SnapShot: COVID-19.

Coronavirus disease 2019 (COVID-19) is a novel respiratory illness caused by SARS-CoV-2. Viral entry is mediated through viral spike protein and host ACE2 enzyme interaction. Most cases are mild; severe disease often involves cytokine storm and organ failure. Therapeutics including antivirals, immunomodulators, and vaccines are in development. To view this SnapShot, open or download the PDF.

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

Biomedical Research Goes Viral: Dangers and Opportunities.

Researchers around the globe have been mounting, accelerating, and redeploying efforts across disciplines and organizations to tackle the SARS-CoV-2 outbreak. However, humankind continues to be afflicted by numerous other devastating diseases in increasing numbers. Here, we outline considerations and opportunities toward striking a good balance between maintaining and redefining research priorities.

ORF8 and ORF3b antibodies are accurate serological markers of early and late SARS-CoV-2 infection.

The SARS-CoV-2 virus emerged in December 2019 and has caused a worldwide pandemic due to the lack of any pre-existing immunity. Accurate serology testing is urgently needed to help diagnose infection, determine past exposure of populations and assess the response to a future vaccine. The landscape of antibody responses to SARS-CoV-2 is unknown. In this study, we utilized the luciferase immunoprecipitation system to assess the antibody responses to 15 different SARS-CoV-2 antigens in patients with COVID-19. We identified new targets of the immune response to SARS-CoV-2 and show that nucleocapsid, open reading frame (ORF)8 and ORF3b elicit the strongest specific antibody responses. ORF8 and ORF3b antibodies, taken together as a cluster of points, identified 96.5% of COVID-19 samples at early and late time points of disease with 99.5% specificity. Our findings could be used to develop second-generation diagnostic tests to improve serological assays for COVID-19 and are important in understanding pathogenicity.

Single-cell landscape of immunological responses in patients with COVID-19.

In coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the relationship between disease severity and the host immune response is not fully understood. Here we performed single-cell RNA sequencing in peripheral blood samples of 5 healthy donors and 13 patients with COVID-19, including moderate, severe and convalescent cases. Through determining the transcriptional profiles of immune cells, coupled with assembled T cell receptor and B cell receptor sequences, we analyzed the functional properties of immune cells. Most cell types in patients with COVID-19 showed a strong interferon-α response and an overall acute inflammatory response. Moreover, intensive expansion of highly cytotoxic effector T cell subsets, such as CD4+ effector-GNLY (granulysin), CD8+ effector-GNLY and NKT CD160, was associated with convalescence in moderate patients. In severe patients, the immune landscape featured a deranged interferon response, profound immune exhaustion with skewed T cell receptor repertoire and broad T cell expansion. These findings illustrate the dynamic nature of immune responses during disease progression.

Immunology of COVID-19: Current State of the Science.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected millions of people worldwide, igniting an unprecedented effort from the scientific community to understand the biological underpinning of COVID19 pathophysiology. In this Review, we summarize the current state of knowledge of innate and adaptive immune responses elicited by SARS-CoV-2 infection and the immunological pathways that likely contribute to disease severity and death. We also discuss the rationale and clinical outcome of current therapeutic strategies as well as prospective clinical trials to prevent or treat SARS-CoV-2 infection.

Unbiased Screens Show CD8+ T Cells of COVID-19 Patients Recognize Shared Epitopes in SARS-CoV-2 that Largely Reside outside the Spike Protein.

Developing effective strategies to prevent or treat coronavirus disease 2019 (COVID-19) requires understanding the natural immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We used an unbiased, genome-wide screening technology to determine the precise peptide sequences in SARS-CoV-2 that are recognized by the memory CD8+ T cells of COVID-19 patients. In total, we identified 3-8 epitopes for each of the 6 most prevalent human leukocyte antigen (HLA) types. These epitopes were broadly shared across patients and located in regions of the virus that are not subject to mutational variation. Notably, only 3 of the 29 shared epitopes were located in the spike protein, whereas most epitopes were located in ORF1ab or the nucleocapsid protein. We also found that CD8+ T cells generally do not cross-react with epitopes in the four seasonal coronaviruses that cause the common cold. Overall, these findings can inform development of next-generation vaccines that better recapitulate natural CD8+ T cell immunity to SARS-CoV-2.

Orthogonal SARS-CoV-2 Serological Assays Enable Surveillance of Low-Prevalence Communities and Reveal Durable Humoral Immunity.

We conducted a serological study to define correlates of immunity against SARS-CoV-2. Compared to those with mild coronavirus disease 2019 (COVID-19) cases, individuals with severe disease exhibited elevated virus-neutralizing titers and antibodies against the nucleocapsid (N) and the receptor binding domain (RBD) of the spike protein. Age and sex played lesser roles. All cases, including asymptomatic individuals, seroconverted by 2 weeks after PCR confirmation. Spike RBD and S2 and neutralizing antibodies remained detectable through 5-7 months after onset, whereas α-N titers diminished. Testing 5,882 members of the local community revealed only 1 sample with seroreactivity to both RBD and S2 that lacked neutralizing antibodies. This fidelity could not be achieved with either RBD or S2 alone. Thus, inclusion of multiple independent assays improved the accuracy of antibody tests in low-seroprevalence communities and revealed differences in antibody kinetics depending on the antigen. We conclude that neutralizing antibodies are stably produced for at least 5-7 months after SARS-CoV-2 infection.

Acute SARS-CoV-2 Infection Impairs Dendritic Cell and T Cell Responses.

The SARS-CoV-2 pandemic has resulted in millions of infections, yet the role of host immune responses in early COVID-19 pathogenesis remains unclear. By investigating 17 acute and 24 convalescent patients, we found that acute SARS-CoV-2 infection resulted in broad immune cell reduction including T, natural killer, monocyte, and dendritic cells (DCs). DCs were significantly reduced with functional impairment, and ratios of conventional DCs to plasmacytoid DCs were increased among acute severe patients. Besides lymphocytopenia, although neutralizing antibodies were rapidly and abundantly generated in patients, there were delayed receptor binding domain (RBD)- and nucleocapsid protein (NP)-specific T cell responses during the first 3 weeks after symptoms onset. Moreover, acute RBD- and NP-specific T cell responses included relatively more CD4 T cells than CD8 T cells. Our findings provided evidence that impaired DCs, together with timely inverted strong antibody but weak CD8 T cell responses, could contribute to acute COVID-19 pathogenesis and have implications for vaccine development.

Population flow drives spatio-temporal distribution of COVID-19 in China.

Sudden, large-scale and diffuse human migration can amplify localized outbreaks of disease into widespread epidemics1-4. Rapid and accurate tracking of aggregate population flows may therefore be epidemiologically informative. Here we use 11,478,484 counts of mobile phone data from individuals leaving or transiting through the prefecture of Wuhan between 1 January and 24 January 2020 as they moved to 296 prefectures throughout mainland China. First, we document the efficacy of quarantine in ceasing movement. Second, we show that the distribution of population outflow from Wuhan accurately predicts the relative frequency and geographical distribution of infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until 19 February 2020, across mainland China. Third, we develop a spatio-temporal 'risk source' model that leverages population flow data (which operationalize the risk that emanates from epidemic epicentres) not only to forecast the distribution of confirmed cases, but also to identify regions that have a high risk of transmission at an early stage. Fourth, we use this risk source model to statistically derive the geographical spread of COVID-19 and the growth pattern based on the population outflow from Wuhan; the model yields a benchmark trend and an index for assessing the risk of community transmission of COVID-19 over time for different locations. This approach can be used by policy-makers in any nation with available data to make rapid and accurate risk assessments and to plan the allocation of limited resources ahead of ongoing outbreaks.

Virological assessment of hospitalized patients with COVID-2019.

Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in late 20191,2. Initial outbreaks in China involved 13.8% of cases with severe courses, and 6.1% of cases with critical courses3. This severe presentation may result from the virus using a virus receptor that is expressed predominantly in the lung2,4; the same receptor tropism is thought to have determined the pathogenicity-but also aided in the control-of severe acute respiratory syndrome (SARS) in 20035. However, there are reports of cases of COVID-19 in which the patient shows mild upper respiratory tract symptoms, which suggests the potential for pre- or oligosymptomatic transmission6-8. There is an urgent need for information on virus replication, immunity and infectivity in specific sites of the body. Here we report a detailed virological analysis of nine cases of COVID-19 that provides proof of active virus replication in tissues of the upper respiratory tract. Pharyngeal virus shedding was very high during the first week of symptoms, with a peak at 7.11 × 108 RNA copies per throat swab on day 4. Infectious virus was readily isolated from samples derived from the throat or lung, but not from stool samples-in spite of high concentrations of virus RNA. Blood and urine samples never yielded virus. Active replication in the throat was confirmed by the presence of viral replicative RNA intermediates in the throat samples. We consistently detected sequence-distinct virus populations in throat and lung samples from one patient, proving independent replication. The shedding of viral RNA from sputum outlasted the end of symptoms. Seroconversion occurred after 7 days in 50% of patients (and by day 14 in all patients), but was not followed by a rapid decline in viral load. COVID-19 can present as a mild illness of the upper respiratory tract. The confirmation of active virus replication in the upper respiratory tract has implications for the containment of COVID-19.

Desorption Separation Ionization Mass Spectrometry (DSI-MS) for Rapid Analysis of COVID-19.

During the coronavirus disease 2019 (COVID-19) pandemic, which has witnessed over 772 million confirmed cases and over 6 million deaths globally, the outbreak of COVID-19 has emerged as a significant medical challenge affecting both affluent and impoverished nations. Therefore, there is an urgent need to explore the disease mechanism and to implement rapid detection methods. To address this, we employed the desorption separation ionization (DSI) device in conjunction with a mass spectrometer for the efficient detection and screening of COVID-19 urine samples. The study encompassed patients with COVID-19, healthy controls (HC), and patients with other types of pneumonia (OP) to evaluate their urine metabolomic profiles. Subsequently, we identified the differentially expressed metabolites in the COVID-19 patients and recognized amino acid metabolism as the predominant metabolic pathway involved. Furthermore, multiple established machine learning algorithms validated the exceptional performance of the metabolites in discriminating the COVID-19 group from healthy subjects, with an area under the curve of 0.932 in the blind test set. This study collectively suggests that the small-molecule metabolites detected from urine using the DSI device allow for rapid screening of COVID-19, taking just three minutes per sample. This approach has the potential to expand our understanding of the pathophysiological mechanisms of COVID-19 and offers a way to rapidly screen patients with COVID-19 through the utilization of machine learning algorithms.

Establishment and application of a quadruplex real-time RT-qPCR assay for differentiation of TGEV, PEDV, PDCoV, and PoRVA.

Porcine viral diarrhea is a common ailment in clinical settings, causing significant economic losses to the swine industry. Notable culprits behind porcine viral diarrhea encompass transmissible gastroenteritis virus (TGEV), porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and porcine rotavirus-A (PoRVA). Co-infections involving the viruses are a common occurrence in clinical settings, thereby amplifying the complexities associated with differential diagnosis. As a consequence, it is therefore necessary to develop a method that can detect and differentiate all four porcine diarrhea viruses (TGEV, PEDV, PDCoV, and PoRVA) with a high sensitivity and specificity. Presently, polymerase chain reaction (PCR) is the go-to method for pathogen detection. In comparison to conventional PCR, TaqMan real-time PCR offers heightened sensitivity, superior specificity, and enhanced accuracy. This study aimed to develop a quadruplex real-time RT-qPCR assay, utilizing TaqMan probes, for the distinctive detection of TGEV, PEDV, PDCoV, and PoRVA. The quadruplex real-time RT-qPCR assay, as devised in this study, exhibited the capacity to avoid the detection of unrelated pathogens and demonstrated commendable specificity, sensitivity, repeatability, and reproducibility, boasting a limit of detection (LOD) of 27 copies/µL. In a comparative analysis involving 5483 clinical samples, the results from the commercial RT-qPCR kit and the quadruplex RT-qPCR for TGEV, PEDV, PDCoV, and PoRVA detection were entirely consistent. Following sample collection from October to March in Guangxi Zhuang Autonomous Region, we assessed the prevalence of TGEV, PEDV, PDCoV, and PoRVA in piglet diarrhea samples, revealing positive detection rates of 0.2 % (11/5483), 8.82 % (485/5483), 1.22 % (67/5483), and 4.94 % (271/5483), respectively. The co-infection rates of PEDV/PoRVA, PEDV/PDCoV, TGEV/PED/PoRVA, and PDCoV/PoRVA were 0.39 %, 0.11 %, 0.01 %, and 0.03 %, respectively, with no detection of other co-infections, as determined by the quadruplex real-time RT-qPCR. This research not only established a valuable tool for the simultaneous differentiation of TGEV, PEDV, PDCoV, and PoRVA in practical applications but also provided crucial insights into the prevalence of these viral pathogens causing diarrhea in Guangxi.

Quantitative assay to analyze neutralization and inhibition of authentic Middle East respiratory syndrome coronavirus.

To date, there is no licensed vaccine for Middle East respiratory syndrome coronavirus (MERS-CoV). Therefore, MERS-CoV is one of the diseases targeted by the Coalition for Epidemic Preparedness Innovations (CEPI) vaccine development programs and has been classified as a priority disease by the World Health Organization (WHO). An important measure of vaccine immunogenicity and antibody functionality is the detection of virus-neutralizing antibodies. We have developed and optimized a microneutralization assay (MNA) using authentic MERS-CoV and standardized automatic counting of virus foci. Compared to our standard virus neutralization assay, the MNA showed improved sensitivity when analyzing 30 human sera with good correlation of results (Spearman's correlation coefficient r = 0.8917, p value < 0.0001). It is important to use standardized materials, such as the WHO international standard (IS) for anti-MERS-CoV immunoglobulin G, to compare the results from clinical trials worldwide. Therefore, in addition to the neutralizing titers (NT50 = 1384, NT80 = 384), we determined the IC50 and IC80 of WHO IS in our MNA to be 0.67 IU/ml and 2.6 IU/ml, respectively. Overall, the established MNA is well suited to reliably quantify vaccine-induced neutralizing antibodies with high sensitivity.

A multiplex real-time RT-qPCR assay for simultaneous detection of porcine epidemic diarrhea virus, porcine deltacoronavirus, and swine acute diarrhea syndrome coronavirus.

Porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and swine acute diarrhea syndrome coronavirus (SADS-CoV) cause intestinal diseases with similar manifestations in suckling piglets. In this study, we developed a multiplex real-time PCR for differential diagnosis of PEDV, PDCoV, and SADS-CoV. The assay demonstrated high specificity with a detection limit of 5 copies/µl for each virus. The assay specifically detected PEDV, PDCoV, and SADS-CoV and excluded all other swine pathogens circulating in pigs. Furthermore, the assay exhibited satisfactory performance in analyzing clinical samples. The data indicate that the newly developed multiplex real-time PCR method can be applied for differential diagnosis of porcine enteric coronaviruses.

Pyrococcus furiosus Argonaute-mediated porcine epidemic diarrhea virus detection.

Porcine epidemic diarrhea virus (PEDV), an enteric coronavirus, induces severe vomiting and acute watery diarrhea in unweaned piglets. The pig industry has suffered tremendous financial losses due to the high mortality rate of piglets caused by PEDV. Consequently, a simple and rapid on-site diagnostic technology is crucial for preventing and controlling PEDV. This study established a detection method for PEDV using recombinase-aided amplification (RAA) and Pyrococcus furiosus Argonaute (PfAgo), which can detect 100 copies of PEDV without cross-reactivity with other pathogens. The entire reaction of RAA and PfAgo to detect PEDV does not require sophisticated instruments, and the reaction results can be observed with the naked eye. Overall, this integrated RAA-PfAgo cleavage assay is a practical tool for accurately and quickly detecting PEDV. KEY POINTS: • PfAgo has the potential to serve as a viable molecular diagnostic tool for the detection and diagnosis of viral genomes • The RAA-PfAgo detection technique has a remarkable level of sensitivity and specificity • The RAA-PfAgo detection system can identify PEDV without needing advanced equipment.

A portable transistor immunosensor for fast identification of porcine epidemic diarrhea virus.

Widespread distribution of porcine epidemic diarrhea virus (PEDV) has led to catastrophic losses to the global pig farming industry. As a result, there is an urgent need for rapid, sensitive and accurate tests for PEDV to enable timely and effective interventions. In the present study, we develop and validate a floating gate carbon nanotubes field-effect transistor (FG CNT-FET)-based portable immunosensor for rapid identification of PEDV in a sensitive and accurate manner. To improve the affinity, a unique PEDV spike protein-specific monoclonal antibody is prepared by purification, and subsequently modified on FG CNT-FET sensor to recognize PEDV. The developed FET biosensor enables highly sensitive detection (LoD: 8.1 fg/mL and 100.14 TCID50/mL for recombinant spike proteins and PEDV, respectively), as well as satisfactory specificity. Notably, an integrated portable platform consisting of a pluggable FG CNT-FET chip and a portable device can discriminate PEDV positive from negative samples and even identify PEDV and porcine deltacoronavirus within 1 min with 100% accuracy. The portable sensing platform offers the capability to quickly, sensitively and accurately identify PEDV, which further points to a possibility of point of care (POC) applications of large-scale surveillance in pig breeding facilities.

Application of a portable instrument for rapid and reliable detection of SARS-CoV-2 infection in any environment.

The ongoing outbreak of the novel coronavirus (SARS-CoV-2) infection is creating serious challenges for health laboratories that seek to identify viral infections as early as possible, optimally at the earliest appearance of symptom. Indeed, there is urgent need to develop and deploy robust diagnostic methodologies not only to use in health laboratory environments but also directly in places where humans circulate and spread the virus such as airports, trains, boats, and any public aggregation places. The success of a reliable and sensitive asymptomatic diagnosis relies on the identification and measurement of informative biomarkers from human host and virus in a rapid, sensitive, and inexpensive manner. The objective of this article is to describe an innovative multidisciplinary approach to develop an efficient, inexpensive, and easy-to-use portable instrument (bCUBE® by Hyris Ltd) that can be employed as a surveillance system for the emergency caused by SARS-CoV-2. A solution for Coronavirus testing, compliant with CDC guidelines, is scheduled to be released in the next weeks. In addition, we will describe a workflow and path of an integrated multi-omic approach that will lead to host and pathogen biomarker discovery in order to train the instrument to provide reliable results based on a specific biomarker's fingerprint of SARS-CoV-2 infection.

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Objective: To construct a deep learning-based target detection method to help radiologists perform rapid diagnosis of lesions in the CT images of patients with novel coronavirus pneumonia (NCP) by restoring detailed information and mining local information. Methods: We present a deep learning approach that integrates detail upsampling and attention guidance. A linear upsampling algorithm based on bicubic interpolation algorithm was adopted to improve the restoration of detailed information within feature maps during the upsampling phase. Additionally, a visual attention mechanism based on vertical and horizontal spatial dimensions embedded in the feature extraction module to enhance the capability of the object detection algorithm to represent key information related to NCP lesions. Results: Experimental results on the NCP dataset showed that the detection method based on the detail upsampling algorithm improved the recall rate by 1.07% compared with the baseline model, with the AP50 reaching 85.14%. After embedding the attention mechanism in the feature extraction module, 86.13% AP50, 73.92% recall, and 90.37% accuracy were achieved, which were better than those of the popular object detection models. Conclusion: The feature information mining of CT images based on deep learning can further improve the lesion detection ability. The proposed approach helps radiologists rapidly identify NCP lesions on CT images and provides an important clinical basis for early intervention and high-intensity monitoring of NCP patients.