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Primary publications, RESULTS

Viral load heritability

Our ability to answer the main question of BEEHIVE is partly determined by the heritability of viral load: the extent to which variation in viral load is explained the virus’ genetic sequence. In this analysis François Blanquart and colleagues determine the heritability in the BEEHIVE data to about one third: Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe.

Tat diversity

For the production of viral genomic RNA, HIV-1 depends on the early viral protein Tat for the production of new viral genomic RNA. Differencies in the efficiency of different Tat variants could be a factor in why viral load varies dramatically between HIV patients. VIral load and therefore virulence has increased in the Netherlands and elsewhere over the past 30 years, however, Antoinette van der Kuyl and colleagues find that this is not due to the action of different Tat variants: The evolution of subtype B HIV-1 tat in the Netherlands during 1985–2012.

Viral load evolution

We found phylogenetic evidence of evolutionary selection pressure acting against those HIV viruses that cause lower viral loads. We saw that individuals with intermediate or high viral loads tended to have viruses that were more closely related to viruses from other individuals, indicating less viral evolution and so less time passing between one infection and the next, i.e. greater infectiousness. This study was published here.

Virulent Variant

We discovered a highly virulent variant of HIV circulating in the Netherlands. Read more in the next tab of the website, focussing on this finding.

Primary publications, METHODS

Sequence alignment with Shiver

Sequencing experiments produce data that is not easy to interpret: a large number of genetic sequence fragments (‘reads’) from the virus, which due to mutation are usually different from viruses that have been previously observed. Chris Wymant and colleagues wrote the computational method shiver to make sense of these reads, by accurately aligning them and finding what mutations are present: Easy and Accurate Reconstruction of Whole HIV Genomes from Short-Read Sequence Data. The software can be found here.

Exploring within-host viral diversity with Phyloscanner

As the HIV virus rapidly mutates and infections are chronic, one individual eventually has many different viruses. We wrote the computational method phyloscanner to allow investigation of the diversity within individuals and between individuals at the same time; this gives us a better understanding of patterns of transmission, and the presence of two different viruses in the same person: PHYLOSCANNER: Inferring Transmission from Within- and Between-Host Pathogen Genetic Diversity. The software can be found here.

RNA processing

RNA quality and quantity are important factors influencing the quality of HIV sequences. Marion Cornelissen and colleagues investigated the optimal method for isolation of HIV-1 viral RNA for long amplicon genome sequencing. Manual isolation with the QIAamp Viral RNA Mini Kit (Qiagen) was superior to robotically extracted RNA: From clinical sample to complete genome: Comparing methods for the extraction of HIV-1 RNA for high-throughput deep sequencing.

Related publications

In these articles, Christophe Fraser and colleagues established the motivation for the BEEHIVE project by presenting evidence that the HIV virus has evolved to have viral loads that are favourable to onward transmission, and determining through meta-analysis that the virus sequence is indeed important for determining viral load:

Variation in HIV-1 set-point viral load: Epidemiological analysis and an evolutionary hypothesis

Virulence and Pathogenesis of HIV-1 Infection: An Evolutionary Perspective

This article describes the methods that were used to prepare the serum and plasma samples for sequencing:

Workup of Human Blood Samples for Deep Sequencing of HIV-1 Genomes

These articles describe the sequencing protocol used for BEEHIVE:

Universal Amplification, Next-Generation Sequencing, and Assembly of HIV-1 Genomes

Complete Genome Sequence of the WHO International Standard for HIV-1 RNA Determined by Deep Sequencing

This article explores how the large differences in set-point viral load between patients can be described by mathematical models and how the presence of latent reservoirs can influence the evolution of the virus:

Large Variations in HIV-1 Viral Load Explained by Shifting-Mosaic Metapopulation Dynamics

Effect of the Latent Reservoir on the Evolution of HIV at the Within- and Between-Host Levels