Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-7969
Authors: Ripp, Fabian
Krombholz, Christopher Felix
Liu, Yongchao
Weber, Mathias
Schäfer, Anne
Schmidt, Bertil
Köppel, Rene
Hankeln, Thomas
Title: All-Food-Seq (AFS) : a quantifiable screen for species in biological samples by deep DNA sequencing
Online publication date: 13-Oct-2022
Year of first publication: 2014
Language: english
Abstract: 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.
DDC: 570 Biowissenschaften
570 Life sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 08 Physik, Mathematik u. Informatik
FB 10 Biologie
Place: Mainz
ROR: https://ror.org/023b0x485
DOI: http://doi.org/10.25358/openscience-7969
Version: Published version
Publication type: Zeitschriftenaufsatz
License: CC BY
Information on rights of use: https://creativecommons.org/licenses/by/2.0/
Journal: BMC genomics
15
Pages or article number: Art. 639
Publisher: BioMed central
Publisher place: London
Issue date: 2014
ISSN: 1471-2164
Publisher URL: http://dx.doi.org/10.1186/1471-2164-15-639
Publisher DOI: 10.1186/1471-2164-15-639
Appears in collections:DFG-OA-Publizieren (2012 - 2017)

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