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Record W4391738645 · doi:10.1038/s42003-024-05840-3

Genomic attributes of airway commensal bacteria and mucosa

2024· article· en· W4391738645 on OpenAlexaff
Leah Cuthbertson, Ulrike Löber, Jonathan Ish-Horowicz, Claire McBrien, Colin Churchward, Jeremy C. Parker, Michael Olanipekun, Conor M. Burke, Aisling McGowan, Gwyneth A. Davies, Keir Lewis, Julian M. Hopkin, Kian Fan Chung, Orla O’Carroll, John L. Faul, Joy Creaser-Thomas, Mark Andrews, Robin Ghosal, Stefan Piatek, Saffron A.G. Willis‐Owen, Theda Ulrike Patricia Bartolomaeus, Till Birkner, Sarah Dwyer, Nitin Kumar, Elena Turek, A W Musk, Jennie Hui, Michael Hunter, Marc‐Emmanuel Dumas, Sarah Filippi, Michael J. Cox, Trevor D. Lawley, Sofia K. Forslund, Miriam F. Moffatt, William Cookson

Bibliographic record

VenueCommunications Biology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMcGill UniversityMcGill Genome Centre
FundersOffice of ScienceGovernment of Western AustraliaDeutsche ForschungsgemeinschaftJoint Programming Initiative on Antimicrobial ResistanceWellcome TrustOffice of Science, Government of Western AustraliaWellcome
KeywordsBiologyCommensalismMicrobiomeImmune systemGenomeImmunologyMicrobiologyBacteriaGenePathogenAirwayBiofilmImmunityMetagenomicsGeneticsMedicine

Abstract

fetched live from OpenAlex

Microbial communities at the airway mucosal barrier are conserved and highly ordered, in likelihood reflecting co-evolution with human host factors. Freed of selection to digest nutrients, the airway microbiome underpins cognate management of mucosal immunity and pathogen resistance. We show here the initial results of systematic culture and whole-genome sequencing of the thoracic airway bacteria, identifying 52 novel species amongst 126 organisms that constitute 75% of commensals typically present in heathy individuals. Clinically relevant genes encode antimicrobial synthesis, adhesion and biofilm formation, immune modulation, iron utilisation, nitrous oxide (NO) metabolism and sphingolipid signalling. Using whole-genome content we identify dysbiotic features that may influence asthma and chronic obstructive pulmonary disease. We match isolate gene content to transcripts and metabolites expressed late in airway epithelial differentiation, identifying pathways to sustain host interactions with microbiota. Our results provide a systematic basis for decrypting interactions between commensals, pathogens, and mucosa in lung diseases of global significance.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.317
Teacher spread0.288 · 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 designObservational
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

Citations8
Published2024
Admission routes1
Has abstractyes

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