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Record W2901345918 · doi:10.1101/471110

Acquired interbacterial defense systems protect against interspecies antagonism in the human gut microbiome

2018· preprint· en· W2901345918 on OpenAlexfundno aff
Benjamin D. Ross, Adrian J. Verster, Matthew C. Radey, Danica T. Schmidtke, Christopher E. Pope, Lucas R. Hoffman, Adeline M. Hajjar, S. Brook Peterson, Elhanan Borenstein, Joseph D. Mougous

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsnot available
FundersNational Institutes of HealthNatural Sciences and Engineering Research Council of CanadaLife Sciences Research FoundationBurroughs Wellcome Fund
KeywordsBiologyMicrobiomeAntagonismGeneGenomeHuman microbiomeComputational biologyGeneticsToxinMicrobiologyReceptor

Abstract

fetched live from OpenAlex

Abstract The impact of direct interactions between co-resident microbes on microbiome composition is not well understood. Here we report the occurrence of acquired interbacterial defense (AID) gene clusters in bacterial residents of the human gut microbiome. These clusters encode arrays of immunity genes that protect against type VI secretion toxin-mediated intra- and inter-species bacterial antagonism. Moreover, the clusters reside on mobile elements and we demonstrate that their transfer is sufficient to confer toxin resistance in vitro and in gnotobiotic mice. Finally, we identify and validate the protective capacity of a recombinase-associated AID subtype ( r AID-1) present broadly in Bacteroidales genomes. These r AID-1 gene clusters have a structure suggestive of active gene acquisition and include predicted immunity factors of toxins deriving from diverse organisms. Our data suggest that neutralization of contact-dependent interbacterial antagonism via AID systems shapes human gut microbiome ecology.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 science0.0000.000
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 head0.271
Teacher spread0.242 · 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
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

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicClostridium difficile and Clostridium perfringens research→French-language works237,207→