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Record W2027961368 · doi:10.1021/ac010583a

Fractionation of Isotopically Labeled Peptides in Quantitative Proteomics

2001· article· en· W2027961368 on OpenAlexfundno aff
Roujian Zhang, Cathy Sioma, Shihong Wang, Fred E. Regnier

Bibliographic record

VenueAnalytical Chemistry · 2001
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Institutes of HealthCanadian Institute for Theoretical AstrophysicsPurdue University
KeywordsChemistryDerivatizationPeptideChromatographyResolution (logic)DeuteriumFractionationIsobaric labelingQuantitative proteomicsIsotopeReversed-phase chromatographyStable isotope ratioReagentProteomicsHigh-performance liquid chromatographyMass spectrometryTandem mass spectrometryBiochemistryOrganic chemistryProtein mass spectrometry

Abstract

fetched live from OpenAlex

The goal of quantitative proteomics is to examine the expression levels of all of the proteins in a biological system and recognize those that change as a function of some stimulus. Quantification is now frequently based on derivatization of peptides with isotopically distinguishable labeling agents. This study examines the extent to which isotopic forms of peptides having the same amino acid sequence are resolved by reversed-phase chromatography and assesses the degree to which resolution of these isotopically different forms of a peptide impact quantification. Three derivatizing agents were examined, the do and d3 forms of N-acetoxysuccinimide, the do and d4 forms of succinic anhydride, and the do and d8 forms of the commercial ICAT reagent Peptide mixtures from control and experimental samples were derivatized individually, mixed, subjected to reversed-phase chromatography, and analyzed by ESI-MS. When partial resolution of the isotopic forms of a peptide occurs, the largest error in assessing the true isotope ratio in a sample occurs when sampling at the extremes of a peak. Early in the elution of a peak, the sample will be enriched in the deuterated species, whereas the opposite is true at the tailing edge of a peak. Acetylated peptides showed the lowest degree of separation. Resolution of the deuterated and nondeuterated forms in this case was 0.023. This amounts to slightly over a 1-s difference in their peak maxima and can cause a typical error of +/- 6% at the leading and tailing edges of a peak. In contrast, resolution of the deuterated and nondeuterated forms of the ICAT reagent were calculated to be 0.45. This means that in a peak of 1-min width (W1/2), the peak maxima will vary by approximately 30 s, and measurement errors of -83 and +500% can occur at the leading and tailing edges of a peak. It is concluded that resolution of isotopic forms of a peptide can cause substantial quantification errors in quantitative proteomics.

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)0.006
metaresearch head score (Gemma)0.004
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: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.315
Teacher spread0.295 · 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
GenreMethods

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

Citations233
Published2001
Admission routes1
Has abstractyes

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