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Record W2094913843 · doi:10.1086/520610

Involvement of Vacuolar Protein Sorting Pathway in Ebola Virus Release Independent of TSG101 Interaction

2007· article· en· W2094913843 on OpenAlexfundno aff
Lynn S. Silvestri, Gordon Ruthel, George Kallstrom, Kelly L. Warfield, Dana L. Swenson, T D Nelle, Patrick L. Iversen, Sina Bavari, M. Javad Aman

Bibliographic record

VenueThe Journal of Infectious Diseases · 2007
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchDefense Threat Reduction AgencyNational Institutes of HealthPublic Health AgencyNational Institute for Health and Care Research
KeywordsTSG101Ebola virusVirologyEbolavirusSortingChemistryBiologyVirusComputer scienceBiochemistryMicrovesiclesGene

Abstract

fetched live from OpenAlex

Budding of Ebola virus (EBOV) particles from the plasma membrane of infected cells requires viral and host proteins. EBOV virus matrix protein VP40 recruits TSG101, an ESCRT-1 (host cell endosomal sorting complex required for transport-1) complex protein in the vacuolar protein sorting (vps) pathway, to the plasma membrane during budding. Involvement of other vps proteins in EBOV budding has not been established. Therefore, we used VP40 deletion analysis, virus-like particle-release assays, and confocal microscopy to investigate the potential role of ESCRT-1 proteins VPS4, VPS28, and VPS37B in EBOV budding. We found that VP40 could redirect each protein from endosomes to the cell surface independently of TSG101 interaction. A lack of VPS4 adenosine triphosphatase activity reduced budding by up to 80%. Inhibition of VPS4 gene expression by use of phosphorodiamidite morpholino antisense oligonucleotides protected mice from lethal EBOV infection. These data show that EBOV can use vps proteins independently of TSG101 for budding and reveal VPS4 as a potential target for filovirus therapeutics.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.060
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.318
Teacher spread0.297 · 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 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

Citations49
Published2007
Admission routes1
Has abstractyes

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