scholarly journals Link between the numbers of particles and variants founding new HIV-1 infections depends on the timing of transmission

2018 ◽  
Author(s):  
Robin N. Thompson ◽  
Chris Wymant ◽  
Rebecca A. Spriggs ◽  
Jayna Raghwani ◽  
Christophe Fraser ◽  
...  
Keyword(s):  
Population Level ◽  
Epidemiological Data ◽  
Heterosexual Transmission ◽  
Next Generation Sequencing Data ◽  
Viral Population ◽  
Sequencing Data ◽  
Set Point ◽  
Viral Loads ◽  
Multiple Variants ◽  
Hiv 1

ABSTRACTUnderstanding which HIV-1 variants are most likely to be transmitted is important for vaccine design and predicting virus evolution. Since most infections are founded by single variants, it has been suggested that selection at transmission has a key role in governing which variants are transmitted. We show that the composition of the viral population within the donor at the time of transmission is also important. To support this argument, we developed a probabilistic model describing HIV-1 transmission in an untreated population, and parameterised the model using both within-host next generation sequencing data and population-level epidemiological data on heterosexual transmission. The most basic HIV-1 transmission models cannot explain simultaneously the low probability of transmission and the non-negligible proportion of infections founded by multiple variants. In our model, transmission can only occur when environmental conditions are appropriate (e.g. abrasions are present in the genital tract of the potential recipient), allowing these observations to be reconciled. As well as reproducing features of transmission in real populations, our model demonstrates that, contrary to expectation, there is not a simple link between the number of viral variants and the number of viral particles founding each new infection. These quantities depend on the timing of transmission, and infections can be founded with small numbers of variants yet large numbers of particles. Including selection, or a bias towards early transmission (e.g. due to treatment) acts to enhance this conclusion. In addition, we find that infections initiated by multiple variants are most likely to have derived from donors with intermediate set-point viral loads, and not from individuals with high set-point viral loads as might be expected. We therefore emphasise the importance of considering viral diversity in donors, and the timings of transmissions, when trying to discern the complex factors governing single or multiple variant transmission.

scholarly journals Schistosomiasis was not associated with higher HIV-1 plasma or genital set point viral loads among HIV seroconverters from four cohort studies

2019 ◽  
Vol 13 (11) ◽  
pp. e0007886 ◽  
Author(s):  
Aaron F. Bochner ◽  
W. Evan Secor ◽  
Jared M. Baeten ◽  
Govert J. van Dam ◽  
Adam A. Szpiro ◽  
...  
Keyword(s):  
Cohort Studies ◽  
Set Point ◽  
Viral Loads ◽  
Hiv 1

scholarly journals Algorithmic methods to infer the evolutionary trajectories in cancer progression

2016 ◽  
Vol 113 (28) ◽  
pp. E4025-E4034 ◽  
Author(s):  
Giulio Caravagna ◽  
Alex Graudenzi ◽  
Daniele Ramazzotti ◽  
Rebeca Sanz-Pamplona ◽  
Luca De Sano ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Current Knowledge ◽  
Population Level ◽  
Selective Advantage ◽  
Explanatory Models ◽  
Next Generation Sequencing Data ◽  
Driver Mutations ◽  
Sequencing Data ◽  
Cross Sectional ◽  
Progression Model

The genomic evolution inherent to cancer relates directly to a renewed focus on the voluminous next-generation sequencing data and machine learning for the inference of explanatory models of how the (epi)genomic events are choreographed in cancer initiation and development. However, despite the increasing availability of multiple additional -omics data, this quest has been frustrated by various theoretical and technical hurdles, mostly stemming from the dramatic heterogeneity of the disease. In this paper, we build on our recent work on the “selective advantage” relation among driver mutations in cancer progression and investigate its applicability to the modeling problem at the population level. Here, we introduce PiCnIc (Pipeline for Cancer Inference), a versatile, modular, and customizable pipeline to extract ensemble-level progression models from cross-sectional sequenced cancer genomes. The pipeline has many translational implications because it combines state-of-the-art techniques for sample stratification, driver selection, identification of fitness-equivalent exclusive alterations, and progression model inference. We demonstrate PiCnIc’s ability to reproduce much of the current knowledge on colorectal cancer progression as well as to suggest novel experimentally verifiable hypotheses.

scholarly journals Behaviour change and competitive exclusion can explain the diverging HIV-1 and HIV-2 prevalence trends in Guinea–Bissau

2007 ◽  
Vol 136 (4) ◽  
pp. 551-561 ◽  
Author(s):  
W. P. SCHMIDT ◽  
M. SCHIM VAN DER LOEFF ◽  
P. AABY ◽  
H. WHITTLE ◽  
R. BAKKER ◽  
...  
Keyword(s):  
Competitive Exclusion ◽  
Risk Behaviour ◽  
Epidemiological Data ◽  
Heterosexual Transmission ◽  
Sexual Risk Behaviour ◽  
Sexually Transmitted ◽  
Guinea Bissau ◽  
Prevalence Trends ◽  
Temporary Rise ◽  
Hiv 1

SUMMARYThe aim of this study was to determine whether a temporary rise in sexual risk behaviour during war in Guinea–Bissau could explain the observed trends in HIV-1 and HIV-2 prevalence, and to explore the possible contribution of competitive elimination of HIV-2 by HIV-1. A simulation model of the heterosexual transmission of sexually transmitted infections was parameterized using demographic, behavioural and epidemiological data from rural Guinea–Bissau, and fitted to the observed HIV-1 and HIV-2 trends with and without a historic rise in risk behaviour. The observed trends could only be simulated by assuming a temporary rise in risk behaviour. Around 30% of the projected decline in HIV-2 prevalence from a peak of 8·7% to 4·3% in 2010 was due to competitive elimination by HIV-1. Importantly for public health, HIV-1 prevalence was predicted to continue increasing and to become the dominant HIV type by 2010. Data collection is required to validate this prediction.

Rising HIV-1 viral load set point at a population level coincides with a fading impact of host genetic factors on HIV-1 control

AIDS ◽  
2011 ◽  
Vol 25 (18) ◽  
pp. 2217-2226 ◽  
Author(s):  
Daniëlle van Manen ◽  
Luuk Gras ◽  
Brigitte D. Boeser-Nunnink ◽  
Ard I. van Sighem ◽  
Irma Maurer ◽  
...  
Keyword(s):  
Viral Load ◽  
Genetic Factors ◽  
Population Level ◽  
Set Point ◽  
Host Genetic ◽  
Viral Load Set Point ◽  
Hiv 1 ◽  
Host Genetic Factors

scholarly journals Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant

2021 ◽  
Author(s):  
Jing Lu ◽  
Baisheng Li ◽  
Aiping Deng ◽  
Kuibiao Li ◽  
Yao Hu ◽  
...  
Keyword(s):  
Mainland China ◽  
Population Level ◽  
Epidemiological Data ◽  
Single Nucleotide Variants ◽  
Symptomatic Infection ◽  
Single Nucleotide ◽  
Viral Loads ◽  
Rapid Spread ◽  
B Lineage ◽  
Local Transmission

Abstract We report the first local transmission of the SARS-CoV-2 Delta variant in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of the quarantined subjects indicated that the viral loads of Delta infections, when they first become PCR+, were on average ~1000 times greater compared to A/B lineage infections during initial epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. We performed high-quality sequencing on samples from 126 individuals. Reliable epidemiological data meant that, for 111 transmission events, the donor and recipient cases were known. The estimated transmission bottleneck size was 1-3 virions with most minor intra-host single nucleotide variants (iSNVs) failing to transmit to the recipients. However, transmission heterogeneity of SARS-CoV-2 was also observed. The transmission of minor iSNVs resulted in at least 4 of the 30 substitutions identified in the outbreak, highlighting the contribution of intra-host variants to population level viral diversity during rapid spread. Disease control activities, such as the frequency of population testing, quarantine during pre-symptomatic infection, and level of virus genomic surveillance should be adjusted in order to account for the increasing prevalence of the Delta variant worldwide.

scholarly journals Bimodal distribution and set point HBV DNA viral loads in chronic infection: retrospective analysis of cohorts from the UK and South Africa

2020 ◽  
Vol 5 ◽  
pp. 113
Author(s):  
Louise O. Downs ◽  
Sabeehah Vawda ◽  
Phillip Armand Bester ◽  
Katrina A. Lythgoe ◽  
Tingyan Wang ◽  
...  
Keyword(s):  
South Africa ◽  
Large Population ◽  
Population Level ◽  
Bimodal Distribution ◽  
Skewed Distribution ◽  
Stable Set ◽  
Cross Sectional ◽  
Set Point ◽  
Viral Loads ◽  
The Uk

Hepatitis B virus (HBV) viral load (VL) is used as a biomarker to assess risk of disease progression, and to determine eligibility for treatment. While there is a well recognised association between VL and the expression of the viral e-antigen protein, the distributions of VL at a population level are not well described. We here present cross-sectional, observational HBV VL data from two large population cohorts in the UK and in South Africa, demonstrating a consistent bimodal distribution. The right skewed distribution and low median viral loads are different from the left-skew and higher viraemia in seen in HIV and hepatitis C virus (HCV) cohorts in the same settings. Using longitudinal data, we present evidence for a stable ‘set-point’ VL in peripheral blood during chronic HBV infection. These results are important to underpin improved understanding of HBV biology, to inform approaches to viral sequencing, and to plan public health interventions.

scholarly journals Sanger and Next-Generation Sequencing data for characterization of CTL epitopes in archived HIV-1 proviral DNA

PLoS ONE ◽  
2017 ◽  
Vol 12 (9) ◽  
pp. e0185211 ◽  
Author(s):  
Camille Tumiotto ◽  
Lionel Riviere ◽  
Pantxika Bellecave ◽  
Patricia Recordon-Pinson ◽  
Alice Vilain-Parce ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Ctl Epitopes ◽  
Proviral Dna ◽  
Generation Sequencing ◽  
Hiv 1

scholarly journals A transmission-virulence evolutionary trade-off explains attenuation of HIV-1 in Uganda

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
François Blanquart ◽  
Mary Kate Grabowski ◽  
Joshua Herbeck ◽  
Fred Nalugoda ◽  
David Serwadda ◽  
...  
Keyword(s):  
Evolutionary Model ◽  
Asymptomatic Infection ◽  
Trade Off ◽  
Set Point ◽  
Viral Loads ◽  
Pathogen Fitness ◽  
Using Data ◽  
Subtype A ◽  
Hiv 1 ◽  
Timely Treatment

Evolutionary theory hypothesizes that intermediate virulence maximizes pathogen fitness as a result of a trade-off between virulence and transmission, but empirical evidence remains scarce. We bridge this gap using data from a large and long-standing HIV-1 prospective cohort, in Uganda. We use an epidemiological-evolutionary model parameterised with this data to derive evolutionary predictions based on analysis and detailed individual-based simulations. We robustly predict stabilising selection towards a low level of virulence, and rapid attenuation of the virus. Accordingly, set-point viral load, the most common measure of virulence, has declined in the last 20 years. Our model also predicts that subtype A is slowly outcompeting subtype D, with both subtypes becoming less virulent, as observed in the data. Reduction of set-point viral loads should have resulted in a 20% reduction in incidence, and a three years extension of untreated asymptomatic infection, increasing opportunities for timely treatment of infected individuals.

scholarly journals Full-Length Envelope Analyzer (FLEA): A tool for longitudinal analysis of viral amplicons

2017 ◽  
Author(s):  
Kemal Eren ◽  
Steven Weaver ◽  
Robert Ketteringham ◽  
Morné Valentyn ◽  
Melissa Laird Smith ◽  
...  
Keyword(s):  
Web Application ◽  
Evolutionary Dynamics ◽  
Full Length ◽  
Viral Population ◽  
Sequencing Data ◽  
Link Type ◽  
Long Read ◽  
Web App ◽  
Client Side ◽  
Hiv 1

AbstractNext generation sequencing of viral populations has advanced our understanding of viral population dynamics, the development of drug resistance, and escape from host immune responses. Many applications require complete gene sequences, which can be impossible to reconstruct from short reads. HIV-1 env, the protein of interest for HIV vaccine studies, is exceptionally challenging for long-read sequencing and analysis due to its length, high substitution rate, and extensive indel variation. While long-read sequencing is attractive in this setting, the analysis of such data is not well handled by existing methods. To address this, we introduce FLEA (Full-Length Envelope Analyzer), which performs end-to-end analysis and visualization of long-read sequencing data.FLEA consists of both a pipeline (optionally run on a high-performance cluster), and a client-side web application that provides interactive results. The pipeline transforms FASTQ reads into high-quality consensus sequences (HQCSs) and uses them to build a codon-aware multiple sequence alignment. The resulting alignment is then used to infer phylogenies, selection pressure, and evolutionary dynamics. The web application provides publication-quality plots and interactive visualizations, including an annotated viral alignment browser, time series plots of evolutionary dynamics, visualizations of gene-wide selective pressures (such as dN /dS) across time and across protein structure, and a phylogenetic tree browser.We demonstrate how FLEA may be used to process Pacific Biosciences HIV-1 env data and describe recent examples of its use. Simulations show how FLEA dramatically reduces the error rate of this sequencing platform, providing an accurate portrait of complex and variable HIV-1 env populations.A public instance of FLEA is hosted at http://flea.datamonkey.org. The Python source code for the FLEA pipeline can be found at https://github.com/veg/flea-pipeline. The client-side application is available at https://github.com/veg/flea-web-app. A live demo of the P018 results can be found at http://flea.murrell.group/view/P018.

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