Hamster model for post-COVID-19 alveolar regeneration offers an opportunity to understand post-acute sequelae of SARS-CoV-2.

COVID-19 survivors often suffer from post-acute sequelae of SARS-CoV-2 infection (PASC). Current evidence suggests dysregulated alveolar regeneration as a possible explanation for respiratory PASC, which deserves further investigation in a suitable animal model. This study investigates morphological, phenotypical and transcriptomic features of alveolar regeneration in SARS-CoV-2 infected Syrian golden hamsters. We demonstrate that CK8+ alveolar differentiation intermediate (ADI) cells occur following SARS-CoV-2-induced diffuse alveolar damage. A subset of ADI cells shows nuclear accumulation of TP53 at 6- and 14-days post infection (dpi), indicating a prolonged arrest in the ADI state. Transcriptome data show high module scores for pathways involved in cell senescence, epithelial-mesenchymal transition, and angiogenesis in cell clusters with high ADI gene expression. Moreover, we show that multipotent CK14+ airway basal cell progenitors migrate out of terminal bronchioles, aiding alveolar regeneration. At 14 dpi, ADI cells, peribronchiolar proliferates, M2-macrophages, and sub-pleural fibrosis are observed, indicating incomplete alveolar restoration. The results demonstrate that the hamster model reliably phenocopies indicators of a dysregulated alveolar regeneration of COVID-19 patients. The results provide important information on a translational COVID-19 model, which is crucial for its application in future research addressing pathomechanisms of PASC and in testing of prophylactic and therapeutic approaches for this syndrome.

Blood transcriptome responses in patients correlate with severity of COVID-19 disease.

Background: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals display a wide spectrum of disease severity, as defined by the World Health Organization (WHO). One of the main factors underlying this heterogeneity is the host immune response, with severe COVID-19 often associated with a hyperinflammatory state. Aim: Our current study aimed to pinpoint the specific genes and pathways underlying differences in the disease spectrum and outcomes observed, through in-depth analyses of whole blood transcriptomics in a large cohort of COVID-19 participants. Results: All WHO severity levels were well represented and mild and severe disease displaying distinct gene expression profiles. WHO severity levels 1-4 were grouped as mild disease, and signatures from these participants were different from those with WHO severity levels 6-9 classified as severe disease. Severity level 5 (moderate cases) presented a unique transitional gene signature between severity levels 2-4 (mild/moderate) and 6-9 (severe) and hence might represent the turning point for better or worse disease outcome. Gene expression changes are very distinct when comparing mild/moderate or severe cases to healthy controls. In particular, we demonstrated the hallmark down-regulation of adaptive immune response pathways and activation of neutrophil pathways in severe compared to mild/moderate cases, as well as activation of blood coagulation pathways. Conclusions: Our data revealed discrete gene signatures associated with mild, moderate, and severe COVID-19 identifying valuable candidates for future biomarker discovery.

Inhibition of p38 signaling curtails the SARS-CoV-2 induced inflammatory response but retains the IFN-dependent antiviral defense of the lung epithelial barrier.

SARS-CoV-2 is the causative agent of the immune response-driven disease COVID-19 for which new antiviral and anti-inflammatory treatments are urgently needed to reduce recovery time, risk of death and long COVID development. Here, we demonstrate that the immunoregulatory kinase p38 MAPK is activated during viral entry, mediated by the viral spike protein, and drives the harmful virus-induced inflammatory responses. Using primary human lung explants and lung epithelial organoids, we demonstrate that targeting p38 signal transduction with the selective and clinically pre-evaluated inhibitors PH-797804 and VX-702 markedly reduced the expression of the pro-inflammatory cytokines IL6, CXCL8, CXCL10 and TNF-α during infection, while viral replication and the interferon-mediated antiviral response of the lung epithelial barrier were largely maintained. Furthermore, our results reveal a high level of drug synergism of both p38 inhibitors in co-treatments with the nucleoside analogs Remdesivir and Molnupiravir to suppress viral replication of the SARS-CoV-2 variants of concern, revealing an exciting and novel mode of synergistic action of p38 inhibition. These results open new avenues for the improvement of the current treatment strategies for COVID-19.

Blood transcriptome responses in patients correlate with severity of COVID-19 disease

Background Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals display a wide spectrum of disease severity, as defined by the World Health Organization (WHO). One of the main factors underlying this heterogeneity is the host immune response, with severe COVID-19 often associated with a hyperinflammatory state. Aim Our current study aimed to pinpoint the specific genes and pathways underlying differences in the disease spectrum and outcomes observed, through in-depth analyses of whole blood transcriptomics in a large cohort of COVID-19 participants. Results All WHO severity levels were well represented and mild and severe disease displaying distinct gene expression profiles. WHO severity levels 1-4 were grouped as mild disease, and signatures from these participants were different from those with WHO severity levels 6-9 classified as severe disease. Severity level 5 (moderate cases) presented a unique transitional gene signature between severity levels 2-4 (mild/moderate) and 6-9 (severe) and hence might represent the turning point for better or worse disease outcome. Gene expression changes are very distinct when comparing mild/moderate or severe cases to healthy controls. In particular, we demonstrated the hallmark down-regulation of adaptive immune response pathways and activation of neutrophil pathways in severe compared to mild/moderate cases, as well as activation of blood coagulation pathways. Conclusions Our data revealed discrete gene signatures associated with mild, moderate, and severe COVID-19 identifying valuable candidates for future biomarker discovery.

Pathway and Network Analyses Identify Growth Factor Signaling and MMP9 as Potential Mediators of Mitochondrial Dysfunction in Severe COVID-19.

Patients with preexisting metabolic disorders such as diabetes are at a higher risk of developing severe coronavirus disease 2019 (COVID-19). Mitochondrion, the very organelle that controls cellular metabolism, holds the key to understanding disease progression at the cellular level. Our current study aimed to understand how cellular metabolism contributes to COVID-19 outcomes. Metacore pathway enrichment analyses on differentially expressed genes (encoded by both mitochondrial and nuclear deoxyribonucleic acid (DNA)) involved in cellular metabolism, regulation of mitochondrial respiration and organization, and apoptosis, was performed on RNA sequencing (RNASeq) data from blood samples collected from healthy controls and patients with mild/moderate or severe COVID-19. Genes from the enriched pathways were analyzed by network analysis to uncover interactions among them and up- or downstream genes within each pathway. Compared to the mild/moderate COVID-19, the upregulation of a myriad of growth factor and cell cycle signaling pathways, with concomitant downregulation of interferon signaling pathways, were observed in the severe group. Matrix metallopeptidase 9 (MMP9) was found in five of the top 10 upregulated pathways, indicating its potential as therapeutic target against COVID-19. In summary, our data demonstrates aberrant activation of endocrine signaling in severe COVID-19, and its implication in immune and metabolic dysfunction.

Itaconate and derivatives reduce interferon responses and inflammation in influenza A virus infection.

Excessive inflammation is a major cause of morbidity and mortality in many viral infections including influenza. Therefore, there is a need for therapeutic interventions that dampen and redirect inflammatory responses and, ideally, exert antiviral effects. Itaconate is an immunomodulatory metabolite which also reprograms cell metabolism and inflammatory responses when applied exogenously. We evaluated effects of endogenous itaconate and exogenous application of itaconate and its variants dimethyl- and 4-octyl-itaconate (DI, 4OI) on host responses to influenza A virus (IAV). Infection induced expression of ACOD1, the enzyme catalyzing itaconate synthesis, in monocytes and macrophages, which correlated with viral replication and was abrogated by DI and 4OI treatment. In IAV-infected mice, pulmonary inflammation and weight loss were greater in Acod1-/- than in wild-type mice, and DI treatment reduced pulmonary inflammation and mortality. The compounds reversed infection-triggered interferon responses and modulated inflammation in human cells supporting non-productive and productive infection, in peripheral blood mononuclear cells, and in human lung tissue. All three itaconates reduced ROS levels and STAT1 phosphorylation, whereas AKT phosphorylation was reduced by 4OI and DI but increased by itaconate. Single-cell RNA sequencing identified monocytes as the main target of infection and the exclusive source of ACOD1 mRNA in peripheral blood. DI treatment silenced IFN-responses predominantly in monocytes, but also in lymphocytes and natural killer cells. Ectopic synthesis of itaconate in A549 cells, which do not physiologically express ACOD1, reduced infection-driven inflammation, and DI reduced IAV- and IFNγ-induced CXCL10 expression in murine macrophages independent of the presence of endogenous ACOD1. The compounds differed greatly in their effects on cellular gene homeostasis and released cytokines/chemokines, but all three markedly reduced release of the pro-inflammatory chemokines CXCL10 (IP-10) and CCL2 (MCP-1). Viral replication did not increase under treatment despite the dramatically repressed IFN responses. In fact, 4OI strongly inhibited viral transcription in peripheral blood mononuclear cells, and the compounds reduced viral titers (4OI>Ita>DI) in A549 cells whereas viral transcription was unaffected. Taken together, these results reveal itaconates as immunomodulatory and antiviral interventions for influenza virus infection.

Genetic Dissection of the Regulatory Mechanisms of Ace2 in the Infected Mouse Lung.

Acute lung injury (ALI) is an important cause of morbidity and mortality after viral infections, including influenza A virus H1N1, SARS-CoV, MERS-CoV, and SARS-CoV-2. The angiotensin I converting enzyme 2 (ACE2) is a key host membrane-bound protein that modulates ALI induced by viral infection, pulmonary acid aspiration, and sepsis. However, the contributions of ACE2 sequence variants to individual differences in disease risk and severity after viral infection are not understood. In this study, we quantified H1N1 influenza-infected lung transcriptomes across a family of 41 BXD recombinant inbred strains of mice and both parents-C57BL/6J and DBA/2J. In response to infection Ace2 mRNA levels decreased significantly for both parental strains and the expression levels was associated with disease severity (body weight loss) and viral load (expression levels of viral NA segment) across the BXD family members. Pulmonary RNA-seq for 43 lines was analyzed using weighted gene co-expression network analysis (WGCNA) and Bayesian network approaches. Ace2 not only participated in virus-induced ALI by interacting with TNF, MAPK, and NOTCH signaling pathways, but was also linked with high confidence to gene products that have important functions in the pulmonary epithelium, including Rnf128, Muc5b, and Tmprss2. Comparable sets of transcripts were also highlighted in parallel studies of human SARS-CoV-infected primary human airway epithelial cells. Using conventional mapping methods, we determined that weight loss at two and three days after viral infection maps to chromosome X-the location of Ace2. This finding motivated the hierarchical Bayesian network analysis, which defined molecular endophenotypes of lung infection linked to Ace2 expression and to a key disease outcome. Core members of this Bayesian network include Ace2, Atf4, Csf2, Cxcl2, Lif, Maml3, Muc5b, Reg3g, Ripk3, and Traf3. Collectively, these findings define a causally-rooted Ace2 modulatory network relevant to host response to viral infection and identify potential therapeutic targets for virus-induced respiratory diseases, including those caused by influenza and coronaviruses.

Prospective validation study of prognostic biomarkers to predict adverse outcomes in patients with COVID-19: a study protocol.

INTRODUCTION: Accurate triage is an important first step to effectively manage the clinical treatment of severe cases in a pandemic outbreak. In the current COVID-19 global pandemic, there is a lack of reliable clinical tools to assist clinicians to perform accurate triage. Host response biomarkers have recently shown promise in risk stratification of disease progression; however, the role of these biomarkers in predicting disease progression in patients with COVID-19 is unknown. Here, we present a protocol outlining a prospective validation study to evaluate the biomarkers' performance in predicting clinical outcomes of patients with COVID-19. METHODS AND ANALYSIS: This prospective validation study assesses patients infected with COVID-19, in whom blood samples are prospectively collected. Recruited patients include a range of infection severity from asymptomatic to critically ill patients, recruited from the community, outpatient clinics, emergency departments and hospitals. Study samples consist of peripheral blood samples collected into RNA-preserving (PAXgene/Tempus) tubes on patient presentation or immediately on study enrolment. Real-time PCR (RT-PCR) will be performed on total RNA extracted from collected blood samples using primers specific to host response gene expression biomarkers that have been previously identified in studies of respiratory viral infections. The RT-PCR data will be analysed to assess the diagnostic performance of individual biomarkers in predicting COVID-19-related outcomes, such as viral pneumonia, acute respiratory distress syndrome or bacterial pneumonia. Biomarker performance will be evaluated using sensitivity, specificity, positive and negative predictive values, likelihood ratios and area under the receiver operating characteristic curve. ETHICS AND DISSEMINATION: This research protocol aims to study the host response gene expression biomarkers in severe respiratory viral infections with a pandemic potential (COVID-19). It has been approved by the local ethics committee with approval number 2020/ETH00886. The results of this project will be disseminated in international peer-reviewed scientific journals.