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Record W1773778812 · doi:10.1128/jvi.01548-15

Differential Ability of Primary HIV-1 Nef Isolates To Downregulate HIV-1 Entry Receptors

2015· article· en· W1773778812 on OpenAlexaff
Mako Toyoda, Yoko Ogata, Macdonald Mahiti, Yosuke Maeda, Xiaomei T. Kuang, Toshiyuki Miura, Heiko Jessen, Bruce D. Walker, Mark A. Brockman, Zabrina L. Brumme, Takamasa Ueno

Bibliographic record

VenueJournal of Virology · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsAIDS VancouverSimon Fraser University
Fundersnot available
KeywordsDownregulation and upregulationBiologyCXCR4ReceptorViral replicationPhenotypeVirologyImmunologyCell biologyChemokineVirusGeneticsGene

Abstract

fetched live from OpenAlex

UNLABELLED: HIV-1 Nef downregulates the viral entry receptor CD4 as well as the coreceptors CCR5 and CXCR4 from the surface of HIV-infected cells, and this leads to promotion of viral replication through superinfection resistance and other mechanisms. Nef sequence motifs that modulate these functions have been identified via in vitro mutagenesis with laboratory HIV-1 strains. However, it remains unclear whether the same motifs contribute to Nef activity in patient-derived sequences and whether these motifs may differ in Nef sequences isolated at different infection stages and/or from patients with different disease phenotypes. Here, nef clones from 45 elite controllers (EC), 46 chronic progressors (CP), and 43 acute progressors (AP) were examined for their CD4, CCR5, and CXCR4 downregulation functions. Nef clones from EC exhibited statistically significantly impaired CD4 and CCR5 downregulation ability and modestly impaired CXCR4 downregulation activity compared to those from CP and AP. Nef's ability to downregulate CD4 and CCR5 correlated positively in all cohorts, suggesting that they are functionally linked in vivo. Moreover, impairments in Nef's receptor downregulation functions increased the susceptibility of Nef-expressing cells to HIV-1 infection. Mutagenesis studies on three functionally impaired EC Nef clones revealed that multiple residues, including those at novel sites, were involved in the alteration of Nef functions and steady-state protein levels. Specifically, polymorphisms at highly conserved tryptophan residues (e.g., Trp-57 and Trp-183) and immune escape-associated sites were responsible for reduced Nef functions in these clones. Our results suggest that the functional modulation of primary Nef sequences is mediated by complex polymorphism networks. IMPORTANCE: HIV-1 Nef, a key factor for viral pathogenesis, downregulates functionally important molecules from the surface of infected cells, including the viral entry receptor CD4 and coreceptors CCR5 and CXCR4. This activity enhances viral replication by protecting infected cells from cytotoxicity associated with superinfection and may also serve as an immune evasion strategy. However, how these activities are maintained under selective pressure in vivo remains elusive. We addressed this question by analyzing functions of primary Nef clones isolated from patients at various infection stages and with different disease phenotypes, including elite controllers, who spontaneously control HIV-1 viremia to undetectable levels. The results indicated that downregulation of HIV-1 entry receptors, particularly CCR5, is impaired in Nef clones from elite controllers. These functional impairments were driven by rare Nef polymorphisms and adaptations associated with cellular immune responses, underscoring the complex molecular pathways responsible for maintaining and attenuating viral protein function in vivo.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.255
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations33
Published2015
Admission routes1
Has abstractyes

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