Influenza A virus infection induces indoleamine 2,3-dioxygenase (IDO) expression and modulates subsequent inflammatory mediators in nasal epithelial cells

Modeling the Immune Response for Pathogenic and Nonpathogenic Orthohantavirus Infections in Human Lung Microvasculature Endothelial Cells

Hantaviruses, genus Orthohantavirus, family Hantaviridae, order Bunyavirales, are negative-sense, single-stranded, tri-segmented RNA viruses that persistently infect rodents, shrews, and moles. Of these, only certain virus species harbored by rodents are pathogenic to humans. Infection begins with inhalation of virus particles into the lung and trafficking to the lung microvascular endothelial cells (LMVEC). The reason why certain rodent-borne hantavirus species are pathogenic has long been hypothesized to be related to their ability to downregulate and dysregulate the immune response as well as increase vascular permeability of infected endothelial cells. We set out to study the temporal dynamics of host immune response modulation in primary human LMVECs following infection by Prospect Hill (nonpathogenic), Andes (pathogenic), and Hantaan (pathogenic) viruses. We measured the level of RNA transcripts for genes representing antiviral, proinflammatory, anti-inflammatory, and metabolic pathways from 12 to 72 h with time points every 12 h. Gene expression analysis in conjunction with mathematical modeling revealed a similar profile for all three viruses in terms of upregulated genes that partake in interferon signaling (TLR3, IRF7, IFNB1), host immune cell recruitment (CXCL10, CXCL11, and CCL5), and host immune response modulation (IDO1). We examined secreted protein levels of IFN-β, CXCL10, CXCL11, CCL5, and IDO in two male and two female primary HLMVEC donors at 48 and 60 h post infection. All three viruses induced similar levels of CCL5, CXCL10, and CXCL11 within a particular donor, and the levels were similar in three of the four donors. All three viruses induced different protein secretion levels for both IFN-β and IDO and secretion levels differed between donors. In conclusion, we show that there was no difference in the transcriptional profiles of key genes in primary HLMVECs following infection by pathogenic and nonpathogenic hantaviruses, with protein secretion levels being more donor-specific than virus-specific.

Nasal nitric oxide is decreased in acute mild COVID-19 and related to viral load

Gaseous nitric oxide levels from the lungs (FeNO) and from the nose (nNO) have been demonstrated to react to acute infection or influenza vaccination. There are no published data on nNO levels during acute COVID-19, but normal levels of FeNO have been reported in one study. Our aim was to assess if acute mild COVID-19 alters nasal or bronchial NO output at the time of acute infection and at a 2-month follow up, and if this is related to symptoms or viral load. This study included 82 subjects with mild acute airway infection who did not need hospitalisation: 43 cases (RT-PCR-positive for SARS-CoV-2 in routine testing from nasopharynx) and 39 age- (+/- 5 years) and gender-matched controls (RT-PCR-negative for SARS-CoV-2). During acute infection, the cases had lower nNO compared to controls (526 [345-688] vs. 773 [677-929] ppb; p<0.001), but after two months, there was no significant difference between the groups (766 [597-965] vs. 893 [739-1066] ppb; p=0.162). There was no difference in FeNO between the groups at either of the visits. Nasal NO correlated with the cycle threshold (Ct) value of the nasopharyngeal RT-PCR test for SARS-CoV-2 (Spearman's rs=0.550; p<0.001), that is, nNO was lower with a higher viral load. Nasal NO output was decreased in acute COVID-19 in relation to higher viral load, suggesting that the type and intensity of inflammatory response affects the release of NO from airway mucosa. In these subjects without significant lower airway involvement, there were no clinically relevant findings regarding FeNO.

Spatial Metabolomics Reveals Localized Impact of Influenza Virus Infection on the Lung Tissue Metabolome

The influenza virus (IAV) is a major cause of respiratory disease, with significant infection increases in pandemic years. Vaccines are a mainstay of IAV prevention but are complicated by IAV’s vast strain diversity and manufacturing and vaccine uptake limitations. While antivirals may be used for treatment of IAV, they are most effective in early stages of the infection, and several virus strains have become drug resistant. Therefore, there is a need for advances in IAV treatment, especially host-directed therapeutics. Given the spatial dynamics of IAV infection and the relationship between viral spatial distribution and disease severity, a spatial approach is necessary to expand our understanding of IAV pathogenesis. We used spatial metabolomics to address this issue. Spatial metabolomics combines liquid chromatography-tandem mass spectrometry of metabolites extracted from systematic organ sections, 3D models, and computational techniques to develop spatial models of metabolite location and their role in organ function and disease pathogenesis. In this project, we analyzed serum and systematically sectioned lung tissue samples from uninfected or infected mice. Spatial mapping of sites of metabolic perturbations revealed significantly lower metabolic perturbation in the trachea compared to other lung tissue sites. Using random forest machine learning, we identified metabolites that responded differently in each lung position based on infection, including specific amino acids, lipids and lipid-like molecules, and nucleosides. These results support the implementation of spatial metabolomics to understand metabolic changes upon respiratory virus infection.

IMPORTANCE The influenza virus is a major health concern. Over 1 billion people become infected annually despite the wide distribution of vaccines, and antiviral agents are insufficient to address current clinical needs. In this study, we used spatial metabolomics to understand changes in the lung and serum metabolome of mice infected with influenza A virus compared to uninfected controls. We determined metabolites altered by infection in specific lung tissue sites and distinguished metabolites perturbed by infection between lung tissue and serum samples. Our findings highlight the utility of a spatial approach to understanding the intersection between the lung metabolome, viral infection, and disease severity. Ultimately, this approach will expand our understanding of respiratory disease pathogenesis.

Disturbed lipid and amino acid metabolisms in COVID-19 patients

The Coronavirus disease 2019 (COVID-19) pandemic is overwhelming the healthcare systems. Identification of systemic reactions underlying COVID-19 will lead to new biomarkers and therapeutic targets for monitoring and early intervention in this viral infection. We performed targeted metabolomics covering up to 630 metabolites within several key metabolic pathways in plasma samples of 20 hospitalized COVID-19 patients and 37 matched controls. Plasma metabolic signatures specifically differentiated severe COVID-19 from control patients. The identified metabolic signatures indicated distinct alterations in both lipid and amino acid metabolisms in COVID-19 compared to control patient plasma. Systems biology-based analyses identified sphingolipid, tryptophan, tyrosine, glutamine, arginine, and arachidonic acid metabolism as mostly impacted pathways in COVID-19 patients. Notably, gamma-aminobutyric acid (GABA) was significantly reduced in COVID-19 patients and GABA plasma levels allowed for stratification of COVID-19 patients with high sensitivity and specificity. The data reveal large metabolic disturbances in COVID-19 patients and suggest use of GABA as potential biomarker and therapeutic target for the infection.

In Vitro Modelling of Respiratory Virus Infections in Human Airway Epithelial Cells - A Systematic Review

Respiratory tract infections (RTI) are a major cause of morbidity and mortality in humans. A large number of RTIs is caused by viruses, often resulting in more severe disease in infants, elderly and the immunocompromised. Upon viral infection, most individuals experience common cold-like symptoms associated with an upper RTI. However, in some cases a severe and sometimes life-threatening lower RTI may develop. Reproducible and scalable in vitro culture models that accurately reflect the human respiratory tract are needed to study interactions between respiratory viruses and the host, and to test novel therapeutic interventions. Multiple in vitro respiratory cell culture systems have been described, but the majority of these are based on immortalized cell lines. Although useful for studying certain aspects of viral infections, such monomorphic, unicellular systems fall short in creating an understanding of the processes that occur at an integrated tissue level. Novel in vitro models involving primary human airway epithelial cells and, more recently, human airway organoids, are now in use. In this review, we describe the evolution of in vitro cell culture systems and their characteristics in the context of viral RTIs, starting from advances after immortalized cell cultures to more recently developed organoid systems. Furthermore, we describe how these models are used in studying virus-host interactions, e.g. tropism and receptor studies as well as interactions with the innate immune system. Finally, we provide an outlook for future developments in this field, including co-factors that mimic the microenvironment in the respiratory tract.

The effects of aging on host resistance and disease tolerance to SARS-CoV-2 infection

The ongoing coronavirus disease 2019 (COVID-19) crisis caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has triggered a large-scale pandemic that is afflicting millions of individuals in over 200 countries. The clinical spectrum caused by SARS-CoV-2 infections can range from asymptomatic infection to mild undifferentiated febrile illness to severe respiratory disease with multiple complications. Elderly patients (aged 60 and above) with comorbidities such as cardiovascular diseases and diabetes mellitus appear to be at highest risk of a severe disease outcome. To protect against pulmonary immunopathology caused by SARS-CoV-2 infection, the host primarily depends on two distinct defense strategies: resistance and disease tolerance. Resistance is the ability of the host to suppress and eliminate incoming viruses. By contrast, disease tolerance refers to host responses that promote host health regardless of their impact on viral replication. Disruption of either resistance or disease tolerance mechanisms or both could underpin predisposition to elevated risk of severe disease during viral infection. Aging can disrupt host resistance and disease tolerance by compromising immune functions, weakening of the unfolded protein response, progressive mitochondrial dysfunction, and altering metabolic processes. A comprehensive understanding of the molecular mechanisms underlying declining host defense in elderly individuals could thus pave the way to provide new opportunities and approaches for the treatment of severe COVID-19.

Nasopharyngeal metabolomics and machine learning approach for the diagnosis of influenza

Background

Respiratory virus infections are significant causes of morbidity and mortality, and may induce host metabolite alterations by infecting respiratory epithelial cells. We investigated the use of liquid chromatography quadrupole time-of-flight mass spectrometry (LC/Q-TOF) combined with machine learning for the diagnosis of influenza infection.

Methods

We analyzed nasopharyngeal swab samples by LC/Q-TOF to identify distinct metabolic signatures for diagnosis of acute illness. Machine learning models were performed for classification, followed by Shapley additive explanation (SHAP) analysis to analyze feature importance and for biomarker discovery.

Findings

A total of 236 samples were tested in the discovery phase by LC/Q-TOF, including 118 positive samples (40 influenza A 2009 H1N1, 39 influenza H3 and 39 influenza B) as well as 118 age and sex-matched negative controls with acute respiratory illness. Analysis showed an area under the receiver operating characteristic curve (AUC) of 1.00 (95% confidence interval [95% CI] 0.99, 1.00), sensitivity of 1.00 (95% CI 0.86, 1.00) and specificity of 0.96 (95% CI 0.81, 0.99). The metabolite most strongly associated with differential classification was pyroglutamic acid. Independent validation of a biomarker signature based on the top 20 differentiating ion features was performed in a prospective cohort of 96 symptomatic individuals including 48 positive samples (24 influenza A 2009 H1N1, 5 influenza H3 and 19 influenza B) and 48 negative samples. Testing performed using a clinically-applicable targeted approach, liquid chromatography triple quadrupole mass spectrometry, showed an AUC of 1.00 (95% CI 0.998, 1.00), sensitivity of 0.94 (95% CI 0.83, 0.98), and specificity of 1.00 (95% CI 0.93, 1.00). Limitations include lack of sample suitability assessment, and need to validate these findings in additional patient populations.

Interpretation

This metabolomic approach has potential for diagnostic applications in infectious diseases testing, including other respiratory viruses, and may eventually be adapted for point-of-care testing.

Inhibition of Tryptophan Catabolism Is Associated With Neuroprotection During Zika Virus Infection

Zika virus (ZIKV) is an arbovirus belonging to Flaviviridae family that emerged as a global health threat due to its association with microcephaly and other severe neurological complications, including Guillain-Barré Syndrome (GBS) and Congenital Zika Syndrome (CZS). ZIKV disease has been linked to neuroinflammation and neuronal cell death. Neurodegenerative processes may be exacerbated by metabolites produced by the kynurenine pathway, an important pathway for the degradation of tryptophan, which induces neuronal dysfunction due to enhanced excitotoxicity. Here, we exploited the hypothesis that ZIKV-induced neurodegeneration can be rescued by blocking a target enzyme of the kynurenine pathway, the Indoleamine 2,3-dioxygenase (IDO-1). RT-PCR analysis showed increased levels of IDO-1 RNA expression in undifferentiated primary neurons isolated from wild type (WT) mice infected by ZIKV ex vivo, as well as in the brain of ZIKV-infected A129 mice. Pharmacological inhibition of IDO-1 enzyme with 1-methyl-D-tryptophan (1-MT), in both in vitro and in vivo systems, led to significant reduction of ZIKV-induced neuronal death without interfering with the ability of ZIKV to replicate in those cells. Furthermore, in vivo analyses using both genetically modified mice (IDO^-/- mice) and A129 mice treated with 1-MT resulted in reduced microgliosis, astrogliosis and Caspase-3 positive cells in the brain of ZIKV-infected A129 mice. Interestingly, increased levels of CCL5 and CXCL-1 chemokines were found in the brain of 1-MT treated-mice. Together, our data indicate that IDO-1 blockade provides a neuroprotective effect against ZIKV-induced neurodegeneration, and this is amenable to inhibition by pharmacological treatment.