A unified protocol for simultaneous extraction of DNA and proteins from archaeological dental calculus
Bibliographic record
Abstract
Archaeological materials are a finite resource, and efforts should be made to minimize destructive analyses. This can be achieved by using protocols combining extraction of several types of biomolecules or microparticles, which decreases the material needed for analyses while maximizing the information yield. Archaeological dental calculus is a source of several different types of biomolecules, as well as microfossils, and can tell us about the human host, microbiome, diet, and even occupational activities. Here, we present a unified protocol allowing for simultaneous extraction of DNA and proteins from a single sample of archaeological dental calculus. We evaluate the protocol on dental calculus from six individuals from a range of time periods and estimated preservation states, and compare it against previously published DNA-only and protein-only protocols. We find that most aspects of downstream analyses are unaltered by the unified protocol, although minor shifts in the recovered proteome can be detected, such as a slight loss of hydrophilic proteins. Total protein recovery depends on both the amount of starting material and choice of extraction protocol, whereas total DNA recovery is significantly reduced using the unified protocol (mean 43%). Nevertheless, total DNA recovery from dental calculus is generally very high, and we found no differences in DNA fragment characteristics or taxonomic profile between the protocols. In conclusion, the unified protocol allows for simultaneous extraction of two complementary lines of biomolecular evidence from archaeological dental calculus without compromising downstream results, thereby minimizing the need for destructive analysis of this finite resource.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".