Nikki Freed, Adam N. H. Smith, Georgia L Breckell, James Dale, O. Silander
{"title":"Nanopore sequencing of metagenomic DNA from rat stomach contents to infer diet","authors":"Nikki Freed, Adam N. H. Smith, Georgia L Breckell, James Dale, O. Silander","doi":"10.20417/nzjecol.47.3554","DOIUrl":null,"url":null,"abstract":": 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.","PeriodicalId":503053,"journal":{"name":"New Zealand Journal of Ecology","volume":"32 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Zealand Journal of Ecology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20417/nzjecol.47.3554","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
: 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.