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突变途径图谱和起源效应定义了宿主内丙型肝炎病毒耐药突变体的范围。

Mutational pathway maps and founder effects define the within-host spectrum of hepatitis C virus mutants resistant to drugs.

机构信息

Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.

Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India.

出版信息

PLoS Pathog. 2019 Apr 1;15(4):e1007701. doi: 10.1371/journal.ppat.1007701. eCollection 2019 Apr.

Abstract

Knowledge of the within-host frequencies of resistance-associated amino acid variants (RAVs) is important to the identification of optimal drug combinations for the treatment of hepatitis C virus (HCV) infection. Multiple RAVs may exist in infected individuals, often below detection limits, at any resistance locus, defining the diversity of accessible resistance pathways. We developed a multiscale mathematical model to estimate the pre-treatment frequencies of the entire spectrum of mutants at chosen loci. Using a codon-level description of amino acids, we performed stochastic simulations of intracellular dynamics with every possible nucleotide variant as the infecting strain and estimated the relative infectivity of each variant and the resulting distribution of variants produced. We employed these quantities in a deterministic multi-strain model of extracellular dynamics and estimated mutant frequencies. Our predictions captured database frequencies of the RAV R155K, resistant to NS3/4A protease inhibitors, presenting a successful test of our formalism. We found that mutational pathway maps, interconnecting all viable mutants, and strong founder effects determined the mutant spectrum. The spectra were vastly different for HCV genotypes 1a and 1b, underlying their differential responses to drugs. Using a fitness landscape determined recently, we estimated that 13 amino acid variants, encoded by 44 codons, exist at the residue 93 of the NS5A protein, illustrating the massive diversity of accessible resistance pathways at specific loci. Accounting for this diversity, which our model enables, would help optimize drug combinations. Our model may be applied to describe the within-host evolution of other flaviviruses and inform vaccine design strategies.

摘要

了解宿主内耐药相关氨基酸变异(RAV)的频率对于确定治疗丙型肝炎病毒(HCV)感染的最佳药物组合非常重要。在任何耐药部位,感染个体体内通常都存在多个低于检测限的 RAV,这定义了可获得的耐药途径的多样性。我们开发了一种多尺度数学模型,以估计选定位置所有突变体的治疗前频率。我们使用氨基酸的密码子水平描述,对每个可能的核苷酸变体作为感染株进行了细胞内动态的随机模拟,并估计了每个变体的相对感染力以及产生的变体分布。我们将这些数量用于细胞外动态的确定性多株模型中,并估计了突变体频率。我们的预测捕捉到了数据库中 R155K 突变体的频率,该突变体对 NS3/4A 蛋白酶抑制剂有耐药性,成功地检验了我们的形式主义。我们发现,突变途径图谱,将所有可行的突变体相互连接,以及强大的创始效应决定了突变体谱。HCV 基因型 1a 和 1b 的谱非常不同,这解释了它们对药物的不同反应。使用最近确定的适应度景观,我们估计在 NS5A 蛋白的第 93 位有 13 个氨基酸变异体,由 44 个密码子编码,说明了特定位置可获得的耐药途径的巨大多样性。考虑到我们的模型能够实现的这种多样性,这将有助于优化药物组合。我们的模型可用于描述其他黄病毒在宿主内的进化,并为疫苗设计策略提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64f5/6459561/f38e9a7014b1/ppat.1007701.g001.jpg

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