Sequence difference of angiotensin-converting enzyme 2 between nonhuman primates affects its binding-affinity with SARS-CoV-2 S receptor binding domain.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused many deaths and contributed to a tremendous public health concern worldwide since 2020. Angiotensin-converting enzyme 2 (ACE2) binds to the SARS-CoV-2 virus as a receptor. The challenge of different nonhuman primate (NHP) species by SARS-CoV-2 virus demonstrated different effects on virus replication and disease pathology. This study characterizes differences between host ACE2 sequences of three NHP species: Macaca mulatta, Macaca fascicularis, and Chlorocebus sabaeus. In addition, the binding affinity between the ACE2 ectodomain and the SARS-CoV-2 S receptor-binding domain (RBD) was analyzed. Variation of ACE2 sequence among NHP species and the binding affinity may account for different susceptibility and responses to SARS-CoV-2 infection.

Interactive Analysis of Epidemic Situations Based on a Spatiotemporal Information Knowledge Graph of COVID-19.

In view of the lack of data association in spatiotemporal information analysis and the lack of spatiotemporal situation analysis in knowledge graphs, this article combines the semantic web of the geographic knowledge graph with the visual analysis model of spatial information and puts forward the comprehensive utilization of the related technologies of the geographic knowledge graph and big data visual analysis. Then, it realizes the situational analysis of COVID-19 (Coronavirus Disease 2019) and the exploration of patient relationships through interactive collaborative analysis. The main contributions of the paper are as follows. (1) Based on the characteristics of the geographic knowledge graph, a patient entity model and an entity relationship type and knowledge representation method are proposed, and a knowledge graph of the spatiotemporal information of COVID-19 is constructed. (2) To analyse the COVID-19 patients' situations and explore their relationships, an analytical framework is designed. The framework, combining the semantic web of the geographic knowledge graph and the visual analysis model of geographic information, allows one to analyse the semantic web by using the node attribute similarity calculation, key stage mining, community prediction and other methods. (3)An efficient epidemic prevention and anti-epidemic method is proposed which is of referential significance. It is based on experiments and the collaborative analysis of the semantic web and spatial information, allowing for real-time situational understanding, the discovery of patients' relationships, the analysis of the spatiotemporal distribution of patients, super spreader mining, key node analysis, and the prevention and control of high-risk groups.

Adaptation of SARS-CoV-2 in BALB/c mice for testing vaccine efficacy.

The ongoing coronavirus disease 2019 (COVID-19) pandemic has prioritized the development of small-animal models for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We adapted a clinical isolate of SARS-CoV-2 by serial passaging in the respiratory tract of aged BALB/c mice. The resulting mouse-adapted strain at passage 6 (called MASCp6) showed increased infectivity in mouse lung and led to interstitial pneumonia and inflammatory responses in both young and aged mice after intranasal inoculation. Deep sequencing revealed a panel of adaptive mutations potentially associated with the increased virulence. In particular, the N501Y mutation is located at the receptor binding domain (RBD) of the spike protein. The protective efficacy of a recombinant RBD vaccine candidate was validated by using this model. Thus, this mouse-adapted strain and associated challenge model should be of value in evaluating vaccines and antivirals against SARS-CoV-2.