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Record W2945366030 · doi:10.1128/mbio.00826-19

Comparative Loss-of-Function Screens Reveal ABCE1 as an Essential Cellular Host Factor for Efficient Translation of <i>Paramyxoviridae</i> and <i>Pneumoviridae</i>

2019· article· en· W2945366030 on OpenAlexafffund
Danielle E. Anderson, Kristin Pfeffermann, So Young Kim, Bevan Sawatsky, James L. Pearson, Mikhail Kovtun, David L. Corcoran, Yvonne Krebs, Kristmundur Sigmundsson, Sharon F. Jamison, Zhen Zhen Joanna Yeo, Linda J. Rennick, Lin‐Fa Wang, Pierre J. Talbot, W. Paul Duprex, Mariano A. García-Blanco, Veronika von Messling

Bibliographic record

VenuemBio · 2019
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsArmand Frappier MuseumInstitut National de la Recherche Scientifique
FundersNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchIndependent Electricity System OperatorNational Medical Research CouncilCanada Foundation for InnovationDeutsches Zentrum für InfektionsforschungWashington State Department of Natural ResourcesUniversity of Washington
KeywordsTranslation (biology)Host (biology)Function (biology)VirologyBiologyCell biologyMessenger RNAGeneBiochemistryGenetics

Abstract

fetched live from OpenAlex

families include important human and animal pathogens. To identify common host factors, we performed genome-scale siRNA screens with wild-type-derived measles, mumps, and respiratory syncytial viruses in the same cell line. A comparative bioinformatics analysis yielded different members of the coatomer complex I, translation factors ABCE1 and eIF3A, and several RNA binding proteins as cellular proteins with proviral activity for all three viruses. A more detailed characterization of ABCE1 revealed its essential role for viral protein synthesis. Taken together, these data sets provide new insight into the interactions between paramyxoviruses and pneumoviruses and host cell proteins and constitute a starting point for the development of broadly effective antivirals.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.655

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 studies0.0000.000
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 head0.047
GPT teacher head0.349
Teacher spread0.302 · 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

Citations33
Published2019
Admission routes2
Has abstractyes

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