High-resolution lineage tracking of within-host evolution and strain transmission in a human gut symbiont across ecological scales
Bibliographic record
Abstract
Summary Gut bacteria rapidly evolve in vivo , but their long-term success requires dispersal across hosts. Here, we quantify this interplay by tracking >50,000 genomically barcoded lineages of the prevalent commensal Bacteroides thetaiotaomicron ( Bt ) among co-housed mice. We find that adaptive mutations rapidly spread between hosts, overcoming the natural colonization resistance of resident Bt strains. Daily transmission rates varied >10-fold across hosts, but shared selection pressures drove predictable engraftment of specific lineages over time. The addition of a 49-species community shifted the adaptive landscape relative to mono-colonized Bt without slowing the rate of evolution, and reduced transmission while still allowing specific mutants to engraft. Whole-genome sequencing uncovered diverse modes of adaptation involving complex carbohydrate metabolism. Complementary in vitro evolution across 29 carbon sources revealed variable overlap with in vivo selection pressures, potentially reflecting synergistic and antagonistic pleiotropies. These results show how high-resolution lineage tracking enables quantification of commensal evolution across ecological scales.
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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 | 0.001 |
| 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) | 0.001 | 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".