Challenges Using Droplet Digital PCR for Environmental Samples

V. Kokkoris, Eric Vukicevich, Andrew Richards, Corrina Thomsen, Miranda M. Hart

Research output: Contribution to JournalArticleAcademicpeer-review


Droplet digital polymerase chain reaction (ddPCR) is a method used to detect and quantify nucleic acids even when present in exceptionally low numbers. While it has proven to be valuable for clinical studies, it has failed to be widely adopted for environmental studies but despite some limitations, ddPCR may represent a better option than classical qPCR for environmental samples. Due to the complexity of the chemical and biological composition of environmental samples, protocols tailored to clinical studies are not appropriate, and results are difficult to interpret. We used environmental DNA samples originating from field studies to determine a protocol for environmental samples. Samples included field soils which had been inoculated with the soil fungus Rhizophagus irregularis (environmental positive control), field soils that had not been inoculated and the targeted fungus was not naturally present (environmental negative control), and root samples from both field categories. To control for the effect of soil inhibitors, we also included DNA samples of an organismal control extracted from pure fungal spores (organismal positive control). Finally, we included a no-template control consisting only of the PCR reaction reagents and nuclease free water instead of template DNA. Using original data, we examined which factors contribute to poor resolution in root and soil samples and propose best practices to ensure accuracy and repeatability. Furthermore, we evaluated manual and automatic threshold determination methods and we propose a novel protocol based on multiple controls that is more appropriate for environmental samples.
Original languageEnglish
Pages (from-to)74-88
Number of pages15
JournalApplied Microbiology
Issue number1
Early online date21 May 2021
Publication statusPublished - Jun 2021
Externally publishedYes


This work was supported by the National Sciences and Engineering Research Council of Canada discovery grant (2018).

FundersFunder number
Natural Sciences and Engineering Research Council of Canada


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