HIV-DRIVES: HIV drug resistance identification, variant evaluation, and surveillance pipeline

Author:

Kanyerezi Stephen123ORCID,Sserwadda Ivan4132ORCID,Ssemaganda Aloysious53ORCID,Seruyange Julius3,Ayitewala Alisen3ORCID,Oundo Hellen Rosette3ORCID,Tenywa Wilson3,Kagurusi Brian A.3ORCID,Tusabe Godwin3ORCID,Were Stacy3,Ssewanyana Isaac3ORCID,Nabadda Susan3ORCID,Namaganda Maria Magdalene21ORCID,Mboowa Gerald126ORCID

Affiliation:

1. Department of Immunology and Molecular Biology, School of Biomedical Sciences, College of Health Sciences, Makerere University, P.O Box 7072 Kampala, Uganda

2. 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

3. National Health Laboratories and Diagnostics Services, Central Public Health Laboratories, Ministry of Health, P.O Box 7272 Kampala, Uganda

4. Amsterdam Institute for Global Health and Development (AIGHD), Department of Global Health, Academic Medical Center, Amsterdam, Netherlands

5. Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, Canada

6. Africa Centres for Disease Control and Prevention, African Union Commission, Roosevelt Street, P.O. Box 3243, W21 K19 Addis Ababa, Ethiopia

Abstract

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 ab1.seq files.

Funder

PHA4GE

CAGE-TB Project

Foundation for the National Institutes of Health

EDCTP

African Doctoral Dissertation Research Fellowship

Eastern Africa Network of Bioinformatics Training (EANBiT) project

Publisher

Microbiology Society

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