The application of multi-locus DNA metabarcoding in traditional medicines

Traditional medicines (TMs) are globally traded and the consumer market is estimated to be $83 billion per annum. The diversity of TM matrices and poor quality of DNA extracted from highly processed TMs makes it challenging to apply standardized DNA-based procedures for ingredient analysis. In the present study, multiple DNA extraction methods were compared for the ability to obtain amplifiable DNA from TMs belonging to different matrices. The best performing DNA extraction was used to successfully obtain DNA from 18 TMs that were subsequently analyzed with a multi-locus DNA metabarcoding method to assess the species composition. In the analysis mini-barcodes accounted for the identification of most of the taxa in the TMs. The plant (ITS2) and animal (mini-16S) mini-barcode markers showed to allow species level identification of targets. In a few cases, full-length barcode markers, requiring higher quality DNA, proved to be critically informative at this level. The applied strategy resulted in the identification of a wide range of declared and undeclared ingredients, including endangered species (Ursus arctos and Aloe sp.). In 14 TMs less than 65% of the identified taxa matched the product label, and in two TMs none of the identified species matched the ingredients list. The current study shows that a multi-locus DNA metabarcoding approach is an informative analytical tool for species identification in TMs, including the potential identification of endangered species.</p

Application of whole genome shotgun sequencing for detection and characterization of genetically modified organisms and derived products

The emergence of high-throughput, massive or next-generation sequencing technologies has created a completely new foundation for molecular analyses. Various selective enrichment processes are commonly applied to facilitate detection of predefined (known) targets. Such approaches, however, inevitably introduce a bias and are prone to miss unknown targets. Here we review the application of high-throughput sequencing technologies and the preparation of fit-for-purpose whole genome shotgun sequencing libraries for the detection and characterization of genetically modified and derived products. The potential impact of these new sequencing technologies for the characterization, breeding selection, risk assessment, and traceability of genetically modified organisms and genetically modified products is yet to be fully acknowledged. The published literature is reviewed, and the prospects for future developments and use of the new sequencing technologies for these purposes are discussed

DNA enrichment approaches to identify unauthorized genetically modified organisms (GMOs)

With the increased global production of different genetically modified (GM) plant varieties, chances increase that unauthorized GM organisms (UGMOs) may enter the food chain. At the same time, the detection of UGMOs is a challenging task because of the limited sequence information that will generally be available. PCR-based methods are available to detect and quantify known UGMOs in specific cases. If this approach is not feasible, DNA enrichment of the unknown adjacent sequences of known GMO elements is one way to detect the presence of UGMOs in a food or feed product. These enrichment approaches are also known as chromosome walking or gene walking (GW). In recent years, enrichment approaches have been coupled with next generation sequencing (NGS) analysis and implemented in, amongst others, the medical and microbiological fields. The present review will provide an overview of these approaches and an evaluation of their applicability in the identification of UGMOs in complex food or feed samples

Advances in DNA metabarcoding for food and wildlife forensic species identification

Species identification using DNA barcodes has been widely adopted by forensic scientists as an effective molecular tool for tracking adulterations in food and for analysing samples from alleged wildlife crime incidents. DNA barcoding is an approach that involves sequencing of short DNA sequences from standardized regions and comparison to a reference database as a molecular diagnostic tool in species identification. In recent years, remarkable progress has been made towards developing DNA metabarcoding strategies, which involves next-generation sequencing of DNA barcodes for the simultaneous detection of multiple species in complex samples. Metabarcoding strategies can be used in processed materials containing highly degraded DNA e.g. for the identification of endangered and hazardous species in traditional medicine. This review aims to provide insight into advances of plant and animal DNA barcoding and highlights current practices and recent developments for DNA metabarcoding of food and wildlife forensic samples from a practical point of view. Special emphasis is placed on new developments for identifying species listed in the Convention on International Trade of Endangered Species (CITES) appendices for which reliable methods for species identification may signal and/or prevent illegal trade. Current technological developments and challenges of DNA metabarcoding for forensic scientists will be assessed in the light of stakeholders’ needs

ALF: a strategy for identification of unauthorized GMOs in complex mixtures by a GW-NGS method and dedicated bioinformatics analysis

The majority of feed products in industrialised countries contains materials derived from genetically modified organisms (GMOs). In parallel, the number of reports of unauthorised GMOs (UGMOs) is gradually increasing. There is a lack of specific detection methods for UGMOs, due to the absence of detailed sequence information and reference materials. In this research, an adapted genome walking approach was developed, called ALF: Amplification of Linearly-enriched Fragments. Coupling of ALF to NGS aims for simultaneous detection and identification of all GMOs, including UGMOs, in one sample, in a single analysis. The ALF approach was assessed on a mixture made of DNA extracts from four reference materials, in an uneven distribution, mimicking a real life situation. The complete insert and genomic flanking regions were known for three of the included GMO events, while for MON15985 only partial sequence information was available. Combined with a known organisation of elements, this GMO served as a model for a UGMO. We successfully identified sequences matching with this organisation of elements serving as proof of principle for ALF as new UGMO detection strategy. Additionally, this study provides a first outline of an automated, web-based analysis pipeline for identification of UGMOs containing known GM elements.</p

Erratum to: ALF: a strategy for identification of unauthorized GMOs in complex mixtures by a GW-NGS method and dedicated bioinformatics analysis

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.</p

NGS-based amplicon sequencing approach; towards a new era in GMO screening and detection

The development and commercialization of Genetically Modified Organisms (GMOs) and its related products have been increasing in the last two decades. This challenges the currently applied time-consuming and expensive qPCR screening procedure from a practical perspective, due to the necessity to develop and validate additional targets at a regular pace and the increasing number of targets included in a single screening. In this study we developed a next generation sequencing (NGS)-based GMO screening approach covering 96 GMO targets and compared it to the two-step qPCR GMO screening approach; the two approaches were evaluated with five feed samples known to contain GMOs. The amplicons obtained from the feed samples were analyzed using 150-bp Paired-End sequencing, Illumina HiSeq 4000 platform. A dedicated data analysis pipeline was developed, which allows automated identification of GMOs and associated genetic elements and constructs. The result of the NGS-based screening were compared with the qPCR approach, indicating that 92% of the targets were commonly identified between the qPCR and NGS-based screening. The remaining 8% of the targets had discrepancies in detection between the two methods. This was mainly observed for targets that were detected in qPCR with high Cq values (above 36), which could not be detected in NGS-based screening. Additionally, due to the more extensive screening in the NGS-based strategy, in total 43 additional GMOs and related targets were identified compared to the standard qPCR screening. From the commonly identified targets in both approaches, 8 targets could not be associated with the detected GMOs. These targets had late Cq values (above 36) and could indicate traces of unknown GMOs in the samples. The current study shows the applicability of NGS as a novel, broad and reliable screening strategy for GMOs and its potential to improve current screening methods.</p

Development and validation of a multi-locus DNA metabarcoding method to identify endangered species in complex samples

DNA metabarcoding provides great potential for species identification in complex samples such as food supplements and traditional medicines. Such a method would aid Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) enforcement officers to combat wildlife crime by preventing illegal trade of endangered plant and animal species. The objective of this research was to develop a multi-locus DNA metabarcoding method for forensic wildlife species identification and to evaluate the applicability and reproducibility of this approach across different laboratories. A DNA metabarcoding method was developed that makes use of 12 DNA barcode markers that have demonstrated universal applicability across a wide range of plant and animal taxa and that facilitate the identification of species in samples containing degraded DNA. The DNA metabarcoding method was developed based on Illumina MiSeq amplicon sequencing of well-defined experimental mixtures, for which a bioinformatics pipeline with user-friendly web-interface was developed. The performance of the DNA metabarcoding method was assessed in an international validation trial by 16 laboratories, in which the method was found to be highly reproducible and sensitive enough to identify species present in a mixture at 1% dry weight content. The advanced multi-locus DNA metabarcoding method assessed in this study provides reliable and detailed data on the composition of complex food products, including information on the presence of CITES-listed species. The method can provide improved resolution for species identification, while verifying species with multiple DNA barcodes contributes to an enhanced quality assurance