MétaCan
Menu
← Back to cohort
Record W3134427137 · doi:10.1093/jcag/gwab002.199

A201 UNDERSTANDING THE INFECTION DYNAMICS OF MYCOBACTERIUM PARATUBERCULOSIS (MAP)

2021· article· en· W3134427137 on OpenAlexaffabout
Grace Baruta, H Zhang, Laurie Alston, Simon A. Hirota

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsParatuberculosisBiologyMycobacterium avium subspecies paratuberculosisMicrobiologyTropismEpitheliumImmunologyMycobacteriumVirologyGenetics

Abstract

fetched live from OpenAlex

Abstract Background Mycobacterium avium subspecies paratuberculosis (MAP) is the causative agent of Johne’s disease (JD) in ruminants. Following infection, JD may present as enteritis, leading to wasting, often causing premature culling of livestock. Beyond veterinary medicine, several mycobacterium species, including MAP, have been implicated in human gastrointestinal disease. While MAP has been incriminated in causing Crohn’s disease (a claim that has yet to be substantiated), there are confirmed cases of MAP infection in immunocompromised individuals, causing profuse diarrhea, fever, and drastic weight loss. Given the economic burden associated with MAP infection, considerable efforts have sought to understand its dynamics. However, these processes have not been completely characterized, hindering our ability to generate novel anti-infective agents. While the current paradigm suggests that MAP travels to the small intestine, gaining entry through the epithelium, the exact cellular tropism and the mechanism(s) of entry are not well defined. Therefore, we have developed an ex vivo enteroid-based system to visualize invasion of MAP in distinct cells of the intestinal epithelium using a GFP-expressing MAP strain. With this, we sought to test the hypothesis that MAP invasion occurs via M cells through receptor-mediated transcytosis. Aims 1) Characterize experimental system and visualize MAP invasion 2) Determine cellular tropism 3) Uncover mechanisms underlying MAP invasion Methods Enteroids (2D and 3D) were generated and M cell differentiation induced via addition of RANKL. Confluent ileal monolayers were exposed to GFP-expressing MAP strain (K10 pWES4). Confocal microscopy was performed, and barrier function was measured via transepithelial electrical resistance (TEER). Results We generated 3D enteroids and confluent enteroid-derived monolayers with functional M cells capable of transcytosis. MAP was detected mainly within M cells. We further confirmed this finding using a human in vitro M cell model, the Caco-2/Raji-B co-culture system. Furthermore, alterations in TEER following MAP exposure in monolayers cultured with RANKL, triggering M cell differentiation, suggest the existence of a novel mechanism by which MAP disrupts the barrier to invade the mucosa. Conclusions Our results suggest that MAP translocates across the epithelium predominantly via M cells, as shown both in a human and murine model. This newly optimized approach provides an experimental system that will enable us to better characterize M cell-MAP interactions, with the hopes of identifying new therapeutic targets to prevent the spread of MAP and reduce economic impact of JD. Beyond MAP infection, this novel ex vivo system has potential to elucidate other host-pathogen interactions. Funding Agencies Natural Sciences and Engineering Research Council of Canada (NSERC)

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.256
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 designNot applicable
Domainnot available
GenreReview

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
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Canadian Association of Gastroenterology→Same topicMycobacterium research and diagnosis→French-language works237,207→