SARS-CoV-2 infection aggravates chronic comorbidities of cardiovascular diseases and diabetes in mice.

Background: Cardiovascular diseases (CVDs) and diabetes mellitus (DM) are top two chronic comorbidities that increase the severity and mortality of COVID-19. However, how SARS-CoV-2 alters the progression of chronic diseases remain unclear. Methods: We used adenovirus to deliver h-ACE2 to lung to enable SARS-CoV-2 infection in mice. SARS-CoV-2's impacts on pathogenesis of chronic diseases were studied through histopathological, virologic and molecular biology analysis. Results: Pre-existing CVDs resulted in viral invasion, ROS elevation and activation of apoptosis pathways contribute myocardial injury during SARS-CoV-2 infection. Viral infection increased fasting blood glucose and reduced insulin response in DM model. Bone mineral density decreased shortly after infection, which associated with impaired PI3K/AKT/mTOR signaling. Conclusion: We established mouse models mimicked the complex pathological symptoms of COVID-19 patients with chronic diseases. Pre-existing diseases could impair the inflammatory responses to SARS-CoV-2 infection, which further aggravated the pre-existing diseases. This work provided valuable information to better understand the interplay between the primary diseases and SARS-CoV-2 infection.

ACE2 partially dictates the host range and tropism of SARS-CoV-2.

COVID-19, which is caused by SARS-CoV-2, has been declared a global pandemic. Although effective strategies have been applied to treat the disease, much is still unknown about this novel virus. SARS-CoV-2 enters host cells through ACE2, which is a component of the angiotensin-regulating system. Binding of the SARS-CoV-2 S protein to ACE2 is a prerequisite for SARS-CoV-2 infection. Many studies have indicated a close relationship between ACE2 expression and SARS-CoV-2 infection. The structural basis of receptor recognition by SARS-CoV-2 has been analyzed in detail. The diversification of the ACE2 sequence due to ACE2 polymorphisms and alternative splicing has to a large extent affected the susceptibility of different species. Differential ACE2 expression makes specific populations more prone to be infected, and ACE2 also plays a role in the broad tropism of SARS-CoV-2 in human organs and tissues. In this review, we comprehensively summarize how the ACE2 expression profile affects the host range and tropism of SARS-CoV-2, which will provide mechanistic insights into the susceptibilities and outcomes of SARS-CoV-2 infection.

A mechanism for SARS-CoV-2 RNA capping and its inhibition by nucleotide analog inhibitors.

Decoration of cap on viral RNA plays essential roles in SARS-CoV-2 proliferation. Here, we report a mechanism for SARS-CoV-2 RNA capping and document structural details at atomic resolution. The NiRAN domain in polymerase catalyzes the covalent link of RNA 5' end to the first residue of nsp9 (termed as RNAylation), thus being an intermediate to form cap core (GpppA) with GTP catalyzed again by NiRAN. We also reveal that triphosphorylated nucleotide analog inhibitors can be bonded to nsp9 and fit into a previously unknown "Nuc-pocket" in NiRAN, thus inhibiting nsp9 RNAylation and formation of GpppA. S-loop (residues 50-KTN-52) in NiRAN presents a remarkable conformational shift observed in RTC bound with sofosbuvir monophosphate, reasoning an "induce-and-lock" mechanism to design inhibitors. These findings not only improve the understanding of SARS-CoV-2 RNA capping and the mode of action of NAIs but also provide a strategy to design antiviral drugs.

Development of Single-Cell Transcriptomics and Its Application in COVID-19.

Over the last three years, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related health crisis has claimed over six million lives and caused USD 12 trillion losses to the global economy. SARS-CoV-2 continuously mutates and evolves with a high basic reproduction number (R0), resulting in a variety of clinical manifestations ranging from asymptomatic infection to acute respiratory distress syndrome (ARDS) and even death. To gain a better understanding of coronavirus disease 2019 (COVID-19), it is critical to investigate the components that cause various clinical manifestations. Single-cell sequencing has substantial advantages in terms of identifying differentially expressed genes among individual cells, which can provide a better understanding of the various physiological and pathological processes. This article reviewed the use of single-cell transcriptomics in COVID-19 research, examined the immune response disparities generated by SARS-CoV-2, and offered insights regarding how to improve COVID-19 diagnosis and treatment plans.

A mechanism for SARS-CoV-2 RNA capping and its inhibition by nucleotide analogue inhibitors

Decoration of cap on viral RNA plays essential roles in SARS-CoV-2 proliferation. Here we report a mechanism for SARS-CoV-2 RNA capping and document structural details at atomic resolution. The NiRAN domain in polymerase catalyzes the covalent link of RNA 5’ end to the first residue of nsp9 (termed as RNAylation), thus being an intermediate to form cap core (GpppA) with GTP catalyzed again by NiRAN. We also reveal that triphosphorylated nucleotide analogue inhibitors can be bonded to nsp9 and fit into a previously unknown ‘Nuc-pocket’ in NiRAN, thus inhibiting nsp9 RNAylation and formation of GpppA. S-loop (residues 50-KTN-52) in NiRAN presents a remarkable conformational shift observed in RTC bound with sofosbuvir monophosphate, reasoning an ‘induce-and-lock’ mechanism to design inhibitors. These findings not only improve the understanding of SARS-CoV-2 RNA capping and the mode of action of NAIs, but also provide a strategy to design antiviral drugs. Graphical Structural analyses reveal how proteins from SARS-CoV-2 cooperate and use GTP to form the cap on viral mRNA, and how this process is interrupted by nucleotide analogues that serve as antiviral drugs.

5' UTR barcode of the 2019 novel Coronavirus leads to insights into its virulence

"Novel coronavirus 2019" (which was renamed subsequently "severe acute respiratory syndrome coronavirus-2" (SARS-CoV-2) on 11 February 2020) caused a pneumonia outbreak in Wuhan (Hubei Province, China) in December 2019. In our previous studies, two important findings regarding SARS-CoV-2 were reported, for the first time, on 21 January 2020: (1) multiple alternative translations of a coding sequence in genomes of betacoronavirus subgroup B;(2) a novel mutation in the spike (S) proteins of betacoronavirus. By this mutation, SARS-CoV-2 acquired a cleavage site for the furin enzyme in its S protein, which is not present in the S proteins of most other betacoronaviruses (e.g. SARS-CoV). In the present study, we performed analyses of 5' untranslated regions (UTRs) in betacoronavirus. Using 5' UTR barcodes, 1,265 betacoronaviruses were clustered into four classes, and viruses in each class had similar virulence. The class 1, 2, 3 and 4 match the subgroup C, B, A and D of betacoronavirus, respectively. In particular, SARS-CoV-2 and SARS-CoV have the same 5' UTR barcode. As the main contribution of the present study, we developed 5' UTR barcoding to be used in the detection, identification, classification and phylogenetic analysis of, but not limited to coronavirus. Our method is very useful for early-warning, prevention and control of coronavirus. We found that Internal Ribosome Entry Sites (IRESs) may have important roles in the virulence of betacoronavirus. This important finding is reported, for the first time, to understand the virulence of SARS-CoV-2 at the molecular level. This finding can be used directly for vaccine development and design of drugs against SARS-CoV-2, but such development is not limited to coronavirus only. In addition, we propose that the upstream hairpin structures neighboring the start codons in mRNAs have important roles in protein translation in eukaryotes.

How the Replication and Transcription Complex Functions in Jumping Transcription of SARS-CoV-2.

Background: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although unprecedented efforts are underway to develop therapeutic strategies against this disease, scientists have acquired only a little knowledge regarding the structures and functions of the CoV replication and transcription complex (RTC). Ascertaining all the RTC components and the arrangement of them is an indispensably step for the eventual determination of its global structure, leading to completely understanding all of its functions at the molecular level. Results: The main results include: 1) hairpins containing the canonical and non-canonical NSP15 cleavage motifs are canonical and non-canonical transcription regulatory sequence (TRS) hairpins; 2) TRS hairpins can be used to identify recombination regions in CoV genomes; 3) RNA methylation participates in the determination of the local RNA structures in CoVs by affecting the formation of base pairing; and 4) The eventual determination of the CoV RTC global structure needs to consider METTL3 in the experimental design. Conclusions: In the present study, we proposed the theoretical arrangement of NSP12-15 and METTL3 in the global RTC structure and constructed a model to answer how the RTC functions in the jumping transcription of CoVs. As the most important finding, TRS hairpins were reported for the first time to interpret NSP15 cleavage, RNA methylation of CoVs and their association at the molecular level. Our findings enrich fundamental knowledge in the field of gene expression and its regulation, providing a crucial basis for future studies.

SNX27 suppresses SARS-CoV-2 infection by inhibiting viral lysosome/late endosome entry.

After binding to its cell surface receptor angiotensin converting enzyme 2 (ACE2), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters the host cell through directly fusing with plasma membrane (cell surface pathway) or undergoing endocytosis traveling to lysosome/late endosome for membrane fusion (endocytic pathway). However, the endocytic entry regulation by host cell remains elusive. Recent studies show ACE2 possesses a type I PDZ binding motif (PBM) through which it could interact with a PDZ domain-containing protein such as sorting nexin 27 (SNX27). In this study, we determined the ACE2-PBM/SNX27-PDZ complex structure, and, through a series of functional analyses, we found SNX27 plays an important role in regulating the homeostasis of ACE2 receptor. More importantly, we demonstrated SNX27, together with retromer complex (the core component of the endosomal protein sorting machinery), prevents ACE2/virus complex from entering lysosome/late endosome, resulting in decreased viral entry in cells where the endocytic pathway dominates. The ACE2/virus retrieval mediated by SNX27-retromer could be considered as a countermeasure against invasion of ACE2 receptor-using SARS coronaviruses.

Simultaneous Detection of Seven Human Coronaviruses by Multiplex PCR and MALDI-TOF MS

Human coronaviruses (HCoVs) are associated with a range of respiratory symptoms. The discovery of severe acute respiratory syndrome (SARS)-CoV, Middle East respiratory syndrome, and SARS-CoV-2 pose a significant threat to human health. In this study, we developed a method (HCoV-MS) that combines multiplex PCR with matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), to detect and differentiate seven HCoVs simultaneously. The HCoV-MS method had high specificity and sensitivity, with a 1–5 copies/reaction detection limit. To validate the HCoV-MS method, we tested 163 clinical samples, and the results showed good concordance with real-time PCR. Additionally, the detection sensitivity of HCoV-MS and real-time PCR was comparable. The HCoV-MS method is a sensitive assay, requiring only 1 μL of a sample. Moreover, it is a high-throughput method, allowing 384 samples to be processed simultaneously in 30 min. We propose that this method be used to complement real-time PCR for large-scale screening studies.

High Concentration and Frequent Application of Disinfection Increase the Detection of Methicillin-Resistant Staphylococcus aureus Infections in Psychiatric Hospitals During the COVID-19 Pandemic.

The tolerance of certain multi-drug resistant bacteria to disinfectants may be promoted while the requirements of environmental disinfection have been raised in the high-risk areas of medical institutions during the COVID-19 pandemic. The current research addressed the mechanisms underlying a sharp increase in the detection of methicillin-resistant Staphylococcus aureus (MRSA) observed in a closed-management unit of elderly patients with mental disorders in 2020 as compared with the previous 4 years. We first conducted microbial detection in staff-hand and environment and a molecular epidemiology analysis, rejecting the hypothesis that the MRSA increase was due to an outbreak. Afterward, we turned to disinfectant concentration and frequency of use and analyzed the varied MRSA detection rates with different concentrations and frequencies of disinfection in 2020 and the previous 4 years. The MRSA detection rate increased with elevated concentration and frequency of disinfection, with 1,000 or 500 mg/L two times per day since January in 2020 vs. 500 mg/L 2-3 times per week in 2016-2019. When the disinfectant concentration was reduced from 1,000 to 500 mg/L, the MRSA detection decreased which indicated a modulatory role of disinfectant concentration. With a sustained frequency of disinfection in 2020, the MRSA detection rate was still higher, even after May, than that in the previous years. This suggested that the frequency of disinfection also contributed to the MRSA increase. Overall, the MRSA detection was augmented with the increase in disinfection concentration and frequency during the COVID-19 epidemic, suggesting that highly-concentrated and highly-frequent preventive long-term disinfection is not recommended without risk assessments in psychiatric hospitals.

Validated tool for early prediction of intensive care unit admission in COVID-19 patients.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) pandemic is a global threat caused by the severe acute respiratory syndrome coronavirus-2. AIM: To develop and validate a risk stratification tool for the early prediction of intensive care unit (ICU) admission among COVID-19 patients at hospital admission. METHODS: The training cohort included COVID-19 patients admitted to the Wuhan Third Hospital. We selected 13 of 65 baseline laboratory results to assess ICU admission risk, which were used to develop a risk prediction model with the random forest (RF) algorithm. A nomogram for the logistic regression model was built based on six selected variables. The predicted models were carefully calibrated, and the predictive performance was evaluated and compared with two previously published models. RESULTS: There were 681 and 296 patients in the training and validation cohorts, respectively. The patients in the training cohort were older than those in the validation cohort (median age: 63.0 vs 49.0 years, P < 0.001), and the percentages of male gender were similar (49.6% vs 49.3%, P = 0.958). The top predictors selected in the RF model were neutrophil-to-lymphocyte ratio, age, lactate dehydrogenase, C-reactive protein, creatinine, D-dimer, albumin, procalcitonin, glucose, platelet, total bilirubin, lactate and creatine kinase. The accuracy, sensitivity and specificity for the RF model were 91%, 88% and 93%, respectively, higher than those for the logistic regression model. The area under the receiver operating characteristic curve of our model was much better than those of two other published methods (0.90 vs 0.82 and 0.75). Model A underestimated risk of ICU admission in patients with a predicted risk less than 30%, whereas the RF risk score demonstrated excellent ability to categorize patients into different risk strata. Our predictive model provided a larger standardized net benefit across the major high-risk range compared with model A. CONCLUSION: Our model can identify ICU admission risk in COVID-19 patients at admission, who can then receive prompt care, thus improving medical resource allocation.

Cover Image, Volume 94, Number 1, January 2022

Front Cover Caption: The cover image is based on the Research Article Palmitoylation of SARS-CoV-2 S protein is critical for S-mediated syncytia formation and virus entry by Daoqun Li et al., https://doi.org/10.1002/jmv.27339.

Palmitoylation of SARS-CoV-2 S protein is critical for S-mediated syncytia formation and virus entry.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. The S protein is the key viral protein for associating with ACE2, the receptor for SARS-CoV-2. There are many kinds of posttranslational modifications in S protein. However, the detailed mechanism of palmitoylation of SARS-CoV-2 S remains to be elucidated. In our current study, we characterized the palmitoylation of SARS-CoV-2 S. Both the C15 and cytoplasmic tail of SARS-CoV-2 S were palmitoylated. Fatty acid synthase inhibitor C75 and zinc finger DHHC domain-containing palmitoyltransferase (ZDHHC) inhibitor 2-BP reduced the palmitoylation of S. Interestingly, palmitoylation of SARS-CoV-2 S was not required for plasma membrane targeting of S but was critical for S-mediated syncytia formation and SARS-CoV-2 pseudovirus particle entry. Overexpression of ZDHHC2, ZDHHC3, ZDHHC4, ZDHHC5, ZDHHC8, ZDHHC9, ZDHHC11, ZDHHC14, ZDHHC16, ZDHHC19, and ZDHHC20 promoted the palmitoylation of S. Furthermore, those ZDHHCs were identified to associate with SARS-CoV-2 S. Our study not only reveals the mechanism of S palmitoylation but also will shed important light into the role of S palmitoylation in syncytia formation and virus entry.

Scenario prediction of public health emergencies using infectious disease dynamics model and dynamic Bayes.

This study was aimed to discuss the predictive value of infectious disease dynamics model (IDD model) and dynamic Bayesian network (DBN) for scenario deduction of public health emergencies (PHEs). Based on the evolution law of PHEs and the meta-scenario representation of basic knowledge, this study established a DBN scenario deduction model for scenario deduction and evolution path analysis of PHEs. At the same time, based on the average field dynamics model of the SIR network, the dimensionality reduction process was performed to calculate the epidemic scale and epidemic time based on the IDD model, so as to determine the calculation methods of threshold value and epidemic time under emergency measures (quarantine). The Corona Virus Disease (COVID) epidemic was undertaken as an example to analyze the results of DBN scenario deduction, and the infectious disease dynamics model was used to analyze the number of reproductive numbers, peak arrival time, epidemic time, and latency time of the COVID epidemic. It was found that after the M1 measure was used to process the S1 state, the state probability and the probability of being true (T) were the highest, which were 91.05 and 90.21, respectively. In the sixth stage of the development of the epidemic, the epidemic had developed to level 5, the number of infected people was about 26, and the estimated loss was about 220 million yuan. The comprehensive cumulative foreground (CF) values of O1  ∼  O3 schemes were -1.34, -1.21, and -0.77, respectively, and the final CF values were -1.35, 0.01, and -0.08, respectively. The final CF value of O2 was significantly higher than the other two options. The household infection probability was the highest, which was 0.37 and 0.35 in Wuhan and China, respectively. Under the measures of home quarantine, the numbers of confirmed cases of COVID in China and Wuhan were 1.503 (95% confidential interval (CI) = 1.328  ∼  1.518) and 1.729 (95% CI = 1.107  ∼  1.264), respectively, showing good fits with the real data. On the 21st day after the quarantine measures were taken, the number of COVID across the country had an obvious peak, with the confirmed cases of 24495, and the model prediction value was 24085 (95% CI = 23988  ∼  25056). The incubation period 1/q was shortened from 8 days to 3 days, and the number of confirmed cases showed an upward trend. The peak period of confirmed cases was advanced, shortening the overall epidemic time. It showed that the prediction results of scenario deduction based on DBN were basically consistent with the actual development scenario and development status of the epidemic. It could provide corresponding decisions for the prevention and control of COVID based on the relevant parameters of the infectious disease dynamic model, which verified the rationality and feasibility of the scenario deduction method proposed in this study.

Cryo-EM Structure of an Extended SARS-CoV-2 Replication and Transcription Complex Reveals an Intermediate State in Cap Synthesis.

Transcription of SARS-CoV-2 mRNA requires sequential reactions facilitated by the replication and transcription complex (RTC). Here, we present a structural snapshot of SARS-CoV-2 RTC as it transitions toward cap structure synthesis. We determine the atomic cryo-EM structure of an extended RTC assembled by nsp7-nsp82-nsp12-nsp132-RNA and a single RNA-binding protein, nsp9. Nsp9 binds tightly to nsp12 (RdRp) NiRAN, allowing nsp9 N terminus inserting into the catalytic center of nsp12 NiRAN, which then inhibits activity. We also show that nsp12 NiRAN possesses guanylyltransferase activity, catalyzing the formation of cap core structure (GpppA). The orientation of nsp13 that anchors the 5' extension of template RNA shows a remarkable conformational shift, resulting in zinc finger 3 of its ZBD inserting into a minor groove of paired template-primer RNA. These results reason an intermediate state of RTC toward mRNA synthesis, pave a way to understand the RTC architecture, and provide a target for antiviral development.

How Does Risk-Information Communication Affect the Rebound of Online Public Opinion of Public Emergencies in China?

The rebound of online public opinion is an important driving force in inducing a secondary crisis in the case of public emergencies. Effective risk-information communication is an important means to manage online public opinion regarding emergencies. This paper employs fuzzy-set qualitative comparative analysis to discover which conditions are combined and may result in the rebound of online public opinion. Five conditions were selected: the type of public emergency, messengers, message attributes, audience, and information feedback. The study used a sample of 25 major public emergencies that occurred between 2015 and 2020 in China. The type of public emergency, audience, and information feedback emerged as critical influencing factors. Message attributes promote the rebound of online public opinion regarding public health emergencies, while messengers play a traction role in the rebound of online public opinion on other types of public emergencies. This study extends risk-information communication theory from the perspective of the type of emergency, explores the causes of rebounded online public opinion regarding public emergencies, and provides policies and suggestions for risk-information communication and online public-opinion governance during emergencies.