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Record W4388680633 · doi:10.1101/2023.11.14.567009

Mitotic deacetylase complex (MiDAC) recognizes the HIV-1 core promoter to control Tat-activated transcription and latency

2023· preprint· en· W4388680633 on OpenAlexafffund
Emmanuelle Wilhelm, Mikaël Poirier, Mikaël Bédard, Patrick P. McDonald, Pierre Lavigne, Christie L. Hunter, Brendan Bell

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsMinistère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des ParcsCentre Hospitalier Universitaire de SherbrookeUniversité de SherbrookeMinistère des Ressources naturelles et des Forêts
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les TechnologiesCanadian Federation of University Women
KeywordsBiologyTranscription (linguistics)Cell biologyPromoterMolecular biologyGeneGeneticsGene expression

Abstract

fetched live from OpenAlex

Abstract The human immunodeficiency virus (HIV) integrates into the host genome forming latent cellular reservoirs that are an obstacle for cure or remission strategies. Viral transcription is the first step in the control of latency and depends upon the hijacking of the host cell RNA polymerase II (Pol II) machinery by the 5’ HIV LTR. Consequently, “block and lock” or “shock and kill” strategies for an HIV cure depend upon a full understanding of HIV transcriptional control. The HIV trans-activating protein, Tat, controls HIV latency as part of a positive feed-forward loop that strongly activates HIV transcription. The recognition of the T ATA box and a djacent s equences of H IV e ssential for T at trans -activation (TASHET) of the core promoter by host cell p re-initiation c omplexes of H IV (PICH) has been shown to be necessary for Tat trans -activation, yet the protein composition of PICH has remained obscure. Here DNA-affinity chromatography was employed to identify the mitotic deacetylase complex (MiDAC) as selectively recognizing TASHET. Using biophysical techniques, we show that the MiDAC subunit DNTTIP1 binds directly to TASHET, in part via its CTGC DNA motifs. Using co-immunoprecipitation assays, we show that DNTTIP1 interacts with MiDAC subunits MIDEAS and HDAC1/2. The Tat-interacting protein, NAT10, is also present in HIV-bound MiDAC. Gene silencing revealed a functional role for DNTTIP1, MIDEAS, and NAT10 in HIV expression in cellulo . Furthermore, point mutations in TASHET that prevent DNTTIP1 binding block the reactivation of HIV by latency reversing agents (LRA) that act via the P-TEFb/7SK axis in a model of latency. Our data reveal a key role for MiDAC subunits DNTTIP1, MIDEAS, as well as NAT10, in Tat-activated HIV transcription and latency. DNTTIP1, MIDEAS and NAT10 emerge as cell cycle-regulated host cell transcription factors that can control HIV latency, and as new drug targets for HIV cure strategies. Author summary Latent HIV integrated within the host cell genome poses a major problem for viral eradication. The reactivation of latent HIV depends on host cell transcription factors that are hijacked by the 5’ long terminal repeat (LTR) region of the HIV genome to produce viral RNA. At the heart of the LTR of HIV lies a particularly crucial DNA region named the core promoter that is specifically required for the reactivation of HIV by a viral protein named Tat. A significant body of work over more than 30 years has established the specific requirement for the HIV core promoter in Tat’s control of HIV latency, but the underlying molecular mechanisms have remained elusive. Here, we identify host cell transcription factors that bind selectively to the HIV core promoter to control HIV gene expression. Our data reveal three human proteins that act in a complex to reactivate latent HIV, including one that directly recognizes the HIV core promoter, one that regulates chromatin, and a third that binds to the HIV Tat protein. Our data fill a significant and long-standing gap in the understanding of latency and identify new potential drug targets for HIV cure strategies.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.001

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 head0.041
GPT teacher head0.251
Teacher spread0.210 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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