Dataset Information

DNA Accounting: Tallying Genomes to Detect Adulterated Saffron.

ABSTRACT: The EU General Food Law not only aims at ensuring food safety but also to 'prevent fraudulent or deceptive practices; the adulteration of food; and any other practices which may mislead the consumer'. Especially the partial or complete, deliberate, and intentional substitution of valuable ingredients (e.g., Saffron) for less valuable ones is of concern. Due to the variety of products on the market an approach to detect food adulteration that works well for one species may not be easily applicable to another. Here we present a broadly applicable approach for the detection of substitution of biological materials based on digital PCR. By simultaneously measuring and forecasting the number of genome copies in a sample, fraud is detectable as a discrepancy between these two values. Apart from the choice of target gene, the procedure is identical across all species. It is scalable, rapid, and has a high dynamic range. We provide proof of concept by presenting the analysis of 141 samples of Saffron (Crocus sativus) from across the European market by DNA accounting and the verification of these results by NGS analysis.

SUBMITTER: Lievens A

PROVIDER: S-EPMC8624925 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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DNA Accounting: Tallying Genomes to Detect Adulterated Saffron.

Lievens Antoon A Paracchini Valentina V Pietretti Danilo D Garlant Linda L Maquet Alain A Ulberth Franz F

Foods (Basel, Switzerland) 20211103 11

The EU General Food Law not only aims at ensuring food safety but also to 'prevent fraudulent or deceptive practices; the adulteration of food; and any other practices which may mislead the consumer'. Especially the partial or complete, deliberate, and intentional substitution of valuable ingredients (e.g., Saffron) for less valuable ones is of concern. Due to the variety of products on the market an approach to detect food adulteration that works well for one species may not be easily applicabl ...[more]

PMID: 34828951

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Project description:BackgroundGenomes store information for building and maintaining organisms. Complete sequencing of many genomes provides the opportunity to study and compare global information properties of those genomes.ResultsWe have analyzed aspects of the information content of Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana, Saccharomyces cerevisiae, and Escherichia coli (K-12) genomes. Virtually all possible (> 98%) 12 bp oligomers appear in vertebrate genomes while < 2% of 19 bp oligomers are present. Other species showed different ranges of > 98% to < 2% of possible oligomers in D. melanogaster (12-17 bp), C. elegans (11-17 bp), A. thaliana (11-17 bp), S. cerevisiae (10-16 bp) and E. coli (9-15 bp). Frequencies of unique oligomers in the genomes follow similar patterns. We identified a set of 2.6 M 15-mers that are more than 1 nucleotide different from all 15-mers in the human genome and so could be used as probes to detect microbes in human samples. In a human sample, these probes would detect 100% of the 433 currently fully sequenced prokaryotes and 75% of the 3065 fully sequenced viruses. The human genome is significantly more compact in sequence space than a random genome. We identified the most frequent 5- to 20-mers in the human genome, which may prove useful as PCR primers. We also identified a bacterium, Anaeromyxobacter dehalogenans, which has an exceptionally low diversity of oligomers given the size of its genome and its GC content. The entropy of coding regions in the human genome is significantly higher than non-coding regions and chromosomes. However chromosomes 1, 2, 9, 12 and 14 have a relatively high proportion of coding DNA without high entropy, and chromosome 20 is the opposite with a low frequency of coding regions but relatively high entropy.ConclusionMeasures of the frequency of oligomers are useful for designing PCR assays and for identifying chromosomes and organisms with hidden structure that had not been previously recognized. This information may be used to detect novel microbes in human tissues.

Dataset Information

DNA Accounting: Tallying Genomes to Detect Adulterated Saffron.

Publications

DNA Accounting: Tallying Genomes to Detect Adulterated Saffron.

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