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Record W2333593079 · doi:10.1021/pr400198e

Displacement of N/Q-rich Peptides on TiO<sub>2</sub>Beads Enhances the Depth and Coverage of Yeast Phosphoproteome Analyses

2013· article· en· W2333593079 on OpenAlexafffund
Evgeny Kanshin, Stephen W. Michnick, Pierre Thibault

Bibliographic record

VenueJournal of Proteome Research · 2013
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersCanadian Institutes of Health Research
KeywordsPhosphoproteomicsPhosphorylationPhosphopeptideYeastChemistryStable isotope labeling by amino acids in cell cultureAsparaginePeptideBiochemistryAmino acidProtein phosphorylationProteomicsChromatographyProtein kinase A

Abstract

fetched live from OpenAlex

Phosphorylation is a reversible protein modification that regulates major cellular processes such as cell division, growth, and differentiation through highly dynamic and complex signaling pathways. Large-scale phosphoproteomics analyses have been greatly facilitated using affinity chromatography such as metal oxide affinity chromatography (e.g., TiO2), which in combination with mass spectrometry has enabled unbiased detection and quantification of thousands of phosphorylation sites in a single experiment. However, global phosphoproteome analyses do not provide comparable enrichment yields for different model organisms. While the proportion of phosphopeptides exceed 90% in mammalian cells using TiO2, similar levels have been notoriously difficult to achieve for yeast or dictylostelium cells. In a systematic study of TiO2 using cell extracts from different organisms, we determined that phosphopeptides are coenriched with peptides containing repetitive stretches of glutamine and asparagine residues. The proportion of these nonspecific binders can reach up to 50% in cell extracts from budding yeast and thus limit the depth and comprehensiveness of phosphoproteomics analyses. To address this limitation, we developed an effective method that used decoy amino acids to reduce the extent of nonspecific peptide binding and improve the recovery and detection of low abundance phosphopeptides that remained undetected by conventional TiO2 enrichment protocols.

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)0.001
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 score0.006
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.058
GPT teacher head0.389
Teacher spread0.331 · 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

Citations29
Published2013
Admission routes2
Has abstractyes

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