Of mice and men: the host response to influenza virus infection

Predictive signature of murine and human host response to typical and atypical pneumonia

BACKGROUND

Pneumonia due to typical bacterial, atypical bacterial and viral pathogens can be difficult to clinically differentiate. Host response-based diagnostics are emerging as a complementary diagnostic strategy to pathogen detection.

METHODS

We used murine models of typical bacterial, atypical bacterial and viral pneumonia to develop diagnostic signatures and understand the host's response to these types of infections. Mice were intranasally inoculated with Streptococcus pneumoniae, Mycoplasma pneumoniae, influenza or saline as a control. Peripheral blood gene expression analysis was performed at multiple time points. Differentially expressed genes were used to perform gene set enrichment analysis and generate diagnostic signatures. These murine-derived signatures were externally validated in silico using human gene expression data. The response to S. pneumoniae was the most rapid and robust.

RESULTS

Mice infected with M. pneumoniae had a delayed response more similar to influenza-infected animals. Diagnostic signatures for the three types of infection had 0.94-1.00 area under the receiver operator curve (auROC). Validation in five human gene expression datasets revealed auROC of 0.82-0.96.

DISCUSSION

This study identified discrete host responses to typical bacterial, atypical bacterial and viral aetiologies of pneumonia in mice. These signatures validated well in humans, highlighting the conserved nature of the host response to these pathogen classes.

Differential lung gene expression changes in C57BL/6 and DBA/2 mice carrying an identical functional Mx1 gene reveals crucial differences in the host response

BACKGROUND

Influenza virus infections represent a major global health problem. The dynamin-like GTPase MX1 is an interferon-dependent antiviral host protein that confers resistance to influenza virus infections. Infection models in mice are an important experimental system to understand the host response and susceptibility to developing severe disease following influenza infections. However, almost all laboratory mouse strains carry a non-functional Mx1 gene whereas humans have a functional MX1 gene. Most studies in mice have been performed with strains carrying a non-functional Mx1 gene. It is therefore very important to investigate the host response in mouse strains with a functional Mx1 gene.

RESULTS

Here, we analyzed the host response to influenza virus infections in two congenic mouse strains carrying the functional Mx1 gene from the A2G strain. B6.A2G-Mx1r/r(B6-Mx1r/r) mice are highly resistant to influenza A virus (IAV) H1N1 infections. On the other hand, D2(B6).A2G-Mx1r/r(D2-Mx1r/r) mice, although carrying a functional Mx1 gene, were highly susceptible, exhibited rapid weight loss, and died. We performed gene expression analysis using RNAseq from infected lungs at days 3 and 5 post-infection (p.i.) of both mouse strains to identify genes and pathways that were differentially expressed between the two mouse strains. The susceptible D2-Mx1r/r mice showed a high viral replication already at day 3 p.i. and exhibited a much higher number of differentially expressed genes (DEGs) and many DEGs had elevated expression levels compared to B6-Mx1r/r mice. On the other hand, some DEGs were specifically up-regulated only in B6-Mx1r/r mice at day 3 p.i., many of which were related to host immune response functions.

CONCLUSIONS

From these results, we conclude that at early times of infection, D2-Mx1r/r mice showed a very high and rapid replication of the virus, which resulted in lung damage and a hyperinflammatory response leading to death. We hypothesize that the activation of certain immune response genes was missing and that others, especially Mx1, were expressed at a time in D2-Mx1r/r mice when the virus had already massively spread in the lung and were thus not able anymore to protect them from severe disease. Our study represents an important addition to previously published studies in mouse models and contributes to a better understanding of the molecular pathways and genes that protect against severe influenza disease.

Anti-inflammatory effects of theaflavin-3'-gallate during influenza virus infection through regulating the TLR4/MAPK/p38 pathway

Severe pathological damage caused by the influenza virus is one of the leading causes of death. However, the prevention and control strategies for influenza virus infection have certain limitations, and the exploration for new influenza antiviral drugs has become the major research direction. This study evaluated the antiviral activities of four theaflavin derivatives (TFs). Cytopathic effect (CPE) reduction assay revealed that theaflavin-3'-gallate (TF2b) and theaflavin (TF1) could effectively inhibit the replication of influenza viruses H1N1-UI182, H1N1-PR8, H3N2, and H5N1, and TF2b exhibited the most significant antiviral activity in vivo. Intraperitoneal injection of TF2b at 40 mg/kg/d effectively alleviated viral pneumonia, maintained body weight, and improved the survival rate of mice infected with a lethal dose of H1N1-UI182 to 55.56%. Hematological analysis of peripheral blood further showed that TF2b increased the number of lymphocytes and decreased the number of neutrophils, monocytes, and platelets in the blood of infected mice. RT-qPCR results showed that TF2b reduced the mRNA expression levels of inflammatory cytokines (IL-6, TNF-α, and IL-1β), chemokines (CXCL-2 and CCL-3), and interferons (IFN-α and IFN-γ) after influenza virus infection. In addition, TF2b significantly down-regulated the expression levels of TLR4, p-p38, p-ERK, and cytokines IL-6, TNF-α, IL-1β, and IL-10. These results suggest that TF2b not only significantly inhibits viral replication and proliferation in vitro, but also alleviates pneumonia injury in vivo. Its antiviral effect might be attributed to the down-regulation of influenza virus-induced inflammatory cytokines by regulating the TLR4/MAPK/p38 signaling pathway.

A GMR-based assay for quantification of the human response to influenza

Detecting and quantifying the host transcriptional response to influenza virus infection can serve as a real-time diagnostic tool for clinical management. We have employed the multiplexing capabilities of GMR sensors to develop a novel assay based on the influenza metasignature (IMS), which can classify influenza infection based on transcript levels. We show that the assay can reliably detect ten IMS transcripts and distinguish subjects with naturally acquired influenza infection from those with other symptomatic viral infections (AUC 0.93, 95% CI: 0.82-1.00). Separately, we validated that the gene IFI27, not included in the IMS panel, has very high single-biomarker accuracy (AUC 0.95, 95% CI: 0.90-0.99) in stratifying patients with influenza. We demonstrate that a portable GMR biosensor can be used as a tool to diagnose influenza infection by measuring the host response, simultaneously highlighting the power of immune system metrics and advancing the field of gene expression-based diagnostics.

Molecular Mechanisms in the Genesis of Seizures and Epilepsy Associated With Viral Infection

Seizures are a common presenting symptom during viral infections of the central nervous system (CNS) and can occur during the initial phase of infection ("early" or acute symptomatic seizures), after recovery ("late" or spontaneous seizures, indicating the development of acquired epilepsy), or both. The development of acute and delayed seizures may have shared as well as unique pathogenic mechanisms and prognostic implications. Based on an extensive review of the literature, we present an overview of viruses that are associated with early and late seizures in humans. We then describe potential pathophysiologic mechanisms underlying ictogenesis and epileptogenesis, including routes of neuroinvasion, viral control and clearance, systemic inflammation, alterations of the blood-brain barrier, neuroinflammation, and inflammation-induced molecular reorganization of synapses and neural circuits. We provide clinical and animal model findings to highlight commonalities and differences in these processes across various neurotropic or neuropathogenic viruses, including herpesviruses, SARS-CoV-2, flaviviruses, and picornaviruses. In addition, we extensively review the literature regarding Theiler's murine encephalomyelitis virus (TMEV). This picornavirus, although not pathogenic for humans, is possibly the best-characterized model for understanding the molecular mechanisms that drive seizures, epilepsy, and hippocampal damage during viral infection. An enhanced understanding of these mechanisms derived from the TMEV model may lead to novel therapeutic interventions that interfere with ictogenesis and epileptogenesis, even within non-infectious contexts.

Genetic background influences survival of infections with Salmonella enterica serovar Typhimurium in the Collaborative Cross

Salmonella infections typically cause self-limiting gastroenteritis, but in some individuals these bacteria can spread systemically and cause disseminated disease. Salmonella Typhimurium (STm), which causes severe systemic disease in most inbred mice, has been used as a model for disseminated disease. To screen for new infection phenotypes across a range of host genetics, we orally infected 32 Collaborative Cross (CC) mouse strains with STm and monitored their disease progression for seven days by telemetry. Our data revealed a broad range of phenotypes across CC strains in many parameters including survival, bacterial colonization, tissue damage, complete blood counts (CBC), and serum cytokines. Eighteen CC strains survived to day 7, while fourteen susceptible strains succumbed to infection before day 7. Several CC strains had sex differences in survival and colonization. Surviving strains had lower pre-infection baseline temperatures and were less active during their daily active period. Core body temperature disruptions were detected earlier after STm infection than activity disruptions, making temperature a better detector of illness. All CC strains had STm in spleen and liver, but susceptible strains were more highly colonized. Tissue damage was weakly negatively correlated to survival. We identified loci associated with survival on Chromosomes (Chr) 1, 2, 4, 7. Polymorphisms in Ncf2 and Slc11a1, known to reduce survival in mice after STm infections, are located in the Chr 1 interval, and the Chr 7 association overlaps with a previously identified QTL peak called Ses2. We identified two new genetic regions on Chr 2 and 4 associated with susceptibility to STm infection. Our data reveal the diversity of responses to STm infection across a range of host genetics and identified new candidate regions for survival of STm infection.

Immune Responses to IAV Infection and the Roles of L-Selectin and ADAM17 in Lymphocyte Homing

Influenza A virus (IAV) infection is a global public health burden causing up to 650,000 deaths per year. Yearly vaccination programmes and anti-viral drugs currently have limited benefits; therefore, research into IAV is fundamental. Leukocyte trafficking is a crucial process which orchestrates the immune response to infection to protect the host. It involves several homing molecules and receptors on both blood vessels and leukocytes. A key mediator of this process is the transmembrane glycoprotein L-selectin, which binds to vascular addressins on blood vessel endothelial cells. L-selectin classically mediates homing of naïve and central memory lymphocytes to lymph nodes via high endothelial venules (HEVs). Recent studies have found that L-selectin is essential for homing of activated CD8⁺ T cells to influenza-infected lungs and reduction in virus load. A disintegrin and metalloproteinase 17 (ADAM17) is the primary regulator of cell surface levels of L-selectin. Understanding the mechanisms that regulate these two proteins are central to comprehending recruitment of T cells to sites of IAV infection. This review summarises the immune response to IAV infection in humans and mice and discusses the roles of L-selectin and ADAM17 in T lymphocyte homing during IAV infection.

Cardiac proteomics reveals sex chromosome-dependent differences between males and females that arise prior to gonad formation

Sex disparities in cardiac homeostasis and heart disease are well documented, with differences attributed to actions of sex hormones. However, studies have indicated sex chromosomes act outside of the gonads to function without mediation by gonadal hormones. Here, we performed transcriptional and proteomics profiling to define differences between male and female mouse hearts. We demonstrate, contrary to current dogma, cardiac sex disparities are controlled not only by sex hormones but also through a sex-chromosome mechanism. Using Turner syndrome (XO) and Klinefelter (XXY) models, we find the sex-chromosome pathway is established by X-linked gene dosage. We demonstrate cardiac sex disparities occur at the earliest stages of heart formation, a period before gonad formation. Using these datasets, we identify and define a role for alpha-1B-glycoprotein (A1BG), showing loss of A1BG leads to cardiac defects in females, but not males. These studies provide resources for studying sex-biased cardiac disease states.

Evolutionarily informed machine learning enhances the power of predictive gene-to-phenotype relationships

Inferring phenotypic outcomes from genomic features is both a promise and challenge for systems biology. Using gene expression data to predict phenotypic outcomes, and functionally validating the genes with predictive powers are two challenges we address in this study. We applied an evolutionarily informed machine learning approach to predict phenotypes based on transcriptome responses shared both within and across species. Specifically, we exploited the phenotypic diversity in nitrogen use efficiency and evolutionarily conserved transcriptome responses to nitrogen treatments across Arabidopsis accessions and maize varieties. We demonstrate that using evolutionarily conserved nitrogen responsive genes is a biologically principled approach to reduce the feature dimensionality in machine learning that ultimately improved the predictive power of our gene-to-trait models. Further, we functionally validated seven candidate transcription factors with predictive power for NUE outcomes in Arabidopsis and one in maize. Moreover, application of our evolutionarily informed pipeline to other species including rice and mice models underscores its potential to uncover genes affecting any physiological or clinical traits of interest across biology, agriculture, or medicine.

Animal Models Utilized for the Development of Influenza Virus Vaccines

Animal models have been an important tool for the development of influenza virus vaccines since the 1940s. Over the past 80 years, influenza virus vaccines have evolved into more complex formulations, including trivalent and quadrivalent inactivated vaccines, live-attenuated vaccines, and subunit vaccines. However, annual effectiveness data shows that current vaccines have varying levels of protection that range between 40–60% and must be reformulated every few years to combat antigenic drift. To address these issues, novel influenza virus vaccines are currently in development. These vaccines rely heavily on animal models to determine efficacy and immunogenicity. In this review, we describe seasonal and novel influenza virus vaccines and highlight important animal models used to develop them.

Long-Term Consequence of Non-neurotropic H3N2 Influenza A Virus Infection for the Progression of Alzheimer's Disease Symptoms

Influenza viruses until today are a leading cause of worldwide severe pandemics and represent a major threat to human and animal health. Although the primary target of influenza viruses is the lung, infection may manifest with acute and even chronic neurological complications (e.g., status epilepticus, encephalopathies, and encephalitis) potentially increasing the long-term risk for neurodegenerative diseases. We previously described that a peripheral influenza A virus (IAV) infection caused by non-neurotropic H3N2 (maHK68) variant leads to long-term neuroinflammation and synapse loss together with impaired memory formation in young adult mice. Processes of neuroinflammation have been associated with neurodegenerative diseases such as Alzheimer’s disease (AD) and prolonged or excessive innate immune responses are considered a risk factor for AD. Here, the role of purely peripheral IAV infection for the development and progression of AD in a transgenic mouse model (APP/PS1) was investigated. At 2 months of age, mice were infected with H3N2 IAV and the detailed analysis of microglia morphology revealed neuroinflammation in the hippocampus already of 6 months old non-infected APP/PS1 mice together with impaired spatial learning, however, microglia activation, amyloid-β plaques load and cognitive impairments were even more pronounced in APP/PS1 mice upon H3N2 infection. Moreover, CA1 hippocampal dendritic spine density was reduced even at 120 dpi compared to wild-type and also to non-infected APP/PS1 mice, whereas neuronal cells number was not altered. These findings demonstrate that non-neurotropic H3N2 IAV infection as a peripheral immune stimulation may exacerbate AD symptoms possibly by triggering microglial hyperactivation.

Baseline T cell immune phenotypes predict virologic and disease control upon SARS-CoV infection in Collaborative Cross mice

The COVID-19 pandemic has revealed that infection with SARS-CoV-2 can result in a wide range of clinical outcomes in humans. An incomplete understanding of immune correlates of protection represents a major barrier to the design of vaccines and therapeutic approaches to prevent infection or limit disease. This deficit is largely due to the lack of prospectively collected, pre-infection samples from individuals that go on to become infected with SARS-CoV-2. Here, we utilized data from genetically diverse Collaborative Cross (CC) mice infected with SARS-CoV to determine whether baseline T cell signatures are associated with a lack of viral control and severe disease upon infection. SARS-CoV infection of CC mice results in a variety of viral load trajectories and disease outcomes. Overall, a dysregulated, pro-inflammatory signature of circulating T cells at baseline was associated with severe disease upon infection. Our study serves as proof of concept that circulating T cell signatures at baseline can predict clinical and virologic outcomes upon SARS-CoV infection. Identification of basal immune predictors in humans could allow for identification of individuals at highest risk of severe clinical and virologic outcomes upon infection, who may thus most benefit from available clinical interventions to restrict infection and disease.

Baseline T cell immune phenotypes predict virologic and disease control upon SARS-CoV infection

The COVID-19 pandemic has revealed that infection with SARS-CoV-2 can result in a wide range of clinical outcomes in humans, from asymptomatic or mild disease to severe disease that can require mechanical ventilation. An incomplete understanding of immune correlates of protection represents a major barrier to the design of vaccines and therapeutic approaches to prevent infection or limit disease. This deficit is largely due to the lack of prospectively collected, pre-infection samples from indiviuals that go on to become infected with SARS-CoV-2. Here, we utilized data from a screen of genetically diverse mice from the Collaborative Cross (CC) infected with SARS-CoV to determine whether circulating baseline T cell signatures are associated with a lack of viral control and severe disease upon infection. SARS-CoV infection of CC mice results in a variety of viral load trajectories and disease outcomes. Further, early control of virus in the lung correlates with an increased abundance of activated CD4 and CD8 T cells and regulatory T cells prior to infections across strains. A basal propensity of T cells to express IFNg and IL17 over TNFa also correlated with early viral control. Overall, a dysregulated, pro-inflammatory signature of circulating T cells at baseline was associated with severe disease upon infection. While future studies of human samples prior to infection with SARS-CoV-2 are required, our studies in mice with SARS-CoV serve as proof of concept that circulating T cell signatures at baseline can predict clinical and virologic outcomes upon SARS-CoV infection. Identification of basal immune predictors in humans could allow for identification of individuals at highest risk of severe clinical and virologic outcomes upon infection, who may thus most benefit from available clinical interventions to restrict infection and disease.

SUMMARY

We used a screen of genetically diverse mice from the Collaborative Cross infected with mouse-adapted SARS-CoV in combination with comprehensive pre-infection immunophenotyping to identify baseline circulating immune correlates of severe virologic and clinical outcomes upon SARS-CoV infection.

Immune Predictors of Mortality After Ribonucleic Acid Virus Infection

BACKGROUND

Virus infections result in a range of clinical outcomes for the host, from asymptomatic to severe or even lethal disease. Despite global efforts to prevent and treat virus infections to limit morbidity and mortality, the continued emergence and re-emergence of new outbreaks as well as common infections such as influenza persist as a health threat. Challenges to the prevention of severe disease after virus infection include both a paucity of protective vaccines as well as the early identification of individuals with the highest risk that may require supportive treatment.

METHODS

We completed a screen of mice from the Collaborative Cross (CC) that we infected with influenza, severe acute respiratory syndrome-coronavirus, and West Nile virus.

RESULTS

The CC mice exhibited a range of disease manifestations upon infections, and we used this natural variation to identify strains with mortality after infection and strains exhibiting no mortality. We then used comprehensive preinfection immunophenotyping to identify global baseline immune correlates of protection from mortality to virus infection.

CONCLUSIONS

These data suggest that immune phenotypes might be leveraged to identify humans at highest risk of adverse clinical outcomes upon infection, who may most benefit from intensive clinical interventions, in addition to providing insight for rational vaccine design.

Complex Genetic Architecture Underlies Regulation of Influenza-A-Virus-Specific Antibody Responses in the Collaborative Cross

Host genetic factors play a fundamental role in regulating humoral immunity to viral infection, including influenza A virus (IAV). Here, we utilize the Collaborative Cross (CC), a mouse genetic reference population, to study genetic regulation of variation in antibody response following IAV infection. CC mice show significant heritable variation in the magnitude, kinetics, and composition of IAV-specific antibody response. We map 23 genetic loci associated with this variation. Analysis of a subset of these loci finds that they broadly affect the antibody response to IAV as well as other viruses. Candidate genes are identified based on predicted variant consequences and haplotype-specific expression patterns, and several show overlap with genes identified in human mapping studies. These findings demonstrate that the host antibody response to IAV infection is under complex genetic control and highlight the utility of the CC in modeling and identifying genetic factors with translational relevance to human health and disease.

Comparison of cytokine profiles induced by nonlethal and lethal doses of influenza A virus in mice

Influenza viruses are among the most common human pathogens and are responsible for causing extensive seasonal morbidity and mortality. To investigate the immunological factors associated with severe influenza infection, the immune responses in mice infected with nonlethal (LD0) doses of A/PR/8/34 (H1N1) influenza virus were compared with those of mice infected with a lethal dose (LD100) of the virus. The virus titer and activation of retinoic acid-inducible gene (RIG)-I-like receptor signaling pathways were similar in the mice infected with LD0 and LD100 at 2 days post-infection; however, mice infected with LD100 exhibited a greater abundance of cytokines and a more diverse cytokine profile. Infection with LD100 induced the expression of the following factors: Interleukins (ILs), IL-4, IL-7, IL-10, IL-11, IL-12p40, IL-13 and IL-15; inflammatory chemokines, C-C motif chemokine ligand (CCL)2, CCL3/4, CCL12, CCL17, CCL19; and lung injury-associated cytokines, leptin, leukaemia inhibitory factor, macrophage colony stimulating factor, pentraxin (PTX)2 and PTX3, WNT1-inducible-signaling pathway protein 1, matrix metallopeptidase (MMP)-2, MMP-3, proprotein convertase subtilisin/kexin type 9, and T cell immunoglobulin and mucin domain. Switching in macrophage polarization from M1 to M2 was evidenced by the increase in M2 markers, including arginase-1 (Arg1) and early growth response protein 2 (Egr2), in the lungs of mice infected with LD100. Since IL-12 and interferon-γ are the major T helper (Th)1 cytokines, increased expression of interferon regulatory factor 4, IL-4, IL-10 and IL-13 promoted the differentiation of naïve CD4⁺ T cells into Th2 cells. In conclusion, the present study identified key cytokines involved in the pathogenicity of influenza infection, and demonstrated that lethal influenza virus infection induces a mixed Th1/Th2 response.

The Collaborative Cross: A Systems Genetics Resource for Studying Host-Pathogen Interactions

Host genetic variation has a major impact on infectious disease susceptibility. The study of pathogen resistance genes, largely aided by mouse models, has significantly advanced our understanding of infectious disease pathogenesis. The Collaborative Cross (CC), a newly developed multi-parental mouse genetic reference population, serves as a tractable model system to study how pathogens interact with genetically diverse populations. In this review, we summarize progress utilizing the CC as a platform to develop improved models of pathogen-induced disease and to map polymorphic host response loci associated with variation in susceptibility to pathogens.