新冠病毒非选择性突变增加相关的非结构蛋白突变探究

Study on Non-Structural Protein Mutations Associated with Increased Non-Selective Mutations in SARS-CoV-2

严重急性呼吸综合征冠状病毒2型(新冠病毒,Severe acute respiratory syndrome coronavirus 2,SARS-CoV-2)基因组不断发生变异,新冠病毒非结构蛋白可影响新冠病毒基因组复制和组装。研究发现,通常认为比较保守的非结构蛋白也存在不同程度的变异。本研究旨在找出可能与新冠病毒非选择性突变增加相关的热点非结构蛋白基因突变。从全球共享流感数据倡议组织(Global Initiative of Sharing All Influenza Data,GISAID)数据库下载新冠病毒序列,将得到的序列与参考序列进行比对得到各序列突变情况。采用逻辑回归检验方法筛选出与病毒非选择性突变增加相关的非结构蛋白,分析这些非结构蛋白中突变频率前五位的核苷酸突变与病毒非选择性突变的关系,找出与非选择性突变频率增加有关的热点核苷酸突变。本研究共纳入236235条序列进行分析,各序列突变数量平均值为39.11。选取选择压力较小的M蛋白和E蛋白(Membrane protein or envelope protein,MoE)的突变总和代表病毒非选择性突变。调整发病时间、地理位置及变异株等因素后,多因素逻辑回归显示,NSP1中T670G、T445C、C745T,NSP3中C3037T、C7124T、C6402T,NSP4中C8986T、G9053T、C9891T,NSP6中T11418C、C11514T,NSP7中C11956T、C12008T,NSP12中C14408T,NSP13中C16466T、A17615G,NSP14中C19220T、A18163G、C18744T、C18877T、C19524T与MoE突变呈正相关(P<0.05),与病毒非选择性突变增加有关。新冠病毒非结构蛋白NSP1、NSP3、NSP4、NSP6、NSP7、NSP8、NSP12、NSP13、NSP14的某些热点核苷酸突变可能与基因组非选择突变增加有关。

Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)genomes are constantly mutating,and SARS-CoV-2 non-structural proteins(NSPs)can affect SARS-CoV-2 genome replication and assembly.It has been found that NSPs,which are usually considered to be relatively conserved,also showed different degree of variations.The aim of this study was to identify hotspot NSPs gene mutations that may be associated with increased non-selective mutations in SARS-CoV-2.Sequences of SARS-CoV-2 were downloaded from the Global Initiative on Sharing All Influenza Data(GISAID)database,and the downloaded sequences were compared with the reference sequences to obtain the mutation status of each sequence.The logistic regression test was used to screen the NSPs associated with increased viral non-selective mutations.The relationship between the top five nucleotide mutations of these NSPs and viral non-selective mutations was analyzed,to find out the hotspot nucleotide mutations that were associated with increased frequency of non-selective mutations.A total of 236,235 sequences were included in this study,and the mean value of the number of mutations in each sequence was 39.11.The sum of the mutations in the M and E proteins(MoE),which suffered less selection pressure,was selected to represent the viral non-selective mutations.After adjusting for time of onset,geographic location and variant strain,multifactorial logistic regression showed that NSP1_T670G,NSP1_T445C,NSP1_C745T,NSP3_C3037T,NSP3_C7124T,NSP3_C6402T,NSP4_C8986T,NSP4_G9053T,NSP4_C9891T,NSP6_T11418C,NSP6_C11514T,NSP7_C11956T,NSP7_C12008T,NSP12_C14408T,NSP13_C16466T,NSP13_A17615G,NSP14_C19220T,NSP14_A18163G,NSP14_C18744T,NSP14_C18877T and NSP14_C19524T were positively correlated with MoE mutations(P<0.05),and associated with increased non-selective mutations in the virus.Certain hotspot nucleotide mutations in NSP1,NSP3,NSP4,NSP6,NSP7,NSP8,NSP12,NSP13,and NSP14 of the SARS-CoV-2may be associated with increased non-selective mutations in the genome.