Estimation of an in vivo fitness landscape experienced by HIV-1 under drug selective pressure useful for prediction of drug resistance evolution during treatment
Estimation of an in vivo fitness landscape experienced by HIV-1 under drug selective pressure useful for prediction of drug resistance evolution during treatment
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DOI：
10.1093/bioinformatics/btm540
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发表时间：
2008-01-01
期刊：
影响因子：
5.8
通讯作者：
Vandamme, A. -M.
中科院分区：
文献类型：
--
作者：
Deforche, K.;Camacho, R.;Vandamme, A. -M.
动机：HIV-1抗病毒耐药性是抗病毒治疗失败的主要原因。病毒在存在治疗的情况下所经历的体内适应情况原则上可以用来确定病毒对治疗的敏感性和对耐药性的遗传障碍。我们提出了一种方法，通过逆向工程从治疗初学者获得的HIV-1序列所需的选择压力，从治疗后的患者获得的序列进化到从治疗患者获得的序列，从不同亚型的横截面临床基因序列数据中估计这种适合度格局。在模拟实验中对该方法进行了评估，恢复了10个随机的虚拟选择压力，并模拟了蛋白酶抑制剂奈非那韦处理下的选择压力。结果：奈非那韦处理下的估计适应度函数考虑了48个位点114个突变的适应度贡献。在519对匹配的基因-表型配对中，估计的适合度与体外耐药表型显著相关(R2=0.47(0.41-0.54))，在奈非那韦选择性压力下预测的进化变化与在奈非那韦治疗39个突变期间观察到的体内进化显著相关(FDR=0.05)。补充信息：补充数据可在BioInformation Online上获得。
Motivation: HIV-1 antiviral resistance is a major cause of antiviral treatment failure. The in vivo fitness landscape experienced by the virus in presence of treatment could in principle be used to determine both the susceptibility of the virus to the treatment and the genetic barrier to resistance. We propose a method to estimate this fitness landscape from cross-sectional clinical genetic sequence data of different subtypes, by reverse engineering the required selective pressure for HIV-1 sequences obtained from treatment naive patients, to evolve towards sequences obtained from treated patients. The method was evaluated for recovering 10 random fictive selective pressures in simulation experiments, and for modeling the selective pressure under treatment with the protease inhibitor nelfinavir.Results: The estimated fitness function under nelfinavir treatment considered fitness contributions of 114 mutations at 48 sites. Estimated fitness correlated significantly with the in vitro resistance phenotype in 519 matched genotype-phenotype pairs (R-2 = 0.47 (0.41 - 0.54)) and variation in predicted evolution under nelfinavir selective pressure correlated significantly with observed in vivo evolution during nelfinavir treatment for 39 mutations (with FDR = 0.05).Supplementary information: Supplementary data are available at Bioinformatics online.