Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

A comprehensive genomics solution for HIV surveillance and clinical monitoring in a global health setting

David Bonsall, Tanya Golubchik, Mariateresa de Cesare, Mohammed Limbada, Barry Kosloff, George MacIntyre-Cockett, Matthew Hall, Chris Wymant, M Azim Ansari, Lucie Abeler-Dörner, Ab Schaap, Anthony Brown, Eleanor Barnes, Estelle Piwowar-Manning, Ethan Wilson, Lynda Emel, Richard Hayes, Sarah Fidler, Helen Ayles, Rory Bowden, Christophe Fraser
doi: https://doi.org/10.1101/397083
David Bonsall
aBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
bWellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tanya Golubchik
aBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
bWellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: david.bonsall@bdi.ox.ac.uk tanya.golubchik@bdi.ox.ac.uk
Mariateresa de Cesare
bWellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mohammed Limbada
cZAMBART, University of Zambia, Lusaka, Zambia
dLondon School of Hygiene and Tropical Medicine, London, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Barry Kosloff
cZAMBART, University of Zambia, Lusaka, Zambia
dLondon School of Hygiene and Tropical Medicine, London, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
George MacIntyre-Cockett
aBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
bWellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Matthew Hall
aBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chris Wymant
aBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
M Azim Ansari
bWellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
ePeter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lucie Abeler-Dörner
aBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ab Schaap
cZAMBART, University of Zambia, Lusaka, Zambia
dLondon School of Hygiene and Tropical Medicine, London, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Anthony Brown
ePeter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Eleanor Barnes
ePeter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Estelle Piwowar-Manning
fHIV Prevention Trials Network (HPTN) Laboratory Core, Johns Hopkins University, Baltimore,vMaryland, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ethan Wilson
gStatistical Centre for HIV/AIDS Research, Fred Hutchinson Cancer Research Centre, Seattle, Washington, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lynda Emel
gStatistical Centre for HIV/AIDS Research, Fred Hutchinson Cancer Research Centre, Seattle, Washington, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Richard Hayes
dLondon School of Hygiene and Tropical Medicine, London, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sarah Fidler
hDepartment of Medicine, Imperial College London, London, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Helen Ayles
cZAMBART, University of Zambia, Lusaka, Zambia
dLondon School of Hygiene and Tropical Medicine, London, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rory Bowden
bWellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christophe Fraser
aBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

High-throughput viral genetic sequencing is needed to monitor the spread of drug resistance, direct optimal antiretroviral regimes, and to identify transmission dynamics in generalised HIV epidemics. Public health efforts to sequence HIV genomes at scale face three major technical challenges: (i) minimising assay cost and protocol complexity, (ii) maximising sensitivity, and (iii) recovering accurate and unbiased sequences of both the genome consensus and the within-host viral diversity. Here we present a novel, high-throughput, virus-enriched sequencing method and computational pipeline tailored specifically to HIV (veSEQ-HIV), which addresses all three technical challenges, and can be used directly on leftover blood drawn for routine CD4 testing. We demonstrate its performance on 1,620 plasma samples collected from consenting individuals attending 10 large urban clinics in Zambia, partners of HPTN 071 (PopART). We show that veSEQ-HIV consistently recovers complete HIV genomes from the majority of samples of different subtypes, and is also quantitative: the number of HIV reads per sample obtained by veSEQ-HIV estimates viral load without the need for additional testing. Both quantitativity and sensitivity were assessed on a subset of 126 samples with clinically measured viral loads, and with standardized quantification controls (VL 100 – 5,000,000 RNA copies/ml). Complete HIV genomes were recovered from 93% (85/91) of samples when viral load was over 1,000 copies per ml. The quantitative nature of the assay implies that variant frequencies estimated with veSEQ-HIV are representative of true variant frequencies in the sample. Detection of minority variants can be exploited for epidemiological analysis of transmission and drug resistance, and we show how the information contained in individual reads of a veSEQ-HIV sample can be used to detect linkage between multiple mutations associated with resistance to antiretroviral therapy. Less than 2% of reads obtained by veSEQ-HIV were identified as in silico contamination events using updates to the phyloscanner software (phyloscanner clean) that we show to be 95% sensitive and 99% specific at ‘decontaminating’ NGS data. The cost of the assay — approximately 45 USD per sample — compares favourably with existing VL and HIV genotyping tests, and provides the additional value of viral load quantification and inference of drug resistance with a single test. veSEQ-HIV is well suited to large public health efforts and is being applied to all ∼9000 samples collected for the HPTN 071-2 (PopART Phylogenetics) study.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted August 21, 2018.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
A comprehensive genomics solution for HIV surveillance and clinical monitoring in a global health setting
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
A comprehensive genomics solution for HIV surveillance and clinical monitoring in a global health setting
David Bonsall, Tanya Golubchik, Mariateresa de Cesare, Mohammed Limbada, Barry Kosloff, George MacIntyre-Cockett, Matthew Hall, Chris Wymant, M Azim Ansari, Lucie Abeler-Dörner, Ab Schaap, Anthony Brown, Eleanor Barnes, Estelle Piwowar-Manning, Ethan Wilson, Lynda Emel, Richard Hayes, Sarah Fidler, Helen Ayles, Rory Bowden, Christophe Fraser
bioRxiv 397083; doi: https://doi.org/10.1101/397083
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
A comprehensive genomics solution for HIV surveillance and clinical monitoring in a global health setting
David Bonsall, Tanya Golubchik, Mariateresa de Cesare, Mohammed Limbada, Barry Kosloff, George MacIntyre-Cockett, Matthew Hall, Chris Wymant, M Azim Ansari, Lucie Abeler-Dörner, Ab Schaap, Anthony Brown, Eleanor Barnes, Estelle Piwowar-Manning, Ethan Wilson, Lynda Emel, Richard Hayes, Sarah Fidler, Helen Ayles, Rory Bowden, Christophe Fraser
bioRxiv 397083; doi: https://doi.org/10.1101/397083

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genomics
Subject Areas
All Articles
  • Animal Behavior and Cognition (3484)
  • Biochemistry (7336)
  • Bioengineering (5308)
  • Bioinformatics (20225)
  • Biophysics (9991)
  • Cancer Biology (7717)
  • Cell Biology (11280)
  • Clinical Trials (138)
  • Developmental Biology (6426)
  • Ecology (9930)
  • Epidemiology (2065)
  • Evolutionary Biology (13298)
  • Genetics (9354)
  • Genomics (12566)
  • Immunology (7687)
  • Microbiology (18979)
  • Molecular Biology (7428)
  • Neuroscience (40944)
  • Paleontology (300)
  • Pathology (1226)
  • Pharmacology and Toxicology (2132)
  • Physiology (3146)
  • Plant Biology (6850)
  • Scientific Communication and Education (1272)
  • Synthetic Biology (1893)
  • Systems Biology (5306)
  • Zoology (1087)