CCR5 antagonist Maraviroc. Our data suggest that the human CCR5+ TRM compartment is functionally and spatially equipped to maintain barrier immunity even in the absence of CCR5-mediated, de novo T cell recruitment from the periphery.

Mucosal-associated invariant T (MAIT) cells acquire effector function in response to proinflammatory signals, which synergize with TCR-mediated signals. We asked if cell-intrinsic regulatory mechanisms exist to curtail MAIT cell effector function akin to the activation-induced expression of inhibitory receptors by conventional T cells. We examined human MAIT cells from blood and oral mucosal tissues by RNA sequencing and found differential expression of immunoregulatory genes, including CTLA-4, by MAIT cells isolated from tissue. Using an ex vivo experimental setup, we demonstrate that inflammatory cytokines were sufficient to induce CTLA-4 expression on the MAIT cell surface in the absence of TCR signals. Even brief exposure to the cytokines IL-12, IL-15, and IL-18 was sufficient for sustained CTLA-4 expression by MAIT cells. These data suggest that control of CTLA-4 expression is fundamentally different between MAIT cells and conventional T cells. We propose that this mechanism serves to limit MAIT cell–mediated tissue damage.

C - C chemokine receptor type 5 (CCR5) is thought to play a central role in orchestrating migration of cells in response to inflammation. CCR5 antagonists can reduce inflammatory disease processes which has led to an increased interest in using CCR5 antagonists in a wide range of inflammation-driven diseases. Paradoxically, these antagonists appear to function without negatively affecting host immunity at barrier sites. We reasoned that the resolution to this paradox may lie in the CCR5(+) T cell populations that permanently reside in tissues. We used a single-cell analysis approach to examine the human CCR5(+) T cell compartment in blood, healthy, and inflamed mucosal tissues to resolve these seemingly contradictory observations. We found that 65% of the tissue-resident (T(RM)) CD4 T cell compartment expressed CCR5. These CCR5(+) T(RM) cells were enriched in and near the epithelial layer and not limited to T(H)1 type cells but also contained a large T(H)17-producing and a stable regulatory T (Treg) cell population. Importantly, the CCR5(+) T(RM) compartment was stably maintained even in inflamed tissues including the preservation of T(H)17 and regulatory T cell populations. Further, using tissues from the CHARM-03 clinical trial we found that CCR5(+) T(RM) are preserved in human mucosal tissue during treatment with the CCR5 antagonist Maraviroc. Our data suggest that the human CCR5(+) T(RM) compartment is functionally and spatially equipped to maintain barrier immunity even in the absence of CCR5-mediated, de novo T cell recruitment from the periphery.

Mucosal-associated invariant T cells (MAIT cells) recognize bacterial metabolites as antigen and are found in blood and tissues, where they are poised to contribute to barrier immunity. Recent data demonstrate that MAIT cells located in mucosal barrier tissues are functionally distinct from their blood counterparts, but the relationship and circulation of MAIT cells between blood and different tissue compartments remains poorly understood. Previous studies raised the possibility that MAIT cells do not leave tissue and may either be retained or undergo apoptosis. To directly address if human MAIT cells exit tissues, we collected human donor-matched thoracic duct lymph and blood and analyzed MAIT cell phenotype, transcriptome, and T cell receptor (TCR) diversity by flow cytometry and RNA sequencing. We found that MAIT cells were present in the lymph, despite being largely CCR7- in the blood, thus indicating that MAIT cells in the lymph migrated from tissues and were capable of exiting tissues to recirculate. Importantly, MAIT cells in the lymph and blood had highly overlapping clonotype usage but distinct transcriptome signatures, indicative of differential activation states.

Conventional memory CD8+ T cells and mucosal-associated invariant T cells (MAIT cells) are found in blood, liver, and mucosal tissues and have similar effector potential following activation, specifically expression of IFN-γ and granzyme B. To better understand each subset’s unique contributions to immunity and pathology, we interrogated inflammation- and TCR-driven activation requirements using human memory CD8+ T and MAIT cells isolated from blood and mucosal tissue biopsies in ex vivo functional assays and single cell gene expression experiments. We found that MAIT cells had a robust IFN-γ and granzyme B response to inflammatory signals but limited responsiveness when stimulated directly via their TCR. Importantly, this is not due to an overall hyporesponsiveness to TCR signals. When delivered together, TCR and inflammatory signals synergize to elicit potent effector function in MAIT cells. This unique control of effector function allows MAIT cells to respond to the same TCR signal in a dichotomous and situation-specific manner. We propose that this could serve to prevent responses to antigen in noninflamed healthy mucosal tissue, while maintaining responsiveness and great sensitivity to inflammation-eliciting infections. We discuss the implications of these findings in context of inflammation-inducing damage to tissues such as BM transplant conditioning or HIV infection.

STUDY DESIGN Experimental quantification of relationships between vertebral endplate morphology, permeability, disc cell density, glycosaminoglycan (GAG) content, and degeneration in samples harvested from human cadaveric spines. OBJECTIVE To test the hypothesis that variation in endplate permeability and porosity contributes to changes in intervertebral disc cell density and overall degeneration. SUMMARY OF BACKGROUND DATA Cells within the intervertebral disc are dependent on diffusive exchange with capillaries in the adjacent vertebral bone. Previous findings suggest that blocked routes of transport negatively affect disc quality, yet there are no quantitative relationships between human vertebral endplate permeability, porosity, cell density, and disc degeneration. Such relationships would be valuable for clarifying degeneration risk factors and patient features that may impede efforts at disc tissue engineering. METHODS Fifty-one motion segments were harvested from 13 frozen cadaveric human lumbar spines (32-85 years) and classified for degeneration using the magnetic resonance imaging-based Pfirrmann scale. A cylindrical core was harvested from the center of each motion segment that included vertebral bony and cartilage endplates along with adjacent nucleus tissue. The endplate mobility, a type of permeability, was measured directly using a custom-made permeameter before and after the cartilage endplate was removed. Cell density within the nucleus tissue was estimated using the picogreen method, while the nuclear GAG content was quantified using the dimethylmethylene blue technique. Specimens were imaged at 8 μm resolution using microCT; bony porosity was calculated. Analysis of variance, linear regression, and multiple comparison tests were used to analyze the data. RESULTS.: Nucleus cell density increased as the disc height decreased (R² = 0.13; P = 0.01) but was not related to subchondral bone porosity (P > 0.5), total mobility (P > 0.4), or age (P > 0.2). When controlling for disc height, however, a significant, negative effect of age on cell density was observed (P = 0.03). In addition to this, GAG content decreased with age nonlinearly (R² = 0.83, P < 0.0001) and a cell function measurement, GAGs/cell, decreased with degeneration (R² = 0.24; P < 0.0001). Total mobility (R² = 0.14; P < 0.01) and porosity (R² = 0.1, P < 0.01) had a positive correlation with age. CONCLUSION Although cell density increased with degeneration, cell function indicated that GAGs/cell decreased. Because permeability and porosity increase with age and degeneration, this implies that cell dysfunction, rather than physical barriers to transport, accelerates disc disease.

Single-cell transcriptomic profiling enables the unprecedented interrogation of gene expression heterogeneity in rare cell populations that would otherwise be obscured in bulk RNA sequencing experiments. The stochastic nature of transcription is revealed in the bimodality of single-cell transcriptomic data, a feature shared across single-cell expression platforms. There is, however, a paucity of computational tools that take advantage of this unique characteristic. We present a new methodology to analyze single-cell transcriptomic data that models this bimodality within a coherent generalized linear modeling framework. We propose a two-part, generalized linear model that allows one to characterize biological changes in the proportions of cells that are expressing each gene, and in the positive mean expression level of that gene. We introduce the cellular detection rate, the fraction of genes turned on in a cell, and show how it can be used to simultaneously adjust for technical variation and so-called “extrinsic noise” at the single-cell level without the use of control genes. Our model permits direct inference on statistics formed by collections of genes, facilitating gene set enrichment analysis. The residuals defined by such models can be manipulated to interrogate cellular heterogeneity and gene-gene correlation across cells and conditions, providing insights into the temporal evolution of networks of co-expressed genes at the single-cell level. Using two single-cell RNA-seq datasets, including newly generated data from Mucosal Associated Invariant T (MAIT) cells, we show how model residuals can be used to identify significant changes across biologically relevant gene sets that are missed by other methods and characterize cellular heterogeneity in response to stimulation.

HIV replication is unrestrained in vivo in the vast majority of infected subjects, and the ability of some rare individuals to control this virus is poorly understood. Standard immunogenicity assays for detecting HIV-1-specific CD8(+) T-cell responses, such as IFN-γ ELISpot and intracellular cytokine staining, generally fail to correlate with in vivo inhibition of HIV replication. Several viral inhibition assays, which measure the effectiveness of CD8(+) T-cell responses in suppressing HIV replication in vitro, have been described; but most depend on in vitro expansion of CD8(+) T cells, and some show inhibitory activity in HIV-negative individuals. We have optimized an assay to assess the suppressive capability of CD8(+) T cells directly ex vivo, eliminating the potential for altering their function through activation or expansion prior to assay setup, and thereby enhancing the assay's sensitivity by avoiding non-specific inhibition. With this method, the ability of ex vivo CD8(+) T cells to control HIV-1 replication in vitro can be quantified over several orders of magnitude. Specifically, our assay can be used to better define the antiviral function of CD8(+) T cells induced by vaccination, and can provide insight into their ability to control viral replication if HIV infection occurs post-vaccination.

Mucosal-associated invariant T (MAIT) cells recognize bacterial metabolites presented on MR1 via their semi-invariant T cell receptor (TCR). MAIT cells are a potent effector population located in tissues that are constantly exposed to the microbiome. This raises the question how MAIT cell activation is regulated to avoid unwanted responses to microbiome-derived metabolites. To address this we dissected the MAIT cell response to TCR- and cytokine-mediated signals. We found that stimulating the MAIT TCR in the absence of inflammatory cytokines was not sufficient to induce effector function such as granzyme B and interferon-g expression. Inflammatory signals acting directly on MAIT cells were absolutely necessary to allow for TCR-mediated acquisition of effector function. Importantly, MAIT cells are not generally hyporesponsive to TCR-mediated signals as TCR stimulation in the absence of inflammation elicited a distinct chemokine response. Single-cell gene expression analysis of MAIT cells isolated from healthy human mucosal tissue revealed increased expression of inflammatory genes compared to their counterparts in the blood, indicating that provided the proper signals mucosal MAIT cells are poised to respond rapidly to infection. Importantly, MAIT cells in the mucosa do not produce inflammatory cytokines directly ex-vivo, despite expressing higher levels of inflammatory transcript. We propose a novel model in which the strict dependence of TCR-mediated signals on pro-inflammatory cytokines to induce effector function represents a MAIT cell-intrinsic mechanism to prevent unwanted responses to commensal bacteria-derived bacterial metabolites, while allowing potent effector responses following infection.

Single-cell transcriptomics reveals gene expression heterogeneity but suffers from stochastic dropout and characteristic bimodal expression distributions in which expression is either strongly non-zero or non-detectable. We propose a two-part, generalized linear model for such bimodal data that parameterizes both of these features. We argue that the cellular detection rate, the fraction of genes expressed in a cell, should be adjusted for as a source of nuisance variation. Our model provides gene set enrichment analysis tailored to single-cell data. It provides insights into how networks of co-expressed genes evolve across an experimental treatment. MAST is available at https://github.com/RGLab/MAST. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0844-5) contains supplementary material, which is available to authorized users.