MassIVE MSV000087017 - Fish species identification in mixed samples using DNA sequencing and a proteomics-based approaches : With globally rising demands for food and increasing pressure on over-exploited food chains, feed and food adulteration has become an emerging problem, threatening both food security and food safety. In this context, development of sensitive molecular tools for food and feed authentication are key; on the one hand to ensure correct labelling of products to remedy safety concerns, on the other hand to tackle fraud such as the replacement of expensive food fish species with cheaper ones or with species that are endangered or unfit for human consumption. DNA metabarcoding approaches for distinguishing fish species in pure samples already are available; however, detection and quantification of fish species in highly processed and mixed products is still a challenge. In the present study, we use high throughput DNA sequencing and shot-gun proteomics to detect and differentiate seven fish species (Melanogrammus aeglefinus, Oreochromis niloticu, Gadus morhua, Salmo salar, Esox Lucius, Pangasianodon hypophthalmus, Xiphophorus maculatus), and to quantify the content of a mixture of three fish species. The results demonstrate that shotgun DNA sequencing in combination with mapping against masked reference genomes can be a useful tool for the identification of fish species and the relative amounts of each species in a mixed sample. Shotgun proteomics based on direct spectral comparison of tandem mass spectra allowed for the construction of phylogenetic trees which separated the seven fish samples accurately without using any genetic information. Spectral libraries built with tandem mass spectra allowed for the detection of species and estimation of quantities in mixed fish samples.

Bibliographic Details
Main Author: Rasinger, Josef Daniel
Format: Dataset
Language:English
Published: MassIVE 2021
Subjects:
Online Access:https://dx.doi.org/10.25345/c5fz3b
https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?accession=MSV000087017
Description
Description not available.