Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada.
Department of Microbiology and Immunology, Western University, London, ON, Canada.
Retrovirology. 2018 Jul 5;15(1):47. doi: 10.1186/s12977-018-0426-1.
The ability of HIV-1 to integrate into the genomes of quiescent host immune cells, establishing a long-lived latent viral reservoir (LVR), is the primary obstacle to curing these infections. Quantitative viral outgrowth assays (QVOAs) are the gold standard for estimating the size of the replication-competent HIV-1 LVR, measured by the number of infectious units per million (IUPM) cells. QVOAs are time-consuming because they rely on culturing replicate wells to amplify the production of virus antigen or nucleic acid to reproducibly detectable levels. Sequence analysis can reduce the required number of culture wells because the virus genetic diversity within the LVR provides an internal replication and dilution series. Here we develop a Bayesian method to jointly estimate the IUPM and variant frequencies (a measure of clonality) from the sequence diversity of QVOAs.
Using simulation experiments, we find our Bayesian approach confers significantly greater accuracy over current methods to estimate the IUPM, particularly for reduced numbers of QVOA replicates and/or increasing actual IUPM. Furthermore, we determine that the improvement in accuracy is greater with increasing genetic diversity in the sample population. We contrast results of these different methods applied to new HIV-1 sequence data derived from QVOAs from two individuals with suppressed viral loads from the Rakai Health Sciences Program in Uganda.
Utilizing sequence variation has the additional benefit of providing information on the contribution of clonality of the LVR, where high clonality (the predominance of a single genetic variant) suggests a role for cell division in the long-term persistence of the reservoir. In addition, our Bayesian approach can be adapted to other limiting dilution assays where positive outcomes can be partitioned by their genetic heterogeneity, such as immune cell populations and other viruses.
HIV-1 整合到静止宿主免疫细胞基因组中从而建立一个长期潜伏的病毒储存库(LVR)的能力,是治愈这些感染的主要障碍。定量病毒扩增检测(QVOA)是估计具有复制能力的 HIV-1 LVR 大小的金标准,通过每百万个细胞的感染性单位(IUPM)数量来衡量。QVOA 非常耗时,因为它们依赖于培养重复的孔来扩增病毒抗原或核酸的产生,以达到可重复检测的水平。序列分析可以减少所需的培养孔数量,因为 LVR 内的病毒遗传多样性提供了内部复制和稀释系列。在这里,我们开发了一种贝叶斯方法,从 QVOA 的序列多样性中联合估计 IUPM 和变体频率(衡量克隆性的指标)。
使用模拟实验,我们发现我们的贝叶斯方法在估计 IUPM 方面明显优于当前方法,尤其是在减少 QVOA 重复次数和/或增加实际 IUPM 时。此外,我们确定随着样本群体遗传多样性的增加,准确性的提高更大。我们对比了这些不同方法应用于来自乌干达 Rakai 健康科学计划的两个病毒载量得到抑制的个体的 QVOA 新 HIV-1 序列数据的结果。
利用序列变异除了提供 LVR 克隆性贡献的信息外,还有额外的好处,其中高克隆性(单一遗传变异的优势)表明细胞分裂在长期维持储库中起作用。此外,我们的贝叶斯方法可以适用于其他限制稀释检测,其中阳性结果可以根据其遗传异质性进行划分,例如免疫细胞群体和其他病毒。