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CO‐INFECTION WITH <i>GIARDIA DUODENALIS</i> PROTECTS THE HOST AGAINST ENTEROPATHOGENIC ESCHERICHIA COLI VIA NLRP <sub>3</sub> INFLAMMASOME‐DEPENDENT ANTI‐MICROBIAL PEPTIDE PRODUCTION

2017· article· en· W4387234324 on OpenAlexafffundabout
Anna Mańko, Jean‐Paul Motta, James A. Cotton, Ayodele Oyeyemi, Bruce A. Vallance, Paul L. Beck, John L. Wallace, André G. Buret

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsUniversity of British ColumbiaUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrobiologyBiologyGiardiaEnteropathogenic Escherichia coliProteasesPathogenEscherichia coli

Abstract

fetched live from OpenAlex

Background Infectious diarrheal disease represents a critical concern for child health in developing countries, and often occurs in the context of polymicrobial infections. Mechanisms whereby concurrent infections may alter clinical disease outcome remain obscure. Recent findings indicate that giardiasis could protect against pediatric diarrhea, but the mechanisms are unknown. We hypothesized that Giardia was able to change the pathogenic outcome of bacterial enteritis, either directly or indirectly. Aim To define the mechanisms by which cysteine protease(s) released by Giardia activate the NLPR 3 inflammasome pathway to increase antimicrobial peptide (AMP) production during co‐infection with enteropathogenic Escherichia coli (EPEC). Methods Mice (wild type or NLRP3 −/− ) were infected with G. muris and/or Citrobacter rodentium to model co‐infections with Giardia and EPEC in humans. AMP production, bacterial pathogen burdens, and colonic disease activity were assessed. Human enterocytes (Caco‐2) were pretreated or not with glyburide (NLRP3 inhibitor; 100 mm, 30 min), and infected with Giardia duodenalis trophozoites (with or without pre‐treatment with cathepsin B‐like inhibitors) and EPEC separately or in combination. Human β‐defensin‐2 (HBD‐2), mouse β‐defensin‐3 (MBD‐3) and trefoil‐factor 3 (TFF3) protein and mRNA expression were assessed by immunofluorescent (IF) staining and by RT‐qPCR, respectively. Colonic Caspase‐1 and ‐11 protein levels were assessed by Western blot. Direct anti‐bacterial effects of Giardia were assessed in vitro . Results Infection with G. muris increased colonic β‐defensin and TFF3 expression, inhibited bacterial colonization, and reduced disease activity in co‐infected animals. These effects were lost in NLRP3 −/− mice. HBD‐2 and TFF3 IF staining intensity was highest in co‐infected epithelial cells. HBD‐2 and TFF3 mRNA levels were highest in co‐infected enterocytes, and the effect was lost upon glyburide treatment. Caspase‐1 and ‐11 protein levels were highest in co‐infected mice when compared to animals given C. rodentium alone. Pre‐treatment of Giardia trophozoites with a selective cathepsin B‐like inhibitor abolished the effects of G. intestinalis . Moreover, G. intestinalis directly inhibited EPEC growth in vitro , in a cathepsin B‐like‐dependent manner. Conclusions Co‐infection with Giardia during EPEC infection activates the NLRP 3 inflammasome, and increases AMP production in human enterocytes. Giardia cathepsin B‐like proteases contribute to this AMP‐mediated protective effect, which is partially NLRP3‐dependent. Giardia cathepsin‐like proteases have direct anti‐bacterial properties. Our data suggest a novel role for the inflammasome in the production of AMP, and reveals its protective effects using models of co‐infection with Giardia . Support or Funding Information Funding for this research was provided by a discovery grant from the Natural Sciences and Engineering Research Council of Canada, and by a NSERC CREATE grant on Host‐Parasite Interactions.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.016
GPT teacher head0.254
Teacher spread0.238 · 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

Citations1
Published2017
Admission routes3
Has abstractyes

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