The rapid evolution of HIV is constrained by interactions between mutations which affect viral fitness. In this work, we explore the role of epistasis in determining the fitness landscape of HIV for multiple drug target proteins, including Protease, Reverse Transcriptase, and Integrase. Epistatic interactions between residues modulate the mutation patterns involved in drug resistance with unambiguous signatures of epistasis best seen in the comparison of a maximum entropy sequence co-variation (Potts) model predicted and experimental HIV sequence ``prevalences" when expressed as higher-order marginals (beyond triplets) of the sequence probability distribution. In contrast, the evidence for epistasis based on experimental measures of fitness such as replicative capacity is weak; the correspondence with Potts model ``prevalence"-based predictions is obscured by site conservation and limited precision. Double mutant cycles provide in principle one of the best ways to probe epistatic interactions experimentally without reference to a particular background, and we find they reveal that the most strongly interacting mutations in HIV involve correlated sets of drug-resistance-associated residues, however the analysis is complicated by the small dynamic range of measurements. The use of correlated models for the design of experiments to probe viral fitness can help identify the epistatic interactions involved in mutational escape, and lead to better inhibitor therapies.

中文翻译：

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上位性在决定 HIV 蛋白适应性景观中的作用

HIV 的快速进化受到影响病毒适应性的突变之间相互作用的限制。在这项工作中，我们探索了上位性在确定多种药物靶蛋白（包括蛋白酶、逆转录酶和整合酶）的 HIV 适应性景观中的作用。残基之间的上位性相互作用调节涉及耐药性的突变模式，上位性的明确特征在最大熵序列协变（Potts）模型预测和实验 HIV 序列“流行率”的比较中最能看出，当表达为高阶边缘时（超越三元组）序列概率分布。相比之下，基于适应性实验测量（如复制能力）的上位性证据较弱；与 Potts 模型“流行率”的对应关系 基于站点的保护和有限的精度掩盖了基于预测的预测。双突变循环原则上提供了在不参考特定背景的情况下通过实验探索上位相互作用的最佳方法之一，我们发现它们揭示了 HIV 中相互作用最强的突变涉及相关的耐药相关残基集，但是分析由于测量的小动态范围而变得复杂。使用相关模型设计实验以探测病毒适应性可以帮助识别突变逃逸中涉及的上位相互作用，并导致更好的抑制剂疗法。双突变循环原则上提供了在不参考特定背景的情况下通过实验探索上位相互作用的最佳方法之一，我们发现它们揭示了 HIV 中相互作用最强的突变涉及相关的耐药相关残基集，但是分析由于测量的小动态范围而变得复杂。使用相关模型来设计实验以探测病毒适应性可以帮助识别突变逃逸中涉及的上位相互作用，并导致更好的抑制剂疗法。双突变循环原则上提供了在不参考特定背景的情况下通过实验探索上位相互作用的最佳方法之一，我们发现它们揭示了 HIV 中相互作用最强的突变涉及相关的耐药相关残基集，但是分析由于测量的小动态范围而变得复杂。使用相关模型设计实验以探测病毒适应性可以帮助识别突变逃逸中涉及的上位相互作用，并导致更好的抑制剂疗法。