Metabolomic Analysis of Human Fecal Microbiota: A Comparison of Feces-Derived Communities and Defined Mixed Communities
Bibliographic record
Abstract
The extensive impact of the human gut microbiota on its human host calls for a need to understand the types of communication that occur among the bacteria and their host. A metabolomics approach can provide a snapshot of the microbe-microbe interactions occurring as well as variations in the microbes from different hosts. In this study, metabolite profiles from an anaerobic continuous stirred-tank reactors (CSTR) system supporting the growth of several consortia of bacteria representative of the human gut were established and compared. Cell-free supernatant samples were analyzed by 1D (1)H nuclear magnetic resonance (NMR) spectroscopy, producing spectra representative of the metabolic activity of a particular community at a given time. Using targeted profiling, specific metabolites were identified and quantified on the basis of NMR analyses. Metabolite profiles discriminated each bacterial community examined, demonstrating that there are significant differences in the microbiota metabolome between each cultured community. We also found unique compounds that were identifying features of individual bacterial consortia. These findings are important because they demonstrate that metabolite profiles of gut microbial ecosystems can be constructed by targeted profiling of NMR spectra. Moreover, examination of these profiles sheds light on the type of microbes present in the gut and their metabolic interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".