Kanyerezi Stephen, Sserwadda Ivan, Ssemaganda Aloysious, Seruyange Julius, Ayitewala Alisen, Oundo Hellen Rosette, Tenywa Wilson, Kagurusi Brian A, Tusabe Godwin, Were Stacy, Ssewanyana Isaac, Nabadda Susan, Namaganda Maria Magdalene, Mboowa Gerald
Department of Immunology and Molecular Biology, School of Biomedical Sciences, College of Health Sciences, Makerere University, P.O Box 7072 Kampala, Uganda.
The African Center of Excellence in Bioinformatics and Data-Intensive Sciences, the Infectious Diseases Institute, College of Health Sciences, Makerere University, P.O Box 22418 Kampala, Uganda.
Access Microbiol. 2024 Jul 17;6(7). doi: 10.1099/acmi.0.000815.v3. eCollection 2024.
The global prevalence of resistance to antiviral drugs combined with antiretroviral therapy (cART) emphasizes the need for continuous monitoring to better understand the dynamics of drug-resistant mutations to guide treatment optimization and patient management as well as check the spread of resistant viral strains. We have recently integrated next-generation sequencing (NGS) into routine HIV drug resistance (HIVDR) monitoring, with key challenges in the bioinformatic analysis and interpretation of the complex data generated, while ensuring data security and privacy for patient information. To address these challenges, here we present HIV-DRIVES (HIV Drug Resistance Identification, Variant Evaluation, and Surveillance), an NGS-HIVDR bioinformatics pipeline that has been developed and validated using Illumina short reads, FASTA, and Sanger .seq files.
对抗病毒药物与抗逆转录病毒疗法（cART）产生耐药性的情况在全球普遍存在，这凸显了持续监测的必要性，以便更好地了解耐药突变的动态，从而指导治疗优化和患者管理，并遏制耐药病毒株的传播。我们最近已将下一代测序（NGS）整合到常规的HIV耐药性（HIVDR）监测中，在对所产生的复杂数据进行生物信息学分析和解读时面临着关键挑战，同时还要确保患者信息的数据安全和隐私。为应对这些挑战，我们在此展示HIV-DRIVES（HIV耐药性鉴定、变异评估和监测），这是一种利用Illumina短读长序列、FASTA和Sanger.seq文件开发并验证的NGS-HIVDR生物信息学流程。
