A probabilistic model for designing and assessing the performance of eDNA sampling protocols

Area of Science:

• Environmental science
• Molecular biology
• Ecology

Background:

• Environmental DNA (eDNA) sampling is a key tool for monitoring aquatic invasive species.
• Understanding how sampling protocol steps affect eDNA detection sensitivity is crucial for accurate monitoring.
• Previous studies lacked a comprehensive model to evaluate protocol optimization impacts.

Purpose of the Study:

• To develop a probabilistic model for characterizing eDNA sampling protocol steps.
• To evaluate the model's application in analyzing historical protocol changes for bighead and silver carp detection.
• To assess how protocol modifications influence eDNA detection sensitivity and result interpretation.

Main Methods:

• Development of a probabilistic model to assess eDNA sampling protocol sensitivity.
• Application of the model to analyze protocol changes from 2009 to the present.
• Quantification of sensitivity fluctuations due to specific protocol modifications (extraction, markers, capture, elution, sample volume).

Main Results:

• Protocol modifications have led to fluctuating detection sensitivity.
• Improved extraction (2013), qPCR assay (2014), and capture methods (2015) increased sensitivity.
• Larger elution volume (2013) and smaller sample volume (2015) decreased sensitivity.
• Current protocol shows higher sensitivity for bighead and silver carp eDNA detection compared to the original (2009-2012).

Conclusions:

• The developed probabilistic model effectively evaluates eDNA sampling protocol sensitivity.
• Protocol optimization significantly impacts detection sensitivity, affecting invasive species monitoring results.
• The model aids researchers in optimizing eDNA sampling and analysis protocols for improved invasive species detection.