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首页> 外文期刊>AIDS Research and Human Retroviruses >Comparison of population and 454 'deep' sequence analysis for HIV type 1 tropism versus the original trofile assay in non-B subtypes
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Comparison of population and 454 'deep' sequence analysis for HIV type 1 tropism versus the original trofile assay in non-B subtypes

机译:非B亚型HIV 1型向性与原始trofile检测的群体和454“深层”序列分析的比较

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HIV-1 tropism can be predicted using V3 genotypic algorithms. The performance of these prediction algorithms for non-B subtypes is poorly characterized. Here, we use these genotypic algorithms to predict viral tropism of HIV-1 subtype A, B, C, and D to find apparent sensitivity, specificity, and concordance against a recombinant phenotypic assay, the original Trofile assay. This is a substudy of an epidemiological study (Pfizer A4001064). Plasma samples were selected to represent a large number of DM/X4 and R5 viruses. The HIV-1 env gene V3 loop was genotyped by Sanger sequencing (N=260) or 454 "deep" sequencing (N=280). Sequences were scored with g2p[coreceptor], PSSM X4/R5, PSSM SI/NSI, and PSSM subtype C matrices. Overall, non-B subtypes tropism prediction had similar concordance and apparent sensitivity and specificity as subtype B in predicting Trofile's results in both population sequencing (81.3%, 65.6%, and 90.5% versus 84.2%, 78.5%, and 88.2%) and 454 "deep" sequencing (82.3%, 80.0%, and 83.6% versus 86.8%, 92.0%, and 82.6%) using g2p[coreceptor]. By population sequencing, subtype A had lower sensitivity, whereas subtype D had lower specificity for non-R5 predictions, both in comparison to subtype B. 454 "deep" sequencing improved subtype A sensitivity but not subtype D. Subtype C had greater concordance than subtype B regardless of sequencing methods. In conclusion, genotypic tropism prediction algorithms may be applied to non-B HIV-1 subtypes with caution. Collective analysis of non-B subtypes revealed a performance similar to subtype B, whereas a subtype-specific analysis revealed overestimation (subtype D) or underestimation (subtype A).
机译:可以使用V3基因型算法预测HIV-1的向性。这些针对非B亚型的预测算法的性能表征不佳。在这里,我们使用这些基因型算法来预测HIV-1亚型A,B,C和D的病毒趋向性,以发现针对重组表型测定法(原始Trofile测定法)的明显敏感性,特异性和一致性。这是流行病学研究(Pfizer A4001064)的子研究。选择血浆样本以代表大量DM / X4和R5病毒。通过Sanger测序(N = 260)或454“深度”测序(N = 280)对HIV-1 env基因V3环进行基因分型。用g2p [共同受体],PSSM X4 / R5,PSSM SI / NSI和PSSM C亚型矩阵对序列进行评分。总体而言,非B亚型的向性性预测与B型亚型在人群测序中预测Trofile的结果时具有相似的一致性,明显的敏感性和特异性(81.3%,65.6%和90.5%,而84.2%,78.5%和88.2%)和454使用g2p [coreceptor]进行“深度”测序(82.3%,80.0%和83.6%,而86.8%,92.0%和82.6%)。通过群体测序,与亚型B相比,亚型A的敏感性较低,而亚型D对非R5预测的特异性较低。454“深度”测序可提高亚型A的敏感性,但不能提高亚型C。亚型C的一致性比亚型大B不论测序方法。总之,基因型向性预测算法可能会谨慎地应用于非B HIV-1亚型。对非B型亚型的集体分析显示出与B型亚型相似的性能,而对特定于亚型的分析则显示出高估(D型)或低估(A型)。

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