https://orcid.org/0000-0002-6714-3335
Figures
Abstract
It is increasingly recognized that innate T cells such as natural killer T (NKT) cells, mucosal associated invariant T (MAIT) cells, and γδ T cells play an important role in shaping adaptive immune responses following influenza infection or vaccination. This is largely through the multiple cytokines these cells release upon activation, which have downstream effects on the scope and magnitude of virus-specific T and B cells, and antibodies which they form. Here, we examined the contribution of NKT cells using pigs, which are considered a highly translational model of human influenza A infection. CD1D-expressing and CD1D-deficient pigs that respectively possess and lack NKT cells, were infected with the swine influenza virus H3N2 A/Swine/Colorado/23619/1999 (CO99), with or without prior mucosal immunization with a recombinant H3N2 A/Swine/Texas/4199–2/1998 (TX98) modified live vaccine encoding a truncated NS1 protein (TX98 NS1Δ126). Vaccination reduced virus load and pulmonary pathology by similar amounts in both genotypes. However, NKT cell status had a significant impact on the underlying immune response: Contrary to the post vaccination period, virus-specific T cell expansion after infection was greater in CD1D-deficient than CD1D-expressing pigs, indicating that NKT cells play opposing roles in different phases of the immune response. NKT cell-deficient pigs also had reduced T cell cuffing around airways. Furthermore, paired single-cell and immune receptor profiling revealed altered gene expression and higher numbers of expanded T and B cell clones in the absence of NKT cells. Our newly established assay using porcine-specific γ and δ chain primers provided new insights into the TCR repertoire of various pulmonary γδ Τcell subsets. Overall, our results indicate a homeostatic role for NKT cells in regulating several important features of the influenza immune response, particularly virus-specific T cell dynamics.
Author summary
While present understanding of influenza A virus (IAV) immunity is focused on conventional major histocompatibility complex-restricted T cells, mouse studies have shown that innate-like T cell subsets, including CD1d-restricted natural killer T (NKT) cells, contribute to IAV immunity. However, caution is needed in extrapolating these findings to other animals due to considerable inter-species differences in the NKT cell-CD1d system and because mice are not naturally infected with IAVs. To determine how NKT cells contribute to IAV immunity in a natural host, we compared IAV-infected CD1D-expressing and CD1D-deficient pigs, which respectively possess and lack NKT cells, with or without prior mucosal immunization with a heterologous modified live virus vaccine. NKT cell deficiency did not affect virus load or pulmonary pathology following IAV infection, regardless of vaccination status. However, removing NKT cells altered the nature of the adaptive immune response, particularly the dynamics of virus-specific T cell accumulation, the localization of T cells in the lung after infection, and the widespread transcriptional and immune receptor repertoire changes in multiple cell types. Understanding NKT cell contributions to IAV immunity in pigs is beneficial for designing swine-tailored vaccines and therapeutics and for utilizing pigs as a model to study human respiratory infections and NKT cell biology.
Citation: Kwon T, Gu W, Morozov I, Carossino M, Lyoo EL, McDowell CD, et al. (2026) Pigs lacking Natural Killer T cells have altered cellular responses to influenza. PLoS Pathog 22(4): e1014094. https://doi.org/10.1371/journal.ppat.1014094
Editor: Kalpana Agnihotri, CSIRO ACDP: CSIRO Australian Centre for Disease Preparedness Business Unit, AUSTRALIA
Received: November 7, 2025; Accepted: March 18, 2026; Published: April 6, 2026
Copyright: © 2026 Kwon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The sequencing data are available at Gene Expression Omnibus (accession GSE306556). The primary code used in this study is available at 10.5281/zenodo.19187727. The final processed data are available for download and direct query at https://singlecell.broadinstitute.org/single_cell/study/SCP3512.
Funding: Funding for this study was provided through grants from the National Institutes of Health grant AI158477 (to JPD and JAR) and the U.S. Department of Agriculture grant 2021-67015 (to JPD). Additional support was provided by the National Bio and Agro-Defense Facility (NBAF) Transition Fund from the State of Kansas (to JAR), the AMP and MCB Core of the Center on Emerging and Zoonotic Infectious Diseases (CEZID) of the National Institutes of General Medical Sciences under award number P20GM130448 (to JAR), and the NIAID supported Center of Excellence for Influenza Research and Response (CEIRR) under contract number 75N93021C00016 (to JAR). The funding for the National Swine Resource and Research Center is from the National Institute of Allergy and Infectious Disease (to JPD and KL), the National Institute of Heart, Lung and Blood, and the Office of the Director (U42OD011140) (to KL). LSU acknowledges support from an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number P20GM130555-5011 (MC), U.S. Department of Agriculture’s (USDA) National Institute of Food and Agriculture (NIFA) Agriculture and Food Research Initiative and American Rescue Plan Act through USDA Animal and Plant Health Inspection Service (APHIS) competitive grant number 2023-70432-39465 (to MC) and the School of Veterinary Medicine, Louisiana State University (PG009641) (to MC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: The J.A.R. laboratory received support from Tonix Pharmaceuticals, Xing Technologies, Esperovax, Genus, and Zoetis, outside of the reported work. J.A.R. is inventor on patents and patent applications on the use of antivirals and vaccines for the treatment and prevention of virus infections, owned by Kansas State University.
Introduction
Invariant natural killer T (NKT) cells are a population of innate T cells expressing a semi-invariant T cell receptor (TCR) that recognizes lipid and glycolipid ligands presented by the major histocompatibility complex (MHC) class I-like molecule CD1d [1–3]. Upon activation, NKT cells supply a wide array of helper functions analogous to CD4+ T helper cells, which can enhance cellular and humoral immune responses against a wide range of pathogens, including against influenza A virus (IAV) [4]. Among the downstream responses modulated by activated NKT cells is the licensing of antigen presenting cells that subsequently shape CD4+ and CD8+ T cell effector and memory functions [5]. NKT cells also boost humoral immunity by either directly interacting with B cells presenting glycolipids via CD1d (known as cognate help), or by indirectly activating B cells via inducing T follicular helper (Tfh) cells specific for the B cell-displayed protein antigens (known as non-cognate help) [6–9].
Synthetic NKT cell ligands, such as α-galactosylceramide (α-GalCer), have been useful in understanding NKT cell-mediated immune responses as they specifically activate NKT cells to induce potent immunity against a wide range of co-delivered antigens. Much of this research is based on using α-GalCer to enhance IAV vaccines in mice. These studies almost invariably find that NKT cell stimulation leads to stronger vaccine-induced immunity and greater protection against IAV infection with both homologous and heterologous influenza strains [3]. However, the question of whether unmanipulated NKT cells have a natural role to play in influenza immunity is less certain. Prior studies reported that NKT cell-deficient CD1d- and Jα18-knockout (KO) mice produced lower concentrations of influenza-specific antibodies and/or T cells following IAV infection or vaccination compared to standard mice [10,11]. In contrast, NKT cells have been reported to play a key role in suppressing influenza-specific CD8+ T cells through indoleamine 2,3-dioxygenase (IDO), an important mediator of immune suppression [12]. In another study, CD1d-KO mice previously infected with H1N1 or H3N2 subtypes of IAV and re-infected after four weeks with homologous or heterosubtypic viruses were found to be equally resistant to re-infection as standard mice, indicating that, at a practical level, NKT cell responses were redundant [13].
While these and other mouse studies have provided important insight into the role of NKT cells in influenza immunity, caution is needed in extrapolating their findings to humans, or other species with the CD1d-NKT cell system, as there are considerable inter-species differences in NKT cell frequencies and subsets [14–23]. Moreover, mice are not naturally infected by IAVs, and after virus adaption, mice usually develop worse clinical disease than humans, but without IAV-specific clinical signs [24–27]. Accordingly, it would be of benefit to re-examine the natural role of NKT cells in IAV-specific immunity using species like pigs, which are natural IAV hosts and that share many anatomical, physiological, and immunological traits with humans, including similar NKT cell frequencies.
Hence, the goal of the current study was to compare pre-existing IAV immunity in CD1D-deficient and CD1D-expressing pigs that respectively lack and possess NKT cells. The pigs were immunized with a modified live IAV vaccine and subsequently challenged with a heterologous IAV to test cross-protective immunity. The results were compared to infected naive pigs of the same two genotypes. This is of interest because NKT cells have been shown to participate in early innate immune responses that inhibit virus replication in mice [28–31]. Our results shed light on how NKT cells coordinate the immune response to IAV in an animal model that closely mirrors human IAV infections.
Results
Virus shedding and replication
Four-week-old pigs carrying an inactive form of the CD1D (CD1D − /−) gene and littermates carrying one inactivated copy (CD1D − /+) were intranasally vaccinated with a modified live virus (MLV) vaccine composed of a recombinant H3N2 A/Swine/Texas/4199–2/1998 (TX98) influenza virus encoding a truncated NS1 protein (TX98 NS1Δ126) (S1 Fig). Pigs were subsequently infected with the heterologous H3N2 A/Swine/Colorado/23619/1999 (CO99) virus at 21 days post-vaccination (DPV) and monitored for 5 days. Additional groups included CD1D − /− and CD1D − / + pigs that were infected without prior vaccination, and unvaccinated CD1D − / + pigs that were not challenged, which were used as a negative control. Of note, CD1D − / + pigs have similar NKT cell frequencies to CD1D intact wildtype pigs [32–35].
After vaccination, both vaccinated groups shed similarly low levels of TX98 NS1Δ126 between 1 and 5 DPV (Fig 1A). After infection, shedding was observed in 2 out of 6 vaccinated CD1D − / + pigs [group 2 (G2)], while no virus was isolated in the vaccinated CD1D − / − pigs (G1) (Fig 1B). Moreover, none of the vaccinated pigs had detectable virus in bronchioalveolar lavage fluid (BALF), nasal turbinates, or trachea at 5 days post-challenge (DPC) (Fig 1C–1E). These results indicate that the MLV vaccine was similarly effective at inhibiting virus replication in NKT cell-deficient and NKT cell-expressing pigs. Unvaccinated CD1D − /− (G3) and CD1D − /+ (G4) pigs shed increasing levels of virus beginning from 1 DPC in nasal swabs and presented high virus titers in nasal turbinates, trachea, and BALF at 5 DPC. While there was no statistical difference between the two genotypes, virus titers tended to be higher in the trachea and nasal turbinates of unvaccinated CD1D − /+ than unvaccinated CD1D − / − pigs. Interestingly, we noticed a similar trend in CD1D − / − pigs infected with pandemic H1N1 A/California/04/2009 virus (pH1N1 CA04), which shed less virus than CD1D − / + pigs across several experiments (S2 Fig). This suggests that, conversely to mice, NKT cells in pigs do not inhibit IAV replication significantly.
(A, B) Virus titers in nasal swabs and frequency of pigs positive for virus shedding at 1, 3, and 5 DPV (A) and at 1–5 DPC (B). (C–E) Virus titers in bronchoalveolar lavage fluid (BALF) (C), nasal turbinates (D), and trachea (E) at 5 DPC. ANOVA and subsequent Tukey’s adjustment was used to determine a statistically significant difference (p < 0.05), and the significance between two groups is indicated by different letters. Data are represented as mean ± SEM of log10 (TCID50/mL or TCID50/g). Symbols represent treatment groups (A, B) or individual pigs (C–E). G1 (n = 6): CD1D − / − vaccinated and challenged; G2 (n = 6): CD1D − / + vaccinated and challenged; G3 (n = 5): CD1D − / − not vaccinated and challenged; G4 (n = 5): CD1D − / + not vaccinated and challenged; G5 (n = 3): CD1D − / + not vaccinated, not challenged.
Pathology
Microscopic changes in the pulmonary parenchyma were scored as described in the Materials and Methods section. Both vaccinated groups (G1 and G2) had overall lower cumulative scores, reflecting less pronounced IAV-associated microscopic lesions (Figs 2A, 3A and 3B). Unvaccinated and challenged groups (G3 and G4) had pronounced airway-centric inflammation compared to vaccinated groups (Figs 2B, 3C and 3D). In general, CD1D − / − pigs tended to have lower histopathology scores than CD1D − / + pigs, although this difference was not statistically significant.
(A) Cumulative histological scores following assessment of the parameters shown in the materials and methods. Histologic alterations occurred at a similar degree between CD1D − /+ and CD1D − / − pigs in the vaccinated and challenged as well as the unvaccinated and challenged groups, with the latter groups showing more severe alterations (reflected by a higher cumulative score). (B) Degree of peribronchiolar/perivascular lymphocytic inflammation. (C, D) Scores for overall CD3+ T cell abundance in the lung (C) and distribution of CD3+ T cells (D), assessed by immunohistochemistry. CD3+ T cell distribution in the pulmonary parenchyma of each pig was classified into two categories: (1) scattered in pulmonary parenchyma with no defined cuffing around airways or (2) airway-centric distribution cuffing small and larger airways. ANOVA and subsequent Tukey’s adjustment was used to determine a statistically significant difference (p < 0.05), and the significance between two groups is indicated by different letters (A, B, and C). Data are represented as mean ± SEM. Symbols represent individual pigs. G1 (n = 6): CD1D − / − vaccinated and challenged; G2 (n = 6): CD1D − / + vaccinated and challenged; G3 (n = 5): CD1D − / − not vaccinated and challenged; G4 (n = 5): CD1D − / + not vaccinated and challenged; G5 (n = 3): CD1D − / + not vaccinated, not challenged.
Histologic alterations in G1 and G2 (A and B) are similar and featured by a mild mononuclear infiltrate delimiting bronchioles (insets) and occasional expansion of the alveolar septa. In G3 and G4 (C and D), the degree of airway-centric inflammation is higher and is additionally characterized by intraluminal exudate composed of degenerate neutrophils and a hyperplastic bronchiolar epithelium with transmigrating lymphocytes and neutrophils (asterisks and insets) and regions of pulmonary atelectasis. CD3+ T cells in CD1D − / + pigs are intensely recruited around airways (F and H) regardless of vaccination status compared to CD1D − / − pigs (E and G). Immunohistochemistry for CD3 (DAB). G1: CD1D − / − vaccinated and challenged; G2: CD1D − / + vaccinated and challenged; G3: CD1D − / − not vaccinated and challenged; G4: CD1D − / + not vaccinated and challenged.
Subsequently, we utilized immunohistochemistry to assess whether NKT cell deficiency affected T cell localization in the lung following IAV vaccination and/or infection. While the overall abundance of CD3+ T cells was similar among the treatment groups (Fig 2C), there was a significantly greater airway-centric distribution of CD3+ T cells in CD1D − / + pigs compared to their CD1D − / − counterparts, regardless of vaccination status (p-value 0.0061; Figs 2D and 3E–3H).
Hemagglutinin (HA)-specific antibody responses
Vaccinated pigs had high TX98-specific hemagglutinin inhibition (HI) titers throughout the vaccination and challenge periods, with no difference between the two pig genotypes (Fig 4A). While a few vaccinated pigs developed low CO99-specific HI titers during the vaccination period, all vaccinated pigs developed high CO99 titers following challenge (Fig 4B). After challenge, unvaccinated pigs developed HI titers against CO99, but not against TX98. There was no significant difference in HI titers between the two pig genotypes.
(A, B) Geometric mean of HI titers against TX98 (A) and CO99 (B) in serum. (C–I) Isotype-specific (IgG, IgG1, IgG2, and IgA) antibody titers against HA in serum (C–G) and BALF (H and I) of vaccinated pigs (G1 and G2). (J) Ratio of HA-specific IgG1/IgG2 titers in serum (J). ANOVA and subsequent Tukey’s adjustment (A and B) and t-test (C–J) were used to determine a statistically significant difference (p < 0.05), and the significance between two groups is indicated by different letters. Data are represented as geometric mean ± geometric SD. Symbols represent individual pigs. G1 (n = 6): CD1D − / − vaccinated and challenged; G2 (n = 6): CD1D − / + vaccinated and challenged; G3 (n = 5): CD1D − / − not vaccinated and challenged; G4 (n = 5): CD1D − / + not vaccinated and challenged; G5 (n = 3): CD1D − / + not vaccinated, not challenged.
Serum and BALF from the two vaccinated groups were measured for HA-specific IgG, high affinity IgG, IgG1, IgG2, and IgA responses at 5 DPC. Assays were performed using a HA protein that shares more than 90% amino acid identities with TX98 and CO99. End-point titers for all antibody isotypes did not differ between genotypes (Fig 4C–4I). However, CD1D − / − pigs had a significantly lower IgG1/IgG2 ratio when compared to CD1D − / + pigs (Fig 4J), suggesting that NKT cell responses affected B cell effector functions.
Flow cytometry and single-cell RNA sequencing
Flow cytometry was used to analyze leukocyte populations in lung tissue and tracheobronchial lymph nodes (TBLNs) at 5 DPC and in blood at −1, 14, 20 and 26 DPV. Vaccinated pigs, but especially the CD1D − / − group (G1), had higher frequencies of CD3+ T cells (Fig 5A) and αβ T cells (Fig 5B) as a proportion of lung lymphocytes compared to unvaccinated pigs. Furthermore, vaccination led to an increase in CD8αβ+ T cells as a proportion of CD3+ T cells in lungs (Fig 5C). However, there were no notable treatment differences in other T cell subsets, natural killer (NK) cells, monocytes, macrophages, dendritic cells, or granulocytes (S1–S6 Tables).
(A) CD3+ T cells as a proportion of lung lymphocytes. (B) αβ T cells as a proportion of lung lymphocytes. (C) CD8αβ+ T cells as a proportion of CD3+ T cells. ANOVA and subsequent Tukey’s adjustment was used to determine a statistically significant difference (p < 0.05), and the significance between two groups is indicated by different letters. Data are represented as mean ± SEM. Symbols represent individual pigs. G1 (n = 6): CD1D − / − vaccinated and challenged; G2 (n = 6): CD1D − / + vaccinated and challenged; G3 (n = 5): CD1D − / − not vaccinated and challenged; G4 (n = 5): CD1D − / + not vaccinated and challenged; G5 (n = 3): CD1D − / + not vaccinated, not challenged.
To obtain more detailed information on the cellular differences between the two pig genotypes, we performed single-cell transcriptomic analysis (scRNAseq) on lung tissue cells from four pigs per vaccinated group at 5 DPC, totaling 69,162 cells. A dimensionality reduction analysis identified 43 clusters by Uniform Manifold Approximation and Projection (UMAP) that we annotated according to a combination of label transfer from previous dataset [35] and established lineage markers (Figs 6A and S3A). The frequencies of CD4+ tissue resident memory T cells (TRMs) (cluster 3), CD2− γδ T cells (cluster 11), cycling B cells (cluster 19), and plasma cells (cluster 20) were significantly higher in CD1D − / − pigs, compared to CD1D − / + pigs (Fig 6B). The frequencies of CD8+ TRMs (clusters 4–6) and cycling T cells (clusters 8–10) were also higher in CD1D − / − pigs, but the difference was not significant. CD1D − / + pigs had higher numbers of resident NK cells (cluster 16) than CD1D − / − pigs, and a tendency for higher frequencies of cells with a mixed monocyte/macrophage phenotype (clusters 21–27) as well as monocytes (clusters 29 and 30).
(A) UMAP visualization of pig lung cells. (B) The average frequency of each cell type is presented for each group. Significance (p < 0.05) was determined by t-test in each cell type. (C) Bar graphs displaying the number of upregulated and downregulated differentially expressed genes (DEGs) in G1 compared to G2 pigs. (D–E) Ingenuity pathway analysis (IPA) of DEGs in lymphocytes (D) and myeloid cells (E). The y-axis shows the top pathways identified in each cell type within the threshold −2.0 < Z > 2.0. Dot size indicates significance [−log10(P value)], and dot color saturation reflects the z-score. G1 (n = 4): CD1D − / − vaccinated and challenged; G2 (n = 4): CD1D − / + vaccinated and challenged.
Next, we compared CD1D − /+ and CD1D − / − pigs for differentially expressed genes (DEGs) within individual cell types (Fig 6C and S1 Data). Overall, we detected substantially more downregulated than upregulated genes in CD1D − / − pigs, compared to CD1D − / + pigs, especially within T cell, B cell, and NK cell populations. An Ingenuity Pathway Analysis (IPA) using DEGs in each cluster revealed that CD1D − / − naïve-like CD8+ T cells, CD4+ TRMs, and plasma cells downregulated a variety of pathways involved in inositol phosphate biosynthesis and degradation (Fig 6D). Inositol phosphates play an integral role in development, proliferation, and differentiation of T and B lymphocytes [36,37]. CD8+ TRMs downregulated pathways related to PI3K/AKT signaling, leukocyte extravasation, integrin signaling, and IL-3 signaling. All lymphocytes, except for cycling T cells, RORC+ γδ T cells, and CD2+ γδ T cells, downregulated the RHO GTPase cycle (S3B Fig), which is a collection of regulatory proteins critical for lymphocyte migration, polarization, adhesion, activation, and differentiation [38–41]. CD1D − / − RORC+ γδ T cells were the only lymphocyte population with mostly upregulated pathways compared to their CD1D − / + counterparts, including Toll-like receptor 3 (TLR3) and TLR4 cascades. CD1D − / − macrophages also had more upregulated than downregulated pathways than CD1D − / + pigs (Fig 6E). These included the class I MHC antigen processing and presentation pathway as well as oxidative phosphorylation, respiratory electron transport, and complex I biogenesis pathways, which are often enriched in macrophages undergoing a type of metabolic reprogramming associated with anti-inflammatory and healing states [42]. Collectively, our findings indicate that NKT cell-derived stimuli influenced a broad range of signaling pathways and cell types in lungs of IAV-infected pigs, some of which might alter the course of the influenza immune response.
Immune receptor profiling
To study the relationship between NKT cell status and immune receptor repertoire diversity, we coupled our scRNAseq dataset with additional assays to enrich αβ TCR and B cell receptor (BCR) chains using primers that target the C regions in mRNA transcripts of αβ TCR and BCR chains and isotypes (S7 Table). Over the eight samples (four vaccinated CD1D − / − pigs in G1 and four vaccinated CD1D − / + pigs in G2), we obtained an average of 187,771,466 reads per αβ TCR library and 206,842,207 reads per BCR library (S2 Data). Across all samples, most TRA- or TRB- positive cells were mapped to T/NK/ILC clusters [1–17]. On average, 95% of these cells had paired TRA + TRB cells (Fig 7A and S2 Data). Only T/NK/ILC cells with annotated paired TRA and TRB chains were used for further analysis (Fig 7B).
(A) UMAP plot showing the alignment of single TRA, single TRB, and paired TRA + TRB cells. (B) UMAP plot of T/NK/ILC cell clusters with paired TRA + TRB, which were used for downstream analysis. (C) Number of cells expressing 1, 2, or ≥3 clones identified by CDR3β sequence. (D) Box plot showing the proportion of cells expressing ≥3 clones across vaccinated groups (G1 and G2). Each dot represents an individual animal. Statistical significance was assessed by t-test. (E) Box plot showing the average length of CDR3β amino acid sequences by vaccinated groups (G1 and G2). Each dot represents the mean CDR3β length of a sample. Statistical significance was assessed by t-test. (F) Proportion of cells expressing the top 5 expanded CDR3β sequences in each animal. (G) Cells expressing the CDR3β sequence CASSSGGSETQYF. (H) UMAP plot showing the alignment of cells expressing single IGK, IGL, IGH, and paired IGL/IGK + IGH chains. (I) UMAP plot of B cells with paired IGL/IGK + IGH, which were used for downstream analysis. (J) Box plot of the proportion of cells expressing ≥3 clones (combined IGL/IGK and IGH CDR3) in vaccinated groups (G1 and G2). Each dot represents an individual animal. Significance was determined by t-test. (K–L) Box plots of the proportion of cells expressing IGHG (K) and IGHA (L) in the vaccinated groups (G1 and G2). Each dot represents an individual animal. G1 (n = 4): CD1D − / − vaccinated and challenged; G2 (n = 4): CD1D − / + vaccinated and challenged.
Next, we examined expanded clonotypes taking advantage of the fact that V(D)J recombination at the TCR and BCR loci can be used as endogenous barcodes to trace T and B cell clonotypes as they expand or transition through different states. The highest concentrations of clonally expanded T cells were among CD4+ TRMs, CD8+ TRMs, and cycling T cells (Fig 7C). CD1D − / − pigs had a higher frequency of expanded clones compared to CD1D − / + pigs (Fig 7D), whereas the CD1D − / + group had shorter average CDR3β lengths than the CD1D − / − group (Fig 7E). The latter observation has been associated with converging TCR motif signatures in a number of diseases [43,44]. Several of the most expanded clones were found in more than one pig, including pigs of both genotypes (Fig 7F). Indeed, the most expanded clonotype (CASSSGGSETQFY) was a vigorously proliferating CD8+ TRM, which was detected in four of the eight samples (Fig 7G). Interestingly, this sequence differs by a single amino acid from a curated human TCR CDR3β sequence (CASSSGESETQYF) in the IEDB database (https://www.iedb.org/), that recognizes the IAV Matrix protein 1 epitope GILGFVFTL when presented by human HLA-A*0201 [45]. It is notable that several expanded clones in this study were identified among expanded clones from a prior study which used lung samples collected from CD1D − /− and CD1D − / + pigs following infection with pH1N1 CA04 and subsequent re-challenge with a heterologous H1N1 virus [35] (S8 Table), indicating their potential as IAV-reactive clonotypes.
A similar analysis of BCR chains was performed, with an average of 99% of paired IGK/IGL + IGH cells mapping to B cells (Fig 7H–7I, S2 Data). We found that CD1D − / − pigs also had a higher frequency of expanded clones compared to CD1D − / + pigs (Fig 7J). Additionally, CD1D − / − B cells expressed a higher proportion of IGHG (Fig 7K) and a lower proportion of IGHA (Fig 7L) heavy chain transcripts compared to CD1D − / + B cells. Unlike in T cells, we did not identify expanded B cell clonotypes in more than one sample, due to the high diversity of heavy chain CDR3 sequences (S4 Fig). Together, these findings indicate that NKT cell-derived stimuli influenced the immune receptor repertoire of the lung.
Finally, we profiled γ and δ TCR chain expression using primers that target the C regions of each chain (S7 Table). Assembled V(D)J sequences were blasted against the international ImMunoGeneTics (IMGT) germline TRGV, TRGJ, and TRDJ databases [46]. Because Vδ genes are not annotated in IMGT, Vδ sequences were assigned according to pig TRAV/TRDV sequences from our previous publication [47] (S2 Data). Over the eight samples (four vaccinated CD1D − / − pigs in G1 and four vaccinated CD1D − / + pigs in G2), we obtained an average of 206,307,805 reads per TCR library with 70% of paired γ + δ cells mapping to γδ T cell clusters (clusters 11–13). An additional 21% mapped to the CD8+ TRM cluster (cluster 4), which we found contained a mixture of CD8 ⁺ αβ and γδ T cells (Fig 8A). Only T cells with paired, productive γ and δ TCR chains were used for further analysis (Fig 8B). As expected, the γ and δ TCR repertoire was comprised of a limited set of VJ and C segments (Fig 8C). We found that CD8+ TRM, CD2− γδ, and RORC+ γδ subsets had high frequencies of cells with identical CDR3γ sequences, whereas CD2+ γδ T cells had a low proportion (Fig 8D). Notably, the five most common CDR3γ sequence, which were shared across samples, comprised a high fraction of each pig’s total sequences, ranging from between 20 and 42% (Fig 8E). These and most other highly prevalent CDR3γ sequences were germline-encoded (no addition of non-template nucleotides). In terms of γ chain V, J, and C segment usage, CD2+ and CD2− subsets had the highest and lowest diversity, respectively (S5A–S5C Fig). All four subsets, but especially CD2− and RORC+ γδ T cells were dominated by TRGV3, TRGV7, TRGJ5, and TRGC5, which are all from the same TRG locus cassette (TRGV3/7/10-TRGJ5-TRGC5) (Fig 8F–8H) [48]. In contrast, segments from remaining three cassettes (TRGV6-TRGJ6-TRGC6, TRGV12–1-TRGJ3-TRGC3, and TRGV12–2-TRGJ4-TRGC4) were almost exclusively found in CD8+ TRM and CD2+ γδ T cell clusters. We also observed that CDR3γ sequences in the CD2− subset were longer and less variable in length than in the other γδ subsets (S5D Fig). As regards the δ chain, we found that the CD2+, CD2−, and RORC+ γδ subsets had greater V segment diversity than CD8+ TRM-resident γδ T cells (S5E–S5H Fig). We next compared CD1D − /− and CD1D − / + pigs to assess if NKT cell status affected the pulmonary γδ TCR repertoire. CD1D − / + pigs tended to have a higher frequency of cells with identical CDR3γ sequences and lower repertoire diversity compared to CD1D − / − pigs (Figs 8I and S5I). Other differences included that the germline CAGWNYSSRWIKIF CDR3γ sequence was more prevalent in CD1D − / + pigs and that CD1D − / − pigs exhibited greater overlap in CDR3γ sequences and more convergent V, J, and C segment usage (Figs 8E and S5J–S5K). These observations suggest that pigs lacking NKT cells have a more homogeneous γδ TCR repertoire than NKT cell-expressing pigs. However, additional studies are needed to confirm this.
(A) UMAP plot showing the alignment of single TRG, single TRD, and paired TRG + TRD cells. (B) UMAP plot of cells with paired TRG + TRD, which were used for downstream analysis. (C) Sankey-plot showing the number of cells expressing TRG and TRD VJC gene segments, as well as their recombination patterns. (D) Number of cells expressing 1, 2, or ≥3 clones identified by CDR3γ sequence. (E) Proportion of cells expressing the top 5 expanded CDR3γ sequences in each animal. (F–H) Proportion of cells expressing TRGV (F), TRGJ (G), and TRGC (H) segments by γδ T cell subtype. (I) Box plot of the proportion of cells expressing ≥3 clones in G1 and G2 groups. Each dot represents an individual animal. G1 (n = 4): CD1D − / − vaccinated and challenged; G2 (n = 4): CD1D − / + vaccinated and challenged.
NKT cells modulate virus-specific T cell kinetics
Finally, interferon-γ (IFN-γ) ELISpot assays were performed to quantify virus-reactive cells in peripheral blood mononuclear cells (PBMCs) and lung cell suspensions. Unvaccinated pigs did not develop measurable TX98- or CO99-specific IFN-γ producing PBMCs until 5 DPC, when they were detected at low levels. On the other hand, both vaccinated groups developed TX98- and CO99-reactive cells by 14 DPV, and their concentration increased substantially after challenge (Fig 9A and 9B). Interestingly, T cell kinetics differed by pig genotype; at 14 DPV, vaccinated CD1D − / + pigs had more TX98- and CO99-reactive PBMCs than CD1D − / − pigs; at 20 DPV, the two groups were comparable; but at 5 DPC, CD1D − / − pigs had significantly more virus-reactive cells than CD1D − / + pigs. The same pattern was observed in lung cells at 5 DPC (Fig 9C and 9D). We also analyzed PBMCs using an IL-2 ELISpot assay, which presented similar results to the IFN-γ ELISpot assay, except that there was no significant difference between the two genotypes at 14 DPV (Fig 9E and 9F). Collectively, these results indicate that NKT cells alter the kinetics of the cellular response, with virus-reactive cells in CD1D − / − pigs taking longer to develop but eventually reaching higher concentrations than in CD1D − / + pigs. This agrees with our single-cell data showing that CD1D − / − lung samples had higher frequencies of expanded αβ T cell clones than CD1D − / + lungs (Fig 7D).
(A, B) Interferon-γ (IFN-γ) production by PBMCs collected at −1, 14, 20, and 26 DPV (5 DPC) after incubation with live TX98 (A) and CO99 (B) virus. (C, D) IFN-γ production by lung cells collected at 5 DPC after incubation with live TX98 (C) and CO99 (D) virus. (E, F) Interleukin-2 (IL-2) production by the same PBMCs after incubation with live TX98 (E) and CO99 (F) virus. ANOVA and subsequent Tukey’s adjustment was used to determine a statistically significant difference (p < 0.05), and the significance between two groups is indicated by different letters. Data are represented as mean ± SEM. Symbols represent individual pigs. G1 (n = 6): CD1D − / − vaccinated and challenged; G2 (n = 6): CD1D − / + vaccinated and challenged; G3 (n = 5): CD1D − / − not vaccinated and challenged; G4 (n = 5): CD1D − / + not vaccinated and challenged; G5 (n = 3): CD1D − / + not vaccinated, not challenged.
Discussion
The current work assessed the contribution of pig NKT cells to immunity induced by a MLV vaccine with a truncated NS1 protein, which in swine generally affords robust protection against heterologous IAV infection. Our premise was based on previous reports that NKT cells function as a type of universal T helper cells enhancing both humoral and cellular immune responses, especially in mucosal tissues like the lower respiratory tract where they are enriched [4]. This is supported by the fact that compared to standard mice, NKT cell-deficient mice develop weaker cellular and humoral responses after IAV immunization [10,11]. While swine possess the NKT cell-CD1d system, the concentration of NKT cells in most pigs is considerably lower than in most inbred mouse strains [33,49]. Moreover, the functional diversity of pig NKT cells differs from the NKT0/1/2/17 subset differentiation paradigm established in mice [50]. Nevertheless, porcine NKT cells react strongly to α-GalCer in vitro and in vivo [33,49,51], and pigs co-administered α-GalCer in combination with inactivated IAV vaccines develop greater humoral and cellular immune responses than pigs administered vaccine alone [3]. In fact, α-GalCer is capable of triggering vaccine-associated enhanced respiratory disease (VAERD) in pigs, an immunopathological condition where vaccination causes enhanced lung disease rather than protection after a subsequent infection [52].
The current work found no evidence that vaccination was less effective at decreasing viral clearance or reducing pulmonary pathology in NKT cell-deficient pigs compared to NKT cell-intact pigs. This agrees with at least one previous mouse study which found no difference in virus titers, pulmonary pathology, or mortality between IAV-infected CD1d-deficient and standard mice that had been previously immunized with a sublethal dose of live virus [13].
In terms of immunological parameters, CD1D − /− and CD1D − / + pigs developed similar antigen-specific humoral responses, except that CD1D − / + pigs had a higher HA-specific IgG1/IgG2 ratio. This resembles prior findings in the mouse model showing that NKT cell activation skews the humoral response towards a Th2-driven IgG1 response [53]. While the mouse IgG subclass-cytokine paradigm may not directly apply to pigs, our results suggest that NKT cells influenced the underlying T helper response.
The impact on cellular immune responses was more pronounced, with virus-specific cells in CD1D − / − pigs taking longer to develop but eventually surpassing CD1D − / + pigs, in both blood and lung tissue. This observation may be related to the fact that, because NKT cells are capable of sequentially secreting pro- and anti-inflammatory cytokines, they often play Janus-like opposing roles in different phases of the immune response [54]. In this regard, our observations support that NKT cells play a stimulatory role during the initial induction of virus-reactive T cells following vaccination but then switch to a suppressive role once pigs became infected with virulent live virus, perhaps as a mechanism to prevent excess inflammation. Our observation agrees with a prior study which showed that virus-specific CD8+ T cell responses were significantly greater in CD1d KO compared to standard mice after vaccination with an inactivated IAV vaccine [12]. The authors attribute this suppression to NKT cell-dependent IDO expression. We found it interesting that NKT cell status seemed to affect the distribution of T cells in infected pig lungs; without them, CD3+ T cells did not accumulate around airways as they did in NKT cell-sufficient pigs. This observation is reminiscent of a previous study in which pigs vaccinated with α-GalCer and an inactivated IAV vaccine had a higher density of intra-epithelial CD3+ T cells associated with the bronchiolar epithelium than did vaccinated pigs that did not receive α-GalCer [52]. Together, these results indicate that NKT cells play a substantial role in coordinating cellular responses following IAV encounter, including diminishing the amount of virus-specific T cells that accumulate around smaller-caliber airways in the infected lung.
Our single-cell transcriptomics analysis revealed that ablating NKT cells changed the cellular composition of the lung at 5 DPC, including that CD1D − / − pigs were enriched for TRMs, consistent with the ELISpot and flow cytometry results. It also revealed that NKT cell deletion downregulated a substantial number of genes and pathways in TRMs and other lymphocyte populations, several of which are integral to lymphocyte trafficking, development, proliferation, differentiation, and effector functions. While this seems contradictory given that CD1D − / − pigs had higher TRM levels than CD1D − / + pigs, lymphocyte homeostasis is governed by a balance of activation and inhibitory signals. Thus, our results may indicate negative feedback mechanisms involving TCR/BCR signaling, inhibitory receptors, and cytokines following activation in CD1D − / − lymphocytes. Also notable is that CD1D − / − lung macrophages and MonoMac cells upregulated pathways associated with anti-inflammatory responses and tissue repair. This suggests that NKT cells activated in response to influenza vaccination/infection play a role in controlling the functional program of macrophages. This is relevant as lung macrophages are essential players in shaping the outcome of immune responses and disease outcomes in viral respiratory infections [55,56].
Our single-cell TCR and BCR sequencing analysis found that CD1D − / − pigs had higher numbers of expanded αβ T cell clones in their lungs, which agrees with our ELISpot assays showing more virus-specific T cells in CD1D − /− than CD1D − / + pigs after infection. Most of the expanded clones were within CD4+ TRM and CD8+ TRM clusters, consistent with the notion that these cells contain antigen specific T cells capable of rapidly responding to IAV infection. Interestingly, several of our most expanded sequences aligned exactly to CDR3β sequences from a prior study where we performed single cell TCR sequencing on lung T cells from CD1D − /− than CD1D − / + pigs sequentially infected with two heterologous H1N1 IAVs [35]. Thus, we may have identified clonotypes capable of recognizing the same conserved IAV antigens. Among the most expanded clonotypes, we identified a clone with a CDR3β sequence almost identical to a human motif that recognizes an immunodominant epitope from the Matrix protein 1 [57,58]. This may arise because peptide binding motifs of some common swine leukocyte antigen (SLA) molecules partly overlap with the binding motifs of human HLA molecules [59].
Our scBCRseq analysis found that CD1D − / − pigs also had higher numbers of expanded lung B cell clones compared to CD1D − / + pigs, indicating that NKT cells may also play a role in modulating B cell expansion. Additionally, there was a shift in heavy chain usage, with CD1D − / − B cells favoring IgG and CD1D − / + B cells favoring IgA transcripts. This could be related to the cognate or non-cognate help that NKT cells are known to provide to B cells, which can affect immunoglobulin heavy chain usage [6–9].
Our new single-cell γδ TCR assay revealed several interesting findings. As in humans [60], there was greater clonal diversity in the pool of rearranged TRD genes compared to TRG genes. Furthermore, the TRG repertoire was comprised of a high proportion of invariant germline-encoded CDR3γ sequences that were public, whereas the TRD repertoire was diverse. We also found that the Th17-associated CD2− and RORC+ subsets had lower diversity in γ chain V-J and C segment usage and CDR3γ sequences compared to the CD2+ subset. Moreover, both CD2− and RORC+ subsets were dominated by TRGV3, TRGV7, TRGJ5, and TRGC5 segments, suggesting that the two populations are related. The CDR3γ sequences of CD2− γδ T cells were more uniform in length due to the more restricted V-J and C segment usage but longer than the other subsets. γδ T cells within the CD8+ TRM cluster had a TRG VJC segment usage pattern similar to CD2+ γδ T cells. However, they were enriched in memory- and cytotoxicity-associated genes. The partial overlap in transcription patterns between γδ and αβ cells in CD8+ TRMs supports previous findings in human where αβ CD8+ TRMs in lung express innate-like features that underlie their sentinel function [61]. Regarding the influence of NKT cells, we found some indication that CD1D − /− and CD1D − / + pigs had different γδ TCR repertoires. However, additional research is needed to confirm this.
Another point of interest was the response of unvaccinated naïve CD1D − /− and CD1D − / + pigs to IAV infection since several studies have shown that NKT cells contribute to early-innate responses in mice that inhibit IAV replication and protect against disease [28–31]. Although not significant, we found that virus titers in CD1D − / + pigs tended to be higher than CD1D − / − pigs, indicating that in pigs, NKT cell responses do not inhibit, and may even support, virus replication. Indeed, we have observed, in several prior IAV challenge studies using pH1N1 CA04 strain, that virus shedding is somewhat delayed in naïve CD1D − / − compared to CD1D − / + pigs (S2 Fig). This discrepancy raises a cautionary note about interpreting the results of NKT cell studies conducted in animal models since we are not yet certain which model best represents human NKT cell biology.
In conclusion, we found that genetically ablating NKT cells did not substantially alter virus load or pulmonary pathology following IAV infection in pigs, regardless of their vaccination status. Nonetheless, removing NKT cells significantly altered the nature of the adaptive immune response, particularly as regards to the dynamics of virus-specific T cell accumulation, the localization of T cells in the lung after infection, and widespread transcriptional and immune receptor repertoire changes in multiple cell types. Future studies are needed to identify the mechanism(s) underpinning these NKT cell-mediated differences, which may include a loss in direct NKT-T cell interactions or altered cytokine responses and antigen presenting cell licensing [3]. Significantly, our data support that NKT cells help to constrain the accumulation of virus-specific T cells in the infected lung, perhaps as a mechanism to prevent excessive pulmonary inflammation. It is therefore reasonable to assume that, although the changes we observed did not affect disease or virus replication in the current investigation, they are likely to be of importance in other settings, such as TRM persistence in the respiratory tract and immunity against heterosubtypic viruses. The same may also be true in humans and therefore warrants further study.
Materials and methods
Ethics statement
The studies approved by Kansas State University’s Institutional Animal Care and Use Committee (IACUC-4708) and Institutional Biosafety Committee (IBC-1757).
Virus and vaccine preparation
The MLV vaccine was generated by reverse genetics from H3N2 A/Swine/Texas/4199–2/1998 (TX98) influenza virus as described previously [62]. Briefly, the MLV (TX98 NS1Δ126) encodes a truncated NS1 protein with four stop codons introduced after 126 reading codons, resulting in a 3’ truncation of the wild-type NS1 protein from 219 to 126 amino acids. The challenge virus, H3N2 A/Swine/Colorado/23619/1999 (CO99), has previously been described [63]. Both the vaccine and challenge viruses were propagated on MDCK cells in IAV infection media (DMEM supplemented with 0.3% bovine serum albumin, 1% MEM vitamin, 1% antibiotic-antimycotic solution and 1µg/mL of TPCK-treated trypsin).
Pigs
The National Swine Resource and Research Center (NSRRC) at University of Missouri produced piglets that were homozygous (CD1D − /−) and heterozygous (CD1D − /+) for a 1,598 bp deletion in the CD1D gene, which has been described [32,64]. This CD1D breeding herd is on a commercial Large White crossbred background and maintained under specific pathogen free conditions. The CD1D genotypes of pigs were determined by PCR as previously described (S6 Fig) [32,64].
Experimental design
Eleven CD1D − /− and 14 CD1D − / + pigs were transferred to biocontainment rooms at 4 weeks of age after being confirmed seronegative for H1 and H3 antibodies by a hemagglutination inhibition assay, as previously described [63]. After a 5-day acclimatization period, the pigs were assigned to 1 of 5 treatment groups. On day 0, 6 CD1D − /− and 6 CD1D − / + pigs in group G1 and G2, respectively, were intranasally vaccinated with 106 median (50%) of tissue culture infectious dose (TCID50) of TX98 NS1Δ126 using an atomization device (MAD Nasal, Teleflex, Morrisville, NC, USA). At the same time, 5 CD1D − /− and 5 CD1D − / + pigs in G3 and G4, respectively, were left unvaccinated. G5, which served as a control, contained 3 CD1D − / + pigs that were left unvaccinated and subjected to postmortem examination at 17 DPV after sedation with tiletamine–zolazepam (Telazol; 4.4 mg/kg of body weight) and xylazine (2.2 mg/kg) and euthanasia with pentobarbital sodium IV injections (100 mg/kg of body weight). At 21 DPV (0 DPC), G1–4 were intratracheally challenged with 106 TCID50 of CO99 as previously described and monitored for 5 days [63]. Peripheral blood was collected from the jugular vein into heparin-coated or serum collection vacutainer tubes (BD Biosciences, San Jose, CA, USA) at −1, 14, 20, and 26 DPV. In order to isolate white blood cells (WBC), peripheral blood was treated with an ammonium chloride-based lysis buffer to remove red blood cells (RBC) [33,65]. PBMCs were isolated from blood samples by density gradient centrifugation using Ficoll-Paque PREMIUM (GE Healthcare BioSciences Corp., Uppsala, Sweden) and SepMate tubes (STEMCELL Technologies, Cambridge, MA, USA). Cells were cryopreserved in liquid nitrogen until use. Nasal swabs were collected at −1, 1, 3, and 5 DPV from vaccinated groups (G1 and G2) and 20, and 22–26 DPV (−1 and 1–5 DPC) from infected pigs (G1–4) in 2 mL DMEM (Corning, Corning, NY) supplemented with 1 × antibiotic-antimycotic (Gibco Life Technologies, Carlsbad, CA), filtered using a 0.45 μm syringe filter (TPP, Trasadingen, Switzerland) and stored at −80 °C. At 5 DPC (26 DPV), infected pigs (G1–4) were euthanized as described above. During necropsy, BALF was collected in 50mL of DMEM supplemented with antibiotic-antimycotic (Gibco Life Technologies, Carlsbad, CA), and tissue samples, including nasal turbinates, trachea, lung, and TBLNs, were collected for virological, immunological, and pathological evaluation. Lung cells were isolated from approximately 3 g of cranial, middle and caudal lung lobes (1 g per each lobe) as previously described with minor modifications [63]: lung tissues were enzymatically digested with 2.5 mg/mL Liberase TL (Roche), 10 mg/mL DNase (Sigma), and 50 mg/mL collagenase (Worthington) in DMEM at 37°C for 30 min and mechanically dissociated using a gentleMACS Octo Dissociator (Miltenyi Biotec). Single cells from TBLN were isolated by mechanical dissociation using a gentleMACS Octo Dissociator and passed through a 100 µm cell strainer (Miltenyi Biotec). Cells were immediately cryopreserved in freezing media in temperature-controlled freezing containers at 1–2 × 107 cells per/mL and stored in liquid nitrogen until used for flow cytometry, ELISpot, or single cell transcriptomics.
Virus titration
Nasal turbinates, trachea, and lung tissue were mechanically homogenized in DMEM using a TissueLyser II (Qiagen, Germantown, MD) and stainless-steel beads. The resulting 10% (w/v) tissue homogenates were filtered through a 0.45 μm syringe filter (TPP, Trasadingen, Switzerland). A 10-fold serial dilution of nasal swab, BALF, and tissue homogenate were prepared in IAV infection media and transferred on pre-washed, confluent MDCK cells in a 96-well plate. On day 2, the plate was fixed, incubated with mouse anti-NP antibodies (HB65 hybridoma supernatant; ATCC, Manassas, VA, USA), and subsequently incubated with goat anti-mouse IgG antibodies conjugated with Alexa Flour 488 (Invitrogen, Carlsbad, CA, USA). The virus-infected cells were visualized on an EVOS FL microscope. Viral titers were determined by the Reed-Muench method [66] and expressed as log transformed values of TCID50/mL or TCID50/g, as appropriate, according to our prior publications [63,65].
Antibody detection and quantification
Influenza-specific antibodies in serum and BALF were determined by HI and ELISA assays. The HI assay was performed as previously described [65]. Briefly, serum was treated with receptor-destroying enzyme II according to the manufacturer’s instructions. Then, samples were serially diluted two-fold, starting 1:10 dilution, and incubated with wild-type TX98 and CO99, followed by incubation with 0.5% washed chicken RBCs as previously described [63,65]. The highest sample dilution that inhibited virus-induced RBC hemagglutination is presented.
HA-specific IgG, IgG1, IgG2a, and IgA antibody responses were measured in serum and BALF using an in-house ELISA. Briefly, 96-well ELISA plates were coated overnight with 2 µg/mL of H3 protein from A/California/07/2004 H3N2 (Sino biologicals, Beijing, China) dissolved in coating buffer. The amino acid sequence identities of this antigen to the HA proteins of TX98 and CO99 are 91.5% and 94.9%, respectively. After H3 antigen solution was removed, plates were washed and incubated with blocking buffer (3% goat serum, 0.5% skim milk, and 0.1% Tween 20 in PBS) at room temperature for 1 h. Plates were washed and incubated for 2 h with serum or BALF serially diluted two-fold in blocking buffer, starting from 1:100 dilution for serum and 1:10 dilution for BALF. Before preparing serial dilutions, BALF was incubated with the equal amount of 10 mM DTT for 1 h at 37°C for mucus disruption. To determine high-affinity IgG titer in serum, low-affinity antibodies were removed after incubation of 6 M urea for 10 minutes at room temperature. Plates were washed and incubated for 1 h at room temperature with 100 µL of blocking buffer containing the following isotype-specific secondary antibodies: HRP-conjugated anti-pig IgG (Invitrogen, Carlsbad, CA, USA; 1:40,000 dilution for both serum and BALF), HRP-conjugated anti-pig IgA (Invitrogen, Carlsbad, CA, USA; 1:20,000 dilution for serum and 1:40,000 for BALF), anti-pig IgG1 (Bio-Rad, Hercules, CA, USA; 1:1000 dilution), and anti-pig IgG2 (Bio-Rad, Hercules, CA, USA; 1:5,000 dilution). For the IgG1 and IgG2 ELISAs, plates were further incubated with an HRP-conjugated goat anti-mouse IgG (H + L) antibody (Invitrogen, Carlsbad, CA, USA: 1:20,000 dilution) for 1 hour. Plates were washed and incubated with 3,3’,5,5’ tetramethylbenzidine solution (Thermo Scientific, Rockford, IL, USA) for 15 min before adding stop solution (Abcam, Cambridge, MA, USA) and read at 450 nm using an ELISA plate reader. The detection cut-off was calculated as the average optical density (O.D.) + 3 × standard deviations of the three G5 control pigs. ELISA titers are represented as the reciprocal of the highest serum dilution above the cut-off value.
Flow cytometry
After thawing, approximately 1–2 million WBC, TBLN, and lung cells were stained using our previously described protocols, with minor modifications [63]. Briefly, cell suspensions were incubated with a viability dye (LIVE/DEAD Fixable Near-IR Dead Cell Stain Kit, Invitrogen, Carlsbad, CA, USA), followed by Fc blocking with rat IgG (Sigma-Aldrich, St. Louis, MO, USA), and then a panel of monoclonal antibodies to identify immune cell populations. T cell and NK cell subsets were identified using antibodies specific for CD3ε (BB23-8E6-8C8; BD Biosciences, Franklin Lakes, NJ, USA), CD4 (74-12-4; Southern Biotech, Birmingham, AL, USA), CD8α (76-2-11; Southern Biotech), CD8β (PPT23; Bio-Rad, Hercules, CA, USA), TCRδ (PGBL22A; WSU Monoclonal Antibody Center, Pullman WA, USA), CD16 (G7; BD Biosciences, Franklin Lakes, NJ, USA), and CD11b (M1/70; BioLegend, San Diego, CA, USA). NKT cells were identified using unloaded and PBS57-loaded mouse CD1d tetramers provided by the National Institutes of Health Tetramer Core Facility. Monocytes, macrophages, and granulocytes were distinguished using antibodies against CD14 (MIL2; Bio-Rad, Hercules, CA, USA), CD16, CD163 (2A10/11; Bio-Rad, Hercules, CA, USA), CD172a (74–22-15A; BD Biosciences, Franklin Lakes, NJ, USA), CD11b, and MHC class II (H42A; WSU Monoclonal Antibody Center). After staining, cells were fixed using the BD Cytofix/Cytoperm kit (BD Biosciences) and acquired on a BD LSRFortessa X-20 flow cytometer with FACSDiva software (version 9.2, BD Biosciences). Fluorescence-minus-one controls were used to determine positive and negative populations. Data was analyzed using FlowJo software (version 10.10.0, Treestar, Palo Alto, CA, USA). Leukocyte populations were identified using a previously published gating strategy [63].
ELISpot assays
After thawing, PBMCs and lung cells were resuspended in RPMI supplemented with 10% FBS, 1% antibiotic-antimycotic, and 55 μM 2-mercaptoethanol (Gibco, Waltham, MA, USA) and rested for at least 1 h. For the IFN-γ ELISpot assay, PBMCs and lung cells were respectively plated at 2.5 × 105 and 2 × 105 cells per well in 96-well MultiScreen IP HTS plates (Millipore, Billerica, MA, USA) pre-coated with anti-IFN-γ (P2G10, BD Biosciences, Franklin Lakes, NJ, USA). The cells were incubated for 48 h with 0.1 MOI of wild-type TX98 and CO99 virus or virus-free MDCK supernatant. Plates were then developed with a biotin-conjugated anti-IFN-γ mAb (P2C11, BD Biosciences, Franklin Lakes, NJ, USA), streptavidin-horseradish peroxidase (BD Biosciences, Franklin Lakes, NJ, USA), and 3-amino-9-ethylcarbazole (AEC) substrate (BD Biosciences, Franklin Lakes, NJ, USA), according to the manufacturer’s instructions. A similar HRP-based IL-2 ELISpot assay was performed using 2.5 × 105 PBMCs per well stimulated with 0.1 MOI of wild-type TX98 and CO99 virus or virus-free MDCK supernatant, as per the manufacturer’s instructions (Mabtech, Stockholm, Sweden). The number of spots in each well were counted using an AID iSpot EliSpot FluoroSpot Reader with AID EliSpot Software Version 7.0 (Advanced Imaging Devices GmbH, Strassberg, Germany).
Gross pathology, histopathology, and immunohistochemistry
At necropsy, the apical and cardiac lung lobes were fixed in 10% neutral buffered formalin, processed and embedded in paraffin, and stained with hematoxylin and eosin (H&E) for histological evaluation following standard procedures. At least two sections of lung per animal were blindly scored for histological lesions according to our previous publication, with minor modifications [67]: (i) epithelial necrosis, attenuation, disruption or hyperplasia (0–4), (ii) airway exudate (0–4), (iii) percentage of airways with inflammation (0–4), (iv) peribronchiolar and perivascular lymphocytic inflammation (0–3), (v) alveolar exudate (0–3), and (vi) alveolar septal inflammation (0–4).
For abundance and distribution of CD3+ T cells in the pulmonary parenchyma, 4-micron formalin-fixed, paraffin-embedded (FFPE) tissue sections were subjected to immunohistochemistry for CD3 using the automated BOND RXm platform and the Polymer Refine Detection kit (Leica Biosystems, Buffalo Grove, IL). Following automated deparaffinization, FFPE tissue sections were subjected to automated heat-induced epitope retrieval (HIER) using a ready-to-use citrate-based retrieval solution (pH 6.0, Leica Biosystems) at 100 °C for 20 min. Subsequently, tissue sections were incubated with the primary antibody (rabbit polyclonal anti-human CD3 [A0452, Dako, Carpinteria, CA] diluted 1:300 in Primary Antibody diluent [Leica Biosystems]) for 30 min at ambient temperature, followed by a polymer-labeled goat anti-rabbit IgG coupled with HRP (8 min). 3’,3’ diaminobenzidine (DAB) was used as the chromogen (10 min), and counterstaining was performed with hematoxylin for 5 min. Slides were dried in a 60°C oven for 30 min and mounted with a permanent mounting medium (Micromount, Leica Biosystems). A pathologist blinded to the study design evaluated abundance of CD3+ T cells (0, none; 1, minimal numbers; 2, mild numbers; 3, moderate numbers; 4, high numbers). In addition, CD3+ T cell distribution in the pulmonary parenchyma of each pig was classified into two categories: (1) scattered in pulmonary parenchyma with no defined cuffing around airways or (2) airway-centric distribution of cuffing around small and larger airways.
Single-cell processing
Thawed lung cells were used to generate libraries as previously described [35]. Gene expression libraries were prepared using the Chromium Next GEM Single Cell 5′ Kit v2 (10 × Genomics, Pleasanton, CA) according to the manufacturer’s instructions. V(D)J libraries were enriched for αβ TCR and BCR transcripts with pig-specific primers, as previously described [35]. We also included new porcine-specific γ and δ chain TCR primers (S7 Table), which were designed and run according to our previously developed single-cell αβ TCR and BCR assays [35]. One of these primers was adapted from a prior publication [48].
Single-cell RNAseq (scRNAseq) analysis
The Sscrofa 11.1 genome assembly was used to align sequencing reads to generate gene matrix data by Cell Ranger (v8.0.0). Each dataset was pre-processed by removing genes expressed in <3 cells, excluding cells with aberrantly high or low gene counts and high mitochondrial gene expression. Afterwards, batch correction and clustering analyses were performed using Seurat (v.5.3.0) [68]. Briefly, transcript counts were log normalized, and highly variable genes were selected for dimensionality reduction analysis. The IntegrateLayers function was used to align cells across multiple samples by correcting batch effects while preserving biological variability, using the CCA integration method. Then, the clustering analysis workflow was performed using FindNeighbours, FindClusters, and RunUMAP functions. The FindTransferAnchors and TransferData functions were used to infer the cell types from our previous datasets [35], and further validated based on the expression of known cell type markers. The differentially expressed genes (DEGs) between treatments in each cluster were computed using the FindMarkers function with the Wilcoxon test. The pathway enrichment analysis was performed using Ingenuity Pathway Analysis (IPA) (QIAGEN Inc.). The Core Analysis function was used to identify canonical pathways significantly associated with the DEGs using a p-value threshold of 0.05.
Single-cell V(D)J data analysis
Single-cell αβ and γδ TCR and BCR V(D)J sequencing reads were assembled into contigs using the cellranger vdj (10 × Genomics) pipeline in de novo mode. To identify the V(D)J chains, we searched assembled contigs against inner-enrichment primers using the usearch_global command. The TCR β, γ, and BCR V(D)J chains were respectively mapped to the pig TRB, TRG, and IG reference sequences in IMGT using the IMGT/V-QUEST [69]. Using MMseqs2 (v17.b804f) [70], primer-matched TCR α TRAJ and TCR δ TRDJ segments were further mapped to the pig TRAJ and TRDJ IMGT genome database, respectively. TRAV and TRDV segments were annotated based on TRAV/TRDV sequences deposited in GenBank [71], which we previously named according to their similarity to human TRAV genes [51]. Single cells with a single unique annotated contig in any of the TCR αβ, γδ, or BCR IGH, IGL, and IGK chains were retained for downstream analysis, while those with multiple contigs per chain were excluded. The filtered annotated contigs were then aligned to their corresponding gene expression profiles. Scirpy (v0.12.0) was used to analyze CDR3 clonal expansion, CDR3 amino acid sequence length, and V(D)J segment usage analyses across samples [72]. In addition, TCR β-chain CDR3 amino acid sequences were analyzed using TCRmatch (http://tools.iedb.org/tcrmatch/) for antigen prediction. The tool compares the input β-chain CDR3 sequences against those in the Immune Epitope Database (IEDB), identifies similar sequences, and retrieves the corresponding epitopes and antigens annotated in the IEDB [73]. CDR3 clonal and V(D)J segment diversity was quantified using the Alakazam package (v1.3.0) [74]. Diversity was assessed across a range of diversity orders (q) based on the Hill diversity framework, with particular emphasis on the exponential Shannon-Weiner index (q = 1) to evaluate V(D)J segment diversity across different cell types [75].
Statistics
The virus titers were log-transformed for statistical analysis. Analysis of variance (ANOVA) and subsequent Tukey’s adjustment were performed for virus titers, pathological scores, HI titers, ELISpot, and flow cytometry, and the t-test was used for ELISA, cell frequencies from scRNA-seq analysis, as well as for clonal expansion, CDR3 length, and antibody isotypes derived from scTCR/BCR-seq analyses, using GraphPad Prism 10 (Boston, MA, USA). CD3+ T cell distribution was analyzed using a nominal logistic regression model in JMP Statistical Discovery (SAS, Cary, NC).
Supporting information
S1 Fig. Experimental design.
Eleven CD1D − /− and 14 CD1D − / + pigs were assigned into five groups: G1 (n = 6): CD1D − / − vaccinated and challenged; G2 (n = 6): CD1D − / + vaccinated and challenged; G3 (n = 5): CD1D − / − not vaccinated and challenged; G4 (n = 5): CD1D − / + not vaccinated and challenged; G5 (n = 3): CD1D − / + not vaccinated, not challenged. G1 and G2 were intranasally vaccinated with TX98 NS1Δ126 H3N2 at 0 day post-vaccination (DPV), while G3, G4, and G5 were left unvaccinated. At 17 DPV, control pigs in G5 were humanly euthanized for post-mortem and sample collection. G1–4 were intratracheally challenged with CO99 H3N2 at 21 DPV [0 days post-challenge (0 DPC)] and monitored for 5 days. Nasal swab and blood were collected throughout the study. Created in BioRender. Kwon, T. (2026) https://BioRender.com/htwvznn.
https://doi.org/10.1371/journal.ppat.1014094.s001
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S2 Fig. Virus shedding is delayed in naïve CD1D − / − compared to CD1D − / + pigs.
(A–G) Viral titers in nasal swabs from seven prior experiments where CD1D − /− and CD1D − / + pigs between 4 and 6 weeks of age were intratracheally infected with pandemic H1N1 A/California/04/2009 influenza A virus. Each line represents an individual pig. (H) Mean viral titers across all experiments are presented as mean ± SEM. To minimize batch effects, titers were log₁₀-transformed and normalized by centering each batch to the overall mean (adjusted value = raw − batch mean + grand mean). The adjusted values were used for statistical analyses. Treatment and time effects were assessed using a mixed-effects model (REML), followed by Sidak’s multiple comparisons test for pairwise comparisons.
https://doi.org/10.1371/journal.ppat.1014094.s002
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S3 Fig. Supplementary information related to Fig 6.
(A) Dot plot showing the mean expression of selected marker genes in each cluster from Fig 6A. (B) Network graph showing cluster-specific DEGs involved in the RHO GTPase cycle pathway. Edge color indicates positive or negative fold change in G1 compared to G2, and edge thickness represents the absolute fold change. G1: CD1D − / − vaccinated and challenged; G2: CD1D − / + vaccinated and challenged.
https://doi.org/10.1371/journal.ppat.1014094.s003
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S4 Fig. Supplementary information related to Fig 7H-7L.
Heatmaps showing the number of overlapping CDR3 sequences across samples for BCR light chain CDR3s (A) and heavy chain CDR3s (B).
https://doi.org/10.1371/journal.ppat.1014094.s004
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S5 Fig. Supplementary information related to Fig 8.
(A–C, F, H) VJC segment diversity measured using the Shannon–Wiener index, corresponding to the Hill diversity index at order q = 1 for each γδ T cell subtype. (D) CDR3γ amino acid length distribution across γδ T cell subtypes. (E, G) Proportion of cells expressing TRDV (E) and TRDJ (G) segments by cell type. (I) CDR3γ diversity across varying Hill diversity orders. (J) Heatmaps showing the number of overlapping CDR3γ sequences across samples. (K) Principal component analysis (PCA) of TRG and TRD VJC segment usages by sample.
https://doi.org/10.1371/journal.ppat.1014094.s005
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S6 Fig. CD1D genotyping results.
CD1D genotype of pigs from three litters was confirmed by PCR targeting a 2,788 bp product of the endogenous porcine CD1D gene. Pigs that possessed an edited CD1D allele produced a deletion of 1,598 bp resulting in a modified product of 1,189 bp. A single 1,189 bp band was detected in homozygous (CD1D − /−) pigs, whereas two PCR products at 1,189 and 2,787 bp were detected in heterozygous (CD1D − /+) pigs. M: DNA molecular marker; PC1: a positive control for the modified allele; PC2: a positive control for an unmodified, “wildtype” sample; NC: negative control. Pigs #1–11 (1–6 are female and 7–11 are male) from litter 1, #1–7 (1–4 are female and 5–7 are male) from litter 2, and 1, 3 and 6–10 (1 and 3 are female and 6–10 are male) from litter 3 were used in this study.
https://doi.org/10.1371/journal.ppat.1014094.s006
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S1 Table. Frequency (mean ± SEM) of leukocyte populations in lungs at 5 days post challenge.
https://doi.org/10.1371/journal.ppat.1014094.s007
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S2 Table. Frequency (mean ± SEM) of leukocyte populations in tracheobronchial lymph nodes at 5 days post challenge.
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S3 Table. Frequency (mean ± SEM) of leukocyte populations in blood at -1 days post vaccination.
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S4 Table. Frequency (mean ± SEM) of leukocyte populations in blood at 14 days post vaccination.
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S5 Table. Frequency (mean ± SEM) of leukocyte populations in blood at 20 days post vaccination.
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S6 Table. Frequency (mean ± SEM) of leukocyte populations in blood at 5 days post challenge.
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S7 Table. Porcine custom primer sets for scTCR/BCRseq.
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S8 Table. Shared expanded CDR3β clones between this study and a prior study.
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S1 Data. Differentially expressed genes between G1 (CD1D − / − vaccinated and challenged) and G2 (CD1D − / + vaccinated and challenged) in each cell type, related to Fig 6.
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S2 Data. scTCRseq and scBCRseq data, related to Figs 7 and 8.
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Acknowledgments
We gratefully thank Shristi Ghimire, Shanmugasundaram Elango, and Sujan Kafle at Kansas State University for technical assistance and Melissa Samuel, Kristin Whitworth, and Anna Spate at University of Missouri for husbandry, maintenance, and genotyping of the CD1D genetically engineered pigs. We also thank members of the Louisiana Animal Disease Diagnostic Laboratory for their assistance in histological processing of tissues, slide preparation and staining. We thank the NIH Tetramer Core Facility (NIH Contract 75N93020D00005 and RRID:SCR_026557) for providing the mouse CD1d tetramer. We thank the University of Missouri Genomics Technology Core for assistance with library preparation and sequencing.
References
- 1. Bendelac A, Lantz O, Quimby ME, Yewdell JW, Bennink JR, Brutkiewicz RR. CD1 recognition by mouse NK1+ T lymphocytes. Science. 1995;268(5212):863–5. pmid:7538697
- 2. Mattner J, Debord KL, Ismail N, Goff RD, Cantu C 3rd, Zhou D, et al. Exogenous and endogenous glycolipid antigens activate NKT cells during microbial infections. Nature. 2005;434(7032):525–9. pmid:15791258
- 3. Driver JP, de Carvalho Madrid DM, Gu W, Artiaga BL, Richt JA. Modulation of immune responses to influenza A virus vaccines by natural killer T cells. Front Immunol. 2020;11:2172. pmid:33193296
- 4. Speir M, Hermans IF, Weinkove R. Engaging natural killer T Cells as “Universal helpers” for vaccination. Drugs. 2017;77(1):1–15. pmid:28005229
- 5. Yoo J-K, Braciale TJ. IL-21 promotes late activator APC-mediated T follicular helper cell differentiation in experimental pulmonary virus infection. PLoS One. 2014;9(9):e105872. pmid:25251568
- 6. Chang P-P, Barral P, Fitch J, Pratama A, Ma CS, Kallies A, et al. Identification of Bcl-6-dependent follicular helper NKT cells that provide cognate help for B cell responses. Nat Immunol. 2011;13(1):35–43. pmid:22120117
- 7. King IL, Fortier A, Tighe M, Dibble J, Watts GFM, Veerapen N, et al. Invariant natural killer T cells direct B cell responses to cognate lipid antigen in an IL-21-dependent manner. Nat Immunol. 2011;13(1):44–50. pmid:22120118
- 8. Barral P, Eckl-Dorna J, Harwood NE, De Santo C, Salio M, Illarionov P, et al. B cell receptor-mediated uptake of CD1d-restricted antigen augments antibody responses by recruiting invariant NKT cell help in vivo. Proc Natl Acad Sci U S A. 2008;105(24):8345–50. pmid:18550831
- 9. Leadbetter EA, Brigl M, Illarionov P, Cohen N, Luteran MC, Pillai S, et al. NK T cells provide lipid antigen-specific cognate help for B cells. Proc Natl Acad Sci U S A. 2008;105(24):8339–44. pmid:18550809
- 10. De Santo C, Salio M, Masri SH, Lee LY-H, Dong T, Speak AO, et al. Invariant NKT cells reduce the immunosuppressive activity of influenza A virus-induced myeloid-derived suppressor cells in mice and humans. J Clin Invest. 2008;118(12):4036–48. pmid:19033672
- 11. Galli G, Pittoni P, Tonti E, Malzone C, Uematsu Y, Tortoli M, et al. Invariant NKT cells sustain specific B cell responses and memory. Proc Natl Acad Sci U S A. 2007;104(10):3984–9. pmid:17360464
- 12. Guillonneau C, Mintern JD, Hubert F-X, Hurt AC, Besra GS, Porcelli S, et al. Combined NKT cell activation and influenza virus vaccination boosts memory CTL generation and protective immunity. Proc Natl Acad Sci U S A. 2009;106(9):3330–5. pmid:19211791
- 13. Benton KA, Misplon JA, Lo CY, Brutkiewicz RR, Prasad SA, Epstein SL. Heterosubtypic immunity to influenza A virus in mice lacking IgA, all Ig, NKT cells, or gamma delta T cells. J Immunol. 2001;166(12):7437–45. pmid:11390496
- 14. Spada FM, Koezuka Y, Porcelli SA. CD1d-restricted recognition of synthetic glycolipid antigens by human natural killer T cells. J Exp Med. 1998;188(8):1529–34. pmid:9782130
- 15. Fernandez CS, Jegaskanda S, Godfrey DI, Kent SJ. In-vivo stimulation of macaque natural killer T cells with α-galactosylceramide. Clin Exp Immunol. 2013;173(3):480–92. pmid:23656283
- 16. Motsinger A, Azimzadeh A, Stanic AK, Johnson RP, Van Kaer L, Joyce S, et al. Identification and simian immunodeficiency virus infection of CD1d-restricted macaque natural killer T cells. J Virol. 2003;77(14):8153–8. pmid:12829854
- 17. Fichtner AS, Paletta D, Starick L, Schumann RF, Niewiesk S, Herrmann T. Function and expression of CD1d and invariant natural killer T-cell receptor in the cotton rat (Sigmodon hispidus). Immunology. 2015;146(4):618–29. pmid:26346465
- 18. Thierry A, Robin A, Giraud S, Minouflet S, Barra A, Bridoux F, et al. Identification of invariant natural killer T cells in porcine peripheral blood. Vet Immunol Immunopathol. 2012;149(3–4):272–9. pmid:22939274
- 19. Renukaradhya GJ, Manickam C, Khatri M, Rauf A, Li X, Tsuji M, et al. Functional invariant NKT cells in pig lungs regulate the airway hyperreactivity: a potential animal model. J Clin Immunol. 2011;31(2):228–39. pmid:21042929
- 20. Yasuda N, Masuda K, Tsukui T, Teng A, Ishii Y. Identification of canine natural CD3-positive T cells expressing an invariant T-cell receptor alpha chain. Vet Immunol Immunopathol. 2009;132(2–4):224–31. pmid:19748683
- 21. Looringh van Beeck FA, Reinink P, Hermsen R, Zajonc DM, Laven MJ, Fun A, et al. Functional CD1d and/or NKT cell invariant chain transcript in horse, pig, African elephant and guinea pig, but not in ruminants. Mol Immunol. 2009;46(7):1424–31. pmid:19185921
- 22. Kawano T, Cui J, Koezuka Y, Toura I, Kaneko Y, Motoki K, et al. CD1d-restricted and TCR-mediated activation of valpha14 NKT cells by glycosylceramides. Science. 1997;278(5343):1626–9. pmid:9374463
- 23. Matsuura A, Kinebuchi M, Chen HZ, Katabami S, Shimizu T, Hashimoto Y, et al. NKT cells in the rat: organ-specific distribution of NK T cells expressing distinct V alpha 14 chains. J Immunol. 2000;164(6):3140–8. pmid:10706704
- 24. Nguyen TQ, Rollon R, Choi YK. Animal models for influenza research: strengths and weaknesses. Viruses. 2021;13(6).
- 25. Thangavel RR, Bouvier NM. Animal models for influenza virus pathogenesis, transmission, and immunology. J Immunol Methods. 2014;410:60–79. pmid:24709389
- 26. Barnard DL. Animal models for the study of influenza pathogenesis and therapy. Antiviral Res. 2009;82(2):A110-22. pmid:19176218
- 27. Starbæk SMR, Brogaard L, Dawson HD, Smith AD, Heegaard PMH, Larsen LE, et al. Animal models for influenza A virus infection incorporating the involvement of innate host defenses: enhanced translational value of the porcine model. ILAR J. 2018;59(3):323–37. pmid:30476076
- 28. Kok WL, Denney L, Benam K, Cole S, Clelland C, McMichael AJ, et al. Pivotal Advance: Invariant NKT cells reduce accumulation of inflammatory monocytes in the lungs and decrease immune-pathology during severe influenza A virus infection. J Leukoc Biol. 2012;91(3):357–68. pmid:22003207
- 29. Ishikawa H, Tanaka K, Kutsukake E, Fukui T, Sasaki H, Hata A, et al. IFN-γ production downstream of NKT cell activation in mice infected with influenza virus enhances the cytolytic activities of both NK cells and viral antigen-specific CD8+ T cells. Virology. 2010;407(2):325–32. pmid:20855097
- 30. Ho L-P, Denney L, Luhn K, Teoh D, Clelland C, McMichael AJ. Activation of invariant NKT cells enhances the innate immune response and improves the disease course in influenza A virus infection. Eur J Immunol. 2008;38(7):1913–22. pmid:18521958
- 31. Lin K-H, Liang J-J, Huang W-I, Lin-Chu S-Y, Su C-Y, Lee Y-L, et al. In vivo protection provided by a synthetic new alpha-galactosyl ceramide analog against bacterial and viral infections in murine models. Antimicrob Agents Chemother. 2010;54(10):4129–36. pmid:20660669
- 32. Yang G, Artiaga BL, Hackmann TJ, Samuel MS, Walters EM, Salek-Ardakani S, et al. Targeted disruption of CD1d prevents NKT cell development in pigs. Mamm Genome. 2015;26(5–6):264–70. pmid:25930071
- 33. Artiaga BL, Whitener RL, Staples CR, Driver JP. Adjuvant effects of therapeutic glycolipids administered to a cohort of NKT cell-diverse pigs. Vet Immunol Immunopathol. 2014;162(1–2):1–13. pmid:25441499
- 34. Artiaga BL, Yang G, Hackmann TJ, Liu Q, Richt JA, Salek-Ardakani S, et al. α-Galactosylceramide protects swine against influenza infection when administered as a vaccine adjuvant. Sci Rep. 2016;6:23593. pmid:27004737
- 35. Gu W, de Carvahlo Madrid DM, Wen Y, Clements S, Touchard L, Bivens N, et al. Single-cell antigen receptor sequencing in pigs with influenza. Commun Biol. 2025;8(1):1108. pmid:40715353
- 36. Srivastava N, Sudan R, Kerr WG. Role of inositol poly-phosphatases and their targets in T cell biology. Front Immunol. 2013;4:288. pmid:24069021
- 37. Kim W, Kim E, Min H, Kim MG, Eisenbeis VB, Dutta AK, et al. Inositol polyphosphates promote T cell-independent humoral immunity via the regulation of Bruton’s tyrosine kinase. Proc Natl Acad Sci U S A. 2019;116(26):12952–7. pmid:31189594
- 38. Saci A, Carpenter CL. RhoA GTPase regulates B cell receptor signaling. Mol Cell. 2005;17(2):205–14. pmid:15664190
- 39. Tybulewicz VLJ, Henderson RB. Rho family GTPases and their regulators in lymphocytes. Nat Rev Immunol. 2009;9(9):630–44. pmid:19696767
- 40. Ahmad Mokhtar AM, Salikin NH, Haron AS, Amin-Nordin S, Hashim IF, Mohd Zaini Makhtar M. RhoG’s role in T cell activation and function. Front Immunol. 2022;13:845064.
- 41. Saoudi A, Kassem S, Dejean A, Gaud G. Rho-GTPases as key regulators of T lymphocyte biology. Small GTPases. 2014;5:e28208. pmid:24825161
- 42. Zhang S, Weinberg S, DeBerge M, Gainullina A, Schipma M, Kinchen JM, et al. Efferocytosis fuels requirements of fatty acid oxidation and the electron transport chain to polarize macrophages for tissue repair. Cell Metab. 2019;29(2):443-456.e5. pmid:30595481
- 43. Teng YHF, Quah HS, Suteja L, Dias JML, Mupo A, Bashford-Rogers RJM, et al. Analysis of T cell receptor clonotypes in tumor microenvironment identifies shared cancer-type-specific signatures. Cancer Immunol Immunother. 2022;71(4):989–98. pmid:34580764
- 44. Gomez-Tourino I, Kamra Y, Baptista R, Lorenc A, Peakman M. T cell receptor β-chains display abnormal shortening and repertoire sharing in type 1 diabetes. Nat Commun. 2017;8(1):1792. pmid:29176645
- 45. Vita R, Blazeska N, Marrama D, IEDB Curation Team Members, Duesing S, Bennett J, et al. The Immune Epitope Database (IEDB): 2024 update. Nucleic Acids Res. 2025;53(D1):D436–43. pmid:39558162
- 46. Barker DJ, Maccari G, Georgiou X, Cooper MA, Flicek P, Robinson J. The IPD-IMGT/HLA database. Nucleic Acids Res. 2022;51(D1):D1053–60.
- 47. Yang G, Artiaga BL, Lomelino CL, Jayaprakash AD, Sachidanandam R, Mckenna R, et al. Next generation sequencing of the pig αβ TCR repertoire identifies the porcine invariant NKT cell receptor. J Immunol. 2019;202(7):1981–91. pmid:30777925
- 48. Linguiti G, Giannico F, D’Addabbo P, Pala A, Caputi Jambrenghi A, Ciccarese S, et al. The organization of the pig T-cell receptor γ (TRG) locus provides insights into the evolutionary patterns of the TRG genes across cetartiodactyla. Genes (Basel). 2022;13(2):177. pmid:35205222
- 49. Yang G, Artiaga BL, Lewis ST, Driver JP. Characterizing porcine invariant natural killer T cells: a comparative study with NK cells and T cells. Dev Comp Immunol. 2017;76:343–51. pmid:28694168
- 50. Gu W, Madrid DMC, Joyce S, Driver JP. A single-cell analysis of thymopoiesis and thymic iNKT cell development in pigs. Cell Rep. 2022;40(1):111050. pmid:35793622
- 51. Yang G, Artiaga BL, Lomelino CL, Jayaprakash AD, Sachidanandam R, Mckenna R, et al. Next generation sequencing of the Pig αβ TCR repertoire identifies the porcine invariant NKT cell receptor. J Immunol. 2019;202(7):1981–91. pmid:30777925
- 52. Artiaga BL, Yang G, Hackmann TJ, Liu Q, Richt JA, Salek-Ardakani S, et al. α-Galactosylceramide protects swine against influenza infection when administered as a vaccine adjuvant. Sci Rep. 2016;6:23593. pmid:27004737
- 53. Lang GA, Shrestha B, Amadou Amani S, Shadid TM, Ballard JD, Lang ML. α-Galactosylceramide-reactive NKT cells increase IgG1 class switch against a Clostridioides difficile polysaccharide antigen and enhance immunity against a live pathogen challenge. Infect Immun. 2021;89(11):e0043821. pmid:34424751
- 54. Godfrey DI, Kronenberg M. Going both ways: immune regulation via CD1d-dependent NKT cells. J Clin Invest. 2004;114(10):1379–88. pmid:15545985
- 55. Panahipoor Javaherdehi A, Ghanbari S, Mahdavi P, Zafarani A, Razizadeh MH. The role of alveolar macrophages in viral respiratory infections and their therapeutic implications. Biochem Biophys Rep. 2024;40:101826. pmid:39324036
- 56. Pöpperl P, Stoff M, Beineke A. Alveolar macrophages in viral respiratory infections: Sentinels and saboteurs of lung defense. Int J Mol Sci. 2025;26(1):407. pmid:39796262
- 57. Chen G, Yang X, Ko A, Sun X, Gao M, Zhang Y, et al. Sequence and structural analyses reveal distinct and highly diverse human CD8+ TCR repertoires to immunodominant viral antigens. Cell Rep. 2017;19(3):569–83. pmid:28423320
- 58. Gotch F, Rothbard J, Howland K, Townsend A, McMichael A. Cytotoxic T lymphocytes recognize a fragment of influenza virus matrix protein in association with HLA-A2. Nature. 1987;326(6116):881–2. pmid:2437457
- 59. Fan S, Wang Y, Wang X, Huang L, Zhang Y, Liu X, et al. Analysis of the affinity of influenza A virus protein epitopes for swine MHC I by a modified in vitro refolding method indicated cross-reactivity between swine and human MHC I specificities. Immunogenetics. 2018;70(10):671–80. pmid:29992375
- 60. Ravens S, Schultze-Florey C, Raha S, Sandrock I, Drenker M, Oberdörfer L, et al. Human γδ T cells are quickly reconstituted after stem-cell transplantation and show adaptive clonal expansion in response to viral infection. Nat Immunol. 2017;18(4):393–401. pmid:28218745
- 61. Paterson S, Kar S, Ung SK, Gardener Z, Bergstrom E, Ascough S, et al. Innate-like gene expression of lung-resident memory CD8+ T cells during experimental human influenza: a clinical study. Am J Respir Crit Care Med. 2021;204(7):826–41. pmid:34256007
- 62. Richt JA, Lekcharoensuk P, Lager KM, Vincent AL, Loiacono CM, Janke BH, et al. Vaccination of pigs against swine influenza viruses by using an NS1-truncated modified live-virus vaccine. J Virol. 2006;80(22):11009–18. pmid:16943300
- 63. Artiaga BL, Morozov I, Ransburgh R, Kwon T, Balaraman V, Indran SV, et al. Evaluating α-galactosylceramide as an adjuvant for live attenuated influenza vaccines in pigs. Anim Dis. 2022;2(1):19. pmid:35936354
- 64. Whitworth KM, Lee K, Benne JA, Beaton BP, Spate LD, Murphy SL, et al. Use of the CRISPR/Cas9 system to produce genetically engineered pigs from in vitro-derived oocytes and embryos. Biol Reprod. 2014;91(3):78. pmid:25100712
- 65. Artiaga BL, Madden D, Kwon T, McDowell C, Keating C, Balaraman V. Adjuvant use of the invariant-natural-killer-T-cell agonist alpha-galactosylceramide leads to vaccine-associated enhanced respiratory disease in influenza-vaccinated pigs. Vaccines (Basel). 2024;12(9). pmid:39340098
- 66. Reed LJ, Muench H. A simple method of estimating fifty per cent endpoints12. Am J Epidemiol. 1938;27(3):493–7.
- 67. Khurana S, Loving CL, Manischewitz J, King LR, Gauger PC, Henningson J, et al. Vaccine-induced anti-HA2 antibodies promote virus fusion and enhance influenza virus respiratory disease. Sci Transl Med. 2013;5(200):200ra114. pmid:23986398
- 68. Hao Y, Stuart T, Kowalski MH, Choudhary S, Hoffman P, Hartman A, et al. Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nat Biotechnol. 2024;42(2):293–304. pmid:37231261
- 69. Giudicelli V, Chaume D, Lefranc M-P. IMGT/V-QUEST, an integrated software program for immunoglobulin and T cell receptor V-J and V-D-J rearrangement analysis. Nucleic Acids Res. 2004;32(Web Server issue):W435-40. pmid:15215425
- 70. Steinegger M, Söding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol. 2017;35(11):1026–8. pmid:29035372
- 71. Yamamoto R, Uenishi H, Hatsuse H, Sato E, Awata T, Yasue H, et al. TRAV gene usage in pig T-cell receptor alpha cDNA. Immunogenetics. 2005;57(3–4):219–25. pmid:15900493
- 72. Sturm G, Szabo T, Fotakis G, Haider M, Rieder D, Trajanoski Z, et al. Scirpy: a Scanpy extension for analyzing single-cell T-cell receptor-sequencing data. Bioinformatics. 2020;36(18):4817–8. pmid:32614448
- 73. Chronister WD, Crinklaw A, Mahajan S, Vita R, Koşaloğlu-Yalçın Z, Yan Z, et al. TCRMatch: predicting T-cell receptor specificity based on sequence similarity to previously characterized receptors. Front Immunol. 2021;12:640725. pmid:33777034
- 74. Gupta NT, Vander Heiden JA, Uduman M, Gadala-Maria D, Yaari G, Kleinstein SH. Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data. Bioinformatics. 2015;31(20):3356–8. pmid:26069265
- 75. Hill MO. Diversity and evenness: a unifying notation and its consequences. Ecology. 1973;54.