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Fast, Flexible, Feasible: A Transparent Framework for Evaluating eDNA Workflow Trade-Offs in Resource-Limited

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Optimizing environmental DNA (eDNA) workflows balances cost, speed, and sensitivity for biodiversity monitoring. The Qiagen BT kit with MiFish-U primers and Nanopore HAC basecalling offers high sensitivity, enabling efficient eDNA analysis.

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Area of Science:

  • Environmental DNA (eDNA) analysis
  • Biodiversity monitoring
  • Molecular ecology

Background:

  • Environmental DNA (eDNA) analysis is a powerful tool for biodiversity monitoring.
  • High costs, complex logistics, and computational demands hinder widespread eDNA adoption, especially in resource-limited regions.
  • Optimizing eDNA workflows is crucial for improving accessibility and scalability.

Purpose of the Study:

  • To directly compare various eDNA workflow components to identify optimal combinations for cost, speed, and sensitivity.
  • To provide a decision framework for selecting eDNA workflows tailored to specific monitoring needs and resource constraints.
  • To assess trade-offs in eDNA analysis to enable resource-limited settings to conduct effective biodiversity monitoring.

Main Methods:

  • Evaluated four DNA extraction methods (Qiagen BT, Chelex, DirectPCR, QuickExtract).
  • Tested two primer sets (MiFish-U, MarVer1).
  • Compared three Nanopore basecalling models (including HAC) and two demultiplexing pipelines (OBITools4, ONTbarcoder2.3).
  • Assessed 48 workflow combinations using fish species in an aquarium setting, analyzing cost, sensitivity, and processing speed.

Main Results:

  • The Qiagen Blood and Tissue (BT) kit combined with the MiFish-U primer set and Oxford Nanopore's high accuracy (HAC) basecalling model demonstrated the highest sensitivity, detecting 12 out of 15 species within 3-5 hours.
  • Lower-cost methods like Chelex showed limited recovery, while field-friendly options (DirectPCR, QuickExtract) offered comparable results within 10-12 hours.
  • Real-time sequencing revealed that optimized workflows could reduce sequencing time without compromising accuracy.
  • The ONTbarcoder2.3 pipeline retained more low-abundance taxa than OBITools4, albeit with manual curation needs.

Conclusions:

  • No single 'best' eDNA workflow exists; optimal choices depend on balancing cost, speed, and sensitivity requirements.
  • The study provides a transparent framework to guide workflow selection for scalable and cost-effective eDNA monitoring.
  • Findings support the broader implementation of eDNA analysis in resource-limited settings for biodiversity assessment.