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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic resulted in significant societal costs. Hence, an in-depth understanding of SARS-CoV-2 virus mutation and its evolution will help determine the direction of the COVID-19 pandemic. In this study, we identified 296,728 de novo mutations in more than 2,800,000 high-quality SARS-CoV-2 genomes. All possible factors affecting the mutation frequency of SARS-CoV-2 in human hosts were analyzed, including zinc finger antiviral proteins, sequence context, amino acid change, and translation efficiency. As a result, we proposed that when adenine (A) and tyrosine (T) bases are in the context of AM (M stands for adenine or cytosine) or TA motif, A or T base has lower mutation frequency. Furthermore, we hypothesized that translation efficiency can affect the mutation frequency of the third position of the codon by the selection, which explains why SARS-CoV-2 prefers AT3 codons usage. In addition, we found a host-specific asymmetric dinucleotide mutation frequency in the SARS-CoV-2 genome, which provides a new basis for determining the origin of the SARS-CoV-2. Finally, we summarize all possible factors affecting mutation frequency and provide insights into the mutation characteristics and evolutionary trends of SARS-CoV-2.

Gut microbiota composition is suggested to associate with coronavirus disease 2019 (COVID-19) severity, but the impact of gut microbiota on health outcomes is largely unclear. We recruited 81 individuals from Wuhan, China, including 13 asymptomatic infection cases (Group A), 24 COVID-19 convalescents with adverse outcomes (Group C), 31 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) re-positive cases (Group D), and 13 non-COVID-19 healthy controls (Group H). The microbial features of Groups A and D were similar and exhibited higher gut microbial diversity and more abundant short-chain fatty acid (SCFA)-producing species than Group C. Group C was enriched with opportunistic pathogens and virulence factors related to adhesion and toxin production. The abundance of SCFA-producing species was negatively correlated, while Escherichia coli was positively correlated with adverse outcomes. All three groups (A, C, and D) were enriched with the mucus-degrading species Akkermansia muciniphila, but decreased with Bacteroides-encoded carbohydrate-active enzymes. The pathways of vitamin B6 metabolic and folate biosynthesis were decreased, while selenocompound metabolism was increased in the three groups. Specifically, the secondary bile acid (BA) metabolic pathway was enriched in Group A. Antibiotic resistance genes were common among the three groups. Conclusively, the gut microbiota was related to the health outcomes of COVID-19. Dietary supplementations (SCFAs, BA, selenium, folate, vitamin B6) may be beneficial to COVID-19 patients.

We present a method of mapping data from publicly available genomics and publication resources to the Resource Description Framework (RDF) and implement a server to publish linked open data (LOD). As one of the largest and most comprehensive semantic databases about coronaviruses, the resulted gcCov database demonstrates the capability of using data in the LOD framework to promote correlations between genotypes and phenotypes. These correlations will be helpful for future research on fundamental viral mechanisms and drug and vaccine designs. These LOD with 62,168,127 semantic triplets and their visualizations are freely accessible through gcCov at https://nmdc.cn/gccov/.