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Record W2921100538 · doi:10.1093/jcag/gwz006.020

A21 ANTIBIOTICS SUPPRESS INTESTINAL ANTIVIRAL RESPONSES IN A MICROBIOTA-INDEPENDENT MANNER

2019· article· en· W2921100538 on OpenAlexaff
André Sharon, Lisa C. Osborne

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAntibioticsImmune systemMurine norovirusNeomycinMicrobiologyBiologyImmunityMetronidazoleImmunologyAntimicrobialGut floraVirusNorovirus

Abstract

fetched live from OpenAlex

Oral antibiotics are commonly administered to mice, and effects seen following these treatments are typically ascribed to the depletion of the intestinal microbiota; however, these effects may also be due to direct effects of the antibiotics on the host. In vitro studies have shown that various antibiotics can suppress many immune functions, but despite the frequent use of antibiotics in the clinic and research, potential microbiota-independent effects of antibiotics in vivo have been understudied. Here, we use murine norovirus strain CR6 (MNV-CR6) to investigate the effects of an oral antibiotic cocktail on intestinal immune responses. MNV-CR6 forms a persistent infection limited to the murine colon, a site containing high numbers of antibiotic-sensitive microbes which have been suggested to influence antiviral immunity. Importantly, while MNV-CR6 provokes an antiviral CD8+ T cell response, the magnitude of this response has no observed effect on the course of the infection, allowing us to study the effects of antibiotics on antiviral immunity without significantly influencing the underlying infection. We aimed to investigate the effects of an oral antibiotic cocktail on antiviral immune responses to MNV-CR6 infection, including whether antibiotic-mediated effects were microbiota-dependent. Conventional (CNV) and Germ-Free (GF) C57Bl/6J mice were administered a cocktail of ampicillin, gentamicin, metronidazole, neomycin, and vancomycin in drinking water for two weeks prior to oral infection with MNV-CR6. At 11 days post-infection, lymphocytes were isolated from the colon and tetramer stained to identify MNV-specific CD8+ T cells. Viral loads were assessed by qPCR of colon tissue. To determine whether the microbiota is necessary for MNV-CR6 infection, we infected CNV and GF mice with MNV-CR6 and assessed viral loads. GF status did not significantly impact viral load, indicating that the microbiota is dispensable for MNV-CR6 infection. Similarly, we assessed the effect of antibiotics on viral load. In both CNV and GF mice, antibiotic treatment did not significantly impact viral load. Next, we assessed the effects of antibiotics on the generation of an antiviral CD8+ T cell response to MNV-CR6. CNV and GF mice were treated with an oral antibiotic cocktail prior to infection with MNV-CR6, and lymphocytes were isolated from the colon. While untreated mice generated MNV-specific CD8+ T cells, antibiotics prevented this response. Importantly, this effect was seen in both CNV and GF mice, indicating that the effect of the antibiotic treatment was microbiota-independent. Our results indicate that antibiotic treatment can profoundly suppress antiviral immune responses in a microbiota-independent manner. These results may have implications for the use of antibiotics clinically and in microbiota research. CIHR

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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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
Published2019
Admission routes1
Has abstractyes

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