Specific Pupylation as IDEntity Reporter (SPIDER) for the identification of Protein-Biomolecule interactions (preprint)

Protein-biomolecule interactions play pivotal roles in almost all biological processes, the identification of the interacting protein is essential. By combining a substrate-based proximity labelling activity from the pupylation pathway of Mycobacterium tuberculosis , and the streptavidin (SA)-biotin system, we developed S pecific P upylation as IDE ntity R eporter (SPIDER) for identifying protein-biomolecular interactions. As a proof of principle, SPIDER was successfully applied for global identification of interacting proteins, including substrates for enzyme (CobB), the readers of m 6 A, the protein interactome of mRNA, and the target proteins of drug (lenalidomide). In addition, by SPIDER, we identified SARS-CoV-2 Omicron variant specific receptors on cell membrane and performed in-depth analysis for one candidate, Protein-g. These potential receptors could explain the differences between the Omicron variant and the Prototype strain, and further serve as target for combating the Omicron variant. Overall, we provide a robust technology which is applicable for a wide-range of protein-biomolecular interaction studies.

15-Month Health Outcomes of Hospitalized COVID-19 Patients from Onset: A Cohort Study (preprint)

Background: The long-term impact of COVID-19 on patient health has been a recent focus. This study aims to determine the persistent symptoms and psychological conditions of patients hospitalized with COVID-19 15 months after onset. The potential risk factors were also explored.Methods: A cohort of COVID-19 patients discharged from February 20, 2020 to March 31, 2020 was recruited. Follow-ups were conducted using validated questionnaires and psychological screening scales at 15 months after onset to evaluate the patients’ health status. The risk factors for long-term health impacts and their associations with disease severity was analyzed.Findings: 534 COVID-19 patients were enrolled. The median age of the patients was 62.0 years old (IQR 52.0-70.0) and 295 were female (55.2%). The median time from onset to follow-up was 460.0 (451.0-467.0) days. Sleep disturbance (18.5%, 99/534) and fatigue (17.2%, 92/534) were the most common persistent symptoms. 6.4% (34/534) of the patients had depression, 9.2% (49/534) were anxious, 13.0% (70/534) had insomnia and 4.7% (25/534) suffered from posttraumatic stress disorder (PTSD). Multivariate adjusted logistic regression analysis showed that glucocorticoid use during hospitalization (OR 3.58, 95% CI 1.12-11.44) was significantly associated with an increased risk of fatigue. The OR values for anxiety and sleep disorders were 2.36 (95% CI 1.07-5.20) and 2.16 (95% CI 1.13-4.14) in females compared with males. The OR value of PTSD was 25.6 (95% CI 3.3-198.4) in patients with persistent symptoms to those without persistent symptoms. No significant associations were observed between fatigue syndrome or adverse mental outcomes and disease severity.Interpretation: 15-month follow-up in this study aroused the need of extended rehabilitation intervention for complete recovery in COVID-19 patients. Funding: None to declare. Declaration of Interest: All the authors declare no competing interests.Ethical Approval: The Research Ethics Committee of Shanghai Changzheng Hospital approved this study (2020SL007).

SARS-CoV-2 Antibody Signatures for Predicting the Outcome of COVID-19 (preprint)

Background: The COIVD-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies remain elevated with disease progression and severity in COIVD-19 patients. We assumed that antibodies may serve as biomarkers for predicting disease outcome.Method: By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgM/IgG responses against 20 SARS-CoV-2 proteins in 1,034 hospitalized COVID-19 patients on admission, who were followed till 66 days. The microarray results were further correlated with clinical information, laboratory test results and patient outcomes. Cox proportional hazards model was used to explore the association between SARS-CoV-2 specific antibodies and COVID-19 mortality.Results: We found that high level of IgM against ORF7b at the time of hospitalization is an independent predictor of patient survival ( p  trend = 0.002), while levels of IgG responses to 6 non-structural proteins and 1 accessory protein, i. e., NSP4, NSP7, NSP9, NSP10, RdRp (NSP12), NSP14, and ORF3b, possess significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory markers for disease severity (all with p trend < 0.05). Spline regression analysis indicated that the correlation between ORF7b IgM, NSP9 IgG, and NSP10 IgG and the risk of COVID-19 mortality shows linear ( p = 0.0013, 0.0073 and 0.0003, respectively). Their AUCs for predictions, determined by computational cross-validations (validation1), were 0.74 (cut-off = 7.59), 0.66 (cut-off = 9.13), and 0.68 (cut-off = 6.29), respectively. Further validations were conducted in the second and third serial samples of these cases (validation2A, n = 633, validation2B, n = 382), with high accuracy of prediction for outcome.Conclusion: These findings have important implications for improving clinical management, and especially for developing medical interventions and vaccines.Funding Statement: This work was supported by grants from the Fundamental Research Funds for the Central Universities (HUST COVID-19 Rapid Response Call No. 2020kfyXGYJ040) and Wuhan Bureau of Science and Technology (No. 2020020601012218).Declaration of Interests: The authors declare no conflicts of interest.Ethics Approval Statement: The study was approved by the Ethical Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (IRB ID:TJ-C20200128).

Antibody Landscape Against SARS-CoV-2 Proteome Revealed Significant Differences between Non-Structural/ Accessory Proteins and Structural Proteins (preprint)

The immunogenicity of SARS-CoV-2 proteome is largely unknown, especially for non-structural proteins and accessory proteins. Here we collected 2,360 COVID-19 sera and 601 control sera. We analyzed these sera on a protein microarray with 20 proteins of SARS-CoV-2, built an antibody response landscape for IgG and IgM. We found that non-structural proteins and accessory proteins NSP1, NSP7, NSP8, RdRp, ORF3b and ORF9b elicit prevalent IgG responses. The IgG patterns and dynamic of non-structural/ accessory proteins are different from that of S and N protein. The IgG responses against these 6 proteins are associated with disease severity and clinical outcome and declined sharply about 20 days after symptom onset. In non-survivors, sharp decrease of IgG antibodies against S1 and N protein before death was observed. The global antibody responses to non-structural/ accessory proteins revealed here may facilitate deeper understanding of SARS-CoV-2 immunology.Funding: This work was partially supported by the National Key Research and Development Program of China Grant (No.2016YFA0500600), National Natural Science Foundation of China (No. 31970130, 31600672, 31670831, 31370813, 31900112 and 21907065).Conflict of Interest: The authors declare no competing interests.Ethical Approval: The study was approved by the Ethical Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (ITJ-C20200128). Written informed consent was obtained from all participants enrolled in this study.

Linear Epitope Landscape of SARS-CoV-2 Spike Protein Constructed from 1,051 COVID-19 Patients (preprint)

Neutralization antibodies and vaccines for treating COVID-19 are desperately needed. For precise development of antibodies and vaccines, the key is to understand which part of SARS-CoV-2 Spike protein is highly immunogenic on a systematic way. We generate a linear epitope landscape of Spike protein by analyzing serum IgG response of 1,051 COVID-19 patients with a peptide microarray. We reveal two regions that rich of linear epitopes, i.e., CTD and a region close to the S2’ cleavage site and fusion peptide. Unexpectedly, we find RBD is lack of linear epitope. Besides 3 moderate immunogenic peptides from RBD, 16 highly immunogenic peptides from other regions of Spike protein are determined. These peptides could serve as the base for precise development of antibodies and vaccines for COVID-19 on a systematic level.Funding: This work was partially supported by National Key Research and Development Program of China Grant (No. 2016YFA0500600), Science and Technology Commission of Shanghai Municipality (No. 19441911900), Interdisciplinary Program of Shanghai Jiao Tong University (No. YG2020YQ10), National Natural Science Foundation of China (No. 31970130, 31600672, 31670831, and 31370813).Conflict of Interest: The authors declare no competing interest.