Ancient Antibiotics, Ancient Resistance
Bibliographic record
Abstract
As the spread of antibiotic resistance threatens our ability to treat infections, avoiding the return of a preantibiotic era requires the discovery of new drugs. While therapeutic use of antibiotics followed by the inevitable selection of resistance is a modern phenomenon, these molecules and the genetic determinants of resistance were in use by environmental microbes long before humans discovered them. In this review, we discuss evidence that antibiotics and resistance were present in the environment before anthropogenic use, describing techniques including direct sampling of ancient DNA and phylogenetic analyses that are used to reconstruct the past. We also pay special attention to the ecological and evolutionary forces that have shaped the natural history of antibiotic biosynthesis, including a discussion of competitive versus signaling roles for antibiotics, proto-resistance, and substrate promiscuity of biosynthetic and resistance enzymes. Finally, by applying an evolutionary lens, we describe concepts governing the origins and evolution of biosynthetic gene clusters and cluster-associated resistance determinants. These insights into microbes' use of antibiotics in nature, a game they have been playing for millennia, can provide inspiration for discovery technologies and management strategies to combat the growing resistance crisis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".