SARS-CoV-2 Infection-Induced Alterations in ADAR Editing Patterns Differ Between Patients Who Developed Critical Compared to Non-Critical COVID-19

Identification of a set of endogenous retroviruses linked to IL-1-mediated immunopathology in severe COVID-19

SARS-CoV-2 infection triggers expression of endogenous retroviruses (ERVs), but whether this persists during COVID-19 and contributes to disease severity has not been well characterized. In this study, we analyzed bulk and single-cell RNA-sequencing datasets from multiple cohorts of severe COVID-19 patients to investigate the role of ERVs in COVID-19 immunopathology. We identified 33 differentially expressed proviral ERV loci in severe COVID-19 compared with healthy individuals (“severe COVID-19 signature ERVs”). ERV activation was associated with dysregulation of ERV epigenetic regulators, and their expression strongly correlated with key inflammatory pathways implicated in severe COVID-19, including neutrophil degranulation, interleukin signaling, and inflammasome activation. Anakinra treatment reversed activation of signature ERVs. Six signature ERVs were specific to intensive care unit (ICU) admission and significantly correlated with hospital-free days at day 45 (HFD-45). At the single-cell level, signature ERVs were significantly upregulated in erythroid-like and erythroid precursor cells and macrophages of patients with severe disease. Within these cells, we found evidence of ERV-associated differences in inflammatory gene expression, whereby cells expressing signature ERVs showed heightened expression of innate immune genes compared with cells not expressing these ERVs. Together, our study unmasked specific ERV loci activated in severe COVID-19 that are linked to immunopathology.

Persistent expression of myeloid lineage markers in resident and circulating T cells induced by SARS-CoV-2 infection 2328943

Coronavirus disease 2019 (COVID-19) is an acute respiratory disease caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Impaired and dysregulated host immunities, such as impaired coordination and disruption of CD4/CD8 T-cell-mediated virus-specific adaptive immune responses to SARS-CoV-2, have been hypothesized as age-related risk factors in COVID-19 disease severity. However, the characteristics and heterogeneity of CD4/CD8 T cell subsets that respond to SARS-CoV-2 remain elusive. In the present study, we focused on investigating those subsets and there role in COVID-19 infection. We established an age-dependent COVID-19 model by infecting middle-age mice (7-8 months old) or young mice (6-8 weeks old) with 100 or 500pfu of a mouse adapted SARS-CoV-2 virus (SARS2-N501YMA30). Lung, spleen tissues and blood harvested at 60 and 90 days post infection (dpi) were subjected to flow-cytometry and CyTOF for CD4/CD8 T cell profiling. Data was analyzed using FlowJo_v10.10.0 software. Only middle-age mice showed an average weight loss of 10% and 20% in low (100pfu) and high (500pfu) viral dose infected group respectively. Immune profiling revealed increase in the CD11b, CD11c expressing CD4/CD8 T cell subsets in the infected mice. These infection-prompted subsets increased significantly in middle-age mice and were found to contribute in effector functions as well as consist T cell-mediated immune memory, characterized by higher Granzyme B and Perforin expression. This study characterizes CD11b, CD11c expressing CD4/CD8 T cell subsets with potent antiviral effects, which is in accord with the reported data of association of CD11b and CD11c T cell with increased cytotoxic activity in other viral infections like Influenza, RSV. Further analysis of these immune cells is underway to better understand their roles in driving protective or pathogenic immune responses upon SARS-CoV-2 infection in mice. Functional Microbiomics, Inflammation and Pathogenicity- COBRE pilot grant (OGMB220226F1) (JZ); UofL starting package (F1256, F1260) (JZ) Viral Immunology (VIR)

Cross-Cohort Computational Inference of miRNA-mRNA Regulatory Programs from scRNA-seq in Convalescent Monocytes Associated with Prior COVID-19 Severity

Severe coronavirus disease 2019 (COVID-19) is characterized by acute immune dysregulation, with monocytes playing a central role in driving inflammation and disease severity. However, the transcriptional and post-transcriptional regulatory mechanisms underlying monocyte dysfunction in severe COVID-19 remain unexplored. In the study, an integrative analysis of paired bulk RNA-seq and miRNA-seq datasets was performed together with independent single-cell RNA-seq (scRNA-seq) data from convalescent individuals with a history of ICU or non-ICU COVID-19. Pooled cell proportions descriptively indicated a higher proportion of classical monocytes and lower proportions of non-classical monocytes, B cells and dendritic cells in individuals with a history of ICU disease; however, none of these differences was statistically significant in patient-level analyses after multiple-testing correction. Using the miRSCAPE framework, miRNA expression was inferred at single-cell resolution and identified distinct cluster-specific inferred miRNA expression patterns. Differential expression analysis of classical monocyte populations identified 284 nominally significant differentially expressed genes between convalescent ICU and non-ICU samples. Integration of miRNA-mRNA correlation analysis with experimentally validated interactions and independent assessment highlighted a focused regulatory network centered on ZMAT3, RHOB and HLA-DQA1. Host–pathogen interaction analysis identified database-supported SARS-CoV-2-host interactions involving ORF3a-RHOB and nucleoprotein-RHPN2, with additional host–host interactions connecting RHPN2, HLA-C and HLA-DQA1. Collectively, these findings provide a computational framework for investigating inferred miRNA associations of monocyte inflammatory pathways associated with prior COVID-19 severity and highlight regulatory interactions that warrant further experimental validation.

Divergent lipid utilization strategies of SARS-CoV-2 and MERS-CoV revealed by comparative multi-omics profiling of infected mouse lung tissues

Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome (MERS-CoV), cause respiratory infections with distinct clinical outcomes and case fatality rates. However, the molecular basis of these differences remains unclear. In this study, we sought to define virus-specific host metabolic programs by directly comparing multiomics profiles of the lungs of lethally infected mouse models. We performed integrated multiomics analyses, including untargeted metabolomics, transcriptomics, and targeted lipidomics, of lung tissues from human angiotensin-converting enzyme 2 (hiACE2)-human dipeptidyl peptidase 4 (hDPP4) double-knock-in (DKI) mice infected in SARS-CoV-2 or MERS-CoV. Data Integration Analysis and Biomarker discovery using Latent cOmponents (DIABLO) was applied across all three omics layers to identify key distinguishing molecular patterns. Additionally, in vitro lipid droplet kinetics were examined in infected Vero E6 cells to validate temporal differences in lipid remodeling. We identified two distinct strategies for lipid utilization. SARS-CoV-2 infection showed strong activation of energy and amino acid metabolism at an early stage of infection (3 days post infection, DPI), whereas MERS-CoV infection was characterized by sustained alterations in lipid and nucleotide metabolism. Integrative DIABLO analysis of all three omics layers revealed that the key distinguishing features clustered into virus-specific molecular signatures: a triacylglycerol–lipid droplet–interferon axis for SARS-CoV-2 and a phospholipid–sphingolipid–membrane hub for MERS-CoV. In vitro lipid droplet kinetics in infected Vero E6 cells confirmed this temporal difference, with SARS-CoV-2 peaking earlier than MERS-CoV. These findings show that β-CoVs exploit host lipid metabolism through virus-specific and time-dependent remodeling programs, providing a framework for understanding differential pathogenesis and developing host-directed antiviral strategies.

RNAemia and Severe COVID-19: Candidate Treatment Targets Identified Through Transcriptomics.

Association Study of IFIH1/MDA5 Gene Variants with COVID-19 in Moroccan Patients