Absence of mucosal-associated invariant T cells in a person with a homozygous point mutation in MR1

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Science Immunology  24 Jul 2020:
Vol. 5, Issue 49, eabc9492
DOI: 10.1126/sciimmunol.abc9492

A human immune system sans MAITs

Here, Howson et al. set out to determine the genetic basis of immunodeficiency in a patient with persistent tattoo-associated human papilloma virus–positive warts. Whole-exome sequencing led them to identify a rare point mutation Arg31His (R9H in the mature protein) in both copies of the MR1 gene. MR1 encodes an MHC-like molecule that presents bacteria-derived riboflavin metabolites to mucosal-associated invariant T (MAIT) cells. MAIT cells represent ~5% of circulating human T cells. MAIT cells reside in high frequency in mucosal tissues and provide enhanced immunity against bacterial and viral infections. By solving the structure of the MR1-R9H mutant, they demonstrate that this mutation disrupted the ligand-binding domain of MR1. Consistent with this finding, the individual lacked circulating MAIT cells.


The role unconventional T cells play in protective immunity in humans is unclear. Mucosal-associated invariant T (MAIT) cells are an unconventional T cell subset restricted to the antigen-presenting molecule MR1. Here, we report the discovery of a patient homozygous for a rare Arg31His (R9H in the mature protein) mutation in MR1 who has a history of difficult-to-treat viral and bacterial infections. MR1R9H was unable to present the potent microbially derived MAIT cell stimulatory ligand. The MR1R9H crystal structure revealed that the stimulatory ligand cannot bind due to the mutation lying within, and causing structural perturbation to, the ligand-binding domain of MR1. While MR1R9H could bind and be up-regulated by a MAIT cell inhibitory ligand, the patient lacked circulating MAIT cells. This shows the importance of the stimulatory ligand for MAIT cell selection in humans. The patient had an expanded γδ T cell population, indicating a compensatory interplay between these unconventional T cell subsets.


Unconventional T cells are a group of immune cell subsets that sit at the interface of innate and adaptive immunity. However, their role in coordinating and participating in human immune responses is unclear. This is partly due to the discrepancy in frequency and phenotype of these unconventional T cells between humans and mice (1). Mucosal-associated invariant T (MAIT) cells are a highly conserved unconventional T cell subset that is found in high frequency in humans (2, 3). These cells recognize microbially derived vitamin B–related metabolites that are presented by the major histocompatibility complex (MHC) class I–related molecule, MR1 (4, 5). Specifically, 5-(2-oxopropylideneamino)-6-D-ribitylaminouracil (5-OP-RU) is a very potent MAIT cell stimulatory ligand (6), whereas other ligands such as 6-formylpterin (6-FP) and its analog acetyl-6-formylpterin (Ac-6-FP) can be presented by MR1 but do not activate MAIT cells (5).

Presently, mouse models of infection and observational studies in humans have largely shaped our understanding of the role MAIT cells play in immunity. MAIT cells have been identified and characterized in various disease settings, including bacterial infection in which they participate in T cell receptor (TCR)–dependent responses and play an important role in controlling the infection (710). They also participate in cytokine-mediated TCR-independent responses, where they play a role in controlling viral infection (11, 12) and have been implicated in autoimmunity (13) and cancer (14). In addition, a loss of MAIT cells [along with a loss of natural killer T (NKT) cells and interleukin-17A (IL-17A)–producing T cells] has been reported in biallelic mutations in RORC. These individuals have difficulty controlling Candida and Mycobacterium infections, suggesting that MAIT cells may be central in controlling these infections. However, examining the specific contribution of MAIT cells to human immunity has not been explored, and we do not know whether they are integral for protective immunity or simply bystanders with a redundant role.

Here, we studied the role of MAIT cells in human immunity when an MR1 mutation was identified in a patient with unexplained primary immunodeficiency, characterized by tattoo-associated persistent human papilloma virus–positive (HPV+) warts. This patient is the first described case of a selective loss of MAIT cells. We show that this lack of MAIT cells is due to an R9H mutation causing structural changes to the ligand-binding pocket of MR1, preventing the accommodation of the MAIT cell stimulatory ligand 5-OP-RU. Extensive immune phenotyping revealed an expanded Vγ9/Vδ2+ T cell population, suggesting a potential immune compensatory mechanism by this innate T cell subset.


Whole-exome sequencing of a patient revealed a homozygous mutation in MR1

A 31-year-old male patient was identified with unexplained primary immunodeficiency, characterized by tattoo-associated persistent HPV+ warts (fig. S1). The patient also had a history of immune-related complications, namely, treatment-refractory Campylobacter gastroenteritis when he was 25 years old and development of pneumonia secondary to varicella-zoster virus infection that caused lung scarring when he was an infant (see Supplementary Text for full case report). The patient was selected for whole-exome sequencing when the cause for this immunodeficiency could not be clinically determined. Whole-exome sequencing revealed that the patient was homozygous for two rare single-nucleotide variants (SNVs) with immune-related functions (Fig. 1A and see tables S1 and S2 for the full list of SNVs).

Fig. 1 Whole-exome analysis reveals rare homozygous missense SNV rs41268456 in MR1.

(A) Diagram showing whole-exome sequencing results for a patient with persistent HPV infection. For the full SNV list, see tables S1 and S2. QC, quality control. (B) Graphical representation of the MR1 protein; line shows location of the point mutation at position 9 of the ligand-binding pocket of MR1. SP, signal peptide. Sanger sequencing results confirm the G>A substitution in the patient’s MR1 gene compared with a WT control and heterozygous parents. (C) Ligand-binding pocket of WT MR1 (PDB: 6PUC) showing how R9 (circled in blue) interactions stabilize 5-OP-RU within the A′-pocket. MR1 helices, sheets, and residues are shown in gray, and 5-OP-RU is shown as green sticks. H-bonds are shown as green dashes, except for R9-mediated H-bonds that are shown as black dashes. (D) Familial segregation of the MR1R9H mutation in a nonconsanguineous Australian family. (E) Population frequency of rs41268456 and the proportion of heterozygous versus homozygous individuals. Values are based on data accessed via the online gnomAD (17).

The first SNV rs35337543, resulting in a splice variant of IFIH1, has been previously characterized as loss-of-function mutation of the MDA5 protein (15), and further examination of this gene mutation in the patient can be found in the rs35337543 SNV report (see Supplementary Text and fig. S2). Therefore, we focused on the patient’s second homozygous immune-related SNV that is yet to be characterized, rs41268456, which is a G>A substitution at position 92 of the MR1 transcript (c.92G>A). It occurs in an exon region that results in an arginine-to-histidine substitution at position 31 of the amino acid sequence, corresponding to position 9 of the mature MR1 protein after the signal peptide is cleaved (R9H) (fig. S3A). R9H has a combined annotation-dependent depletion (CADD) score of 9.12 and a polyphen score of 0.92 with a prediction of probably damaging. This mutation resides within the ligand-binding pocket of the MR1 amino acid sequence (Fig. 1B), with R9 being a conserved residue across mammalian species (fig. S3B). Structural studies have shown that R9 lies within the A′-pocket of MR1 and interacts directly with the ligand, but this interaction differs depending on the ligand bound. For example, R9 forms hydrogen bonds with the ribityl 3′ and 4′-hydroxyl groups and the uracil C-2 carbonyl oxygen of 5-OP-RU (Fig. 1C) while making hydrogen bonds to the ring carbonyl oxygen of 6-FP (4, 5, 16). The patient was born to nonconsanguineous parents who were both heterozygous for the MR1R9H mutation, confirming an autosomal recessive inheritance pattern (Fig. 1, B and D). The homozygous population frequency for rs41268456 is 0.000106 (15 individuals from a total cohort of 141,456), with a slightly higher frequency of 0.000203 in the European population, based on the Genome Aggregation Database (gnomAD) cohort (Fig. 1E) (17). However, there is no clinical information available for the 15 homozygous individuals in the gnomAD database, and there are yet to be any scientific studies that report the biological implications of this mutation.

The MR1R9H/R9H patient lacked circulating MAIT cells

To determine the functional implications of the MR1R9H mutation, the frequency of MAIT cells in the peripheral blood of the MR1R9H/R9H patient was examined and compared with healthy age- and gender-matched donors with wild-type (WT) MR1 (fig. S3C). The MR1R9H/R9H patient had no MAIT cells present based on MR1-5-OP-RU antigen-loaded tetramer staining or by staining with the MAIT cell surrogate markers: TCR Vα7.2 and CD161 (Fig. 2A). To confirm that the MR1R9H/R9H patient lacked functional MR1-5-OP-RU–reactive MAIT cells, we stimulated peripheral blood mononuclear cells (PBMCs) with the MAIT cell antigen 5-OP-RU (6). In contrast to the response of PBMCs from healthy controls, we failed to detect any circulating T cells producing tumor necrosis factor (TNF) from the patient (Fig. 2B). We also confirmed that the Vα7.2+ CD161 population did not display any difference compared with healthy donors in their reactivity to stimulation (fig. S5). We next examined the circulating αβ T cell populations from the MR1R9H/R9H patient. He had a normal frequency of NKT cells but was mildly lymphopenic with reduced CD4 and CD8 T cell total cell counts and frequencies (fig. S6A and table S3). The MR1R9H/R9H T cells were also mostly composed of memory T cells and showed a robust effector response to stimulation (fig. S6, B and C). Thus, the MR1R9H/R9H patient has a selective loss of MAIT cells, while all other T cell subsets remained intact.

Fig. 2 The MR1R9H/R9H patient lacks MAIT cells, and their antigen-presenting cells cannot activate in an MR1-restricted manner.

Analysis of MAIT cells in PBMCs from MR1WT/WT controls (n = 3 to 5, age/gender-matched to patient), MR1WT/R9H parents (n = 2), and MR1R9H/R9H patient (n = 1, two or three time points, 3 months apart). (A) Representative flow cytometry plots showing circulating MAIT cells. Cells are gated on the CD3+ TCRαβ+ TCRγδ population, and MAIT cells were identified by the surrogate markers Vα7.2+ CD161+ or by the MR1-5-OP-RU–loaded tetramer. Graph shows the frequency of MAIT cells (Va7.2+ CD161+ MR1-5-OP-RU tetramer+). (B) Representative flow cytometry plots of TNF production by PBMCs (gated on CD3+ TCRαβ+ TCRγδ population) when cultured with 1 nM 5-OP-RU and BFA for 18 hours. (C) Allogeneic MAIT cell activation coculture, where MR1WT/WT control B cells (n = 2), MR1WT/R9H parent B cells (n = 2), or MR1R9H/R9H patient B cells (n = 1, two time points, 3 months apart) were preincubated for 4 hours with indicated concentrations of 5-OP-RU. Cells were washed, and BFA was added and cocultured with allogeneic healthy donor T cells for 18 hours. Cytokine production by CD3+ Vα7.2+ CD161+ cells was then measured by intracellular staining for TNF and IFNγ. See fig. S4 for flow cytometry gating strategies.

The MR1R9H/R9H patient’s antigen-presenting cells were defective in antigen presentation

We next wanted to understand whether the lack of MAIT cells in the MR1R9H/R9H patient was a result of his antigen-presenting cells being unable to present MAIT cell–activating ligands. To test this, we pulsed B cells with 5-OP-RU and then cultured them with T cells from an allogeneic MR1WT/WT donor. We found that MR1R9H/R9H B cells had a diminished capacity to activate the allogeneic MAIT cells compared with B cells from a MR1WT/WT donor (Fig. 2C). Thus, the MR1R9H mutation has a direct impact on MR1-restricted antigen presentation.

To directly examine the impact of the MR1R9H mutation on ligand binding, we tested the capacity of MR1R9H/R9H B cells to up-regulate MR1 in response to 5-OP-RU and the nonstimulatory MR1 ligand Ac-6-FP, both of which induce WT MR1 up-regulation (18). We observed that, although the MR1R9H/R9H patient’s B cells could up-regulate MR1 upon addition of Ac-6-FP, 5-OP-RU did not induce MR1 up-regulation (Fig. 3A). This observation was confirmed by examining MR1 up-regulation on C1R cells overexpressing either MR1R9H or WT MR1 (Fig. 3, B and C). Thus, the MR1R9H mutation appears to selectively disrupt 5-OP-RU binding to MR1.

Fig. 3 MR1R9H does not up-regulate in response to 5-OP-RU.

(A) Histogram and graph showing the expression of MR1 on CD19+ B cells. PBMCs were incubated with Ac-6-FP (10 μM) or 5-OP-RU (1 μM) for 4 hours and then stained with MR1 8F2.F9 antibody and anti-CD19. Each symbol in the graph represents an individual, line is at mean, and error bars represent SE. (B) Histogram shows MR1 expression on C1R.MR1 WT and C1R.MR1R9H cell lines after addition of Ac-6-FP (10 μM) or 5-OP-RU (1 μM) and incubation for 4 hours. (C) MR1 up-regulation time course assay showing the dynamics of MR1 up-regulation after addition of Ac-6-FP (10 μM) or 5-OP-RU (1 μM) on C1R.MR1 WT and C1R.MR1R9H over 24 hours. Each point represents the mean between three independent experiments, and error bars represent SE. Statistical significance was calculated using two-way ANOVA with Geisser-Greenhouse correction and Sidak’s multiple comparison test, where *P < 0.05. See fig. S4 for flow cytometry gating strategies.

The MR1R9H mutation caused structural changes to the A′-pocket of MR1

To understand how the MR1R9H mutation affects ligand binding, we expressed and refolded MR1R9H in the presence of Ac-6-FP and 5-OP-RU and then crystallized their co-complexes with a MAIT cell TCR and subsequently solved the structures to high resolution (see table S4 for all crystal structure supporting data). Unexpectedly, MR1R9H was refolded in the presence of 5-OP-RU, but the A′-pocket was empty (Fig. 4A). WT MR1 requires binding of a ligand for stabilization and correct folding (5). However, the MR1R9H protein appears to not require the presence of a ligand to refold, similar to how the MR1K43A mutant protein can be refolded without ligand (19). This was confirmed when MR1R9H refolded in the absence of any exogenously added ligand (fig. S7). Within the empty MR1R9H A′-pocket, the imidazole side chain of the H9 residue formed new van der Waals interactions with the indole group of W69, causing W69 to flip and reorientate toward the base of the A′-pocket (Fig. 4A and fig. S8B). In addition, water molecules found within the A′-pocket established a network of H-bonds with K43, H58, H9, and S24 residues. Together, these hydrophobic and polar interactions stabilized MR1R9H, enabling it to be refolded without ligand. Moreover, this reorientation of W69 and the presence of H9 partially fill the A′-pocket and sterically preclude 5-OP-RU binding (Fig. 4B). However, MR1R9H did refold and complex with Ac-6-FP, where the ligand formed a Schiff base with K43 of MR1 (Fig. 4C and fig. S7D). Here, the reorientation of W69 does not interfere with Ac-6-FP binding but forms hydrophobic interactions with the ligand in an analogous manner to how Ac-6-FP binds to WT MR1 (Fig. 4D). Consequently, although the nonstimulatory ligand can still bind MR1R9H, the stimulatory ligand cannot.

Fig. 4 The R9H mutation causes structural changes to the ligand-binding pocket of MR1.

The crystal structures of the ligand-binding pocket of WT MR1 and MR1R9H. (A) MR1R9H-empty and (C) MR1R9H-Ac-6-FP of the ternary MAIT TCR-MR1R9H complexes. Maps were prepared using the Phenix.refine crystallographic structure refinement program and presented as a 2FobsFcalc map (observed structure factor − calculated structure factor; mesh) contoured at 1σ. (B) Superposition of the ligand-binding pocket of WT MR1-5-OP-RU [PDB: 6PUC (16)] and MR1R9H-empty; arrow shows the new orientation of W69, and steric clashes between 5-OP-RU conformation in WT MR1 and MR1R9H-empty structures are shown as red dashes. (D) Superposition of the ligand-binding pocket of WT MR1-Ac-6-FP [PDB: 4PJ5 (39)] and MR1R9H-Ac-6-FP, showing similar binding of Ac-6-FP within the pocket. Ac-6-FP and 5-OP-RU ligands are shown as ruby and green sticks, respectively. Water molecules are shown as red spheres, and hydrogen bonding is shown as dashed lines.

The MR1R9H mutation caused structural instability of MR1, affecting its cellular trafficking

Thermal stability assays showed that the empty MR1R9H molecule was less stable compared with MR1R9H-Ac-6-FP and much less stable than WT MR1 when it is bound to either 5-OP-RU or Ac-6-FP (Fig. 5A). To examine whether the unstable nature of MR1R9H affected its cellular trafficking, we examined its maturation through the secretory pathway by testing endoglycosidase H (endo-H) sensitivity. It has been previously shown that WT MR1 is largely retained in the endoplasmic reticulum (ER) (endo-H–sensitive), and the presence of ligand causes it to refold and traffic through the Golgi apparatus to the cell surface (endo-H–resistant) (18). We observed that MR1R9H resides mostly in the ER, similar to WT MR1, and in the presence of Ac-6-FP, it could traffic to the cell surface (Fig. 5B), whereas upon addition of 5-OP-RU the MR1R9H remained in the ER. Furthermore, when we examined the stability of MR1 molecules at the cell surface by measuring its rate of internalization, MR1R9H was internalized faster than WT MR1, both without ligand and in the presence of Ac-6-FP (Fig. 5C). These results confirm the MR1R9H ligand discrimination that we have previously described above and also demonstrate the unstable nature of MR1R9H at the cell surface.

Fig. 5 The R9H mutation affects the stability and cellular trafficking of MR1.

(A) Thermostability of soluble WT MR1 and MR1R9H as measured by fluorescence-based thermal shift assay. Graph shows baseline-corrected, normalized emission at 610 nm plotted against temperature (°C) and Boltzmann curve fits. Each point represents the mean of at least two technical replicates, and error bars represent SD. The half-maximum melting point (Tm50) is represented as a dotted line. Table shows the mean Tm50 across three independent experiments, each measured in at least technical duplicate. Data are representative of three independent experiments. (B) C1R cells transduced with either WT MR1 or MR1R9H were cultured alone or with 2 μM 5-OP-RU or Ac-6-FP for 5 hours. MR1 was immunoprecipitated (IP) using anti–MR1-CT or normal rabbit serum (NRS) as a control, treated with or without endo-H, and then immunoblotted (IB) for MR1. Actin IB was on a portion of whole cell lysate. Graph shows the amount of endo-H–resistant MR1 determined by densitometry and calculated as a percentage of the total MR1 for each immunoprecipitation. Graph bars represent the mean of four independent experiments, and error bars represent SEM. S, endo-H–sensitive; R, endo-H–resistant. (C) C1R.MR1 WT or C1R.MR1R9H cell lines were cultured alone or with 10 μM Ac-6-FP overnight. The amount of internalized MR1 was measured using a FIP conjugated to anti–MR1 8F2.F9 antibody. Each point represents the mean of two independent experiments, and error bars represent SD.

The MR1R9H/R9H patient did not have any detectable MR1-restricted T cell populations

To examine the MR1R9H/R9H patient’s MR1-restricted T cell populations, we stained PBMCs with WT MR1 and MR1R9H tetramers. The patient did not have any WT MR1-restricted T cell populations present (fig. S9). We also did not observe any difference between MR1WT/WT controls’ and MR1R9H/R9H patient’s MR1R9H-Ac-6-FP or MR1R9H-empty tetramer+ T cell frequencies, because no distinct populations were detected. This lack of TCR reactivity toward MR1R9H was confirmed by surface plasmon resonance (SPR) experiments (fig. S10). Thus, the MR1R9H/R9H patient does not have any detectable MR1-restricted T cell populations.

Immune phenotyping of the MR1R9H/R9H patient’s PBMCs revealed that all other immune cell populations were present

We next wanted to determine whether the MR1R9H/R9H patient’s immune system was altered or compensating for the absence of MAIT cells. Immune cell phenotyping revealed that the MR1R9H/R9H patient’s circulating NK cell and monocyte frequencies were similar or slightly lower (for NK cells) compared with those of MR1WT/WT controls, and there were no major differences to the NK or monocyte subsets (fig. S11). However, when examining the B cell subsets, we observed a reduction in memory B cells in the MR1R9H/R9H patient (fig. S12). This lack of memory B cells could be an indication of deficient humoral immunity and is a typical observation made in a range of primary immunodeficiencies, such as specific antibody deficiency and common variable immunodeficiency (20). However, the MR1R9H/R9H patient still had detectable plasma cells (fig. S12B), normal serum immunoglobulin (Ig) levels (table S5), and a robust vaccine response (see Supplementary Text), indicating that their low frequency of memory B cells does not have a considerable impact on the ability to mount humoral immune responses. These results confirm that the MR1R9H/R9H patient’s immune cell subsets are otherwise intact, with only a possible impairment in their memory B cell compartment.

The MR1R9H/R9H patient’s Vγ9/Vδ2+ T cells were overexpanded and fully functional in response to various stimuli

We also examined the MR1R9H/R9H patient’s γδ T cells and observed a sevenfold higher circulating frequency compared with healthy donors (Fig. 6A). This expanded γδ T cell population was almost exclusively composed of Vγ9/Vδ2+ T cells (Fig. 6B) that had a distinct CD27 CD28 phenotype (Fig. 6C). This is not a hallmark of HPV infection associated with primary immunodeficiency, because we also analyzed samples from patients with confirmed CXCR4 gain-of-function mutations resulting in WHIM (warts, hypogammaglobulinemia, immunodeficiency, and myelokathexis) syndrome, in which patients are highly susceptible to HPV infections (21, 22). The WHIM syndrome patients who tested HPV+ were examined and found to have a normal frequency of γδ T cells (Fig. 6, A and B). We tested the functionality of the MR1R9H/R9H patient’s Vγ9/Vδ2+ T cells and found that they exhibited intact effector functions in response to a range of different stimuli similar to MR1WT/WT controls (Fig. 6D). Paired TCR repertoire analysis revealed that the MR1R9H/R9H patient’s Vγ9/Vδ2+ T cells are clonally expanded, with one dominant clone comprising ~30% of the γδ T cell population (Fig. 6E), which is not typically seen in Vγ9/Vδ2+ T cells from healthy donors (23). An unusual feature of the MR1R9H/R9H patient’s Vγ9/Vδ2+ T cell population was that 50% of the TCR repertoire used the TRDJ3 gene segment, compared with healthy adults that predominantly used TRDJ1 (Fig. 6F).

Fig. 6 The MR1R9H/R9H patient has a highly expanded circulating Vδ2 γδ T cell population.

(A) Graph showing the frequency of circulating γδ T cells as a proportion of total T cells for controls (n = 4 age/gender-matched to MR1R9H/R9H patient, solid symbols; n = 6 age-matched to WHIM patients, open symbols), WHIM HPV+ patients (n = 3), MR1WT/R9H parents (n = 2), and MR1R9H/R9H patient (n = 1, three time points, 3 months apart). (B) Representative flow cytometry plots showing circulating frequencies of Vδ1 and Vδ2 as a percentage of the γδ T cell population in MR1WT/WT controls (n = 4), MR1WT/R9H parents (n = 2), and MR1R9H/R9H patient (n = 1, three time points, 3 months apart). Graph shows the frequency of Vγ9/Vδ2+ as a proportion of total γδ T cells. (C) Representative flow cytometry plots showing the frequency of Vδ2 T cells expressing CD27 and CD28. Graph shows the frequency of Vδ2+ γδ T cells that are CD27/CD28 (double negative, DN), CD27/CD28+, CD27+/CD28, and CD27+/CD28+. (D) Activation assay examining the Vδ2+ γδ T cell cytokine production in MR1WT/WT controls (n = 4), MR1WT/R9H parents (n = 2), and MR1R9H/R9H patient (n = 1, two time points, 3 months apart). Response to various stimuli is measured by intracellular staining for IL-2, TNF, and IFNγ after 18 hours of stimulation in the presence of BFA. Graph shows stacked results, where bar is at mean for each cytokine combination and error bars represent SE. (E) Vδ2+ γδ T cell clones revealed by single-cell multiplex PCR sequencing from the MR1R9H/R9H patient. Clones that were identified once are colored gray and clones that were identified multiple times are colored blue, and their CDR3γ and CDR3δ sequences are listed. (F) Graph of the TRDJ usage by Vγ9/Vδ2+ T cells in healthy controls (n = 3) compared with MR1R9H/R9H patient (n = 1). NS, no stimulation; EC, E. coli.

Next, we examined the total TNF/interferon γ (IFNγ) production by PBMCs in response to stimuli. The MR1R9H/R9H PBMCs showed a robust TNF/IFNγ response, for which 89% of the cells producing cytokine in response to Escherichia coli were the Vγ9/Vδ2+ T cells (Fig. 7A). To confirm this robust antibacterial response, we challenged PBMCs ex vivo to a variety of bacteria and examined the total cytokine production and cytotoxic response. We found that the patient’s PBMCs could produce proinflammatory cytokines and cytotoxic granules to all bacteria strains to the same extent as healthy donors (Fig. 7B and fig. S13). These results suggest that the MR1R9H/R9H patient is still able to produce a robust effector response when challenged with bacteria.

Fig. 7 The MR1R9H/R9H patient’s Vδ2+ γδ T cell population compensates functionally for the lack of MAIT cells during ex vivo bacterial challenge.

(A) Plots show the total TNF and IFNγ production by live PBMCs in response to various stimuli as measured by intracellular staining for TNF and IFNγ after 18 hours of stimulation in the presence of BFA. Pie charts show the proportions of each cell type contributing to the TNF and/or IFNγ production. HMBPP, (E)-4-hydroxy-3-methyl-but-2-enyl pyrophosphate (10 ng/ml); IL-12/IL-18, two doses of 200 ng/ml with IL-2 (100 U/ml) that were added 72 hours apart; EC, E. coli at MOI 50; PMA, phorbol 12-myristate 13-acetate (50 ng/ml) and ionomycin (1 μg/ml). (B) Graphs showing the concentration of cytokines and cytotoxic molecules measured using the LEGENDplex CD8/NK panel produced by PBMCs from MR1WT/WT controls (n = 3 to 4) and MR1R9H/R9H patient (n = 1, two time points, 3 months apart) when cultured with various bacteria at MOI 50 for 24 hours. PA, P. aeruginosa; SA, S. aureus; SE, S. epidermidis; EF, E. faecalis; Gr, granzyme. Each symbol in a graph represents an individual, bar is at mean, and error bars represent SEM.


The discovery of a patient with a homozygous mutation that affects MR1 presentation provided a unique opportunity to understand the role and importance of MAIT cells in human immunity. Alterations in MAIT cells have been previously observed in primary immunodeficiencies, where they are decreased in individuals with dominant mutations in STAT3 (24) and recessive mutations in IL12RB1 or IL23R (25). Furthermore, MAIT cells (along with NKT cells and IL-17A–producing T cells) are absent in cases of biallelic mutations in RORC (26). However, the immune phenotype of the MR1R9H/R9H patient is distinct, because there is a selective absence of MAIT cells.

Our observation that the MR1R9H homozygous mutation leads to a lack of MAIT cells provides some insights into what factors are vital for MAIT cell selection and/or survival in humans. Because MR1R9H cannot present 5-OP-RU, it suggests that 5-OP-RU itself or ligands that are structurally similar to 5-OP-RU are required for the selection and survival of MAIT cells in humans, consistent with a study that recently demonstrated this concept in mice (27).

A notable observation was the expansion of Vγ9/Vδ2+ T cells observed in the MR1R9H/R9H patient. This observation is consistent with the observed γδ T cell expansion reported in RORC mutated individuals (who lack MAIT cells) (26), suggesting that this could be an immune compensatory mechanism that occurs when MAIT cells are not present. This is unexpected, because it has been previously hypothesized that NKT cells, which are the most functionally and transcriptionally similar to MAIT cells (28), were the most likely cell subset to share a functional niche with MAIT cells. This was further supported by the observation that MAIT cells are expanded in CD1d knockout mice that lack NKT cells (29). Further evidence that Vγ9/Vδ2+ T cells and MAIT cells reside in the same functional niche is the MR1R9H/R9H patient’s robust ex vivo antibacterial immune response, which is largely mediated by the expanded Vγ9/Vδ2+ T cells. This observed ex vivo immune compensation may explain why the MR1R9H/R9H patient does not have a history of more severe and frequent bacterial infections, even though they lack MAIT cells.

Another unusual observation was the enrichment of the TRDJ3 TCR gene segment usage by Vγ9/Vδ2+ T cells. Enrichment of this gene segment is a hallmark of Vγ9/Vδ2+ T cells that are generated during ontogeny in the fetal thymus, compared with adult Vγ9/Vδ2+ T cells that typically use TRDJ1 and are generated independently of the thymus after birth (30). Thus, the Vγ9/Vδ2+ T cell population may have undergone selective pressures during early development of the MR1R9H/R9H patient’s immune system and resulted in retention and expansion of “fetal-like” Vγ9/Vδ2+ T cells.

The clinical aspect of this patient’s case is the onset of persistent HPV+ warts associated with extensive tattooing. Difficult-to-treat HPV is a hallmark of primary immunodeficiency, although the mechanism is unclear because the host immune defense against HPV is multifaceted, with immunity provided by various immune cells as well as nonimmune cells such as keratinocytes (31, 32). There have also been several cases reported of tattoo-associated HPV in otherwise immunocompetent individuals (33, 34), but in these cases, the lesions are localized to the tattoo itself, unlike the patient who has widespread lesions. This suggests that the barrier disruption caused by tattooing may contribute to the host’s lack of ability to mount an effective immune response against HPV. However, without information about which immune cells are at the site of the HPV lesions, it is not known which cells are implicated in the patient’s HPV-specific immune response.

A limitation of this study is that we have identified and characterized the MR1R9H mutation in a single patient who also had an immune-related homozygous mutation in IFIH1. This makes it difficult to attribute a clinical phenotype to the lack of MAIT cells caused by the MR1 mutation. Thus, a greater understanding would be gained from studying this mutation across multiple homozygous and heterozygous individuals to appreciate the nature and penetrance of clinical symptoms associated with MR1R9H and the degree of microbial susceptibility in those who carry this mutation.


Study design

The MR1R9H/R9H patient was recruited to the Genetic Immunology Flagship of Australian Genomics Health Alliance, which was approved by human research ethics committees at Australian Capital Territory Health Human Research Ethics Committee and Melbourne Health (protocols ETH.8.17.171E and HREC/16/MH/251) for whole-exome sequencing to determine the underlying cause of his primary immunodeficiency. Immune phenotyping of the patient’s blood samples was done with ethical approval for additional samples collected on three separate occasions at Monash Medical Centre from the Monash Health Human Research Ethics Committee (project ID: 52046). The MR1R9H/R9H patient’s parents’ blood was also collected for immune phenotyping. For comparison with the patient, age- and gender-matched healthy donors were recruited and blood samples were taken with ethical approval from the Monash University Human Research Ethics Committee (project ID: 19488). To provide an HPV+ control group for immune phenotyping comparison, WHIM patient samples were collected as part of a clinical research protocol approved by the Institutional Review Board of the National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH). Written informed consent was obtained from all study volunteers in accordance with the Declaration of Helsinki. The study was unblinded, and sample sizes were limited by the availability of donors but adequate to detect differences between sample groups.

Whole-exome sequencing

Genomic DNA was isolated from blood using the QIAamp DNA Blood Kit (Qiagen) according to the manufacturer’s instructions. For whole-exome sequencing, input DNA was analyzed for integrity and then fragmented by nebulization. DNA library preparation was performed using Agilent High Sensitivity whole exome capture, and libraries were sequenced as paired-end reads [100–base pair (bp) runs] on Illumina HiSeq 2500. Bioinformatics analysis was performed as previously described (35).

Human samples

Patients were recruited to the study at the Monash Medical Centre, and a blood sample was taken during a routine appointment. Healthy adult blood donors were from laboratory volunteers and from buffy packs obtained from Australian Red Cross Lifeblood or were obtained from the NIH Clinical Center Department of Transfusion Medicine. PBMCs were isolated from all blood samples and buffy packs by gradient centrifugation using Lymphoprep (STEMCELL Technologies) or Ficoll-Paque PLUS density gradient medium (GE Healthcare). Cells were then either used fresh or cryogenically frozen for later analysis.

Polymerase chain reaction confirmation of IFIH1 splice variation

RNA was extracted from PBMC samples using the PureLink RNA Mini Kit (Ambion), and complementary DNA (cDNA) was produced using SuperScript IV First-Strand Synthesis System (Invitrogen) following the manufacturer’s instructions. The cDNA was then used in a standard polymerase chain reaction (PCR) with GoTaq Green Master Mix (Promega) following the manufacturer’s instructions using the following primers designed to amplify the regions flanking exon 8 of the IFIH1 transcript: IFIH1.F, 5′-ACGAAGCAAGCCAAAGCTGA, and IFIH1.R, 5′-GGCCCATTGTTCATAGGGTTGA. Samples were then run on a 2% agarose gel with a 100-bp DNA ladder (New England Biolabs). Band size of the PCR product indicated whether exon 8 was present (258 bp) or absent (139 bp).

TaqMan qPCR assay for IFNA1 and IFNB1 induction

PBMCs were cultured with or without Poly(I:C) high molecular weight (HMW)/LyoVec (10 μg/ml) (InvivoGen) for 24 hours. RNA was extracted and cDNA was synthesized as described in the previous section. The cDNA was then used in a TaqMan quantitative PCR (qPCR) assay using TaqMan Fast Advanced Master Mix (Applied Biosystems) with TaqMan Gene Expression Assays for IFNA1 and IFNB1 and the reference gene HPRT1 (Thermo Fisher Scientific). Samples were then run on the CFX Connect Real-Time PCR Detection System (Bio-Rad) and quantified using the comparative CT method (2−ΔΔCT method).

Sanger sequencing of MR1

RNA was extracted and cDNA was synthesized as described in the previous section. The cDNA was then used in a standard PCR with GoTaq Green Master Mix following the manufacturer’s instructions using the following primers designed to amplify position R9 on the MR1 transcript: MR1.F, 5′-GGAACTGATGGCGTTCCTGT, and MR1.R, 5′-GTGGTGATAGGGTGCGAGTC. Samples were then sequenced with BigDye Terminator v3.1 (Applied Biosystems) following the manufacturer’s instructions and run on an Applied Biosystems 3730S capillary sequencer (Micromon Genomics, Monash University). Results were visualized using SnapGene Viewer.

Antibodies and staining reagents

Allophycocyanin (APC) anti-human CD56 (NCAM16.2), BB700 anti-human CD19 (SJ25C1), BUV395 anti-human CD3 (NCAM16.2), BUV395 anti-human CD8 (RPA-T8), BV786 anti-human IFNγ (4S.B3), fluorescein isothiocyanate (FITC) anti-human IgM (G20-127), phycoerythrin (PE) streptavidin, PE-CF594 anti-human IgD (IA6-2), and peridinin chlorophyll protein (PerCP)–Cy5.5 anti-human TNF (MAb11) were purchased from BD Biosciences. Alexa Fluor 700 anti-human CD16 (3G8), Alexa Fluor 700 anti-human CD4 (SK3), APC or Alexa Fluor 700 anti-human CD161 (HP-3G10), Brilliant Violet 605 anti-human CD38 (HIT2), Brilliant Violet 605 anti-human TCR Vα7.2 (3C10), Brilliant Violet 650 anti-human CD28 (CD28.2), Brilliant Violet 711 anti-human CD45RA (HI100), Brilliant Violet 785 anti-human CD45RO (UCHL1), PE anti-human CD14 (M5E2), PE anti-human IL-2 (MQ1-17H12), PE/Cy7 anti-human CD27 (M-T271), PE/Cy7 anti-human CD3 (UCHT-1), and PE/Dazzle 594 anti-human CD27 (M-T271) were purchased from BioLegend. APC anti-human TCR Vδ2 (123R3), APC-Vio770 anti-human TCRγ/δ (REA591), FITC anti-human TCR Vδ1 (REA173), and VioBlue anti-human TCRα/β (REA652) were purchased from Miltenyi Biotec. PC5 anti-human TCR Vγ9 (IMMU 360) was purchased from Beckman Coulter. A hybridoma cell line was used to produce the MR1 8F2.F9 and 26.5 antibodies (36). PBS-57–loaded CD1d tetramer was obtained from the NIH Tetramer Core Facility. Dead cells were excluded using the viability dye LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (Life Technologies). For immunoprecipitation experiments, a polyclonal rabbit antiserum was generated by the Walter and Eliza Hall Institute Antibody Facility against a peptide corresponding to the final 15 residues of the cytosolic tail of human MR1 (PREQNGAIYLPTPDR) (anti–MR1-CT).

Flow cytometry and cell sorting

For standard flow cytometry cell staining, cells were first stained with viability dye for 10 min at room temperature, followed by antibodies diluted in phosphate-buffered saline with 10% fetal bovine serum (Sigma-Aldrich) for 20 min on ice. Flow cytometry data were collected on BD LSRFortessa X20. Cell sorting was performed on BD FACSAria Fusion Cell Sorter. Data were analyzed using FlowJo cell analysis software (FlowJo LLC).

Ligands and compounds

Production of 5-OP-RU has been described previously (6). Ac-6-FP was purchased from Schircks Laboratories.

MAIT cell activation assay

PBMCs were cultured with 1 nM 5-OP-RU for 4 hours, and then brefeldin A (BFA) solution (eBioscience) was added and cells were cultured for 18 hours. Cells were collected and stained with viability dye before fixation and permeabilization using the eBioscience Intracellular Fixation and Permeabilization Buffer Set (Invitrogen). Antibodies diluted in permeabilization buffer were then incubated with cells for 45 min at room temperature.

Cell lines

Production of C1R cells overexpressing MR1 under the control of the p-MSCV-IRES-eGFP (pMIG) vector has been previously described (37). Using this protocol, we produced C1R cells expressing a single amino acid substitution R9H in MR1 by designing gBlock gene fragments (Integrated DNA Technologies) and cloning it into the pMIG vector and transfecting it into 293T cells with the retroviral packaging vectors (pPAM-E and pVSVG) using Fugene 6. The supernatant containing viral particles was then filtered through a 0.45-μm filter and added to WT C1R cells with polybrene to produce a stable transduction of cells overexpressing MR1R9H. The transduced C1R.MR1R9H cell line was then sorted for high expression of green fluorescent protein (GFP) and MR1.

Bacterial cultures

Bacteria E. coli, Pseudomonas aeruginosa, Staphylococcus aureus, Staphylococcus epidermidis, and Enterococcus faecalis were grown in lysogeny broth (LB) overnight and then diluted 1:100 and grown to log phase for 3 hours. OD600 (optical density at 600 nm) was measured and used to determine concentration.

MR1 up-regulation assay

Cells were cultured in the presence of 5-OP-RU (1 μM) or Ac-6-FP (10 μM) for 4 hours (unless specified otherwise) before staining with viability dye. Cells were then stained with biotinylated MR1 8F2.F9 for 30 min on ice, followed by streptavidin-PE (and any directly conjugated primary antibodies, if being used) for 20 min on ice. Cells were then analyzed on a flow cytometer.

Expression, refold, and purification of MR1-β2m and MAIT TCR proteins

Human WT MR1-β2m and MR1R9H-β2m were refolded in the presence of either Ac-6-FP or 5-OP-RU, as described previously (4). Human MR1R9H-β2m-empty was refolded in the absence of any ligand, producing refolded protein, confirmed by native gel and size exclusion chromatography (fig. S6). Soluble A-F7 (TRAV1-2/TRBV6-1) and TRAV1-2/TRBV6-4 MAIT TCR proteins were refolded from inclusion bodies, as described previously (38, 39). Refolded MR1 ligand and TCR proteins were purified by three consecutive purification steps: crude anion exchange, S200 15/60 size exclusion chromatography, and HiTrap Q HP anion exchange. The protein purity was then assessed using SDS–polyacrylamide gel electrophoresis (SDS-PAGE) and quantified using a NanoDrop spectrophotometer.

Generation of MR1 tetramers

C-terminal cysteine-tagged human MR1-β2m (complexed with ligand where indicated) was refolded and purified, as described in the previous section. The purified proteins were reduced by dithiothreitol (DTT), buffer-exchanged into Hepes-buffered saline [10 mM Hepes (pH 7.3), 150 mM NaCl, and 1 mM EDTA], and then biotinylated by incubation with biotin-maleimide overnight at 4°C. The biotinylated samples were purified by gel filtration, and biotinylation efficiency was assessed by native gel. Biotinylated proteins were then tetramerized with PE-conjugated streptavidin and used to stain cells at a 1:50 dilution.

Thermal stability assay

A thermal shift assay of the WT MR1 and MR1R9H proteins was performed in a real-time detection system (Corbett RotorGene 3000) using the fluorescent dye SYPRO Orange (Sigma-Aldrich) to monitor the protein unfolding upon heating. Both WT and MR1R9H (complexed with ligand where indicated) were purified by gel filtration just before the experiment and eluted in buffer of 10 mM tris-HCl (pH 8) and 150 mM NaCl. The samples were then heated from 25° to 95°C with a heating rate of 1°C/min. The fluorescence intensity was measured (excitation, 530 nm; emission, 610 nm) and used to infer protein unfolding. The half-maximum melting point (Tm50) represents the temperature for which 50% of the protein is unfolded.

Protein crystallization, structure determination, and refinement

Purified TRAV1-2/TRBV6-1 TCR was mixed with either WT or MR1R9H proteins (complexed with ligand where indicated) in a 1:1 molar ratio at a concentration of 2 to 4 mg/ml and incubated on ice for 4 hours. Hanging-drop method was used to produce crystals with a precipitant consisting of 100 mM bis-tris propane (BTP) (pH 6.1 to 6.7), 8 to 14% PEG3350, and 200 mM sodium acetate, as reported previously (38). Hexagonal complex crystals formed within a week at 20°C and were flash-frozen in liquid nitrogen after a short soak in reservoir solution with 14% glycerol for cryo-protection. X-ray diffraction data were collected at 100 K at the Australian Synchrotron at either MX1 or MX2 beamlines. Diffraction images were processed using XDS (40) and programs from the CCP4 suite (41) and Phenix package (42). Both ternary structures were determined by molecular replacement using PHASER (43), where a modified TCR-MR1 ternary complex [Protein Data Bank (PDB): 4NQC] was used as a search model. Model building was performed in COOT (44), accompanied with iterative rounds of refinement using Phenix.refine (42). The Grade Webserver and Phenix tools were used to build and to generate ligand restraints. The models were validated using MolProbity (45), and graphical representations were generated using PyMOL Molecular Graphics System Version 1.8 (Schrödinger LLC, New York, NY).


For immunoblotting and detection of MR1, cells were lysed in 0.5% IGEPAL CA-630 (Sigma-Aldrich), 50 mM tris-HCl (pH 7.4), and 5 mM MgCl2 with Complete Protease Inhibitor Cocktail (Roche), and nuclei were separated by centrifugation at 13,000g for 10 min. Lysates were precleared with normal rabbit serum (Sigma-Aldrich) and protein G-Sepharose and then with protein G-Sepharose alone. MR1 was immunoprecipitated using anti–MR1-CT and protein G-Sepharose and then washed three times with NET buffer [0.5% IGEPAL CA-630, 50 mM tris-Cl (pH 7.4), 150 mM NaCl, and 5 mM EDTA] and treated with Endoglycosidase Hf (New England Biolabs) according to the manufacturer’s instructions. Protein samples were denatured with reducing SDS-PAGE sample buffer, separated on NuPAGE 4 to 12% bis-tris precast gel (Life Technologies), and immunoblotted onto nitrocellulose membrane using the iBlot system (Life Technologies). Band density was quantified using FIJI analysis software.

Internalization assay

To measure MR1 internalization, a fluorescence internalization probe (FIP) using MR1 8F2.F9 antibody was generated as previously described (46). Briefly, the FIP conjugated to MR1 contains a DNA sequence conjugated to the fluorescent dye Cy5, which can be quenched by using a quencher conjugated to the cDNA sequence. Any Cy5 signal not quenched indicates protection due to internalization. Cells were labeled with MR1-FIP on ice and then washed and incubated at 37°C for the indicated times before being placed on ice to halt internalization. Cells were washed and resuspended with or without the quencher, and Cy5 fluorescence was analyzed by flow cytometry. The Cy5 signal remaining after quenching indicates internalized MR1 and was calculated as a percentage of the initial signal before internalization.

γδ T cell activation assay

PBMCs were cultured and pulsed with a range of stimulants. For cytokine stimulation, human IL-2 (100 U/ml; Roche), human IL-12 (200 ng/ml; Miltenyi Biotec), and human IL-18 (200 ng/ml; BioLegend), two doses 72 hours apart, with BFA (BioLegend) were added after the second dose and cultured for 18 hours. For bacterial stimulation, E. coli at a multiplicity of infection (MOI) of 50 was added to the PBMCs, left for 1 hour before adding gentamicin (50 μg/ml; Sigma-Aldrich) and BFA, and cultured for 18 hours. For (E)-4-hydroxy-3-methyl-but-2-enyl pyrophosphate (HMBPP) stimulation, HMBPP (10 ng/ml; Cayman Chemicals) was added and cultured for 4 hours before adding BFA and cultured for 18 hours. For a positive control, phorbol 12-myristate 13-acetate (PMA; 50 ng/ml) (Sigma-Aldrich) and ionomycin (1 μg/ml; Sigma-Aldrich) were added with BFA and cultured for 18 hours. After stimulation, cells were collected and stained with viability dye and stained with surface antibodies for 20 min on ice before fixation and permeabilization using the eBioscience Intracellular Fixation and Permeabilization Buffer Set (Invitrogen). Intracellular antibodies were diluted in permeabilization buffer, then added to cells and incubated for 45 min.

Single-cell γδ TCR sequencing

PBMCs were surface-stained with antibodies, and γδ T cells were single-cell sorted directly into individual wells in a 96-well PCR plate containing 2 μl of SensiFAST cDNA Synthesis Kit reaction mix (Bioline) with 0.1% Triton X-100. Samples were incubated according to the manufacturer’s instructions. TCRγ and TCRδ sequences were amplified using two rounds of nested PCR using GoTaq mastermix (Promega) and the following primers: Vδ2, TCTGGGCAGGAGTCATGT (external) and GAAAGGAGAAGCGATCGGTAAC (internal); Cδ, GCAGGATCAAACTCTGTTATCTTC (external) and TCCTTCACCAGACAAGCGAC (internal); Vγ1–8, CTGGTACCTACACCAGGAGGGGAAGG (external) and TGTGTTGGAATCAGGAVTCAG (internal); Vγ9, AGAGAGACCTGGTGAAGTCATACA (external) and GGTGGATAGGATACCTGAAACG (internal); and Cγ, CTGACGATACATCTGTGTTCTTTG (external) and AATCGTGTTGCTCTTCTTTTCTT (internal). PCR products were visualized on a 2% agarose gel, and products of successful reactions were incubated with ExoSAP-IT PCR Product Cleanup Reagent (Applied Biosystems) before sequencing with BigDye Terminator v3.1 (Applied Biosystems) following the manufacturer’s instructions and running on an Applied Biosystems 3730S capillary sequencer (Micromon Genomics, Monash University). Results were visualized using SnapGene Viewer.

Bulk γδ TCR repertoire sequencing

RNA was purified from 10,000 sorted Vγ9+/Vδ2+ T cells using an RNAmicro kit (Qiagen) according to the manufacturer’s instructions. Amplicon-rescued multiplex PCR and next-generation sequencing (NGS) methods (47) were used to analyze the sorted γδ T cell population from three healthy donors. After initial first-round reverse transcription PCR using high concentrations of gene-specific primers, universal primers were used for the exponential phase of amplification (patent: WO2009137255A2) (48). All cDNA synthesis, amplification, and NGS library preparation were performed using the TRD/TRG iR-Profile Kits (HTGI-M or HTDI-M; iRepertoire Inc., Huntsville, USA), and subsequent libraries were pooled and deep-sequenced using an Illumina MiSeq NGS platform (Micromon Genomics, Monash University).

Allogeneic T cell/B cell coculture assay

B cells were isolated from PBMCs using B Cell Isolation Kit II, human (Miltenyi Biotec) and T cells from an allogeneic donor were isolated using CD2 MicroBeads, human (Miltenyi Biotec), and cell isolation was performed using the Miltenyi Biotec MidiMACS separator following the manufacturer’s instructions. B cells were cultured with 5-OP-RU at indicated concentrations for 4 hours. The B cells were then washed twice before addition of BFA and allogeneic (MHC-mismatched, as MR1 is monomorphic) T cells at a 1:1 effector:target ratio and cultured for 18 hours. Cells were collected and stained with viability dye before fixation and permeabilization using the eBioscience Intracellular Fixation and Permeabilization Buffer Set (Invitrogen). Antibodies diluted in permeabilization buffer were then incubated for 45 min at room temperature.

Whole PBMC ex vivo bacterial challenge

PBMCs were cultured with the indicated bacteria at MOI 50 for 1 hour, and then gentamicin (50 μg/ml) was added and cultured for 24 hours. Supernatant was then collected, and the cytokine and cytotoxic profile was examined using the LEGENDplex CD8/NK panel following the manufacturer’s instructions. Samples were then run on BD LSRFortessa X20, and data were analyzed using the LEGENDplex Data Analysis Software.

Statistical analysis

Statistical analysis was performed using GraphPad Prism version 8 for macOS (GraphPad Software, San Diego, CA, USA). For multiple comparisons with two independent variables, two-way analysis of variance (ANOVA) with Geisser-Greenhouse correction and Sidak’s multiple comparison test were used. Significant result is indicated where P < 0.05.



Fig. S1. Medical images of MR1R9H/R9H patient skin lesions involving limbs and neck.

Fig. S2. IFIH1 transcript, splice variant confirmation, and the patient’s antiviral response.

Fig. S3. MR1R9H amino acid position, conservation of R9 across species, and Sanger sequencing confirmation of mutation.

Fig. S4. PBMC gating strategy for flow cytometry.

Fig. S5. MR1R9H/R9H patient’s Vα7.2+ CD161 T cells are not reactive to bacterial stimulation.

Fig. S6. MR1R9H/R9H patient has reduced frequency of T cells, with the majority having a memory phenotype.

Fig. S7. MR1R9H can be refolded and purified without addition of exogenous ligand.

Fig. S8. Crystal structures of A′-pocket of WT MR1 and MR1R9H.

Fig. S9. MR1R9H-empty tetramer does not distinguish a distinct population of cells in MR1R9H/R9H patient’s PBMCs.

Fig. S10. SPR for MR1R9H.

Fig. S11. MR1R9H/R9H patient NK cells and monocytes have the typical subsets.

Fig. S12. MR1R9H/R9H patient has reduced memory B cells.

Fig. S13. MR1R9H/R9H patient has robust production of cytokines and cytotoxic granules in response to bacterial challenge.

Table S1. List of novel SNVs identified in the patient by whole-exome sequencing.

Table S2. List of rare SNVs identified in the patient by whole-exome sequencing.

Table S3. Total cell counts for T cell populations.

Table S4. Data collection and refinement statistics for crystal structures.

Table S5. MR1R9H/R9H patient immunoglobulin testing.

Table S6. Raw data in Excel spreadsheet.

References (4953)


Acknowledgments: We would like to thank all study participants, A. Fletcher (Monash University) and D. Velez (NIH) for assistance with healthy donor blood collection, F. Morris and A. Peleg (Monash University) for providing bacterial strains, and S. Tangye (Garvin Institute of Medical Research) for critical reading of the manuscript. We acknowledge use of the services and facilities of Micromon Genomics at Monash University and FlowCore for sorting of cells using fluorescence-activated cell sorting. This research was undertaken, in part, by using the MX2 beamline at the Australian Synchrotron, part of ANSTO, and made use of the Australian Cancer Research Foundation (ACRF) detector. Funding: This work was supported by a program grant from the National Health and Medical Research Council of Australia (NHMRC) (1013667 and 1016629), a Targeted Call for Research grant (NHMRC) (1113531), the Australian Research Council (ARC) (CE140100011 and DP170102471), and the Division of Intramural Research, NIAID/NIH. J.L.N. is supported by an ARC Future Fellowship (FT160100074), D.P.F. is supported by an NHMRC Senior Principal Research Fellowship (1117766), J.A.V. is supported by a NHMRC Principal Research Fellowship (1154502). M.S.D. and H.E.G.M. are supported by ARC DECRA Fellowships, and J.R. is supported by an Australian ARC Laureate Fellowship. Author contributions: Conceptualization: L.J.H., M.S.D., and J.R.; investigation: L.J.H., W.A., A.v.B., H.J.L., H.E.G.M., M.L.S.-R., and S.M.; formal analysis: A.R.H. and T.D.A.; resources: J.Y.W.M., L.L., D.P.F., J.M., and S.O.; project administration: L.J.H., D.H.M., P.M.M., J.L.N., J.A.V., M.C.C., S.O., and J.R.; writing (original draft): L.J.H. and J.R.; supervision: S.J.T., M.S.D., and J.R. Competing interests: J.Y.W.M., L.L., D.P.F., J.M., and J.R. are inventors on patents describing MR1 tetramers and MR1 ligands. Data and materials availability: The coordinates of the ternary complexes of MAIT A-F7 TCR-MR1R9H-Ac-6-FP and TCR-MR1R9H-empty have been deposited in the PDB under accession codes 6W9U and 6W9V. The whole-exome sequencing data have been deposited in the NCBI BioSample database with the accession code: SAMN15159016.

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