key: cord-0830944-lfzswq65 authors: Parrot, T.; Gorin, J.-B.; Ponzetta, A.; Maleki, K. T.; Kammann, T.; Emgard, J.; Perez Potti, A.; Sekine, T.; Rivera-Ballesteros, O.; Karolinska COVID-19 Study Group,; Folkesson, E.; Rooyackers, O.; Eriksson, L. I.; Norrby-Teglund, A.; Ljunggren, H.-G.; Bjorkstrom, N. K.; Aleman, S.; Buggert, M.; Klingstrom, J.; Stralin, K.; Sandberg, J. K. title: MAIT cell activation and dynamics associated with COVID-19 disease severity and outcome date: 2020-09-01 journal: nan DOI: 10.1101/2020.08.27.20182550 sha: bffc16eeb20124be9cb64218cfb7dfcbfe01b994 doc_id: 830944 cord_uid: lfzswq65 Severe COVID-19 is characterized by excessive inflammation of the lower airways. The balance of protective versus pathological immune responses in COVID-19 is incompletely understood. Mucosa-associated invariant T (MAIT) cells are antimicrobial T cells that recognize bacterial metabolites, and can also function as innate-like sensors and mediators of antiviral responses. Here, we investigated the MAIT cell compartment in COVID-19 patients with moderate and severe disease, as well as in convalescence. We show profound and preferential decline in MAIT cells in circulation of patients with active disease paired with strong activation, as well as significant MAIT cell enrichment and pro-inflammatory IL-17A bias in the airways. Unsupervised analysis identified MAIT cell CD69high and CXCR3low immunotypes associated with poor clinical outcome. MAIT cell levels normalized in the convalescent phase, consistent with dynamic recruitment to the tissues and subsequent release with disease resolution. These findings indicate that MAIT cells are engaged in the immune response against SARS-CoV-2 and suggest their involvement in COVID-19 immunopathogenesis. Severe acute respiratory syndrome (SARS) Coronavirus-19 (SARS-CoV-2) causes viral pneumonia and coronavirus disease 2019 , which in some individuals progresses to acute respiratory distress syndrome (ARDS) characterized by aggressive inflammatory responses in the lower airways (reviewed in (1)). Severe COVID-19 is not only due to direct effects of the virus, but also in part to a misdirected host response with complex immune dysregulation of both innate and adaptive immune and inflammatory components (2, 3) . The COVID-19 pandemic has been met with an unprecedented research effort by academia as well as the pharmaceutical industry. Nevertheless, by mid-2020 many aspects of COVID-19 immunopathogenesis still remain poorly characterized. The majority of T cells respond in an adaptive fashion to peptide antigens governed by MHC-restriction, and the role of CD8 and CD4 T cell responses against COVID-19 has recently been demonstrated (4) (5) (6) (7) (8) (9) (10) . However, the T cell compartment also encompasses several unconventional invariant T cell subsets that have innate-like functions (11). Mucosaassociated invariant T (MAIT) cells represent 1-10% of T cells in the circulation, have strong tissue homing characteristics and are particularly abundant in the liver and lung (reviewed in (12)). MAIT cells are activated by TCR recognition of microbial vitamin B2 (riboflavin) metabolites from a range of microbes presented by MHC-Ib-related protein 1 (MR1) molecules (13) . However, some MAIT cell functions can be activated or co-activated by cytokines such as IL-18 and type I IFNs (14, 15) . MAIT cells rapidly produce IFNγ, TNF, and IL-17, and mediate effective cytolytic function dependent on granzyme B (GrzB) (16) (17) (18) . This broad effector profile contributes to the role of MAIT cells in the protection against bacterial pulmonary infections (19) (20) (21) , where MAIT cells have a role in recruiting adaptive T cells to the lung (22) . MAIT cells in mucosa have an IL-17/22-biased functional profile distinct from that of circulating cells (23) , and can also be pro-fibrogenic in chronic inflammatory disease (24) . Human MAIT cells are activated in response to several RNA viruses (25, 26) , expand during acute stages of HIV-1 infection (27), and may have a protective role in influenza virus infection as deduced from studies in murine models (28) . Based on these distinct innate-like, tissue homing and pro-inflammatory characteristics of MAIT cells, we set out to study these cells in Our findings indicate that MAIT cells are engaged in the immune response against SARS-CoV-2 and suggest their possible involvement in COVID-19 immunopathogenesis. Profound MAIT cell decline in the circulation and enrichment in the airways of COVID- With the aim to study COVID-19 immunopathogenesis, 24 patients were prospectively recruited after admission to the Karolinska University Hospital as part of the Karolinska COVID- 19 Immune Atlas project (10, 29) . Inclusion and exclusion criteria defined two groups of acute patients with moderate (AM) or severe (AS) disease matched with respect to other patient characteristics (Table S1 ). Fourteen matched healthy donors (HD) who were SARS-CoV-2 IgG seronegative and symptom-free at time of sampling were included as controls. To minimize inter-experimental variability and batch effects, all samples were acquired, processed, and analyzed fresh during three consecutive weeks in the spring of 2020 at the peak of the COVID-19 pandemic in Stockholm, Sweden. To study changes in conventional and unconventional T cell subsets in patients with AM and AS COVID-19 disease, a 22-parameter flow cytometry panel was designed to evaluate frequency, activation, homing and functional phenotypes of MAIT cells, invariant natural killer T (iNKT) cells, CD4 and CD8 double negative T (DNT) cells (30) , γδ T cells as well as conventional CD4 and CD8 T cells (Fig. S1A) . We initially analyzed the whole data set through an unsupervised approach using Uniform Manifold Approximation and Projection (UMAP) analysis on CD3 + single live events in all patients and controls (n=38). Projection of defining markers allowed visualization of the location of distinct T cell subsets on the UMAP topography ( Fig. 1A) , which was confirmed using manual gating. Projecting data from HD, AM and AS subjects separately, revealed a clear difference between patients and controls with severe reduction in the distinct topography defined by the MR1-5-OP-RU tetramer suggesting loss of MAIT cells in COVID-19 (Fig. 1B) . The profound decline in MAIT cell percentage (Fig. 1C) , and absolute counts (Fig. 1D ), in COVID-19 patients was confirmed by manual gating. The absolute count decline extended to conventional CD4 and CD8 T cell subsets, and DNT cells, while iNKT cells and γδ T cells were largely unchanged. However, the MAIT cell lymphopenia was distinct in its severity, and was pronounced already in the AM group where loss of overall T cell subsets was not significant. The circulating MAIT cell pool comprises three subsets expressing CD8, CD4, or DN displaying some functional differences (31) . The numerical decline of the DN MAIT cell subset was more marked than that of the main CD8 + MAIT cell population (Fig. S1B ). Analysis of a publicly available single cell RNA sequencing (scRNAseq) data set on nasopharyngeal samples (32) , allowed identification of MAIT cells in the upper respiratory tract of COVID-19 patients and healthy control subjects using a combination of MAIT cell defining transcripts (KLRB1, SLC4A10, IL7R and DPP4) (Fig. 1E) . Interestingly, the scRNAseq data indicated that MAIT cells were highly enriched within T cells infiltrating the airways of COVID-19 patients as compared to controls (Fig. 1E) , consistent with the profound decline of the circulating MAIT cell pool in COVID-19 disease and a possible recruitment to this site. This pattern was corroborated by analysis of MAIT cells in a second published scRNAseq data set on bronchoalveolar lavage (BAL) fluid (33) (Fig. S1C ). The interpretation that MAIT cells are recruited to the airways in COVID-19 was further supported by inverse correlations between MAIT cell counts and serum levels of CCL20 and CXCL11 in our cohort (Fig. 1F) , the receptors for which (CCR6 and CXCR3, respectively) MAIT cells express at high levels (34) . Furthermore, MAIT cell counts were inversely correlated with IL-17C levels in plasma, supporting a possible link between MAIT cell recruitment and lung epithelium inflammation (Fig. 1F) . These soluble factors were all increased in serum of COVID-19 patients compared to HD (Fig. S1D ). Together, these findings identify a pattern of profound and preferential decline of circulating MAIT cells in COVID-19, and suggest that this is at least partly caused by recruitment of MAIT cells to the airways. Next, we were interested to analyze MAIT cell characteristics in the context of COVID-19. Unsupervised analysis of MAIT cell flow cytometry phenotypes in all Atlas cohort patients and controls (n=38) revealed a pattern of enhanced CD69 expression and diminished CXCR3 expression in both AM and AS COVID-19 patients ( Fig. 2A, 2B) . The activated CD69 high phenotype was shared between AM and AS COVID-19 patients, although AS patients had slightly higher levels of GrzB and Ki67 than AM patients (Fig. 2C ). Expression levels of PD-1, IL-7R, CXCR6, Granzyme A (GrzA), and CD56 were similar between HD, AM and AS groups ( Fig. S2A ). Activation patterns were largely shared between CD8 + and DN MAIT cell subsets, although the CD8 + MAIT cell pool showed somewhat higher levels of activation (Fig. S2B ). The patterns with CD69 upregulation and CXCR3 downregulation were more pronounced in MAIT cells as compared to conventional CD4 and CD8 T cells (Fig. S2C ). Correlation analyses of the MAIT cell phenotype data set (Fig. 2D ) indicated that activation levels reflected by CD69 expression were inversely linked with CXCR3 expression (Fig. 2E) , and MAIT cell percentages were directly correlated with CXCR6 expression (Fig. 2F) . Analysis of the scRNAseq data set on nasopharyngeal samples (32) , allowed characterization of the transcriptional profile of MAIT cells in the airways of COVID-19 patients (Fig. S3) . The CD69 + CXCR3phenotype of MAIT cells in peripheral blood was reproduced at the transcriptional level in the airways. Strikingly, the transcriptional profile indicated that MAIT cells were the main subset of airway T cells expressing IL17A. This profile was paired with expression of TNF, and an apparent lack of IFNG and GZMB transcripts. Together, these results indicate that the residual circulating MAIT cell pool is highly activated with lowered All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. We next analyzed the markers influencing PhenoGraph clustering in relation to outcome. Strikingly, the four patients who died at hospital had significantly higher CD69 expression on their MAIT cells than patients who survived, suggesting an association between MAIT cell activation-levels and clinical outcome (Fig. 3F , left panel). To explore this pattern further, we retrospectively identified another seven deceased Intensive Care Unit (ICU) patients and seven matching ICU patients who were discharged alive (Table S2) , retrieved cryopreserved Biobank PBMC samples from these patients and stained their PBMCs using the same flow cytometry panel. In this retrospective sampling of severely ill patients the association between CD69 levels and outcome was not reproduced (Fig. 3F , right panel). In comparing the first Atlas patient group with the second retrospective Biobank group, the Biobank patients were found to be sampled significantly later following symptom onset (25 vs 14 days, p < 0.001, Table S3 ). Plotting data from all deceased patients in both cohorts revealed an inverse correlation between MAIT cell CD69 levels and days since symptom debut to sampling (Fig. 3G) , raising the possibility that high levels of MAIT cell activation early in disease may be associated with immunopathogenesis and poor outcome. In addition to high CD69, low CXCR3 and slightly higher PD-1 expression also characterized the PhenoGraph clusters associated with poor outcome (Fig. 3B ). The four patients of the Atlas cohort who died at hospital tended to have lower CXCR3 expression on their MAIT cells than patients who survived, and this pattern reached significance in the Biobank cohort (Fig. 3H) . A similar pattern was observed with high PD-1 expression on MAIT cells, which was associated with poor outcome in the Biobank cohort (Fig. 3I ). Together, these All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20182550 doi: medRxiv preprint findings suggest that activation and chemokine receptor expression in MAIT cells is associated with disease severity and may be associated with clinical outcome of COVID-19 disease. Some chronic viral diseases are associated with partial loss of MAIT cells in circulation, which may be persistent with failure to recover when viremia is suppressed or cleared by treatment (35) (36) (37) . To determine the ability of MAIT cells to recover after COVID-19, we analyzed peripheral blood samples drawn from patients recovering from mild disease (MC) (n=23), and from patients in the convalescent phase after severe COVID-19 (SC) (n=22), within one to six weeks from resolution of disease (Table S1) In contrast, CXCR3 levels were still suppressed, in particular in the SC group, raising the possibility that low CXCR3 expression may be a persistent alteration in MAIT cells post-COVID-19 (Fig. 4D ). CD38 and other activation markers tended to normalize (Fig. S5 ). Together, these results indicate that MAIT cells recover in circulation within weeks of resolution of COVID-19 symptoms, although some phenotypical perturbations still persist. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20182550 doi: medRxiv preprint MAIT cells play a significant role in the immune defence against microbial infections in mucosal barriers via TCR-mediated recognition of MR1-presented riboflavin metabolites. However, cytokines such as IL-18 and IFNα (12). We here found that MAIT cells are highly activated in COVID-19, and decline sharply in numbers in circulation already in moderate disease in a manner correlated with serum levels of CCL20, CXCL11, CCL28 and IL-17C. Notably, the MAIT cell lymphopenia was more profound than that observed for conventional CD8 and CD4 T cells, and other unconventional T cell subsets. Findings in two separate scRNAseq data sets indicated that MAIT cells are highly enriched among T cells infiltrating the airways during COVID-19. MAIT cell activation levels (CD69 high ) were associated with detectable plasma viremia and correlated with increased serum levels of CXCL10 and CX3CL1. MAIT cell activation may be associated with downregulation of CXCR3, as indicated by the inverse correlation between CD69 and CXCR3. The CXCR3 low phenotype seems more stable and was seen also in the mucosal scRNAseq data. Notably, both these MAIT cell phenotypes (CD69 high and CXCR3 low ) were associated with poor clinical outcome among COVID-19 patients as assessed in the present cohort. One should bear in mind however that the number of patients studied here is small, and these MAIT cell phenotypes should not be interpreted as predictive biomarkers of poor outcome. Nevertheless, these associations and patterns support a model where MAIT cell activation may be part of the broader virus-driven type I IFN response (38) (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20182550 doi: medRxiv preprint activated in response to SARS-CoV-2 infection, preferentially recruited to the inflamed airway mucosa, and contribute to tissue inflammation during COVID-19 disease. Persistent loss of MAIT cells can have detrimental long term consequences for immune defense against microbial disease and immune homeostasis at barrier sites (45, 46) . Thus, it is interesting and promising that MAIT cells seem to recover in convalescent COVID-19 patients, even within weeks from resolution of symptoms. This pattern is compatible with recruitment to the airways rather than physical loss of MAIT cells during active disease. It is possible that, as inflammation is resolved, the MAIT cells are again released to circulation. With regard to the phenotypical MAIT cell characteristics, most seem to normalize in convalescence. However, CXCR3 expression remains suppressed and some convalescent donors have a disturbed balance of CD8 + and DN MAIT cell subsets. The CXCR3 low phenotype is more stable than the more transient CD69 high phenotype. Overall, the relatively rapid recovery of the MAIT cell compartment bodes well for the ability of these individuals to control future microbial infections, although this topic will require dedicated studies. Loss of detectable CXCR3 expression in MAIT cells seems to be linked to activation as indicated by the inverse correlation with CD69 expression. However, a range of other chemokine receptors might be involved in recruitment of MAIT cells to inflamed airways. This includes CXCR6, which is consistently expressed by MAIT cells in healthy donors, and largely remains expressed in COVID-19 albeit with somewhat lower expression in patients with reduced MAIT cell frequencies (Fig. 2F) . It is interesting to note that the gene encoding CXCR6 is one of six genes located within the 3p21.31 locus strongly associated with severe COVID-19 in a recent genome wide association study (47) . The role of CXCR6, as well as of CCR5 and CXCR4, in MAIT cell recruitment in COVID-19, and in COVID-19 in general, is currently unclear and should be topics of future investigation. The current study presents evidence for a role of MAIT cells in COVID-19 disease, which is distinct from that of adaptive conventional T cells. However, the study at the same time has several limitations. COVID-19 is heterogeneous in its presentation with a wide range of disease severity, symptoms and kinetics of disease. While the patient groups studied here were all well-defined, they still do not reflect the full complexity of the disease. Furthermore, the cross-sectional design does not capture the full disease dynamics. In particular, sampling very early following infection or symptom debut would be valuable in future studies. Nevertheless, despite these limitations the current study suggests a role for MAIT cells in COVID-19 and opens new avenues to be explored for better understanding of the immunopathogenesis of this disease. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. Samples obtained from individuals in the convalescent phase after mild disease (MC) (n=23), were collected 49-64 days after disease onset, corresponding to 25-53 days after resolution of symptoms. Samples from the COVID-19 Biobank cohort were PBMC from ICU patients cryopreserved in liquid nitrogen, and thawed immediately before staining (n=14). The severity of the disease was also graded with NIH Ordinal Scale (48) , and SOFA score at the sampling (49). For detailed clinical information, see Tables S1 and S2. The study was approved by the Swedish Ethical Review Authority and all patients gave informed consent. The following antibodies were used for staining: CD69-BUV395 (clone FN50), CD38-BUV496 (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. PBMCs. Sera were evaluated for soluble factors using proximity extension assay technology (Olink AB, Uppsala). All sera were heat-inactivated (56ºC for 30 min) before analysis. Absolute counts in whole blood were assessed by flow cytometry using BD Multitest™ 6-color TBNK reagents in association with BD Trucount™ tubes (BD Biosciences) following the manufacturer's instructions. Samples were fixed 2 h at RT in 1% PFA before acquisition on the BD FACSymphony (BD Biosciences). CD3 + T cells were gated out of CD45 + CD14 -CD15 -CD19cells and the number of events obtained was used to determine the absolute CD3 counts as follow: (Number of CD3+ events acquired x number of beads per tubes) / (number of beads events acquired x sample volume in μL). The absolute count of each T cell subset analyzed was subsequently calculated using their frequencies out of total CD3 + cells. Publicly available scRNAseq datasets were analyzed using standard Seurat All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. PCA were performed in Python, using scikit-learn 0.22.1. Phenotypic data obtained from flow cytometry for each cell subset was normalized using sklearn.preprocessing. StandardScaler and PCA were computed on the resulting z-scores. Prism V7.0 (GraphPad Software) and python were used for statistical analysis. Statistically significant differences between unpaired groups were determined using non-parametric Mann-Whitney test for two group comparison or Kruskal-Wallis test followed by Dunn's post-hoc correction when more than two groups were compared. Two parameter correlations were evaluated using the Spearman correlation. Correlation heat maps were generated in Python using the pingouin package v0.3.6 (https://pingouin-stats.org) for computing Spearman and rank-biserial correlations as well as the associated p-values. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20182550 doi: medRxiv preprint Table S1 . Demographic and clinical characteristics of the acute COVID-19 Atlas cohort, healthy donors, and convalescent patients. Table S2 . Demographic and clinical characteristics of the COVID-19 Biobank cohort patients. Table S3 . Demographic and clinical data comparison between the acute COVID-19 Atlas cohort and the Biobank cohort. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20182550 doi: medRxiv preprint Kruskal-Wallis test and Dunn's post-hoc test were used to detect significant differences between groups. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. test were used to detect significant differences between the acute and convalescent groups. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20182550 doi: medRxiv preprint Figure 1 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20182550 doi: medRxiv preprint Figure 2 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20182550 doi: medRxiv preprint Figure 3 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20182550 doi: medRxiv preprint Figure 4 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20182550 doi: medRxiv preprint The trinity of COVID-19: immunity, inflammation and intervention Complex Immune Dysregulation in COVID-19 Patients with Severe Respiratory Failure Clinical and immunological features of severe and moderate coronavirus disease 2019 Detection of SARS-CoV-2-Specific Humoral and Cellular Immunity in COVID-19 Convalescent Individuals Marked T cell activation, senescence, exhaustion and skewing towards TH17 in patients with COVID-19 pneumonia Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls Comprehensive mapping of immune perturbations associated with severe COVID-19 MR1 presents microbial vitamin B metabolites to MAIT cells CD161++ CD8+ T cells, including the MAIT cell subset, are specifically activated by IL-12+IL-18 in a TCR-independent manner Ussher, Type I interferons are important co-stimulatory signals during T cell receptor mediated human MAIT cell activation MAIT cells are licensed through granzyme exchange to kill bacterially sensitized targets Arming of MAIT Cell Cytolytic Antimicrobial Activity Is Induced by IL-7 and Defective in HIV-1 Infection Human MAIT cell cytolytic effector proteins synergize to overcome carbapenem resistance in Escherichia coli Antimicrobial activity of mucosal-associated invariant T cells MAIT cells protect against pulmonary Legionella longbeachae infection MAIT cells are critical for optimal mucosal immune responses during in vivo pulmonary bacterial infection MAIT cells promote inflammatory monocyte differentiation into dendritic cells during pulmonary intracellular infection MAIT cells reside in the female genital mucosa and are biased towards IL-17 and IL-22 production in response to bacterial stimulation Mucosal-associated invariant T cells are a profibrogenic immune cell population in the liver Human mucosalassociated invariant T cells contribute to antiviral influenza immunity via IL-18-dependent activation MAIT cells are activated during human viral infections Dynamic MAIT cell response with progressively enhanced innateness during acute HIV-1 infection MAIT cells contribute to protection against lethal influenza infection in vivo Natural killer cell immunotypes related to COVID-19 disease severity Neutrophils Driving Unconventional T Cells Mediate Resistance against Murine Sarcomas and Selected Human Tumors The CD4(-)CD8(-) MAIT cell subpopulation is a functionally distinct subset developmentally related to the main CD8(+) MAIT cell pool COVID-19 severity correlates with airway epithelium-immune cell interactions identified by single-cell analysis Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19 Human MAIT cells are xenobiotic-resistant, tissue-targeted, CD161hi IL-17-secreting T cells Activation, exhaustion, and persistent decline of the antimicrobial MR1-restricted MAIT-cell population in chronic HIV-1 infection Early and nonreversible decrease of CD161++/MAIT cells in HIV infection Nonreversible MAIT cell-dysfunction in chronic hepatitis C virus infection despite successful interferon-free therapy Immunophenotyping of COVID-19 and influenza highlights the role of type I interferons in development of severe COVID-19 CD8(+) MAIT cells infiltrate into the CNS and alterations in their blood frequencies correlate with IL-18 serum levels in multiple sclerosis MAIT cells are activated and accumulated in the inflamed mucosa of ulcerative colitis MAIT cells launch a rapid, robust and distinct hyperinflammatory response to bacterial superantigens and quickly acquire an anergic phenotype that impedes their cognate antimicrobial function: Defining a novel mechanism of superantigen-induced immunopathology and immunosuppression MAIT Cells Are Major Contributors to the Cytokine Response in Group A Streptococcal Toxic Shock Syndrome Tissueresident MAIT cell populations in human oral mucosa exhibit an activated profile and produce IL-17 Severely Impaired Control of Bacterial Infections in a Patient With Cystic Fibrosis Defective in Mucosal-Associated Invariant T Cells Absence of mucosal-associated invariant T cells in a person with a homozygous point mutation in MR1 We express our gratitude to all donors, health care personnel, study coordinators, administrators, and laboratory managers involved in this work. The MR1 tetramer technology was developed jointly by Dr. James McCluskey, Dr. Jamie Rossjohn, and Dr. David Fairlie, and the material was produced by the NIH Tetramer Core Facility as permitted to be distributed by the University of Melbourne. The authors declare that they have no competing financial interests, patents, patent applications, or material transfer agreements associated with this study. Curated flow cytometry data is available for exploration via the Karolinska COVID-19 Immune Atlas (homepage currently under construction). Other data are available on request from the corresponding author.