Switch-on Fluorescence Analysis of Protease Activity with the Assistance of a Nickel Ion-Nitrilotriacetic Acid-Conjugated Magnetic Nanoparticle.

Heterogeneous protease biosensors show high sensitivity and selectivity but usually require the immobilization of peptide substrates on a solid interface. Such methods exhibit the disadvantages of complex immobilization steps and low enzymatic efficiency induced by steric hindrance. In this work, we proposed an immobilization-free strategy for protease detection with high simplicity, sensitivity and selectivity. Specifically, a single-labeled peptide with oligohistidine-tag (His-tag) was designed as the protease substrate, which can be captured by a nickel ion-nitrilotriacetic acid (Ni-NTA)-conjugated magnetic nanoparticle (MNP) through the coordination interaction between His-tag and Ni-NTA. When the peptide was digested by protease in a homogeneous solution, the signal-labeled segment was released from the substrate. The unreacted peptide substrates could be removed by Ni-NTA-MNP, and the released segments remained in solution to emit strong fluorescence. The method was used to determine protease of caspase-3 with a low detection limit (4 pg/mL). By changing the peptide sequence and signal reporters, the proposal could be used to develop novel homogeneous biosensors for the detection of other proteases.

Isolation of a Novel Bat Rhabdovirus with Evidence of Human Exposure in China.

Bats are well-recognized reservoirs of zoonotic viruses. Several spillover events from bats to humans have been reported, causing severe epidemic or endemic diseases including severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), SARS-CoV, Middle East respiratory syndrome-CoV (MERS-CoV), henipaviruses, and filoviruses. In this study, a novel rhabdovirus species, provisionally named Rhinolophus rhabdovirus DPuer (DPRV), was identified from the horseshoe bat (Rhinolophus affinis) in Yunnan province, China, using next-generation sequencing. DPRV shedding in the spleen, liver, lung, and intestinal contents of wild bats with high viral loads was detected by real-time quantitative PCR, indicating that DPRV has tropism for multiple host tissues. Furthermore, DPRV can replicate in vitro in multiple mammalian cell lines, including BHK-21, A549, and MA104 cells, with the highest efficiency in hamster kidney cell line BHK-21, suggesting infectivity of DPRV in these cell line-derived hosts. Ultrastructure analysis revealed a characteristic bullet-shaped morphology and tightly clustered distribution of DPRV particles in the intracellular space. DPRV replicated efficiently in suckling mouse brains and caused death of suckling mice; death rates increased with passaging of DPRV in suckling mice. Moreover, 421 serum samples were collected from individuals who lived near the bat collection site and had fever symptoms within 1 year. DPRV-specific antibodies were detected in 20 (4.75%) human serum samples by indirect immunofluorescence assay. Furthermore, 10 (2.38%) serum samples were DPRV positive according to plaque reduction neutralization assay, which revealed potential transmission of DPRV from bats to humans and highlighted the potential public health risk. Potential vector association with DPRV was not found with negative viral RNA in bloodsucking arthropods. IMPORTANCE We identified a novel rhabdovirus from the horseshoe bat (Rhinolophus thomasi) in China with probable infectivity in humans. DPRV was isolated in vitro from several mammalian cell lines, indicating wide host tropism, excluding bats, of DPRV. DPRV replicated in the brains of suckling mice, and the death rate of suckling mice increased with passaging of DPRV in vivo. Serological tests indicated the possible infectivity of DPRV in humans and the potential transmission to humans. The present findings provide preliminary evidence for the potential risk of DPRV to public health. Additional studies with active surveillance are needed to address interspecies transmission and determine the pathogenicity of DPRV in humans.

Development of an Early Warning Model for Predicting the Death Risk of Coronavirus Disease 2019 Based on Data Immediately Available on Admission.

Introduction: COVID-19 has overloaded worldwide medical facilities, leaving some potentially high-risk patients trapped in outpatient clinics without sufficient treatment. However, there is still a lack of a simple and effective tool to identify these patients early. Methods: A retrospective cohort study was conducted to develop an early warning model for predicting the death risk of COVID-19. Seventy-five percent of the cases were used to construct the prediction model, and the remaining 25% were used to verify the prediction model based on data immediately available on admission. Results: From March 1, 2020, to April 16, 2020, a total of 4,711 COVID-19 patients were included in our study. The average age was 63.37 ± 16.70 years, of which 1,148 (24.37%) died. Finally, age, SpO2, body temperature (T), and mean arterial pressure (MAP) were selected for constructing the model by univariate analysis, multivariate analysis, and a review of the literature. We used five common methods for constructing the model and finally found that the full model had the best specificity and higher accuracy. The area under the ROC curve (AUC), specificity, sensitivity, and accuracy of full model in train cohort were, respectively, 0.798 (0.779, 0.816), 0.804, 0.656, and 0.768, and in the validation cohort were, respectively, 0.783 (0.751, 0.815), 0.800, 0.616, and 0.755. Visualization tools of the prediction model included a nomogram and an online dynamic nomogram (https://wanghai.shinyapps.io/dynnomapp/). Conclusion: We developed a prediction model that might aid in the early identification of COVID-19 patients with a high probability of mortality on admission. However, further research is required to determine whether this tool can be applied for outpatient or home-based COVID-19 patients.

A novel SARS-CoV-2 related coronavirus with complex recombination isolated from bats in Yunnan province, China.

At the end of 2019, A new type of beta-CoV, SARS-CoV-2 emerged and triggered the COVID-19 pandemic, which spread overwhelmingly around the world in less than a year. However, the origin and direct ancestral viruses of SARS-CoV-2 remain unknown. RaTG13, a novel coronavirus found in bats in China's Yunnan Province, is the closest relative virus of the SARS-CoV-2 identified so far. In this study, a new SARS-CoV-2 related virus, provisionally named PrC31, was discovered in Yunnan province by retrospectively analyse bat next generation sequencing (NGS) data of intestinal samples collected in 2018. PrC31 shared 90.7% and 92.0% nucleotide identities to the genomes of SARS-CoV-2 and the bat SARSr-CoV ZC45, respectively. Sequence alignment of PrC31 showed that several genomic regions, especially orf1a and orf8 had the highest homology with those corresponding genomic regions of SARS-CoV-2 than any other related viruses. Phylogenetic analysis indicated that PrC31 shared a common ancestor with SARS-CoV-2 in evolutionary history. The differences between the PrC31 and SARS-CoV-2 genomes were mainly manifested in the spike genes. The amino acid homology between the receptor binding domains of PrC31 and SARS-CoV-2 was only 64.2%. Importantly, recombination analysis revealed that PrC31 underwent multiple complex recombination events (including three recombination breakpoints) involving the SARS-CoV and SARS-CoV-2 sub-lineages, indicating that PrC31 evolved from yet-to-be-identified intermediate recombination strains. Combined with previous studies, it is revealed that the beta-CoVs may possess a more complex recombination mechanism than we thought.

Triglyceride regulate ACE2 level through MTHFD1

Obesity has been followed with interest as a risk factor for COVID-19, with triglycerides as one of four common criteria used to define obesity, which have been used to study the mechanism of obesity. In this study, we showed that angiotensin-converting enzyme-2 (ACE2) is widely expressed in the mouse body, including the kidney, spleen, brain, heart, lung, liver, and testis, and that ACE2 levels increased after a high-fat diet. The ACE2 levels were recorded at 0 days, 3 days, 7 days, and 14 days after a high-fat diet, and they increased at 14 days after high-fat diet initiation. In addition, triglyceride levels were also significantly increased at 14 days after high-fat diet initiation, but body weight was not changed. Furthermore, we examined the ACE2 levels in Calu3 cells (a lung cancer cell line) after triglyceride treatment, and the results indicated that ACE2 levels were increased at 25 μM and reached their peak at 200 μM. Finally, we found that the mRNA level of mthfd1 was significantly increased in the high-fat diet group. Given these findings, we hypothesize that triglycerides can regulate the expression of ACE2 and Mthfd1.

Molecular Insights into Small‐Molecule Drug Discovery for SARS‐CoV‐2

The mainstream approach to antiviral drugs against COVID‐19 is to focus on key stages of the SARS‐CoV‐2 life cycle. The vast majority of candidates under investigation are repurposed from agents of other indications. Understanding protein–inhibitor interactions at the molecular scale will provide crucial insights for drug discovery to stop this pandemic. In this article, we summarize and analyze the most recent structural data on several viral targets in the presence of promising inhibitors for COVID‐19 in the context of the perspective of modes of action (MOA) to unravel insightful mechanistic features with atomistic resolution. The targets include spike glycoprotein and various host proteases mediating the entry of the virus into the cells, viral chymotrypsin‐ and papain‐like proteases, and RNA‐dependent RNA polymerase. The main purpose of this review is to present detailed MOA analysis to inspire fresh ideas for both de novo drug design and optimization of known scaffolds to combat COVID‐19.

Molecular Insights into Small-Molecule Drug Discovery for SARS-CoV-2.

The mainstream approach to antiviral drugs against COVID-19 is to focus on key stages of the SARS-CoV-2 life cycle. The vast majority of candidates under investigation are repurposed from agents of other indications. Understanding protein-inhibitor interactions at the molecular scale will provide crucial insights for drug discovery to stop this pandemic. In this article, we summarize and analyze the most recent structural data on several viral targets in the presence of promising inhibitors for COVID-19 in the context of the perspective of modes of action (MOA) to unravel insightful mechanistic features with atomistic resolution. The targets include spike glycoprotein and various host proteases mediating the entry of the virus into the cells, viral chymotrypsin- and papain-like proteases, and RNA-dependent RNA polymerase. The main purpose of this review is to present detailed MOA analysis to inspire fresh ideas for both de novo drug design and optimization of known scaffolds to combat COVID-19.