Microbial exoenzymes catalyzed the transition to an oxygenated Earth
Bibliographic record
Abstract
Microbial exoenzymes, extracellular enzymes secreted to degrade complex organic polymers, are essential for recycling carbon and nutrients, thus sustaining primary productivity in todays oceans. Yet, their evolutionary history and role in shaping Earths early biosphere remain entirely unexplored. Here, we trace the origins of microbial exoenzymes and reveal their previously unrecognized role in driving planetary oxygenation. Our results show that exoenzymes are more common in microorganisms utilizing high-energy metabolisms, likely reflecting the energetic costs of enzyme biosynthesis and secretion. They are especially advantageous in environments rich in particulate organic matter (POM). A refined carbon cycle model indicates that early Archean oceans offered few such habitats, as low productivity and intense UV radiation rapidly photodegraded POM. However, with a Paleoproterozoic rise of atmospheric oxygen, increased oxidative weathering boosted marine primary productivity and POM accumulation, creating conditions favoring exoenzyme evolution. Molecular clock analyses further indicate that alkaline phosphatase, a key phosphorus-releasing exoenzyme, had likely emerged with the permanent rise of oxygen, enabling more efficient phosphorus recycling. We propose that exoenzymes initiated a positive feedback loop: by accelerating nutrient regeneration, they fueled cyanobacterial productivity and oxygen release, which in turn favored greater exoenzyme capacity, reinforcing long-term oxygenation of the planet.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".