Abstract
SARS-CoV-2 variants are constantly emerging,hampering public health measures in controlling the number of infections.While it is well established that mutations in spike proteins observed for the different variants directly affect virus entry into host cells,there remains a need for further expansion of systematic and multifaceted comparisons.Here,we comprehensively studied the effect of spike protein mutations on spike expression and proteolytic activation,binding affinity,viral entry efficiency and host cell tropism of eight variants of concern(VOC)and variants of interest(VOI).We found that both the full-length spike and its receptor-binding domain(RBD)of Omicron bind to hACE2 with an affinity similar to that of the wild-type.In addition,Alpha,Beta,Delta and Lambda pseudoviruses gained significantly enhanced cell entry ability compared to the wild-type,while the Omicron pseudoviruses showed a slightly increased cell entry,suggesting the vastly increased rate of transmission observed for Omicron variant is not associated with its affinity to hACE2.We also found that the spikes of Omicron and Mu showed lower S1/S2 cleavage efficiency and inefficiently utilized TMPRSS2 to enter host cells than others,suggesting that they prefer the endocytosis pathway to enter host cells.Furthermore,all variants'pseudoviruses we tested gained the ability to enter the animal ACE2-expressing cells.Especially the infection potential of rats and mice showed significantly increased,strongly suggesting that rodents possibly become a reservoir for viral evolution.The insights gained from this study provide valuable guidance for a targeted approach to epidemic control,and contribute to a better understanding of SARS-CoV-2 evolution.
基金项目
Strategic Priority Research Program of the Chinese Academy of Sciences(XDB29050100)
National Key Research and Development Program of China(2022YFC0869900)
National Key Research and Development Program of China(2022YFC2303501)
National Key Research and Development Program of China(2020YFC0861100)
Program of the Chinese Academy of Sciences(2020YJFK-Z-0150)
NETL
NSTL
万方数据