ArticleBMC infectious diseases2015
Impact of naturally occurring amino acid variations on the detection of HIV-1 p24 in diagnostic antigen tests.
Article in BMC infectious diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- Tools to Quantify and Characterize the Persistent Reservoir in People with HIV-1: Focus on Non-B Subtypes.Viruses · 2026Review
- Nanomechanical systems for the rapid detection of HIV-1 p24 antigen.Biosensors & bioelectronics · 2025Article
- QuickFit: A High-Throughput RT-qPCR-Based Assay to Quantify Viral Growth and Fitness In Vitro.Viruses · 2024Article
- In-house ELISA protocols for capsid p24 detection of diverse HIV isolates.Virology journal · 2023Article
- Halo Library, a Tool for Rapid Identification of Ligand Binding Sites on Proteins Using Crystallographic Fragment Screening.Journal of medicinal chemistry · 2023Article
- HIV Capsid Protein Genetic Diversity Across HIV-1 Variants and Impact on New Capsid-Inhibitor Lenacapavir.Frontiers in microbiology · 2022Article
- Computational Design of Epitope-Enriched HIV-1 Gag Antigens with Preserved Structure and Function for Induction of Broad CD8Scientific reports · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe detection of HIV-1 p24 antigen in diagnostic tests relies on antibodies binding to conserved areas of the protein to cover the full range of HIV-1 subtypes. Using a panel of 43 different virus-like particles (VLPs) expressing Gag from clinical HIV-1 isolates, we previously found that some highly sensitive tests completely failed to detect p24 of certain VLPs, seemingly unrelated to their subtype. Here we aimed to investigate the reason for this failure, hypothesising that it might be due to single amino acid variations in conserved epitopes.
methodsUsing amino acid alignment, we identified single amino acid variations at position 16 or 170 of p24, unique to those VLPs that failed to be detected in certain diagnostic tests. Through DNA-mutagenesis, these amino acids were changed to ones more commonly found at these positions. The impact of these changes on p24 detection was tested in commercial diagnostic tests as well as by Western Blot and ELISA, using epitope-specific antibodies. RESULTS AND
conclusionsChanging positions 16 or 170 to consensus amino acids restored the detection of p24 by the investigated diagnostic tests as well as by epitope-specific antibodies in Western Blot and ELISA. Hence, single amino acid changes in conserved epitopes can lead to the failure of p24 detection and thus to false-negative results. To optimise HIV diagnostic tests, they should also be evaluated using isolates which harbour less-frequent epitope variants.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.