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Record W2789656041 · doi:10.1093/jcag/gwy008.296

A295 FUCOSE AVAILABILITY AND ITS UTILIZATION IMPACT IN VIVOENTERIC PATHOGEN VIRULENCE.

2018· article· en· W2789656041 on OpenAlexaff
Joannie M. Allaire, Kirandeep Bhullar, Shauna M. Crowley, Martin Ståhl, Hong Yang, Elena F. Verdú, Hongbing Yu, Bruce A. Vallance

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsMcMaster UniversityBC Children's Hospital
Fundersnot available
KeywordsCitrobacter rodentiumFucoseMicrobiologyVirulencePathogenBiologyIn vivoSecretionBiochemistryGalactoseGene

Abstract

fetched live from OpenAlex

Attaching and effacing (A/E) pathogens such as Enterohemorrhagic E. coli (EHEC) are important causes of diarrheal disease worldwide. Interestingly, little is known about how these bacteria obtain key nutrients, and whether these nutrients modulate pathogen colonization and gut infection. For example, fucose is an important sugar and bacterial food source cleaved from host glycans found on the intestinal mucosal surface via the actions of commensal microbes expressing fucosidase enzymes. Interestingly, although the mouse A/E pathogen Citrobacter rodentium does not itself express a fucosidase, recent studies have found that it and EHEC use a fucose sensing system to modulate their pathogenicity in vitro. At present, it is unclear what role fucose metabolism may play in A/E pathogen virulence and metabolism in vivo. To address this, we focused on C. rodentium enzyme L-fuculose kinase (encoded by the fucK gene), which plays a key role in the L-fucose metabolic pathway and fucose utilization as a food source. We investigated the roles of fucose and the enzyme L-fuculose kinase in controlling C. rodentium pathogenesis. Wildtype (WT) and ΔfucK C. rodentium were used for in vitro assays (type three secretion, growth and adhesion assays) and for in vivo infection. C57Bl/6 mice were infected either separately, or with both C. rodentium strains at a dose of 10^8 colony forming units. In some infections, mice were pretreated with streptomycin (20mg 24h pre-infection) or were fed fucose (200ul of 25mM L-fucose 2x/day). Bacterial burdens, pathology score and competitive assay were assessed on day 6 post-infection. In vitro virulence assays identified no significant differences between ΔfucK and WT C. rodentium regarding type three secretion, growth or adherence to cultured epithelial cells. Moreover, both WT and ΔfucK C. rodentium readily colonized the intestines of mice either pretreated (or not), with streptomycin, with pathogen burdens, localisation and histological pathology scores similar between the two strains. In contrast, simultaneous infection by both strains (competitive assay) within the same mice revealed the ΔfucK strain was significantly impaired when competing with WT C. rodentium (no streptomycin). In contrast, ΔfucK was able to equally compete with WT C. rodentium when streptomycin pretreatment was given to deplete commensal bacteria. Feeding fucose to these streptomycin treated mice again reduced the ability of the ΔfucK strain to compete with WT C. rodentium. These results indicate that the fucK-dependent fucose metabolic pathway promotes but is not essential to C. rodentium pathogenesis. Moreover these findings suggest that commensal microbes play a key role in controlling fucose availability in the gut, and thereby impact A/E pathogen metabolism and virulence. CCC, CIHRNSERC, FRQS

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.280
Teacher spread0.264 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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