Maintaining an autocatalytic reaction system in a protocell: Nonenzymatic RNA templating and the link between replication and metabolism
Bibliographic record
Abstract
The first protocells must have been driven by a reaction system in which autocatalysis is maintained inside the cell while food molecules outside the cell are unreactive. We show that if there is a second-order autocatalytic mechanism, then an active state can be stable inside the cell with a high catalyst concentration while the environment remains stable in an unreactive state with no catalyst. Addition of a small amount of catalyst to the environment does not cause the initiation of the autocatalytic cycle outside the cell. In contrast, for a first-order mechanism, addition of a small amount of catalyst initiates the reaction outside the cell unless there is continual removal of the catalyst from the environment. Hence, a second-order reaction mechanism maintains the difference between the inside and outside of a protocell much better than a first-order mechanism. The formose reaction, although a prebiotically plausible autocatalytic system, is first order and therefore is unlikely as a means of support for the first protocells. We give other theoretical examples of first- and second-order reaction networks but note there are few known real-world chemical systems that fit these schemes. However, we show that nonenzymatic RNA templating constitutes a second-order autocatalytic system with the necessary properties to support a protocell. Templating is maintained inside the cell but is not initiated outside the cell. If the reaction is driven by an external supply of activated nucleotides, then templating is itself a metabolic cycle. It is not necessary to have an additional separate metabolic cycle before templating reactions can occur. In this view, templating reactions, which are usually considered as the origin of replication and heredity, are also the origin of metabolism.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".