Prise en charge des enfants obèses au CHU d'Angers (Comparaison de l'efficacité d'une éducation thérapeutique collective à une prise en charge individuelle)

ANGERS-BU Médecine-Pharmacie (490072105) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Getting rid of rain and stars: mitigating inhibition effects in ddPCR assays, the case of the invasive crayfish Pacifastacus leniusculus in the streams of Luxembourg

ddPCR is getting more and more popular in the field of eDNA-based aquatic monitoring. Even if emulsion PCR used in ddPCR confers a partial resistance to inhibition due to the high number of reactions for the same sample (between 10K and 20K), it is not impervious to it. Inhibition impacts the fluorescence amplitude of positive droplets, affecting both their dispersion and their position relatively to the negative droplets cloud. This fluctuation could jeopardize the use of a shared threshold among several samples and thus the objective assignation of the positive droplets.This is even more critical for low concentration samples such as eDNA samples: the positive droplets are scarce and it is thus crucial to objectively discriminate if they can be counted as positive by establishing an appropriate threshold. Another issue is the artifactual generation of high fluorescence droplets that could be counted as positive with a single threshold solution.Here we propose a double threshold method to take both high fluorescence droplets and PCR inhibition impact into account allowing for an objective sorting of the positive and negative droplets in ddPCR assays

Schematic workflow of the data treatment.

(a) Export of the raw fluorescence data from positive control (genomic extract at 15 ng/μl) spiked with two different amount of river eDNA extract in order to define the part of the signal that can be accounted as ‘rain’ and stars’; (b) from these data, for each rivers (n = 6 for the main rivers Alzette and Sûre and n = 3 for tributaries Eisch, Attert, Mamer, Wiltz, Clerve), the descriptive statistics (Mean pos. = Mean fluorescence value for the positive droplets cloud, ∂ = standard deviation for the positive cloud and mean neg. = Mean fluorescence value for the negative droplets cloud) were calculated and, in turn, used to estimate the two threshold correction factors (Upper Threshold Correction Factor (UTCF) and Lower Threshold Correction Factor (LTCF); (c) River specific threshold correction factors were applied to the analysis of the samples in order to consistently detect and measure target DNA concentrations.</p

Fig 4 -

Boxplot representation of the standard deviations measured in (a) negative and (b) positive clouds for different amounts of eDNA samples (0, 0.5 and 1 μl) spiked in positive controls (P. leniusculus genomic DNA). Pairwise Wilcoxon test P values with Holm correction are indicated on horizontal bars (NS = non-significant).</p

Boxplot representation of the differential fluorescence amplitudes between the mean fluorescence of the positive and the negative droplet clouds for different amounts of eDNA samples (0, 0.5 and 1 μl) spiked into positive controls (<i>P</i>. <i>leniusculus</i> genomic DNA).

Pairwise Wilcoxon test P values with Holm correction are indicated on horizontal bars.</p

Raw data.

(ZIP)</p

Inhibition impact in different river samples (reference value of the positive control = 6831.77), correlation between the DNA replicates’ concentrations produced with the two classifications methods (Quantasoft and the two threshold method developed here) and the number of false negatives and positives generated with Quantasoft at the replicate and site levels (the number in bracket is the value normalized to 40 replicates for rivers sampled in 7 sites instead of 4).

Inhibition impact in different river samples (reference value of the positive control = 6831.77), correlation between the DNA replicates’ concentrations produced with the two classifications methods (Quantasoft and the two threshold method developed here) and the number of false negatives and positives generated with Quantasoft at the replicate and site levels (the number in bracket is the value normalized to 40 replicates for rivers sampled in 7 sites instead of 4).</p

Map of the ddPCR results.

(a) Number of successful amplification out of 10 replicates; (b) Mean concentrations per site in cp/μl.</p

Localization of the 34 sampling sites.

The colors of the dots represent the different rivers sampled (Red = Alzette, Blue = Sure, Green = Eisch, Brown = Clerve, Pink = Wiltz, Orange = Attert, Purple = Mamer).</p

Concentration measured and volume filtered for each replicate.

0* = replicates in which 3 or less positive amplification events were observed; NLOQ = Concentration measured under LOQ, replicates only retained for absence/presence information. (XLSX)</p