Dotrang Thoai, Sherman Brad T, Dai Lisheng, Khan Muhammad Ayub, Highbarger Helene C, Bruchey Whitney, Laverdure Sylvain, Baseler Michael W, Imamichi Tomozumi, Dewar Robin L, Chang Weizhong
Laboratory of Human Retrovirology and Immunoinformatics, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
Virus Isolation and Serology Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
BMC Bioinformatics. 2025 Jul 7;26(1):168. doi: 10.1186/s12859-025-06201-5.
The emergence of HIV drug resistance is a challenge in controlling the acquired immunodeficiency syndrome (AIDS) pandemic caused by human immunodeficiency virus-1 (HIV-1) infection. Detection of drug resistance variants at minor frequencies can help to formulate successful antiretroviral therapy (ART) regimens for people living with HIV (PLWH) and reduce the emergence of drug resistance. Therefore, a pipeline which can accurately produce consensus nucleotide sequences and identify drug resistance mutations (DRMs) at defined frequency thresholds will be helpful in the treatment of PLWH, analysis of virus evolution, and the control of the pandemic.
We have developed a pipeline, HIVGenoPipe, to determine HIV drug resistance variants within the gag-pol region above user-defined frequencies for HIV-1 samples sequenced using Illumina technology. The pipeline has been validated by comparing its results with the results generated by a widely used pipeline, HyDRA, which is limited to the pol region, and with the results generated by Sanger sequencing technology using the same set of 30 samples. The variant frequency used to generate ambiguous consensus sequences in HIVGenoPipe is more accurate than other pipelines because a sample-specific reference, which is generated in real-time with a novel hybrid strategy of de novo and reference-based assembly, is used for the frequency calculation, leading to more accurate drug resistance calls for use by clinicians. In addition, since Nextflow is used as the pipeline platform, HIVGenoPipe inherently has great portability, scalability and reproducibility; and the components can be updated or replaced independently if required.
We developed HIVGenoPipe for the detection of HIV-1 drug resistance. It constructs more accurate gag-pol consensus sequences, leading to improved detection of DRMs. HIVGenoPipe is open source and freely available under the MIT license at https://github.com/LHRI-Bioinformatics/HIVGenoPipe . The current release (v1.0.1) is archived and available at https://doi.org/ https://doi.org/10.5281/zenodo.15528502 .
HIV耐药性的出现是控制由人类免疫缺陷病毒1型（HIV-1）感染引起的获得性免疫缺陷综合征（AIDS）大流行的一项挑战。检测低频耐药变异有助于为HIV感染者（PLWH）制定成功的抗逆转录病毒治疗（ART）方案，并减少耐药性的出现。因此，一个能够准确生成一致核苷酸序列并在定义的频率阈值下识别耐药突变（DRM）的流程，将有助于PLWH的治疗、病毒进化分析以及大流行的控制。
我们开发了一个名为HIVGenoPipe的流程，用于确定使用Illumina技术测序的HIV-1样本中，gag-pol区域内高于用户定义频率的HIV耐药变异。通过将其结果与广泛使用的、限于pol区域的流程HyDRA所产生的结果，以及使用同一组30个样本通过桑格测序技术所产生的结果进行比较，对该流程进行了验证。HIVGenoPipe中用于生成模糊一致序列的变异频率比其他流程更准确，因为在频率计算中使用了一个样本特异性参考序列，该序列通过一种全新的从头组装和基于参考的混合策略实时生成，从而使临床医生能够做出更准确的耐药性判断。此外，由于使用Nextflow作为流程平台，HIVGenoPipe天生具有很强的可移植性、可扩展性和可重复性；并且如果需要，组件可以独立更新或替换。
我们开发了用于检测HIV-1耐药性的HIVGenoPipe。它构建了更准确的gag-pol一致序列，从而改进了DRM的检测。HIVGenoPipe是开源的，根据麻省理工学院许可可在https://github.com/LHRI-Bioinformatics/HIVGenoPipe免费获取。当前版本（v1.0.1）已存档，可在https://doi.org/https://doi.org/10.5281/zenodo.15528502获取。
