Virus gone wild.

An ambitious U.S. project aims to sample more than 50 animal species to clarify how the COVID-19 virus moves between people and wildlife.

Transmission dynamics, complications and mitigation strategies of the current mpox outbreak: A comprehensive review with bibliometric study.

As the mankind counters the ongoing COVID-19 pandemic by the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), it simultaneously witnesses the emergence of mpox virus (MPXV) that signals at global spread and could potentially lead to another pandemic. Although MPXV has existed for more than 50 years now with most of the human cases being reported from the endemic West and Central African regions, the disease is recently being reported in non-endemic regions too that affect more than 50 countries. Controlling the spread of MPXV is important due to its potential danger of a global spread, causing severe morbidity and mortality. The article highlights the transmission dynamics, zoonosis potential, complication and mitigation strategies for MPXV infection, and concludes with suggested 'one health' approach for better management, control and prevention. Bibliometric analyses of the data extend the understanding and provide leads on the research trends, the global spread, and the need to revamp the critical research and healthcare interventions. Globally published mpox-related literature does not align well with endemic areas/regions of occurrence which should ideally have been the scenario. Such demographic and geographic gaps between the location of the research work and the endemic epicentres of the disease need to be bridged for greater and effective translation of the research outputs to pubic healthcare systems, it is suggested.

Efficient detection of nitric oxide a biomarker associated with COVID19 via N, P co-doped C60 fullerene: a computational study.

CONTEXT: Coronavirus (COVID-19) is a novel respiratory viral infection, causing a relatively large number of deaths especially in people who underly lung diseases such as chronic obstructive pulmonary and asthma, and humans are still suffering from the limited testing capacity. In this article, a solution is proposed for the detection of COVID-19 viral infections through the analysis of exhaled breath gasses, i.e., nitric oxide, a prominent biomarker released by respiratory epithelial, as a non-invasive and time-saving approach. Here, we designed a novel and low-cost N and P co-doped C60 fullerene-based breathalyzer for the detection of NO gas exhaled from the respiratory epithelial cells. This breathalyzer shows a quick response to the detection of NO gas by directly converting NO to NO2 without passing any energy barrier (0 kcal/mol activation energy). The recovery time of breathalyzer is very short (0.98 × 103 s), whereas it is highly selective for NO sensing in the mixture of CO2 and H2O gasses. The study provides an idea for the synthesis of low-cost (compared to previously reported Au atom decorated nanostructure and metal-based breathalyzer), efficient, and highly selective N and P co-doped C60 fullerene-based breathalyzer for COVID-19 detection. METHODS: The geometries of N and P-doped systems and gas molecules are simulated using spin-polarized density functional theory calculations.

SARS-CoV-2 induces blood-brain barrier and choroid plexus barrier impairments and vascular inflammation in mice.

The coronavirus disease of 2019 (COVID-19) pandemic has led to more than 700 million confirmed cases and nearly 7 million deaths. Although severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus mainly infects the respiratory system, neurological complications are widely reported in both acute infection and long-COVID cases. Despite the success of vaccines and antiviral treatments, neuroinvasiveness of SARS-CoV-2 remains an important question, which is also centered on the mystery of whether the virus is capable of breaching the barriers into the central nervous system. By studying the K18-hACE2 infection model, we observed clear evidence of microvascular damage and breakdown of the blood-brain barrier (BBB). Mechanistically, SARS-CoV-2 infection caused pericyte damage, tight junction loss, endothelial activation and vascular inflammation, which together drive microvascular injury and BBB impairment. In addition, the blood-cerebrospinal fluid barrier at the choroid plexus was also impaired after infection. Therefore, cerebrovascular and choroid plexus dysfunctions are important aspects of COVID-19 and may contribute to neurological complications both acutely and in long COVID.

Presence of SARS-CoV-2 RNA in COVID-19 survivors with post-COVID symptoms 2 years after hospitalization: The VIPER study.

The SARS-CoV-2 VIrus PERsistence (VIPER) study investigated the presence of long-lasting SARS-CoV-2 RNA in plasma, stool, urine, and nasopharyngeal samples in COVID-19 survivors. The presence of SARS-CoV-2 RNA reverse transcription polymerase chain reactions (RT-PCR) were analyzed within plasma, stool, urine, and nasopharyngeal swab samples in COVID-19 survivors with post-COVID symptoms and a comparison group of COVID-19 survivors without post-COVID symptoms matched by age, sex, body mass index and vaccination status. Participants self-reported the presence of any post-COVID symptom (defined as a symptom that started no later than 3 months after the initial infection). Fifty-seven (57.9% women, age: 51.1, standard deviation [SD]: 10.4 years) previously hospitalized COVID-19 survivors with post-COVID symptoms and 55 (56.4% women, age: 50.0, SD: 12.8 years) matched individuals who had a past SARS-CoV-2 infection without post-COVID symptoms were evaluated 27 (SD 7.5) and 26 (SD 8.7) months after hospital discharge, respectively. The presence of SARS-CoV-2 RNA was identified in three nasopharyngeal samples of patients with post-COVID symptoms (5.2%) but not in plasma, stool, or urine samples. Thus, SARS-CoV-2 RNA was not identified in any sample of survivors without post-COVID symptoms. The most prevalent post-COVID symptoms consisted of fatigue (93%), dyspnea, and pain (both, 87.7%). This study did not find SARS-CoV-2 RNA in plasma, stool, or urine samples, 2 years after the infection. A prevalence of 5.2% of SARS-CoV-2 RNA in nasopharyngeal samples, suggesting a potential active or recent reinfection, was found in patients with post-COVID symptoms. These results do not support the association between SARS-CoV-2 RNA in plasma, stool, urine, or nasopharyngeal swab samples and post-COVID symptomatology in the recruited population.

In silico analysis of non-structural protein 12 sequences from SARS-COV-2 found in Manaus, Amazonas, Brazil, reveals mutations linked to higher transmissibility.

The disease coronavirus COVID-19 has been the cause of millions of deaths worldwide. Among the proteins of SARS-CoV-2, non-structural protein 12 (NSP12) plays a key role during COVID infection and is part of the RNA-dependent RNA polymerase complex. The monitoring of NSP12 polymorphisms is extremely important for the design of new antiviral drugs and monitoring of viral evolution. This study analyzed the NSP12 mutations detected in circulating SARS-CoV-2 during the years 2020 to 2022 in the population of the city of Manaus, Amazonas, Brazil. The most frequent mutations found were P323L and G671S. Reports in the literature indicate that these mutations are related to transmissibility efficiency, which may have contributed to the extremely high numbers of cases in this location. In addition, two mutations described here (E796D and R914K) are close and have RMSD that is similar to the mutations M794V and N911K, which have been described in the literature as influential on the performance of the NSP12 enzyme. These data demonstrate the need to monitor the emergence of new mutations in NSP12 in order to better understand their consequences for the treatments currently used and in the design of new drugs.

Strategic Retesting to Reduce False Positive SARS-CoV-2 PCR Test Results.

BACKGROUND: Nucleic acid amplification testing is the gold standard for SARS-CoV-2 diagnostics, although it may produce a certain number of false positive results. There has not been much published about the characteristics of false positive results. In this study, based on retesting, specimens that initially tested positive for SARS-CoV-2 were classified as true or false positive groups to characterize the distribution of cycle threshold (CT) values for N1 and N2 targets and number of targets detected for each group. METHODS: Specimens that were positive for N-gene on retesting and accompanied with S-gene were identified as true positives (true positive based on retesting, rTP), while specimens that retested negative were classified as false positives (false positive based on retesting, rFP). RESULTS: Of the specimens retested, 85/127 (66.9%) were rFP, 16/47 (34.0%) specimens with both N1 and N2 targets initially detected were rFP, and the CT values for each target was higher in rFP than in rTP. ROC curve analysis showed that optimal cutoff values of CT to differentiate between rTP and rFP were 34.8 for N1 and 33.0 for N2. With the optimal cutoff values of CT for each target, out of the 24 specimens that were positive for both N1 and N2 targets and classified as rTP, 23 (95.8%) were correctly identified as true positives. rFP specimens had a single N1 target in 52/61 (85.2%) and a single N2 target in 17/19 (89.5%). Notably, no true positive results were obtained from any specimens with only N2 target detected. CONCLUSIONS: These results suggest that retesting should be performed for positive results with a CT value greater than optimal cutoff value for each target or with a single N1 target amplified, considering the possibility of a false positive. This may provide guidance on indications to perform retesting to minimize the number of false positives.

In-vitro and in-vivo assessment of nirmatrelvir penetration into CSF, central nervous system cells, tissues, and peripheral blood mononuclear cells.

Three years after SARS-CoV-2 emerged as a global infectious threat, the virus has become endemic. The neurological complications such as depression, anxiety, and other CNS complications after COVID-19 disease are increasing. The brain, and CSF have been shown as viral reservoirs for SARS-CoV-2, yielding a potential hypothesis for CNS effects. Thus, we investigated the CNS pharmacology of orally dosed nirmatrelvir/ritonavir (NMR/RTV). Using both an in vitro and an in vivo rodent model, we investigated CNS penetration and potential pharmacodynamic activity of NMR. Through pharmacokinetic modeling, we estimated the median CSF penetration of NMR to be low at 18.11% of plasma with very low accumulation in rodent brain tissue. Based on the multiples of the 90% maximal effective concentration (EC90) for SARS-CoV-2, NMR concentrations in the CSF and brain do not achieve an exposure level similar to that of plasma. A median of only 16% of all the predicted CSF concentrations in rats were > 3xEC90 (unadjusted for protein binding). This may have implications for viral persistence and neurologic post-acute sequelae of COVID-19 if increased NMR penetration in the CNS leads to decreased CNS viral loads and decreased CNS inflammation.

LINC01002 functions as a ceRNA to regulate FRMD8 by sponging miR-4324 for the development of COVID-19.

BACKGROUND: Syndrome coronavirus-2 (SARS-CoV-2) has developed various strategies to evade the antiviral impact of type I IFN. Non-structural proteins and auxiliary proteins have been extensively researched on their role in immune escape. Nevertheless, the detailed mechanisms of structural protein-induced immune evasion have not been well elucidated. METHODS: Human alveolar basal epithelial carcinoma cell line (A549) was stimulated with polyinosinic-polycytidylic acid (PIC) and independently transfected with four structural proteins expression plasmids, including nucleocapsid (N), spike (S), membrane (M) and envelope (E) proteins. By RT-qPCR and ELISA, the structural protein with the most pronounced inhibitory effects on IFN-ß induction was screened. RNA-sequencing (RNA-Seq) and two differential analysis strategies were used to obtain differentially expressed genes associated with N protein inhibition of IFN-ß induction. Based on DIANA-LncBase and StarBase databases, the interactive competitive endogenous RNA (ceRNA) network for N protein-associated genes was constructed. By combining single-cell sequencing data (GSE158055), lncRNA-miRNA-mRNA axis was further determined. Finally, RT-qPCR was utilized to illustrate the regulatory functions among components of the ceRNA axis. RESULTS: SARS-CoV-2 N protein inhibited IFN-ß induction in human alveolar epithelial cells most significantly compared with other structural proteins. RNA-Seq data analysis revealed genes related to N protein inhibiting IFNs induction. The obtained 858 differentially expressed genes formed the reliable ceRNA network. The function of LINC01002-miR-4324-FRMD8 axis in the IFN-dominated immune evasion was further demonstrated through integrating single-cell sequencing data. Moreover, we validated that N protein could reverse the effect of PIC on LINC01002, FRMD8 and miR-4324 expression, and subsequently on IFN-ß expression level. And LINC01002 could regulate the production of FRMD8 by inhibiting miR-4324. CONCLUSION: SARS-CoV-2 N protein suppressed the induction of IFN-ß by regulating LINC01002 which was as a ceRNA, sponging miR-4324 and participating in the regulation of FRMD8 mRNA. Our discovery provides new insights into early intervention therapy and drug development on SARS-CoV-2 infection.

SARS-CoV-2 aberrantly elevates mitochondrial bioenergetics to induce robust virus propagation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a 'highly transmissible respiratory pathogen, leading to severe multi-organ damage. However, knowledge regarding SARS-CoV-2-induced cellular alterations is limited. In this study, we report that SARS-CoV-2 aberrantly elevates mitochondrial bioenergetics and activates the EGFR-mediated cell survival signal cascade during the early stage of viral infection. SARS-CoV-2 causes an increase in mitochondrial transmembrane potential via the SARS-CoV-2 RNA-nucleocapsid cluster, thereby abnormally promoting mitochondrial elongation and the OXPHOS process, followed by enhancing ATP production. Furthermore, SARS-CoV-2 activates the EGFR signal cascade and subsequently induces mitochondrial EGFR trafficking, contributing to abnormal OXPHOS process and viral propagation. Approved EGFR inhibitors remarkably reduce SARS-CoV-2 propagation, among which vandetanib exhibits the highest antiviral efficacy. Treatment of SARS-CoV-2-infected cells with vandetanib decreases SARS-CoV-2-induced EGFR trafficking to the mitochondria and restores SARS-CoV-2-induced aberrant elevation in OXPHOS process and ATP generation, thereby resulting in the reduction of SARS-CoV-2 propagation. Furthermore, oral administration of vandetanib to SARS-CoV-2-infected hACE2 transgenic mice reduces SARS-CoV-2 propagation in lung tissue and mitigates SARS-CoV-2-induced lung inflammation. Vandetanib also exhibits potent antiviral activity against various SARS-CoV-2 variants of concern, including alpha, beta, delta and omicron, in in vitro cell culture experiments. Taken together, our findings provide novel insight into SARS-CoV-2-induced alterations in mitochondrial dynamics and EGFR trafficking during the early stage of viral infection and their roles in robust SARS-CoV-2 propagation, suggesting that EGFR is an attractive host target for combating COVID-19.

Drug repurposing: identification of SARS-CoV-2 potential inhibitors by virtual screening and pharmacokinetics strategies.

INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic caused global health, economic, and population loss. Variants of the coronavirus contributed to the severity of the disease and persistent rise in infections. This study aimed to identify potential drug candidates from fifteen approved antiviral drugs against SARS-CoV-2 (6LU7), SARS-CoV (5B6O), and SARS-CoV-2 spike protein (6M0J) using virtual screening and pharmacokinetics to gain insights into COVID-19 therapeutics. METHODOLOGY: We employed drug repurposing approach to analyze binding performance of fifteen clinically approved antiviral drugs against the main protease of SARS-CoV-2 (6LU7), SARS-CoV (5B6O), and SARS-CoV-2 spike proteins bound to ACE-2 receptor (6M0J), to provide an insight into the therapeutics of COVID-19. AutoDock Vina was used for docking studies. The binding affinities were calculated, and 2-3D structures of protein-ligand interactions were drawn. RESULTS: Rutin, hesperidin, and nelfinavir are clinically approved antiviral drugs with high binding affinity to proteins 6LU7, 5B6O, and 6M0J. These ligands have excellent pharmacokinetics, ensuring efficient absorption, metabolism, excretion, and digestibility. Hesperidin showed the most potent interaction with spike protein 6M0J, forming four H-bonds. Nelfinavir had a high human intestinal absorption (HIA) score of 0.93, indicating maximum absorption in the body and promising interactions with 6LU7. CONCLUSIONS: Our results indicated that rutin, hesperidin, and nelfinavir had the highest binding results against the proposed drug targets. The computational approach effectively identified SARS-CoV-2 inhibitors. COVID-19 is still a recurrent threat globally and predictive analysis using natural compounds might serve as a starting point for new drug development against SARS-CoV-2 and related viruses.

SARS-CoV-2 clade dynamics and their associations with hospitalisations during the first two years of the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic was characterised by rapid waves of disease, carried by the emergence of new and more infectious SARS-CoV-2 virus variants. How the pandemic unfolded in various locations during its first two years has yet to be sufficiently covered. To this end, here we are looking at the circulating SARS-CoV-2 variants, their diversity, and hospitalisation rates in Estonia in the period from March 2000 to March 2022. METHODS: We sequenced a total of 27,550 SARS-CoV-2 samples in Estonia between March 2020 and March 2022. High-quality sequences were genotyped and assigned to Nextstrain clades and Pango lineages. We used regression analysis to determine the dynamics of lineage diversity and the probability of clade-specific hospitalisation stratified by age and sex. RESULTS: We successfully sequenced a total of 25,375 SARS-CoV-2 genomes (or 92%), identifying 19 Nextstrain clades and 199 Pango lineages. In 2020 the most prevalent clades were 20B and 20A. The various subsequent waves of infection were driven by 20I (Alpha), 21J (Delta) and Omicron clades 21K and 21L. Lineage diversity via the Shannon index was at its highest during the Delta wave. About 3% of sequenced SARS-CoV-2 samples came from hospitalised individuals. Hospitalisation increased markedly with age in the over-forties, and was negligible in the under-forties. Vaccination decreased the odds of hospitalisation in over-forties. The effect of vaccination on hospitalisation rates was strongly dependent upon age but was clade-independent. People who were infected with Omicron clades had a lower hospitalisation likelihood in age groups of forty and over than was the case with pre-Omicron clades regardless of vaccination status. CONCLUSIONS: COVID-19 disease waves in Estonia were driven by the Alpha, Delta, and Omicron clades. Omicron clades were associated with a substantially lower hospitalisation probability than pre-Omicron clades. The protective effect of vaccination in reducing hospitalisation likelihood was independent of the involved clade.

Predicting drug-Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which represents a new life-threatening disaster. Regarding viral infection, many therapeutics have been investigated to alleviate the epidemiology such as vaccines and receptor decoys. However, the continuous mutating coronavirus, especially the variants of Delta and Omicron, are tended to invalidate the therapeutic biological product. Thus, it is necessary to develop molecular entities as broad-spectrum antiviral drugs. Coronavirus replication is controlled by the viral 3-chymotrypsin-like cysteine protease (3CLpro) enzyme, which is required for the virus's life cycle. In the cases of severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV), 3CLpro has been shown to be a promising therapeutic development target. Here we proposed an attention-based deep learning framework for molecular graphs and sequences, training from the BindingDB 3CLpro dataset (114,555 compounds). After construction of such model, we conducted large-scale screening the in vivo/vitro dataset (276,003 compounds) from Zinc Database and visualize the candidate compounds with attention score. geometric-based affinity prediction was employed for validation. Finally, we established a 3CLpro-specific deep learning framework, namely GraphDPI-3CL (AUROC: 0.958) achieved superior performance beyond the existing state of the art model and discovered 10 molecules with a high binding affinity of 3CLpro and superior binding mode.

An Overview of SARS-CoV-2 Potential Targets, Inhibitors, and Computational Insights to Enrich the Promising Treatment Strategies.

The rapid spread of the SARS-CoV-2 virus has emphasized the urgent need for effective therapies to combat COVID-19. Investigating the potential targets, inhibitors, and in silico approaches pertinent to COVID-19 are of utmost need to develop novel therapeutic agents and reprofiling of existing FDA-approved drugs. This article reviews the viral enzymes and their counter receptors involved in the entry of SARS-CoV-2 into host cells, replication of genomic RNA, and controlling the host cell physiology. In addition, the study provides an overview of the computational techniques such as docking simulations, molecular dynamics, QSAR modeling, and homology modeling that have been used to find the FDA-approved drugs and other inhibitors against SARS-CoV-2. Furthermore, a comprehensive overview of virus-based and host-based druggable targets from a structural point of view, together with the reported therapeutic compounds against SARS-CoV-2 have also been presented. The current study offers future perspectives for research in the field of network pharmacology investigating the large unexplored molecular libraries. Overall, the present in-depth review aims to expedite the process of identifying and repurposing drugs for researchers involved in the field of COVID-19 drug discovery.

SARS-CoV-2 strains bearing Omicron BA.1 spike replicate in C57BL/6 mice.

Introduction: SARS-CoV-2, the cause of the COVID pandemic, is an RNA virus with a high propensity to mutate. Successive virus variants, including variants of concern (VOC), have emerged with increased transmission or immune escape. The original pandemic virus and early variants replicated poorly, if at all, in mice at least partly due to a mismatch between the receptor binding domain on the viral spike protein and the murine angiotensin converting enzyme 2 (ACE2). Omicron VOC emerged in late 2021 harboring > 50 new mutations, 35 of them in the spike protein. This variant resulted in a very large wave of infections, even in the face of prior immunity, albeit being inherently less severe than earlier variants. Reflecting the lower severity reported in humans, Omicron displayed attenuated infection in hamsters and also in the K18-hACE2 mouse model. K18-hACE2 mice express both the human ACE2 as well as the endogenous mouse ACE2. Methods: Here we infected hACE2 knock-in mice that express only human ACE2 and no murine ACE2, or C57BL/6 wildtype mice with SARS-CoV-2 D614G (first-wave isolate), Delta or Omicron BA.1 variants and assessed infectivity and downstream innate immune responses. Results: While replication of SARS-CoV-2 Omicron was lower in the lungs of hACE2 knock-in mice compared with SARS-CoV-2 D614G and VOC Delta, it replicated more efficiently than the earlier variants in C57BL/6 wildtype mice. This opens the opportunity to test the effect of host genetics on SARS-CoV-2 infections in wildtype mice. As a proof of principle, we tested Omicron infection in mice lacking expression of the interferon-alpha receptor-1 (IFNAR1). In these mice we found that loss of type I IFN receptor signaling resulted in higher viral loads in the lungs were detected. Finally, using a chimeric virus of first wave SARS-CoV-2 harboring the Omicron spike protein, we show that Omicron spike increase infection of C57BL/6 wildtype mice, but non-spike genes of Omicron confer attenuation of viral replication. Discussion: Since this chimeric virus efficiently infected C57BL/6 wildtype mice, and replicated in their lungs, our findings illustrate a pathway for genetic mapping of virushost interactions during SARS-CoV-2 infection.

Biolayer-Interferometry-Guided Functionalization of Screen-Printed Graphene for Label-Free Electrochemical Virus Detection.

Additive manufacturing holds promise for rapid prototyping and low-cost production of biosensors for diverse pathogens. Among additive manufacturing methods, screen printing is particularly desirable for high-throughput production of sensing platforms. However, this technique needs to be combined with carefully formulated inks, rapid postprocessing, and selective functionalization to meet all requirements for high-performance biosensing applications. Here, we present screen-printed graphene electrodes that are processed with thermal annealing to achieve high surface area and electrical conductivity for sensitive biodetection via electrochemical impedance spectroscopy. As a proof-of-concept, this biosensing platform is utilized for electrochemical detection of SARS-CoV-2. To ensure reliable specificity in the presence of multiple variants, biolayer interferometry (BLI) is used as a label-free and dynamic screening method to identify optimal antibodies for concurrent affinity to the Spike S1 proteins of Delta, Omicron, and Wild Type SARS-CoV-2 variants while maintaining low affinity to competing pathogens such as Influenza H1N1. The BLI-identified antibodies are robustly bound to the graphene electrode surface via oxygen moieties that are introduced during the thermal annealing process. The resulting electrochemical immunosensors achieve superior metrics including rapid detection (55 s readout following 15 min of incubation), low limits of detection (approaching 500 ag/mL for the Omicron variant), and high selectivity toward multiple variants. Importantly, the sensors perform well on clinical saliva samples detecting as few as 103 copies/mL of SARS-CoV-2 Omicron, following CDC protocols. The combination of the screen-printed graphene sensing platform and effective antibody selection using BLI can be generalized to a wide range of point-of-care immunosensors.

Long COVID: lights and shadows on the clinical characterization of this emerging pathology.

More than 800 million individuals have contracted SARSCOV2 infection worldwide. It was estimated that almost 10-20% of these might suffer from Long COVID. It is a multisystemic syndrome, which negatively affects the quality of life with a significant burden of health loss compared to COVID negative individuals. Moreover, the risk of sequelae still remains high at 2 years in both nonhospitalized and hospitalized individuals. This review summarizes studies regarding long COVID and clarifies the definitions, the risk factors and the management of this syndrome. Finally, it delves into the most frequent long-term outcomes, especially postural orthostatic tachycardia syndrome" (POTS), myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), brain fog, and their therapeutical possibilities.

Sequestration of membrane cholesterol by cholesterol-binding proteins inhibits SARS-CoV-2 entry into Vero E6 cells.

Membrane lipids and proteins form dynamic domains crucial for physiological and pathophysiological processes, including viral infection. Many plasma membrane proteins, residing within membrane domains enriched with cholesterol (CHOL) and sphingomyelin (SM), serve as receptors for attachment and entry of viruses into the host cell. Among these, human coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), use proteins associated with membrane domains for initial binding and internalization. We hypothesized that the interaction of lipid-binding proteins with CHOL in plasma membrane could sequestrate lipids and thus affect the efficiency of virus entry into host cells, preventing the initial steps of viral infection. We have prepared CHOL-binding proteins with high affinities for lipids in the plasma membrane of mammalian cells. Binding of the perfringolysin O domain four (D4) and its variant D4E458L to membrane CHOL impaired the internalization of the receptor-binding domain of the SARS-CoV-2 spike protein and the pseudovirus complemented with the SARS-CoV-2 spike protein. SARS-CoV-2 replication in Vero E6 cells was also decreased. Overall, our results demonstrate that the integrity of CHOL-rich membrane domains and the accessibility of CHOL in the membrane play an essential role in SARS-CoV-2 cell entry.

Unique Synthetic Strategy for Probing in Situ Lysosomal NO for Screening Neuroinflammatory Phenotypes against SARS-CoV-2 RNA in Phagocytotic Microglia.

In the pathogenesis of microglia, brain immune cells promote nitrergic stress by overproducing nitric oxide (NO), leading to neuroinflammation. Furthermore, NO has been linked to COVID-19 progression, which has caused significant morbidity and mortality. SARS-CoV-2 infection activates inflammation by releasing excess NO and causing cell death in human microglial clone 3 (HMC3). In addition, NO regulates lysosomal functions and complex machinery to neutralize pathogens through phagocytosis. Therefore, developing lysosome-specific NO probes to monitor phagocytosis in microglia during the COVID-19 infection would be a significant study. Herein, a unique synthetic strategy was adopted to develop a NO selective fluorescent probe, PDM-NO, which can discriminate activated microglia from their resting state. The nonfluorescent PDM-NO exhibits a turn-on response toward NO only at lysosomal pH (4.5-5.5). Quantum chemical calculations (DFT/TD-DFT/PCM) and photophysical study revealed that the photoinduced electron transfer (PET) process is pivotal in tuning optical properties. PDM-NO demonstrated good biocompatibility and lysosomal specificity in activated HMC3 cells. Moreover, it can effectively map the dynamics of lysosomal NO against SARS-CoV-2 RNA-induced neuroinflammation in HMC3. Thus, PDM-NO is a potential fluorescent marker for detecting RNA virus infection and monitoring phagocytosis in HMC3.

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.