DNA barcoding for biosecurity: case studies from the UK plant protection program
Abstract
Since its conception, DNA barcoding has seen a rapid uptake within the research community. Nevertheless, as with many new scientific tools, progression towards the point of routine deployment within diagnostic laboratories has been slow. In this paper, we discuss the application of DNA barcoding in the Defra plant health diagnostic laboratories, where DNA barcoding is used primarily for the identification of invertebrate pests. We present a series of case studies that demonstrate the successful application of DNA barcoding but also reveal some potential limitations to expanded use. The regulated plant pest, Bursephalenchus xylophilus, and one of its vectors, Monochamus alternatus, were found in dining chairs. Some traded wood products are potentially high risk, allowing the movement of longhorn beetles; Trichoferus campestris, Leptura quadrifasciata, and Trichoferus holosericeus were found in a wooden cutlery tray, a railway sleeper, and a dining chair, respectively. An outbreak of Meloidogyne fallax was identified in Allium ampeloprasum and in three weed species. Reference sequences for UK native psyllids were generated to enable the development of rapid diagnostics to be used for monitoring following the release of Aphalara itadori as a biological control agent for Fallopia japonica.
Résumé
Depuis son développement, le codage à barres de l’ADN a connu une adoption rapide au sein de la communauté scientifique. Néanmoins, comme pour plusieurs nouveaux outils scientifiques, les avancées en vue d’un usage routinier au sein de laboratoires de diagnostic ont été lentes. Dans ce travail, les auteurs discutent de l’emploi du codage à barres au sein des laboratoires de diagnostique phytosanitaire de DEFRA, où le codage à barres est principalement employé pour l’identification des ravageurs invertébrés. Les auteurs présentent une série d’études de cas le codage à barres a été mis en œuvre avec succès tout en révélant des limitations potentielles à son usage accru. Le parasite réglementé, Bursephalenchus xylophilus, et l’un de ses vecteurs, Monochamus alternatus, ont été retrouvés dans des chaises de salle à manger. Certains produits du bois sont potentiellement à haut risque en facilitant le mouvement des longicornes; Trichoferus campestris, Leptura quadrifasciata et Trichoferus holosericeus ont été trouvés, respectivement, dans un range-couvert en bois, une traverse ferroviaire, et une chaise de salle à manger. Une épidémie du Meloidogyne fallax a été identifiée chez l’Allium ampeloprasum et chez trois adventices. Des séquences de référence pour des psylles indigènes du Royaume-Uni ont été générées pour permettre le développement d’outils diagnostiques rapides en vue de surveiller l’Aphalara itadori suite à son introduction en tant qu’agent de lutte biologique contre le Fallopia japonica. [Traduit par la Rédaction]
Introduction
DNA barcoding is a molecular method that can be used for identification to species; PCR amplification, followed by sequencing of a short conserved gene region and comparison of the sequence to a database of reference sequences, is used to identify the specimen. Fundamentally, the method allows the determination of whether a given gene sequence contains differences from reference sequences that are expected to be seen within a species compared to those seen between different species. First described for species identification by Hebert and co-workers in 2003 (Hebert et al. 2003), it has been rapidly embraced by the scientific community despite early reservations by certain taxonomists (DeSalle et al. 2005; Will et al. 2005). Due to the generic nature and universal workflow of the technique, DNA barcoding has been applied to a wide range of scientific disciplines, from food authenticity to conservation studies (Holmes et al. 2009; Francis et al. 2010; Hrcek et al. 2011; Adamowicz 2015). The most common applications of DNA barcoding are to aid with species description, resolution of species complexes, and the identification of specimens of unknown taxa to species (Kress et al. 2015).
DNA barcoding as an identification tool is most often compared to “traditional” species identification based on morphological characters (Hajibabaei et al. 2007), given the comparison to identified reference sequences. However, it can also be compared to numerous other species-specific molecular detection or identification methods that identify species such as polymerase chain reaction (PCR) (Kiewnick et al. 2013), real-time PCR (qPCR) (Huang et al. 2010), and isothermal amplification techniques such as loop-mediated isothermal amplification (LAMP) (Kikuchi et al. 2009). However, the latter methods are typically targeted to a single species (or occasionally a small group of species), and therefore they are used in the context of answering the question “is this specimen species x?”. Techniques such as DNA barcoding provide a fundamental step change, instead answering the question “what species is this specimen?”.
Plant health within the United Kingdom (UK) is enacted by the National Plant Protection Organisation (NPPO, government designated organisations) in adherence to the European Council Directive 2000/29/EC (EU 2000) (and its subsidiary legislation). The overarching aim of the legislation is to provide a legal framework for the protection of forests and natural landscapes and to enable productive agricultural and horticultural trades by preventing the introduction and spread of harmful pests and pathogens. The European and Mediterranean Plant Protection Organisation (EPPO) is an inter-governmental organisation with responsibilities for harmonisation and cooperation of plant protection within the region (EPPO 2016). EPPO also maintains lists of pests recommended for regulation: the A1 list (species absent from the EPPO region), the A2 list (species present in the EPPO region but not widely distributed), and the alert list (species posing new potential phytosanitary risks) (EPPO PM1/2 (24) 2015; EPPO 2015). Contingent to delivering policy objectives is the establishment of diagnostic methods, which allow the accurate and rapid identification of pests and pathogens. The EC directive and national legislation (UK 2015) lists species that are actionable, thus intrinsically linking legislative action with taxonomy and identification.
The large numbers of specimens that need identifying, and the requirement for reference data for all the species from which these need to be discriminated, poses a challenge for DNA barcoding within the diagnostic laboratory. For every taxonomic group, the presence of a unique species-level barcode (which encompasses intraspecific variation but allows discrimination of interspecific variation) must be demonstrated, requiring access to different populations of the species. This is one of the major hurdles in the deployment of DNA barcoding in routine diagnostics, as there are often not enough sequences to describe the variation within a species or for closely related species (Virgilio et al. 2012). Furthermore, there are important differences when utilising a scientific tool in a research context as opposed to a diagnostic context, especially if the consequences of an identification are significant; i.e., they may lead to the destruction of imported material, leading to significant financial losses. Currently, diagnostic laboratories are moving towards the use of only accredited and validated methods (EPPO PM 7/98 (2) 2014) that are well established. DNA barcoding reference datasets (e.g., GenBank, BOLD—the Barcode of Life Data Systems, Ratnasingham and Hebert 2007) are continually changing, and thus protocols need constant evaluation prior to use. This presents difficulties in terms of standardisation of methods and accreditation. Often, a “critical mass” of reference sequences for organismal groups is only obtained when there is a particular reason to study a group or if it is used as a model system by interested research groups (Armstrong and Ball 2005). In the EU context, attempts to address these gaps have been undertaken, with the creation of a sequence database for EU regulated plant pests (Q-bank) (Bonants et al. 2013). Nevertheless, with global trade, the range of species that may require identification, and therefore reference sequences, is vast.
Traditional morphological taxonomy (using morphological keys and diagnostic structures) is still the primary technique used for the identification of invertebrate samples, which in the hands of skilled and experienced taxonomic specialists can often result in a rapid and reliable identification. Molecular (as opposed to morphological) identification strategies may be needed for a number of reasons. Most commonly, key diagnostic structures may be damaged or missing, or there is no primary description or morphological key to the taxa or life stage being examined (Shin et al. 2015). Another common application is to expedite identification following detection. Many important pests are intercepted as immature specimens, and often these cannot be identified as they lack definitive morphological characters. The traditional solution is to rear these to an identifiable life stage, such as the adult (Ruiter et al. 2013). This, however, can be a lengthy process (often weeks) and frequently fails due to high levels of mortality. This is clearly not feasible when trade relations or, for example, the release of fresh produce at the border is at stake. The use of DNA barcoding in these situations can support a presumptive morphological identification and result in a much more rapid identification, or indeed generate an identification when one may not have been possible by morphological methods alone. Considering that identifications may reveal new zoogeographic record for regulated pest species, this could have a significant impact on, or even stop, trade from a country or region, with both financial and political consequences. Consequently, it is vital that the identification is robust. Multiple diagnostic methods, such as morphological identification and molecular tools, producing the same identification can add rigour and robustness to a finding to support any resulting action, and therefore combined diagnoses can be favourable to NPPOs.
In this paper, we will use a series of data-linked case studies to illustrate some of the varied scenarios in which DNA barcoding has been used by Defra plant health in England and Wales. This will illustrate the diverse applications, beyond the identification process itself, in which DNA barcoding can be used, as well as highlighting some of the limitations and drawbacks that still exist and hamper broader deployment of the technique. In case study 1, we will illustrate the use of DNA barcoding for the identification of a combined interception of a significant plant pest alongside its vector, which is also a plant pest. Case study 2 studies a series of examples that have highlighted potentially high-risk trade routes for plant pests. Case study 3 demonstrates the use of DNA barcoding for the identification of regulated plant pests, and case study 4 highlights the limitations of DNA barcoding posed by lack of reference sequences in understudied taxa, in this instance psyllids.
Materials and methods
Details of sample collection for each case study are presented in the Results and discussion section to provide a more succinct interpretation associated with each case study. The Materials and methods section outlines the identification and molecular methods used in the study.
Morphological identification and sample preparation
Vermiform endoparasitic nematodes were extracted from wood samples following the Baermann funnel method (EPPO PM 7/119 (1) 2013), as recommended in the EPPO diagnostic protocol for Bursaphelenchus xylophilus (EPPO PM 7/4 (3) 2013) (Case study 1). Free-living Meloidogyne males and infective juveniles were extracted from soil substrate using the Oostenbrink elutriator technique (EPPO PM 7/119 (1) 2013) (Case study 3.1). Nematode specimens were fixed in TAF (Hooper 1986) and mounted on glass slides for microscopic examination at 100× magnification. EPPO diagnostic protocols EPPO PM 7/4 (3) 2013, EPPO PM 7/41 (2) 2009, and reference works Ryss et al. (2005) and Perry et al. (2009), were used to facilitate morphological identification of Bursaphelenchus and Meloidogyne nematode specimens. Nematodes used for molecular analysis were mounted in water on glass slides, examined under a compound microscope at 400×, and then placed in 1.5 mL microcentrifuge tubes and immediately frozen.
Insect morphological identifications were made with reference to all available and relevant taxonomic keys, original descriptions, and preserved museum specimens as follows: psyllid genera Aphalara, Baopelma, Cacopsylla, Diaphorina, Psylla, Psyllopsis, and Trioza with reference works Hodkinson and White (1979), Ossiannilsson (1992), and Bantock and Botting (2013) (Case study 4); Monochamus alternatus with reference works Hope (1843), Kojima (1931), Gressitt (1942), Duffey (1968), Invasive.org (2010), and CABI (2016) (Case study 1). The principles followed when taking samples for molecular analysis was to remove a representative amount of material without completely disrupting the most important diagnostic characters. For large adult insects (such as beetles), the right rear leg was taken, and for smaller softer-bodied insects (such as psyllids) the right middle and right hind legs were taken. For intact larval specimens, a section such as abdominal segments 1–3 was excised. For completely disrupted specimens that were too damaged for morphological identification, a representative sample of the most fleshy material was taken, as it has been found that heavily chitinised structures such a mandibles and other part of the exoskeleton often fail to yield sufficient DNA. Samples for molecular analysis were placed in 1.5 mL microcentrifuge tubes and immediately frozen. The remains of the specimen were frozen and retained for future reference or further sampling if needed.
Samples were removed from the specimen whilst viewing on a petri-dish or other suitably sized container under a binocular dissecting microscope at magnifications of up to 160× and using a combination of fine entomological forceps, seekers, entomological pins, and a scalpel. Between specimens, all instruments were sterilised by flaming and were then cleaned with 70% ethanol.
Sample information is provided in Table 1. Each sample (or sub-sample of larger specimens) was assigned a unique identifying number for the molecular study.
Table 1.
Note: Where left blank the information is not available.
*
A specimen freshly collected and identified as Aphalara polygoni showing a 99.8% sequence identity to a published sequence identified as Aphalara freiji.
†
A specimen freshly collected and identified as Baopelma foersteri shares an 84% sequence identity to a published sequence labelled as the same species, and a 100% match to a non-disclosed specimen (Psyllidae sp. BOLD:ACV498).
‡
Percentage sequence identity to nearest match in database.
DNA extraction
For all samples apart from psyllids, DNA extractions were performed using a DNeasy® blood and tissue kit (QIAGEN, West Sussex, UK), following the manufacture’s protocol for animal tissues using spin columns. For larger samples (i.e., beetle legs, abdomen sections), tissue was homogenised with a micro-pestle (STARLAB, Milton Keynes, UK) prior to overnight lysis. Smaller samples (e.g., nematodes, psyllid legs) were not subject to homogenisation and were re-suspended in homogenisation buffer prior to overnight lysis. The final elution volume was adjusted relative to the size of the sample tissue, ranging from 100 to 400 μL.
Alternatively for psyllid samples (Case study 4), DNA was extracted using a Chelex-100 resin based method (Boonham et al. 2002). Single legs and wings of whole insects were removed using sterile fine forceps and placed in individual 0.6 mL microcentrifuge tubes. The tissue sample was homogenised using a sterile micro-pestle, 100 μL of molecular-grade water was added, and the sample was further homogenised. A slurry of 100 μL of a 50% w/w chelex resin:molecular grade water was added, the sample heated to 95 °C for 5 min, centrifuged for 5 min, and the supernatant transferred and stored at −30 °C prior to use.
PCR
For invertebrate samples, three primer pairs were used (separately); two of these amplify the “standard” cytochrome c oxidase subunit I (COI) barcode and the third a partial 3-prime section of the COI barcode region (Table 2). Using this approach, the majority of samples are positive with one of the three primer pairs. On occasions when these do not amplify the sample, alternate primers for the same gene region are selected based on the suspected family; typically those described in Simon et al. (1994 and 2006) are used as a starting point. PCR primers JB3/JB5 were used in PCR of Meloidogyne species nematodes to amplify a 450-bp fragment of the COI gene (not the standard COI barcode region). For Bursaphelenchus species nematodes, PCR primers LCO1490/HCO2198 were used as described for invertebrate samples. All primers were synthesised by Eurofins-MWG-Operon.
Table 2.
All PCR reactions were performed using a proof reading DNA polymerase in a GeneAmp® 9700 thermocycler (Applied Biosystems, California, USA). PCR reactions (25 μL) comprised 12.5 μL 2x bio-x-act short PCR mix (Bioline, London, UK), 400 nm each primer, and 1 μL DNA (concentration as extracted). To stream line testing, PCR conditions were harmonised for the three invertebrate primer pairs so that all could be run in parallel in a single thermocycler at the same time as follows: 5 min at 94 °C; followed by 35 cycles of 30 s at 94 °C, 45 s at 50 °C, and 1 min at 72 °C; and 10 min at 72 °C. Cycling conditions for primers JB3/JB5 were as follows: 5 min at 95 °C; followed by 40 cycles of 1 min at 95 °C, 1 min 30 s at 41 °C, and 1 min at 72 °C; and 10 min at 72 °C.
PCR products (5 μL) were separated by gel electrophoresis in 1% agarose gel in 1x Tris-borate-EDTA buffer (89 mmol/L Tris, 89 mmol/L boric acid, 2mmol/L EDTA), stained with ethidium bromide, and visualised using a UV transilluminator. PCR products were purified using the QIAquick® PCR purification Kit (QIAGEN, West Sussex, UK) prior to sequencing on both strands using the PCR primers by Eurofins-MWG-Operon. In instances when multiple COI primer sets generated a PCR amplicon, one of the full length barcode regions was selected in preference to the shorter amplicon. To generate reference sequences for a reference specimen of each Meloidogyne species, the PCR product was cloned into the pGEM®-T easy vector system (Promega, Wisconsin, USA) following the manufactures protocol. Where possible, multiple specimens or populations of each species (preferably a minimum of three) were subjected to DNA sequencing (see the supplementary data, Table S12, for sample information). Sequences were submitted to NCBI (see Table 1 for accession numbers).
Sequence analysis
DNA sequences were proofread by eye in Sequence Scanner version 2 (Applied Biosystems California, USA) and consensus sequences created in MEGA version 4.1 (Tamura et al. 2007) where each nucleotide position had been sequenced twice (single read sections were excluded from the consensus sequence). The IUPAC Ambiguity Code (Cornish-Bowden 1985) was used for true polymorphic positions (not sequencing ambiguity). Alignments and analyses were performed using MEGA version 4.1 software using the neighbour-joining method with default values, Kimura 2-parameter distance metric, and 1000 replications for bootstrap analysis. Database searches (BLAST) were performed at the NCBI website (http://www.ncbi.nlm.nih.gov/), BOLD website (http://www.boldsystems.org/, using the “Species Level Barcode Records” database), and Q-bank website (http://www.q-bank.eu/); in all cases, sequences were analysed using all three databases, apart from Meloidogyne species, which were only analysed using Q-bank (due to this database containing more reliable reference sequences for the genus). To assess the reliability of the DNA barcode to produce a species-level identification, results were assessed in terms of percentage sequence identity to reference sequences, intra- and interspecies variation compared to reference sequences (using Kimura 2-parameter distance metric), representation of reference sequences for other species within the genus or family (as appropriate), and assessment of availability of references sequences from species within the genus and those taxa known to be present in the country of origin of the sample (for elimination purposes). Database searches were performed at the date mentioned in each case study (2010–2015) and repeated in January 2016.
Results and discussion of case studies
Case study 1: Interception of the pine wood nematode and its vector the Japanese pine sawyer beetle from dining room furniture
The detection of any live regulated plant pest or pathogen is always significant. However, the interception of a pathogen and pest together with a known vector increases the ability of the pathogen and pest to disperse and establish, thereby increasing the significance of the finding. The following case study illustrates one such example and demonstrates the combined use of DNA barcoding with morphological identification in the sample identification process.
There is no specific regulation relating to the treatment of the wood used in the manufacture of goods such as furniture or domestic wares. Traditionally, furniture is manufactured from kiln-dried or seasoned wood. Kiln drying to a core temperature of a minimum of 56 °C for 30 min ensures that any pests are killed or rendered inactive. This treatment is required to meet the standard ISPM 15 (International Standards for Phytosanitary Measures 15) that applies to wood packaging material (WPM) such as pallets. Whilst compliance with this standard is monitored by NPPO’s through the inspection of WPM at points of entry where relevant, inspection does not routinely cover manufactured goods such as furniture. In 2013, two live adult longhorn beetles emerged from one of a pair of identical dining chairs in a domestic dwelling. The chairs had been manufactured and shipped directly from China to a UK distributor prior to purchase by the homeowner. The beetles were identified by an expert from morphological characters as Monochamus alternatus Hope (Coleoptera: Cerambycidae) the Japanese pine sawyer beetle. As a further confirmation, DNA barcoding of the specimens was carried out (accession number KU531393), and this provided a 100% sequence identity to published reference sequences (accession number JN087407) for this species.
Monochamus alternatus is a EU I/A1 (EPPO A1) quarantine-listed plant pest, and one of the known vectors of Bursaphelenchus nematodes (Togashi 1985). This includes the EU II/A1 (EPPO A2) quarantine-listed plant pest B. xylophilus (Steiner and Buhrer 1934) Nickle 1970, the pine wood nematode (PWN), a serious and damaging pathogen of Pinus spp. including many native European species (Braasch 2001; EPPO PM 7/4 (3) 2013). Wood samples were taken from near the beetle galleries and processed to extract any live free-living endoparasitic nematodes present. Several hundred live immature nematodes were isolated from the wood. As no adults were present, morphological identification beyond genus level could not be confirmed; therefore, DNA barcoding was utilised to identify the species (accession number KU531399). This confirmed the presence of PWN with 100% sequence identity to published reference sequences (e.g., accession number JQ514067) for this species, and represented, to our knowledge, the first known UK record of B. xylophilus being intercepted together with one of its known vectors, M. alternatus.
Because of the significance of the finding, other chairs from the same consignment were traced and examined. This revealed that approximately 25% of the consignment contained wood with evidence of beetle activity, and a dead beetle larva was found in one of these chairs (Fig. 1). As no morphological key or description to enable the identification of the larval stages of M. alternatus was available, DNA barcoding was employed to confirm the identity of the specimen (accession number KU531394). This provided a positive identification of the larva as M. alternatus, with a 99.8% sequence identity to that of the adult specimen that had previously been identified and sequenced.
Fig. 1.
Very large numbers of this type of chair are imported and distributed across the EU each year, with figures indicating that the UK alone imported approximately 84 000 chairs in 2012–2013 (S. Mears, Forestry Commission, personal communication, 2013). Since these findings, other similar chairs have been found with evidence of beetle activity. Clearly, the wood components of these chairs had not been kiln dried, as live organisms were present within them. This case illustrates how the furniture trade has the potential to pose significant risks to plant health by providing a clear pathway for the movement and dispersal of large numbers of potentially damaging plant pests (Ostojá-Starzewski 2014).
Case study 2: Discovering potentially high-risk trades—longhorn beetles (Coleoptera: Cerambycidae) in wood-based products
Trade is a major driver of the global economy, and, whilst essential, it does come with inherent risks that can impact on all trading countries. One significant risk is the unintentional introduction of exotic plant pests and diseases that can seriously impact plant health in the importing country. The volume and diversity of imports makes the mitigation of all risks a challenge, and so identifying new pests and pathways is vitally important. The following three examples from recent years specifically illustrate the potential risk associated with the importation of products manufactured from wood and how identification by DNA barcoding has proven to be a vital tool.
Trichoferus campestris (Faldermann, 1835), an EU I/A1 (EPPO A2) quarantine-listed pest, from a wooden cutlery tray
In June 2013, a single adult beetle emerged from a wooden cutlery tray in a domestic dwelling in the UK and was reported by the householder to their local plant health inspector. The tray, apparently constructed from beech wood (Fagus spp.) and purchased from a large UK retailer, had been manufactured and imported from China. Given the origin of the specimen, the concern was that this could be a potentially serious pest species. The beetle had been crushed by the householder during “capture”, making identification by morphological means impossible as the spatial arrangement of key features was disrupted and some were completely missing; as a result, DNA barcoding was employed. This rapidly confirmed the specimen to be T. campestris (accession number KU531395) with 100% sequence identity to reference sequences in the BOLD database (and 98% sequence identity to reference sequences in NCBI (accession number GQ404374) and Q-bank). This longhorn beetle species has a natural geographic range that includes China, Korea (North and South), Japan, Kazakhstan, Kyrgyzstan, Mongolia, Russia (Eastern Siberia, Far East, European Russia), Tajikistan, and Uzbekistan (EPPO 2009) and is a polyphagous pest recorded to feed on and damage at least 40 genera of woody conifers and deciduous trees (Bullas-Appleton et al. 2014). Therefore, this poses a risk to native flora and highlights a rarely considered pathway for pests to enter the country.
Trichoferus holosericeus (Rossi, 1790) from a dining chair
In April 2015, chewing sounds were heard coming from a hardwood dining chair purchased in 2010 from a large department store in the UK. The chair had apparently been manufactured in France from hardwood, probably European beech (Fagus sylvatica). In June 2015, a 15 mm × 4 mm hole was discovered in one of the chair legs, but no insect was found. More sounds were heard in August, suggesting another organism was present. Upon destructive examination of the chair in the laboratory, extensive internal larval feeding galleries and one live and partially formed longhorn beetle larvae were found. An attempt was made to rear this to an adult to allow morphological identification, but the specimen died before it completed its development. Again, DNA barcoding was employed (accession number KU531396), which provided a 100% sequence identity to reference sequences (in BOLD, NCBI (accession number KM286394) and Q-bank), confirming the sample as the native European species T. holocericerus, a species not known to be present in the UK but considered to be less of a risk than T. campestris.
Leptura quadrifasciata (L.) from wooden railway sleepers
In July 2015, beetle emergence holes were spotted in wooden railway sleepers used as structural elements in a private garden near Windsor forest, Berkshire. This was of concern because the sleepers had been purchased from a merchant that regularly sources wood from overseas; therefore, there was the potential for an alien species of wood-boring insect to have been introduced. Only fragmentary remains could be extracted from the sample, which could not be identified morphologically, and so molecular identification was employed. DNA barcoding of a leg confirmed the specimen as L. quadrifasciata (accession number KU531397) with a 100% sequence identity to reference sequences in NCBI (accession number KM285985) and BOLD. Leptura quadrifasciata is a common and widespread species that occurs naturally in the UK (Twinn and Harding 1999) and was therefore of no plant health concern. This example also demonstrates the benefits of having various sequence databases available, because the Q-bank database, which is focused on regulated pests, did not have reference sequences available to identify the species.
Case study 3: Identification of plant pests
3.1. Detection of Meloidogyne fallax in Allium ampeloprasum (leek) in the UK
Species belonging to the genus Meloidogyne, commonly referred to as root-knot nematodes, are a major group of plant–parasitic nematodes that are globally distributed and considered one of the most economically damaging nematode genera (Elling 2013). Obligate parasites of the roots, corms, and tubers of almost all species of vascular plants (Jones et al. 2013), they induce galls that cause adverse effects on the quality and yield of crops. Of the ∼100 putative species described, two species are listed in the EC directive 2000/29/EC, M. fallax and M. chitwoodi. Meloidogyne enterolobii has been added to the EPPO A2 list, and M. ethiopica and M. mali have been recently added to the EPPO alert list. Meloidogyne fallax has previously been found in sports turf in the UK in England and Northern Ireland in 2011 (EPPO-RS 2013), whilst the other regulated species are considered to be absent. There are many species native to the UK, including M. ardenensis, M. artiellia, M. duytsi, M. hapla, M. kralli, M. maritima, and M. minor (Wesemael et al. 2011).
Due to the large number of species in the genus, definitive morphological identification in samples is challenging (Braun-Kiewnick et al. 2016); multiple life stages are often required for confident identification by taxonomic experts, and in diagnostic samples these are often not present, precluding species-level identification. Specific PCR, PCR-RFLP, and qPCR assays are available for some, but not all, species (Kiewnick et al. 2013; Han et al. 2004; Sapkota et al. 2016), leading to the development of a sequence-based identification method (Kiewnick et al. 2014). The COI barcoding region provided species-level identification and, importantly, could distinguish between the closely related listed species M. fallax and M. chitwoodi. Interestingly, none of the genes studied by Kiewnick et al. (2014) could differentiate the three tropical Meloidogyne species (M. incognita, M. arenaria, and M. javanica). However, due to these taxa all being non-native tropical species, it is likely the same action would be taken if any were intercepted on consignments entering the UK; consequently, the lack of differentiation of these species is not problematic. Accordingly, as recommended within the Q-Bol project (Bonants et al. 2010) the partial COI region was considered sufficient for Meloidogyne species DNA barcoding.
In August 2013, the grower of a field crop of Allium ampeloprasum (leek, formerly A. porrum), of the cultivars Belton, Duraton, and Megaton, in the UK observed stunted growth of plants in approximately 1 ha within a 19 ha field. The symptomatic plants were around half the size of asymptomatic plants, chlorotic, and with obvious root nodulation (Figs. 2 and 3). The plants were supplied by a UK propagator who had grown them from seed in peat blocks.
Fig. 2.
Fig. 3.
A representative sample of symptomatic leeks and the weed species Trifolium pratense (red clover), Cirsium arvense (creeping thistle), and Viola spp. (field pansy) and associated soil were collected from the field for testing. All plant samples were found to be infested with root-knot nematodes; adult nematode females and egg masses were extracted from the root galls using a dissecting microscope and free-living root-knot nematode males and infective juveniles were isolated from the soil using elutriation methods (EPPO PM 7/119 (1) 2013).
Sequence analysis (Fig. 4) and database searches (KU517179–KU517182) were used to identify the nematodes in all plant species tested as Meloidogyne fallax (Karssen, 1996). Following the identification, the EU and EPPO were notified of an outbreak of the IAII (EPPO A2) listed pest. Analysis of published reference sequences for Meloidogyne demonstrated that, for this genus, both NCBI and BOLD are un-informative due to errors with reference sequences, preventing species identification by generating sequence clusters that contain multiple Meloidogyne species. However, the more recently generated and curated Q-bank database can be reliably used to identify species within the genus. This is thought to be the first record of M. fallax infesting Allium spp. After assessment of the spread of the nematode within the leek, M. fallax was only found in the roots and not within the root plate.
Fig. 4.
Whilst the source of the infestation is unknown, it is proposed that the nematodes may have been introduced into the field with plant waste and soil applied as a green manure, generated over numerous years from the on-site processing and packing of imported leeks. The risk to the industry was considered to be relatively low as the grower does not produce any plants for planting and does not grow ware or seed potatoes. The crop roots are removed before the plants are marketed, therefore further reducing the risk of spread. In response to the outbreak and to support containment and reduce spread as part of an eradication strategy, hygiene measures were introduced, symptomatic plants were destroyed by mechanical cultivation, and cropping restrictions were implemented. In this instance, when suspicion of an infection was raised, morphological identification of the population could not be confirmed, and culturing of juvenile nematodes to facilitate identification would have caused a delay of a number of weeks. The application of DNA barcoding led to a rapid identification of the nematodes at the site of an outbreak in days, and allowed screening of a large number of samples. This rapid identification enabled immediate action to be taken, limiting the potential spread across the surrounding area by contaminated machinery. The field population was sampled again in 2015 and was found to be below detectable levels.
3.2. Discounting interceptions of suspected serious pests
Whilst the most obvious application of DNA barcoding is to directly identify a specimen, in certain circumstances the method can be used as means of eliminating suspects from an investigation by demonstrating a lack of sequence matches to the species of concern. This may be as valuable as providing an identification as it can prevent unnecessary actions being taken and the consequences that could arise thereafter, as described in the following case.
A single dead weevil (Coleoptera: Curculionidae) larva was found by the Animal and Plant Health Agency (APHA) inspectorate inside a chilli (Capsicum frutescens L.) originating from Brazil during a routine inspection of goods arriving at Heathrow airport. Morphological identification to species was not possible as there are no comprehensive keys to the weevil larvae of South America; also, the larva was dead, so rearing to the more readily identifiable adult stage was not possible. Given the host plant species, the obvious suspect was Anthonomus eugenii Cano, the pepper weevil, an extremely damaging pest of Capsicum spp. In the previous year, this species has been detected on a number of separate occasions in consignments of chillies arriving in the UK from the Caribbean and Mexico. This pest is thought to originate from Mexico but is now known to occur in the southern states of North America, Central America, the Caribbean, Hawaii, and French Polynesia (Speranza et al. 2014). It is, however, not known to occur at all in South America, and furthermore it is an A1 quarantine listed pest for Brazil. If confirmed as A. eugenii, this would have represented a very significant extension of the geographic range for this pest. As a consequence, the finding would need to be reported to the Brazilian NPPO given its potential impact on Capsicum production within that country and future trade in this commodity.
DNA barcoding of the specimen (accession number KU531398) was undertaken in an attempt to provide a confirmatory identification, but the closest sequence matches were at 84%–85% similarity with those in the NCBI database (e.g., accession numbers GU981502, KM440232). More significantly, there was only a 79% sequence identity between the specimen and in-house reference sequences for A. eugenii, which allowed us to rule out A. eugenii as the intercepted species. The specimen in this case represents a species for which there are currently no published sequences, suggesting perhaps that it is a little known or very minor pest that would not warrant any further action being taken. In the past, when this technology was not available it is possible that destruction of the consignment could have been actioned as a precautionary measure on suspicion of the presence of A. eugeniii. In this case, the use of DNA barcoding prevented such unnecessary action from being taken.
Case study 4: Understudied taxa
Perhaps the greatest limiting factor in the deployment of DNA barcoding for diagnostic purposes is the lack of sufficiently robust references sequences produced from correctly identified material. Numerous international efforts to build reference sequence databases have occurred, but there remain countless omissions, particularly for niche and unusual applications, less abundant species, and understudied taxa. Specific efforts to build reference databases for regulated pest and pathogens have been undertaken (Bonants et al. 2013; van de Vossenberg et al. 2013). These have included important aspects such as sequencing closely related species so that a decisions can be made as to whether or not a barcode is discriminatory, and so that morphologically similar “look-a-like” species, which may be intercepted alongside regulated pests, can be differentiated. However, the substantial breadth of taxonomic samples that may pass through a diagnostic laboratory means that this is very difficult to accomplish comprehensively. Indeed, when barcoding protocols have been developed the taxonomic coverage is often to meet a specific local need (Armstrong and Ball 2005). These situations are further compounded by not all sequence databases making reference sequences available for public download; whilst users can search these databases they cannot then perform in-depth analysis themselves. It is the combination of these issues that can lead to instances where DNA barcoding is inadequate for identification. However, it can be deployed to develop the method for future scenarios, as seen in the following example.
Fallopia japonica (Japanese knotweed) is an invasive weed species and is spreading rapidly in the UK, the rest of Europe, and North America where it causes extensive damage (Kurose et al. 2015). The plant is a threat on multiple fronts, affecting buildings and infrastructure, reducing floral and faunal biodiversity, and increasing the risk of flooding (Skinner et al. 2012). In its native habitat in Japan, F. japonica is controlled to an extent by naturally occurring predators and pathogens; therefore, classical biological control studies have aimed at identifying a suitable control agent from this cohort (Myint et al. 2012; Kurose et al. 2015).
One candidate organism that reached the point of field trials as a potential biological control agent for F. japonica in the UK is the specialist knotweed-feeding psyllid, or jumping plant louse, Aphalara itadori Shinji (Hemiptera: Psyllidae). Aphalara itadori has been shown to have a very narrow host range, primarily feeding only on F. japonica. This was proven to the satisfaction of UK regulatory bodies by extensive long-term biological studies based on forced rearing experiments on other closely related plants native to the UK (Shaw et al. 2009). The data clearly indicated that when released A. itadori would be restricted to F. japonica and should not spread onto other plants. Thus, in 2010 a population of A. itadori was brought from Japan and released on several sites in the South of the UK (Myint et al. 2012).
The morphological identification of A. itadori is a time-consuming job that requires specialist skills and experience, so it was clear that there was a need for alternative methods for rapidly identifying psyllids in and around release sites. As there are no species-specific molecular detection methods for A. itadori, DNA barcoding was selected; however, database searches revealed a very limited number of reference sequences for UK native psyllids. Therefore, the first stage of the developmental process was to obtain a range of UK native psyllid species, confirm their identity using classical morphological methods and key reference works, and from these generate a series of reference sequences. Of the 13 species obtained, only 4 could be identified by comparison to published sequences (>99% identity). A further two presented possible problems with published reference sequences (Table 1). For one of those (Baopelma foersteri, Flor), the freshly collected and verified specimens were found to share only an 84% sequence identity to the published sequences labelled as the same species (accession number JX987966), and there was a 100% match to a non-disclosed specimen (Psyllidae sp. BOLD:ACV498). The second, a specimen freshly collected and identified as Aphalara polygoni (Foerster, 1848), showed a 99.8% sequence identity to a published sequence identified as Aphalara freiji (BOLD:ACY0265). These anomalies suggest that either the published sequences are based on misidentified specimens, or possibly that the freshly collected material represents a previously unknown and morphologically cryptic new species.
The reference sequences generated in this project could be used to discriminate between all the reference species (Fig. 5) and were successfully deployed to identify unknown specimens collected from the field. In addition, the new sequences could be used to develop a more rapid, species-specific molecular identification tool such as real-time PCR should this be required in the future.
Fig. 5.
General discussion
Within a diagnostic laboratory, DNA barcoding is an attractive proposition; it can provide an identification in the absence of the required taxonomic expert. Even in laboratories that draw upon a combination of morphological and molecular methods, there are numerous reasons for the deployment of barcoding, which are most often related to instances of damaged specimens or interception of life stages that cannot be morphologically identified. Using DNA barcoding to rule-out a suspected high-risk species, for example, preventing “false alarms” by identifying native species, can often be as important as those instances of findings of significant regulated quarantine species. With the understanding that performing DNA barcoding may not necessarily result in a species identification, the technique has many merits that will lead to its implementation and use in diagnostics laboratories.
The seminal work of Dr. Paul Hebert and co-workers (Hebert et al. 2003) brought DNA barcoding to the scientific mainstream; the wide applicability of DNA barcoding has meant that it has been very broadly used across numerous scientific disciplines. The advent of any new diagnostic protocol is typically the start of a lengthy process of evolution, before those techniques that are truly widely applicable, robust, and practical make their way into diagnostic laboratories. Whilst sequencing is not a new concept, the neat conceptual framework of DNA barcoding make it an attractive proposition for diagnostic laboratories, which often need generic methodologies to use alongside species-specific tests (Boonham et al. 2008) and morphological identification.
Nevertheless, there are still limitations and drawbacks of DNA barcoding, primarily around the lack of required referenced sequences. Furthermore, care must be taken when utilising methods such as DNA barcoding that rely upon species placement within phylogenetic trees and (or) percentage sequence similarities. In particular, robustness of identifications must be ensured when reference sequences for relevant taxa may not be present, and systems for determining when relevant taxa are not present or are not reliable must be in place (Collins and Cruickshank 2013). Thorough analysis and contextualisation of an identification to ensure its congruence with other pertinent information such as origin, pathway, and past host and geographic records enable the suitability of DNA barcoding of a given sample to be determined on a case-by-case basis. The lack of reference sequences will gradually reduce over time as more sequences are made available; however, the quality of reference sequences, from correctly identified specimens, is essential, and there are numerous examples of sequences assigned to the incorrect species in public databases (Shen et al. 2013). These erroneous sequences can make assessment of a potential barcode challenging, and compliance of all scientists using DNA barcoding with the recommended data standards for DNA barcode sequence records (Hanner et al. 2009) will help to reduce these issues. The lack of whole-organism taxonomic expertise is, however, going to remain a rate-limiting step.
A more recent development of DNA barcoding is its combination with next-generation, or massively parallel, sequencing technologies leading to what has been called metabarcoding. Metabarcoding promises to provide a step change, in particular for the identification of organisms within mixtures or communities (Shokralla et al. 2014). Whilst many studies have demonstrated proof of concept (Ji et al. 2013), the technique is still in its infancy in terms of front-line application. Next-generation sequencing has decreased considerably in cost in recent years, but this has come at the expense of usable read-length. The most cost-effective sequencing platforms are MiSeq and HiSeq (Illumina), which would enable metabarcoding to be carried out cost effectively as a front-line service. However, due to the significant decrease in quality as the individual reads exceed 200 nucleotides, the maximum length of sequence that can be generated with an error rate low enough to enable accurate identification is approximately 450 nucleotides (2 × 300 nucleotides paired reads on a MiSeq). Whilst the methodology is well established for bacterial communities sequencing a 250 nucleotide fragment of the v4 region of the 16S rRNA gene (Kozich et al. 2013), this is considerably shorter than the standard barcode length for invertebrates of 650 bp, and in some applications the reduction in length results in poor species-level resolution (Liu et al. 2013). Some researchers have explored the use of shorter regions of the standard barcode, or study alternate genes that may provide improved species resolution with shorter fragments; however, this presents the perennial issue of lack of reference sequences (Deagle et al. 2014). The large number of sequencing reads generated enables some solutions; the use of multiple, shorter overlapping amplicons to assemble longer amplicons or amplifying the standard COI barcode and producing a barcode sequence by assembling together sequences from each end with shotgun sequence of the whole amplicon (Liu et al. 2013). Next-generation sequencing technologies are rapidly evolving (e.g., MinIon from Oxford Nanopore), and it is probable that within a short period of time they will be able to generate suitable read-lengths for DNA barcoding, enabling the use of existing databases.
It is interesting to note the trend towards using DNA barcoding to assign samples to molecular operational taxonomic units (MOTUs), as opposed to linking a DNA sequence to a species name assigned following morphological identification (Blaxter et al. 2005). This is a phenomenon that the overwhelming diversity of undescribed species on earth and the taxonomic impediment for identifying and describing them is driving forward (Ratnasingham and Hebert 2013) and next-generation sequencing is facilitating, and there are many potential benefits to this approach. Unfortunately, within a regulatory context this is unsatisfactory as identification of samples to a named species is needed, either using conventional or molecular means. A move towards regulation of a species described only by a numbered sequence (MOTU), not including any linkage to traditional morphological species, would be a substantial step change in methodology that is hard to envisage in the near future.
The risks posed to plant health biosecurity are continually expanding due to impacts such as increases and changes in global trade, resulting in the increased movement of exotic pests and pathogens into new regions, as well as expansion of the EU and climate change affecting both crop ranges and pest ranges (Armstrong and Ball 2005). The application of DNA barcoding can enable the identification of a wide range of pests and pathogens, and its use has resulted in the identification of quarantine-listed species and subsequent actions to contain and prevent potentially high-risk species from entering the UK. Furthermore, the use of the method has flagged potential trade routes that may pose a biosecurity risk as a pest pathway, which can then be subject to increased scrutiny. When employed within a defined scope that considers and understands the limitations of DNA barcoding, the method shows great potential as a tool that can be embedded within diagnostic laboratories.
Acknowledgements
This work was funded with the support of the Plant Health Division of the UK Department for Environment, Food & Rural Affairs (Defra). The work on Aphalara itadori was completed with funding from CABI. Material reared at Fera was held under the authority of Plant Health Licence number 33173/220099-2 and its predecessors. The authors would like to thank David Crossley (Fera) for the sample photography.
Footnote
2
Supplementary data are available with the article through the journal Web site at Supplementary Material.
References
Adamowicz S.J. 2015. International Barcode of Life: Evolution of a global research community. Genome, 58(5): 151–162.
Armstrong K.F. and Ball S.L. 2005. DNA barcodes for biosecurity: invasive species identification. Philos. Trans. R. Soc. B. Biol. Sci. 360(1462): 1813–1823.
Bantock, T., and Botting, J. 2013. British Bugs: An online identification guide to UK Hemiptera. [Online.] Available from http://www.britishbugs.org.uk/index.html [accessed 15 January 2016].
Blaxter M., Mann J., Chapman T., Thomas F., Whitton C., Floyd R., and Abebe E. 2005. Defining operational taxonomic units using DNA barcode data. Philos. Trans. R. Soc. B. Biol. Sci. 360(1462): 1935–1943.
Bonants P., Groenewald E., Rasplus J.Y., Maes M., de Vos P., Frey J., et al. 2010. QBOL: a new EU project focusing on DNA barcoding of quarantine organisms. EPPO Bull. 40(1): 30–33.
Bonants P., Edema M., and Robert V. 2013. Q-bank, a database with information for identification of plant quarantine plant pest and diseases. EPPO Bull. 43(2): 211–215.
Boonham N., Smith P., Walsh K., Tame J., Morris J., Spence N., et al. 2002. The detection of Tomato spotted wilt virus (TSWV) in individual thrips using real time fluorescent RT-PCR (TaqMan). J. Virol. Methods, 101(1–2): 37–48.
Boonham N., Glover R., Tomlinson J., and Mumford R. 2008. Exploiting generic platform technologies for the detection and identification of plant pathogens. Eur. J. Plant Pathol. 121: 355–363.
Bowles J., Blair D., and McManus D.P. 1992. Genetic variants within the genus Echinococcus identified by mitochondrial DNA sequencing. Mol. Biochem. Parasitol. 54: 165–173.
Braasch H. 2001. Bursaphelenchus species in conifers in Europe: distribution and morphological relationships. EPPO Bull. 31(2): 127–142.
Braun-Kiewnick A., Viaene N., Folcher L., Ollivier F., Anthoine G., Niere B., et al. 2016. Assessment of a new qPCR tool for the detection and identification of the root-knot nematode Meloidogyne enterolobii by an international test performance study. Eur. J. Plant Pathol. 144(1): 97–108.
Bullas-Appleton E., Kimoto T., and Turgeon J.J. 2014. Discovery of Trichoferus campestris (Coleoptera: Cerambycidae) in Ontario, Canada and first host record in North America. Can. Entomol. 146(1): 111–116.
CABI. 2016. Monochamus alternatus (Japanese pine sawyer). [Online.] In invasive species compendium. CAB International, Wallingford, U.K. Available from www.cabi.org/isc [accessed 15 January 2016].
Collins R.A. and Cruickshank R.H. 2013. The seven deadly sins of DNA barcoding. Mol. Ecol. Resour. 13(6): 969–975.
Cornish-Bowden A. 1985. Nomenclature for incompletely specified bases in nucleic acid sequences: recommendations 1984. Nucleic Acids Res. 13(9): 3021–3030.
Deagle B.E., Jarman S.N., Coissac E., Pompanon F., and Taberlet P. 2014. DNA metabarcoding and the cytochrome c oxidase subunit I marker: not a perfect match. Biol. Lett. 10: 20140562.
Derycke S., Remerie T., Vierstraete A., Backeljau T., Vanfleteren J., Vincx M., and Moens T. 2005. Mitochondrial DNA variation and cryptic speciation within the free-living marine nematode Pellioditis marina. Mar. Ecol. Prog. Ser. 300: 91–103.
DeSalle R., Egan M.G., and Siddall M. 2005. The unholy trinity: taxonomy, species delimitation and DNA barcoding. Philos. Trans. R. Soc. B Biol. Sci. 360: 1905–1916.
Duffey, E.A.J. 1968. A monograph of the immature stages of oriental timber beetles (Cerambycidae). British Museum (Natural History) London. Plate XVII.
Elling A.A. 2013. Major emerging problems with minor Meloidogyne species. Phytopathology, 103(11): 1092–1102.
EPPO. 2009. Hesperophanes campestris. EPPO Bull. 39: 51–54.
EPPO. 2015. EPPO Alert list. [Online.] Available from http://www.eppo.org/QUARANTINE/quarantine.htm [accessed 15 January 2016].
EPPO. 2016. European and Mediterranean Plant Protection Organisation [Online.] Available from https://www.eppo.int/ [accessed 15 January 2016].
EPPO PM 1/2 (24). 2015. EPPO A1 and A2 lists of pests recommended for regulation as quarantine pests. [Online.] Available from https://www.eppo.int/QUARANTINE/quarantine.htm [accessed 15 January 2016].
EPPO PM 7/119 (1). 2013. Nematode extraction. EPPO Bull. 43: 471–495.
EPPO PM 7/4 (3). 2013. Bursaphelenchus xylophilus. EPPO Bull. 43: 105–118.
EPPO PM 7/41 (2). 2009. Meloidogyne chitwoodi and Meloidogyne fallax. EPPO Bull. 39: 5–17.
EPPO PM 7/98 (2). 2014. Specific requirements for laboratories preparing accreditation for a plant pest diagnostic activity. EPPO Bull. 44(2): 117–147.
EPPO Reporting Service No. 10. 2013. Article number 2013/217.
EU. 2000. Council Directive 2000/29/EC of 8 May 2000 on protective measures against the introduction into the Community of organisms harmful to plants or plant products and against their spread within the Community. Off. J. Eur. Communities: Legis. L169/1: 1–112.
Folmer O., Black M., Hoeh W., Lutz R., and Vrijenhoek R. 1994. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol. Mar. Biol. Biotechnol. 3(5): 294–297.
Francis C.M., Borisenko A.V., Ivanova N.V., Eger J.L., Lim B.K., Guillén-Servent A., et al. 2010. The role of DNA barcodes in understanding and conservation of mammal diversity in Southeast Asia. PLoS ONE, 5(9): e12575.
Gressitt J.L. 1942. Destructive longhorn beetle borers at Canton, China. Spec. Publ. Lingnan Nat. Hist. Surv. Mus. 1: 1–60.
Hajibabaei M., Janzen D.H., Burns J.M., Hallwachs W., and Hebert P.D.N. 2006. DNA barcodes distinguish species of tropical Lepidoptera. Proc. Natl. Acad. Sci. U.S.A. 103(4): 968–971.
Hajibabaei M., Singer G.A.C., Hebert P.D.N., and Hickey D.A. 2007. DNA barcoding: how it complements taxonomy, molecular phylogenetics and population genetics. Trends Genet. 23(4): 167–172.
Han H., Cho M.R., Jeon H.Y., Lim C.K., and Jang H.I. 2004. PCR-RFLP identification of three major Meloidogyne species in Korea. J. Asia-Pac. Entomol. 7(2): 171–175.
Hanner, R., Database Working Group, Consortium for the Barcode of Life. 2009. Data standards for BARCODE records in INSDC (BRIs).
Hebert P.D., Cywinska A., Ball S.L., and deWaard J.R. 2003. Biological identifications through DNA barcodes. Proc. R. Soc. (Lond.), 270(1512): 313–321.
Hodkinson, I.D., and White, I.M. 1979. Homoptera, Psylloidea. Handbooks for the Identification of British Insects. Vol. 2, part 5A. Royal Entomological Society, London.
Holmes B.H., Steinke D., and Ward R.D. 2009. Identification of shark and ray fins using DNA barcoding. Fish. Res. 95(2–3): 280–288.
Hooper, D.J. 1986. Extraction of nematodes from plant tissue. In Laboratory methods for work with plant and soil nematodes. Edited by J.F. Southey. Reference Book 402. 6th ed. London, Ministry of Agriculture, Fisheries and Food. pp. 51–58.
Hope F.W. 1843. Descriptions of the coleopterous insects sent to England by Dr. Cantor from Chusan and Canton, with observations on the entomology of China. Ann. Mag. Nat. Hist. 11: 62–66.
Hrcek J., Miller S.E., Quicke D.L.J., and Smith M.A. 2011. Molecular detection of trophic links in a complex insect host–parasitoid food web. Mol. Ecol. Resour. 11(5): 786–794.
Huang K.S., Lee S.E., Yeh Y., Shen G.S., Mei E., and Chang C.M. 2010. Taqman real-time quantitative PCR for identification of western flower thrip (Frankliniella occidentalis) for plant quarantine. Biol. Lett. 6(4): 555–557.
Invasive.org. 2010. Bugwood wiki for Japanese pine sawyer (Monochamus alternatus Hope, 1843). [Online.] Available from http://www.invasive.org/ [accessed 15 January 2016].
Ji Y., Ashton L., Pedley S.M., Edwards D.P., Tang Y., Nakamura A., et al. 2013. Reliable, verifiable and efficient monitoring of biodiversity via metabarcoding. Ecol Lett. 16(10): 1245–1257.
Jones J.T., Haegeman A., Danchin E.G., Gaur H.S., Helder J., Jones M.G., et al. 2013. Top 10 plant–parasitic nematodes in molecular plant pathology. Mol. Plant Pathol. 14(9): 946–961.
Karssen G. 1996. Description of Meloidogyne fallax n.sp. (Nematoda: Heteroderidae), a root-knot nematode from the Netherlands. Fund. Appl. Nematol. 19(6): 593–599.
Kiewnick S., Wolf S., Willareth M., and Frey J.-E. 2013. Identification of the tropical root-knot nematode species Meloidogyne incognita, M. javanica and M. arenaria using a multiplex PCR assay. Nematology, 15: 891–894.
Kiewnick S., Holterman M., van den Elsen S., van Megen H., Frey J.E., and Helder J. 2014. Comparison of two short DNA barcoding loci (COI and COII) and two longer ribosomal DNA genes (SSU & LSU rRNA) for specimen identification among quarantine root-knot nematodes (Meloidogyne spp.) and their close relatives. Eur. J. Plant Pathol. 140(1): 97–110.
Kikuchi T., Aikawa T., Oeda Y., Karim N., and Kanzaki N. 2009. A rapid and precise diagnostic method for detecting the pinewood nematode Bursaphelenchus xylophilus by loop-mediated isothermal amplification. Phytopathology, 99(12): 1365–1369.
Kojima T. 1931. Further investigation on the immature stages of some Japanese cerambycid-beetles, with notes on their habits. J. Coll. Agric. Imperial Univ. Tokyo, 11(3): 263–308.
Kozich J.J., Westcott S.L., Baxter N.T., Highlander S.K., and Schloss P.D. 2013. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 79(17): 5112–5120.
Kress W.J., García-Robledo C., Uriarte M., and Erickson D.L. 2015. DNA barcodes for ecology, evolution, and conservation. Trends Ecol. Evol. 30(1): 25–35.
Kurose D., Furuya N., Seier M.K., Djeddour D.H., Evans H.C., Matsushita Y., et al. 2015. Factors affecting the efficacy of the leaf-spot fungus Mycosphaerella polygoni-cuspidati (Ascomycota): a potential classical biological control agent of the invasive alien weed Fallopia japonica (Polygonaceae) in the UK. Biol. Control, 85: 1–11.
Liu S., Li Y., Lu J., Su X., Tang M., Zhang R., et al. 2013. SOAPBarcode: revealing arthropod biodiversity through assembly of Illumina shotgun sequences of PCR amplicons. Methods Ecol. Evol. 4: 1142–1150.
Myint Y.Y., Nakahira K., Takagi M., Furuya N., and Shaw R.H. 2012. Using life-history parameters and a degree-day model to predict climate suitability in England for the Japanese knotweed psyllid Aphalara itadori Shinji (Hemiptera: Psyllidae). Biol. Control, 63(2): 129–134.
Ossiannilsson, F. 1992. The Psylloidea (Homoptera) of Fennoscandia and Denmark. Fauna Entomologica Scandinavica. Vol. 26. Brill, Leiden.
Ostojá-Starzewski J.C. 2014. Imported furniture—a pathway for the introduction of plant pests into Europe. EPPO Bull. 44(1): 34–36.
Perry, R.N., Moens, M., and Starr, J.L. 2009. Root-knot nematodes. CABI International, Oxfordshire, UK.
Ratnasingham S. and Hebert P.D.N. 2007. BOLD: The Barcode of Life Data System (http://www.barcodinglife.org). Mol. Ecol. Notes, 7(3): 355–364.
Ratnasingham S. and Hebert P.D.N. 2013. A DNA-Based Registry for All Animal Species: The Barcode Index Number (BIN) System. PLoS ONE, 8(7): e66213.
Ruiter D.E., Boyle E.E., and Zhou X. 2013. DNA barcoding facilitates associations and diagnoses for Trichoptera larvae of the Churchill (Manitoba, Canada) area. BMC Ecol. 13: 5.
Ryss A., Vieira P., Mota M., and Kulinich O. 2005. A synopsis of the genus Bursaphelenchus Fuchs, 1937 (Aphelenchida: Parasitaphelenchidae) with keys to species. Nematology, 7(3): 393–458.
Sapkota R., Skantar A.M., and Nicolaisen M. 2016. A TaqMan real-time PCR assay for detection of Meloidogyne hapla in root galls and in soil. Nematology, 18(2): 147–154.
Shaw R.H., Bryner S., and Tanner R. 2009. The life history and host range of the Japanese knotweed psyllid, Aphalara itadori Shinji: Potentially the first classical biological weed control agent for the European Union. Biol. Control, 49(2): 105–113.
Shen Y.-Y., Chen X., and Murphy R.W. 2013. Assessing DNA barcoding as a tool for species identification and data quality control. PLoS ONE, 8(2): e57125.
Shin S., Jung S., Heller K., Menzel F., Hong T.K., Shin J.S., et al. 2015. DNA barcoding of Bradysia (Diptera: Sciaridae) for detection of the immature stages on agricultural crops. J. Appl. Entomol. 139(8): 638–645.
Shokralla S., Gibson J.F., Nikbakht H., Janzen D.H., Hallwachs W., and Hajibabaei M. 2014. Next-generation DNA barcoding: using next-generation sequencing to enhance and accelerate DNA barcode capture from single specimens. Mol. Ecol. Resour. 14(5): 892–901.
Simon C., Frati F., Beckenbach A., Crespi B., Liu H., and Flook P. 1994. Evolution, weighting and phylogenetic utility of mitochondrial gene sequences and a compilation of conserved polymerase chain reaction primers. Ann. Entomol. Soc. Am. 87(6): 651–701.
Simon C., Buckley T.R., Frati F., Stewart J.B., and Beckenbach A.T. 2006. Incorporating molecular evolution into phylogenetic analysis, and a new compilation of conserved polymerase chain reaction primers for animal mitochondrial DNA. Annu. Rev. Ecol. Evol. Syst. 37: 545–579.
Skinner R.H., van der Grinten M., and Gover A.E. 2012. Planting native species to control site reinfestation by Japanese knotweed (Fallopia japonica). Ecol. Restor. 30(3): 192–199.
Speranza S., Colonnelli E., Garonna A.P., and Laudonia S. 2014. First record of Anthonomus eugenii (Coleoptera: Curculionidae) in Italy. Fla. Entomol. 97(2): 844–845.
Steiner G. and Buhrer E.M. 1934. Aphelenchoides xylophilus, n. sp, a nematode associated with blue stain and other fungi in timber. J. Agric. Res. 48: 949–951.
Tamura K., Dudley J., Nei M., and Kumar S. 2007. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24(8): 1596–1599.
Togashi K. 1985. Transmission curves of Bursaphelenchus xylophilus (Nematoda: Aphelenchoididae) from its vector, Monochamus alternatus (Coleoptera: Cerambycidae), to pine trees with reference to population performance. Appl. Entomol. Zool. (Jpn.), 20(3): 246–251.
Twinn, P.F.G., and Harding, P.T. 1999. Provisional atlas of the longhorn beetles (Coleoptera, Cerambycidae) of Britain. Biological Records Centre, Cambridge, UK. ISBN 1 87 0393 40 0.
UK. 2015. The plant health (England) order 2015. No. 610 of 1 July 2015. Statutory Instruments, pp. 1–144.
van de Vossenberg B.T.L.H., Westenberg M., and Bonants P.J.M. 2013. DNA barcoding as an identification tool for selected EU-regulated plant pests: an international collaborative test performance study among 14 laboratories. EPPO Bull. 43(2): 216–228.
Virgilio M., Jordaens K., Breman F.C., Backeljau T., and De Meyer M. 2012. Identifying insects with incomplete DNA barcode libraries, African fruit flies (Diptera: Tephritidae) as a test case. PLoS ONE, 7(2): e31581.
Wesemael W.M.L., Viaene N., and Moens M. 2011. Root-knot nematodes (Meloidogyne spp.) in Europe. Nematology, 13(1): 3–16.
Will K.W., Mishler B.D., and Wheeler Q.D. 2005. The perils of DNA barcoding and the need for integrative taxonomy. Syst. Biol. 54(5): 844–851.
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Volume 59 • Number 11 • November 2016
Pages: 1033 - 1048
Editor: John-James Wilson
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Received: 15 January 2016
Accepted: 15 July 2016
Version of record online: 28 October 2016
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This paper is part of a special issue entitled Barcodes to Biomes.
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Jennifer Hodgetts, Jozef C. Ostojá-Starzewski, Thomas Prior, Rebecca Lawson, Jayne Hall, and Neil Boonham. 2016. DNA barcoding for biosecurity: case studies from the UK plant protection program. Genome. 59(11): 1033-1048. https://doi.org/10.1139/gen-2016-0010