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Record W4388895414 · doi:10.1073/pnas.2314043120

Proteome-wide tagging with an H <sub>2</sub> O <sub>2</sub> biosensor reveals highly localized and dynamic redox microenvironments

2023· article· en· W4388895414 on OpenAlexfundno aff
Paraskevi Kritsiligkou, Katharina Bosch, Tzu Keng Shen, Matthias Meurer, Michael Knop, Tobias P. Dick

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRedox biology and oxidative stress
Canadian institutionsnot available
FundersStem Cell NetworkEuropean CommissionDeutsches Krebsforschungszentrum
KeywordsProteomeRedoxBiosensorComputational biologyChemistryNanotechnologyBiologyBiochemistryMaterials scienceInorganic chemistry

Abstract

fetched live from OpenAlex

Hydrogen peroxide (H 2 O 2 ) sensing and signaling involves the reversible oxidation of particular thiols on particular proteins to modulate protein function in a dynamic manner. H 2 O 2 can be generated from various intracellular sources, but their identities and relative contributions are often unknown. To identify endogenous “hotspots” of H 2 O 2 generation on the scale of individual proteins and protein complexes, we generated a yeast library in which the H 2 O 2 sensor HyPer7 was fused to the C-terminus of all protein-coding open reading frames (ORFs). We also generated a control library in which a redox-insensitive mutant of HyPer7 (SypHer7) was fused to all ORFs. Both libraries were screened side-by-side to identify proteins located within H 2 O 2 -generating environments. Screening under a variety of different metabolic conditions revealed dynamic changes in H 2 O 2 availability highly specific to individual proteins and protein complexes. These findings suggest that intracellular H 2 O 2 generation is much more localized and functionally differentiated than previously recognized.

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 score0.083
Threshold uncertainty score0.567

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 studies0.0000.002
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 head0.013
GPT teacher head0.263
Teacher spread0.250 · 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

Citations43
Published2023
Admission routes1
Has abstractyes

Explore more

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