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Record W4412093883 · doi:10.1038/s41564-025-02054-z

HIV-1 nuclear import is selective and depends on both capsid elasticity and nuclear pore adaptability

2025· article· en· W4412093883 on OpenAlexfundno aff
Zhen Hou, Y. Shen, Stanley Fronik, Juan Shen, Jiong Shi, Jialu Xu, Long Chen, Nathan Hardenbrook, Alan Engelman, Christopher Aiken, Peijun Zhang

Bibliographic record

VenueNature Microbiology · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesBiotechnology and Biological Sciences Research CouncilChinese Academy of Medical SciencesU.S. Department of Health and Human ServicesGovernment of CanadaWellcome TrustEuropean Molecular Biology Organization
KeywordsCapsidNuclear transportNuclear poreCell biologyBiologyHuman immunodeficiency virus (HIV)BiophysicsCell nucleusVirologyVirusNucleus

Abstract

fetched live from OpenAlex

Lentiviruses, such as HIV-1, infect non-dividing cells by traversing the nuclear pore complex (NPC); however, the detailed molecular processes remain unclear. Here we reconstituted functional HIV-1 nuclear import using permeabilized T cells and isolated HIV-1 cores, which significantly increases import events, and developed an integrated three-dimensional cryo-correlative workflow to specifically target and image 1,489 native HIV-1 cores at 4 distinct nuclear import stages using cryo-electron tomography. We found HIV-1 nuclear import depends on both capsid elasticity and nuclear pore adaptability. The NPC acts as a selective filter, preferentially importing smaller cores, while expanding and deforming to accommodate their passage. Brittle mutant cores fail to enter the NPC, while CPSF6-binding-deficient cores enter but stall within the NPC, leading to impaired nuclear import. This study uncovers the interplay between the HIV-1 core and the NPC and provides a framework to dissect HIV-1 nuclear import and downstream events, such as uncoating and integration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.004
GPT teacher head0.239
Teacher spread0.235 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations21
Published2025
Admission routes1
Has abstractyes

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