Evidence map›Paper›PMID 37832752›Full record

ArticleInfection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases2023

HIV-1 subtypes maintain distinctive physicochemical signatures in Nef domains associated with immunoregulation.

Susanna L Lamers, Gary B Fogel, Enoch S Liu, David J Nolan, Rebecca Rose, Michael S McGrath

Open access · goldAbstract read
In one paragraph

Article in Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 39% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 3 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Susanna L LamersBioInfoExperts , Thibodaux, Louisiana, USA. Electronic address: susanna@bioinfox.com.
Gary B FogelNatural Selection, San Diego, California, USA.
Enoch S LiuNatural Selection, San Diego, California, USA.
David J NolanBioInfoExperts , Thibodaux, Louisiana, USA.
Rebecca RoseBioInfoExperts , Thibodaux, Louisiana, USA.
Michael S McGrathUniversity of California, San Francisco, California, USA.
Natural Selection (United States) · USNicholls State University · USUniversity of California, San Francisco · US

Funding

Pathogenesis of the cART unresponsive Kaposi’s sarcoma tumor nicheR01CA239263 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MCGRATH, MICHAEL SHANNON · 2019 to 2023
$2.8M
NCI NIH HHS R01 CA239263
6 · The paper itself

Abstract

backgroundHIV subtype is associated with varied rates of disease progression. The HIV accessory protein, Nef, continues to be present during antiretroviral therapy (ART) where it has numerous immunoregulatory effects. In this study, we analyzed Nef sequences from HIV subtypes A1, B, C, and D using a machine learning approach that integrates functional amino acid information to identify if unique physicochemical features are associated with Nef functional/structural domains in a subtype-specific manner.

methods2253 sequences representing subtypes A1, B, C, and D were aligned and domains with known functional properties were scored based on amino acid physicochemical properties. Following feature generation, we used statistical pruning and evolved neural networks (ENNs) to determine if we could successfully classify subtypes. Next, we used ENNs to identify the top five key Nef physicochemical features applied to specific immunoregulatory domains that differentiated subtypes. A signature pattern analysis was performed to the assess amino acid diversity in sub-domains that differentiated each subtype.

resultsIn validation studies, ENNs successfully differentiated each subtype at A1 (87.2%), subtype B (89.5%), subtype C (91.7%), and subtype D (85.1%). Our feature-based domain scoring, followed by t-tests, and a similar ENN identified subtype-specific domain-associated features. Subtype A1 was associated with alterations in Nef CD4 binding domain; subtype B was associated with alterations with the AP-2 Binding domain; subtype C was associated with alterations in a structural Alpha Helix domain; and, subtype D was associated with alterations in a Beta-Sheet domain.

conclusionsRecent studies have focused on HIV Nef as a driver of immunoregulatory disease in those HIV infected and on ART. Nef acts through a complex mixture of interactions that are directly linked to the key features of the subtype-specific domains we identified with the ENN. The study supports the hypothesis that varied Nef subtypes contribute to subtype-specific disease progression.

Indexed as

HIV-1HIV InfectionsAmino AcidsAmino Acid SequenceDisease ProgressionHumansnef Gene Products, Human Immunodeficiency VirusAmino Acidsnef Gene Products, Human Immunodeficiency VirusBioinformaticsHIVHIV subtypesMachine-learningNef proteinSequence analysis

Identifiers

PMID37832752
PMCPMC10842591
OpenAlexW4387520826

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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 Socratic graph.