Primate-specific BTN3A2 protects against SARS-CoV-2 infection by interacting with and reducing ACE2 (preprint)

Coronavirus disease 2019 (COVID-19) is an immune-related disorder caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 invades cells via the entry receptor angiotensin-converting enzyme 2 (ACE2). While several attachment factors and co-receptors for SARS-CoV-2 have been identified, the complete pathogenesis of the virus remains to be determined. Unraveling the molecular mechanisms governing SARS-CoV-2 interactions with host cells is crucial for the formulation of effective prophylactic measures and the advancement of COVID-19 therapeutics. Here, we identified butyrophilin subfamily 3 member A2 (BTN3A2) as a potent inhibitor of SARS-CoV-2 infection. The mRNA level of BTN3A2 was correlated with COVID-19 severity. Upon re-analysis of a human lung single-cell RNA sequencing dataset, BTN3A2 expression was predominantly identified in epithelial cells. Moreover, this expression was elevated in pathological epithelial cells from COVID-19 patients and co-occurred with ACE2 expression in the same cellular subtypes in the lung. Additionally, BTN3A2 primarily targeted the early stage of the viral life cycle by inhibiting SARS-CoV-2 attachment through direct interactions with the receptor-binding domain (RBD) of the Spike protein and ACE2. Furthermore, BTN3A2 inhibited ACE2-mediated SARS-CoV-2 infection by reducing ACE2 in vitro and in a BTN3A2 transgenic mouse model. These results reveal a key role of BTN3A2 in the fight against COVID-19 and broaden our understanding of the pathobiology of SARS-CoV-2 infection. Identifying potential monoclonal antibodies that target BTN3A2 may facilitate disruption of SARS-CoV-2 infection, providing a therapeutic avenue for COVID-19.

SARS-CoV-2 NSP13 suppresses the Hippo pathway downstream effector YAP (preprint)

The Hippo pathway plays critical roles in tissue development, regeneration, and immune homeostasis. The widespread pandemic of Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has resulted in a global healthcare crisis and strained health resources. How SARS-CoV-2 affects Hippo signaling in host cells has remained poorly understood. Here, we report that SARS-CoV-2 infection in patient lung cells and cardiomyocytes derived from human induced pluripotent stem cells (iPS-CMs) suppressed YAP target gene expression, as evidenced by RNA sequencing data. Furthermore, in a screening of nonstructural proteins from SARS-CoV-2, nonstructural protein 13 (NSP13) significantly inhibited YAP transcriptional activity independent of the YAP upstream suppressor kinase Lats1/2. Consistent with this, NSP13 suppressed active YAP (YAP5SA) in vivo, whereby NSP13 expression reverted the phenotype of YAP5SA transgenic mice. From a mechanistic standpoint, NSP13 helicase activity was shown to be required for its suppression of YAP. Furthermore, through the interaction of NSP13 with TEAD4, which is the most common YAP-interacting transcription factor in the nucleus, NSP13 recruited endogenous YAP suppressors such as CCT3 and TTF2 to inactivate the YAP/TEAD4 complex. These findings reveal the function and mechanism of the SARS-CoV-2 helicase NSP13 in host cells and partially explain the toxic effect of SARS-CoV-2 in particular host tissue with high YAP activity.

Evaluation of the Safety and Efficacy of Azvudine and Paxlovid in the Treatment of Hospitalized Patients With COVID-19

Effects of media exposure on PTSD symptoms in college students during the COVID-19 outbreak.

Objective: We aimed to investigate the influence of media on college students' mental health during the COVID-19 pandemic. Methods: After the COVID-19 outbreak, we used cross-sectional surveys through online questionnaires to investigate the mental health of college students in lockdown at home. We identified the influencing factors of PTSD symptoms using the Chi-Square test and ordinal logistic regression analysis. Results: In 10,989 valid questionnaires, 9,906 college students with no PTSD symptoms, 947 college students with subclinical PTSD symptoms (1-3 items), and 136 college students with four or more PTSD symptoms were screened out. The results showed that media content impacted the mental health of college students in lockdown at home. Positive media content was negatively correlated with PTSD symptoms among college students. PTSD symptoms were not associated with sources of information. Moreover, College students with PTSD symptoms would reduce their willingness to learn and could not complete online learning efficiently. Conclusion: PTSD symptoms are related to media exposure and excessive information involvement of COVID-19 in college students, which influences the willingness to attend online classes.

Entangling of Peptide Nanofibers Reduces the Invasiveness of SARS-CoV-2.

The viral spike (S) protein on the surface of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to angiotensin-converting enzyme 2 (ACE2) receptors on the host cells, facilitating its entry and infection. Here, functionalized nanofibers targeting the S protein with peptide sequences of IRQFFKK, WVHFYHK and NSGGSVH, which are screened from a high-throughput one-bead one-compound screening strategy, are designed and prepared. The flexible nanofibers support multiple binding sites and efficiently entangle SARS-CoV-2, forming a nanofibrous network that blocks the interaction between the S protein of SARS-CoV-2 and the ACE2 on host cells, and efficiently reduce the invasiveness of SARS-CoV-2. In summary, nanofibers entangling represents a smart nanomedicine for the prevention of SARS-CoV-2.

Preventive and therapeutic benefits of nelfinavir in rhesus macaques and human beings infected with SARS-CoV-2.

Effective drugs with broad spectrum safety profile to all people are highly expected to combat COVID-19 caused by SARS-CoV-2. Here we report that nelfinavir, an FDA approved drug for the treatment of HIV infection, is effective against SARS-CoV-2 and COVID-19. Preincubation of nelfinavir could inhibit the activity of the main protease of the SARS-CoV-2 (IC50 = 8.26 µM), while its antiviral activity in Vero E6 cells against a clinical isolate of SARS-CoV-2 was determined to be 2.93 µM (EC50). In comparison with vehicle-treated animals, rhesus macaque prophylactically treated with nelfinavir had significantly lower temperature and significantly reduced virus loads in the nasal and anal swabs of the animals. At necropsy, nelfinavir-treated animals had a significant reduction of the viral replication in the lungs by nearly three orders of magnitude. A prospective clinic study with 37 enrolled treatment-naive patients at Shanghai Public Health Clinical Center, which were randomized (1:1) to nelfinavir and control groups, showed that the nelfinavir treatment could shorten the duration of viral shedding by 5.5 days (9.0 vs. 14.5 days, P = 0.055) and the duration of fever time by 3.8 days (2.8 vs. 6.6 days, P = 0.014) in mild/moderate COVID-19 patients. The antiviral efficiency and clinical benefits in rhesus macaque model and in COVID-19 patients, together with its well-established good safety profile in almost all ages and during pregnancy, indicated that nelfinavir is a highly promising medication with the potential of preventative effect for the treatment of COVID-19.

Realizing the value in "non-standard” parts of the qPCR standard curve by integrating fundamentals of quantitative microbiology

The real-time polymerase chain reaction (PCR), commonly known as quantitative PCR (qPCR), is increasingly common in environmental microbiology applications. During the COVID-19 pandemic, qPCR combined with reverse transcription (RT-qPCR) has been used to detect and quantify SARS-CoV-2 in clinical diagnoses and wastewater monitoring of local trends. Estimation of concentrations using qPCR often features a log-linear standard curve model calibrating quantification cycle (Cq) values obtained from underlying fluorescence measurements to standard concentrations. This process works well at high concentrations within a linear dynamic range but has diminishing reliability at low concentrations because it cannot explain "non-standard” data such as Cq values reflecting increasing variability at low concentrations or non-detects that do not yield Cq values at all. Here, fundamental probabilistic modeling concepts from classical quantitative microbiology were integrated into standard curve modeling approaches by reflecting well-understood mechanisms for random error in microbial data. This work showed that data diverging from the log-linear regression model at low concentrations as well as non-detects can be seamlessly integrated into enhanced standard curve analysis. The newly developed model provides improved representation of standard curve data at low concentrations while converging asymptotically upon conventional log-linear regression at high concentrations and adding no fitting parameters. Such modeling facilitates exploration of the effects of various random error mechanisms in experiments generating standard curve data, enables quantification of uncertainty in standard curve parameters, and is an important step toward quantifying uncertainty in qPCR-based concentration estimates. Improving understanding of the random error in qPCR data and standard curve modeling is especially important when low concentrations are of particular interest and inappropriate analysis can unduly affect interpretation, conclusions regarding lab performance, reported concentration estimates, and associated decision-making.

Realizing the value in "non-standard" parts of the qPCR standard curve by integrating fundamentals of quantitative microbiology.

The real-time polymerase chain reaction (PCR), commonly known as quantitative PCR (qPCR), is increasingly common in environmental microbiology applications. During the COVID-19 pandemic, qPCR combined with reverse transcription (RT-qPCR) has been used to detect and quantify SARS-CoV-2 in clinical diagnoses and wastewater monitoring of local trends. Estimation of concentrations using qPCR often features a log-linear standard curve model calibrating quantification cycle (Cq) values obtained from underlying fluorescence measurements to standard concentrations. This process works well at high concentrations within a linear dynamic range but has diminishing reliability at low concentrations because it cannot explain "non-standard" data such as Cq values reflecting increasing variability at low concentrations or non-detects that do not yield Cq values at all. Here, fundamental probabilistic modeling concepts from classical quantitative microbiology were integrated into standard curve modeling approaches by reflecting well-understood mechanisms for random error in microbial data. This work showed that data diverging from the log-linear regression model at low concentrations as well as non-detects can be seamlessly integrated into enhanced standard curve analysis. The newly developed model provides improved representation of standard curve data at low concentrations while converging asymptotically upon conventional log-linear regression at high concentrations and adding no fitting parameters. Such modeling facilitates exploration of the effects of various random error mechanisms in experiments generating standard curve data, enables quantification of uncertainty in standard curve parameters, and is an important step toward quantifying uncertainty in qPCR-based concentration estimates. Improving understanding of the random error in qPCR data and standard curve modeling is especially important when low concentrations are of particular interest and inappropriate analysis can unduly affect interpretation, conclusions regarding lab performance, reported concentration estimates, and associated decision-making.

Characteristics of replication and pathogenicity of SARS-CoV-2 Alpha and Delta isolates.

The continuously arising of SARS-CoV-2 variants has been posting a great threat to public health safety globally, from B.1.17 (Alpha), B.1.351 (Beta), P.1 (Gamma), B.1.617.2 (Delta) to B.1.1.529 (Omicron). The emerging or re-emerging of the SARS-CoV-2 variants of concern is calling for the constant monitoring of their epidemics, pathogenicity and immune escape. In this study, we aimed to characterize replication and pathogenicity of the Alpha and Delta variant strains isolated from patients infected in Laos. The amino acid mutations within the spike fragment of the isolates were determined via sequencing. The more efficient replication of the Alpha and Delta isolates was documented than the prototyped SARS-CoV-2 in Calu-3 and Caco-2 â€‹cells, while such features were not observed in Huh-7, Vero E6 and HPA-3 â€‹cells. We utilized both animal models of human ACE2 (hACE2) transgenic mice and hamsters to evaluate the pathogenesis of the isolates. The Alpha and Delta can replicate well in multiple organs and cause moderate to severe lung pathology in these animals. In conclusion, the spike protein of the isolated Alpha and Delta variant strains was characterized, and the replication and pathogenicity of the strains in the cells and animal models were also evaluated.

A novel quantification method of lung fibrosis based on Micro-CT images developed with the optimized pulmonary fibrosis mice model induced by bleomycin.

Background and aims: Idiopathic pulmonary fibrosis (IPF) is a fibrosing lung disease with unknown etiology, leading to cough and dyspnoea, which is also one of the most common sequelae affecting the quality of life of COVID-19 survivors. There is no cure for IPF patients. We aim to develop a reliable IPF animal model with quantification of fibrosis based on Micro-Computer Tomography (micro-CT) images for the new drug discovery, because different bleomycin administration routes, doses, and intervals are reported in the literature, and there is no quantitative assessment of pulmonary fibrosis based on micro-CT images in animal studies. Methods: We compared three dosages (1.25 mg/kg, 2.5 mg/kg, and 5 mg/kg) of intratracheal bleomycin administration and experiment intervals (14 and 21 days) in C57BL/6 mice by investigating survival rates, pulmonary histopathology, micro-CT, peripheral CD4+ & CD8+ cells, and cytokines. Moreover, a simple and reliable new method was developed for scoring fibrosis in live mice based on Micro-CT images by using Image J software, which transfers the dark sections in pulmonary Micro-CT images to light colors on a black background. Results: The levels of hydroxyproline, inflammation cytokine, fibrotic pathological changes, and collagen deposition in the lungs of mice were bleomycin dose-dependent and time-dependent as well as the body weight loss. Based on the above results, the mice model at 21 days after being given bleomycin at 1.25 mg/kg has optimal pulmonary fibrosis with a high survival rate and low toxicity. There is a significant decrease in the light area (gray value at 9.86 ± 0.72) in the BLM mice, indicating that a significant decrease in the alveolar air area was observed in BLM injured mice compared to normal groups (###p < 0.001), while the Pirfenidone administration increased the light area (gray value) to 21.71 ± 2.95 which is close to the value observed in the normal mice (gray value at 23.23 ± 1.66), which is consistent with the protein levels of Col1A1, and α-SMA. Notably, the standard deviations for the consecutive six images of each group indicate the precision of this developed quantitation method for the micro-CT image taken at the fifth rib of each mouse. Conclusion: Provided a quantifying method for Micro-CT images in an optimal and repeatable pulmonary fibrosis mice model for exploring novel therapeutic interventions.

Symptomatic and Asymptomatic SARS-CoV-2 Infection and Follow-up of Neutralizing Antibody Levels.

Objective: To investigate neutralizing antibody levels in symptomatic and asymptomatic patients with coronavirus disease 2019 (COVID-19) at 6 and 10 months after disease onset. Methods: Blood samples were collected at three different time points from 27 asymptomatic individuals and 69 symptomatic patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Virus-neutralizing antibody titers against SARS-CoV-2 in both groups were measured and statistically analyzed. Results: The symptomatic and asymptomatic groups had higher neutralizing antibodies at 3 months and 1-2 months post polymerase chain reaction confirmation, respectively. However, neutralizing antibodies in both groups dropped significantly to lower levels at 6 months post-PCR confirmation. Conclusion: Continued monitoring of symptomatic and asymptomatic individuals with COVID-19 is key to controlling the infection.

Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism (preprint)

Wastewater-based surveillance (WBS) is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19 impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with local workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.3 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5% (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4,524 unrelated absences COVID-19 cases were recorded. Employee absences significantly increased as wastewater signal increased through pandemic waves. Strong correlations between COVID-19-confirmed absences and wastewater SARS-CoV-2 signals (N1 gene: r=0.824, p<0.0001 and N2 gene: r=0.826, p<0.0001) were observed. Linear regression with adjusted R2-value demonstrated a robust association (adjusted R2=0.783), when adjusted by 7 days, indicating wastewater provides a one-week leading signal. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P<0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.

A study on level of mental health and influencing factors of medical staff in the makeshift hospital during COVID-19 in Shanghai

Objective　To analyze the mental health status of medical staff in the Fourth Branch of National Convention and Exhibition Center Makeshift Hospital during the COVID-19 epidemic in Shanghai to lay a theoretical foundation for the mental health and psychological intervention of medical staff in COVID-19 and other public health emergencies. Methods　An online questionnaire survey was conducted with the generalized anxiety disorder scale (GAD-7), patient health questionnaire (PHQ-9), and Athens insomnia scale (AIS) before medical staff entering the makeshift hospital and one month later. Results　The detection rates of anxiety, depression and insomnia were 18.4%, 22.1% and 27.0% respectively before entering the makeshift hospital, and 28.8%, 59.3% and 64.2% respectively during the follow-up period one month later. The GAD-7, PHQ-9 and AIS scores of medical staff after working in the makeshift hospital for one month increased significantly compared with those at the baseline period (P<0.01). Female and previous history of using sedative and hypnotic drugs were risk factors for increased depression level among medical staff in the makeshift hospital. Conclusions　The anxiety, depression and insomnia levels of the medical staff in Shanghai increased after working in the makeshift hospital for one month. It is of great significance for the front-line support work to identify the medical staff with serious psychological problems and carry out psychological intervention in the early stage.

Epidemiological and genetic characteristics of respiratory syncytial virus infection in children from Hangzhou after the peak of COVID-19.

BACKGROUND: Respiratory syncytial virus (RSV) is one of the main pathogens that causes acute lower respiratory tract infection (ARTI) in infants. During the Coronavirus Disease 2019 (COVID-19) pandemic, although strict interventions have been implemented, RSV infection has not decreased. OBJECTIVES: To study the epidemiological and genetic characteristics of RSV circulating in Hangzhou after the peak of COVID-19. METHODS: A total of 1225 nasopharyngeal swabs were collected from outpatients with ARTIs from July 2021 to January 2022 in The Children's Hospital, Zhejiang University School of Medicine. RESULTS: A total of 267 (21.79%) of the 1225 samples were RSV positive. There was no gender bias. However, an obvious age preference for infection was observed, and children aged 3-6 years were more susceptible, which was very different from previous RSV pandemic seasons. Phylogenetic analysis of 115 sequenced RSV isolates showed that all the RSV-A viruses belong to the ON1 subtype, which could be clustered into three clusters. While all the RSV-B viruses belong to BA9. Further analysis of the mutations highlights the fixation of ten mutations, which should be given extra attention regarding their biological properties. CONCLUSION: The incidence of RSV infection in preschool children reported in this study is high. Phylogenetic analysis showed that the subtype A ON1 genotype was the dominant strain in Hangzhou from July 2021 to January 2022.

A variant-proof SARS-CoV-2 vaccine targeting HR1 domain in S2 subunit of spike protein.

The emerging SARS-CoV-2 variants, commonly with many mutations in S1 subunit of spike (S) protein are weakening the efficacy of the current vaccines and antibody therapeutics. This calls for the variant-proof SARS-CoV-2 vaccines targeting the more conserved regions in S protein. Here, we designed a recombinant subunit vaccine, HR121, targeting the conserved HR1 domain in S2 subunit of S protein. HR121 consisting of HR1-linker1-HR2-linker2-HR1, is conformationally and functionally analogous to the HR1 domain present in the fusion intermediate conformation of S2 subunit. Immunization with HR121 in rabbits and rhesus macaques elicited highly potent cross-neutralizing antibodies against SARS-CoV-2 and its variants, particularly Omicron sublineages. Vaccination with HR121 achieved near-full protections against prototype SARS-CoV-2 infection in hACE2 transgenic mice, Syrian golden hamsters and rhesus macaques, and effective protection against Omicron BA.2 infection in Syrian golden hamsters. This study demonstrates that HR121 is a promising candidate of variant-proof SARS-CoV-2 vaccine with a novel conserved target in the S2 subunit for application against current and future SARS-CoV-2 variants.

Tri-light Warning System for Hospitalized COVID-19 Patients]{A Tri-light Warning System for Hospitalized COVID-19 Patients: Credibility-based Risk Stratification under Data Shift (preprint)

Early warning of the novel coronavirus pneumonia (COVID-19) during the evolving pandemic waves is crucial for the timely treatment of patients and optimization of medical resource allocation. However, prior AI-based models often lack the reliability and performance validation under data distribution drifts, and are therefore problematic to be reliably utilized in real-world clinical practice. To address this challenge, we developed a tri-light warning system based on conformal prediction for rapidly stratification of COVID-19 inpatients. This system can automatically extract radiomic features from CT images and integrate clinical record information to output a prediction probability, as well as a credibility of each prediction. This system classifies patients in the general ward into red label (high risk) indicating a possible admission to ICU care, yellow label (uncertain risk) indicating closer monitoring, and green label (low risk) indicating a stable condition. The subsequent health policies can be further designed based on this system according to the specific needs of different hospitals. Extensive experiment from a multi-center cohort (n= 8,721) shows that our method is applicable to both the original strain and the variant strains of COVID-19. Given the rapid mutation rate of COVID-19, the proposed system demonstrates its potential to identify epidemiological risks early to improve patient stratification performance under data shift.

Pre-COVID resting-state brain activity in the fusiform gyrus prospectively predicts social anxiety alterations during the pandemic (preprint)

Persistent social anxiety (SA) has been reported to be associated with the coronavirus disease 2019 (COVID-19) pandemic, but the neurobiopsychological mechanisms underlying this relationship remain unclear. This study aimed to elucidate the neurofunctional markers for the development of SA during the pandemic and the potential roles of COVID-related posttraumatic stress symptoms (PTSS) in the brain-SA alterations link. Before the COVID-19 pandemic (T1), 100 general college students underwent baseline brain resting-state magnetic resonance imaging and behavioral tests for SA. During the period of community-level outbreaks (T2), these students were recontacted to undergo follow-up assessments of SA and COVID-related PTSS. Whole-brain correlation analyses and prediction analyses found that pre-pandemic spontaneous neural activity (measured by fractional amplitude of low-frequency fluctuations) in the right fusiform gyrus (FG) was positively linked with SA alterations (T2 – T1) during the pandemic. Moreover, mediation analyses revealed a mediating role of COVID-specific PTSS in the association of right FG activity with SA alterations. Importantly, our results persisted even after adjusting for the effects of pre-pandemic family socioeconomic status, other stressful life events, and general anxiety. Overall, our study provides fresh evidence for neurofunctional markers of COVID-induced aggravation of SA and may help individuals vulnerable to SA exacerbation benefit from targeted clinical interventions.