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Record W2791451024 · doi:10.1093/jcag/gwy009.017

A17 DIETARY MODULATION OF THE IMMUNE RESPONSE TO CITROBACTER RODENTIUM

2018· article· en· W2791451024 on OpenAlexaff
Mitra Yousefi, Deanna M. Pepin, Eun-Young Kang, Linghua Zhu, Benjamin P. Willing, Samantha Gruenheid

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of AlbertaMcGill University
Fundersnot available
KeywordsCitrobacter rodentiumBiologyImmune systemMicrobiologyPathogenCitrobacterEnteropathogenic Escherichia coliImmunologyWnt signaling pathwayGut floraGeneGeneticsEscherichia coliEnterobacteriaceae

Abstract

fetched live from OpenAlex

A leading cause of diarrheal disease is gastrointestinal infection by enteropathogenic and enterohaemorrhagic Escherichia coli (EPEC and EHEC, respectively). Despite evidence of variability in disease severity and clinical outcome of EPEC and EHEC infections, little is known about the mechanisms regulating host susceptibility to these pathogens and the related mouse-specific pathogen Citrobacter rodentium serves as a good model to study these mechanisms. Our group has identified a single gene R-spondin 2 (Rspo2) encoding a secreted potentiator of WNT signalling as the common genetic determinant underlying mortality during C. rodentium infection. Induction of Rspo2 during infection of susceptible mice drives uncontrolled proliferation and loss of differentiation of the intestinal epithelium, leading to mortality. We have also recently observed that, in addition to the large impact of host genetics, susceptibility to C. rodentium infection is strongly influenced by diet. Based on our observations and considering the fact that diet could have an impact on the gut microbiota, we aimed to investigate the role of microbiota and nutrition in the susceptibility to C. rodentium infection. To this end, we performed Microbiota analysis, deep immuno-profiling of the gut and gene experession analysis before and during infection with C. rodentium. Our data reveals that, diet impacts C. rodentium colonization in susceptible mice early upon infection, although bacterial loads equalize at later time points. Rspo2 induction is attenuated in mice on the resistance-associated diet, correlating with decreased upregulation of some WNT target genes. Microbiota analysis reveals that resistance-associated diet correlates with less diversity of microbial community and more abundance of Bacteriodes. Deep immuno-profiling of the susceptible mice on the two different diets reveals an early increase in infiltration of phagocytes to the gut lamina propria in mice on the susceptibility-associated diet. Furthermore, mice on this diet have higher total dendritic cell abundance at realy stages upon infection, which is mostly due to an increase in dendritic cells of a subtype known to induce Th17 cells. Indeed, our data also show that diet mediated susceptibility to C. rodentium infection correlates with a more prominent Th17 response, whereas mice on the resistance-associated diet have a more prominent induction of Tregs and Th22 cells, as well as induction of anti-microbial compounds RegIIIβ and RegIIIγ. These data suggest that different standard mouse chow diets can have large impacts on susceptibility to infection, correlating with changes in microbiota composition and immune status before and during the course of infection. We anticipate that our findings might be applicable towards new dietary and microbial strategies of therapeutic potentials. CIHRFerring Postdoctoral Award-Strauss Foundation, Wares Family Postdoctoral Award

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 score0.005

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 integrity0.0000.001
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 head0.014
GPT teacher head0.219
Teacher spread0.204 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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