Amplification-Free Detection of SARS-CoV-2 Down to Single Virus Level by Portable Carbon Nanotube Biosensors.

The rapid and sensitive detection of trace-level viruses in a simple and reliable way is of great importance for epidemic prevention and control. Here, a multi-functionalized floating gate carbon nanotube field effect transistor (FG-CNT FET) based biosensor is reported for the single virus level detection of SARS-CoV-2 virus antigen and RNA rapidly with a portable sensing platform. The aptamers functionalized sensors can detect SARS-CoV-2 antigens from unprocessed nasopharyngeal swab samples within 1 min. Meanwhile, enhanced by a multi-probe strategy, the FG-CNT FET-based biosensor can detect the long chain RNA directly without amplification down to single virus level within 1 min. The device, constructed with packaged sensor chips and a portable sensing terminal, can distinguish 10 COVID-19 patients from 10 healthy individuals in clinical tests both by the RNAs and antigens by a combination detection strategy with an combined overall percent agreement (OPA) close to 100%. The results provide a general and simple method to enhance the sensitivity of FET-based biochemical sensors for the detection of nucleic acid molecules and demonstrate that the CNT FG FET biosensor is a versatile and reliable integrated platform for ultrasensitive multibiomarker detection without amplification and has great potential for point-of-care (POC) clinical tests.

Novel insight into the underlying dysregulation mechanisms of immune cell-to-cell communication by analyzing multitissue single-cell atlas of two COVID-19 patients.

How does SARS-CoV-2 cause lung microenvironment disturbance and inflammatory storm is still obscure. We here performed the single-cell transcriptome sequencing from lung, blood, and bone marrow of two dead COVID-19 patients and detected the cellular communication among them. Our results demonstrated that SARS-CoV-2 infection increase the frequency of cellular communication between alveolar type I cells (AT1) or alveolar type II cells (AT2) and myeloid cells triggering immune activation and inflammation microenvironment and then induce the disorder of fibroblasts, club, and ciliated cells, which may cause increased pulmonary fibrosis and mucus accumulation. Further study showed that the increase of T cells in the lungs may be mainly recruited by myeloid cells through ligands/receptors (e.g., ANXA1/FPR1, C5AR1/RPS19, and CCL5/CCR1). Interestingly, we also found that certain ligands/receptors (e.g., ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1) are significantly activated and shared among lungs, blood and bone marrow of COVID-19 patients, implying that the dysregulation of ligands/receptors may lead to immune cell's activation, migration, and the inflammatory storm in different tissues of COVID-19 patients. Collectively, our study revealed a possible mechanism by which the disorder of cell communication caused by SARS-CoV-2 infection results in the lung inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.

Targeted screening of genetic associations with COVID-19 susceptibility and severity.

The COVID-19 pandemic has resulted in great morbidity and mortality worldwide and human genetic factors have been implicated in the susceptibility and severity of COVID-19. However, few replicate researches have been performed, and studies on associated genes mainly focused on genic regions while regulatory regions were a lack of in-depth dissection. Here, based on previously reported associated variants and genes, we designed a capture panel covering 1,238 candidate variants and 25 regulatory regions of 19 candidate genes and targeted-sequenced 96 mild and 145 severe COVID-19 patients. Genetic association analysis was conducted between mild and severe COVID-19 patients, between all COVID-19 patients and general population, or between severe COVID-19 patients and general population. A total of 49 variants were confirmed to be associated with susceptibility or severity of COVID-19 (p < 0.05), corresponding to 18 independent loci. Specifically, rs1799964 in the promoter of inflammation-related gene TNF, rs9975538 in the intron of interferon receptor gene IFNAR2, rs429358 in the exon of APOE, rs1886814 in the intron of FOXP4-AS1 and a list of variants in the widely reported 3p21.31 and ABO gene were confirmed. It is worth noting that, for the confirmed variants, the phenotypes of the cases and controls were highly consistent between our study and previous reports, and the confirmed variants identified between mild and severe patients were quite different from those identified between patients and general population, suggesting the genetic basis of susceptibility and severity of SARS-CoV-2 infection might be quite different. Moreover, we newly identified 67 significant associated variants in the 12 regulatory regions of 11 candidate genes (p < 0.05). Further annotation by RegulomeDB database and GTEx eQTL data filtered out two variants (rs11246060 and rs28655829) in the enhancer of broad-spectrum antiviral gene IFITM3 that might affect disease severity by regulating the gene expression. Collectively, we confirmed a list of previously reported variants and identified novel regulatory variants associated with susceptibility and severity of COVID-19, which might provide biological and clinical insights into COVID-19 pathogenesis and treatment.

Environmental contamination with SARS-CoV-2 in COVID-19 hospitals in Wuhan, China, 2020.

Coronavirus disease 2019 (COVID-19) pandemic has caused high number of infections and deaths of healthcare workers globally. Distribution and possible transmission route of SARS-CoV-2 in hospital environment should be clarified. We herein collected 431 environmental (391 surface and 40 air) samples in the intensive care unit (ICU) and general wards (GWs) of three hospitals in Wuhan, China from February 21 to March 4, 2020, and detected SARS-CoV-2 RNA by real-time quantitative PCR. The viral positive rate in the contaminated areas was 17.8% (28/157), whereas there was no virus detected in the clean areas. Higher positive rate (22/59, 37.3%) was found in ICU than that in GWs (3/63, 4.8%). The surfaces of computer keyboards and mouse in the ICU were the most contaminated (8/10, 80.0%), followed by the ground (6/9, 66.7%) and outer glove (2/5, 40.0%). From 17 air samples in the contaminated areas, only one sample collected at a distance of around 30 cm from the patient was positive. Enhanced surface disinfection and hand hygiene effectively decontaminated the virus from the environment. This finding might help understand the transmission route and contamination risk of SARS-CoV-2 and evaluate the effectiveness of infection prevention and control measures in healthcare facilities.

Comparison of the respiratory tract microbiome in hospitalized COVID-19 patients with different disease severity.

Little is known about the characteristics of respiratory tract microbiome in Coronavirus disease 2019 (COVID-19) inpatients with different severity. We conducted a study that expected to clarify these characteristics as much as possible. 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 gene V3-V4 region sequencing. The bacterial profiles were analyzed to find potential biomarkers by the two-step method, the combination of random forest model and the linear discriminant analysis effect size, and explore the connections with clinical characteristics by Spearman's rank test. 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, Leptotrichia, Lachnoanaerobaculum, Parvimonas, 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 in two groups. Intensive care unit admission, neutrophil count, and lymphocyte count were significantly correlated with different genera in the two groups. In addition, there was a positive correlation between Klebsiella and white blood cell count in two groups. The respiratory tract microbiome had significant differences in COVID-19 patients with different severity. The value of the respiratory tract microbiome as predictive biomarkers for COVID-19 severity deserves further exploration.

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 reverse-transcription qPCR and droplet digital PCR for the detection of SARS-CoV-2 in clinical specimens of hospitalized patients.

Accurate detection of severe acute respiratory syndrome coronavirus 2 is not only necessary for viral load monitoring to optimize treatment in hospitalized coronavirus disease 2019 patients, but also critical for deciding whether the patient could be discharged without any risk of viral shedding. Digital droplet PCR (ddPCR) is more sensitive than reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) and is usually considered the superior choice. In the current study, we compared the clinical performance of RT-qPCR and ddPCR using oropharyngeal swab samples from patients hospitalized in the temporary Huoshenshan Hospital, Wuhan, Hubei, China. Results demonstrated that ddPCR was indeed more sensitive than RT-qPCR. Negative results might be caused by poor sampling technique or recovered patients, as the range of viral load in these patients varied significantly. In addition, both methods were highly correlated in terms of their ability to detect all three target genes as well as the ratio of copies of viral genes to that of the IC gene. Furthermore, our results evidenced that both methods detected the N gene more easily than the ORF gene. Taken together, these findings imply that the use of ddPCR, as an alternative to RT-qPCR, is necessary for the accurate diagnosis of hospitalized coronavirus disease 2019 patients.

GP73 is a glucogenic hormone contributing to SARS-CoV-2-induced hyperglycemia.

Severe cases of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are associated with elevated blood glucose levels and metabolic complications. However, the molecular mechanisms for how SARS-CoV-2 infection alters glycometabolic control are incompletely understood. Here, we connect the circulating protein GP73 with enhanced hepatic gluconeogenesis during SARS-CoV-2 infection. We first demonstrate that GP73 secretion is induced in multiple tissues upon fasting and that GP73 stimulates hepatic gluconeogenesis through the cAMP/PKA signaling pathway. We further show that GP73 secretion is increased in cultured cells infected with SARS-CoV-2, after overexpression of SARS-CoV-2 nucleocapsid and spike proteins and in lungs and livers of mice infected with a mouse-adapted SARS-CoV-2 strain. GP73 blockade with an antibody inhibits excessive glucogenesis stimulated by SARS-CoV-2 in vitro and lowers elevated fasting blood glucose levels in infected mice. In patients with COVID-19, plasma GP73 levels are elevated and positively correlate with blood glucose levels. Our data suggest that GP73 is a glucogenic hormone that likely contributes to SARS-CoV-2-induced abnormalities in systemic glucose metabolism.

Genome-wide association study of COVID-19 severity among the Chinese population.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes a broad clinical spectrum of coronavirus disease 2019 (COVID-19). The development of COVID-19 may be the result of a complex interaction between the microbial, environmental, and host genetic components. To reveal genetic determinants of susceptibility to COVID-19 severity in the Chinese population, we performed a genome-wide association study on 885 severe or critical COVID-19 patients (cases) and 546 mild or moderate patients (controls) from two hospitals, Huoshenshan and Union hospitals at Wuhan city in China. We identified two loci on chromosome 11q23.3 and 11q14.2, which are significantly associated with the COVID-19 severity in the meta-analyses of the two cohorts (index rs1712779: odds ratio [OR] = 0.49; 95% confidence interval [CI], 0.38-0.63 for T allele; P = 1.38 × 10-8; and index rs10831496: OR = 1.66; 95% CI, 1.38-1.98 for A allele; P = 4.04 × 10-8, respectively). The results for rs1712779 were validated in other two small COVID-19 cohorts in the Asian populations (P = 0.029 and 0.031, respectively). Furthermore, we identified significant eQTL associations for REXO2, C11orf71, NNMT, and CADM1 at 11q23.3, and CTSC at 11q14.2, respectively. In conclusion, our findings highlight two loci at 11q23.3 and 11q14.2 conferring susceptibility to the severity of COVID-19, which might provide novel insights into the pathogenesis and clinical treatment of this disease.

Development and evaluation of a serological test for diagnosis of COVID-19 with selected recombinant spike proteins.

Serological test is a valuable diagnostic tool for coronavirus disease 2019 (COVID-19). However, considerable improvements to these tests are needed, especially in the detection sensitivity. In this study, six recombinant nucleocapsid and spike proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were prepared and evaluated, including three prokaryotic expression nucleocapsid proteins (rN, rN1, rN2) and three eukaryotic expression spike proteins (rS1, rS-RBD, rS-RBD-mFc). The recombinant proteins with the highest ELISA titers (rS1 and rS-RBD-mFc) were selected to develop a double-antigen sandwich colloidal gold immunochromatography assay (GICA) to detect total antibodies against SARS-CoV-2. The clinical evaluation results showed that the sensitivity and specificity of GICA were 92.09% (419/455) and 99.44% (706/710), respectively. Moreover, a significant number (65.63%, 21/32) of COVID-19 patients with undetectable viral RNA were correctly diagnosed by the GICA method. In conclusion, the eukaryotic expression spike proteins (rS1 and rS-RBD-mFc) are more suitable than the prokaryotic expression nucleocapsid proteins for serological diagnosis of SARS-CoV-2. The proposed GICA for detection of total antibodies could be a powerful complement to the current RNA tests for COVID-19.

Clinical features and antibody response of patients from a COVID-19 treatment hospital in Wuhan, China.

Coronavirus disease 2019 (COVID-19) has rapidly evolved into a global pandemic. A total of 1578 patients admitted into a newly built hospital specialized for COVID-19 treatment in Wuhan, China, were enrolled. Clinical features and the levels of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin (Ig)M and IgG were analyzed. In total, 1532 patients (97.2%) were identified as laboratory-confirmed cases. Seventy-seven patients were identified as asymptomatic carriers (n = 64) or SARS-CoV-2 RNA positive before symptom onset (n = 13). The positive rates of SARS-CoV-2 IgM and IgG were 80.4% and 96.8%, respectively. The median of IgM and IgG titers were 37.0A U/ml (interquartile range [IQR]: 13.4-81.1 AU/ml) and 156.9 AU/ml (IQR: 102.8-183.3 AU/ml), respectively. The IgM and IgG levels of asymptomatic patients (median titers, 8.3 AU/ml and 100.3 AU/ml) were much lower than those in symptomatic patients (median titers, 38.0 AU/ml and 158.2 AU/ml). A much lower IgG level was observed in critically ill patients 42-60 days after symptom onset. There were 153 patients with viral RNA shedding after IgG detection. These patients had a higher proportion of critical illness during hospitalization (p < .001) and a longer hospital stay (p < .001) compared to patients with viral clearance after IgG detection. Coronary heart disease (odds ratio [OR], 1.89 [95% confidence interval [CI], 1.11-3.24]; p = .020), and intensive care unit admission (OR, 2.47 [95% CI, 1.31-4.66]; p = .005) were independent risk factors associated with viral RNA shedding after IgG detection. Symptomatic patients produced more antibodies than asymptomatic patients. The patients who had SARS-CoV-2 RNA shedding after developing IgG were more likely to be sicker patients.