5例HIV-1感染者pol基因进化和感染时间推断研究

Intra-host genetic evolution of HIV-1 pol gene and estimation of infection time for five infections

目的研究未接受抗反转录病毒治疗的HIV-1感染者pol基因进化特征,并用贝叶斯合并理论推断感染时间,为艾滋病疫情评估提供依据。方法募集5例未接受抗反转录病毒治疗的HIV-1感染者,定期随访并采集血样,用RT-PCR法扩增pol基因片段,分析基因型耐药突变;采用贝叶斯合并理论分析毒株进化关系,构建最大可信(MCC)进化树,推测其最近共同祖先株形成时间,进而推断感染时间。结果5例HIV-1感染者均为男性,年龄为27~50岁。每例感染者有5~9个采样时间点,其pol基因序列各自聚集成一个独立的次级进化簇(后验概率值为100%)。1例急性期感染者携带传播性耐药突变(M46I突变),并表现出快速疾病进展和准种病毒变异特征。推断3例急性期感染者的感染时间为HIV抗体初筛有反应前1~5个月;2例初检即确证病例感染时间分别为HIV抗体初筛有反应前14个月和前7个月。结论运用贝叶斯合并理论分析HIV-1感染者pol基因进化情况,可大致推断感染时间,有助于艾滋病疫情形势研判。

Objective To explore the intra-host genetic evolution of HIV-1 pol gene via follow-up for treatment-na?ve HIV infections,and estimate the infection time with Bayesian coalescent theory,so as to support the evaluation of HIV epidemic.Methods Five cases were recruited and followed up.The pol gene fragments were amplified for the characteristics of transmitted drug resistance(TDR)by RT-PCR.Bayesian coalescent theory was utilized to construct maximum clade credibility(MCC)tree for genetic evolution and calculate the time to the most recent common ancestor(t MRCA).Results The five cases were all male,and aged from 27 to 50 years old.Five to nine sampling times were obtained from each case,and the pol gene sequences from each case formed a unique subcluster(posterior probability:100%),with different evolution characteristics,in the MCC tree.The three cases in primary HIV-1 infection were estimated to be infected one to five months before the first positive reaction of HIV screening,whereas the two HIV-1 diagnosed cases at first screening were extrapolated to get infected fourteen months and seven months before diagnosis,respectively.One case with acute HIV-1 infection carried TDR mutation(M46I),expressing fast disease progress and quasispecies variation.Conclusions The general infection time can be estimated by analyzing the characteristics of intra-host genetic evolution of HIV-1 pol gene with Bayesian coalescent theory,and this method can help to estimate the HIV epidemic.