Getting Rid of 'rain' and 'stars': Mitigating Inhibition Effects on DdPCR Data Analysis, the Case Study of the Invasive Crayfish Pacifastacus Leniusculus in the Streams of Luxembourg

ddPCR is becoming one of the most widely used tool in the field of eDNA-based aquatic monitoring. Although emulsion PCR used in ddPCR confers a partial mitigation to inhibition due to the high number of reactions for a single sample (between 10K and 20K), it is not impervious to it. Our results showed that inhibition impacts the amplitude of fluorescence in positive droplets with a different intensity among rivers. This signal fluctuation could jeopardize the use of a shared threshold among samples from different origin, and thus the accurate assignment of the positive droplets which is particularly important for low concentration samples such as eDNA ones: amplification events are scarce, thus their objective discrimination as positive is crucial. Another issue, related to target low concentration, is the artifactual generation of high fluorescence droplets ('stars'). Indeed, these could be counted as positive with a single threshold solution, which in turn could produce false positive and incorrect target concentration assessments. Approximating the positive and negative droplets distribution as normal, we proposed here a double threshold method accounting for both high fluorescence droplets ('stars') and PCR inhibition impact in delineating positive droplets clouds. In the context of low concentration template recovered from environmental samples, the application of this method of double threshold establishment could allow for a consistent sorting of the positive and negative droplets throughout ddPCR data generated from samples with varying levels of inhibitor contents. Due to low concentrations template and inhibition effects, Quantasoft software produced an important number of false negatives and positive comparatively to the double threshold method developed here. This case study allowed the detection of the invasive crayfish P. leniusculus in 32 out of 34 sampled sites from two main rivers (Alzette and Sûre) and five of their tributaries (Eisch, Attert, Mamer, Wiltz and Clerve).