Inactivation of SARS-CoV-2 in clinical exhaled breath condensate samples for metabolomic analysis

Metabolic signatures of acute respiratory distress syndrome: COVID versus non-COVID

Acute respiratory distress syndrome (ARDS) is a fatal pulmonary disorder characterized by severe hypoxia and inflammation. ARDS is commonly triggered by systemic and pulmonary infections, with bacteria and viruses. Notable pathogens include Pseudomonas aeruginosa, Streptococcus aureus, Enterobacter species, coronaviruses, influenza viruses, and herpesviruses. COVID-19 ARDS represents the latest etiological phenotype of the disease. The pathogenesis of ARDS caused by bacteria and viruses exhibits variations in host immune responses and lung mesenchymal injury. We postulate that the systemic and pulmonary metabolomics profiles of ARDS induced by COVID-19 pathogens may exhibit distinctions compared with those induced by other infectious agents. This review aims to compare metabolic signatures in blood and lung specimens specifically within the context of ARDS. Both prevalent and phenotype-specific metabolomic signatures, including but not limited to glycolysis, ketone body production, lipid oxidation, and dysregulation of the kynurenine pathways, were thoroughly examined in this review. The distinctions in metabolic signatures between COVID-19 and non-COVID ARDS have the potential to reveal new biomarkers, elucidate pathogenic mechanisms, identify druggable targets, and facilitate differential diagnosis in the future.

Oxylipin concentration shift in exhaled breath condensate (EBC) of SARS-CoV-2 infected patients

Infection of airway epithelial cells with severe acute respiratory coronavirus 2 (SARS-CoV-2) can lead to severe respiratory tract damage and lung injury with hypoxia. It is challenging to sample the lower airways non-invasively and the capability to identify a highly representative specimen that can be collected in a non-invasive way would provide opportunities to investigate metabolomic consequences of COVID-19 disease. In the present study, we performed a targeted metabolomic approach using liquid chromatography coupled with high resolution chromatography (LC-MS) on exhaled breath condensate (EBC) collected from hospitalized COVID-19 patients (COVID+) and negative controls, both non-hospitalized and hospitalized for other reasons (COVID-). We were able to noninvasively identify and quantify inflammatory oxylipin shifts and dysregulation that may ultimately be used to monitor COVID-19 disease progression or severity and response to therapy. We also expected EBC-based biochemical oxylipin changes associated with COVID-19 host response to infection. The results indicated ten targeted oxylipins showing significative differences between SAR-CoV-2 infected EBC samples and negative control subjects. These compounds were prostaglandins A2 and D2, LXA4, 5-HETE, 12-HETE, 15-HETE, 5-HEPE, 9-HODE, 13-oxoODE and 19(20)-EpDPA, which are associated with specific pathways (i.e. P450, COX, 15-LOX) related to inflammatory and oxidative stress processes. Moreover, all these compounds were up-regulated by COVID+, meaning their concentrations were higher in subjects with SAR-CoV-2 infection. Given that many COVID-19 symptoms are inflammatory in nature, this is interesting insight into the pathophysiology of the disease. Breath monitoring of these and other EBC metabolites presents an interesting opportunity to monitor key indicators of disease progression and severity.

Predominant SARS-CoV-2 variant impacts accuracy when screening for infection using exhaled breath vapor

BACKGROUND

New technologies with novel and ambitious approaches are being developed to diagnose or screen for SARS-CoV-2, including breath tests. The US FDA approved the first breath test for COVID-19 under emergency use authorization in April 2022. Most breath-based assays measure volatile metabolites exhaled by persons to identify a host response to infection. We hypothesized that the breathprint of COVID-19 fluctuated after Omicron became the primary variant of transmission over the Delta variant.

METHODS

We collected breath samples from 142 persons with and without a confirmed COVID-19 infection during the Delta and Omicron waves. Breath samples were analyzed by gas chromatography-mass spectrometry.

RESULTS

Here we show that based on 63 exhaled compounds, a general COVID-19 model had an accuracy of 0.73 ± 0.06, which improved to 0.82 ± 0.12 when modeling only the Delta wave, and 0.84 ± 0.06 for the Omicron wave. The specificity improved for the Delta and Omicron models (0.79 ± 0.21 and 0.74 ± 0.12, respectively) relative to the general model (0.61 ± 0.13).

CONCLUSIONS

We report that the volatile signature of COVID-19 in breath differs between the Delta-predominant and Omicron-predominant variant waves, and accuracies improve when samples from these waves are modeled separately rather than as one universal approach. Our findings have important implications for groups developing breath-based assays for COVID-19 and other respiratory pathogens, as the host response to infection may significantly differ depending on variants or subtypes.

Metabolic profile of exhaled breath condensate from the pneumonia patients

PURPOSE OF THE STUDY

Exhaled breath condensate (EBC) is increasingly being used for disease diagnosis and environmental exposure assessment as a noninvasive method reducing the risk of exposure. The purpose of this study was to investigate the application of a new sample type of EBC in pneumonia by metabolomics and to explore differential metabolites and potential metabolic pathways.

MATERIALS AND METHODS

A case-control study was performed at the Peking University Third Hospital from August to December 2020. C-MS/MS analyses were performed on EBC samples using a UHPLC system.

RESULTS

Totally 22 patients with pneumonia and 24 healthy controls were recruited. Using untargeted metabolomics based on LC-MS/MS analysis, 25 kinds of differential metabolites were found. Through a comprehensive analysis of the pathways in which the differential metabolites were located, the key pathway with the highest correlation with the difference of metabolites was taurine and hypotaurine metabolism.

CONCLUSIONS

The study implicates that the hypotaurine/taurine metabolic pathway may play a role on the development of pneumonia through metabolism analysis on EBC and the 3-Sulfinoalanine may be used as a biomarker in the diagnosis of pneumonia.

Altered Expression of ACE2 and Co-receptors of SARS-CoV-2 in the Gut Mucosa of the SIV Model of HIV/AIDS

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the cause of the COVID-19 pandemic, is initiated by its binding to the ACE2 receptor and other co-receptors on mucosal epithelial cells. Variable outcomes of the infection and disease severity can be influenced by pre-existing risk factors. Human immunodeficiency virus (HIV), the cause of AIDS, targets the gut mucosal immune system and impairs epithelial barriers and mucosal immunity. We sought to determine the impact and mechanisms of pre-existing HIV infection increasing mucosal vulnerability to SARS-CoV-2 infection and disease. We investigated changes in the expression of ACE2 and other SARS-CoV-2 receptors and related pathways in virally inflamed gut by using the SIV infected rhesus macaque model of HIV/AIDS. Immunohistochemical analysis showed sustained/enhanced ACE2 expression in the gut epithelium of SIV infected animals compared to uninfected controls. Gut mucosal transcriptomic analysis demonstrated enhanced expression of host factors that support SARS-CoV-2 entry, replication, and infection. Metabolomic analysis of gut luminal contents revealed the impact of SIV infection as demonstrated by impaired mitochondrial function and decreased immune response, which render the host more vulnerable to other pathogens. In summary, SIV infection resulted in sustained or increased ACE2 expression in an inflamed and immune-impaired gut mucosal microenvironment. Collectively, these mucosal changes increase the susceptibility to SARS-CoV-2 infection and disease severity and result in ineffective viral clearance. Our study highlights the use of the SIV model of AIDS to fill the knowledge gap of the enteric mechanisms of co-infections as risk factors for poor disease outcomes, generation of new viral variants and immune escape in COVID-19.