Mucosal Immunity

Abstract Mucosa‐associated invariant T (MAIT) cells are unconventional T lymphocytes defined by their innate‐like characteristics and broad antimicrobial responsiveness. Whether MAIT cells are part of the tissue‐resident defense in the oral mucosal barrier is unknown. Here, we found MAIT cells present in the buccal mucosa, with a tendency to cluster near the basement membrane, and located in both epithelium and the underlying connective tissue. Overall MAIT cell levels were similar in the mucosa compared to peripheral blood, in contrast to conventional T cells that showed an altered representation of CD4+ and CD8+ subsets. The major mucosal MAIT cell subset displayed a tissue‐resident and activated profile with high expression of CD69, CD103, HLA‐DR, and PD‐1, as well as a skewed subset distribution with higher representation of CD4–/CD8– double‐negative cells and CD8αα+ cells. Interestingly, tissue‐resident MAIT cells had a specialized polyfunctional response profile with higher IL‐17 levels, as assessed by polyclonal stimulus and compared to tissue nonresident and circulating populations. Furthermore, resident buccal MAIT cells were low in perforin. Together, these data indicate that MAIT cells form a part of the oral mucosal T cell compartment, where they exhibit a tissue‐resident‐activated profile biased toward IL‐17 production. Introduction Mucosa‐associated invariant T (MAIT) cells are nonclassical innate‐like T cells that recognize microbial antigens presented by the MHC‐Ib‐related protein 1 (MR1) 1, 2. MR1 displays an extraordinary level of evolutionary conservation among mammals 2-4, and was shown to present microbial vitamin B2 (riboflavin) metabolites from a wide range of microbes that carry the riboflavin biosynthesis pathway 5, 6. MAIT cells express a semi‐invariant T cell receptor (TCR), including the Vα7.2 segment coupled with Jα33, Jα12, or Jα20, and limited TCR β‐chain diversity 7, 8. This TCR repertoire endows MAIT cells with the capacity to respond to the MR1‐restricted riboflavin derivatives produced by diverse microbes 9, 10. MAIT cells respond to antigenic stimulus with an innate‐like speed and produce proinflammatory cytokines including TNF, IFN‐γ, and IL‐17 9, 11-14. They can furthermore kill cells infected by microbes expressing the riboflavin pathway 15, 16 and inhibit intracellular microbial growth 17. Human MAIT cells are also defined by their high expression of CD161, the IL‐18 receptor α subunit (IL‐18Rα), and the transcription factor ZBTB16 18, also known as promyelocytic leukemia zinc finger protein (PLZF) 9, 19. The majority of MAIT cells are CD8+, with some being CD4–/CD8– double‐negative (DN), and a minor CD4+ population 9, 11, 12, 19. Human MAIT cells acquire innate‐like antimicrobial activity in the fetal intestinal mucosa prenatally, prior to the establishment of the commensal microflora 14. In adults, MAIT cells are highly abundant in mucosal tissues, liver, and peripheral blood 1, 2, 20-22. Studies of the murine oral immune system revealed diverse populations of DCs 23, 24, and provided insight into oral T‐cell function 25, but the immunology of the human oral mucosa remains relatively little studied. However, Dutzan et al. recently performed a broad characterization of the immune cell network at the gingival interface and identified T cells as the dominant immune cell population in both the buccal and gingival mucosa 26. CD4+ T cells, mainly of the CD45RO+ "memory" phenotype, were found to be the largest subset at around half of CD3+ cells, whereas smaller subsets of CD8+ and γδ T cells were also present 26. The same study also identified tissue‐resident CD4+ T cells as major producers of IL‐17 in periodontitis. IL‐17 is a cytokine central to the regulation of immune activity at mucosal surfaces 27, 28. Although IL‐17 is implicated in a variety of functions, its role in the regulation of mucosal immunity hinges on three core effects: maintenance of mucosal integrity via regulation of tight junction proteins, induction of antimicrobial molecule production by epithelial cells, and recruitment of neutrophils to sites of infection. Given the capacity of MAIT cells to recognize and respond to several commensal and disease causing microbes occurring in the oral cavity, and the ability of these cells to locate to mucosal sites, one can hypothesize a role for MAIT cells in the oral mucosal barrier. However, the immunobiology of MAIT cells at this mucosal site has to date not been explored. In the present study, we therefore investigated the presence, location, characteristics, and function of MAIT cells in the human buccal mucosa. The findings demonstrate that MAIT cells are part of the healthy buccal mucosal immune defense with specialized tissue‐resident and nonresident subpopulations exhibiting distinct functional profiles, where in particular, the CD69+CD103+ MAIT cell population show strong IL‐17 production. We discuss these findings in the context of contemporary knowledge of immune homeostasis and defense at this important barrier site. Results Identification of MAIT cells in the buccal mucosa Given the broad antimicrobial reactivity of MAIT cells, we were interested in investigating the potential role of these cells in oral mucosa, a site continuously exposed to a broad array of microbial stimuli. Buccal biopsies and matched peripheral blood samples were collected from healthy donors (Supporting Information Table 1), and cells isolated after tissue processing were analyzed by flow cytometry. All subjects were examined for their oral health and showed no oral mucosal disease, active dental caries, infection, or periodontitis. Using antibody combinations allowing identification of MAIT cells in blood, buccal MAIT cells were defined as CD45+ CD3+ CD161hi Vα7.2+ cells (Fig. 1A). To ensure that cells defined by this gating strategy were bona fide MAIT cells, their MR1 restriction was confirmed by staining with the MR1 5‐(2‐oxopropylideneamino)‐6‐D‐ribitylaminouracil (5‐OP‐RU) tetramer (Fig. 1B). The percentage of MAIT cells in the mucosa ranged between 0.1 and 7% of total T cells (Fig. 1C). Overall, these levels were not significantly different from those in matched blood, although in any given individual, the levels seen at the two sites were often rather divergent. Interestingly, major conventional T‐cell subsets were present in the buccal mucosa at frequencies different from those in the blood. Levels of CD4+ T cells were lower than in blood, whereas CD8+ T cells and CD4–CD8– T cells were enriched in buccal mucosa as compared to blood (Fig. 1C). These data demonstrate that MAIT cells are part of the buccal mucosa T‐cell compartment. Detection of buccal mucosal MAIT cells in situ To determine MAIT cell location within the buccal mucosa, we performed in situ staining for Vα7.2 and IL‐18Rα in oral mucosal sections (Fig. 1D). In mucosa, staining for IL‐18Rα can be used in lieu of CD161, as we have previously shown for genital mucosa 22. Using the Vα7.2+ IL‐18Rα+ definition, MAIT cells were readily identified in buccal mucosal sections, and they tended to locate close to the basement membrane (Fig. 1D). MAIT cells were present in the epithelial layer, just above the basal membrane (distance from basal membrane: median = 14.6 μm; range = 1.0–75.9 μm), as well as in the underlying connective tissue, just beneath the basal membrane (median = 20.7 μm; range = 2.8–292.2 μm). Non‐MAIT T cells, as well as MR1‐expressing HLA‐DR+ antigen‐presenting cells, were also found in buccal mucosa as determined by immunofluorescence staining (Fig. 1E and F). MAIT cell location around the basement membrane is consistent with a possible role as innate‐like T cell sentinels to detect microbial epithelial barrier breach. Altered subset distribution and Jα‐TCR usage in mucosal MAIT cells In peripheral blood, MAIT cells are predominantly CD8+, with some CD4–CD8– cells and a very small CD4+ subpopulation. In the buccal mucosa, MAIT cells were enriched in CD4–CD8– and CD4+ subsets, and had significantly lower levels of the CD8+ subset (Fig. 2A). Within the CD8+ subset, similar to blood MAIT cells, the mucosal MAIT cells exhibited an increased frequency of CD8αα+ cells compared to non‐MAIT T cells (Fig. 2B and C). Notably, MAIT cells represented almost half of all CD8αα+ T cells in the buccal mucosa, with significant donor variability (Fig. 2D). The distribution of Jα‐TCR usage within the MAIT cell populations in the buccal mucosa and blood was compared using quantitative real‐time PCR (qRT‐PCR; Fig. 2E). We quantified the relative expression of three Jα previously shown to be represented within the MAIT cell TCR repertoire, the Jα12, Jα20, and Jα33 8, 29, 30. As expected, blood MAIT cells displayed a consistent pattern with dominant Jα33 usage, with smaller Jα20 and Jα12 usage. However, in matched mucosa, the pattern was more diverse, with different Jα segments dominating in different donors. Together, these data support a model of compartmentalization where the subset representation and TCR‐Jα usage in buccal MAIT cell population are partly different that of the circulating MAIT cells found in blood. MAIT cells in buccal mucosa express an activated perforinlow phenotype To assess the phenotypic characteristics of the buccal MAIT cells in more detail, we next stained isolated mucosal cells with markers of activation, CD38 and HLA‐DR (Fig. 3A). The staining pattern revealed the presence of an activated HLA‐DR+CD38+ MAIT cell population in buccal mucosa (Fig. 3B). Compared to their blood counterparts, the mucosal MAIT cells expressed higher levels of HLA‐DR, whereas CD38 levels appear to be slightly lower (Fig. 3C). In addition, expression of PD‐1 was common in mucosal MAIT cells, whereas PD‐1 was less expressed in peripheral blood MAIT cells (Fig. 3C). To investigate the phenotype of MAIT cells in more detail, paired blood and mucosal cell samples were stained intracellularly for the expression of the master transcription factor PLZF, as well as the cytolytic effector molecules perforin and granulysin (Fig. 3D). Perforin levels were mostly lower in the buccal MAIT cells than in their blood counterparts (Fig. 3E), whereas expression levels of PLZF and granulysin were similar in both compartments. These findings suggest that MAIT cells in the buccal mucosa are highly activated cells with significant expression of the checkpoint inhibition receptor PD‐1, and display a reduced perforin content as compared to circulating MAIT cells. Characterization of resident and nonresident MAIT cells in the buccal mucosa We next investigated the MAIT cell expression of receptors associated with tissue residency in the mucosa. Resident T cells can be distinguished by coexpression of CD69 and CD103 (αE integrin) in a range of tissues 31-35, including intestinal mucosa 36. Flow cytometric assessment of CD69 and CD103 expression revealed the existence of a major CD69+CD103+ tissue‐resident MAIT cell population in the buccal mucosa (Fig. 4A). However, a minority of MAIT cells were negative for CD69 and CD103, consistent with a tissue nonresident or "passing through" phenotype (Fig. 4A). Compared to peripheral blood MAIT cells, the buccal mucosal MAIT cell population was highly enriched in CD69 and CD103 expression, and CD69 expression was mostly seen in the CD103+ population (Fig. 4B). As the CD69 expression formed a continuum including dim cells of both CD103+ and CD103– character, we compared the four MAIT cell populations defined by CD69 and CD103 with regard to CD4+ and CD8+ expression. CD103+ MAIT cells were mainly CD8+ with a minority CD4–CD8– cells, whereas CD103– MAIT cells had a distinct opposite pattern with a majority CD4–CD8– character (Fig. 4C and D). CD69 expression did not significantly influence this pattern (Fig. 4C). In addition, CD103+ MAIT cells were more activated than their CD103– counterparts, as evidenced by higher expression of HLA‐DR and CD38 (Fig. 4E). In contrast, the CD103+ subpopulation expressed lower levels of the cytolytic effector molecule perforin, whereas PLZF did not vary depending on CD103 (Fig. 4F). These results indicate the existence of two distinct buccal MAIT cell subpopulations where one express the CD103 marker of tissue residency and one lacks CD103 consistent with a nonresident character. Distinct polyfunctional responses of mucosal resident, nonresident, and circulating MAIT cells To investigate the functional profile of MAIT cells in buccal mucosa in comparison with peripheral blood, isolated lymphocytes from the two tissues were activated with PMA/ionomycin and their repertoire of functions evaluated by flow cytometry staining for TNF, IFN‐γ, IL‐2, IL‐17, and granzyme B (Fig. 5A). Overall, both blood and mucosal MAIT cells displayed detectable production of all these effector functions, with some notable tissue‐dependent differences. Peripheral blood MAIT cells produced TNF and IFN‐γ more strongly than their mucosal counterparts, whereas IL‐2 and granzyme B were similar (Fig. 5A and B). In contrast, IL‐17 production was very low in blood MAIT cells, with the exception of one outlier, while this cytokine was clearly more highly expressed in the buccal MAIT cells (Fig. 5A and B). In the mucosal tissue, the resident CD103+ subset and the CD103– nonresident subset were largely similar in their response patterns with two notable exceptions. IL‐17 in particular, and to some extent granzyme B expression, were significantly higher in the CD103+ MAIT cell subset. To understand the functional specialization of mucosal resident, mucosal nonresident, and circulating MAIT cells in more detail, we analyzed the polyfunctional response profiles of these subsets. First, we determined the percentages of MAIT cells in the three locations that responded with at least one of the five functions measured (Fig. 5C). For all three sites, the vast majority of MAIT cells expressed at least one function. However, the mucosal MAIT cells displayed somewhat lower responsiveness, where in particular, the CD103– MAIT cells were less responsive. When the overall polyfunctionality was analyzed, the ability to express 1, 2, 3, 4, or 5 functions was fairly similar between the different tissue locations, although the CD103+ resident MAIT cells tended to be more 4‐ or 5‐functional (Fig. 5D). Finally, we analyzed the data by Boolean gating to assess which specific polyfunctional profiles were expressed by peripheral blood, CD103+ mucosal resident, and CD103– nonresident MAIT cells (Fig. 5E; Supporting Information Table 2). This analysis brought forward the pattern that peripheral blood MAIT cells were focused primarily on TNF production, either alone or in combinations with IFN‐γ and IL‐2. The mucosal CD103+ resident MAIT cells instead primarily focused on IL‐17 production either alone or in combinations with TNF or IL‐2. The CD103– nonresident MAIT cells had a functional profile intermediate between the circulating and resident populations, and were mostly expressing TNF with or without IL‐2, and less IL‐17. Altogether, these findings indicate that the mucosal resident, the mucosal nonresident, and the circulating MAIT cells deploy different effector cytokine response profiles. Discussion Tissue‐resident immune cell populations are increasingly recognized for their importance in defense against invading pathogens. The oral mucosa is continuously exposed to a range of antigens derived from food, microbiota, and pathogens. To maintain barrier immune defenses at this site, while not reacting against nonpathogenic encounters, is a considerable challenge. Recent studies have started to address this research question 37, 38, but no studies to date have addressed the potential role of the MR1‐restricted MAIT cell population in oral mucosa. Here, we observe that MAIT cells are dispersed throughout the buccal mucosa with a preferential location close to the basement membrane. The buccal MAIT cells are biased toward a CD4–/CD8– DN profile, and the CD8+ subset is primarily CD8αα and make up a significant proportion of all CD8αα T cells in the mucosa. The MAIT cell population in this mucosal site is composed of distinct CD69+CD103+ intraepithelial resident and CD69–CD103– nonresident subsets. The CD103+ subset is enriched in CD8+ MAIT cells, is more activated, and has lower cytolytic potential. Finally, the buccal MAIT cells show a distinct functional profile with enhanced IL‐17 production and less TNF and IFN‐γ, as compared to their peripheral blood counterparts, and this pattern was particularly pronounced for the CD103+ resident MAIT cells. The MR1‐presented riboflavin metabolite antigens recognized by MAIT cells are conserved among many prokaryotic and eukaryotic microbes relevant for mucosal health. Thus, MAIT cells may play a unique role in the oral mucosa with broad innate‐like recognition of such microbes in a manner that does not require the kind of priming which conventional adaptive T‐cell responses do. It is interesting that the MAIT cells to at least some extent locate around the basement membrane, where they may function as innate‐like T‐cell sentinels to detect microbial epithelial barrier breach. Around the similar location, MR1+HLA–DR+ cells are residing and those may be able to present riboflavin metabolite antigens from invading microbes. Together, MAIT cells and MR1+ antigen presenting cells may form a rapid innate response immune unit at the mucosal barrier, capable of responding to pathogens to which the host has no preexisting adaptive immunity. The CD103+CD69+ mucosal‐resident MAIT cell population is fairly strongly biased toward IL‐17 production, with less TNF and IFN‐γ expression, as compared to the CD103– MAIT cell subpopulation. Resident MAIT cell recognition of an invading microbial pathogen may thus setoff an IL‐17‐mediated inflammatory response with induction of antimicrobial peptides in epithelium and recruitment of neutrophils. Such a pattern would be reminiscent to the situation described for chronic severe periodontitis by Dutzan et al. 26, where IL‐17 produced by presumably adaptive Th17 cells was associated with increased gingival tissue infiltration of neutrophils. Given their innate‐like response characteristics, MAIT cells may be among the first immune cells to detect microbial infiltration and respond with IL‐17 release. Here, it is interesting to note that IL‐17 has emerged as an important mediator and amplifier of immunity against Candida albicans 38. The dimorphic fungus C. albicans expresses the riboflavin biosynthesis pathway and is recognized by MAIT cells in an MR1‐restricted manner 10. Many cells respond to IL‐17 by upregulation of proinflammatory cytokines, such as IL‐6, and chemokines for recruitment of neutrophils including CXCL1, CXCL2, and CXCL5 39. In addition, IL‐17 stimulates production of β‐defensins in epithelial cells 40. MAIT cells are thus well located to initiate mucosal immune responses in oropharyngeal candidiasis. Peripheral blood MAIT cells are predominantly CD8+ with a minority CD4–CD8– subset. This pattern is reversed in buccal mucosa, such that the CD4–CD8– MAIT cells are more numerous. It is however interesting to note that the CD8+ MAIT subset in buccal mucosa is primarily CD8αα, and that this subset makeup almost half of all CD8αα T cells in the oral mucosa. These CD8αα MAIT cells bear resemblance to the intestinal mucosal CD8αα intraepithelial lymphocytes (IELs) that have been extensively characterized in murine models, but may be less frequent in humans 41, 42. The intestinal IELs of mice are a mix of TCRγδ T cells and TCRαβ T cells with diverse specificities, and the representation of MAIT cells among these IELs in different sites is to our knowledge largely unknown. Our data indicate that the CD103+ MAIT cell population is mostly, but not exclusively, CD8+ and composed of both CD8αα and CD8αβ cells. These findings together suggest that MAIT cells makeup a significant part of the human buccal IEL‐like population. The human oral mucosal barrier retains a commensal bacterial microbiota that is both varied and unique among other sites 43, 44, dominated by the genera Streptococcus, Haemophilus, Prevotella, and Veillonella. In addition to bacteria, the oral mucosal barrier is home to many species of fungi including C. albicans 45. The oral immune system thus has to manage and tolerate a diverse commensal microbiome, and at the same time guard against conditions arising either from dysfunction of normal oral homeostasis or caused by pathogens normally not present in the oral cavity. T cells are believed to play a role in multiple oral mucosa pathologies including aphthous stomatitis, oral leukoplakia, oral reticular or ulcerative lichen planus, celiac disease, and oral psoriasis 46, 47. Whether MAIT cells have a role in any such conditions in humans remains to be explored. In summary, we have shown that MAIT cell populations with resident and nonresident characteristics are part of the buccal mucosal immune system in healthy donors and that they have unique functional profiles. Future studies should aim to investigate how these populations respond to commensal and pathogenic microbes, and how they are affected in different disease conditions. Materials and methods Tissue donor recruitment and sample collection A total of 94 volunteers were recruited in two healthy donor groups A and B (Supporting Information Table 1). Inclusion criteria for both groups were: 20–50 years of age, HIV‐negative, non‐smoking, no antibiotics in the last 3 months, and not pregnant. Ethical permission was obtained from the Regional Ethical Review Board in Stockholm in accordance with the Declaration of Helsinki. All participants gave written informed consent. The oral health of all subjects was evaluated using standard dental examination procedures, including inspection of oral mucosa, teeth, and surrounding soft tissues, to ensure the donors had no visible mucosal lesions, no signs of gingivitis, active dental caries, or periodontitis. All donors were instructed to abstain from food or drink for 1 h before tissue collection. Oral mucosal tissue samples and matched peripheral blood samples were collected from two sets of healthy donors. Donor group A was recruited from the general population. A matched blood sample of 20–30 mL venous blood was taken from each participant on the day of the procedure, prior to the oral sample collection. The blood was stored in heparin tubes at room temperature until analysis. Local anesthesia with xylocain/adrenalin was applied to the left bucca and three punch biopsies (5 mm in diameter, 3–4 mm deep) were taken from the site. For donor group B, tissue samples were taken before wound closure on patients who underwent orthognatic surgery of the mandible. The patients underwent these corrective surgeries due to abnormal position of the mandible in relation to the base of skull, but no buccal disease or inflammation is associated with these conditions. The patients were treated under general anesthesia and local anesthesia was additionally applied. Tissue samples 20 × 10 mm in size were taken bilaterally from the mucosa. Matched blood samples from donor group B were collected at the time of the procedure. After collection, the biopsies were stored at 4°C in serum‐free RPMI (ThermoFisher Scientific, Waltham, MA, USA) supplemented with 50 μg/mL gentamicin (ThermoFisher Scientific) and 100 μg/mL normocin (InvivoGen, San Diego, CA, USA). Biopsies intended for qPCR analysis were stored in RNAlater (QIAgen, Venlo, Netherlands) at −20°C. Biopsies intended for in situ microscopic analysis were submerged in OCT Cryomount (HistoLab, Askim, Sweden), snap‐frozen in liquid nitrogen, and then stored at −80°C. Sample processing for flow cytometry All collected samples were processed within 3 h of collection. Buccal biopsies were placed into serum‐free RPMI supplemented with 50 μg/mL gentamicin and 100 μg/mL normocin and then incubated with 1 mg/mL DNase I and collagenase A (both from Roche, Penzberg, Germany) at 37°C with shaking at 800 rpm for 1 h. After incubation, the reaction was stopped by addition of fetal calf serum (FCS; Sigma‐Aldrich, St Louis, MO, USA) to a final concentration of 10%. The biopsies were then pressed through a 100 μm cell strainer in order to detach loose cells. The cells were then washed in PBS and incubated in RBC lysis buffer for 10 min at RT to remove any erythrocyte contamination. The cells were washed again in PBS and stained for flow cytometry. Donor‐matched PBMCs were isolated from blood samples by Ficoll‐Hypaque density gradient centrifugation using Lymphoprep (Axis‐Shield, Dundee, Scotland). The PBMC layer was washed twice with PBS, and incubated in RBC lysis buffer for 10 minutes at room temperature to remove erythrocyte contamination. The cells were washed again in PBS and 106 cells were stained for flow cytometry. In situ staining In situ staining was performed on 8‐μm‐thick sections of frozen biopsies, as previously described 22. Sections were fixed in 2% formaldehyde and stained sequentially. Antibody reagents used for tissue staining are listed in Supporting Information Table 3. The tissue sections stained for Vα7.2 in combination with IL‐18Rα were scanned into digital images using a Pannoramic 250 Flash Slide Scanner (3DHistech, Budapest, Hungary). The distance measurement was performed using the digital microscope application CaseViewer (3DHistech), where the distance from the surface of the double‐positive cells to the basal membrane was measured. The tissue sections stained for HLA‐DR in combination with MR1, and Vα7.2 in combination with CD3 were visualized using DMR‐X microscope (Leica, Weitzlar, Germany) and images were acquired with a Retiga 2000 R camera (Qimaging, Surrey, Canada). Functional assay One million lymphocytes in suspension were cultured overnight in RPMI +10% FCS, supplemented with 100 μg/mL normocin and 50 μg/mL gentamicin. After overnight incubation, they were activated using Leukocyte Activation Cocktail (PMA/ionomycin) (BD Biosciences, San Jose, CA, USA) in the presence of GolgiPlug (monensin) for 6 h. At the end of the incubation, the cells were stained and analyzed by flow cytometry. Flow cytometry and antibodies Cells in suspension were stained for surface antigens in FACS buffer (PBS with 2 mM EDTA and 2% FCS) for 20 min at 4°C. Afterwards, they were washed in FACS buffer and permeabilized using the transcription factor fixation and permeabilization buffer (BD Biosciences) for 30 min at 4°C. Following permeabilization, cells were washed twice in transcription factor wash and permeabilization buffer (BD Biosciences), and then stained for intracellular antigens in the same buffer for 20 min at 4°C. PE‐conjugated human MR1:5‐OP‐RU tetramer was obtained from the NIH Tetramer Core Facility. For tetramer staining, cells in suspension were incubated with MR1:5‐OP‐RU tetramer for 40 min at room temperature and then washed with FACS buffer prior to surface antibody staining. Monoclonal antibody reagents used in the study are listed in Supporting Information Table 4. After staining, cells were washed and analyzed using an LSRFortessa flow cytometer (BD Biosciences) equipped with 355, 405, 488, 561, and 639 nm lasers. In addition to the antibodies, cells were stained with LIVE/DEAD Fixable Dead Cell Stain (Near‐Infrared or Aqua; ThermoFisher Scientific). Quantitative RT‐PCR qRT‐PCR was performed to determine the mRNA expression of TCRs Vα7.2‐Jα33, Vα7.2‐Jα20, and Vα7.2‐Jα12 as well as the constant Cα chain, in healthy oral mucosa and blood. Briefly, total RNA was extracted from buccal mucosa and PBMCs using TRIzol reagent (ThermoFisher Scientific). For reverse transcription, 250 ng of RNA was used in a 15 μL total reaction volume using the IScript cDNA Synthesis kit (BioRad, Hercules, CA, USA). For amplification, a 20 μL supermix reaction was prepared accordingly: 1 μL cDNA, 5 μL SsoAdvanced™ Universal® SYBR Green (BioRad), 1 μL of each primer at a final concentration of 500 nM, and nuclease free H2O. Primer sequences as well as annealing temperatures for each of the primer sets are listed in Supporting Information Table 5. qPCR was performed using 7500 Fast real time PCR system (Applied Biosystems, Waltham, CA, USA) with the following cycling conditions: 1 cycle at 95°C for 5 min, then 40 cycles at 94°C for 10 s, 58°C or 60°C depending on primer for 30 s, and 72°C for 27 s. The relative abundance of each Vα7.2‐Jα was determined as relative to Cα by the comparative ΔΔCT method. Software and statistical analysis Analysis of flow cytometric data was performed using FlowJo 10 (FlowJo LLC, Ashland, OR, USA), and microscopic images were processed using Image‐Pro Premier 9.3 (Media Cybernetics, Rockville, MD, USA). Statistical tests were performed using GraphPad Prism version 7.0c for Mac OS X (GraphPad Software, La Jolla, CA, USA). Statistical significance was assessed using Wilcoxon matched pairs test for paired data, and Mann–Whitney U‐test for unpaired data. For data presented in Fig. 5, analysis and presentation of distributions were performed using SPICE version 5.1, downloaded from http://exon.niaid.nih.gov 48. Comparison of distributions was performed using a Wilcoxon matched pairs test as described 48. For all statistical analysis, p‐values below 0.05 were regarded as significant. Acknowledgements The authors wish to acknowledge the contribution of Sam Chehrehgosha, Angelica Kroonder, Emelie Molin, and Beatrice Wiberg in recruiting study volunteers and gathering oral biopsies. This research was supported by grants to JKS from the Swedish Research Council (2016‐03052), the Swedish Cancer Society (CAN 2017/777), and the US National Institutes of Health (R01DK108350). Grants to M.S.C. were from the Foundation for Odontological Research (OF11211233), and the Swedish Cancer Society (CAN 2016/731). Further support to E.L. was from the Swedish Research Council (2015‐00174) and Marie Skłodowska Curie Actions, Cofund, Project INCA 600398. J.D. was supported by Fundação para a Ciência e a Tecnologia (SFRH/BD/85290/2012, doctoral fellowship), through program QREN‐POPH‐typology 4.1. 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 wish to thank the healthy volunteers that contributed time and effort to sample donation for this study. Author contributions J.K.S., E.L., and M.S.C. conceived the original research idea and study design. M.J.S., H.D., M.M., A.T., J.D., E.L., M.S.C., and J.K.S. designed experiments. M.J.S., H.D, A.G., and J.E. conducted experiments. M.J.S., H.D., and A.G. analyzed experimental data. R.H., S.A., and C.K.W. recruited study volunteers and collected essential human samples. M.J.S. and J.K.S. wrote the manuscript. All authors reviewed and commented on the manuscript. Conflict of interest The authors declare no commercial or financial conflict of interest. Supporting Information References Abbreviations IEL intraepithelial lymphocyte MAIT mucosal‐associated invariant T MR1 MHC‐Ib‐related protein 1 PLZF promyelocytic leukemia zinc finger protein

Abstract Mucosal‐associated invariant T (MAIT) cells develop in the thymus and migrate into the periphery to become the largest antigen‐specific αβ T‐cell population in the human immune system. However, the frequency of MAIT cells varies widely between human individuals, and the basis for this is unclear. While MAIT cells are highly conserved through evolution and are phenotypically similar between humans and mice, they represent a much smaller proportion of total T cells in mice. In this review, we discuss how MAIT cells transition through a three‐stage development pathway in both mouse and human thymus, and continue to mature and expand after they leave the thymus. Moreover, we will explore and speculate on how specific factors regulate different stages of this process. Introduction Mucosal‐associated invariant T (MAIT) cells are a highly conserved population of T lymphocytes that exhibit innate‐like functions similar to those described for natural killer T (NKT) cells.1-4 MAIT cells are defined by their invariant T‐cell receptor (TCR)‐α chain, and their restriction to the nonpolymorphic major histocompatibility complex class I‐like molecule, MHC‐related protein 1 (MR1).2 In mice, MAIT cells express a TCR comprising of Vα19 joined to Jα33, which pairs with Vβ6 or Vβ8.5-7 In humans, MAIT cells predominantly express Vα7.2 joined to Jα33, Jα20 or Jα12, and these pair with Vβ2 or Vβ13.3, 5, 7 Smaller subsets of MR1‐restricted Vα7.2− T cells have been identified in humans,8-10 although this review will focus on the major population of Vα7.2+ MAIT cells, herein simply described as MAIT cells. In this issue, Lantz and Legoux11 provide a historical perspective of the MAIT cell field, including the initial identification and the description of MAIT cells as “mucosal‐associated” due to their presence within the gut lamina propria.2 It is now appreciated that MAIT cells can be found in all sites where conventional T cells are present,6, 12, 13 although functionally distinct subsets of MAIT cell exist at mucosal sites, suggesting an important role for these cells in barrier tissue immunity.12, 14 MAIT cells are abundant in humans, making up to 10% of T cells in peripheral blood and up to 50% in the liver,14, 15 yet their frequency can significantly vary between individuals.13, 15-17 In mice, the frequency of MAIT cells is much lower, and it is currently unclear what factors regulate MAIT cell numbers and cause this disparity between species.6, 7, 16 Our understanding of human MAIT cells has progressed predominantly through the study of CD3+ Vα7.2+ CD161hi T cells, which incorporates most MAIT cells in peripheral blood and organs.13, 18, 19 Conversely, because MAIT cell numbers in laboratory mice are very low, and monoclonal antibodies against the invariant mouse MAIT TCRα chain do not exist, Vα19Jα33 transgenic mice were established to investigate the biology of mouse MAIT cells.16, 20 The discovery of riboflavin derivatives as antigens (Ags) for MAIT cells21, 22 (described in this issue by Kjer‐Nielsen, Corbett and colleagues23), coupled with the production of MR1 tetramers that incorporate these Ags,5 has fueled new studies into the development and function of MAIT cells. These tetramer reagents now provide a basis for distinguishing MAIT cells from other T‐cell populations that share similar phenotypic markers.8, 9, 24, 25 MR1 is expressed at low levels in a wide range of tissues26, 27 and shows strong evolutionary conservation between species.28 This, together with the broad microbial reactivity of MAIT cells suggests that they play a key role in host immunity.29-32 The role that MAIT cells play in microbial immunity is extensively reviewed in this issue by Ussher, Willberg and Klenerman (MAIT cells and Viruses)33 and Meermeier, Harriff, Karamooz and Lewinsohn (MAIT cells and Microbial Immunity).34 Given the wide variation in MAIT cell frequency between individuals13, 16, 19, 35 and evidence that reduced MAIT cell numbers are associated with aberrant immune responses in humans and mice,29-31, 36-39 it is important to understand how MAIT cells develop and determine what factors regulate this process. In this review, we describe how MAIT cells undergo a three‐stage development pathway within the thymus and continue to mature after they enter the periphery, in both mice and humans. In addition, we examine similarities and differences with the development of NKT cells, which may compete with MAIT cells for a similar environmental niche. Thymic Selection Studies in mice revealed that MAIT cells arise intrathymically following interaction of the MAIT TCR with MR1.2, 7, 16, 40 Furthermore, analysis of Vα19‐Jα33 Cα−/− and Vβ6 transgenic mice revealed that MAIT cells are selected by MR1‐expressing DP cortical thymocytes, compared to thymic epithelial cells that select MHC/peptide reactive T cells.40 It is currently unclear whether specific Ags must be presented in association with MR1 for intrathymic selection, and if so, the nature of the selecting Ags. Selection may require agonist ligands like the MAIT activating riboflavin derivative Ags such as 5‐(2‐oxopropylideneamino)‐6‐d‐ribitylaminouracil (5‐OP‐RU) and 5‐(2‐oxoethylideneamino)‐6‐d‐ribitylaminouracil (5‐OE‐RU).22 Alternatively, MAIT cells might be selected by a weak or nonagonist Ag, such as 6‐formylpterin (6‐FP), a vitamin B9 derivative that binds to MR1 but does not activate the majority of MAIT cells.21, 41 Although these vitamin‐derivative Ags have microbial or dietary origins, it is also possible that MAIT cells are selected in the context of an endogenous self‐Ag produced in the thymus. Early evidence supported a role for microbial derived Ags for the selection of MAIT cells as these cells could not be detected in germ‐free (GF) mice using RT‐PCR.2 We recently re‐examined GF mice using MR1 tetramers and detected the presence of normal numbers of immature MAIT cells in the thymus, but these cells were unable to fully mature and expand in the periphery.24 These data suggest that microbial colonization is not required for the initial selection of MAIT cells, but is essential for their subsequent expansion.16, 24 Another important question surrounding the selection of MAIT cells is whether their TCR repertoire is shaped by negative selection. Like MAIT cells, NKT cells are selected by DP cortical thymocytes,42 and in vivo injection of the NKT cell agonist Ag α‐galactosylceramide or the addition of this lipid Ag to fetal thymic organ cultures ablated the development of mouse NKT cells, suggesting these cells had undergone negative selection.43, 44 It will be important to establish if similar selection criteria also exist for MAIT cells. For instance, would the overexpression of MR1 or the presence of a high affinity Ag lead to the deletion of MAIT cells? Accordingly, further studies are required to examine the types of Ags (if any) that govern the intrathymic selection of MAIT cells. A Three‐Stage Pathway for MAIT Cell Development in Mice and Humans Analysis of MAIT cells from the periphery of WT mice using MR1‐5‐OP‐RU tetramers revealed that they expressed high levels of CD44 and had a memory phenotype, whereas most MAIT cells from Vα19‐Jα33 Cα−/− transgenic mice lacked CD44 expression and were described as naïve.6, 16 Moreover, and in contrast to previous findings,16 MAIT cells from WT mice expressed the transcription factor, promyelocytic leukemia zinc finger (PLZF).6, 45 PLZF was previously reported to be required for the development of other innate‐like T cells such as NKT cells,46, 47 innate lymphoid cells48, 49 and some γδ T cells.50, 51 These data highlight important differences in the phenotype of MAIT cells from WT and Vα19 transgenic mice and suggest that the overexpression of the mouse MAIT TCR α‐chain likely alters the development of MAIT cells. Our studies of mouse thymus revealed three populations of MAIT cells based on their expression of CD24 and CD44, including CD24+CD44−, CD24−CD44− and CD24−CD44+ MAIT cells.24 Through a combination of phenotypic analysis, ontogeny experiments and in vitro development studies, we determined that the CD24+CD44− population were least mature, defined as stage 1 MAIT cells. These give rise to CD24−CD44− stage 2 cells and ultimately these differentiate into CD24−CD44+ stage 3 cells, which more closely resemble MAIT cells in the periphery (Figure 1). Importantly, MR1 expression appears to be required at each stage of development, as progression from stage 1 to stage 3 in vitro, is severely impaired by the addition of an anti‐MR1 blocking antibody.24 These distinct MAIT cell precursor populations were further characterized for expression of differentiation markers, cytokine receptors and transcription factors (Table 1). For example, PLZF is not expressed in stage 1 MAIT cells, while mature populations of stage 3 MAIT cells express PLZF.24 This contrasts with the development of NKT cells, as early NKT cell progenitors express high levels of PLZF, and expression levels decline to moderate levels as NKT cells become more mature, with the notable exception of NKT2 cells that express high levels of PLZF (discussed below).46 Analysis of PLZF‐null mice revealed that the development of stage 1 and 2 MAIT cells was unperturbed, while mature stage 3 cells failed to develop within the thymus and periphery. Moreover, residual MAIT cells from PLZF‐null mice were unable to produce cytokines and were hence functionally incompetent.24 Therefore, PLZF is a critical factor governing the transition from stage 2 to stage 3 MAIT cells, as well as the acquisition of MAIT cell functional potential. Stage 1 Stage 2 Stage 3 CD4 and CD8 coreceptor CD4+, CD8+ or CD4+CD8+ h: CD4+, CD8+ or CD4+CD8+ CD4+, CD8+ or m: CD4+, CD8+ or CD4−CD8− CD4−CD8− CD8αβ CD8αβ+ CD8αβ+ CD8αβ+ CD24 (m) Positive Negative Negative CD27 (h) Negative Positive Low to positive CD44 (m) Negative Negative Positive CD62L (m) Intermediate n.d. Negative CD69 (m) Positive n.d. Negative CD103 (m) Negative n.d. Low to positive CD161 (h) Negative Negative Positive (h) NK1.1 (m) Low to positive (m) CD278/ICOS (m) Negative n.d. Positive Cytokine receptors CD122/IL‐2Rβ (m) Negative n.d. Intermediate CD127/IL‐7R (m) Negative n.d. Positive CD218/IL‐18R Negative n.d. Positive Transcription factors PLZF Negative Low Positive T‐bet and RORγt Low Low T‐bet+ or RORγt+ (m) T‐bet+ RORγt+ (h) n.d. = not determined; m = mouse; h = human. Most studies on MAIT cell development in humans have utilized surrogate markers, such as Vα7.2 or co‐expression of Vα7.2 and CD161, to identify MAIT cells. Using this strategy, MAIT‐like cells could be detected within human thymus and were shown to express PLZF.16, 52, 53 Moreover, Leeansyah and colleagues examined a panel of human fetal tissues including the thymus and cord blood, and described a maturation pathway of microbial reactive Vα7.2+ CD161+ cells.52 Our laboratory examined MAIT cells from human thymus using MR1 tetramers and similar to our mouse studies, we identified three populations of MAIT precursors based on the differential expression of cell surface markers.24 Ontogeny and functional studies showed that stage 1 human MAIT cells could be defined as CD27−CD161−, followed by stage 2 CD27+CD161− and then stage 3 CD27lo/+CD161+ (Figure 1 and Table 1). Moreover, the expression of CD161 on MAIT cells from human thymus also coincided with the expression of IL‐18R, the latter expressed by stage 3 thymic MAIT cells from both humans and mice (Table 1).24 Notably, the vast majority of human thymic MAIT cells lack expression of CD161 and these cells would have been excluded from previous studies that relied on CD161 as a surrogate marker of MAIT cells.16, 24, 52 In addition, we also found many MAIT‐like Vα7.2+ CD161+ T cells in human thymus that do not bind MR1‐5‐OP‐RU tetramer, a result that was recently observed by another group with human cord blood and neonatal blood samples.25 The majority of peripheral blood MAIT cells have upregulated CD161 and IL‐18R, although residual CD161− IL‐18R− MAIT cells could still be found in cord blood and young peripheral blood.24 These data reveal that MAIT cells upregulate CD161 and IL‐18R as they exit the thymus or soon after they enter the periphery. Factors That Regulate MAIT Cell Development The identification of a three‐stage development pathway for MAIT cells now allows for a detailed assessment of factors that influence this process. In addition to PLZF, we also showed that microRNAs are critical for MAIT cell development, as mice deficient for a member of the RNase III superfamily, Drosha, have drastically reduced MAIT cells and accumulate stage 1 thymic MAIT cells.24 NKT cells were also diminished in these mice, supporting previous data that microRNAs are required for NKT cell development.54 Future studies should investigate which specific microRNAs are important for MAIT cell development and whether there is overlap with the microRNAs shown to be important for the development of NKT cells (e.g. miR150,55 miR‐181 family56 and miR17–92 family cluster57). Let‐7 microRNAs will be an important candidate to investigate, as they have been shown to directly target the Zbtb16 gene and downregulate PLZF expression in NKT cells.58 The loss of IL‐18 and commensal microbiota from GF mice impaired MAIT cell numbers and progression to stage 3 MAIT cells.24 A previous study also showed that B cells were not required for MAIT cell development, but were required for peripheral expansion.16 Given that thymic precursors for MAIT cells and NKT cells express similar (but not identical) phenotypic markers and both require PLZF and microRNAs for their development, future studies will likely assess whether other factors are common for their development. For instance, several members of the NFkB family of transcription factors have been shown to be important for NKT cell development.59 Furthermore, mice deficient for the transcription factors Rorγt, HeLa E‐box binding protein and c‐Myb, have fewer NKT cells as they are unable to rearrange the distal TCR gene segments due to reduced lifespan of DP thymocytes.59 Hence, factors that affect thymocyte survival may impact on the development of MAIT cells as the gene encoding the MAIT TCR Vα‐chain (Vα19) is located at the extreme end of the 5′ end of the TCRα locus.60 Inhibitors of DNA transcription factors (Id2 and Id3), which interact with E proteins, have also been implicated in the development and differentiation of NKT cells,61-64 and more recently, we showed that members of the linear ubiquitin chain assembly complex, Hoil and Hoip, were required for normal NKT cell development in the thymus.65 Interestingly, the SLAM/SAP/Fyn pathway does not appear to be necessary for the development of MAIT cells, whereas it is important for the development of NKT cells.16, 66-69 The use of MR1 tetramers in candidate gene knockout mice should lead to the discovery of key molecules that are important for the development of MAIT cells and these can be compared with those that regulate the development of NKT cells. MAIT Cell Heterogeneity At least two functionally distinct subsets of stage 3 MAIT cells exist in mice and these develop following the expression of PLZF.24 The major population of MAIT cells in mice expresses RORγt and secretes IL‐17 upon activation, while a smaller subset expresses T‐bet and produces IFN‐γ upon activation.6, 24 With the exception of PLZF which is high on both these populations, they are reminiscent of mouse PLZFlo T‐bethi NKT1 cells and PLZFint Rorγt+ NKT17 cells, which secrete IFN‐γ and IL‐17, respectively.70 Notably, mouse thymus contains a third population of NKT cells, termed NKT2 cells, which are PLZFhi T‐betlo cells and predominantly produce IL‐4.70 While low levels of IL‐4 production were detected upon stimulation of mouse thymic MAIT cells,6 a defined population of MAIT cells that are equivalent to NKT2 cells has yet to be identified. In human thymus and peripheral blood, stage 3 MAIT cells coexpress intermediate levels of T‐bet and RORγt and secrete predominantly IFN‐γ and TNF upon activation.12, 18, 24, 71-73 This differs to stage 3 MAIT cells from naïve mice, which are mutually exclusive for T‐bet and RORγt expression, although intranasal infection of mice with Salmonella Typhimurium causes MAIT cells to coexpress these transcription factors. Thus, previously activated MAIT cells in mice appear to more closely resemble their human counterparts.32 While very few MAIT cells from human blood appear to produce IL‐17, MAIT cells from other human tissues can secrete IL‐17. For instance, MAIT cells isolated from the female genital tract express more IL‐17 in response to microbial stimuli compared to MAIT cells from peripheral blood.12 Moreover, tissue resident MAIT cells isolated from human liver vascular beds were the dominant population of IL‐17 producing T cells from this tissue14 and several studies have reported a role for IL‐17 producing MAIT cells in various autoimmune diseases (reviewed in this issue by Rouxel and Lehuen).74 Accordingly, mice and humans contain functionally distinct populations of MAIT cells, although the precise molecular mechanisms that underpin the differentiation into each distinct population remain largely unknown. Extrathymic Development of MAIT Cells MAIT cells continue to mature after they exit the thymus. While stage 3 MAIT cells from human and mouse thymus coexpress CD8α and CD8β, many peripheral MAIT cells express CD8α with low or no CD8β.5, 24, 52 These data suggest that CD8αα+ MAIT cells are likely derived from CD8αβ+ MAIT cells.18, 52 Moreover, stage 3 MAIT cells from human thymus have a limited capacity to produce cytokines compared to stage 3 MAIT cells from human blood, suggesting they undergo further maturation in the periphery. In support of this, stage 2 MAIT cells could be detected in the cord blood and the peripheral blood from young donors and stage 2 MAIT cells could be detected in the periphery of PLZF null mice, revealing that MAIT cells can exit the thymus as stage 2 cells, prior to further maturation to stage 3 cells in the periphery.24 It is currently unclear what factors drive extrathymic development of MAIT cells, whether it is direct exposure to microbial Ags or other environmental signals such as IL‐18 and/or other cytokines.24 The variation in MAIT cell frequency between humans and mice highlights important differences in the development and expansion of MAIT cells between these species. Several factors have been proposed to explain these differences. The housing of mice in specific pathogen‐free conditions likely limits their exposure to microbial Ags and, as described above, MAIT cells are drastically reduced in GF conditions.2, 24 Interestingly, attempts to reconstitute GF mice with monomicrobial flora or human microbiota only recovered MAIT cell numbers to levels akin to mice housed in specific pathogen‐free conditions, thus levels well below those found in humans.29, 45 In contrast, intranasal inoculation of mice with Francisella tularensis or Salmonella Typhimurium leads to rapid expansion of MAIT cells within the lungs of infected mice, levels more consistent with those observed in humans.31, 32 Future studies will likely examine whether mice caught from the wild or obtained from pet shops have elevated MAIT cells due to increased microbial exposure. Homeostasis and Expansion of MAIT Cells Genetic variability may also contribute to differences in MAIT cell frequency. For example, Cui et al. showed that Castaneus mice, a strain of mice originally derived from the wild but housed in specific pathogen‐free conditions, had a 20‐fold increase in MAIT cell numbers compared to common laboratory strains.45 The higher number of MAIT cells in Castaneus mice was not due to differences in thymocyte survival but rather to an increase in Vα19‐Jα33 transcripts that was linked to a genetic factor mapped to the Castaneus TCRα locus.45 Intriguingly, we recently showed that MAIT cells are over‐represented in NKT cell deficient CD1d−/− mice, suggesting that NKT cells and MAIT cells compete for a similar environmental niche (Figure 1).24 This has important implications for the field because NKT cell deficient mice are often used to assess the role of NKT cells in disease models and it is unclear how MAIT cells contribute to these diseases.75, 76 Furthermore, the frequency of MAIT cells and NKT cells in mice is inversed in humans, such that humans have high numbers of MAIT cells and low numbers of NKT cells, while the reverse is true in mice.4 Hence, it will be interesting to determine what factors these innate‐like T cells are competing for, and if other cell types are also involved in this interplay. For example, it was recently shown in mice that innate lymphoid cells compete with T cells for a limited supply of IL‐7.77 Furthermore, IL‐7 is also required for the homeostasis and survival of mouse NKT17 cells.78 In contrast to these findings in mice, we recently demonstrated a direct correlation in the frequency of MAIT cells and NKT cells in blood from the same human donor.19 A similar correlation between MAIT cells and NKT cell frequencies was shown in neonates in a recent study by Ben Youssef and colleagues.25 Moreover, they also demonstrated a parallel relationship between Vα7.2+ and Vα7.2− subsets of CD161+ T cells and while the latter population did not bind MR1 tetramer, their data suggests that both populations undergo a similar postnatal development pathway.25 These reports collectively support the concept that MAIT cells, NKT cells and related lineages share environmental maintenance factors, such that when the factors are abundant, these cell populations are increased in blood. Clearly, more work is required to fully appreciate the interactions that maintain innate‐like T cells in the immune system. The high abundance of MAIT cells in humans is likely due to ongoing exposure to microbial stimuli, which drives oligoclonal expansion of MAIT cells that have a reduced TCR repertoire.7, 45, 79 The frequency of MAIT cells increases with age such that very few MAIT cells are observed in the cord blood, presumably due to limited microbial exposure in the womb, while the numbers of MAIT cells increase in the blood from neonates and steadily rise until young adulthood (~30 years of age) before declining over subsequent decades16, 18, 24, 25, 35, 52, 80 (Figure 2). It is currently unclear how reduced numbers of MAIT cells impacts on the immune system of older individuals, although it is well described that as humans age they become increasingly immunocompromised.81, 82 Thus, one key factor that underpins the variability of MAIT cells in humans appears to be age, with optimal MAIT cell numbers coinciding with optimal immunological fitness. Taken together, these data highlight how MAIT cells continue to develop and expand after they exit the thymus and this process is likely dependent on microbial stimuli. Concluding Remarks MAIT cells, on average, represent the most abundant αβ T‐cell population with a single specificity in the human immune system. Understanding MAIT cell development and homeostasis cells may provide important clues as to why MAIT cell numbers vary between individuals (and species). The recent mapping of a three‐stage MAIT cell development pathway in mice and humans is facilitating further studies to determine the factors that govern this process. There appears to be functional overlap of MAIT cells with other innate‐like T‐cell populations and we must carefully assess the role of these different cell types in the context of microbial immunity. It will also be interesting to address how other related T‐cell subsets develop, including atypical MR1‐restricted Vα7.2− T cells and populations of Vα7.2−CD161+ T cells, that do not bind MR1 tetramer but share similar characteristics with MAIT cells. Future studies into the development and homeostasis of MAIT cells (and related subsets thereof) may lead to the identification of novel targets to modulate the numbers of these cells which would be valuable in settings where they are depleted, potentially leading to a compromised immune system, such as in cancer and HIV patients. Acknowledgments DGP is supported by a National Health and Medical Research Council (NHMRC) Career Development Fellowship (1144308). DIG is supported by an NHMRC Senior Principal Research Fellowship (1020770 and 1117766). The authors are supported by NHMRC project grants 1145373, 1122890 and 1140126 and the Australian Research Council (ARC; CE140100011). Conflict of Interest The authors declare no conflict of interest. References Citing Literature Number of times cited according to CrossRef: 2 Hui‐Fern Koay and Dale I Godfrey, MicroRNA‐managing the development of MAIT cells, Immunology & Cell Biology, 97, 2, (121-123), (2019). Wiley Online Library Erik Seth, Christine L. Zimmer, Marcus Reuterwall‐Hansson, Ammar Barakat, Urban Arnelo, Annika Bergquist, Martin A. Ivarsson and Niklas K. Björkström, Primary sclerosing cholangitis leads to dysfunction and loss of MAIT cells, European Journal of Immunology, 48, 12, (1997-2004), (2018). Wiley Online Library

Research ArticleInfectious diseaseTherapeutics Free access | 10.1172/jci.insight.97844 Enhancing IgG distribution to lung mucosal tissue improves protective effect of anti–Pseudomonas aeruginosa antibodies M. Jack Borrok,1 Antonio DiGiandomenico,2 Nurten Beyaz,1 Gabriela M. Marchetti,1,3 Arnita S. Barnes,1 Kristen J. Lekstrom,1 Sandrina S. Phipps,1 Michael P. McCarthy,2 Herren Wu,1 William F. Dall’Acqua,1 Ping Tsui,1 and Ruchi Gupta3 First published June 21, 2018 - More info Abstract IgG antibodies are abundantly present in the vasculature but to a much lesser extent in mucosal tissues. This contrasts with antibodies of the IgA and IgM isotype that are present at high concentration in mucosal secretions due to active delivery by the polymeric Ig receptor (pIgR). IgG is the preferred isotype for therapeutic mAb development due to its long serum half-life and robust Fc-mediated effector function, and it is utilized to treat a diverse array of diseases with antigen targets located in the vasculature, serosa, and mucosa. As therapeutic IgG antibodies targeting the luminal side of mucosal tissue lack an active transport delivery mechanism, we sought to generate IgG antibodies that could be transported via pIgR, similarly to dimeric IgA and pentameric IgM. We show that an anti–Pseudomonas aeruginosa IgG fused with pIgR-binding peptides gained the ability to transcytose and be secreted via pIgR. Consistent with these results, pIgR-binding IgG antibodies exhibit enhanced localization to the bronchoalveolar space when compared with the parental IgG antibody. Furthermore, pIgR-binding mAbs maintained Fc-mediated functional activity and promoted enhanced survival compared with the parental mAb in a P. aeruginosa acute pneumonia model. Our results suggest that increasing IgG accumulation at mucosal surfaces by pIgR-mediated active transport can improve the efficacy of therapeutic mAbs that act at these sites. Introduction Immunoglobulin isotype classes (IgG, IgA, IgM, IgD, and IgE) have distinct roles in humoral immunity and are distributed differently throughout the body. Of these, the IgG isotype is overwhelmingly favored for therapeutic mAbs for numerous reasons. Primarily, the neonatal Fc receptor (FcRn) confers long serum half-life, and Fcγ receptors (FcγRs) impart immune effector function to IgG antibodies exclusively. Additionally, the production, purification, and overall manufacturability properties of IgG mAbs are considered superior to other isotypes, which generally exhibit more complex oligomerization and glycosylation patterns. The clinical preference for the IgG isotype limits therapeutic antibodies to certain types of (FcγR-mediated) immune engagement and governs distribution throughout the body. IgG cannot be secreted to mucosal tissues like IgA and IgM, and it must rely on passive transport or transudation to accumulate at these sites. Many IgG antibodies approved or under clinical evaluation treat diseases affecting mucosal organs. These include antibodies targeting pulmonary diseases caused by viruses or bacteria (1–3), as well as other respiratory (4) and intestinal diseases (5). For therapeutic antibodies targeting antigens located in these tissues, the mainly vascular distribution of IgG could be unfavorable compared with IgA and IgM, which can be transported into the mucosal lumen at high levels. Indeed, systemically administered IgG levels in bronchoalveolar lavage (BAL) fluid have been reported to be approximately 1,000 times lower than levels of IgG in serum (6–8). The polymeric Ig receptor (pIgR) facilitates the conversion of dimeric IgA (dIgA) and pentameric IgM to their secreted forms (sIgA and sIgM), while transporting these molecules from the lamina propria of mucosal tissues to the lumen (9, 10). The secretory forms of IgA and IgM differ from those found in serum in that the extracellular portion of pIgR (after facilitating luminal transport) is proteolytically cleaved and remains bound to these Ig as the secretory component (11). The secretory component confers stability and protease resistance to IgA in the mucosal environment and enhances the protective ability of these molecules (12–14). In this study, we sought to determine whether the distribution and efficacy of an IgG antibody could be altered by endowing it with the ability to bind and be transported by pIgR. We chose Cam-003, a human IgG mAb that targets the polysaccharide synthesis locus (Psl) exopolysaccharide of Pseudomonas aeruginosa (P. aeruginosa) (15), as our model therapeutic antibody. P. aeruginosa is an important respiratory pathogen and a significant cause of acute pneumonia in ventilated subjects. In addition, P. aeruginosa is also a major cause of chronic lung infections in cystic fibrosis patients and leads to persistent lung function damage, ultimately causing death in this patient population. Psl is a serotype-independent exopolysaccharide produced by P. aeruginosa that mediates attachment to epithelial cells and is important in the formation and maintenance of antibiotic recalcitrant biofilms (16, 17). In addition, Psl prevents complement deposition on the bacterial surface, thus allowing P. aeruginosa to escape immune recognition by host effector cells (18, 19). Cam-003 targeting of Psl mediates potent complement-dependent opsonophagocytic killing (OPK) of P. aeruginosa by host effector cells and confers significant protective activity against diverse P. aeruginosa strains in a murine lung infection model (15). In this work, we show that Cam-003 fused to pIgR-binding peptides binds to pIgR and undergoes pIgR-mediated transcytosis. In addition, i.v. administration of the mAb in mice resulted in greater accumulation of pIgR peptide–fused antibodies in BAL fluid when compared with the parental IgG mAb. Consistent with these results, i.v. administration of pIgR peptide–fused Cam-003 to mice 24 hours before infection resulted in enhance survival against lethal P. aeruginosa lung infection compared with animals receiving the parental Cam-003 mAb. Our results demonstrate that conferring therapeutic IgG antibodies with pIgR binding capabilities could enhance the accumulation of therapeutic IgG antibodies targeting bacteria to the lung lumen. Results Generation and characterization of pIgR-binding peptide antibody fusions. Peptides have previously been identified that bind to pIgR and promote transcytosis of phage particles or other cargo (20, 21). To assess whether addition of these peptides to IgGs can alter antibody biodistribution, several of these peptides were generated as C-terminal fusions to the heavy chain of Cam-003 (a human IgG1 antibody that binds to the Psl exopolysaccharide of P. aeruginosa) (15). A GGGGS linker was employed to link the C-terminus of the antibody with the peptides tested. Several peptides known to bind pIgR (20, 21), as well as full-length human and mouse J-chains (known to facilitate pIgR binding in IgA and IgM), were constructed. Many of the antibody-peptide fusions (including the J-chain fusions) had extremely poor expression or severe aggregation issues (Supplemental Table 1; supplemental material available online with this article; https://doi.org/10.1172/jci.insight.97844DS1). However, 2 peptides with the sequences QRNPRLRLIRRHPTLRIPPI and SAMFVPFDIAVGVRDGQQGLGGSRRKGARLREAISSYAE (referred to hereafter as QRN and SAM) were well expressed and had high monomeric content. Binding to either human (h) or murine (m) pIgR was then evaluated via ELISA (Figure 1). Cam-003–QRN was found to bind to m-pIgR with a half maximal effective concentration (EC50) of 0.50 μg/ml and to h-pIgR with an EC50 of 0.52 μg/ml. Cam-003–QRN binding exceeded that of human dIgA, a natural ligand for pIgR, which bound with an EC50 of 11.7 μg/ml for h-pIgR and 8.7 μg/ml for m-pIgR. Cam-003–SAM had only minimal binding to pIgR via ELISA and was not carried forward for further experiments. Figure 1 Cam-003 peptide fusions bind to human and murine pIgR. Binding of C-terminal peptide antibody fusions to pIgR was determined by ELISA. Cam-003 alone showed no binding to either human (A) or murine (B) pIgR at the highest concentration tested (200 μg/ml). Cam-003–QRN and its derivative Cam-003–KLKL had improved binding to pIgR compared with the natural pIgR ligand dimeric IgA, whereas another peptide fusion Cam-003–SAM exhibited poorer binding (n = 4). Data are representative of at least 2 independent experiments. Generation of the Cam-003–QRN variants. Cam-003–QRN bound effectively to both human and murine pIgR, yet mass spectrometric analysis of purified Cam-003–QRN revealed that protease cleavage occurred at 2 regions within the QRN peptide sequence (Supplemental Figure 1). The major species (species 1) observed was full length or missing the C-terminal isoleucine or the C-terminal dipeptide PI. An additional less abundant species observed was cleaved in the RLRL region midpeptide (species 2). Peak heights were used to estimate the abundance of the 2 species (Supplemental Figure 1). Analysis of 3 separate batches revealed QRN species 1 was ~70% abundant upon purification, whereas QRN species 2 was present at ~30% abundance. To increase the amount of species 1 QRN peptide, several mutants were generated in the RLRL sequence of the QRN peptide fusion (Supplemental Table 2). Of these, 1 mutant with lysines replacing 2 arginine residues in this sequence (referred to as KLKL) could be expressed consistently with high species 1 content (~85%) and maintained binding to h-pIgR and m-pIgR similarly to the parental QRN fusion (Figure 1). Cam-003–KLKL bound to m-pIgR with an EC50 of 0.43 μg/ml and to h-pIgR with an EC50 of 0.89 μg/ml via ELISA. Other mutations within the RLRL sequence of the QRN peptide either did not retain pIgR binding or had less full-length (species 1) heavy chains observed than the original QRN peptide. IgG peptide fusions transcytosis in pIgR-expressing cells. As the QRN C-terminal antibody fusion and engineered KLKL variant bound to the pIgR receptor, we next sought to determine whether these antibody fusions could be cargo for pIgR-mediated transcytosis. Stable human and murine pIgR expressing Madin-Darby canine kidney (MDCK) cells were generated to assess pIgR-mediated transcytosis (22). Cam-003 and Cam-003 peptide fusions were then evaluated in transwell assays. Antibodies were added in the bottom (basolateral side) chamber, and transcytosis was measured by quantifying antibody in the top (apical) chamber (Figure 2A). In either h-pIgR– or m-pIgR–expressing MDCK cells, Cam-003 levels in the apical chamber were at low levels, similar to untransfected MDCK cells (Figure 2B). After 24 hours, increased transcytosis was observed for both Cam-003–KLKL and Cam-003–QRN when compared with Cam-003 alone in wells with both h-pIgR– and m-pIgR–expressing MDCK cells (Figure 2B). Figure 2 Transcytosis of Cam-003 peptide fusions in pIgR-transfected MDCK cells. Antibodies were added to the bottom chamber (basolateral) of transwells containing either untransfected, h-pIgR–, or m-pIgR–transfected Madin-Darby canine kidney (MDCK) monolayers (A). At 24 hours, antibodies in the top chamber (apical) were quantified by ELISA. Cam-003 levels were similar in all 3 cell lines, whereas Cam-003–QRN and Cam-003–KLKL, as well as human dimeric IgA, had increased accumulation in the apical chamber (B). Data are representative of at least 2 independent experiments (n = 10 for Cam-003 antibodies, n = 6 for dIgA). Significance was determined using 2-way ANOVA (with Tukey’s post hoc test; ****P < 0.0001). pIgR-binding IgG fusion levels increased in BAL. We then determined how Cam-003–QRN and Cam-003–KLKL fusions would alter antibody localization to the lung lumen when administered i.v. to mice. Cam-003–QRN, Cam-003–KLKL, and Cam-003 IgG were dosed via tail-vein injection into mice, followed by collection of BAL fluid 48 hours after administration. Serum samples taken at 24 and 48 hours were also collected, and antibody levels were determined by biolayer interferometry (OCTET). Serum levels were similar between Cam-003 and the Cam-003 pIgR peptide fusions (Figure 3A). However, Cam-003–QRN and Cam-003–KLKL exhibited 2.7- and 3.9-fold higher IgG concentrations, respectively, in BAL fluid 48 hours after antibody administration when compared with Cam-003 (Figure 3B). Figure 3 Increased levels of Cam-003 variants in bronchoalveolar lavage and similar levels in serum. (A) Serum levels of Cam-003, Cam-003–QRN, and Cam-003–KLKL were quantified from BALB/c mice 24 and 48 hours after initial i.v. injection. Serum levels did not differ significantly at 24 or 48 hours. (B) Cam-003–QRN and Cam-003–KLKL levels in BAL (assessed at 48 hours) were elevated from those of Cam-003 alone (P = 0.195 and 0.023, respectively; 1-way ANOVA with Tukey’s post hoc test; *P < 0.05). Data are representative of at least 2 independent experiments; n = 4 per group. Assessing antibody fusions for OPK activity against P. aeruginosa. Prior to testing the pIgR-binding Cam-003 fusions in a P. aeruginosa infection model, we first assessed whether these antibodies maintain the ability to promote Fc-mediated phagocyte-dependent killing of P. aeruginosa. It has previously been shown that Cam-003 promotes OPK of P. aeruginosa and that this mechanism of action correlates with protective activity in vivo (15). Robust complement-dependent OPK of the P. aeruginosa strain PAO1 was observed with Cam-003 with EC50 values of 0.11 μg/ml (Figure 4A). Cam-003–QRN– and Cam-003–KLKL–mediated OPK was similar to Cam-003 alone (EC50 values 0.09 and 0.15 μg/ml, respectively), suggesting the C-terminal peptide fusions did not significantly impair OPK activity. Samples lacking antibody (media only) or with an isotype control IgG failed to elicit OPK activity against P. aeruginosa (Figure 4A). For this experiment, human serum (depleted of Pseudomonas-binding antibodies) was used as a complement source. OPK with an additional commonly used complement source (baby rabbit complement) was also evaluated (Supplemental Figure 3). Again, Cam-003, Cam-003–QRN, and Cam-003–KLKL displayed robust OPK activity, with the peptide fusions having slightly lower EC50 values than Cam-003. Figure 4 pIgR-binding Cam-003 fusions elicit opsonophagocytic killing and improved protection against lethal challenge in a P. aeruginosa acute pneumonia model. (A) Opsonophagocytosis assay with luminescent P. aeruginosa serogroup 05 strain PAO1 (PAO1.lux). OPK with Cam-003–QRN, Cam-003–KLKL, and Cam-003 are shown with the isotype control IgG R347. (B–D) Survival of BALB/c mice prophylactically immunized with an IgG isotype control R347, Cam-003, and either Cam-003–QRN (B) or Cam-003–KLKL (C and D) prior to i.n. infection with P. aeruginosa strain 6077. Results are represented as Kaplan-Meier survival curves; differences in survival were calculated by the log-rank test (Mantel-Cox). Data are representative of at least 2 independent experiments; n = 10 per group for survival experiments. (B) Cam-003 and Cam-003–QRN had significantly better protection than the isotype control at both doses tested (P < 0.0001 for both 5 and 10 mg/kg doses; 4.5 × 105 CFU inculcation). Cam-003–QRN survival was significantly improved compared with Cam-003, as well (P = 0.0014 for 5 mg/kg doses and P = 0.0098 for 10 mg/kg doses). (C) At 5 × 105 CFU, Both Cam-003 and Cam-003–KLKL were protective compared with R347 at both doses (P = 0.017, 2 mg/kg Cam-003; P = 0.0004, 6 mg/kg Cam-003; P < 0.0001, 2 and 6 mg/kg doses of Cam-003–KLKL). Cam-003–KLKL survival was superior to Cam-003 when comparing both the 2 mg/kg doses (P = 0.0042) and 6 mg/kg doses (P = 0.017). (D) At an 8 × 105 CFU inoculum dose, Cam-003 and Cam-003–KLKL survival was again enhanced compared with R347 (P < 0.0001, 2 mg/kg Cam-003; P = 0.0002, 6 mg/kg Cam-003; P < 0.0001, Cam-003–KLKL), with Cam-003–KLKL survival also enhanced compared with Cam-003 (P = 0.017, 6 mg/kg; not significant, 2 mg/kg). pIgR-binding peptide fusion mAbs exhibit enhanced protective activity in vivo. Given that Cam-003 pIgR fusion mAbs could still elicit OPK activity, we next sought to evaluate whether they provided improved protection in vivo in comparison with the parental Cam-003 mAb and a control IgG. The pIgR-binding peptide fusions, as well as Cam-003, were then tested for their ability to protect against lethal P. aeruginosa infection in a murine acute pneumonia model following prophylactic administration of the antibodies. A highly pathogenic strain of P. aeruginosa (strain 6077) was delivered i.n. 24 hours after i.v. administration of either Cam-003, Cam-003–QRN, or the isotype control antibody R347, and survival was monitored. In this initial experiment, both Cam-003–QRN and the parental Cam-003 mAbs at both concentrations exhibited significant enhanced survival when compared with the control IgG (Figure 4B). Moreover, Cam-003–QRN at both 10 and 5 mg/kg yielded enhanced protective activity when compared with the parental Cam-003 mAb at each antibody concentration (Figure 4B). We next sought to evaluate the activity of Cam-003–KLKL using a similar experimental design. In this experiment, both Cam-003–KLK–dosed groups (6 and 2 mg/kg) survived challenge (Figure 4C). This 100% protective effect for Cam-003–KLKL was a statistically significant when compared with both the isotype control and the parental Cam-003 molecule at both the 2 and 6 mg/kg dosage levels. A higher infectious inoculum, approximately 4-fold above the 100% lethal dose (LD100) for this strain (8 × 105 CFU/mouse), was then administered to assess whether the survival improvement over the parental Cam-003 afforded by Cam-003–KLKL would persist with greater lung burden. Cam-003 again had a significant protective effect compared with the isotype control at both dosage levels; however, all Cam-003–treated animals succumbed to infection within 50 hours (Figure 4D). Cam-003–KLKL–dosed animals again showed improved survival compared with both the isotype control and the parental molecule Cam-003. Even with an infectious inoculum at 4 times the LD100 for strain 6077, multiple animals within the Cam-003–KLKL groups survived the challenge until the end of the study, again demonstrating superiority to the parental molecule. Discussion The pIgR plays a key role in mucosal immunity by transporting large amounts of oligomeric IgA and IgM into the lumen of organs such as lungs and intestine. In addition to these endogenous pIgR ligands, IgG antibodies (23), Fabs (24–26), single-chain variable fragments (scFvs) (27, 28), camelid VHH domains (29), and phage-derived peptides (20, 21) have been generated over the last 2 decades by several laboratories to bind and become cargo for pIgR-mediated transport. Most of these engineered pIgR ligands show some level of transcytosis in cell monolayers, but few of these have been tested in vivo as to whether they can be transported to mucosal organs. In a notable exception, Fab domains targeting pIgR conjugated to polylysine and bound to condensed plasmid DNA were used to for gene delivery to the mouse lung lumen after i.v. administration (25). In that study, protein expression of the delivered gene was highly elevated in the lung lumen compared with the same complex with a nontargeting Fab. This unique proof-of-concept work showed for the first time to our knowledge that pIgR targeting can lead to accumulation of cargo in the lung lumen upon systemic administration. Our work herein expands on these results by using a human IgG antibody, Cam-003, as cargo to be transported to the lung lumen by high-affinity pIgR-binding peptides. Cam-003 targets the Psl exopolysaccharide of P. aeruginosa and has been shown to mediate protection in a murine model of acute pneumonia (15). We show that, by appending pIgR binding capabilities to Cam-003, we increase its levels in BAL fluid and that this enhanced accumulation correlates with improved protective activity when compared with the parental IgG. This result underscores the potential for this approach to improve the efficacy of antibodies with targets in the lung lumen. In this study, we screened multiple peptides reported to bind and be transported by pIgR for their ability to be expressed as IgG fusions and maintain pIgR binding. Only the QRN peptide met these criteria. The KLKL peptide offered a modest improvement in full-length peptide content compared with QRN. Ultimately, further peptide engineering will be needed to both eliminate protease susceptibility and identify optimal attachment sites to IgG for mitigating any potential decreases in FcγR or C1q binding. The binding of peptide-IgG fusions to FcγR or C1q was not assessed because OPK activity was minimally affected by the addition of peptides; however, the potential exists that effector function could be impaired by attaching peptides or other fusions to the Fc. As an alternative to peptide engineering, we predict a similar result could be achieved with bispecific antibodies (with 1 or more pIgR-targeting arms) rather than peptides. A dIgA format (a natural pIgR ligand) has recently been used to deliver antibody to mouse kidney cysts, tissue that is relatively inaccessible to IgG antibodies (30). We predict a similar result could be achieved using our approach to endowing existing IgG antibodies with the ability to bind and be transported by pIgR. An IgG-based approach could be advantageous compared with dIgA due to IgG’s favorable pharmacokinetics, relative ease of manufacture, and homogeneity. Indeed, serum levels of Cam-003–QRN and Cam-003–KLKL at 24 and 48 hours were similar to those of the parental IgG. dIgA is known to have a much quicker serum clearance (~4–5 times faster) (31). As our study and another (25) have shown, systemic administration of pIgR-targeting antibodies or fragments increases accumulation in lungs. In this study, we did not assess accumulation in other mucosal organs such as the kidneys or intestines. Results with dIgA accumulation in kidney cysts (30) confirm pIgR-binding Ig can indeed accumulate in organs other than the lungs. Further studies will be necessary to determine where pIgR-binding Ig accumulate upon various routes of administration (ROA) and whether a specific ROA can cause more accumulation in specific mucosal tissues versus others. Nevertheless, the ability to access mucosal surfaces that have previously been poorly accessible to IgG therapeutics presents an opportunity for enhancing efficacy to both microbial and endogenous targets within these tissues. Methods Cloning. C-terminal peptide fusions were generated using overlapping PCR with synthetic oligonucleotides synthesized at Integrated DNA Technologies. PCR fragments were cloned into a MedImmune proprietary mammalian expression vector (32). Standard molecular biology methods were used for cloning, vectors preparation, and DNA sequencing. E. coli One Shot Stbl3 chemically competent cells, used for DNA amplification, were purchased from Thermo Fisher Scientific. Expression and purification. Antibodies were expressed as previously described (33). Briefly, expression vectors expressing both antibody light and heavy chains were transfected in CHO-G22 cells. CHO-G22 cells were cultured with 25 μM l-methionine sulfoximine and 100 μg/ml hygromycin in MedImmune’s proprietary CHO-V2 medium at 37°C, 5% CO2, and 80% humidity. Twenty-four hours prior to transfection, CHO-G22 cells were diluted to 1 × 106 cells/ml in CHO-V2 medium without hygromycin and l-methionine sulfoximine and grown overnight. mAb expression vector (500 μg) was diluted into 7.5 ml of 150 mM sodium chloride, and 2.5 ml of 1 mg/ml PEI MAX (Polysciences) was mixed with 5 ml of the 150 mM sodium chloride solution (VWR). The DNA and PEI-max solutions were combined and incubated for 1 minute at room temperature before being added to 500 ml of 2 × 106 CHO-G22 cells. The transfected cells were grown for 24 hours as described above. Thereafter, the temperature was changed to 34°C and supplemented with 500 ml of CHO-V2 medium. Culture medium was collected 10 days after transfection. Antibody variants were purified using standard protein A affinity chromatography and were subsequently buffer exchanged using dialysis in PBS (pH 7.2). Monomeric content of the antibodies and antibody fusions were analyzed using analytical size-exclusion chromatography (SEC-HPLC). Antibodies having an initial monomer content below 98% had aggregate removed by preparative SEC-HPLC prior to testing (Supplemental Figure 2). ELISA binding to pIgR. Human or murine pIgR extracellular domain (R&D Systems) was coated on 96-well maxisorp plates (Nunc) overnight at 4°C (2 μg/ml in PBS). Plates were then blocked with 2% BSA in PBS for 2 hours at room temperature. After washing, titrated antibodies or antibody fusions were added and allowed to incubate for 1 hour. After 3 washes in PBS, peroxidase-conjugated anti–human Fd (Southern Biotech, catalog 2046-05) was used to as a detection reagent. The wells were washed 3 times, and TMB substrate solution was added. The reaction was stopped with 2 N H2SO4, and the absorbance at 450 nm was measured. Transcytosis assay. MDCK (purchased from ATCC) transcytosis experiments were conducted similarly to Jerdeva et. al (34). Stably transfected MDCK cells expressing either murine or human full-length pIgR were plated in transwell plates with at 500,000 cells/well with MEM + 10% or FBS + 1% penicillin-streptomycin. MDCK pIgR cells were generated in house using a lentiviral vector and confirmed to have pIgR expression. Media (1 ml) was added on the top (apical) side; 0.5 ml of media was added on the bottom (basolateral) side. Media was changed every 48 hours prior to beginning transcytosis experiment. Cells were used for experiments on the fourth or fifth day after plating, after confluent monolayers had formed. Antibody (20 μg) was added to the bottom chamber, and media was collected from the top chamber; antibody amount was assessed by OCTET or quantitative ELISA. BAL and serum collection and quantification. BALB/c mice (6–8 weeks old; Envigo) were given a bolus i.v. dose of 2.5 mg/kg antibody. Four mice were used per antibody. Blood samples were obtained from the retro-orbital plexus using capillary pipettes at 24 hours and via cardiac puncture at 48 hours. BAL was taken at 48 hours by washing the lung lumen with 1 ml of PBS 3× and collecting. Biolayer interferometry (OCTET; FortéBio Inc.) was used to monitor the serum or BAL concentrations of the tested antibodies. Briefly, samples or buffer were dispensed into 384-well microtiter plates (FortéBio Inc.) at a volume of 50 μl per well. Operating temperature was maintained at 30°C. Anti–human Fab–coated biosensor tips (FortéBio Inc.) were prewetted with PBS. Standard curves were generated for each antibody variant, generated via OCTET analysis software. Sample concentrations were generated automatically based on the standard curve via the OCTET User Software (version 3.1) and was subsequently analyzed via Prism (GraphPad Software). OPK assay. Assays were performed as previously described, with some modifications (15). OPK assays were performed in a 96-well plate format. P. aeruginosa strain PA01-lux (expressing luciferase) was constructed as previously reported (35) and grown to mid log-phase in LB media, and cultures were diluted to 2 × 106 cells/ml. Bacteria (25 μl) were then combined with an equal volume of 10% baby rabbit serum; differentiated HL-60 cells (2 × 107 cells/ml) as the polymorphonuclear leukocyte source; and titrated mAb. After 2-hour shaking at 37°C, relative luciferase units (RLUs) for each well were determined using an Envision Multilabel plate reader (PerkinElmer). The percentage of killing was determined by comparing RLUs derived from assays lacking mAb (no OPK) to RLUs obtained from assays with anti-Psl mAbs or the control R347 mAb (generated in-house). For OPK assays using human sera as a complement source, human serum was first adsorbed against an isogenic Psl-deficient mutant strain (PAO1ΔpslA) (15) and filter sterilized (0.2 μm). Adsorbed sera was then used in place of rabbit sera in the OPK assay described above. HL-60 cells were purchased from ATCC. In vivo P. aeruginosa model. Studies were performed essentially as described previously (15, 36) with some modifications. Guidelines for humane end points were strictly followed. Antibodies were administered 24 hours before infection with P. aeruginosa strain 6077 in the acute pneumonia model. BALB/c mice (Envigo) were infected with 6077 suspended in a 0.05-ml inoculum. Strain 6077 was a gift from Joanna Goldberg (Emory University, Atlanta, Georgia, USA). Statistics. Data were analyzed using 1-way ANOVA with Tukey’s post hoc test or 2-way ANOVA with Tukey’s post hoc test. For survival studies, data are presented as Kaplan-Meier survival curves and were analyzed by the log-rank test. All statistical analyses were performed using GraphPad Prism version 7 software. Study approval. All animal studies were approved by the MedImmune IACUC and were conducted in an Association for Assessment and Accreditation of Laboratory Animal Care–accredited facility in compliance with US regulations governing the housing and use of animals. Donor serum was obtained using a MedImmune approved IRB protocol (IRB Pro00004341). Author contributions MJB, AD, and RG designed experiments, performed experiments, analyzed data, and wrote the manuscript. GMM and NB performed experiments. 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