DOI: 10.13102/sociobiology.v65i3.2885Sociobiology 65(3): 422-432 (September, 2018) Open access journal: http://periodicos.uefs.br/ojs/index.php/sociobiology ISSN: 0361-6525 Sequencing the Ant fauna of a Small Island: Can Metagenomic Analysis Enable Faster Identification for Routine Ant Surveys? Introduction Recent advances in sequencing technology (Next Generation Sequencing or NGS) have expanded the possibilities of using DNA barcoding to identify species in complex environmental surveys (Telfer et al., 2015). Using improved NGS techniques, often referred to as Abstract All known ant species from a small Western Australian island were subjected to DNA barcoding of the CO1 gene, with a view to using the database to identify ants by Next Generation Sequencing in subsequent, routine surveys. A further aim was to evaluate whether the data could be used to see if any new species had arrived on the island since the total fauna had been inventoried. Of the 125 unique ant species then known from the island, 72 were successfully barcoded. Those that were refractory to amplification were largely the result of sample age and/or contamination. Following this base-line barcoding, ants were sampled from 14 regular sampling sites and ant sequences were obtained from the bulked ‘metagenomic soup’. Prior to doing this, a parataxonomist had identified all ant species in the samples and returned them to the ‘soup’. Successful identification for each site varied from 38% (Sites 12 and 27) to 100% of species (Site 10). Comparison of the number of species recovered with the number of sequences obtained from each sample showed a positive correlation between the two variables. When a site had >1,000 sequences, the average recovery rate was 79%, which is in contrast to the lowest four recovery rates (Site samples 12, 22, 26 and 27), which had fewer than 440 amplicon sequences. The ability to detect individuals that occur at low frequencies is also important. We analysed each site individually to determine if a species was detected and how that related to the proportion of individuals in the pooled sample. Where a species was present at <4% of the total sample, it was only detected 10% of the time, indicating that adequate sequencing depth is critical to species recovery. We conclude that this technique was only partially successful in replacing conventional taxonomy and that it could have limited ability to detect incursions unless the new arrival is abundant. Current barcoding is no longer limited to the CO1 gene and other genes are characterised for identification of intractable groups where CO1 does not provide appropriate levels of resolution. Sociobiology An international journal on social insects JD Majer1,2,3, MA Castalanelli4, JL Ledger4, NR Gunawardene 2, BE Heterick2,3 Article History Edited by Gilberto M. M. Santos, UEFS, Brazil Received 09 February 2018 Initial acceptance 28 March 2018 Final acceptance 10 Abril 2018 Publication date 02 October 2018 Keywords Next Generation Sequencing, Barrow Island, Evaluation, Biosecurity, Ant incursion. Corresponding author Jonathan D. Majer School of Biological Sciences University of Western Australia Perth, WA 6009, Australia E-Mail: jonathan.majer@uwa.edu.au “Metagenomics”, the effects of environmental change (e.g., deforestation, resource extraction, site development) can be examined at the level of whole ecosystems (e.g., Beng et al., 2016; Gibson et al., 2014; Ji et al., 2013; Smith et al., 2005; Yang et al., 2014; Yu et al., 2012). This can be achieved by establishing a baseline record of biodiversity within an ecosystem and then routinely comparing the 1 - School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia 2 - Department of Environment and Agriculture, Curtin University, Perth, WA 6102, Australia 3 - Western Australian Museum, Perth, WA 6000, Australia 4 - EcoDiagnostics Pty. Ltd., 46 - 48 Banksia Rd, Welshpool WA 6106, Australia RESEARCH ARTICLE - ANTS Sociobiology 65(3): 422-432 (September, 2018) 423 current biodiversity to that of the baseline, a procedure that is exemplified by the approaches of Yu et al. (2012) and Kocher et al. (2017). Rather than sorting and separating specimens, DNA is extracted from a batch or ‘soup’ of specimens from a field collection (often >100 specimens in a vial) and the DNA sequenced using NGS techniques (Pochon et al., 2013; Yoon et al., 2016). This technique allows hundreds of different taxa to be sequenced simultaneously and the sequence data that is generated can be compared, as a batch, to the DNA reference library. Outputs from studies of this type provide huge data- sets, and lead to a good understanding of sample diversity at a reasonable cost (Ji et al., 2013). More importantly, previously unrecorded species that are rare, cryptic, or are invasive may be identified because their genetic signature differs from the reference database. The Barrow Island Invertebrate Surveillance project provided an opportunity to evaluate the application of this technique in an invertebrate species context, concentrating on the ant fauna. Barrow Island is Western Australia’s second largest offshore island; it is a Class A Reserve and also happens to be Australia’s only land-based oil field. The presence of industrial interests on the island, and also its important conservation value, has meant that the island is not publicly accessible. This has resulted in the exclusion, or control and eradication of non-indigenous or invasive species. In 2009, Chevron Australia Pty Ltd and its Joint Venture Participants undertook the construction of a liquefied natural gas plant on the island. One of the conditions under which approval for the plant was granted was the implementation of a rigorous biosecurity effort to ensure that no non-indigenous species (NIS) were allowed to establish on the island and, if any new species were to be introduced, have a 0.8 probability of detection if they are present. To fulfill this condition a non- indigenous species surveillance program was implemented. If NGS procedures were to be used for diagnostics, it would be critical for the technique to be sensitive and reliable enough to detect previously unrecorded species. The aim of this pilot study is to evaluate whether this is achievable using a single gene. A series of systematic surveys on flora and fauna has been performed using purpose-designed sampling protocols in order to provide baseline data on the existing terrestrial invertebrate species on Barrow Island. As part of the fauna surveys, terrestrial invertebrates were sampled between 2005 and 2008 (Majer et al., 2013). Callan et al. (2011) initially recorded a total of 1,873 species and morphospecies, with subsequent surveys and taxonomic developments increasing the count to 2,670 species with 25 invertebrate species considered non-indigenous to BWI (Thomas et al., 2017). The Barrow Island collection represents one of the few areas in Australia where sampling of invertebrates has occurred before and after development. The ant species on Barrow Island are well-documented, totalling 125 (since upgraded to 129) species, none of which are endemic to the island (Heterick, 2013). The presence of a voucher specimen library of dry and wet preserved ant species from the island enabled us to establish a reference DNA barcoding library for the Barrow Island ants. DNA was extracted and barcoded for specimens of each species to establish a DNA reference database. As regular, repeated surveys of invertebrate species are still ongoing on Barrow Island, a pilot study was then conducted to test whether the ant specimens collected in subsequent samples could be verified using the NGS technique and the DNA reference database. Specifically, we evaluated the efficacy of universal forward primer CI-J-1718 and the reverse primers HCO and CI-N-2191 in recovering and identifying multiple ant species within a trap using a Roche’s 454 GS-Junior metabarcoding approach. GS-Junior was selected due to its ability (at the time) to sequence >400 bps per direction, and this was seen as a cost effective solution. We intended that the reference database of ant species barcodes could be used by future researchers to rapidly determine the species composition within samples taken from the field, a process that normally takes two weeks of a taxonomist’s time. In view of the fact that our surveys were designed to detect whether any NIS had been introduced during the construction of the gas liquification plant, it was thought that the technique also might have the potential to identify non-indigenous ant species if present within the collection. The NGS procedure that we utilised has since been superseded by more refined techniques such as Illumina Mi and Hi-Seq. Nevertheless, we consider it timely to report on our experiences with this procedure and to consider the feasibility of routinely using newer barcoding procedures for identifying ants and, ultimately, other invertebrates in bulk samples. Methods Invertebrate sampling: All ant species from the Barrow Island voucher specimen collection were identified morphologically by BEH. Specimens were vouchered between 2005 and 2008 at Curtin University and are now curated at the Western Australian Museum, with a duplicate set at the Western Australian Department of Primary Industries and Regional Development. The majority of the voucher collection is dry-preserved, with some species requiring vouchers from more recent surveys due to the deterioration of the original voucher specimen. Single specimens of all 125 ant species (Appendix 1) were submitted for barcoding in order to provide baseline data for the ant fauna of the Island. Then, in order to test whether it is feasible to identify ants from unsorted trap samples, 14 of the Barrow Island sites were sampled in September 2013 using multiple trapping methods. These were: 1) Night Hand Collection (NHC), a method whereby trained field workers collect ants by hand in the evening (this method typically yields low abundances of ant species but more cryptic diversity); 2) Window Trap (WIN), which is a water trap with JD Majer, MA Castalanelli, JL Ledger, NR Gunawardene, BE Heterick – Ant bar coding for detecting incursions424 a Perspex window that captures flying insects (one drawback with this method is that many ant species are attracted by the water); 3) Suction Samples (SUC), a method whereby a garden blower/vacuum suctions small insects from low shrubs and branches and which usually yields high abundances of shrub-foraging ant species; and 4) Barrier Pitfall Trap, Bait Trap and Litter Trap (BBL), a combination of three sampling methods that focus on ground-dwelling ants and often yield high abundances of a few species. For the purpose of this exercise, all samples from a site were combined. All other invertebrate groups were removed from the samples, and the ants were identified to morphospecies by a parataxonomist before being returned to 14 vials representing the bulked samples for each of the sampling sites. The specimens were preserved in 70% ethanol. Barcoding procedure: A non-destructive DNA extraction method, ANDE (Castalanelli et al., 2010), was used to extract DNA from the morphologically identified ant specimens and from the bulked, unsorted trap samples. Amplification of the target barcoding region from individual ant specimens was performed using the Cytochrome Oxidase 1 (CO1) primers outlined in Table 1. Following PCR amplification of the target region and subsequent DNA sequencing, sequences were edited using Geneious Pro 8.0.3 (Biomatters Ltd) and aligned with the reference data set using Geneious’ built-in alignment algorithm. Geneious Pro 8.0.3 was used to detect the presence of NuMTs by translating each CO1 sequence with the standard invertebrate and Drosophila codes. Forward and reverse sequences were manually edited, primer sequences removed, and the final quality checked. Consensus sequences were used to interrogate all available public sequence databases to determine if the morphological and molecular results used to determine the identifications were congruent. The NGS run was conducted using Roche GS Junior (454). This NGS platform was selected due to its lower cost and its ability to generate sequence lengths >400bp per direction. The sequencing run was performed at the Western Australian State Agriculture Biotechnology Centre (SABC). Analysis of the NGS data was conducted using an EcoDiagnostics Pty. Ltd. in-house bioinformatics pipeline which de-convoluted the DNA sequences into individual site samples and then compared sets of sequences from each sample to the CO1 reference database. Results Baseline ant data: a summary of the sample sequencing outcomes for the 126 ant species is shown in Table 2 and sequences for each of these species are deposited in Genbank. In total, 72 species were successfully DNA barcoded and the remaining 53 were unsuccessful. Five samples returned a DNA barcode that was incongruent with the morphological result and were considered contaminated due to their molecular similarity to the barcode for a species of gastropod that is commonly found in some of the invertebrate samples. Of the remaining 48 species that failed to generate a sequence age of the specimens was a possible reason for failure. For 13 species that failed to amplify, sequences from public databases (i.e., NCBI; Genbank) were available and hence substituted for the failed amplification. Primer Sequence 5’ – 3’ CI-J-1718 GGA GGA TTT GGA AAT TGA TTA GTT CC CI-N-2191 CCC GGT AAA ATT AAA ATA TAA ACT TC LCO GGT CAA CAA ATC ATA AAG ATA TTG G HCO TAA ACT TCA GGG TGA CCA AAA AAT CA Table 1. Cytochrome Oxidase 1 primers used to generate DNA barcodes for the reference database. DNA originating from each site sample was amplified using the forward primer CI-J-1718 and the reverse primers HCO and CI-N-2191, with the additional M13 sequences added to the 5` end of the forward and reverse primers. A second round of PCR amplification was performed to attach the Roche Lib-A adapters to the previous PCR product. A unique MIDTag barcode specific to each individual Barrow Island site sample was also incorporated, allowing multiple samples to be pooled together for sequencing on the GS Junior. The GS Junior sequencing run was set up as per the manufacturer’s instruction, and run for 200 flows. Sequencing Result Count Successfully sequenced 72 No sequence generated 53 Sample contaminated 5 External public database sequence (e.g. NCBI) 13 Total 125 Table 2. Summary of sample sequencing outcomes. Pooled sample analysis: The ant species found in each of the 14 pooled samples and the species that were recovered by NGS from each site are shown in Table 3. The sequencing run generated 42,098 high quality sequences; any sequences <400bp in length were removed, reducing the data set to 23,072 sequences from the 14 site samples. The number of sequences dramatically varied between site samples, with between 13 (Site sample 12) and 10,046 (Site sample 17; Table 4) amplicon sequences being recovered. Valid assignments were made when similarity of the NGS sequence to one of the reference species was greater than 95%. Since the samples were taken in September 2013, which represents only a small time capsule of the total invertebrate surveillance effort, only 39 out of the 126 ant species were present within the 14 site samples (Table 3). Six species in the 14 site samples did not have a corresponding CO1 reference sequence. Despite several sites missing one to three reference species (Table 4), the majority of site samples had >92% of their sequences assigned to a reference (Table 4). Sociobiology 65(3): 422-432 (September, 2018) 425 Species/Site ID 9 10 11 12 14 16 17 20 21 22 23 24 26 27 Anochetus rectangularis B Camponotus capito M N M Camponotus gibbinotus B M M M Camponotus fieldeae B B M B M M B B M Camponotus scratius B Camponotus simpsoni M Cardiocondyla atalanta M Iridomyrmex anceps B B B M B B B B B Iridomyrmex cephaloinclinus B Iridomyrmex chasei M B M M Iridomyrmex dromus N N N N Iridomyrmex exsanguis B B M M B M B B Iridomyrmex minor B B B B B B B M M B Iridomyrmex mjobergi M Iridomyrmex sanguineus M M M N M M M M M Melophorus biroi M M Melophorus paramorphomenus B Melophorus hirsutipes B M Meranoplus curvispina M M Monomorium laeve M M M Monomorium leae M Monomorium sydneyense B B B B Ochetellus flavipes B Ochetellus sp. JDM 527 B B B M Paratrechina longicornis B B Pheidole turneri B Pheidole variabilis B B B B B B M B B Polyrhachis ammonoeides M B M Polyrhachis inconspicua M M M M M Polyrhachis seducta M Polyrhachis sp. JDM 808 M M M N M M M M Rhytidoponera crassinoda M M Rhytidoponera taurus M M M Tetramorium spininode M Tetramorium striolatum complex M * M = Morphological identification only; N = Next generation sequencing detection only; B = Both morphological identification and Next Generation Sequencing detection Table 3. Comparison between morphological identification and molecular detection using Next Generation Sequencing. The only exception was site sample 9, where the percentage of unassigned species was 31% (Table 4). Analysis of these unassigned sequences showed that in the majority of cases they clustered with Camponotus, Iridomyrmex, and Polyrhachis clades but weren’t closely related to any particular species (>15% pairwise divergence from its closest neighbor). One issue known to occur during PCR when multiple templates are present is cross amplification of two species (Hass et al., 2017), i.e. the front half is of one species the back half is of another. Combined, they create a unique chimeric sequence that cannot be assigned to a reference. The term “recovery” is here defined as the number of species identified using the NGS barcoding approach compared to the number of morphologically identified species. Recovery for each site varied from 38% (Sites 12 and 27) to 100% (Site 10; Table 4). Six sites had additional species that JD Majer, MA Castalanelli, JL Ledger, NR Gunawardene, BE Heterick – Ant bar coding for detecting incursions426 were not recognised by morphological methods. Of particular note were the highly similar species Iridomyrmex exsanguis and Iridomyrmex dromus (Table 3). Comparison of the number of species recovered with the number of sequences obtained from each trap sample shows a positive correlation between the two variables (Fig 1). Site ID 9 10 11 12 14 16 17 20 21 22 23 24 26 27 No. of species identified morphologically 6 6 7 8 4 3 6 10 8 15 13 9 7 13 No. of species identified with NGS 6 6 6 3 2 3 6 7 7 7 7 7 3 5 No. of morphologically identified species in NGS result 5 6 6 3 2 2 5 7 5 7 6 6 3 5 No. of species missed by NGS 1 1 1 2 1 1 Percentage of species identified with NGS 83 100 86 38 50 67 83 70 63 47 46 67 43 38 No. of sequences 2,431 1,498 651 13 876 3,796 10,046 481 1,871 256 434 308 26 385 No. of species missing a CO1 reference 1 1 2 3 2 1 2 1 3 Percentage of assigned sequences 69 95 96 100 97 97 97 95 97 95 98 93 96 96 Table 4. Overview of the NGS sequencing data, including the number of species present at each site and whether they were recovered by NGS. Also shown are the outcomes of the NGS sequencing run output for each site, including the number of sequences that were assigned with > 95% similarity to a reference sequence. Fig 1. Number of 454 sequences generated per sample in relation to the percentage of species recovered. Fig 2. Sensitivity of the Next Generation Sequencing technique, illustrated by showing the rate at which a species was detected in preserved Barrow Island ant material. The “Hit” (light part of bar) shows the degree of success relative to the frequency at which that particular ant species occurred within the material. When a site had >1,000 sequences, the average recovery rate was 79%, which is in contrast to the lowest four recovery rates (Site samples 12, 22, 26 and 27), which had fewer than 440 sequences. One exception was Site 24, which produced a low number of sequences but still had 67% recovery rate (Table 4). Validating a highly sensitive technique with the ability to detect individuals that occur at low frequencies is one of the most important functions of any biosecurity venture. To examine the sensitivity of the NGS technique, we analysed each site individually to determine if a species was detected (hit) and how that related to the number of individuals per species (determined by dividing the number of species identified per site by the total number of individuals per site sample [termed species occurrence). Figure 2 indicates that where a species was present at <4% of the total sample size, it was only detected 10% of the time. As the frequency at which a species occurred increased, so too did the rate at which that species was detected. The only exceptions were Iridomyrmex minor at Sites 24 and 26, Iridomyrmex chasei at Site 24, Camponotus fieldeae at Site 16, Monomorium laeve at Site 24, and Polyrhachis ammonoeides at Site 14. Sociobiology 65(3): 422-432 (September, 2018) 427 Discussion This study demonstrates the encouraging potential of NGS metabarcoding to characterise ant species from bulk trap samples, despite the study being resource-limited (only a single sequencing run was costed). A number of technical difficulties have been highlighted in this pilot study. These include variation in the number of sequences recovered between trap sample sites (13 to 10,046) and lack of sequencing depth, which clearly affects the ability to recover species. This can be largely overcome by the rapid development of improved technologies, and we acknowledge that the sequencing platform and chemistry used in this study has largely been superseded and discontinued. Newer procedures will lead to significant improvements in the recovery of sequences from mixed trap samples that here varied between 38 and 100% for individual trap samples. Another major factor that needs to be overcome is preferential amplification. Future projects need to select priming sites that are either void of mutations or have minimal mutations and are shown to detect all intended target species in a comprehensive fashion. Increased depth and more suitable primers may lead to the development of robust and practical monitoring methods with a very high diagnostic sensitivity and specificity. The occasional incongruence between species identified by NGS and morphological species was probably caused by contamination from unrelated taxa due to their molecular similarity to the barcode concerned. This probably arose in some of our samples because traces of gastropod DNA, which were often found in our samples prior to removal of the ants, were preferentially amplified. These invertebrates were much larger than the ants and exuded a DNA-rich slime. Because of the nature of the project and its restricted resourcing, only three primer pairs could be used to try and generate sequences. These three primer pairs (Table 1) are generalist primers that have been shown to successfully amplify genetic material from invertebrates (Simon et al., 1994). However, experience has shown that 20% or more of the samples will be refractory to amplification due to primer mismatch, poor quality DNA, and PCR inhibition. Future work should involve the design of more specific primers and, if possible, fresh samples that haven’t been collected in pitfall traps. (Pitfall trapped material reveals rapid degradation of DNA and may also have high levels of contaminating DNA present (Castalanelli et al., 2011).) The variation in number of sequences between sites may be in part be attributed to the preservation of specimens in a lower grade of ethanol (i.e., 70%), which was used throughout the NIS project for specimen preservation. This may have contributed to the lack of amplification success and also to technical difficulties in making the PCR products from each trap sample of similar molarity prior to NGS library preparation. Species Species Recovery Rate (%) Number of Mutations (26bp) Number of Mutations @ 5` (5bp) Anochetus rectangularis 100 1 0 Camponotus capito 50 3 1 Camponotus gibbinotus 25 3 1 Camponotus fieldeae 56 4 1 Camponotus scratius 100 0 0 Camponotus simpsoni 0 2 1 Cardiocondyla atalanta 0 5 1 Iridomyrmex anceps 89 3 1 Iridomyrmex cephaloinclinus 100 2 1 Iridomyrmex chasei 50 2 1 Iridomyrmex exsanguis 63 NA* Missing datum Iridomyrmex minor 80 NA NA Iridomyrmex mjobergi 0 0 0 Iridomyrmex sanguineus 50 2 1 Melophorus biroi 0 NA NA Melophorus paramorphomenus 100 4 1 Melophorus hirsutipes 50 NA Missing datum Meranoplus curvispina 0 4 1 Monomorium laeve 0 3 2 Monomorium leae 0 2 0 Monomorium sydneyense 100 2 1 Ochetellus flavipes 100 3 1 Ochetellus sp. JDM 527 75 5 1 Paratrechina longicornis 100 3 1 Pheidole turneri 100 1 0 Pheidole variabilis 78 1 0 Polyrhachis ammonoeides 33 2 1 Polyrhachis inconspicua 0 NA Missing datum Polyrhachis seducta 0 NA NA Polyrhachis sp. JDM 808 43 2 0 Rhytidoponera crassinoda 0 3 1 Rhytidoponera taurus 66 4 1 Tetramorium spininode 100 1 0 Tetramorium striolatum complex 100 0 0 * NA indicates that no data was available to examine bind efficiency. Table 5. Comparison of species recovery over all sites and number of mutations within the CI-J-1715 priming site. The species that were not recovered are underlined. JD Majer, MA Castalanelli, JL Ledger, NR Gunawardene, BE Heterick – Ant bar coding for detecting incursions428 Lessons learned: This pilot study successfully generated a reference ant DNA barcode database that is fundamental to the development of improved NGS metabarcoding and DNA based individual specimen identification approaches. Our investigation revealed a number of issues of which users should be aware and take care to address, namely: • Age of material – try to use as fresh a sample as possible; • Appropriate, high-grade preservative – use preservatives that maximise preservation of genetic material; • Morphologically based taxonomy – underpin investigation with a sound taxonomic database; • Contamination of samples by non-target taxa – be aware of other taxa, including plant material, that occur in the samples and how this could contaminate the DNA; • Cross amplification between related taxa – be aware of this possibility; and • Cost of barcoding has to be considered at the outset of investigations such as this. Returning to the original thrust behind this investigation, can barcoding using the CO1 gene be used to detect ant incursions with an 80% confidence of detection? With recovery rates averaging only 79% and sometimes falling as low as 38%, the answer is no. However, though there are acknowledged gaps in the database that we have generated, these can be rectified with further study to increase the robustness of data interpretation and species identification. Furthermore, barcoding is no longer limited to CO1; more recently, other genes have been preferred for the intractable groups (e.g., see tables in Purty & Chatterjee, 2016). Acknowledgements The Gorgon Gas Development is operated by an Australian subsidiary of Chevron and is a joint venture of the Australian subsidiaries of Chevron (47.3%), ExxonMobil (25%), Shell (25%), Osaka Gas (1.25%), Tokyo Gas (1%) and JERA (0.417%). The authors are grateful to Chevron Australia Pty Ltd for on-island support with logistics, and the Gorgon Joint Venturers for financial support to undertake the surveillance component of this project. Funding from Curtin University was provided in order to undertake the barcoding of specimens. Christopher Taylor, Morgan Lythe, Brad Scanlon, and Callum Smithyman all assisted the project, either in the field and/or in the laboratory. References Beng, K.C., Tomlinson, K.W., Shen, X.H., Surget-Groba, Y., Hughes, A.C., Corlett, R.T. & Silk, J.F. (2016). The Utility of DNA Metabarcoding for Studying the Response of Arthropod Diversity and Composition to Land-use Change in the Tropics. Scientific Reports, 6: 24965. doi: 10.1038/srep24965 Recovery and sensitivity: The ability to detect an individual accurately within a particular sample is one of the most important functions of biosecurity surveillance, regardless of whether it involves morphological or molecular techniques. Therefore, we believe that the most important aspect of this pilot study is understanding recovery and sensitivity. Underpinning this is the need for good baseline data from conventional morphological taxonomic approaches. As mentioned earlier, Iridomyrmex exsanguis and Iridomyrmex dromus were not distinguished by morphological methods (Table 3). These two species are morphologically very similar, but seem to have a different nest structure and behaviour around the nest. Physically, they can only be distinguished with difficulty. The Iridomyrmex exsanguis worker is always pale yellow and has a noticeable propodeal angle, i.e., is truncate when viewed in profile. Iridomyrmex dromus is commonly pale also, but the colour can range from depigmented yellow to almost black, and viewed in profile the propodeum lacks a noticeable angle, i.e., is not truncate. Anyone considering using NGS procedures should be aware of this sort of subtlety in taxonomic differentiation. Apart from the anomaly with site 24, these results suggest that an important contributor to recovery for a given sample is the number of sequences; namely, the more sequences, or greater sequencing depth, the greater the recovery. These results are congruent with other studies that used newer technologies. For instance, Brandon-Mong et al. (2015) evaluated the MiSeq (Illumina) and showed that for lepidopteran specific primers, 106,070 sequences recovered 60%, which was increased to 80% when the number of sequences was increased to 685,208. The results presented here can generally be firstly explained by preferential amplification. While species occurrence is likely to cause some bias towards preferential amplification, it seems that primer design is the most probable cause. Since full-length DNA barcoding only allowed us to examine the primer binding site for CI-J-1715, only this section was scrutinised (Table 5). The data suggest that as the mutations within the priming site increase, the chance of recovery decreases. The noteworthy examples where primers clearly contributed to good sequence recovery were Anochetus rectangularis, Camponotus scratius, Pheidole turneri, Tetramorium spininode, and Tetramorium striolatum, all of which had either zero mutations or a single mutation and 100% recovery. In comparison, Monomorium laeve and Cardiocondyla atalanta, which had three and four mutated sites, respectively, failed to be recovered; more importantly Monomorium laeve had two mutations that occurred within the 5` binding site which is the most important part of the priming site (Table 5). Interestingly, the species that were not recovered (Table 5: underlined) tended to have mutations that ranged from two to five and a species occurrence of <7%; suggesting that priming mutations and rarity compounded the failure to recover a species. Sociobiology 65(3): 422-432 (September, 2018) 429 Biomatters Ltd. Geneious version 8.0.3. Biomatters. Available from http://www.geneious.com/ Brandon-Mong, G. J., Gan H. M., Sing, K. W., Lee, P. S., Lim, P. E. & Wilson, J.J. (2015). DNA Metabarcoding of Insects and Allies: an Evaluation of Primers and Pipelines. Bulletin of Entomological Research, 105: 717-27. doi: 10.10 17/S0007485315000681 Callan, S. K., Majer, J. D., Edwards, K. & Moro, D. (2011). Documenting the Terrestrial Invertebrate Fauna of Barrow Island, Western Australia. Australian Journal of Entomology, 50: 323-343. doi: 10.1111/j.1440-6055.2011.00818.x Castalanelli, M. A., Severtson, D. L., Brumley, C. J., Szito, A., Foottit, R. G., Grimm, M., Munyard, K. & Groth, D .M. (2010). A Rapid Non-destructive DNA Extraction Method for Insects and Other arthropods. Journal of Asia-Pacific Entomology, 13: 243-248. doi: 10.1016/j.aspen.2010.04.003 Castalanelli, M. A., Mikac, K. M., Baker, A. M., Munyard, K., Grimm, M. & Groth, D. M. (2011). Multiple Incursions and Putative Species Revealed Using a Mitochondrial and Nuclear Phylogenetic Approach to the Trogoderma variabile (Coleoptera: Dermestidae) trapping program in Australia. Bulletin of Entomological Research, 101: 333-343. doi: 10.1017/S0007485310000544 Gibson, J., Shokralla, S., Porter, T. M., King, I., Van Konynenburg, S., Janzen, D. H., Hallwachs, W. & Hajibabael, M. (2014). Simultaneous Assessment of the Macrobiome and Microbiome in a Bulk Sample of Tropical Arthropods through DNA Metasystematics. PNAS, 111: 8007-8012. doi: 10.1073/pnas.1406468111 Haas, B. J., Gevers, D., Earl, A. M., Feldgarden, M., Ward, D. V., Giannoukos, G., Ciulla, D., Tabbaa, D., Highlander, S. K., Sodergren, E. & Methé, B. (2011). Chimeric 16S rRNA Sequence Formation and Detection in Sanger and 454-pyrosequenced PCR Amplicons. Genome Research, 21: 494-504. doi: 10.1101/gr.112730.110 Heterick, B. E. (2013). A Taxonomic Overview and Key to the Ants of Barrow Island, Western Australia. Records of the Western Australian Museum, Supplement, 83: 375-404. doi: 10.18195/issn.0313-122x.83.2013.375-404 Ji, Y, Ashton, L., Pedley S. M., Edwards, D. P., Tang, Y., Nakamura, A., Kitching, R., Dolman, P. M., Woodcock, P., Edwards, F. A. & Larsen, T. H. (2013). Reliable, Verifiable and Efficient Monitoring of Biodiversity via Metabarcoding. Ecology Letters, 16: 1245-1257. doi: 10.1111/ele.12162 Kocher, A., Gantier, J. C., Gaborit, P., Zinger, L., Holota, H., Valiere, S., Dusfour, I., Girod, R., Bañuls, A. L. & Murienne, J. (2017). Vector Soup: High-Throughput Identification of Neotropical Phlebotomine Sand flies Using Metabarcoding. Molecular Ecology Resources, 17: 172-182. doi: 10.1111/1755-0998.12556 Majer, J. D., Callan, S. K., Edwards, K., Gunawardene, N. R. & Taylor, C. K. (2013). Baseline Survey of the Terrestrial Invertebrate Fauna of Barrow Island. Records of the Western Australian Museum, Supplement, 83: 13-112. doi: 10.18195/ issn.0313-122x.83.2013.013-112 Pochon, X., Bott, N. J., Smith, K. F. & Wood, S. A. (2013). Evaluating Detection Limits of Next-generation Sequencing for the Surveillance and Monitoring of International Marine Pests. PLoS ONE, 8(9): e73935. doi: 10.1371/journal.pone.0073935 Purty, R. S. & Chatterjee, S. (2016). DNA Barcoding: An Effective Technique in Molecular Taxonomy. Austin Journal of Biotechnology and Bioengineering, 3: 1059. Simon, C., Frati, F., Beckenbach, A., Crespi, B., Liu, H., & Flook, P. (1994). Evolution, Weighting, and Phylogenetic Utility of Mitochondrial Gene Sequences and a Compilation of Conserved Polymerase Chain Reaction Primers. Annals of the Entomological Society of America, 87: 651-701. doi: 10.1093/aesa/87.6.651 Smith, M. A., Fisher, B. L. & Hebert P. D. N. (2005). DNA Barcoding for Effective Biodiversity Assessment of a Hyperdiverse Arthropod Group: the Ants of Madagascar. Philosophical Transactions of the Royal Society of London, B Biological Sciences, 360: 1825-34. doi: 10.1098/rstb.2005.1714 Telfer, A. C., Young, M. R., Quinn, J., Perez, K., Sobel, C. N., Sones, J. E., Levesque-Beaudin, V., Derbyshire, R., Fernandez- Triana, J., Rougerie, R. & Thevanayagam, A., (2015). Biodiversity Inventories in High Gear: DNA Barcoding Facilitates a Rapid Biotic Survey of a Temperate Nature Reserve. Biodiversity Data Journal, 3: e6313. doi: 10.3897/BDJ.3.e6313 Thomas, M. L., Gunawardene, N., Horton, K., Williams, A., O’Connor, S., McKirdy, S. & Van der Merwe, J. (2017). Many Eyes on the Ground: Citizen Science is an Effective Early Detection Tool for Biosecurity. Biological Invasions, 19: 1-15. doi: 10.1007/s10530-017-1481-6 Yang, C., Wang, X., Miller, J. A., De Blécourt, M., Ji, Y, Yang, C, Harrison, R.D. & Douglas, W. Y. (2014). Using Metabarcoding to Ask if Easily Collected Soil and Leaf-litter Samples Can be used as a General Biodiversity Indicator. Ecological Indicators, 46: 379-89. doi: 10.1016/j.ecolind.2014.06.028 Yoon, T. H., Kang, H. E., Kang, C. K., Lee, S. H., Ahn, D. H., Park, H. & Kim, H. W. (2016). Development of a Cost-effective Metabarcoding Strategy for Analysis of the Marine Phyto- plankton Community. PeerJ, 4: e2115. doi: 10.7717/peerj.2115 Yu, D. W., Ji, Y., Emerson, B.C., Wang, X., Ye, C., Yang, C. & Ding, Z. (2012). Biodiversity Soup: Metabarcoding of Arthropods for Rapid Biodiversity Assessment and Biomonitoring. Methods in Ecology and Evolution, 3: 613- 623. doi: 10.1111/j.2041-210X.2012.00198.x JD Majer, MA Castalanelli, JL Ledger, NR Gunawardene, BE Heterick – Ant bar coding for detecting incursions430 Genus Species/sub-species Author Sequence GenBank Accession Number Aenictus turneri Forel Pass TBC Amblyopone sp. [queen] Pass TBC Anochetus rectangularis Mayr Pass TBC Anochetus renatae Shattuck & Slipinska, 2012 Failed Arnoldius sp. JDM 433 Failed Brachyponera lutea (Mayr) Pass TBC Camponotus capito Mayr Pass TBC Camponotus donnellani Shattuck & McArthur Failed; Old Camponotus evae zeuxis Forel Failed Camponotus fieldeae Forel Pass TBC Camponotus gibbinotus Forel Pass TBC Camponotus lownei Forel Pass TBC Camponotus rubiginosus complex sp. JDM 1158 Failed; Old Camponotus scratius Forel Pass TBC Camponotus simpsoni McArthur Pass TBC Cardiocondyla atalanta Forel Pass TBC Cardiocondyla nuda (Mayr) Contaminated Carebara sp. JDM 1131 Failed Crematogaster laeviceps chasei Forel Pass TBC Crematogaster queenslandica Forel Failed Discothyrea clavicornis Emery Contaminated Doleromyrma rottnestensis (Wheeler) Failed Hypoponera queenslandensis (Forel) Pass TBC Iridomyrmex agilis Forel Failed; Old Iridomyrmex anceps Roger Pass TBC Iridomyrmex bicknelli Emery Pass TBC Iridomyrmex cephaloinclinus Shattuck Pass TBC Iridomyrmex chasei Forel Pass TBC Iridomyrmex coeruleus Heterick & Shattuck Pass TBC Iridomyrmex difficilis Heterick & Shattuck Pass TBC Iridomyrmex discors Forel Pass TBC Iridomyrmex dromus Clark Pass TBC Iridomyrmex exsanguis Forel Pass TBC Iridomyrmex gibbus Heterick & Shattuck Failed; Old Iridomyrmex hartmeyeri Forel Failed Iridomyrmex minor Forel Pass TBC Iridomyrmex mjobergi Forel Pass TBC Iridomyrmex sanguineus Forel NCBI Iridomyrmex suchieri Heterick & Shattuck Pass TBC Iridomyrmex tenuiceps Heterick & Shattuck Pass TBC Iridomyrmex xanthocoxa Heterick & Shattuck Pass TBC Leptanilla swani Wheeler [males only] Failed Leptogenys tricosa Taylor Pass TBC Leptogenys sp. JDM 1128 Failed Appendix 1. List of species supplied for DNA barcoding, indicating which were successfully barcoded, which failed and species for which sequences were obtained from the NCBH public database. SUPPLEMENTARY MATERIAL Sociobiology 65(3): 422-432 (September, 2018) 431 Appendix 1. List of species supplied for DNA barcoding, indicating which were successfully barcoded, which failed and species for which sequences were obtained from the NCBH public database. (Continuation) Genus Species/sub-species Author Sequence GenBank Accession Number Lioponera brevis Clark NCBI Lioponera clarki Crawley Failed Lioponera iovis (Forel) Pass TBC Lioponera longitarsus Mayr Failed Lioponera ruficornis Clark Pass TBC Lioponera sp. JDM 942 Pass TBC Melophorus aeneovirens Wheeler Pass TBC Melophorus biroi Forel NCBI Melophorus hirsutipes Heterick, Castalanelli & Shattuck Pass TBC Melophorus ludius Forel NCBI Melophorus microtriches Heterick, Castalanelli & Shattuck Pass TBC Melophorus paramorphomenus Heterick, Castalanelli & Shattuck Pass TBC Melophorus parvimolaris Heterick, Castalanelli & Shattuck Pass TBC Melophorus rufoniger Heterick, Castalanelli & Shattuck Pass TBC Melophorus sulla Forel NCBI Melophorus teretinotus Heterick, Castalanelli & Shattuck Pass TBC Melophorus turneri Forel Pass TBC Meranoplus dimidiatus Smith Failed Meranoplus fenestratus Smith Failed Meranoplus mjobergi Forel Contaminated Meranoplus curvispina Forel Pass TBC Meranoplus sp. JDM 865 Failed Meranoplus sp. JDM 1133 Failed Monomorium antipodum (NW form) Forel NCBI Monomorium antipodum complex sp. JDM 717 Contaminated Monomorium arenarium Heterick Pass TBC Monomorium disetigerum Heterick Failed; Old Monomorium euryodon Heterick Pass TBC Monomorium fieldi Forel NCBI Monomorium insolescens Wheeler NCBI Monomorium laeve Mayr NCBI Monomorium leae Forel Pass TBC Monomorium punctulatum Heterick Pass TBC Monomorium rubriceps gp sp. JDM 1175 NCBI Monomorium sydneyense Forel Pass TBC Monomorium sydneyense complex sp. JDM 101 Pass TBC Nylanderia glabrior (Forel) Pass TBC Ochetellus flavipes Kirby Pass TBC Ochetellus sp. JDM 527 Pass TBC Odontomachus ruficeps Smith Pass TBC Opisthopsis haddoni rufoniger Forel NCBI JD Majer, MA Castalanelli, JL Ledger, NR Gunawardene, BE Heterick – Ant bar coding for detecting incursions432 Appendix 1. List of species supplied for DNA barcoding, indicating which were successfully barcoded, which failed and species for which sequences were obtained from the NCBH public database. (Continuation) Genus Species/sub-species Author Sequence GenBank Accession Number Paraparatrechina minutula Forel Pass TBC Paraparatrechina minutula gp sp. JDM 916 Failed; Old Paratrechina longicornis (Latreille) Pass TBC Pheidole mjobergi Forel Pass TBC Pheidole rugosula Gregg Pass TBC Pheidole turneri Forel Pass TBC Pheidole variabilis Mayr Pass TBC Pheidole sp. JDM 684 Pass TBC Platythyrea sp. [male] Pass TBC Polyrhachis ammonoeides Roger Pass TBC Polyrhachis bohemia Kohout Failed Polyrhachis gravis Clark Failed; Old Polyrhachis inconspicua Emery NCBI Polyrhachis lata Emery NCBI Polyrhachis melaneura Kohout Failed Polyrhachis seducta Kohout Pass TBC Polyrhachis (Campomyrma) sp. JDM 703 Failed; Old Polyrhachis (Campomyrma) sp. JDM 1009 Pass TBC Polyrhachis (Campomyrma) sp. JDM 1010 Pass TBC Polyrhachis (Chariomyrma) sp. JDM 807 Failed Polyrhachis (Chariomyrma) sp. JDM 808 Failed Probolomyrmex latalongus Shattuck, Gunawardene & Heterick, 2012 Contaminated Pseudoneoponera denticulata (Kirby) Pass TBC Rhytidoponera convexa complex sp. JDM 1129 Failed; Old Rhytidoponera crassinoda Forel Pass TBC Rhytidoponera taurus Forel Pass TBC Rhytidoponera tyloxys Brown & Douglas Failed Solenopsis belisarius Forel Failed Solenopsis clarki Crawley Pass TBC Stigmacros punctatissima McAreavey Failed Stigmacros termitoxena Wheeler Failed; Old Strumigenys emmae Emery Failed Tapinoma minutum broomense Forel Pass TBC Tapinoma sp. JDM 981 Failed Tetramorium cf. megalops Bolton Pass TBC Tetramorium sjostedti Forel Pass TBC Tetramorium spininode Bolton Pass TBC Tetramorium striolatum complex Pass TBC Tetramorium striolatum complex sp. JDM 36 Pass TBC Tetraponera punctulata Smith Pass TBC Zasphinctus duchaussoyi André Pass TBC