Nikki Freed, Adam N. H. Smith, Georgia L Breckell, James Dale, O. Silander
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We calibrate the accuracy of this method by comparing the characteristics of reads matching the ground-truth host genome (rat) to those matching non-rat non-microbial taxa (i.e. stomach content) and show that at the family-level taxon assignments are approximately 97.5% accurate. Some inaccuracies may arise from biases in sequence databases, for example due to overrepresentation of DNA sequences from commonly studied species. We suggest a means to decrease the effects of database biases on inferring taxon membership when using metagenomic approaches. Finally, we implement a constrained ordination analysis and show that it is possible to identify the sampling location of an individual rat within tens of kilometres based on stomach contents alone. This work establishes proof-of-principle for long-read metagenomic methods in quantitative analysis of the stomach contents of a terrestrial mammal. 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引用次数: 0
摘要
:准确测定动物日粮很困难。分子条形码或元基因组学等方法为定量、灵敏地检测不同类群提供了一种可行的方法。在这里,我们展示了利用便携式牛津纳米孔技术公司(ONT)MinION 进行元基因组测序,可以快速、低成本地量化胃内容物中的动物、植物和真菌成分。我们采用无扩增方法对 24 只野生捕获的大鼠的胃内容物进行了分析。我们保守地鉴定出胃内容物来自九个门的 50 多个分类目,包括植物、脊椎动物、无脊椎动物和真菌。这突显了使用这种方法可以识别的分类群范围之广。我们通过比较与真实宿主基因组(大鼠)相匹配的读数特征和与非大鼠非微生物类群(即胃内容物)相匹配的读数特征来校准这种方法的准确性,结果表明在科一级的类群分配准确率约为 97.5%。一些不准确性可能是由于序列数据库的偏差造成的,例如由于来自常见研究物种的 DNA 序列所占比例过高。我们提出了一种方法,可以在使用元基因组方法时减少数据库偏差对推断分类群成员资格的影响。最后,我们实施了一项受限排序分析,结果表明,仅凭胃内容物就能确定数十公里范围内大鼠个体的采样位置。这项研究为用长读元基因组方法对陆生哺乳动物的胃内容物进行定量分析提供了原理证明。我们的研究表明,即使专业技能有限,也可以利用简单、无扩增的工作流程和相对廉价、易于使用的新一代测序方法对胃内容物进行定量分析。随着 ONT 测序准确性和通量的不断提高,以及基因组数据库的不断完善,对胃内容物以及动物膳食进行定量分析的元基因组方法将成为未来的一种重要方法。
Nanopore sequencing of metagenomic DNA from rat stomach contents to infer diet
: Accurate determination of animal diets is difficult. Methods such as molecular barcoding or metagenomics offer a promising approach allowing quantitative and sensitive detection of different taxa. Here we show that rapid and inexpensive quantification of animal, plant, and fungal content from stomach contents is possible through metagenomic sequencing with the portable Oxford Nanopore Technologies (ONT) MinION. Using an amplification-free approach, we profile the stomach contents from 24 wild-caught rats. We conservatively identify stomach contents from over 50 taxonomic orders, ranging across nine phyla, including plants, vertebrates, invertebrates, and fungi. This highlights the wide range of taxa that can be identified using this approach. We calibrate the accuracy of this method by comparing the characteristics of reads matching the ground-truth host genome (rat) to those matching non-rat non-microbial taxa (i.e. stomach content) and show that at the family-level taxon assignments are approximately 97.5% accurate. Some inaccuracies may arise from biases in sequence databases, for example due to overrepresentation of DNA sequences from commonly studied species. We suggest a means to decrease the effects of database biases on inferring taxon membership when using metagenomic approaches. Finally, we implement a constrained ordination analysis and show that it is possible to identify the sampling location of an individual rat within tens of kilometres based on stomach contents alone. This work establishes proof-of-principle for long-read metagenomic methods in quantitative analysis of the stomach contents of a terrestrial mammal. We show that stomach content can be quantified even with limited expertise using a simple, amplification free workflow and a relatively inexpensive and accessible next generation sequencing method. Continued increases in the accuracy and throughput of ONT sequencing, along with improved genomic databases, suggests that a metagenomic approach for quantification of stomach contents, and by proxy animal diets, will become an important method in the future.