RNA-sequencing unravels unique host-response to infection with SARS-CoV-2

Introduction/Aim: As the causative agent of COVID-19, SARS-CoV-2 remains a global cause for concern. Compared to other highly pathogenic coronaviruses (SARS-CoV and MERS-CoV), SARS-CoV-2 exhibits stronger transmissibility but less lethality, indicating that SARS-CoV-2 displays unique characteristics, despite the partial genomic proximity. Thus, we aim to employ RNA sequencing to define transcriptional differences in epithelial responses following infection with SARS-CoV-2 compared to pathogenic SARS-CoV and MERS-CoV, and low pathogenic HCoV-229E. Method(s): Primary human bronchial epithelial cells (PBEC) were differentiated for 6 weeks at the air-liquid interface (ALI) before parallel infection by the 4 different coronaviruses (n = 4). After infection following apical application of coronaviruses at low dose (MOI 0.1), cells were harvested for bulk RNA sequencing. Gene were considered significant with a fold change (FC) > 2 and false discovery rate of FDR < 0.05. Inhibitor experiments were conducted on CALU-3 cells using DIM-C-pPhOH 10 muM (NR4A1 antagonist), Sp600125 10 muM (JNK inhibitor), T-5224 10 muM (AP-1 transcription factor inhibitor) and Cytosporone B (CsB 5 muM;NR4A1 agonist) preincubated for 1 h with these compounds and subsequently infected with SARS-CoV-2 or MERS-CoV (MOI of 1). Samples were collect 24 h later for PCR. Result(s): PCR and RNA-Seq demonstrated that all tested coronaviruses efficiently infected ALI-PBEC and replicated over 72 h (p < 0.05). RNA sequencing analysis revealed that infection with SARS-CoV, MERS-CoV and HCoV-229E resulted in largely similar transcriptional responses by the epithelial cells. However, whereas infection with these viruses was accompanied by an increased expression of genes associated with JNK/AP-1 signalling, including FOS, FOSB and NR4A1 (FC > 1, FDR < 0.05), no such increase was observed following SARS-CoV-2 infection. Further, we found that an NR4A1 antagonist reduced viral replication of MERS and SARs-CoV-2 100-fold in Calu-3 cells. Conclusion(s): In conclusion, these data suggest that SARS-CoV-2-infected ALI-PBEC exhibit a unique transcriptional response compared to other coronaviruses, which might relate to the pathogenicity of the virus.

RNA sequencing unravels unique host transcriptional responses to infection with SARS-CoV-2 in well differentiated primary human bronchial epithelial cells compared to other coronaviruses

As the causative agent of COVID-19, SARS-CoV-2 remains a global cause for concern. Compared to other highly pathogenic coronaviruses (SARS-CoV and MERS-CoV), SARS-CoV-2 exhibits stronger transmissibility but less lethality, indicating that SARS-CoV-2 displays unique characteristics, despite the partial genomic proximity. Thus, we aim to employ RNA sequencing to define transcriptional differences in epithelial responses following infection with SARS-CoV-2 compared to pathogenic SARS-CoV and MERS-CoV, and low pathogenic HCoV-229E. Primary human bronchial epithelial cells (PBEC) were differentiated for 6 weeks at the air-liquid interface (ALI) before parallel infection by the 4 different coronaviruses. After infection following apical application of coronaviruses at low dose, cells were harvested for bulk RNA sequencing. Results demonstrated that all tested coronaviruses efficiently infected ALI-PBEC. RNA sequencing analysis revealed that infection with SARS-CoV, MERS-CoV and HCoV-229E resulted in largely similar transcriptional responses by the epithelial cells. However, whereas infection with these viruses was accompanied by an increased expression of genes associated with JNK/AP-1 signalling, including FOS, FOSB and NR4A1, no such increase was observed following SARS-CoV-2 infection. Further, preliminary experiments indicated that an NR4A1 antagonist reduced viral replication in Calu-3 cells. In conclusion, these data suggest that SARS-CoV2-infected ALI-PBEC exhibit a unique transcriptional response compared to other coronaviruses, which might relate to the pathogenicity of the virus.

Single-cell RNA-sequencing for immune profiling of SARS-CoV2 vaccine response in healthy individuals and patients with precursor plasma cell malignancies

Introduction: Patients with hematological malignancies exhibit inferior response to SARS-CoV2 vaccination, compared to healthy individuals, however little is known about patients with precursor hematological malignancies and the cellular underpinnings of vaccination response. Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Myeloma (SMM) are plasma cell premalignancies that precede Multiple Myeloma (MM) and exhibit signs of immune dysregulation;they affect approximately 5% of the population over 50 years of age, who remain largely undiagnosed, due to lack of screening. In November 2019, we launched the IMPACT study to characterize the immune response to SARS-CoV2 vaccination in patients with plasma cell dyscrasias and healthy individuals. Methods: We performed single-cell RNA-sequencing on 224 peripheral blood mononuclear cell samples drawn from 118 IMPACT (IRB #20-332) participants with MGUS (n=20), SMM (n=48), or MM (n=24), as well as healthy individuals (n=26). Samples were collected before vaccination and after 2 doses of BNT162b2 (Pfizer-BioNtech) (n=123), mRNA-1273 (Moderna) (n=83) or 1 dose of Ad26.COV2.S (Janssen) (n=14). Results: Overall, we sequenced 2,025,611 cells from 224 samples of 118 patients with MGUS, SMM, MM and healthy individuals pre- and post-vaccination for SARS-CoV2, and profiled 553,082 T-cells, 95,392 B-cells, 74,394 NK cells, 195,371 Monocytes, and 35,236 Dendritic cells (DC). We identified activated clusters of B-cells, NK cells and DCs expressing genes such as CD83, CD69, CXCR4, and genes related to the NF-kB and AP-1 pathways. We compared cell type abundances pre- and post-vaccination within each participant population and found that activated CD83+ cells significantly increased post-vaccination in healthy individuals and patients with MGUS (paired t-test, q < 0.1), but not in patients with SMM or overt MM. At baseline, patients with SMM and MM had significantly fewer memory B-cells and significantly more cytotoxic T-cells and NK cells, compared to healthy individuals (Wilcoxon, q < 0.1), which could partly explain the differences observed post-vaccination. Patients with MM also had significantly higher levels of tolerogenic IL-10-expressing DCs (DC10) at baseline (Wilcoxon, q < 0.1), which could be dampening antigen-specific T-cell responses. Conclusion: We identified a significant expansion of activated B-cell, NK cell and DC subpopulations expressing CD83, CD69 and CXCR4, following vaccination in healthy individuals and patients with MGUS, but less so in patients with SMM and overt MM. Our results provide insight into the cellular mechanisms of immune response to SARS-CoV2 vaccination in healthy individuals and patients with precursor plasma cell malignancies and suggest that asymptomatic individuals with SMM may exhibit inferior response to vaccination.

MicroRNAs based regulation of cytokine regulating immune expressed genes and their transcription factors in COVID-19.

BACKGROUND: Coronavirus disease 2019 is characterized by the elevation of a broad spectrum of inflammatory mediators associated with poor disease outcomes. We aimed at an in-silico analysis of regulatory microRNA and their transcription factors (TF) for these inflammatory genes that may help to devise potential therapeutic strategies in the future. METHODS: The cytokine regulating immune-expressed genes (CRIEG) were sorted from literature and the GEO microarray dataset. Their co-differentially expressed miRNA and transcription factors were predicted from publicly available databases. Enrichment analysis was done through mienturnet, MiEAA, Gene Ontology, and pathways predicted by KEGG and Reactome pathways. Finally, the functional and regulatory features were analyzed and visualized through Cytoscape. RESULTS: Sixteen CRIEG were observed to have a significant protein-protein interaction network. The ontological analysis revealed significantly enriched pathways for biological processes, molecular functions, and cellular components. The search performed in the miRNA database yielded ten miRNAs that are significantly involved in regulating these genes and their transcription factors. CONCLUSION: An in-silico representation of a network involving miRNAs, CRIEGs, and TF, which take part in the inflammatory response in COVID-19, has been elucidated. Thus, these regulatory factors may have potentially critical roles in the inflammatory response in COVID-19 and may be explored further to develop targeted therapeutic strategies and mechanistic validation.