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去除“雨”和“星”:减轻 ddPCR 数据分析中的抑制效应,以卢森堡溪流中的入侵性小龙虾 Pacifastacus leniusculus 为例。

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.

机构信息

Musée National d'histoire Naturelle, Life Science Department-Invertebrate Zoology, Population Biology and Evolution, Luxembourg, Luxembourg.

Fondation Faune Flore, Luxembourg, Luxembourg.

出版信息

PLoS One. 2022 Nov 16;17(11):e0275363. doi: 10.1371/journal.pone.0275363. eCollection 2022.

Abstract

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).

摘要

ddPCR 正成为基于 eDNA 的水生监测领域中最广泛使用的工具之一。尽管 ddPCR 中使用的乳液 PCR 由于单个样本的反应数量多(在 10K 和 20K 之间),对抑制作用有一定的缓解作用,但它并不是完全不受抑制作用的影响。我们的结果表明,抑制作用会对阳性液滴中的荧光幅度产生影响,而不同河流之间的影响强度不同。这种信号波动可能会影响来自不同来源的样品之间共享阈值的使用,从而无法准确分配阳性液滴,对于像 eDNA 这样浓度较低的样本尤其重要:扩增事件很少,因此准确识别阳性液滴至关重要。另一个与目标低浓度相关的问题是人为产生高荧光液滴(“星”)。实际上,使用单个阈值解决方案可以将其计数为阳性,这反过来又可能导致假阳性和错误的目标浓度评估。由于目标浓度低,我们近似地将阳性和阴性液滴分布视为正态分布,在此提出了一种双阈值方法,该方法考虑了高荧光液滴(“星”)和 PCR 抑制作用的影响,以描绘阳性液滴云。在从环境样本中回收的低浓度模板的背景下,应用这种双阈值建立方法可以在抑制物含量不同的样本产生的 ddPCR 数据中,始终如一地区分阳性和阴性液滴。由于模板浓度低和抑制作用的影响,Quantasoft 软件生成的假阴性和阳性数量与我们这里开发的双阈值方法相比都很多。这项案例研究在两条主要河流(阿尔泽特河和叙尔河)及其五条支流(埃希河、阿特尔特河、马默尔河、威尔茨河和克里弗河)的 34 个采样点中的 32 个点中检测到了入侵的小龙虾 P. leniusculus。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd90/9668142/4be288e8414f/pone.0275363.g001.jpg

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