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Record W3152412627 · doi:10.1038/s41467-021-22306-w

High-throughput fitness screening and transcriptomics identify a role for a type IV secretion system in the pathogenesis of Crohn’s disease-associated Escherichia coli

2021· article· en· W3152412627 on OpenAlexafffund
Wael Elhenawy, Sarah Hordienko, Steven J. Gould, Alexander Oberc, Caressa N. Tsai, Troy P. Hubbard, Matthew K. Waldor, Brian K. Coombes

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchCrohn's and Colitis CanadaHoward Hughes Medical Institute
KeywordsBiologyEscherichia coliTranscriptomeColonizationVirulenceMicrobiologySecretionGenePhenotypeDiseaseGenomeBacterial geneticsHost (biology)GeneticsCrohn's diseaseGene expression

Abstract

fetched live from OpenAlex

Adherent-invasive Escherichia coli (AIEC) are pathogenic bacteria frequently isolated from patients who have Crohn's disease (CD). Despite the phenotypic differences between AIEC and commensal E. coli, comparative genomic approaches have been unable to differentiate these two groups, making the identification of key virulence factors a challenge. Here, we conduct a high-resolution, in vivo genetic screen to map AIEC genes required for intestinal colonization of mice. In addition, we use in vivo RNA-sequencing to define the host-associated AIEC transcriptome. We identify diverse metabolic pathways required for efficient gut colonization by AIEC and show that a type IV secretion system (T4SS) is required to form biofilms on the surface of epithelial cells, thereby promoting AIEC persistence in the gut. E. coli isolated from CD patients are enriched for a T4SS, suggesting a possible connection to disease activity. Our findings establish the T4SS as a principal AIEC colonization factor and highlight the use of genome-wide screens in decoding the infection biology of CD-associated bacteria that otherwise lack a defined genetic signature.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.966
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.028
GPT teacher head0.322
Teacher spread0.294 · 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 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

Citations68
Published2021
Admission routes2
Has abstractyes

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