Promise and limitations of 18S genetic screening of extracted fecal DNA from wild capuchins
Bibliographic record
Abstract
Genomic screening of fecal DNA provides insight into diet, parasite infection dynamics, and other aspects of the ecology and pathogens of wild populations. Here, we amplify and sequence the V4/V5 regions of the eukaryotic 18S ribosomal RNA gene from fecal DNA of wild capuchin monkeys (Cebus imitator). We collected 94 fecal samples from 26 individuals, each sampled 1-4 times across a 19-month period and examined the eukaryotic diversity in 63 of these samples which had sufficient numbers and quality of reads during downstream analyses. We found a total of 234 distinct amplicon sequence variants (ASVs) classified as Eukaryotes in our samples. Of these, 66 were assigned to the phylum Nematoda. 64 ASVs are from taxa that possibly parasitize monkeys or their food items: 33 were assigned to lungworms (Superfamily Metastrongyloidae; genus Angiostrongylus), two to the genus Strongyloides, and one to the genus Austrostrongylus. The remaining 28 ASVs were assigned to nematodes that likely parasitize plants and/or invertebrates that the monkeys consume. Taken together with past dietary and coprological study of the same primate population, our results suggest that invertebrate consumption and parasitic infection, especially by lungworms, is common and widespread among this population of wild monkeys. We also discuss limitations of our approach, including the amplification of off-target ASVs, and make suggestions for future research. Overall, 18S screening shows promise for identifying various components of the capuchin gastrointestinal eukaryotic ecosystem, including parasitic helminths, and its utility will increase with the improvement of genetic databases.
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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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".