Porcine Enteric Alphacoronavirus Entry through Multiple Pathways (Caveolae, Clathrin, and Macropinocytosis) Requires Rab GTPases for Endosomal Transport.

Porcine enteric alphacoronavirus (PEAV) is a new bat HKU2-like porcine coronavirus, and its endemic outbreak has caused severe economic losses to the pig industry. Its broad cellular tropism suggests a potential risk of cross-species transmission. A limited understanding of PEAV entry mechanisms may hinder a rapid response to potential outbreaks. This study analyzed PEAV entry events using chemical inhibitors, RNA interference, and dominant-negative mutants. PEAV entry into Vero cells depended on three endocytic pathways: caveolae, clathrin, and macropinocytosis. Endocytosis requires dynamin, cholesterol, and a low pH. Rab5, Rab7, and Rab9 GTPases (but not Rab11) regulate PEAV endocytosis. PEAV particles colocalize with EEA1, Rab5, Rab7, Rab9, and Lamp-1, suggesting that PEAV translocates into early endosomes after internalization, and Rab5, Rab7, and Rab9 regulate trafficking to lysosomes before viral genome release. PEAV enters porcine intestinal cells (IPI-2I) through the same endocytic pathway, suggesting that PEAV may enter various cells through multiple endocytic pathways. This study provides new insights into the PEAV life cycle. IMPORTANCE Emerging and reemerging coronaviruses cause severe human and animal epidemics worldwide. PEAV is the first bat-like coronavirus to cause infection in domestic animals. However, the PEAV entry mechanism into host cells remains unknown. This study demonstrates that PEAV enters into Vero or IPI-2I cells through caveola/clathrin-mediated endocytosis and macropinocytosis, which does not require a specific receptor. Subsequently, Rab5, Rab7, and Rab9 regulate PEAV trafficking from early endosomes to lysosomes, which is pH dependent. The results advance our understanding of the disease and help to develop potential new drug targets against PEAV.

Empirical Quantitative Analysis of COVID-19 Forecasting Models (preprint)

COVID-19 has been a public health emergency of international concern since early 2020. Reliable forecasting is critical to diminish the impact of this disease. To date, a large number of different forecasting models have been proposed, mainly including statistical models, compartmental models, and deep learning models. However, due to various uncertain factors across different regions such as economics and government policy, no forecasting model appears to be the best for all scenarios. In this paper, we perform quantitative analysis of COVID-19 forecasting of confirmed cases and deaths across different regions in the United States with different forecasting horizons, and evaluate the relative impacts of the following three dimensions on the predictive performance (improvement and variation) through different evaluation metrics: model selection, hyperparameter tuning, and the length of time series required for training. We find that if a dimension brings about higher performance gains, if not well-tuned, it may also lead to harsher performance penalties. Furthermore, model selection is the dominant factor in determining the predictive performance. It is responsible for both the largest improvement and the largest variation in performance in all prediction tasks across different regions. While practitioners may perform more complicated time series analysis in practice, they should be able to achieve reasonable results if they have adequate insight into key decisions like model selection.

Research on pregnant women suspected of having COVID-19 in the epidemic outbreak area (preprint)

Background COVID-19 has become a major public health problem around the world. There are limited data on maternal and neonatal outcomes of pregnant women with COVID-19 pneumonia. The purpose of this study is to investigate and analysis the clinical features, imaging findings, related laboratory indicators, treatments and outcomes of maternal-fetal for cases of suspected infection COVID-19 pregnant women in outbreak area in order to provide reference for clinical work.Methods A case-control study was conducted to compare clinical features, treatment, maternal and neonatal outcomes of pregnant women with and without COVID-19 pneumonia.Results One confirmed patient who was discharged from hospital after a negative RT-PCR result, was readmitted and subsequently tested positive on RT-PCR. The vaginal delivery rate and gestational week of confirmed case group showed significantly lower than 2019 control group. Pulmonary CT images were initially same between confirmed group and suspected group, but changed over time with different trends. The two case groups shared similar dynamic profiles on blood routine test. Four confirmed cases which had COVID-19 antibody test were all positive for IgG antibody and negative for IgM antibody, via both umbilical cord blood and the newborns. Fifteen of newborns (three confirmed and twelve suspected cases) at nearly three months old were tested negative by antibodies.Conclusions Pulmonary CT images showed different trends with the extending of time between confirmed group and suspected group. Blood test results weren’t strong enough to make differential diagnosis between two case groups. Perform antibody test can understand the antibody responses mounted in response to the virus, and to identify individuals who are potentially immune to re-infection. Infant obtain COVID-19 IgG antibody from maternal that only may last for less than three months.

Genetic determinants of COVID-19 drug efficacy revealed by genome-wide CRISPR screens (preprint)

Immunomodulatory agents dexamethasone and colchicine, antiviral drugs remdesivir, favipiravir and ribavirin, as well as antimalarial drugs chloroquine phosphate and hydroxychloroquine are currently used in the combat against COVID-19. However, whether some of these drugs have clinical efficacy for COVID-19 is under debate. Moreover, these drugs are applied in COVID-19 patients with little knowledge of genetic biomarkers, which will hurt patient outcome. To answer these questions, we designed a screen approach that could employ genome-wide sgRNA libraries to systematically uncover genes crucial for these drugs' action. Here we present our findings, including genes crucial for the import, export, metabolic activation and inactivation of remdesivir, as well as genes that regulate colchicine and dexamethasone's immunosuppressive effects. Our findings provide preliminary information for developing urgently needed genetic biomarkers for these drugs. Such biomarkers will help better interpret COVID-19 clinical trial data and point to how to stratify COVID-19 patients for proper treatment with these drugs.

Binding Mode of SARS-CoV2 Fusion Peptide to Human Cellular Membrane (preprint)

Infection of human cells by the SARS-CoV2 relies on its binding to a specific receptor and subsequent fusion of the viral and host cell membranes. The fusion peptide (FP), a short peptide segment in the spike protein, plays a central role in the initial penetration of the virus into the host cell membrane, followed by the fusion of the two membranes. Here, we use an array of molecular dynamics (MD) simulations taking advantage of the Highly Mobile Membrane Mimetic (HMMM) model, to investigate the interaction of the SARS-CoV2 FP with a lipid bilayer representing mammalian cellular membranes at an atomic level, and to characterize the membrane-bound form of the peptide. Six independent systems were generated by changing the initial positioning and orientation of the FP with respect to the membrane, and each system was simulated in five independent replicas. In 60% of the simulations, the FP reaches a stable, membrane-bound configuration where the peptide deeply penetrated into the membrane. Clustering of the results reveals two major membrane binding modes, the helix-binding mode and the loop-binding mode. Taken into account the sequence conservation among the viral FPs and the results of mutagenesis studies establishing the role of specific residues in the helical portion of the FP in membrane association, we propose that the helix-binding mode represents more closely the biologically relevant form. In the helix-binding mode, the helix is stabilized in an oblique angle with respect to the membrane with its N-terminus tilted towards the membrane core. Analysis of the FP-lipid interactions shows the involvement of specific residues of the helix in membrane binding previously described as the fusion active core residues. Taken together, the results shed light on a key step involved in SARS-CoV2 infection with potential implications in designing novel inhibitors.

Interaction network of SARS-CoV-2 with host receptome through spike protein (preprint)

Host cellular receptors are key determinants of virus tropism and pathogenesis. Virus utilizes multiple receptors for attachment, entry, or specific host responses. However, other than ACE2, little is known about SARS-CoV-2 receptors. Furthermore, ACE2 cannot easily interpret the multi-organ tropisms of SARS-CoV-2 nor the clinical differences between SARS-CoV-2 and SARS-CoV. To identify host cell receptors involved in SARS-CoV-2 interactions, we performed genomic receptor profiling to screen almost all human membrane proteins, with SARS-CoV-2 capsid spike (S) protein as the target. Twelve receptors were identified, including ACE2. Most receptors bind at least two domains on S protein, the receptor-binding-domain (RBD) and the N-terminal-domain (NTD), suggesting both are critical for virus-host interaction. Ectopic expression of ASGR1 or KREMEN1 is sufficient to enable entry of SARS-CoV-2, but not SARS-CoV and MERS-CoV. Analyzing single-cell transcriptome profiles from COVID-19 patients revealed that virus susceptibility in airway epithelial ciliated and secretory cells and immune macrophages highly correlates with expression of ACE2, KREMEN1 and ASGR1 respectively, and ACE2/ASGR1/KREMEN1 (ASK) together displayed a much better correlation than any individual receptor. Based on modeling of systemic SARS-CoV-2 host interactions through S receptors, we revealed ASK correlation with SARS-CoV-2 multi-organ tropism and provided potential explanations for various COVID-19 symptoms. Our study identified a panel of SARS-CoV-2 receptors with diverse binding properties, biological functions, and clinical correlations or implications, including ASGR1 and KREMEN1 as the alternative entry receptors, providing insights into critical interactions of SARS-CoV-2 with host, as well as a useful resource and potential drug targets for COVID-19 investigation.

A population-based retrospective study of the spread of COVID-19 from Wuhan to Henan province, China (preprint)

The epidemic of COVID-19 has now spread globally and affected over 110 countries. As of Mar 10th, using publicly available data and official news reports in Henan province, we tracked a total of 1272 cases and a retrospective study was conducted to investigate the related factors in COVID-19 spread and control. We confirmed 554 primary patients had travel or residential history of Wuhan in the recent 2 weeks. Secondary cases accounted for 77.9% (141/181) among all the patients aged 61 or older, in whom contacted with unconfirmed returnees from Wuhan was responsible for 27.0% (38/141). The median incubate period is 7 (IQR, 4-10) days by analyzing time information in 469 cases. For 442 patients with discharge dates, the duration from onset to cure is 19 (IQR, 15-23) days. The time from onset to seeking care at a hospital varied in age groups, and differed between primary and secondary cases. Patients visiting different hospitals affected the time from seeking care to cure. Thus, our results showed the spread of COVID-19 and factors associated with outcomes of patients in Henan province, which helps to understand the epidemiological features outside of the epidemic area and control the disease in other regions and countries.

Highly accurate and sensitive diagnostic detection of SARS-CoV-2 by digital PCR (preprint)

BACKGROUND: The outbreak of COVID-19 caused by a novel Coronavirus (termed SARS-CoV-2) has spread to over 140 countries around the world. Currently, reverse transcription quantitative qPCR (RT-qPCR) is used as the gold standard for diagnostics of SARS-CoV-2. However, the positive rate of RT-qPCR assay of pharyngeal swab samples are reported to vary from 30~60%. More accurate and sensitive methods are urgently needed to support the quality assurance of the RT-qPCR or as an alternative diagnostic approach. METHODSWe established a reverse transcription digital PCR (RT-dPCR) protocol to detect SARS-CoV-2 on 194 clinical pharyngeal swab samples, including 103 suspected patients, 75 close contacts and 16 supposed convalescents. RESULTS: The limit of blanks (LoBs) of the RT-dPCR assays were ~1.6, ~1.6 and ~0.8 copies/reaction for ORF 1ab, N and E genes, respectively. The limit of detection (LoD) was 2 copies/reaction. For the 103 fever suspected patients, the sensitivity of SARS-CoV-2 detection was significantly improved from 28.2% by RT-qPCR to 87.4% by RT-dPCR. For close contacts, the suspect rate was greatly decreased from 21% down to 1%. The overall sensitivity, specificity and diagnostic accuracy of RT-dPCR were 90%, 100% and 93 %, respectively. In addition, quantification of the viral load for convalescents by RT-dPCR showed that a longer observation period was needed in the hospital for elderly patients. CONCLUSION: RT-dPCR could be a confirmatory method for suspected patients diagnosed by RT-qPCR. Furthermore, RT-dPCR was more sensitive and suitable for low viral load specimens from the both patients under isolation and those under observation who may not be exhibiting clinical symptoms.