Defining the role of <i>Parasutterella</i>, a previously uncharacterized member of the core gut microbiota
Bibliographic record
Abstract
The genus of Parasutterella has been defined as a core component of the human and mouse gut microbiota, and has been correlated with various health outcomes. However, like most core microbes in the gastrointestinal tract (GIT), very little is known about the biology of Parasutterella and its role in intestinal ecology. In this study, Parasutterella was isolated from the mouse GIT and characterized in vitro and in vivo. Mouse, rat, and human Parasutterella isolates were all asaccharolytic and producers of succinate. The murine isolate stably colonized the mouse GIT without shifting bacterial composition. Notable changes in microbial-derived metabolites were aromatic amino acid, bilirubin, purine, and bile acid derivatives. The impacted bile acid profile was consistent with altered expression of ileal bile acid transporter genes and hepatic bile acid synthesis genes, supporting the potential role of Parasutterella in bile acid maintenance and cholesterol metabolism. The successful colonization of Parasutterella with a single environmental exposure to conventional adult mice demonstrates that it fills the ecological niche in the GIT and contributes to metabolic functionalities. This experiment provides the first indication of the role of Parasutterella in the GIT, beyond correlation, and provides insight into how it may contribute to host health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".