Ligand/Receptor-mediated Cell Communication Alteration Causes the Lung Inflammation Microenvironment and the Redistribution of Inter-tissue Immune Cells in COVID-19 Patients (preprint)

How SARS-CoV-2 causes disturbances of the lung microenvironment and systemic immune response remains a mystery. Here, we first analyze detailedly paired single-cell transcriptome data of the lungs, blood and bone marrow of two patients who died of COVID-19. Second, our results demonstrate that SARS-CoV-2 infection significantly increases the cellular communication frequency between AT1/AT2 cells and highly inflammatory myeloid cells, and induces the pulmonary inflammation microenvironment, and drives the disorder of fibroblasts, club and ciliated cells, thereby causing the increase of pulmonary fibrosis and mucus accumulation. Third, our works reveal that the increase of the lung T cell infiltration is mainly recruited by myeloid cells through certain ligands/receptors (ANXA1/FPR1, C5AR1/RPS19 and CCL5/CCR1), rather than AT1/AT2. Fourth, we find that some ligands and receptors such as ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1, are significantly activated and shared among patients’ lungs, blood and bone marrow, implying that dysregulated ligands and receptors may cause the migration, redistribution and the inflammatory storm of immune cells in different tissues. Overall, our study reveals a latent mechanism by which the disorders of ligands and receptors caused by SARS-CoV-2 infection drive cell communication alteration, the pulmonary inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.

Comparison of the Respiratory Tractmicrobiome in Hospitalized COVID-19 Patients with Different Disease Severity (preprint)

Background: Little is known about the characteristics of respiratory tract microbiome in Coronavirus disease 2019 (COVID-19) inpatients with different severity. Methods: A cross-sectional study was conducted to characterize respiratory tract microbial communities of 69 COVID-19 inpatients from 64 nasopharyngeal swabs and 5 sputum specimens using 16S ribosomal RNA (rRNA) gene V3-V4 region sequencing. The bacterial profiles were used to find potential biomarkers by the two-step method, the combination of random forest model and the linear discriminant analysis effect size (LEfSe), and explore the connections with clinical characteristics by Spearman’s rank test. Results: : Compared with mild COVID-19 patients, severe patients had significantly decreased bacterial diversity ( P values were less than 0.05 in the alpha and beta diversity) and relative lower abundance of opportunistic pathogens, including Actinomyces , Prevotella , Rothia , Streptococcus , Veillonella . Eight potential biomarkers including Treponema, Lachnoanaerobaculum , Parvimonas, Selenomonas, Alloprevotella , Porphyromonas , Gemella and Streptococcus were found to distinguish the mild COVID-19 patients from the severe COVID-19 patients. The genera of Actinomyces and Prevotella were negatively correlated with age and inpatient days. Intensive Care Unit (ICU) admission, neutrophil count (GRA) and lymphocyte count (LYMPH) were significantly correlated with different genera in the two groups. In addition, there were a positive correlation between Klebsiella and white blood cell count (WBC) in two groups. Conclusion: The respiratory tract microbiome had significant difference in COVID-19 patients with different severity. The value of the respiratory tract microbiome as predictive biomarkers for COVID-19 severity merits further exploration.

GP73 is a glucogenic hormone that contributes to SARS-CoV-2-induced hyperglycemia (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection induces new-onset diabetes and severe metabolic complications of pre-existing diabetes. The pathogenic mechanism underlying this is incompletely understood. Here, we provided evidence linking circulating GP73 with the exaggerated gluconeogenesis triggered by SARS-CoV-2 infection. We found that SARS-CoV-2 infection or glucotoxic conditions increased GP73 production and secretion. Secreted GP73 then trafficked to the liver and kidney to stimulate gluconeogenesis through the cAMP/PKA pathway. By using global phosphoproteomics, we found a drastic remodeling of the PKA kinase hub exerted by GP73. Notably, plasma GP73 levels were elevated and positively correlated with blood glucose in patients with COVID19 and diabetes. Neutralization of circulating GP73 in serum of individuals infected with SARS-CoV-2 or with diabetes reduced excessive gluconeogenesis in cultured hepatocytes, and lowered blood glucose levels in animal models of diabetes. Ablation of GP73 from whole animals has a profound glucose-lowering effect secondary to reduced gluconeogenesis. Thus, GP73 is a key glucogenic hormone contributing to SARS-CoV-2-induced glucose abnormality.

GP73 is a glucogenic hormone regulating SARS-CoV-2-induced hyperglycemia (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection induces new-onset diabetes and severe metabolic complications of pre-existing diabetes. The pathogenic mechanism underlying this is incompletely understood. Here, we provided evidence linking circulating GP73 with the exaggerated gluconeogenesis triggered by SARS-CoV-2 infection. We found that SARS-CoV-2 infection or glucotoxic condition increased the cellular secretion of GP73. Secreted GP73 trafficked to the liver and kidney to stimulate gluconeogenesis through cAMP/PKA pathway. By using global phosphoproteomics, we found a drastic remodeling of PKA kinase hub exerted by GP73. Notably, COVID-19 patients showed pathologically elevated plasma GP73, and neutralization of the secreted GP73 inhibited enhanced PKA signaling and glucose production associated with SARS-CoV-2 infection. GP73 blockade also reduced gluconeogenesis and lowered hyperglycemia in type 2 (T2D) diabetic mice. Therefore, our findings provide novel insight into the roles of GP73 as a key glucogenic hormone and mechanistic clues underlying the development of SARS-CoV-induced glucose abnormalities.

Evaluation of recombinant nucleocapsid and spike proteins for serological diagnosis of novel coronavirus disease 2019 (COVID-19) (preprint)

Background: The colloidal gold immunochromatography assay (GICA) is a rapid diagnostic tool for novel coronavirus disease 2019 (COVID-19) infections. However, with significant numbers of false negatives, improvements to GICA are needed. Methods: Six recombinant HCoV-19 nucleocapsid and spike proteins were prepared and evaluated. The optimal proteins were employed to develop a sandwich-format GICA strip to detect total antibodies (IgM and IgG) against HCoV-19. GICA performance was assessed with comparison of viral RNA detection. Results: Recombinant HCoV-19 proteins were obtained, including three prokaryotically expressed rN, rN1, rN2 nucleocapsid proteins, and three eukaryotically expressed rS1, rS-RBD, rS-RBD-mFc spike proteins. The recombinant proteins with the highest ELISA titers (rS1 and rS-RBD-mFc) against coronavirus-specific IgM and IgG were chosen for GICA development. The GICA has a sensitivity and specificity of 86.89% (106/122) and 99.39% (656/660), respectively. Furthermore, 65.63% (21/32) of the clinically confirmed but RT-PCR negative samples were GICA positive. Conclusions: The eukaryotically-expressed spike proteins (rS1and rS-RBD-mFc) are more suitable than the prokaryotically expressed nucleocapsid proteins for HCoV-19 serological diagnosis. The GICA sandwich used to detect total antibodies is a powerful complement to the current standard RNA-based tests.