Context: Since the outbreak of COVID-19 in 2019, the 2019-nCov coronavirus has appeared diverse mutational characteristics due to its own flexible conformation. One multiple-mutant strain (Omicron) with surprisingly infective activity outburst, and affected the biological activities of current drugs and vaccines, making the epidemic significantly difficult to prevent and control, and seriously threaten health around the world. Importunately exploration of mutant characteristics for novel coronavirus Omicron can supply strong theoretical guidance for learning binding mechanism of mutant viruses. What’s more, full acknowledgement of key mutated-residues on Omicron strain can provide new methodology of the novel pathogenic mechanism to human ACE2 receptor, as well as the subsequent vaccine development. Methods: In this research, 3D structures of 32 single-point mutations of 2019-nCov were firstly constructed, and 32-sites multiple-mutant Omicron were finally obtained based one the wild-type virus by homology modeling method. One total number of 33 2019-nCov/ACE2 complex systems were acquired by protein-protein docking, and optimized by using preliminary molecular dynamic simulations. Binding free energies between each 2019-nCov mutation system and human ACE2 receptor were calculated, and corresponding binding patterns especially the regions adjacent to mutation site were analyzed. The results indicated that one total number of 6 mutated sites on the Omicron strain played crucial role in improving binding capacities from 2019-nCov to ACE2 protein. Subsequently, we performed long-term molecular dynamic simulations and protein-protein binding energy analysis for the selected 6 mutations. 3 infected individuals, the mutants T478K, Q493R and G496S with lower binding energies -66.36, -67.98 and -67.09 kcal/mol also presents the high infectivity. These findings indicated that the 3 mutations T478K, Q493R and G496S play the crucial roles in enhancing binding affinity of Omicron to human ACE2 protein. All these results illuminate important theoretical guidance for future virus detection of the Omicron epidemic, drug research and vaccine development.

Background: With the development of the sequencing technology, RNA-seq is becoming more and more popular. The method of using RNA-seq technology to analyze the immune repertoire has the advantages of low sample demand, simple operation, and comprehensive information.Result: The RNA-seq data from public database were used to analyze and compare the TCR and BCR sequences of cancer and normal tissues in four types of cancers, including colon adenocarcinoma, lung adenocarcinoma, pancreatic adenocarcinoma and stomach adenocarcinoma. It was found that the clonal diversity of TCR among various types of cancer is different, and the variety of BCR between cancer tissues and healthy tissues is obvious. Based on the analysis of non-shared CDR3 sequences, the degree of the heterogeneity of TRB is: different cancer types> different individuals with same cancer> cancer tissues and paracancerous tissues of the same individual. Also, the correlation between the expression levels of the five main immune checkpoints genes and the count of TCR clones displayed various among different types of cancers.Conclusion: The results verify the advantage of RNA-seq analyzing in acquiring individual immune repertoire. Moreover, the heterogeneity of TCR in different cancers and the diversity of BCR in tumour and adjacent tissues shown in the results, provide hints at developing the strategies of tumour immunotherapy.