Entomopathogenic nematodes (EPNs) are widely distributed in soils across all continents except Antarctica. Assessing the EPN community structure in an ecoregion can help reveal their biological control potential against important crop pests. Common methods for detecting EPNs in soil samples include baiting with sentinel insects, direct observation of extracted nematodes, or use of species-specific primer-probe combinations using qPCR. Less well studied is the use of high throughput sequencing (HTS), which has tremendous potential to characterize soil communities of EPNs and natural enemies of EPNs. Here, for the first time, we compared qPCR and HTS to characterize EPN food webs. The frequency and abundance of 10 EPN species and 13 organisms associated with EPNs from 50 orchard and natural area sites in two ecoregions of Portugal were evaluated using qPCR tools, and results were published in 2019. We applied an HTS approach to analyze frozen DNA samples from 36 sites in that study. Universal primers targeting ITS1 were used for nematode detection. All EPN species detected by qPCR were also detected by HTS. The EPN species and nearly all free-living nematodes detected by both processes were highly correlated (P < 0.01). Steinernema feltiae, the dominant EPN species, was detected by HTS in 55% more sites than by qPCR. HTS also detected more EPN species than did qPCR. Sample accuracy, measured by the fit of Taylor's Power Law to data from each method, was significantly better using HTS (r² = 0.95, P < 0.01) than qPCR (r² = 0.76, P < 0.01). The effect of biotic and abiotic variables on individual EPN species did not differ according to ANOVA and multiple regression analyses of both data sets while the drivers of EPN community structure did not differ when analyzing either data set with CCA. Our results combined with decreasing costs of metabarcoding, suggest that HTS may provide the most cost-effective and accurate means of assessing soil food webs of methods currently available.

昆虫致病线虫（EPN）广泛分布在除南极洲以外的所有大陆的土壤中。评估一个生态区域中的EPN群落结构可以帮助揭示其对重要农作物害虫的生物防治潜力。检测土壤样品中EPN的常用方法包括用定点昆虫诱饵，直接观察提取的线虫或通过qPCR使用物种特异性引物-探针组合。对高通量测序（HTS）的使用研究较少，这在表征EPNs的土壤群落和EPNs的天敌方面具有巨大潜力。在这里，我们第一次比较了qPCR和HTS来表征EPN食物网。使用qPCR工具评估了来自葡萄牙两个生态区的50个果园和自然区站点的10个EPN种类和13个与EPN相关的生物的频率和丰度，并于2019年发表了结果。我们采用HTS方法分析了来自冰冻DNA的冷冻DNA样品该研究中有36个站点。靶向ITS1的通用引物用于线虫检测。通过qPCR检测到的所有EPN种类也通过HTS检测。这两个过程检测到的EPN种类和几乎所有的自由生存线虫都高度相关（P  <0.01）。用HTS检测到，最主要的EPN物种为Steinernema feeliae，比qPCR检测的多55％。与qPCR相比，HTS还检测到更多的EPN种类。使用HTS（r ²  = 0.95，P  <0.01）通过泰勒幂定律对每种方法的数据进行拟合所测量的样品准确度明显优于qPCR（r ²  = 0.76，P <0.01）。根据ANOVA和两个数据集的多元回归分析，生物变量和非生物变量对单个EPN物种的影响没有差异，而使用CCA分析任一数据集时，EPN群落结构的驱动因素也没有差异。我们的结果与降低元条形码的成本相结合，表明HTS可能提供评估当前可用方法的土壤食物网的最具成本效益和最准确的方法。