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Record W2884102005 · doi:10.1101/375071

Transient DNA Binding Induces RNA Polymerase II Compartmentalization During Herpesviral Infection Distinct From Phase Separation

2018· preprint· en· W2884102005 on OpenAlexaff
David T. McSwiggen, Anders S. Hansen, Hervé Marie-Nelly, Sheila S. Teves, Alec Heckert, Claire Dugast‐Darzacq, Yvonne Hao, Kayla K. Umemoto, Robert Tjian, Xavier Darzacq

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPolymeraseCell biologyBiologyDNALytic cycleRNADNA replicationVirologyVirusGeneticsGene

Abstract

fetched live from OpenAlex

Summary During lytic infection, Herpes Simplex Virus 1 generates replication compartments (RCs) in host nuclei that efficiently recruit protein factors, including host RNA Polymerase II (Pol II). Pol II and other cellular factors form hubs in uninfected cells that are proposed to phase separate via multivalent protein-protein interactions mediated by their intrinsically disordered regions. Using a battery of live cell microscopic techniques, we show that although RCs superficially exhibit many characteristics of phase separation, the recruitment of Pol II instead derives from nonspecific interactions with the viral DNA. We find that the viral genome remains nucleosome-free, profoundly affecting the way Pol II explores RCs by causing it to repetitively visit nearby binding sites, thereby creating local Pol II accumulations. This mechanism, distinct from phase separation, allows viral DNA to outcompete host DNA for cellular proteins. Our work provides new insights into the strategies used to create local molecular hubs in cells.

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 score0.005

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 integrity0.0000.001
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 head0.021
GPT teacher head0.288
Teacher spread0.267 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicHerpesvirus Infections and Treatments→French-language works237,207→