Elongation arrest blocking primers enhance parasite detection in 18S rRNA metabarcoding study of Mesonauta festivus gut eukaryotic communities.
Bibliographic record
Abstract
The study of the eukaryotic fraction of the microbiota using a metabarcoding approach is usually hindered by the high host to eukaryotic microbiota DNA ratio in samples. Indeed, the 18S rRNA gene is very similar for both the host and its eukaryotic communities, leading to a preferential amplification of the predominant host DNA when using universal primers. Multiple approaches have been developed to reduce host DNA amplification. One method is based on elongation arrest blocking primers, oligonucleotides modified with a C3 Spacer that stops the advancement of the DNA polymerase at non-conserved regions of a target gene. In this paper, we successfully developed and tested species-specific elongation arrest blocking primers to block the Flag cichlid, Mesonauta festivus, 18S rRNA SSU. Our elongation arrest blocking primers significantly reduced the amount of host DNA in samples by 66 %. In addition to reducing the amount of sequencing wasted, the blocking primers increased the detectability of potentially dangerous parasitic taxa in fish gut, highlighting the potential of the method for parasitic screening. For instance, we discovered a case of infection by the parasitic ciliate Nyctotherus sp. Also, we detected the presence of a parasitic Trematode and an Amoebae, collected compelling data on the species feeding habits and obtained data on the commensal eukaryotic diversity present in M. festivus gut. While our data support the possibility of achieving a complete inhibition of host DNA amplification using elongation arrest blocking primers, more research is still required. Still, there is a need for the development and additional testing of protocols to study the eukaryotic diversity present in fish gut, a slow-growing field of study in comparison to its prokaryotic counterpart.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".