Evidence map›Paper›PMID 19531207›Full record

ArticleBMC systems biology2009

Serial evolutionary networks of within-patient HIV-1 sequences reveal patterns of evolution of X4 strains.

Patricia Buendia, Giri Narasimhan

Abstract read
In one paragraph

Article in BMC systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. The CD8Microbiology and molecular biology reviews : MMBR · 2021
    Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Patricia BuendiaDepartment of Biology and Center for Computational Science, University of Miami, Coral Gables, FL 33146, USA. pbuendia@miami.edu
Giri Narasimhan

Funding

Theaflavins and Gallic Acid in TeaS06GM008205 · NIGMS · FLORIDA INTERNATIONAL UNIVERSITY · PI BIGGER, CHARLES H · 1989 to 2008
$17.6M
MBRS RESEARCH INITIATIVE FOR SCIENTIFIC ENHANCEMENTR25GM061347 · NIGMS · FLORIDA INTERNATIONAL UNIVERSITY · PI LICKLITER, ROBERT E · 2000 to 2016
$14.7M
NIGMS NIH HHS R25 GM061347NIGMS NIH HHS R25 GM61347NIGMS NIH HHS S06 GM008205
6 · The paper itself

Abstract

backgroundThe HIV virus is known for its ability to exploit numerous genetic and evolutionary mechanisms to ensure its proliferation, among them, high replication, mutation and recombination rates. Sliding MinPD, a recently introduced computational method 1, was used to investigate the patterns of evolution of serially-sampled HIV-1 sequence data from eight patients with a special focus on the emergence of X4 strains. Unlike other phylogenetic methods, Sliding MinPD combines distance-based inference with a nonparametric bootstrap procedure and automated recombination detection to reconstruct the evolutionary history of longitudinal sequence data. We present serial evolutionary networks as a longitudinal representation of the mutational pathways of a viral population in a within-host environment. The longitudinal representation of the evolutionary networks was complemented with charts of clinical markers to facilitate correlation analysis between pertinent clinical information and the evolutionary relationships.

resultsAnalysis based on the predicted networks suggests the following:: significantly stronger recombination signals (p = 0.003) for the inferred ancestors of the X4 strains, recombination events between different lineages and recombination events between putative reservoir virus and those from a later population, an early star-like topology observed for four of the patients who died of AIDS. A significantly higher number of recombinants were predicted at sampling points that corresponded to peaks in the viral load levels (p = 0.0042).

conclusionOur results indicate that serial evolutionary networks of HIV sequences enable systematic statistical analysis of the implicit relations embedded in the topology of the structure and can greatly facilitate identification of patterns of evolution that can lead to specific hypotheses and new insights. The conclusions of applying our method to empirical HIV data support the conventional wisdom of the new generation HIV treatments, that in order to keep the virus in check, viral loads need to be suppressed to almost undetectable levels.

Indexed as

Evolution, MolecularBase SequenceDatabases, GeneticHIV-1HumansMutationPhylogenyRecombination, GeneticSystems Biology

Identifiers

PMID19531207
PMCPMC2709891

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.