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Record W2795358647 · doi:10.1038/s41467-018-03387-6

A licensing step links AID to transcription elongation for mutagenesis in B cells

2018· article· en· W2795358647 on OpenAlexafffund
Stephen P. Methot, Ludivine C. Litzler, Poorani Ganesh Subramani, Anil K. Eranki, Heather Fifield, Anne‐Marie Patenaude, Julian C. Gilmore, Gabriel E. Santiago, Halil Bagci, Jean‐François Côté, Mani Larijani, Ramiro E. Verdún, Javier M. Di Noia

Bibliographic record

VenueNature Communications · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsBombardier (Canada)Memorial University of NewfoundlandMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
FundersNational Institute of General Medical SciencesCanadian Institutes of Health ResearchCancer Research Society
KeywordsSomatic hypermutationMutagenesisImmunoglobulin class switchingMutantBiologyGeneCytidine deaminaseGeneticsTranscription factorTranscription (linguistics)AntibodyB cell

Abstract

fetched live from OpenAlex

Activation-induced deaminase (AID) mutates the immunoglobulin (Ig) genes to initiate somatic hypermutation (SHM) and class switch recombination (CSR) in B cells, thus underpinning antibody responses. AID mutates a few hundred other loci, but most AID-occupied genes are spared. The mechanisms underlying productive deamination versus non-productive AID targeting are unclear. Here we show that three clustered arginine residues define a functional AID domain required for SHM, CSR, and off-target activity in B cells without affecting AID deaminase activity or Escherichia coli mutagenesis. Both wt AID and mutants with single amino acid replacements in this domain broadly associate with Spt5 and chromatin and occupy the promoter of AID target genes. However, mutant AID fails to occupy the corresponding gene bodies and loses association with transcription elongation factors. Thus AID mutagenic activity is determined not by locus occupancy but by a licensing mechanism, which couples AID to transcription elongation.

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 score0.479
Threshold uncertainty score0.830

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 science0.0010.000
Research integrity0.0010.001
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 head0.022
GPT teacher head0.282
Teacher spread0.261 · 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

Citations55
Published2018
Admission routes2
Has abstractyes

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