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Record W2794873645 · doi:10.1016/j.celrep.2018.02.104

A Screen for Candidate Targets of Lysine Polyphosphorylation Uncovers a Conserved Network Implicated in Ribosome Biogenesis

2018· article· en· W2794873645 on OpenAlexafffund
Amanda Bentley‐DeSousa, Charlotte Holinier, Houman Moteshareie, Yi‐Chieh Tseng, Sam Kajjo, Christine C. Nwosu, Giuseppe Amodeo, Emma Bondy‐Chorney, Yuka Sai, Adam D. Rudner, Ashkan Golshani, Norman E. Davey, Michael Downey

Bibliographic record

VenueCell Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsCarleton UniversityUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsLysineRibosome biogenesisBiogenesisTranslation (biology)BiologyRibosomeComputational biologyConserved sequenceCell biologyGeneticsGeneAmino acidRNAPeptide sequenceMessenger RNA

Abstract

fetched live from OpenAlex

Polyphosphates (polyP) are chains of inorganic phosphates found in all cells. Previous work has implicated these chains in diverse functions, but the mechanism of action is unclear. A recent study reports that polyP can be non-enzymatically and covalently attached to lysine residues on yeast proteins Nsr1 and Top1. One question emerging from this work is whether so-called "polyphosphorylation" is unique to these proteins or instead functions as a global regulator akin to other lysine post-translational modifications. Here, we present the results of a screen for polyphosphorylated proteins in yeast. We uncovered 15 targets including a conserved network of proteins functioning in ribosome biogenesis. Multiple genes contribute to polyphosphorylation of targets by regulating polyP synthesis, and disruption of this synthesis results in translation defects as measured by polysome profiling. Finally, we identify 6 human proteins that can be modified by polyP, highlighting the therapeutic potential of manipulating polyphosphorylation in vivo.

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 score0.012
Threshold uncertainty score0.500

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 head0.010
GPT teacher head0.234
Teacher spread0.225 · 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

Citations89
Published2018
Admission routes2
Has abstractyes

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