Abstract
Food fraud through species substitution has been reported for edible gastropods, particularly in processed products where morphological identification is not feasible. DNA-based methods have been used to identify gastropod species in food products, but are largely limited to targeted analyses. To address this limitation, we applied, for the first time, an untargeted DNA metabarcoding approach to detect and identify gastropod species in processed foods. Mitochondrial 16S rDNA fragments of approximately 150 bp were analyzed. In 17 of 18 reference samples, taxa were resolved to genus or species level, in agreement with Codex Alimentarius Austriacus guidelines, facilitated by a curated reference database that enables assignments across freshwater, marine, and terrestrial gastropods. Thirteen DNA extract mixtures were analyzed for method validation, yielding few false-negative results for minor components. These likely resulted from primer–template mismatches causing amplification bias. Analysis of 20 commercial food products revealed seven mislabeled samples. The approach is compatible with established in-house metabarcoding assays targeting other animal species and consequently complements broad application across various taxa. This qualitative screening tool is suitable for routine food authentication, supporting supply chain transparency and regulatory monitoring.
Acknowledgements
The authors gratefully acknowledge the excellent cooperation with the Austrian Competence Centre for Feed and Food Quality, Safety and Innovation (FFoQSI GmbH) on this project. This study was funded by the Austrian Agency for Health and Food Safety (AGES), Institute for Food Safety Vienna, Department for Molecular Biology and Microbiology. This article was supported by the Open Access Publishing Fund of the University of Vienna. The funders played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript.
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Declaration of generative AI and AI-assisted technologies in the writing process
During the preparation of this work the author used ChatGPT in order to improve the readability and language of the manuscript. After using this tool, the author reviewed and edited the content as needed and takes full responsibility for the content of the published article.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary information (download PDF )
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Reprints and permissions
About this article
Cite this article
Andronache, J., Cichna-Markl, M., Dobrovolny, S. et al. DNA metabarcoding for food authentication: identification of freshwater, marine, and terrestrial gastropods in commercial food products.
npj Sci Food (2026). https://doi.org/10.1038/s41538-026-00961-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41538-026-00961-x
Source: Ecology - nature.com

