Evidence for vagal sensory neural involvement in influenza pathogenesis and disease.

Influenza A virus (IAV) is a common respiratory pathogen and a global cause of significant and often severe morbidity. Although inflammatory immune responses to IAV infections are well described, little is known about how neuroimmune processes contribute to IAV pathogenesis. In the present study, we employed surgical, genetic, and pharmacological approaches to manipulate pulmonary vagal sensory neuron innervation and activity in the lungs to explore potential crosstalk between pulmonary sensory neurons and immune processes. Intranasal inoculation of mice with H1N1 strains of IAV resulted in stereotypical antiviral lung inflammation and tissue pathology, changes in breathing, loss of body weight and other clinical signs of severe IAV disease. Unilateral cervical vagotomy and genetic ablation of pulmonary vagal sensory neurons had a moderate effect on the pulmonary inflammation induced by IAV infection, but significantly worsened clinical disease presentation. Inhibition of pulmonary vagal sensory neuron activity via inhalation of the charged sodium channel blocker, QX-314, resulted in a moderate decrease in lung pathology, but again this was accompanied by a paradoxical worsening of clinical signs. Notably, vagal sensory ganglia neuroinflammation was induced by IAV infection and this was significantly potentiated by QX-314 administration. This vagal ganglia hyperinflammation was characterized by alterations in IAV-induced host defense gene expression, increased neuropeptide gene and protein expression, and an increase in the number of inflammatory cells present within the ganglia. These data suggest that pulmonary vagal sensory neurons play a role in the regulation of the inflammatory process during IAV infection and suggest that vagal neuroinflammation may be an important contributor to IAV pathogenesis and clinical presentation. Targeting these pathways could offer therapeutic opportunities to treat IAV-induced morbidity and mortality.

Increasing HbA1c is associated with reduced CD8+ T cell functionality in response to influenza virus in a TCR-dependent manner in individuals with diabetes mellitus.

Diabetes mellitus is on the rise globally and is a known susceptibility factor for severe influenza virus infections. However, the mechanisms by which diabetes increases the severity of an influenza virus infection are yet to be fully defined. Diabetes mellitus is hallmarked by high glucose concentrations in the blood. We hypothesized that these high glucose concentrations affect the functionality of CD8+ T cells, which play a key role eliminating virus-infected cells and have been shown to decrease influenza disease severity. To study the effect of hyperglycemia on CD8+ T cell function, we stimulated peripheral blood mononuclear cells (PBMCs) from donors with and without diabetes with influenza A virus, anti-CD3/anti-CD28-coated beads, PMA and ionomycin (PMA/I), or an influenza viral peptide pool. After stimulation, cells were assessed for functionality [as defined by expression of IFN-γ, TNF-α, macrophage inflammatory protein (MIP)-1ß, and lysosomal-associated membrane protein-1 (CD107a)] using flow cytometry. Our results showed that increasing HbA1c correlated with a reduction in TNF-α production by CD8+ T cells in response to influenza stimulation in a TCR-specific manner. This was not associated with any changes to CD8+ T cell subsets. We conclude that hyperglycemia impairs CD8+ T cell function to influenza virus infection, which may be linked with the increased risk of severe influenza in patients with diabetes.

Nasal Delivery of Haemophilus haemolyticus Is Safe, Reduces Influenza Severity, and Prevents Development of Otitis Media in Mice.

BACKGROUND: Despite vaccination, influenza and otitis media (OM) remain leading causes of illness. We previously found that the human respiratory commensal Haemophilus haemolyticus prevents bacterial infection in vitro and that the related murine commensal Muribacter muris delays OM development in mice. The observation that M muris pretreatment reduced lung influenza titer and inflammation suggests that these bacteria could be exploited for protection against influenza/OM. METHODS: Safety and efficacy of intranasal H haemolyticus at 5 × 107 colony-forming units (CFU) was tested in female BALB/cARC mice using an influenza model and influenza-driven nontypeable Haemophilus influenzae (NTHi) OM model. Weight, symptoms, viral/bacterial levels, and immune responses were measured. RESULTS: Intranasal delivery of H haemolyticus was safe and reduced severity of influenza, with quicker recovery, reduced inflammation, and lower lung influenza virus titers (up to 8-fold decrease vs placebo; P ≤ .01). Haemophilus haemolyticus reduced NTHi colonization density (day 5 median NTHi CFU/mL = 1.79 × 103 in treatment group vs 4.04 × 104 in placebo, P = .041; day 7 median NTHi CFU/mL = 28.18 vs 1.03 × 104; P = .028) and prevented OM (17% OM in treatment group, 83% in placebo group; P = .015). CONCLUSIONS: Haemophilus haemolyticus has potential as a live biotherapeutic for prevention or early treatment of influenza and influenza-driven NTHi OM. Additional studies will deem whether these findings translate to humans and other respiratory infections.

Host transcriptomics and machine learning for secondary bacterial infections in patients with COVID-19: a prospective, observational cohort study.

BACKGROUND: Viral respiratory tract infections are frequently complicated by secondary bacterial infections. This study aimed to use machine learning to predict the risk of bacterial superinfection in SARS-CoV-2-positive individuals. METHODS: In this prospective, multicentre, observational cohort study done in nine centres in six countries (Australia, Indonesia, Singapore, Italy, Czechia, and France) blood samples and RNA sequencing were used to develop a robust model of predicting secondary bacterial infections in the respiratory tract of patients with COVID-19. Eligible participants were older than 18 years, had known or suspected COVID-19, and symptoms of a recent respiratory infection. A control cohort of participants without COVID-19 who were older than 18 years and with no infection symptoms was also recruited from one Australian centre. In the pre-analysis phase, data were filtered to include only individuals with complete blood transcriptomics and patient data (ie, age, sex, location, and WHO severity score at the time of sample collection). The dataset was then divided randomly (4:1) into a training set (80%) and a test set (20%). Gene expression data in the training set and control cohort were used for differential expression analysis. Differentially expressed genes, along with WHO severity score, location, age, and sex, were used for feature selection with least absolute shrinkage and selection operator (LASSO) in the training set. For LASSO analysis, samples were excluded if gene expression data were not obtained at study admission, no longitudinal clinical information was available, a bacterial infection at the time of study admission was present, or a fungal infection in the absence of a bacterial infection was detected. LASSO regression was performed using three subsets of predictor variables: patient data alone, gene expression data alone, or a combination of patient data and gene expression data. The accuracy of the resultant models was tested on data from the test set. FINDINGS: Between March, 2020, and October, 2021, we recruited 536 SARS-CoV-2-positive individuals and between June, 2013, and January, 2020, we recruited 74 participants into the control cohort. After prefiltering analysis and other exclusions, samples from 158 individuals were analysed in the training set and 47 in the test set. The expression of seven host genes (DAPP1, CST3, FGL2, GCH1, CIITA, UPP1, and RN7SL1) in the blood at the time of study admission was identified by LASSO as predictive of the risk of developing a secondary bacterial infection of the respiratory tract more than 24 h after study admission. Specifically, the expression of these genes in combination with a patient's WHO severity score at the time of study enrolment resulted in an area under the curve of 0·98 (95% CI 0·89-1·00), a true positive rate (sensitivity) of 1·00 (95% CI 1·00-1·00), and a true negative rate (specificity) of 0·94 (95% CI 0·89-1·00) in the test cohort. The combination of patient data and host transcriptomics at hospital admission identified all seven individuals in the training and test sets who developed a bacterial infection of the respiratory tract 5-9 days after hospital admission. INTERPRETATION: These data raise the possibility that host transcriptomics at the time of clinical presentation, together with machine learning, can forward predict the risk of secondary bacterial infections and allow for the more targeted use of antibiotics in viral infection. FUNDING: Snow Medical Research Foundation, the National Health and Medical Research Council, the Jack Ma Foundation, the Helmholtz-Association, the A2 Milk Company, National Institute of Allergy and Infectious Disease, and the Fondazione AIRC Associazione Italiana per la Ricerca contro il Cancro.

In situ single-cell profiling sheds light on IFI27 localisation during SARS-CoV-2 infection.

The utilization of single-cell resolved spatial transcriptomics to delineate immune responses during SARS-CoV-2 infection was able to identify M1 macrophages to have elevated expression of IFI27 in areas of infection.

Whole transcriptome profiling of placental pathobiology in SARS-CoV-2 pregnancies identifies placental dysfunction signatures.

Objectives: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus infection in pregnancy is associated with higher incidence of placental dysfunction, referred to by a few studies as a 'preeclampsia-like syndrome'. However, the mechanisms underpinning SARS-CoV-2-induced placental malfunction are still unclear. Here, we investigated whether the transcriptional architecture of the placenta is altered in response to SARS-CoV-2 infection. Methods: We utilised whole-transcriptome, digital spatial profiling, to examine gene expression patterns in placental tissues from participants who contracted SARS-CoV-2 in the third trimester of their pregnancy (n = 7) and those collected prior to the start of the coronavirus disease 2019 (COVID-19) pandemic (n = 9). Results: Through comprehensive spatial transcriptomic analyses of the trophoblast and villous core stromal cell subpopulations in the placenta, we identified SARS-CoV-2 to promote signatures associated with hypoxia and placental dysfunction. Notably, genes associated with vasodilation (NOS3), oxidative stress (GDF15, CRH) and preeclampsia (FLT1, EGFR, KISS1, PAPPA2) were enriched with SARS-CoV-2. Pathways related to increased nutrient uptake, vascular tension, hypertension and inflammation were also enriched in SARS-CoV-2 samples compared to uninfected controls. Conclusions: Our findings demonstrate the utility of spatially resolved transcriptomic analysis in defining the underlying pathogenic mechanisms of SARS-CoV-2 in pregnancy, particularly its role in placental dysfunction. Furthermore, this study highlights the significance of digital spatial profiling in mapping the intricate crosstalk between trophoblasts and villous core stromal cells, thus shedding light on pathways associated with placental dysfunction in pregnancies with SARS-CoV-2 infection.