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Record W2806124281 · doi:10.1186/s40168-018-0478-4

Gut microbiota in experimental murine model of Graves’ orbitopathy established in different environments may modulate clinical presentation of disease

2018· article· en· W2806124281 on OpenAlexaff
Giulia Masetti, Sajad Moshkelgosha, Hedda-Luise Köhling, Danila Covelli, J. Paul Banga, Utta Berchner‐Pfannschmidt, Mareike Horstmann, Salvador J. Díaz‐Cano, Gina-Eva Goertz, Sue Plummer, Anja Eckstein, Marian Ludgate, Filippo Biscarini, Julian R. Marchesi

Bibliographic record

VenueMicrobiome · 2018
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Eye Disorders
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersFP7 People: Marie-Curie ActionsDeutsche Forschungsgemeinschaft
KeywordsBiologyPresentation (obstetrics)DiseaseMedical microbiologyMicrobial ecologyGut floraImmunologyGraves' diseaseMedicinePathologyGeneticsBacteria

Abstract

fetched live from OpenAlex

BACKGROUND: Variation in induced models of autoimmunity has been attributed to the housing environment and its effect on the gut microbiota. In Graves' disease (GD), autoantibodies to the thyrotropin receptor (TSHR) cause autoimmune hyperthyroidism. Many GD patients develop Graves' orbitopathy or ophthalmopathy (GO) characterized by orbital tissue remodeling including adipogenesis. Murine models of GD/GO would help delineate pathogenetic mechanisms, and although several have been reported, most lack reproducibility. A model comprising immunization of female BALBc mice with a TSHR expression plasmid using in vivo electroporation was reproduced in two independent laboratories. Similar orbital disease was induced in both centers, but differences were apparent (e.g., hyperthyroidism in Center 1 but not Center 2). We hypothesized a role for the gut microbiota influencing the outcome and reproducibility of induced GO. RESULTS: We combined metataxonomics (16S rRNA gene sequencing) and traditional microbial culture of the intestinal contents from the GO murine model, to analyze the gut microbiota in the two centers. We observed significant differences in alpha and beta diversity and in the taxonomic profiles, e.g., operational taxonomic units (OTUs) from the genus Lactobacillus were more abundant in Center 2, and Bacteroides and Bifidobacterium counts were more abundant in Center 1 where we also observed a negative correlation between the OTUs of the genus Intestinimonas and TSHR autoantibodies. Traditional microbiology largely confirmed the metataxonomics data and indicated significantly higher yeast counts in Center 1 TSHR-immunized mice. We also compared the gut microbiota between immunization groups within Center 2, comprising the TSHR- or βgal control-immunized mice and naïve untreated mice. We observed a shift of the TSHR-immunized mice bacterial communities described by the beta diversity weighted Unifrac. Furthermore, we observed a significant positive correlation between the presence of Firmicutes and orbital-adipogenesis specifically in TSHR-immunized mice. CONCLUSIONS: The significant differences observed in microbiota composition from BALBc mice undergoing the same immunization protocol in comparable specific-pathogen-free (SPF) units in different centers support a role for the gut microbiota in modulating the induced response. The gut microbiota might also contribute to the heterogeneity of induced response since we report potential disease-associated microbial taxonomies and correlation with ocular disease.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.031
GPT teacher head0.336
Teacher spread0.305 · 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

Citations139
Published2018
Admission routes1
Has abstractyes

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