Project description:Here we propose that using shotgun sequencing to examine food leads to accurate authentication of ingredients and detection of contaminants. To demonstrate this, we developed a bioinformatic pipeline, FASER (Food Authentication from SEquencing Reads), designed to resolve the relative composition of mixtures of eukaryotic species using RNA or DNA sequencing. Our comprehensive database includes >6000 plants and animals that may be present in food. FASER accurately identified eukaryotic species with 0.4% median absolute difference between observed and expected proportions on sequence data from various sources including sausage meat, plants, and fish. FASER was applied to 31 high protein powder raw factory ingredient total RNA samples. The samples mostly contained the expected source ingredient, chicken, while three samples unexpectedly contained pork and beef. Our results demonstrate that DNA/RNA sequencing of food ingredients, combined with a robust analysis, can be used to find contaminants and authenticate food ingredients in a single assay.
Project description:•MinION DNA metabarcoding is a promising tool for species identification in food.•MinION and Illumina MiSeq sequencing platforms perform equally accurate.•Species identification with MinION sequencing requires dedicated bioinformatics.
Project description:Truffles are certainly the most expensive mushrooms; the price depends primarily on the species and secondly on the origin. Because of the price differences for the truffle species, food fraud is likely to occur, and the visual differentiation is difficult within the group of white and within the group of black truffles. Thus, the aim of this study was to develop a reliable method for the authentication of five commercially relevant truffle species via Fourier transform near-infrared (FT-NIR) spectroscopy as an easy to handle approach combined with chemometrics. NIR-data from 75 freeze-dried fruiting bodies were recorded. Various spectra pre-processing techniques and classification methods were compared and validated using nested cross-validation. For the white truffle species, the most expensive Tuber magnatum could be differentiated with an accuracy of 100% from Tuber borchii. Regarding the black truffle species, the relatively expensive Tuber melanosporum could be distinguished from Tuber aestivum and the Chinese truffles with an accuracy of 99%. Since the most expensive Italian Tuber magnatum is highly prone to fraud, the origin was investigated and Italian T. magnatum truffles could be differentiated from non-Italian T. magnatum truffles by 83%. Our results demonstrate the potential of FT-NIR spectroscopy for the authentication of truffle species.
Project description:Viable pathogenic bacteria are major biohazards that pose a significant threat to food safety. Despite the recent developments in detection platforms, multiplex identification of viable pathogens in food remains a major challenge. A novel strategy is developed through direct metatranscriptome RNA-seq and multiplex RT-PCR amplicon sequencing on Nanopore MinION to achieve real-time multiplex identification of viable pathogens in food. Specifically, this study reports an optimized universal Nanopore sample extraction and library preparation protocol applicable to both Gram-positive and Gram-negative pathogenic bacteria, demonstrated using a cocktail culture of E. coli O157:H7, Salmonella enteritidis, and Listeria monocytogenes, which were selected based on their impact on economic loss or prevalence in recent outbreaks. Further evaluation and validation confirmed the accuracy of direct metatranscriptome RNA-seq and multiplex RT-PCR amplicon sequencing using Sanger sequencing and selective media. The study also included a comparison of different bioinformatic pipelines for metatranscriptomic and amplicon genomic analysis. MEGAN without rRNA mapping showed the highest accuracy of multiplex identification using the metatranscriptomic data. EPI2ME also demonstrated high accuracy using multiplex RT-PCR amplicon sequencing. In addition, a systemic comparison was drawn between Nanopore sequencing of the direct metatranscriptome RNA-seq and RT-PCR amplicons. Both methods are comparable in accuracy and time. Nanopore sequencing of RT-PCR amplicons has higher sensitivity, but Nanopore metatranscriptome sequencing excels in read length and dealing with complex microbiome and non-bacterial transcriptome backgrounds.
Project description:BACKGROUND:DNA-based testing has been gaining acceptance as a tool for authentication of a wide range of food products; however, its applicability for testing of herbal supplements remains contentious. METHODS:We utilized Sanger and Next-Generation Sequencing (NGS) for taxonomic authentication of fifteen herbal supplements representing three different producers from five medicinal plants: Echinacea purpurea, Valeriana officinalis, Ginkgo biloba, Hypericum perforatum and Trigonella foenum-graecum. Experimental design included three modifications of DNA extraction, two lysate dilutions, Internal Amplification Control, and multiple negative controls to exclude background contamination. Ginkgo supplements were also analyzed using HPLC-MS for the presence of active medicinal components. RESULTS:All supplements yielded DNA from multiple species, rendering Sanger sequencing results for rbcL and ITS2 regions either uninterpretable or non-reproducible between the experimental replicates. Overall, DNA from the manufacturer-listed medicinal plants was successfully detected in seven out of eight dry herb form supplements; however, low or poor DNA recovery due to degradation was observed in most plant extracts (none detected by Sanger; three out of seven-by NGS). NGS also revealed a diverse community of fungi, known to be associated with live plant material and/or the fermentation process used in the production of plant extracts. HPLC-MS testing demonstrated that Ginkgo supplements with degraded DNA contained ten key medicinal components. CONCLUSION:Quality control of herbal supplements should utilize a synergetic approach targeting both DNA and bioactive components, especially for standardized extracts with degraded DNA. The NGS workflow developed in this study enables reliable detection of plant and fungal DNA and can be utilized by manufacturers for quality assurance of raw plant materials, contamination control during the production process, and the final product. Interpretation of results should involve an interdisciplinary approach taking into account the processes involved in production of herbal supplements, as well as biocomplexity of plant-plant and plant-fungal biological interactions.
Project description:Phenolic compounds are well-known bioactive compounds in plants that can have a protective role against cancers, cardiovascular diseases and many other diseases. To promote local food development, a comprehensive overview of the phenolic compounds' composition and their impact on human health from typical Mediterranean plants such as Punica granatum L., Ziziphus jujuba Mill., Arbutus unedo L., Celtis australis L., Ficus carica L., Cynara cardunculus var. Scolymus L. is provided. Moreover, the potential use of these data for authenticity determination is discussed. Some of the plants' phenolic compounds and their impact to human health are very well determined, while for others, the data are scarce. However, in all cases, more data should be available about the content, profile and health impacts due to a high variation of phenolic compounds depending on genetic and environmental factors. Quantifying variation in phenolic compounds in plants relative to genetic and environmental factors could be a useful tool in food authentication control. More comprehensive studies should be conducted to better understand the importance of phenolic compounds on human health and their variation in certain plants.
Project description:Increasing demand for organic products and their premium prices make them an attractive target for fraudulent malpractices. In this study, a large-scale comparative metabolomics approach was applied to investigate the effect of the agronomic production system on the metabolite composition of carrots and to build statistical models for prediction purposes. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) was applied successfully to predict the origin of the agricultural system of the harvested carrots on the basis of features determined by liquid chromatography-mass spectrometry. When the training set used to build the OPLS-DA models contained samples representative of each harvest year, the models were able to classify unknown samples correctly (100% correct classification). If a harvest year was left out of the training sets and used for predictions, the correct classification rates achieved ranged from 76% to 100%. The results therefore highlight the potential of metabolomic fingerprinting for organic food authentication purposes.
Project description:Although significant progress has recently been made towards realizing the goal of direct nanopore based DNA sequencing , there are still numerous hurdles that need to be overcome. One such hurdle associated with the use of the biological nanopore α-hemolysin (αHL) is the fact that the wild type channel contains three very distinct recognition or sensing regions within the β-barrel [2, 3], making identification of the bases residing within or moving through the pore very difficult. Through site directed mutagenesis, we have been able to selectively remove one of two sensing regions while simultaneously enhancing the third. Our approach has led to the creation of αHL pores containing single sensing zones and provides the basis for engineering αHL pores suitable for direct DNA sequencing.
Project description:We have developed a novel analysis method that can interrogate the authenticity of biological samples used for generation of transcriptome profiles in public data repositories. The method uses RNA sequencing information to reveal mutations in expressed transcripts and subsequently confirms the identity of analysed cells by comparison with publicly available cell-specific mutational profiles. Cell lines constitute key model systems widely used within cancer research, but their identity needs to be confirmed in order to minimise the influence of cell contaminations and genetic drift on the analysis. Using both public and novel data, we demonstrate the use of RNA-sequencing data analysis for cell line authentication by examining the validity of COLO205, DLD1, HCT15, HCT116, HKE3, HT29 and RKO colorectal cancer cell lines. We successfully authenticate the studied cell lines and validate previous reports indicating that DLD1 and HCT15 are synonymous. We also show that the analysed HKE3 cells harbour an unexpected KRAS-G13D mutation and confirm that this cell line is a genuine KRAS dosage mutant, rather than a true isogenic derivative of HCT116 expressing only the wild type KRAS. This authentication method could be used to revisit the numerous cell line based RNA sequencing experiments available in public data repositories, analyse new experiments where whole genome sequencing is not available, as well as facilitate comparisons of data from different experiments, platforms and laboratories. Overall design: RNA-sequencing of three colorectal cancer cell lines (HCT116, HKE3 and RKO) with either three (HCT116, RKO) or four (HKE3) replicates each.
Project description:We have developed a novel analysis method that can interrogate the authenticity of biological samples used for generation of transcriptome profiles in public data repositories. The method uses RNA sequencing information to reveal mutations in expressed transcripts and subsequently confirms the identity of analysed cells by comparison with publicly available cell-specific mutational profiles. Cell lines constitute key model systems widely used within cancer research, but their identity needs to be confirmed in order to minimise the influence of cell contaminations and genetic drift on the analysis. Using both public and novel data, we demonstrate the use of RNA-sequencing data analysis for cell line authentication by examining the validity of COLO205, DLD1, HCT15, HCT116, HKE3, HT29 and RKO colorectal cancer cell lines. We successfully authenticate the studied cell lines and validate previous reports indicating that DLD1 and HCT15 are synonymous. We also show that the analysed HKE3 cells harbour an unexpected KRAS-G13D mutation and confirm that this cell line is a genuine KRAS dosage mutant, rather than a true isogenic derivative of HCT116 expressing only the wild type KRAS. This authentication method could be used to revisit the numerous cell line based RNA sequencing experiments available in public data repositories, analyse new experiments where whole genome sequencing is not available, as well as facilitate comparisons of data from different experiments, platforms and laboratories.