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Fish species identification in mixed samples using DNA sequencing and proteomics-based approaches

ABSTRACT: Replacement of high-value fish species with cheaper varieties or mislabelling of food unfit for human consumption is a global problem violating both consumers’ rights and safety. For distinguishing fish species in pure samples, DNA approaches are available; however, authentication and quantification of fish species in mixtures remains a challenge. In the present study, a novel high-throughput shotgun DNA sequencing approach applying masked reference libraries was developed and used for authentication and abundance calculations of fish species in mixed samples. Results demonstrate that the analytical protocol presented here can discriminate and predict relative abundances of different fish species in mixed samples with high accuracy. In addition to DNA analyses, shotgun proteomics tools based on direct spectra comparisons were employed on the same mixture. Similar to the DNA approach, the identification of individual fish species and the estimation of their respective relative abundances in a mixed sample also were feasible. Furthermore, the data obtained indicated that DNA sequencing using masked libraries predicted species-composition of the fish mixture with higher specificity, while at a taxonomic family level, relative abundances of the different species in the fish mixture were predicted with slightly higher accuracy using proteomics tools. Taken together, the results demonstrate that both DNA and protein-based approaches presented here can be used to efficiently tackle current challenges in feed and food authentication analyses.

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Danio Rerio (ncbitaxon:7955)

SUBMITTER: Josef Daniel Rasinger

PROVIDER: MSV000087017 | MassIVE | Tue Mar 09 07:57:00 GMT 2021

REPOSITORIES: MassIVE

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Project description:Background: Food supply is a major factor influencing growth rates in animals. This has important implications for both natural and farmed fish populations, since food restriction may difficult reproduction. However, a study on the effects of food supply on the development of juvenile gonads has never been transcriptionally described in fish. Methods and Findings: This study investigated the consequences of growth on gonadal transcriptome of European sea bass in: 1) 4-month-old sexually undifferentiated fish, comparing the gonads of fish with the highest vs. the lowest growth, to explore a possible link between transcriptome and future sex, and 2) testis from 11-month-old juveniles where growth had been manipulated through changes in food supply. The four groups used were: i) sustained fast growth, ii) sustained slow growth, iii) accelerated growth, iv) decelerated growth. The transcriptome of undifferentiated gonads was not drastically affected by initial natural differences in growth. Further, changes in the expression of genes associated with protein turnover were seen, favoring catabolism in slow-growing fish and anabolism in fast-growing fish. Moreover, while fast-growing fish took energy from glucose, as deduced from the pathways affected and the analysis of protein-protein interactions examined, in slow-growing fish lipid metabolism and gluconeogenesis was favored. Interestingly, the highest transcriptomic differences were found when forcing initially fast-growing fish to decelerate their growth, while accelerating growth of initially slow-growing fish resulted in full transcriptomic convergence with sustained fast-growing fish. Conclusions: Food availability during sex differentiation shapes the juvenile testis transcriptome, as evidenced by adaptations to different energy balances. Remarkably, this occurs in absence of major histological changes in the testis. Thus, fish are able to recover transcriptionally their testes if they are provided with enough food supply during sex differentiation; however, an initial fast growth does not represent any advantage in terms of transcriptional fitness if later food becomes scarce.

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Fish species identification in mixed samples using DNA sequencing and proteomics-based approaches

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