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Record W4205585898 · doi:10.3410/f.735953986.793564262

Faculty Opinions recommendation of An enzymatic pathway in the human gut microbiome that converts A to universal O type blood.

2019· dataset· en· W4205585898 on OpenAlexaboutno aff
Vincent Cattoir

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2019
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsnot available
Fundersnot available
KeywordsEnzymeBlood type (non-human)MetagenomicsAntigenMicrobiomeBiologyBiochemistryMicrobiologyChemistryComputational biologyGeneGeneticsABO blood group system

Abstract

fetched live from OpenAlex

Access to efficient enzymes that can convert A and B type red blood cells to 'universal' donor O would greatly increase the supply of blood for transfusions. Here we report the functional metagenomic screening of the human gut microbiome for enzymes that can remove the cognate A and B type sugar antigens. Among the genes encoded in our library of 19,500 expressed fosmids bearing gut bacterial DNA, we identify an enzyme pair from the obligate anaerobe Flavonifractor plautii that work in concert to efficiently convert the A antigen to the H antigen of O type blood, via a galactosamine intermediate. The X-ray structure of the N-acetylgalactosamine deacetylase reveals the active site and mechanism of the founding member of an esterase family. The galactosaminidase expands activities within the CAZy family GH36. Their ability to completely convert A to O of the same rhesus type at very low enzyme concentrations in whole blood will simplify their incorporation into blood transfusion practice, broadening blood supply. PMID: 31182795 Funding information This work was supported by: NIGMS NIH HHS, United States Grant ID: R24 GM098791 CIHR, Canada Grant ID: MOP-136940

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.094
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.008
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0940.067

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 head0.039
GPT teacher head0.362
Teacher spread0.323 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2019
Admission routes1
Has abstractyes

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