Spatiotemporal evolution of NO2 diffusion in Beijing in response to COVID-19 lockdown using complex network.

The COVID-19 pandemic and the corresponding lockdown measures have been confirmed to reduce the air pollution in major megacities worldwide. Especially at some monitoring hotspots, NO2 has been verified to show a significant decrease. However, the diffusion pattern of these hotspots in responding to COVID-19 is not clearly understood at present stage. Hence, we selected Beijing, a typical megacity with the strictest lockdown measures during COVID-19 period, as the studied city and attempted to discover the NO2 diffusion process through complex network method. The improved metrics derived from the topological structure of the network were adopted to describe the performance of diffusion. Primarily, we found evidences that COVID-19 had significant effects on the spatial diffusion distribution due to combined effect of changed human activities and meteorological conditions. Besides, to further quantify the impacts of disturbance caused by different lockdown measures, we discussed the evolutionary diffusion patterns from lockdown period to recovery period. The results displayed that the difference between normal operation and pandemic operation firstly increased at the cutoff of lockdown measures but then declined after the implement of recovery measures. The source areas had greater vulnerability and lower resilience than receptors areas. Furthermore, based on the conclusion that the diffusion pattern changed during different periods, we explored the key stations on the path of diffusion process to further gain information. These findings could provide references for comprehending spatiotemporal pattern on city scale, which might be help for high-resolution air pollution mapping and prediction.

Characterizing the interruption-recovery patterns of urban air pollution under the COVID-19 lockdown in China.

The COVID-19 pandemic provides an opportunity to study the effects of urban lockdown policies on the variation in pollutant concentrations and to characterize the recovery patterns of urban air pollution under the interruption of COVID-19 lockdown policies. In this paper, interruption-recovery models and regression discontinuity design were developed to characterize air pollution interruption-recovery patterns and analyze environmental impacts of the COVID-19 lockdown, using air pollution data from four Chinese metropolises (i.e., Shanghai, Wuhan, Tianjin, and Guangzhou). The results revealed the air pollutant interruption-recovery curve represented by the three lockdown response periods (Level I, Level II and Level III) during COVID-19. The curve decreased during Level I (A 25.3%-48.8% drop in the concentration of NO2 has been observed in the four metropolises compared with the same period in 2018-2019.), then recovered around reopening, but decreased again during Level III. Moreover, the interruption-recovery curve of the year-on-year air pollution difference suggests a process of first decreasing during Level I and gradually recovering to a new equilibrium during Level III (e.g., the unit cumulative difference of NO2 mass concentrations in Shanghai was 21.7, 22.5, 11.3 (µg/m3) during Level I, II, and III and other metropolises shared similar results). Our findings reveal general trends in the air quality externality of different lockdown policies, hence could provide valuable insights into air pollutant interruption-recovery patterns and clear scientific guides for policymakers to estimate the effect of different lockdown policies on urban air quality.

Three epitope-distinct human antibodies from RenMab mice neutralize SARS-CoV-2 and cooperatively minimize the escape of mutants.

Coronavirus disease 2019 (COVID-19), a pandemic disease caused by the newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused more than 3.8 million deaths to date. Neutralizing antibodies are effective therapeutic measures. However, many naturally occurring mutations at the receptor-binding domain (RBD) have emerged, and some of them can evade existing neutralizing antibodies. Here, we utilized RenMab, a novel mouse carrying the entire human antibody variable region, for neutralizing antibody discovery. We obtained several potent RBD-blocking antibodies and categorized them into four distinct groups by epitope mapping. We determined the involved residues of the epitope of three representative antibodies by cryo-electron microscopy (Cryo-EM) studies. Moreover, we performed neutralizing experiments with 50 variant strains with single or combined mutations and found that the mixing of three epitope-distinct antibodies almost eliminated the mutant escape. Our study provides a sound basis for the rational design of fully human antibody cocktails against SARS-CoV-2 and pre-emergent coronaviral threats.

Molecular basis of cross-species ACE2 interactions with SARS-CoV-2-like viruses of pangolin origin.

Pangolins have been suggested as potential reservoir of zoonotic viruses, including SARS-CoV-2 causing the global COVID-19 outbreak. Here, we study the binding of two SARS-CoV-2-like viruses isolated from pangolins, GX/P2V/2017 and GD/1/2019, to human angiotensin-converting enzyme 2 (hACE2), the receptor of SARS-CoV-2. We find that the spike protein receptor-binding domain (RBD) of pangolin CoVs binds to hACE2 as efficiently as the SARS-CoV-2 RBD in vitro. Furthermore, incorporation of pangolin CoV RBDs allows entry of pseudotyped VSV particles into hACE2-expressing cells. A screen for binding of pangolin CoV RBDs to ACE2 orthologs from various species suggests a broader host range than that of SARS-CoV-2. Additionally, cryo-EM structures of GX/P2V/2017 and GD/1/2019 RBDs in complex with hACE2 show their molecular binding in modes similar to SARS-CoV-2 RBD. Introducing the Q498H substitution found in pangolin CoVs into the SARS-CoV-2 RBD expands its binding capacity to ACE2 homologs of mouse, rat, and European hedgehog. These findings suggest that these two pangolin CoVs may infect humans, highlighting the necessity of further surveillance of pangolin CoVs.

Structural basis for bivalent binding and inhibition of SARS-CoV-2 infection by human potent neutralizing antibodies.

Neutralizing monoclonal antibodies (nAbs) to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represent promising candidates for clinical intervention against coronavirus disease 2019 (COVID-19). We isolated a large number of nAbs from SARS-CoV-2-infected individuals capable of disrupting proper interaction between the receptor binding domain (RBD) of the viral spike (S) protein and the receptor angiotensin converting enzyme 2 (ACE2). However, the structural basis for their potent neutralizing activity remains unclear. Here, we report cryo-EM structures of the ten most potent nAbs in their native full-length IgG-form or in both IgG-form and Fab-form bound to the trimeric S protein of SARS-CoV-2. The bivalent binding of the full-length IgG is found to associate with more RBDs in the "up" conformation than the monovalent binding of Fab, perhaps contributing to the enhanced neutralizing activity of IgG and triggering more shedding of the S1 subunit from the S protein. Comparison of a large number of nAbs identified common and unique structural features associated with their potent neutralizing activities. This work provides a structural basis for further understanding the mechanism of nAbs, especially through revealing the bivalent binding and its correlation with more potent neutralization and the shedding of S1 subunit.

Impact of the COVID-19 lockdown on roadside traffic-related air pollution in Shanghai, China.

The outbreak of COVID-19 has significantly inhibited global economic growth and impacted the environment. Some evidence suggests that lockdown strategies have significantly reduced traffic-related air pollution (TRAP) in regions across the world. However, the impact of COVID-19 on TRAP on roadside is still not clearly understood. In this study, we assessed the influence of the COVID-19 lockdown on the levels of traffic-related air pollutants in Shanghai. The pollution data from two types of monitoring stations-roadside stations and non-roadside stations were compared and evaluated. The results show that NO2, PM2.5, PM10, and SO2 had reduced by ~30-40% at each station during the COVID-19 pandemic in contrast to 2018-2019. CO showed a moderate decline of 28.8% at roadside stations and 16.4% at non-roadside stations. In contrast, O3 concentrations increased by 30.2% at roadside stations and 5.7% at non-roadside stations. This result could be resulted from the declined NOx emissions from vehicles, which lowered O3 titration. Full lockdown measures resulted in the highest reduction of primary pollutants by 34-48% in roadside stations and 18-50% in non-roadside stations. The increase in O3 levels was also the most significant during full lockdown by 64% in roadside stations and 33% in non-roadside stations due to the largest decrease in NO2 precursors, which promote O3 formation. Additionally, Spearman's rank correlation coefficients between NO2 and other pollutants significantly decreased, while the values between NO2 and O3 increased at roadside stations.

Cross-species recognition of SARS-CoV-2 to bat ACE2.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as a major threat to global health. Although varied SARS-CoV-2-related coronaviruses have been isolated from bats and SARS-CoV-2 may infect bat, the structural basis for SARS-CoV-2 to utilize the human receptor counterpart bat angiotensin-converting enzyme 2 (bACE2) for virus infection remains less understood. Here, we report that the SARS-CoV-2 spike protein receptor binding domain (RBD) could bind to bACE2 from Rhinolophus macrotis (bACE2-Rm) with substantially lower affinity compared with that to the human ACE2 (hACE2), and its infectivity to host cells expressing bACE2-Rm was confirmed with pseudotyped SARS-CoV-2 virus and SARS-CoV-2 wild virus. The structure of the SARS-CoV-2 RBD with the bACE2-Rm complex was determined, revealing a binding mode similar to that of hACE2. The analysis of binding details between SARS-CoV-2 RBD and bACE2-Rm revealed that the interacting network involving Y41 and E42 of bACE2-Rm showed substantial differences with that to hACE2. Bats have extensive species diversity and the residues for RBD binding in bACE2 receptor varied substantially among different bat species. Notably, the Y41H mutant, which exists in many bats, attenuates the binding capacity of bACE2-Rm, indicating the central roles of Y41 in the interaction network. These findings would benefit our understanding of the potential infection of SARS-CoV-2 in varied species of bats.

Broad host range of SARS-CoV-2 and the molecular basis for SARS-CoV-2 binding to cat ACE2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the recent pandemic COVID-19, is reported to have originated from bats, with its intermediate host unknown to date. Here, we screened 26 animal counterparts of the human ACE2 (hACE2), the receptor for SARS-CoV-2 and SARS-CoV, and found that the ACE2s from various species, including pets, domestic animals and multiple wild animals, could bind to SARS-CoV-2 receptor binding domain (RBD) and facilitate the transduction of SARS-CoV-2 pseudovirus. Comparing to SARS-CoV-2, SARS-CoV seems to have a slightly wider range in choosing its receptor. We further resolved the cryo-electron microscopy (cryo-EM) structure of the cat ACE2 (cACE2) in complex with the SARS-CoV-2 RBD at a resolution of 3 Å, revealing similar binding mode as hACE2 to the SARS-CoV-2 RBD. These results shed light on pursuing the intermediate host of SARS-CoV-2 and highlight the necessity of monitoring susceptible hosts to prevent further outbreaks.