Evaluating the usefulness of next-generation sequencing for herb authentication.

Authenticity testing Barcodes Food Herbs Next generation sequencing

Journal

Food chemistry. Molecular sciences
ISSN: 2666-5662
Titre abrégé: Food Chem (Oxf)
Pays: England
ID NLM: 9918367084406676

Informations de publication

Date de publication:
30 Dec 2021
Historique:
received: 06 05 2021
revised: 13 09 2021
accepted: 02 10 2021
entrez: 13 4 2022
pubmed: 14 4 2022
medline: 14 4 2022
Statut: epublish

Résumé

Food authentication is a rapidly growing field driven by increasing public awareness of food quality and safety. Foods containing herbs are particularly prone to industrial fraud and adulteration. Several methodologies are currently used to evaluate food authenticity. DNA-based technologies have increased focus, with DNA barcoding the most widely used. DNA barcoding is based on the sequencing and comparison of orthologous DNA regions from all species in a sample, but the approach is limited by its low resolution to distinguish closely-related species. Here we developed a customised database and bioinformatics pipeline (Herbs Authenticity - GitHub) to identify herbal ingredients implemented as a metagenomics approach for plant-derived product authenticity testing. We evaluated the accuracy of the method by using publicly available plant genomes and databases to allow the construction of our customised database barcodes, which were also complemented with entries from publicly available resources (iBOL and ENA). The pipeline performance was then tested with new 47 de novo partly sequenced whole plant genomes or barcodes as query sequences. Our results show that using our mapping algorithm with the customised barcode database correctly identifies the main components of a wide range of plant-derived samples, albeit with variable additional noise across samples depending on the tested samples and barcodes. Our result also show that at the current stage the usefulness of metagenomics is limited by the availability of reference sequences and the needed sequencing depth. However, this method shows promise for evaluating the authenticity of different herbal products provided that the method is further refined to increase the qualitative and quantitative accuracy.

Identifiants

pubmed: 35415645
doi: 10.1016/j.fochms.2021.100044
pii: S2666-5662(21)00035-6
pmc: PMC8991511
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100044

Informations de copyright

© 2021 The Author(s).

Déclaration de conflit d'intérêts

The authors declare no conflict of interest. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Références

J AOAC Int. 2018 Jan 1;101(1):162-169
pubmed: 29202918
Mol Ecol. 2016 Apr;25(7):1423-8
pubmed: 26821259
Food Chem. 2019 Apr 25;278:144-162
pubmed: 30583355
Biol Rev Camb Philos Soc. 2015 Feb;90(1):157-66
pubmed: 24666563
Sci Rep. 2015 Feb 12;5:8348
pubmed: 25672218
BMC Bioinformatics. 2018 Aug 29;19(1):307
pubmed: 30157759
Philos Trans R Soc Lond B Biol Sci. 2016 Sep 5;371(1702):
pubmed: 27481790
Plant Biotechnol J. 2016 Jan;14(1):8-21
pubmed: 26079154
J Agric Food Chem. 2019 Apr 10;67(14):3854-3864
pubmed: 30901215
Nat Rev Genet. 2016 May 17;17(6):333-51
pubmed: 27184599
Food Chem. 2016 Nov 1;210:551-7
pubmed: 27211681
Food Chem. 2018 Feb 1;240:767-774
pubmed: 28946341

Auteurs

Anna Delgado-Tejedor (A)

Research Group for Genomic Epidemiology, Division for Global Surveillance, National Food Institute, Technical University of Denmark, 2800 Kgs Lyngby, Denmark.

Pimlapas Leekitcharoenphon (P)

Research Group for Genomic Epidemiology, Division for Global Surveillance, National Food Institute, Technical University of Denmark, 2800 Kgs Lyngby, Denmark.

Frank M Aarestrup (FM)

Research Group for Genomic Epidemiology, Division for Global Surveillance, National Food Institute, Technical University of Denmark, 2800 Kgs Lyngby, Denmark.

Saria Otani (S)

Research Group for Genomic Epidemiology, Division for Global Surveillance, National Food Institute, Technical University of Denmark, 2800 Kgs Lyngby, Denmark.

Classifications MeSH