The future of NGS (Next Generation Sequencing) analysis in testing food authenticity

Abstract The authenticity of foodstuffs is an important issue for consumers, regulators, producers and processors, as fraudulent practices can negatively affect consumer confidence and safety, as well as the operating models of legitimate businesses. This review provides an overview of the current landscape of Next Generation Sequencing (NGS) applications for food authenticity, and looks to identify the potential future developments for this technology. Specific areas highlighted include the range of NGS platforms and sequence databases available, validation of NGS, and limitations and appropriate uses of these technologies. Many NGS platforms are available, with different properties (such as sequence read length and output) suited to different analyses. Despite this wealth of options, more platforms are being brought out frequently, and advances such as reduced error rate will enable their expanded use for food authenticity. This rapid expansion in the use of DNA sequencing has led to an equally rapid enlargement in sequence databases, and the construction of contemporaneous, authenticated databases may be a useful innovation for the application of NGS to authenticity. Such applications will require robust quality control criteria and proficiency testing schemes, both of which are being developed. Despite several caveats, for example around effective extraction and amplification of DNA, NGS is a strong candidate to become a valuable aid or even the technology of choice to achieve regulatory compliance and reputation protection in a number of food fraud situations, particularly for highly complex food matrices.

[1]  Yongchao Liu,et al.  All-Food-Seq (AFS): a quantifiable screen for species in biological samples by deep DNA sequencing , 2013, BMC Genomics.

[2]  J. Shay,et al.  Comparison of DNA Quantification Methods for Next Generation Sequencing , 2016, Scientific Reports.

[3]  Wensheng Huang,et al.  A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food , 2017, PloS one.

[4]  Yongchao Liu,et al.  AFS: identification and quantification of species composition by metagenomic sequencing , 2017, Bioinform..

[5]  Kang Ning,et al.  Assessment of quality control approaches for metagenomic data analysis , 2014, Scientific Reports.

[6]  Jeffrey D Wolt,et al.  The Regulatory Status of Genome‐edited Crops , 2015, Plant biotechnology journal.

[7]  A. Sajantila,et al.  Expansion of Microbial Forensics , 2016, Journal of Clinical Microbiology.

[8]  W. John Kress,et al.  A DNA barcode for land plants , 2009, Proceedings of the National Academy of Sciences.

[9]  Shashikant Kulkarni,et al.  Assuring the quality of next-generation sequencing in clinical laboratory practice , 2012, Nature Biotechnology.

[10]  B. Taminiau,et al.  The use of 16S rRNA gene metagenetic monitoring of refrigerated food products for understanding the kinetics of microbial subpopulations at different storage temperatures: the example of white pudding. , 2017, International journal of food microbiology.

[11]  Niklas Krumm,et al.  One Codex: A Sensitive and Accurate Data Platform for Genomic Microbial Identification , 2015, bioRxiv.

[12]  Ruth Timme,et al.  Practical Value of Food Pathogen Traceability through Building a Whole-Genome Sequencing Network and Database , 2016, Journal of Clinical Microbiology.

[13]  Litao Yang,et al.  Characterization of GM events by insert knowledge adapted re-sequencing approaches , 2013, Scientific Reports.

[14]  Kin-Fan Au,et al.  PacBio Sequencing and Its Applications , 2015, Genom. Proteom. Bioinform..

[15]  James Haile,et al.  Deep Sequencing of Plant and Animal DNA Contained within Traditional Chinese Medicines Reveals Legality Issues and Health Safety Concerns , 2012, PLoS genetics.

[16]  Jukon Kim,et al.  Efficiency to Discovery Transgenic Loci in GM Rice Using Next Generation Sequencing Whole Genome Re-sequencing , 2015, Genomics & informatics.

[17]  Ingrid M. J. Scholtens,et al.  Advances in DNA metabarcoding for food and wildlife forensic species identification , 2016, Analytical and Bioanalytical Chemistry.

[18]  David Laehnemann,et al.  Denoising DNA deep sequencing data—high-throughput sequencing errors and their correction , 2015, Briefings Bioinform..

[19]  E. Garcia-Vazquez,et al.  A case study for assessing fish traceability in Egyptian aquafeed formulations using pyrosequencing and metabarcoding , 2016 .

[20]  W. M. Vos,et al.  Comparative genome analysis of Lactobacillus casei strains isolated from Actimel and Yakult products reveals marked similarities and points to a common origin , 2013, Microbial biotechnology.

[21]  Samuele Bovo,et al.  Application of next generation semiconductor based sequencing for species identification in dairy products. , 2018, Food chemistry.

[22]  Rob Ogden,et al.  Gene-associated markers provide tools for tackling illegal fishing and false eco-certification , 2012, Nature Communications.

[23]  K. Crandall,et al.  Many species in one: DNA barcoding overestimates the number of species when nuclear mitochondrial pseudogenes are coamplified , 2008, Proceedings of the National Academy of Sciences.

[24]  Mintu Porel,et al.  Real-time single-molecule electronic DNA sequencing by synthesis using polymer-tagged nucleotides on a nanopore array , 2016, Proceedings of the National Academy of Sciences.

[25]  Vitali Sintchenko,et al.  Proficiency testing for bacterial whole genome sequencing: an end-user survey of current capabilities, requirements and priorities , 2015, BMC Infectious Diseases.

[26]  C Burks,et al.  The GenBank genetic sequence data bank. , 1988, Nucleic acids research.

[27]  S. Primrose,et al.  Measurement issues associated with quantitative molecular biology analysis of complex food matrices for the detection of food fraud. , 2016, The Analyst.

[28]  J. McPherson,et al.  Coming of age: ten years of next-generation sequencing technologies , 2016, Nature Reviews Genetics.

[29]  Joshua K Young,et al.  Targeted Mutagenesis, Precise Gene Editing, and Site-Specific Gene Insertion in Maize Using Cas9 and Guide RNA[OPEN] , 2015, Plant Physiology.

[30]  M. Portillo,et al.  Bacterial diversity of Grenache and Carignan grape surface from different vineyards at Priorat wine region (Catalonia, Spain). , 2016, International journal of food microbiology.

[31]  Susan R. Leonard,et al.  Application of Metagenomic Sequencing to Food Safety: Detection of Shiga Toxin-Producing Escherichia coli on Fresh Bagged Spinach , 2015, Applied and Environmental Microbiology.

[32]  E. Garcia-Vazquez,et al.  NGS tools for traceability in candies as high processed food products: Ion Torrent PGM versus conventional PCR-cloning. , 2017, Food chemistry.

[33]  Martin I. Taylor,et al.  Species‐specific TaqMan probes for simultaneous identification of (Gadus morhua L.), haddock (Melanogrammus aeglefinus L.) and whiting (Merlangius merlangus L.). , 2002 .

[34]  E. Waltz USDA approves next-generation GM potato , 2015, Nature Biotechnology.

[35]  S. D. De Keersmaecker,et al.  Use of next generation sequencing data to develop a qPCR method for specific detection of EU-unauthorized genetically modified Bacillus subtilis overproducing riboflavin , 2015, BMC Biotechnology.

[36]  M. Gadanho,et al.  Food metagenomics: Next generation sequencing identifies species mixtures and mislabeling within highly processed cod products , 2017 .

[37]  David L. Wheeler,et al.  GenBank , 2015, Nucleic Acids Res..

[38]  M. Pardo Evaluation of a dual-probe real time PCR system for detection of mandarin in commercial orange juice. , 2015, Food chemistry.

[39]  Birgit Funke,et al.  College of American Pathologists' laboratory standards for next-generation sequencing clinical tests. , 2015, Archives of pathology & laboratory medicine.

[40]  Wen J. Li,et al.  Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation , 2015, Nucleic Acids Res..

[41]  R. Prather,et al.  Gene-edited pigs are protected from porcine reproductive and respiratory syndrome virus , 2016, Nature Biotechnology.

[42]  C. Douady,et al.  Preventing the pollution of mitochondrial datasets with nuclear mitochondrial paralogs (numts). , 2011, Mitochondrion.

[43]  Pradeep Kumar,et al.  Current perspectives on genetically modified crops and detection methods , 2017, 3 Biotech.

[44]  Emily Waltz,et al.  Gene-edited CRISPR mushroom escapes US regulation , 2016, Nature.

[45]  L. Fontanesi,et al.  A Next Generation Semiconductor Based Sequencing Approach for the Identification of Meat Species in DNA Mixtures , 2015, PloS one.

[46]  Marie-Alice Fraiture,et al.  How Can We Better Detect Unauthorized GMOs in Food and Feed Chains? , 2017, Trends in biotechnology.

[47]  Jan Haas,et al.  The Role of Quality Control in Targeted Next-generation Sequencing Library Preparation , 2016, Genom. Proteom. Bioinform..

[48]  Kieran Jordan,et al.  A Review on the Applications of Next Generation Sequencing Technologies as Applied to Food-Related Microbiome Studies , 2017, Front. Microbiol..

[49]  B. Corradini,et al.  Forensic botany II, DNA barcode for land plants: Which markers after the international agreement? , 2015, Forensic science international. Genetics.

[50]  Theo W. Prins,et al.  Development and validation of a multi-locus DNA metabarcoding method to identify endangered species in complex samples , 2017, GigaScience.

[51]  James W. Fickett,et al.  The GenBank genetic sequence databank , 1986, Nucleic Acids Res..

[52]  D. Deforce,et al.  An integrated strategy combining DNA walking and NGS to detect GMOs. , 2017, Food chemistry.

[53]  Rasko Leinonen,et al.  The sequence read archive: explosive growth of sequencing data , 2011, Nucleic Acids Res..

[54]  S. Primrose,et al.  Food forensics: methods for determining the authenticity of foodstuffs , 2010 .

[55]  Martin Wiedmann,et al.  Omics approaches in food safety: fulfilling the promise? , 2014, Trends in microbiology.

[56]  Ira W. Deveson,et al.  Reference standards for next-generation sequencing , 2017, Nature Reviews Genetics.

[57]  Eoin L. Brodie,et al.  Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB , 2006, Applied and Environmental Microbiology.

[58]  Christoph Endrullat,et al.  Standardization and quality management in next-generation sequencing , 2016, Applied & translational genomics.

[59]  Mick Watson,et al.  A Review of Bioinformatics Tools for Bio-Prospecting from Metagenomic Sequence Data , 2017, Front. Genet..

[60]  C. Thermes,et al.  Library preparation methods for next-generation sequencing: tone down the bias. , 2014, Experimental cell research.

[61]  Andy Smith,et al.  CLIMB (the Cloud Infrastructure for Microbial Bioinformatics): an online resource for the medical microbiology community , 2016, bioRxiv.

[62]  Alice Giusti,et al.  Advances in the analysis of complex food matrices: Species identification in surimi-based products using Next Generation Sequencing technologies , 2017, PloS one.

[63]  Mark J. Clement,et al.  Targeted Amplicon Sequencing (TAS): A Scalable Next-Gen Approach to Multilocus, Multitaxa Phylogenetics , 2011, Genome biology and evolution.

[64]  Anna Sandionigi,et al.  Grape microbiome as a reliable and persistent signature of field origin and environmental conditions in Cannonau wine production , 2017, PloS one.

[65]  Erika Check Hayden,et al.  Technology: The $1,000 genome , 2014, Nature.

[66]  Niaz Banaei,et al.  Next-Generation Sequencing for Infectious Disease Diagnosis and Management: A Report of the Association for Molecular Pathology. , 2015, The Journal of molecular diagnostics : JMD.

[67]  Jeremy R. deWaard,et al.  Biological identifications through DNA barcodes , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[68]  Peter Henriksson,et al.  JRC GMO-Amplicons: a collection of nucleic acid sequences related to genetically modified organisms , 2015, Database J. Biol. Databases Curation.

[69]  M. Alegret Standardization and quality , 1992 .

[70]  R. Ward FISH-BOL, a case study for DNA barcodes. , 2012, Methods in molecular biology.

[71]  Samuele Bovo,et al.  Application of next generation semiconductor based sequencing to detect the botanical composition of monofloral, polyfloral and honeydew honey , 2018 .

[72]  W. Ansorge,et al.  Next Generation DNA Sequencing (II): Techniques, Applications , 2015 .

[73]  Jamie Alnasir,et al.  Investigation into the annotation of protocol sequencing steps in the sequence read archive , 2015, GigaScience.

[74]  J. White,et al.  Impact of organic and conventional management on the phyllosphere microbial ecology of an apple crop. , 2009, Journal of food protection.

[75]  Lisa Kalman,et al.  Assuring the Quality of Next-Generation Sequencing in Clinical Microbiology and Public Health Laboratories , 2016, Journal of Clinical Microbiology.

[76]  M. S. Grando,et al.  Experimental Review of DNA-Based Methods for Wine Traceability and Development of a Single-Nucleotide Polymorphism (SNP) Genotyping Assay for Quantitative Varietal Authentication. , 2016, Journal of agricultural and food chemistry.

[77]  G. McCracken,et al.  Disparities in second‐generation DNA metabarcoding results exposed with accessible and repeatable workflows , 2018, Molecular ecology resources.

[78]  Hideaki Sugawara,et al.  The Sequence Read Archive , 2010, Nucleic Acids Res..

[79]  E. Grice,et al.  Next-Generation Sequencing: A Review of Technologies and Tools for Wound Microbiome Research. , 2015, Advances in wound care.

[80]  Jennifer A. Doudna,et al.  A prudent path forward for genomic engineering and germline gene modification , 2015, Science.

[81]  E. Garcia-Vazquez,et al.  Detection of Different DNA Animal Species in Commercial Candy Products. , 2016, Journal of food science.

[82]  Rob Ogden,et al.  Development of a genetic tool for product regulation in the diverse British pig breed market , 2012, BMC Genomics.

[83]  Junli Feng,et al.  Application of Loop-Mediated Isothermal Amplification (LAMP) for Rapid Detection of Jumbo Flying Squid Dosidicus gigas (D’Orbigny, 1835) , 2017, Food Analytical Methods.

[84]  Ioannis Ganopoulos,et al.  Advances of DNA-based methods for tracing the botanical origin of food products , 2014 .

[85]  W. Ludwig,et al.  SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB , 2007, Nucleic acids research.

[86]  W. Davidson,et al.  FINS (forensically informative nucleotide sequencing): A procedure for identifying the animal origin of biological specimens. , 1992, BioTechniques.

[87]  P. Hebert,et al.  Rapid identification of the botanical and entomological sources of honey using DNA metabarcoding. , 2017, Food chemistry.

[88]  Baltasar Mayo,et al.  Impact of Next Generation Sequencing Techniques in Food Microbiology , 2014, Current genomics.

[89]  Wenxun Huang,et al.  Comparison of error correction algorithms for Ion Torrent PGM data: application to hepatitis B virus , 2017, Scientific Reports.

[90]  Áine McConnon,et al.  Consumers' confidence, reflections and response strategies following the horsemeat incident , 2016 .

[91]  C. Consolandi,et al.  Olive variety identification by ligation detection reaction in a universal array format. , 2007, Journal of biotechnology.

[92]  Shazia Mahamdallie,et al.  The Quality Sequencing Minimum (QSM): providing comprehensive, consistent, transparent next generation sequencing data quality assurance , 2018, Wellcome open research.

[93]  M. Cichna‐Markl,et al.  High resolution melting (HRM) analysis of DNA--its role and potential in food analysis. , 2014, Food chemistry.

[94]  P. Hebert,et al.  bold: The Barcode of Life Data System (http://www.barcodinglife.org) , 2007, Molecular ecology notes.

[95]  Keith Warriner,et al.  Droplet digital polymerase chain reaction (ddPCR) assays integrated with an internal control for quantification of bovine, porcine, chicken and turkey species in food and feed , 2017, PloS one.