Propylene glycol-based antifreeze as an effective preservative for DNA metabarcoding of benthic arthropods
Bibliographic record
Abstract
Abstract Maintaining the integrity of DNA in bulk environmental samples from source to laboratory is crucial for capturing the true range of taxa present within an ecosystem. Preservation consideration of DNA is particularly important if samples are being collected in remote areas and by non-specialist ‘citizen scientists’ in nationwide programs. Traditionally, absolute ethanol is used as the preferred preservative for environmental samples collected for downstream DNA metabarcoding analyses. However, transport, shipping and DNA extraction of samples preserved in ethanol is a lengthy procedure due to safety restrictions and the requirement of full ethanol evaporation prior to extraction. We examined the efficacy of an easily accessible, non-toxic propylene glycol-based antifreeze as an alternative to absolute ethanol for preserving macroinvertebrate DNA from bulk-benthos DNA samples. We tested the differences in both cytochrome oxidase I (COI) exact sequence variants (ESVs) and COI taxonomic orders detected in both ethanol and antifreeze samples using two processing methods (no evaporation of preservative versus full evaporation). In addition, we assessed the detection of families and genera within the Arthropoda phylum for preservative type, site and processing method. Our results suggest that antifreeze is a suitable alternative to ethanol, a greater global ESV richness reported for antifreeze samples. Additionally, a higher proportion of arthropod reads in ESVs were detected in antifreeze (average 69%) compared with ethanol (average 53%). Finally, antifreeze samples produced similar results for the different processing methods, whereas ethanol samples failed to produce similar results without prior evaporation. Although ethanol is currently widely used for DNA preservation, our results demonstrate that by using antifreeze, it is possible to achieve similar taxonomic coverage and community assemblages of bulk-benthos DNA samples for macroinvertebrates, with the added simplicity and shorter laboratory processing time achieved using an easily available, unregulated preservative.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".