All-Food-Seq (AFS): a quantifiable screen for species in biological samples by deep DNA sequencing

作者：Ripp Fabian; Krombholz Christopher Felix; Liu Yongchao; Weber Mathias; Schaefer Anne; Schmidt Bertil; Koeppel Rene; Hankeln Thomas^*

来源：BMC Genomics, 2014, 15(1): 639.

DOI：10.1186/1471-2164-15-639

• Illumina
• Next-generation sequencing
• Real-time PCR
• Species identification
• Metagenomics

Background: DNA-based methods like PCR efficiently identify and quantify the taxon composition of complex biological materials, but are limited to detecting species targeted by the choice of the primer assay. We show here how untargeted deep sequencing of foodstuff total genomic DNA, followed by bioinformatic analysis of sequence reads, facilitates highly accurate identification of species from all kingdoms of life, at the same time enabling quantitative measurement of the main ingredients and detection of unanticipated food components.
Results: Sequence data simulation and real-case Illumina sequencing of DNA from reference sausages composed of mammalian (pig, cow, horse, sheep) and avian (chicken, turkey) species are able to quantify material correctly at the 1% discrimination level via a read counting approach. An additional metagenomic step facilitates identification of traces from animal, plant and microbial DNA including unexpected species, which is prospectively important for the detection of allergens and pathogens.
Conclusions: Our data suggest that deep sequencing of total genomic DNA from samples of heterogeneous taxon composition promises to be a valuable screening tool for reference species identification and quantification in biosurveillance applications like food testing, potentially alleviating some of the problems in taxon representation and quantification associated with targeted PCR-based approaches.

• 出版日期2014-7-31