Deep sequencing SARS-CoV-2 samples from New Mexico to interrogate immunological selection on genetic variants

尽管疫苗接种在几个国家削弱了SARS-CoV-2大流行的影响，但未来的影响 这种病毒的安全性将取决于它的传播性、毒力以及逃避自然获得和疫苗接种的能力。 中介免疫。由于新型SARS的进化和传播，这三种表型目前都在变化- 令人担忧的CoV-2变种。重要的是，所有这些变体都在广泛传播之前声名鹊起 接种疫苗。因此，虽然有些可能是免疫调节选择的产物，但它们并不是作为回应而进化的。 对于疫苗接种本身，我们几乎不知道疫苗接种是否以及如何对 SARS-CoV-2。为了缩小这一知识差距，拟议中的研究将解决这个问题：接种疫苗吗 研究参与者仍然感染SARS-CoV-2病毒，如果是这样的话，他们携带的是什么变种？我们 假设疫苗介导的免疫可能以以下三种方式之一对变种施加选择：(I)在- 接种者更有可能被预先适应免疫逃逸的变种感染的宿主选择， (Ii)宿主内选择，在这种选择中，具有免疫逃逸能力的新变体首先在个体中进化 然后可传播给已接种或未接种疫苗的个人，或(Iii)以下各项的组合 在主机选择内和主机选择之间。此外，我们假设疫苗介导的免疫将施加 对SARS-CoV-2的选择性强于自然诱导免疫或单抗治疗。推断出的模式 寄主内选择需要关于寄主内种群变异的数据，但到目前为止，对寄主内的研究 SARS-CoV-2的群体在很大程度上被忽略了，而倾向于一致的序列。因此，我们将获得 来自下列人群的≥-CoV-2阳性样本的残留物：(1)SARS-CoV-2感染者 接种疫苗后至少5天及之后的任何间隔，(2)≥50人正在接受单抗治疗，(3) 200至400名持续感染的人，在首次阳性检测后至少5天检测呈阳性，以及 (4)在大流行早期检测呈阳性的100人的第一个阳性检测，代表控制组 这很可能是在他们首次感染的早期。这些样本将由TriCore实验室从 在新墨西哥州接受测试的个人。从样品中提取的RNA将同时受到Illumina和PacBio的影响 测序；来自两种方法的数据将被用于检测一致的变体、INDELs和宿主内 频率为2%的单核苷酸变异(ISNV)，读取时间较长的Pac Bio数据将用于 评估突变之间的联系，促进重组的检测，例如(20)和混合变异 感染(混合感染)。这些数据将被用来量化宿主内部的多样性和选择、频率 常见的亚共识突变，VOC中存在的高危突变的趋同进化。系统发育 还将分析iSNV的关联。位于已记录的抗体结合位点内的新突变 或者，T细胞表位将被标记并仔细检查是否传播。

Although vaccination has blunted the impact of the SARS-CoV-2 pandemic in several countries, the future impact of this virus will depend on its transmissibility, virulence, and ability to evade naturally-acquired and vaccine- mediated immunity. All three phenotypes are currently in flux due to the evolution and spread of novel SARS- CoV-2 variants of concern. Importantly, all of these variants rose to prominence prior to widespread vaccination. Thus, while some may be the product of immune-mediated selection, they did not evolve in response to vaccination per se, and we know next to nothing about whether and how vaccination imposes selection on SARS-CoV-2. To close this knowledge gap, the proposed research will address the question: Do vaccinated study participants still acquire the SARS-CoV-2 virus, and if so, what variants do they carry? We hypothesize that vaccine-mediated immunity may impose selection on variants in one of three ways: (i) between- host selection in which vaccinees are more likely to be infected by variants pre-adapted for immune escape, (ii) within-host selection in which novel variants with capacity for immune escape first evolve in individual vaccinees, and may then be transmitted to vaccinated or unvaccinated individuals, or (iii) a combination of within- and between host selection. Furthermore, we hypothesize that vaccine-mediated immunity will impose stronger selection on SARS-CoV-2 than naturally-induced immunity or mAb therapy. Inferring patterns of within-host selection requires data on within-host population variation, but to date, studies of within-host populations of SARS-CoV-2 have been largely neglected in favor of consensus sequences. Thus, we will obtain residual material from SARS-CoV-2 positive samples from the following groups: (1) ≥ 100 individuals infected at least 5 days and any interval thereafter following vaccination, (2) ≥50 individuals being treated with mAbs, (3) 200 to 400 persistently infected individuals testing positive at least 5 days following an initial positive test, and (4) the first positive test from 100 individuals testing positive early in the pandemic, to represent a control group that is likely at an early point in their first infection. These samples will be provided by Tricore labs from individuals tested in New Mexico. RNA extracted from samples will be subject to both Illumina and PacBio sequencing; data from both approaches will be used to detect consensus variants, indels, and intra-host single-nucleotide variants (iSNVs) at frequencies >2%, and the longer-read Pac Bio data will be used to assess linkage between mutations, facilitating detection of recombination, e.g. (20), and mixed-variant infections (co-infection). These data will be used to quantify intra-host diversity and selection, frequency of common, sub-consensus mutations, convergent evolution of high-risk mutations present in VOC. Phylogenetic association of iSNVs will also be analyzed. Novel mutations that fall within documented antibody binding sites or T cell epitopes will be flagged and scrutinized for spread.