Identification of FasL as a crucial host factor driving COVID-19 pathology and lethality.

The dysregulated immune response and inflammation resulting in severe COVID-19 are still incompletely understood. Having recently determined that aberrant death-ligand-induced cell death can cause lethal inflammation, we hypothesized that this process might also cause or contribute to inflammatory disease and lung failure following SARS-CoV-2 infection. To test this hypothesis, we developed a novel mouse-adapted SARS-CoV-2 model (MA20) that recapitulates key pathological features of COVID-19. Concomitantly with occurrence of cell death and inflammation, FasL expression was significantly increased on inflammatory monocytic macrophages and NK cells in the lungs of MA20-infected mice. Importantly, therapeutic FasL inhibition markedly increased survival of both, young and old MA20-infected mice coincident with substantially reduced cell death and inflammation in their lungs. Intriguingly, FasL was also increased in the bronchoalveolar lavage fluid of critically-ill COVID-19 patients. Together, these results identify FasL as a crucial host factor driving the immuno-pathology that underlies COVID-19 severity and lethality, and imply that patients with severe COVID-19 may significantly benefit from therapeutic inhibition of FasL.

Neutrophil extracellular traps induce persistent lung tissue damage via thromboinflammation without altering virus resolution in a mouse coronavirus model.

BACKGROUND: During infection, neutrophil extracellular traps (NETs) are associated with severity of pulmonary diseases such as acute respiratory disease syndrome. NETs induce subsequent immune responses, are directly cytotoxic to pulmonary cells, and are highly procoagulant. Anticoagulation treatment was shown to reduce in-hospital mortality, indicating thromboinflammatory complications. However, data are sparsely available on the involvement of NETs in secondary events after virus clearance, which can lead to persistent lung damage and postacute sequelae with chronic fatigue and dyspnea. OBJECTIVES: This study focuses on late-phase events using a murine model of viral lung infection with postacute sequelae after virus resolution. METHODS: C57BL/6JRj mice were infected intranasally with the betacoronavirus murine coronavirus (MCoV, strain MHV-A95), and tissue samples were collected after 2, 4, and 10 days. For NET modulation, mice were pretreated with OM-85 or GSK484 and DNase I were administered intraperitoneally between days 2 to 5 and days 4 to 7, respectively. RESULTS: Rapid, platelet-attributed thrombus formation was followed by a second, late phase of thromboinflammation. This phase was characterized by negligible virus titers but pronounced tissue damage, apoptosis, oxidative DNA damage, and presence of NETs. Inhibition of NETs during the acute phase did not impact virus burden but decreased lung cell apoptosis by 67% and oxidative stress by 94%. Prevention of neutrophil activation by immune training before virus infection reduced damage by 75%, NETs by 31%, and pulmonary thrombi by 93%. CONCLUSION: NETs are detrimental inducers of tissue damage during respiratory virus infection but do not contribute to virus clearance.

Increasing test specificity without impairing sensitivity: lessons learned from SARS-CoV-2 serology.

BACKGROUND: Serological tests are widely used in various medical disciplines for diagnostic and monitoring purposes. Unfortunately, the sensitivity and specificity of test systems are often poor, leaving room for false-positive and false-negative results. However, conventional methods were used to increase specificity and decrease sensitivity and vice versa. Using SARS-CoV-2 serology as an example, we propose here a novel testing strategy: the 'sensitivity improved two-test' or 'SIT²' algorithm. METHODS: SIT² involves confirmatory retesting of samples with results falling in a predefined retesting zone of an initial screening test, with adjusted cut-offs to increase sensitivity. We verified and compared the performance of SIT² to single tests and orthogonal testing (OTA) in an Austrian cohort (1117 negative, 64 post-COVID-positive samples) and validated the algorithm in an independent British cohort (976 negatives and 536 positives). RESULTS: The specificity of SIT² was superior to single tests and non-inferior to OTA. The sensitivity was maintained or even improved using SIT² when compared with single tests or OTA. SIT² allowed correct identification of infected individuals even when a live virus neutralisation assay could not detect antibodies. Compared with single testing or OTA, SIT² significantly reduced total test errors to 0.46% (0.24-0.65) or 1.60% (0.94-2.38) at both 5% or 20% seroprevalence. CONCLUSION: For SARS-CoV-2 serology, SIT² proved to be the best diagnostic choice at both 5% and 20% seroprevalence in all tested scenarios. It is an easy to apply algorithm and can potentially be helpful for the serology of other infectious diseases.

One-Year Follow-Up of COVID-19 Patients Indicates Substantial Assay-Dependent Differences in the Kinetics of SARS-CoV-2 Antibodies.

Determination of antibody levels against the nucleocapsid (N) and spike (S) proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are used to estimate the humoral immune response after SARS-CoV-2 infection or vaccination. Differences in the design and specification of antibody assays challenge the interpretation of test results, and comparative studies are often limited to single time points per patient. We determined the longitudinal kinetics of antibody levels of 145 unvaccinated coronavirus disease 2019 (COVID-19) patients at four visits over 1 year upon convalescence using 8 commercial SARS-CoV-2 antibody assays (from Abbott, DiaSorin, Roche, Siemens, and Technoclone), as well as a virus neutralization test (VNT). A linear regression model was used to investigate whether antibody results obtained in the first 6 months after disease onset could predict the VNT results at 12 months. Spike protein-specific antibody tests showed good correlation to the VNT at individual time points (rS, 0.74 to 0.92). While longitudinal assay comparison with the Roche Elecsys anti-SARS-CoV-2 S test showed almost constant antibody concentrations over 12 months, the VNT and all other tests indicated a decline in serum antibody levels (median decrease to 14% to 36% of baseline). The antibody level at 3 months was the best predictor of the VNT results at 12 months after disease onset. The current standardization to a WHO calibrator for normalization to binding antibody units (BAU) is not sufficient for the harmonization of SARS-CoV-2 antibody tests. Assay-specific differences in absolute values and trends over time need to be considered when interpreting the course of antibody levels in patients. IMPORTANCE Determination of antibodies against SARS-CoV-2 will play an important role in detecting a sufficient immune response. Although all the manufacturers expressed antibody levels in binding antibody units per milliliter, thus suggesting comparable results, we found discrepant behavior between the eight investigated assays when we followed the antibody levels in a cohort of 145 convalescent patients over 1 year. While one assay yielded constant antibody levels, the others showed decreasing antibody levels to a varying extent. Therefore, the comparability of the assays must be improved regarding the long-term kinetics of antibody levels. This is a prerequisite for establishing reliable antibody level cutoffs for sufficient individual protection against SARS-CoV-2.

Borderline and weakly positive antibody levels against the S-protein of SARS-CoV-2 exhibit limited agreement with virus neutralization titres.

The presence of neutralizing antibodies against SARS-CoV-2 in a large number of people is - besides cellular immunity - important to overcome the SARS-CoV-2 pandemic. While determination of neutralizing antibodies via virus neutralization tests are laborious, assays to determine the antibody levels serologically are fully automated and widely available. Correlations between these methodologies were recently given by the manufacturers, however performance in samples close to the cut off value have not yet been fully validated. Thus, we analysed 22 borderline and low positive (<100 BAU/ml) samples and 9 high positive (≥ 100 BAU/ml) from infected and/or vaccinated individuals and compared the SARS-CoV-2 IgG II Quant assay (Abbott), LIAISON SARS-CoV-2 TrimericS IgG (Diasorin), Elecsys Anti-SARS-CoV-2 S (Roche), and SARS-CoV-2 IgG (Siemens) with results obtained from a virus neutralization test. Based on the cut off values given by Abbott, Diasorin, Roche, and Siemens, the positive serologic results were concordant with the virus neutralization test in 100%, 76%, 88%, and 71%, respectively, while in turn, negative ones were in agreement in 29%, 79%, 93%, and 86%, respectively. In conclusion, weakly positive, serologic results are challenging to correctly predict the presence of neutralizing antibodies. Our study suggests, that different cut off values (for positivity vs. presence of neutralizing antibodies) could improve the test's performance, but determination thereof requires more samples to be analysed.

Innate Immune Training with Bacterial Extracts Enhances Lung Macrophage Recruitment to Protect from Betacoronavirus Infection.

Training of the innate immune system with orally ingested bacterial extracts was demonstrated to have beneficial effects on infection clearance and disease outcome. The aim of our study was to identify cellular and molecular processes responsible for these immunological benefits. We used a murine coronavirus (MCoV) A59 mouse model treated with the immune activating bacterial extract Broncho-Vaxom (BV) OM-85. Tissue samples were analysed with qPCR, RNA sequencing, histology, and flow cytometry. After BV OM-85 treatment, interstitial macrophages accumulated in lung tissue leading to a faster response of type I interferon (IFN) signalling after MCoV infection resulting in overall lung tissue protection. Moreover, RNA sequencing showed that lung tissue from mice receiving BV OM-85 resembled an intermediate stage between healthy and viral infected lung tissue at day 4, indicating a faster return to normal tissue homoeostasis. The pharmacologic effect was mimicked by adoptively transferring naive lung macrophages into lungs from recipient mice before virus infection. The beneficial effect of BV OM-85 was abolished when inhibiting initial type I IFN signalling. Overall, our data suggest that BV OM-85 enhances lung macrophages allowing for a faster IFN response towards a viral challenge as part of the oral-induced innate immune system training.

Comparing Host Module Activation Patterns and Temporal Dynamics in Infection by Influenza H1N1 Viruses.

Influenza is a serious global health threat that shows varying pathogenicity among different virus strains. Understanding similarities and differences among activated functional pathways in the host responses can help elucidate therapeutic targets responsible for pathogenesis. To compare the types and timing of functional modules activated in host cells by four influenza viruses of varying pathogenicity, we developed a new DYNAmic MOdule (DYNAMO) method that addresses the need to compare functional module utilization over time. This integrative approach overlays whole genome time series expression data onto an immune-specific functional network, and extracts conserved modules exhibiting either different temporal patterns or overall transcriptional activity. We identified a common core response to influenza virus infection that is temporally shifted for different viruses. We also identified differentially regulated functional modules that reveal unique elements of responses to different virus strains. Our work highlights the usefulness of combining time series gene expression data with a functional interaction map to capture temporal dynamics of the same cellular pathways under different conditions. Our results help elucidate conservation of the immune response both globally and at a granular level, and provide mechanistic insight into the differences in the host response to infection by influenza strains of varying pathogenicity.

Mitochondrial localization and moderated activity are key to murine erythroid enucleation.

Mammalian red blood cells (RBCs), which primarily contain hemoglobin, exemplify an elaborate maturation process, with the terminal steps of RBC generation involving extensive cellular remodeling. This encompasses alterations of cellular content through distinct stages of erythroblast maturation that result in the expulsion of the nucleus (enucleation) followed by the loss of mitochondria and all other organelles and a transition to anaerobic glycolysis. Whether there is any link between erythroid removal of the nucleus and the function of any other organelle, including mitochondria, remains unknown. Here we demonstrate that mitochondria are key to nuclear clearance. Using live and confocal microscopy and high-throughput single-cell imaging, we show that before nuclear polarization, mitochondria progressively move toward one side of maturing erythroblasts and aggregate near the nucleus as it extrudes from the cell, a prerequisite for enucleation to proceed. Although we found active mitochondrial respiration is required for nuclear expulsion, levels of mitochondrial activity identify distinct functional subpopulations, because terminally maturing erythroblasts with low relative to high mitochondrial membrane potential are at a later stage of maturation, contain greatly condensed nuclei with reduced open chromatin-associated acetylation histone marks, and exhibit higher enucleation rates. Lastly, to our surprise, we found that late-stage erythroblasts sustain mitochondrial metabolism and subsequent enucleation, primarily through pyruvate but independent of in situ glycolysis. These findings demonstrate the critical but unanticipated functions of mitochondria during the erythroblast enucleation process. They are also relevant to the in vitro production of RBCs as well as to disorders of the erythroid lineage.

A comprehensive antigen production and characterisation study for easy-to-implement, specific and quantitative SARS-CoV-2 serotests.

BACKGROUND: Antibody tests are essential tools to investigate humoral immunity following SARS-CoV-2 infection or vaccination. While first-generation antibody tests have primarily provided qualitative results, accurate seroprevalence studies and tracking of antibody levels over time require highly specific, sensitive and quantitative test setups. METHODS: We have developed two quantitative, easy-to-implement SARS-CoV-2 antibody tests, based on the spike receptor binding domain and the nucleocapsid protein. Comprehensive evaluation of antigens from several biotechnological platforms enabled the identification of superior antigen designs for reliable serodiagnostic. Cut-off modelling based on unprecedented large and heterogeneous multicentric validation cohorts allowed us to define optimal thresholds for the tests' broad applications in different aspects of clinical use, such as seroprevalence studies and convalescent plasma donor qualification. FINDINGS: Both developed serotests individually performed similarly-well as fully-automated CE-marked test systems. Our described sensitivity-improved orthogonal test approach assures highest specificity (99.8%); thereby enabling robust serodiagnosis in low-prevalence settings with simple test formats. The inclusion of a calibrator permits accurate quantitative monitoring of antibody concentrations in samples collected at different time points during the acute and convalescent phase of COVID-19 and disclosed antibody level thresholds that correlate well with robust neutralization of authentic SARS-CoV-2 virus. INTERPRETATION: We demonstrate that antigen source and purity strongly impact serotest performance. Comprehensive biotechnology-assisted selection of antigens and in-depth characterisation of the assays allowed us to overcome limitations of simple ELISA-based antibody test formats based on chromometric reporters, to yield comparable assay performance as fully-automated platforms. FUNDING: WWTF, Project No. COV20-016; BOKU, LBI/LBG.

Clinical validation of the Siemens quantitative SARS-CoV-2 spike IgG assay (sCOVG) reveals improved sensitivity and a good correlation with virus neutralization titers.

OBJECTIVES: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections cause coronavirus disease 2019 (COVID-19) and induce a specific antibody response. Serological assays detecting IgG against the receptor binding domain (RBD) of the spike (S) protein are useful to monitor the immune response after infection or vaccination. The objective of our study was to evaluate the clinical performance of the Siemens SARS-CoV-2 IgG (sCOVG) assay. METHODS: Sensitivity and specificity of the Siemens sCOVG test were evaluated on 178 patients with SARS-CoV-2-infection and 160 pre-pandemic samples in comparison with its predecessor test COV2G. Furthermore, correlation with virus neutralization titers was investigated on 134 samples of convalescent COVID-19 patients. RESULTS: Specificity of the sCOVG test was 99.4% and sensitivity was 90.5% (COV2G assay 78.7%; p<0.0001). S1-RBD antibody levels showed a good correlation with virus neutralization titers (r=0.843; p<0.0001) and an overall qualitative agreement of 98.5%. Finally, median S1-RBD IgG levels increase with age and were significantly higher in hospitalized COVID-19 patients (median levels general ward: 25.7 U/mL; intensive care: 59.5 U/mL) than in outpatients (3.8 U/mL; p<0.0001). CONCLUSIONS: Performance characteristics of the sCOVG assay have been improved compared to the predecessor test COV2G. Quantitative SARS-CoV-2 S1-RBD IgG levels could be used as a surrogate for virus neutralization capacity. Further harmonization of antibody quantification might assist to monitor the humoral immune response after COVID-19 disease or vaccination.

Deciphering the combinatorial landscape of immunity.

From cellular activation to drug combinations, immunological responses are shaped by the action of multiple stimuli. Synergistic and antagonistic interactions between stimuli play major roles in shaping immune processes. To understand combinatorial regulation, we present the immune Synergistic/Antagonistic Interaction Learner (iSAIL). iSAIL includes a machine learning classifier to map and interpret interactions, a curated compendium of immunological combination treatment datasets, and their global integration into a landscape of ~30,000 interactions. The landscape is mined to reveal combinatorial control of interleukins, checkpoints, and other immune modulators. The resource helps elucidate the modulation of a stimulus by interactions with other cofactors, showing that TNF has strikingly different effects depending on co-stimulators. We discover new functional synergies between TNF and IFNß controlling dendritic cell-T cell crosstalk. Analysis of laboratory or public combination treatment studies with this user-friendly web-based resource will help resolve the complex role of interaction effects on immune processes.

Evaluation of a Novel Parent-Rated Scale for Selective Mutism.

Assessment of selective mutism (SM) is hampered by the lack of diagnostic measures. The Frankfurt Scale of Selective Mutism was developed for kindergarteners, schoolchildren, and adolescents, including the diagnostic scale (DS) and the severity scale (SS). The objective of this study was to evaluate this novel, parent-rated questionnaire among individuals aged 3 to 18 years (n = 334) with SM, social phobia, internalizing disorders, and a control group. Item analysis resulted in high item-total correlations, and internal consistency in both scales was excellent with Cronbach's α = .90-.98. Exploratory factor analysis of the SS consistently yielded a one-factor solution. Mean sum scores of the DS differed significantly between the diagnostic groups, and the receiver operating characteristic analysis resulted in optimal cutoffs for distinguishing SM from all other groups with the area under the curves of 0.94-1.00. The SS sum scores correlated significantly with SM's clinician-rated symptom severity.

Differential Modulation of Innate Immune Responses in Human Primary Cells by Influenza A Viruses Carrying Human or Avian Nonstructural Protein 1.

The influenza A virus (IAV) nonstructural protein 1 (NS1) contributes to disease pathogenesis through the inhibition of host innate immune responses. Dendritic cells (DCs) release interferons (IFNs) and proinflammatory cytokines and promote adaptive immunity upon viral infection. In order to characterize the strain-specific effects of IAV NS1 on human DC activation, we infected human DCs with a panel of recombinant viruses with the same backbone (A/Puerto Rico/08/1934) expressing different NS1 proteins from human and avian origin. We found that these viruses induced a clearly distinct phenotype in DCs. Specifically, viruses expressing NS1 from human IAV (either H1N1 or H3N2) induced higher levels of expression of type I (IFN-α and IFN-ß) and type III (IFN-λ1 to IFNλ3) IFNs than viruses expressing avian IAV NS1 proteins (H5N1, H7N9, and H7N2), but the differences observed in the expression levels of proinflammatory cytokines like tumor necrosis factor alpha (TNF-α) or interleukin-6 (IL-6) were not significant. In addition, using imaging flow cytometry, we found that human and avian NS1 proteins segregate based on their subcellular trafficking dynamics, which might be associated with the different innate immune profile induced in DCs by viruses expressing those NS1 proteins. Innate immune responses induced by our panel of IAV recombinant viruses were also characterized in normal human bronchial epithelial cells, and the results were consistent with those in DCs. Altogether, our results reveal an increased ability of NS1 from avian viruses to antagonize innate immune responses in human primary cells compared to the ability of NS1 from human viruses, which could contribute to the severe disease induced by avian IAV in humans.IMPORTANCE Influenza A viruses (IAVs) cause seasonal epidemics which result in an important health and economic burden. Wild aquatic birds are the natural host of IAV. However, IAV can infect diverse hosts, including humans, domestic poultry, pigs, and others. IAVs circulating in animals occasionally cross the species barrier, infecting humans, which results in mild to very severe disease. In some cases, these viruses can acquire the ability to be transmitted among humans and initiate a pandemic. The nonstructural 1 (NS1) protein of IAV is an important antagonist of the innate immune response. In this study, using recombinant viruses and primary human cells, we show that NS1 proteins from human and avian hosts show intrinsic differences in the modulation of the innate immunity in human dendritic cells and epithelial cells, as well as different cellular localization dynamics in infected cells.

Innate Immune Response to Influenza Virus at Single-Cell Resolution in Human Epithelial Cells Revealed Paracrine Induction of Interferon Lambda 1.

Early interactions of influenza A virus (IAV) with respiratory epithelium might determine the outcome of infection. The study of global cellular innate immune responses often masks multiple aspects of the mechanisms by which populations of cells work as organized and heterogeneous systems to defeat virus infection, and how the virus counteracts these systems. In this study, we experimentally dissected the dynamics of IAV and human epithelial respiratory cell interaction during early infection at the single-cell level. We found that the number of viruses infecting a cell (multiplicity of infection [MOI]) influences the magnitude of virus antagonism of the host innate antiviral response. Infections performed at high MOIs resulted in increased viral gene expression per cell and stronger antagonist effect than infections at low MOIs. In addition, single-cell patterns of expression of interferons (IFN) and IFN-stimulated genes (ISGs) provided important insights into the contributions of the infected and bystander cells to the innate immune responses during infection. Specifically, the expression of multiple ISGs was lower in infected than in bystander cells. In contrast with other IFNs, IFN lambda 1 (IFNL1) showed a widespread pattern of expression, suggesting a different cell-to-cell propagation mechanism more reliant on paracrine signaling. Finally, we measured the dynamics of the antiviral response in primary human epithelial cells, which highlighted the importance of early innate immune responses at inhibiting virus spread.IMPORTANCE Influenza A virus (IAV) is a respiratory pathogen of high importance to public health. Annual epidemics of seasonal IAV infections in humans are a significant public health and economic burden. IAV also causes sporadic pandemics, which can have devastating effects. The main target cells for IAV replication are epithelial cells in the respiratory epithelium. The cellular innate immune responses induced in these cells upon infection are critical for defense against the virus, and therefore, it is important to understand the complex interactions between the virus and the host cells. In this study, we investigated the innate immune response to IAV in the respiratory epithelium at the single-cell level, providing a better understanding on how a population of epithelial cells functions as a complex system to orchestrate the response to virus infection and how the virus counteracts this system.

Pathway-level information extractor (PLIER) for gene expression data.

A major challenge in gene expression analysis is to accurately infer relevant biological insights, such as variation in cell-type proportion or pathway activity, from global gene expression studies. We present pathway-level information extractor (PLIER) ( https://github.com/wgmao/PLIER and http://gobie.csb.pitt.edu/PLIER ), a broadly applicable solution for this problem that outperforms available cell proportion inference algorithms and can automatically identify specific pathways that regulate gene expression. Our method improves interstudy replicability and reveals biological insights when applied to trans-eQTL (expression quantitative trait loci) identification.

Interpretation of an individual functional genomics experiment guided by massive public data.

A key unmet challenge in interpreting omics experiments is inferring biological meaning in the context of public functional genomics data. We developed a computational framework, Your Evidence Tailored Integration (YETI; http://yeti.princeton.edu/ ), which creates specialized functional interaction maps from large public datasets relevant to an individual omics experiment. Using this tailored integration, we predicted and experimentally confirmed an unexpected divergence in viral replication after seasonal or pandemic human influenza virus infection.

Single-cell stabilization method identifies gonadotrope transcriptional dynamics and pituitary cell type heterogeneity.

Immediate-early response genes (IEGs) are rapidly and transiently induced following an extracellular signal. Elucidating the IEG response patterns in single cells (SCs) requires assaying large numbers of timed samples at high accuracy while minimizing handling effects. To achieve this, we developed and validated RNA stabilization Buffer for Examination of Single-cell Transcriptomes (RNA-Best), a versatile single-step cell and tissue preservation protocol that stabilizes RNA in intact SCs without perturbing transcription patterns. We characterize for the first time SC heterogeneity in IEG responses to pulsatile gonadotropin-releasing hormone (GnRH) stimuli in pituitary gonadotrope cells. Our study identifies a gene-specific hierarchical pattern of all-or-none transcript induction elicited by increasing concentrations of GnRH. This quantal pattern of gene activation raises the possibility that IEG activation, when accurately resolved at the SC level, may be mediated by gene bits that behave as pure binary switches.

High-density single cell mRNA sequencing to characterize circulating tumor cells in hepatocellular carcinoma.

Patients with hepatocellular carcinoma (HCC) release tumor cells to the bloodstream, which can be detected using cell surface markers. Despite numerous reports suggest a direct correlation between the number of circulating tumor cells (CTCs) and poor clinical outcomes, few studies have provided a thorough molecular characterization of CTCs. Due to the limited access to tissue samples in patients at advanced stages of HCC, it is crucial to develop new technologies to identify HCC cancer drivers in routine clinical conditions. Here, we describe a method that sequentially combines image flow cytometry and high density single-cell mRNA sequencing to identify CTCs in HCC patients. Genome wide expression profiling of CTCs using this approach demonstrates CTC heterogeneity and helps detect known oncogenic drivers in HCC such as IGF2. This integrated approach provides a novel tool for biomarker development in HCC using liquid biopsy.

Pandemic H1N1 influenza A viruses suppress immunogenic RIPK3-driven dendritic cell death.

The risk of emerging pandemic influenza A viruses (IAVs) that approach the devastating 1918 strain motivates finding strain-specific host-pathogen mechanisms. During infection, dendritic cells (DC) mature into antigen-presenting cells that activate T cells, linking innate to adaptive immunity. DC infection with seasonal IAVs, but not with the 1918 and 2009 pandemic strains, induces global RNA degradation. Here, we show that DC infection with seasonal IAV causes immunogenic RIPK3-mediated cell death. Pandemic IAV suppresses this immunogenic DC cell death. Only DC infected with seasonal IAV, but not with pandemic IAV, enhance maturation of uninfected DC and T cell proliferation. In vivo, circulating T cell levels are reduced after pandemic, but not seasonal, IAV infection. Using recombinant viruses, we identify the HA genomic segment as the mediator of cell death inhibition. These results show how pandemic influenza viruses subvert the immune response.