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

ABSTRACT: 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.

SUBMITTER: Arulandhu AJ

PROVIDER: S-EPMC5632295 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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

Arulandhu Alfred J AJ Staats Martijn M Hagelaar Rico R Voorhuijzen Marleen M MM Prins Theo W TW Scholtens Ingrid I Costessi Adalberto A Duijsings Danny D Rechenmann François F Gaspar Frédéric B FB Barreto Crespo Maria Teresa MT Holst-Jensen Arne A Birck Matthew M Burns Malcolm M Haynes Edward E Hochegger Rupert R Klingl Alexander A Lundberg Lisa L Natale Chiara C Niekamp Hauke H Perri Elena E Barbante Alessandra A Rosec Jean-Philippe JP Seyfarth Ralf R Sovová Tereza T Van Moorleghem Christoff C van Ruth Saskia S Peelen Tamara T Kok Esther E

GigaScience 20171001 10

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 ...[more]

PMID: 29020743

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Project description:BackgroundThe mutualistic interaction between entomophilous plants and pollinators is fundamental to the structure of most terrestrial ecosystems. The sensitive nature of this relationship has been disrupted by anthropogenic modifications to natural landscapes, warranting development of new methods for exploring this trophic interaction. Characterizing the composition of pollen collected by pollinators, e.g. Apis mellifera, is a common means of exploring this relationship, but traditional methods of microscopic pollen assessment are laborious and limited in their scope. The development of pollen metabarcoding as a method of rapidly characterizing the abundance and diversity of pollen within mixed samples presents a new frontier for this type of work, but metabarcoding may have limitations, and validation is warranted before any suite of primers can be confidently used in a research program. We set out to evaluate the utility of an integrative approach, using a set of established primers (ITS2 and rbcL) versus melissopalynological analysis for characterizing 27 mixed-pollen samples from agricultural sites across Canada.ResultsBoth individual markers performed well relative to melissopalynology at the family level with decreases in the strength of correlation and linear model fits at the genus level. Integrating data from both markers together via a multi-locus approach provided the best rank-based correlation between metagenetic and melissopalynological data at both the genus (ρ = 0.659; p < 0.001) and family level (ρ = 0.830; p < 0.001). Species accumulation curves indicated that, after controlling for sampling effort, melissopalynological characterization provides similar or higher species richness estimates than either marker. The higher number of plant species discovered via the metabarcoding approach simply reflects the vastly greater sampling effort in comparison to melissopalynology.ConclusionsPollen metabarcoding performed well at characterizing the composition of mixed pollen samples relative to a traditional melissopalynological approach. Limitations to the quantitative application of this method can be addressed by adopting a multi-locus approach that integrates information from multiple markers.

Project description:Organoarsenic species in marine matrices have been studied for many years but knowledge gaps still exist. Most literature focuses on monitoring of arsenic (As) species using previously published methods based on anion- and cation-exchange high-performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS). These studies are often limited to few As species and/or only specific method performance characteristics are described. Most marine certified reference materials (CRMs) are only certified for arsenobetaine (AB) and dimethylarsinate (DMA), making it difficult to evaluate the accuracy of analytical methods for other organoarsenic species. To address these gaps, the main objective of this work was to develop and validate a method for speciation analysis of a broad range of organoarsenic species in marine matrices. Optimum extraction conditions were identified through a 27-3 fractional factorial design using blue mussel as test sample. The effects of sample weight, type and volume of extraction solution, addition of H2O2 to the extraction solution, extraction time and temperature, and use of ultrasonication were investigated. The highest As recoveries were obtained by using 0.2 g as sample weight, 5 mL of aqueous methanol (MeOH:H2O, 50% v/v) as extractant, extraction carried out at 90 °C for 30 min, and without ultrasonication. Anion- and cation-exchange HPLC-ICP-MS settings were subsequently optimized. The method detected a total of 33 known and unknown As species within a run time of 23 and 20 min for cation-exchange and anion-exchange, respectively. A single-laboratory validation was conducted using several marine CRMs: BCR 627 (tuna fish tissue), ERM-CE278k (mussel tissue), DORM-4 (fish protein), DOLT-5 (dogfish liver), SQID-1 (cuttlefish), TORT-3 (lobster hepatopancreas), and CRM 7405-b (hijiki seaweed). Method performance characteristics were evaluated based on selectivity, limits of detection and quantification, linearity, trueness, precision, and measurement uncertainty. This work proposes an extraction procedure which allowed satisfactory quantification of As species with low solvent and energy consumption, supporting "Green Chemistry" principles. The study also presents a new set of As speciation data, including methylated arsenic species and arsenosugars, in recently issued marine CRMs, which will be valuable for future speciation studies on As. This work is the first to report a total of 33 different As species in marine CRMs.

Project description:Understanding the diet of an endangered species illuminates the animal's ecology, habitat requirements, and conservation needs. However, direct observation of diet can be difficult, particularly for small, nocturnal animals such as the Pacific pocket mouse (Heteromyidae: Perognathus longimembris pacificus). Very little is known of the dietary habits of this federally endangered rodent, hindering management and restoration efforts. We used a metabarcoding approach to identify source plants in fecal samples (N = 52) from the three remaining populations known. The internal transcribed spacers (ITS) of the nuclear ribosomal loci were sequenced following the Illumina MiSeq amplicon strategy and processed reads were mapped to reference databases. We evaluated a range of threshold mapping criteria and found the best-performing setting generally recovered two distinct mock communities in proportions similar to expectation. We tested our method on captive animals fed a known diet and recovered almost all plant sources, but found substantial heterogeneity among fecal pellets collected from the same individual at the same time. Observed richness did not increase with pooling of pellets from the same individual. In field-collected samples, we identified 4-14 plant genera in individual samples and 74 genera overall, but over 50 percent of reads mapped to just six species in five genera. We simulated the effects of sequencing error, variable read length, and chimera formation to infer taxon-specific rates of misassignment for the local flora, which were generally low with some exceptions. Richness at the species and genus levels did not reach a clear asymptote, suggesting that diet breadth remained underestimated in the current pool of samples. Large numbers of scat samples are therefore needed to make inferences about diet and resource selection in future studies of the Pacific pocket mouse. We conclude that our minimally invasive method is promising for determining herbivore diets given a library of sequences from local plants.

Dataset Information

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

Publications

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

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