Antivirulence Activity of the Human Gut Metabolome
Bibliographic record
Abstract
The mammalian gut contains a complex assembly of commensal microbes termed microbiota. Although much has been learned about the role of these microbes in health, the mechanisms underlying these functions are ill defined. We have recently shown that the mammalian gut contains thousands of small molecules, most of which are currently unidentified. Therefore, we hypothesized that these molecules function as chemical cues used by hosts and microbes during their interactions in health and disease. Thus, a search was initiated to identify molecules produced by the microbiota that are sensed by pathogens. We found that a secreted molecule produced by clostridia acts as a strong repressor of Salmonella virulence, obliterating expression of the Salmonella pathogenicity island 1 as well as host cell invasion. It has been known for decades that the microbiota protects its hosts from invading pathogens, and these data suggest that chemical sensing may be involved in this phenomenon. Further investigations should reveal the exact biological role of this molecule as well as its therapeutic potential. Importance: Microbes can communicate through the production and sensing of small molecules. Within the complex ecosystem formed by commensal microbes living in and on the human body, it is likely that these molecular messages are used extensively during the interactions between different microbial species as well as with host cells. Deciphering such a molecular dialect will be fundamental to our understanding of host-microbe interactions in health and disease and may prove useful for the design of new therapeutic strategies that target these mechanisms of communication.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".