Advertisement

Identification and quantification of meat product ingredients by whole-genome metagenomics (All-Food-Seq)

  • Sören Lukas Hellmann
  • Fabian Ripp
  • Sven-Ernö Bikar
  • Bertil Schmidt
  • Rene Köppel
  • Thomas HankelnEmail author
Original Paper
  • 23 Downloads

Abstract

Complex food matrices bear the risk of intentional or accidental admixture of non-declared species. Moreover, declared components can be present in false proportions, since expensive taxa might be exchanged for cheaper ones. We have previously reported that PCR-free metagenomic sequencing of total DNA extracted from sausage samples combined with bioinformatic analysis (termed All-Food-Seq, AFS) can be a valuable screening tool to identify the taxon composition of food ingredients. Here, we illustrate this principle by analysing regional Doner kebap samples, which revealed unexpected and unlabelled poultry and plant components in three of five cases. In addition, we systematically apply AFS to a broad set of reference meat material of known composition (i.e. reference sausages) to evaluate quantification accuracy and potential limitations. We include a detailed analysis of the effect of different food matrices and the possibility of false-positive sequence read assignment to closely related species, and we compare AFS quantification results to quantitative real-time PCR (qPCR) and droplet digital PCR (ddPCR). AFS emerges as a potent PCR-free screening tool, which can detect multiple target species of different kingdoms of life within a single assay. Mathematical calibration accounting for pronounced matrix effects can significantly improve AFS quantification accuracy. In comparison, AFS performs better than classical qPCR, and is on par with ddPCR.

Keywords

Food metagenomics Species identification Doner Kebap Read mapping Next-generation-sequencing 

Notes

Acknowledgements

TH and SLH gratefully acknowledge funding by the Federal Office for Agriculture and Food (project ID: 2816503814), Johannes Gutenberg University Center for Computational Sciences (CSM) and the Ministry of Justice and for Consumer Safety Rhineland-Palatinate.

Compliance with ethics standards

Conflict of interest

The authors declare that they have no conflict of interest.

Research involving human participants and/or animals

This article does not contain any studies with human and animal subjects.

Supplementary material

217_2019_3404_MOESM1_ESM.docx (29 kb)
Supplementary material 1 (DOCX 29 kb)
217_2019_3404_MOESM2_ESM.docx (136 kb)
Supplementary material 2 (DOCX 136 kb)
217_2019_3404_MOESM3_ESM.xlsx (23 kb)
Supplementary material 3 (XLSX 22 kb)
217_2019_3404_MOESM4_ESM.docx (74 kb)
Supplementary material 4 (DOCX 73 kb)
217_2019_3404_MOESM5_ESM.docx (23 kb)
Supplementary material 5 (DOCX 22 kb)

References

  1. 1.
    German Federal Office for Risk Assessment: Food safety and globalisation—challenges and opportunities (Bundesamt für Risikobewertung) (2019) https://www.bfr.bund.de/en/press_information/2014/13/food_safety_and_globalisation___challenges_and_opportunities-190341.html. Accessed 28 Aug 2019
  2. 2.
    German Federal Office of Consumer Protection and Food Safety (Bundesamt für Verbraucherschutz und Lebensmittelsicherheit) (2019) https://www.bvl.bund.de/DE/Home/homepage_node.html. Accessed 28 Aug 2019
  3. 3.
    German Drug Law (Bundesministerium der Justiz und für Verbraucherschutz: Gesetz über den Verkehr mit Arzneimitteln) (2019) https://www.gesetze-im-internet.de/amg_1976/AMG.pdf. Accessed 28 Aug 2019
  4. 4.
    Swiss Food Legislation (Schweizerisches Bundesgesetz über Lebensmittel und Gebrauchsgegenstände (Lebensmittelgesetz, LMG) vom 20 (2014) https://www.admin.ch/opc/de/official-compilation/2017/249.pdf. Accessed 28 Aug 2019
  5. 5.
    Brodmann PD, Moor D (2003) Sensitive and semi-quantitative TaqManTM real-time polymerase chain reaction systems for the detection of beef (Bos taurus) and the detection of the family Mammalia in food and feed. Meat Sci 65:599–607.  https://doi.org/10.1016/S0309-1740(02)00253-X CrossRefPubMedGoogle Scholar
  6. 6.
    Zhang C-L, Fowler MR, Scott NW et al (2007) A TaqMan real-time PCR system for the identification and quantification of bovine DNA in meats, milks and cheeses. Food Control 18:1149–1158.  https://doi.org/10.1016/J.FOODCONT.2006.07.018 CrossRefGoogle Scholar
  7. 7.
    Köppel R, Ruf J, Zimmerli F, Breitenmoser A (2008) Multiplex real-time PCR for the detection and quantification of DNA from beef, pork, chicken and turkey. Eur Food Res Technol 227:1199–1203.  https://doi.org/10.1007/s00217-008-0837-7 CrossRefGoogle Scholar
  8. 8.
    Köppel R, Ruf J, Rentsch J (2011) Multiplex real-time PCR for the detection and quantification of DNA from beef, pork, horse and sheep. Eur Food Res Technol 232:151–155.  https://doi.org/10.1007/s00217-010-1371-y CrossRefGoogle Scholar
  9. 9.
    Köppel R, Eugster A, Ruf J, Rentsch J (2012) Quantification of meat proportions by measuring DNA contents in raw and boiled sausages using matrix-adapted calibrators and multiplex real-time PCR. J AOAC Int 95:494–499.  https://doi.org/10.5740/jaoacint.11-115 CrossRefPubMedGoogle Scholar
  10. 10.
    Ulca P, Balta H, Çağın İ, Senyuva HZ (2013) Meat species identification and Halal authentication using PCR analysis of raw and cooked traditional Turkish foods. Meat Sci 94:280–284.  https://doi.org/10.1016/j.meatsci.2013.03.008 CrossRefPubMedGoogle Scholar
  11. 11.
    Floren C, Wiedemann I, Brenig B et al (2015) Species identification and quantification in meat and meat products using droplet digital PCR (ddPCR). Food Chem 173:1054–1058.  https://doi.org/10.1016/j.foodchem.2014.10.138 CrossRefPubMedGoogle Scholar
  12. 12.
    Song K-Y, Hwang HJ, Kim JH (2017) Ultra-fast DNA-based multiplex convection PCR method for meat species identification with possible on-site applications. Food Chem 229:341–346.  https://doi.org/10.1016/j.foodchem.2017.02.085 CrossRefGoogle Scholar
  13. 13.
    Köppel R, Ganeshan A, Weber S et al (2019) Duplex digital PCR for the determination of meat proportions of sausages containing meat from chicken, turkey, horse, cow, pig and sheep. Eur Food Res Technol 245:853–862.  https://doi.org/10.1007/s00217-018-3220-3 CrossRefGoogle Scholar
  14. 14.
    Markoulatos P, Siafakas N, Moncany M (2002) Multiplex polymerase chain reaction: a practical approach. J Clin Lab Anal 16:47–51.  https://doi.org/10.1002/jcla.2058 CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Berry D, Ben Mahfoudh K, Wagner M, Loy A (2011) Barcoded primers used in multiplex amplicon pyrosequencing bias amplification. Appl Environ Microbiol 77:7846–7849.  https://doi.org/10.1128/AEM.05220-11 CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Tedersoo L, Anslan S, Bahram M et al (2015) Shotgun metagenomes and multiple primer pair-barcode combinations of amplicons reveal biases in metabarcoding analyses of fungi. MycoKeys 10:1–43.  https://doi.org/10.3897/mycokeys.10.4852 CrossRefGoogle Scholar
  17. 17.
    Sze MA, Schloss PD (2019) The Impact of DNA Polymerase and Number of Rounds of Amplification in PCR on 16S rRNA Gene Sequence Data. mSphere 4:e00163–19.  https://doi.org/10.1128/msphere.00163-19
  18. 18.
    Ripp F, Krombholz C, Liu Y et al (2014) All-Food-Seq (AFS): a quantifiable screen for species in biological samples by deep DNA sequencing. BMC Genomics 15:639.  https://doi.org/10.1186/1471-2164-15-639 CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Liu Y, Ripp F, Koeppel R et al (2017) AFS: identification and quantification of species composition by metagenomic sequencing. Bioinformatics 33:btw822.  https://doi.org/10.1093/bioinformatics/btw822 CrossRefGoogle Scholar
  20. 20.
    Eugster A, Ruf J, Rentsch J, Köppel R (2009) Quantification of beef, pork, chicken and turkey proportions in sausages: use of matrix-adapted standards and comparison of single versus multiplex PCR in an interlaboratory trial. Eur Food Res Technol 230:55–61.  https://doi.org/10.1007/s00217-009-1138-5 CrossRefGoogle Scholar
  21. 21.
    FASTQC (2019) A quality control tool for high throughput sequence data. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/. Accessed 28 Aug 2019
  22. 22.
    Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120.  https://doi.org/10.1093/bioinformatics/btu170 CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    BBTools (2019) A suite of fast, multithreaded bioinformatics tools designed for analysis of DNA and RNA sequence data. https://sourceforge.net/projects/bbmap/. Accessed 28 Aug 2019
  24. 24.
    Kumar S, Stecher G, Suleski M, Hedges SB (2017) TimeTree: a resource for timelines, timetrees, and divergence times. Mol Biol Evol 34:1812–1819.  https://doi.org/10.1093/molbev/msx116 CrossRefPubMedGoogle Scholar
  25. 25.
    Armbruster DA, Pry T (2008) Limit of blank, limit of detection and limit of quantitation. Clin Biochem Rev 29(Suppl 1):S49–S52PubMedPubMedCentralGoogle Scholar
  26. 26.
    Marking of “doner kebab” and “similar” products by bulk delivery (2019) (Kenntlichmachung von „Döner Kebab“und „ähnlichen“Erzeugnissen bei loser Abgabe. Bayerisches Landesamt für Gesundheit und Lebensmittelsicherheit). https://www.lgl.bayern.de/downloads/lebensmittel/doc/merkblatt_doener_kebab.pdf. Accessed 28 Aug 2019
  27. 27.
    The composition and labelling of doner kebabs (2019) LACORS. https://www.ihsti.com/lacors/ContentDetails.aspx?id=21001. Accessed 28 Aug 2019
  28. 28.
    Frequently minced meat and additives in doner kebab (2019) (Häufig Fleischbrät und Zusatzstoffe im Döner. Norddeutscher Rundfunk). https://www.ndr.de/ratgeber/verbraucher/Haeufig-Fleischbraet-und-Zusatzstoffe-im-Doener,doener164.html. Accessed 28 Aug 2019
  29. 29.
    Cai Y, Li X, Lv R et al (2014) Quantitative analysis of pork and chicken products by droplet digital PCR. Biomed Res Int 2014:810209.  https://doi.org/10.1155/2014/810209 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Organismic and Molecular Evolution, Molecular Genetics and Genome AnalysisJohannes Gutenberg University MainzMainzGermany
  2. 2.MVZ Labor VolkmannKarlsruheGermany
  3. 3.StarSEQ GmbHMainzGermany
  4. 4.Institute of InformaticsJohannes Gutenberg University MainzMainzGermany
  5. 5.Official Food Control Authority of the Canton ZurichZurichSwitzerland

Personalised recommendations