Prospects and challenges of implementing DNA metabarcoding for high-throughput insect surveillance

A novel diagnostic gene region for distinguishing between two pest fruit flies: Bactrocera tryoni (Froggatt) and Bactrocera neohumeralis (Hardy) (Diptera: Tephritidae)

Bactrocera tryoni and Bactrocera neohumeralis are morphologically similar sibling pest fruit fly species that possess different biological attributes, geographic distributions, and host ranges. The need to differentiate between the two species is critical for accurate pest status assessment, management, biosecurity, and maintenance of reference colonies. While morphologically similar, adults may be separated based on subtle characters; however, some characters exhibit intraspecific variability, creating overlap between the two species. Additionally, there is currently no single molecular marker or rapid diagnostic assay that can reliably distinguish between B. neohumeralis and B. tryoni; therefore, ambiguous samples remain undiagnosed. Here we report the first molecular marker that can consistently distinguish between B. tryoni and B. neohumeralis. Our diagnostic region consists of two adjacent single nucleotide polymorphisms (SNPs) within the pangolin (pan) gene region. We confirmed the genotypes of each species are consistent across their distributional range, then developed a tetra-primer amplification refractory mutation system (ARMS) PCR assay for rapid diagnosis of the species. The assay utilizes four primers in multiplex, with two outer universal primers, and two internal primers: one designed to target two adjacent SNPs (AA) present in B. tryoni and the other targeting adjacent SNPs present in B. neohumeralis (GG). The assay accurately discriminates between the two species, but their SNP genotypes are shared with other nontarget tephritid fruit fly species. Therefore, this assay is most suited to adult diagnostics where species confirmation is necessary in determining ambiguous surveillance trap catches; maintaining pure colony lines; and in Sterile Insect Technique management responses.

Unlocking Antarctic molecular time-capsules - Recovering historical environmental DNA from museum-preserved sponges

Marine sponges have recently emerged as efficient natural environmental DNA (eDNA) samplers. The ability of sponges to accumulate eDNA provides an exciting opportunity to reconstruct contemporary communities and ecosystems with high temporal and spatial precision. However, the use of historical eDNA, trapped within the vast number of specimens stored in scientific collections, opens up the opportunity to begin to reconstruct the communities and ecosystems of the past. Here, we define the term 'heDNA' to denote the historical environmental DNA that can be obtained from the recent past with high spatial and temporal accuracy. Using a variety of Antarctic sponge specimens stored in an extensive marine invertebrate collection, we were able to recover information on Antarctic fish biodiversity from specimens up to 20 years old. We successfully recovered 64 fish heDNA signals from 27 sponge specimens. Alpha diversity measures did not differ among preservation methods, but sponges stored frozen had a significantly different fish community composition compared to those stored dry or in ethanol. Our results show that we were consistently and reliably able to extract the heDNA trapped within marine sponge specimens, thereby enabling the reconstruction and investigation of communities and ecosystems of the recent past with a spatial and temporal resolution previously unattainable. Future research into heDNA extraction from other preservation methods, as well as the impact of specimen age and collection method, will strengthen and expand the opportunities for this novel resource to access new knowledge on ecological change during the last century.

The "Dry-Lab" Side of Food Authentication: Benchmark of Bioinformatic Pipelines for the Analysis of Metabarcoding Data

Next Generation Sequencing Technologies (NGS), particularly metabarcoding, are valuable tools for authenticating foodstuffs and detecting eventual fraudulent practices such as species substitution. This technique, mostly used for the analysis of prokaryotes in several environments (including food), is in fact increasingly applied to identify eukaryotes (e.g., fish, mammals, avian, etc.) in multispecies food products. Besides the "wet-lab" procedures (e.g., DNA extraction, PCR, amplicon purification, etc.), the metabarcoding workflow includes a final "dry-lab" phase in which sequencing data are analyzed using a bioinformatic pipeline (BP). BPs play a crucial role in the accuracy, reliability, and interpretability of the metabarcoding results. Choosing the most suitable BP for the analysis of metabarcoding data could be challenging because it might require greater informatics skills than those needed in standard molecular analysis. To date, studies comparing BPs for metabarcoding data analysis in foodstuff authentication are scarce. In this study, we compared the data obtained from two previous studies in which fish burgers and insect-based products were authenticated using a customizable, ASV-based, and command-line interface BP (BP1) by analyzing the same data with a customizable but OTU-based and graphical user interface BP (BP2). The final sample compositions were compared statistically. No significant difference in sample compositions was highlighted by applying BP1 and BP2. However, BP1 was considered as more user-friendly than BP2 with respect to data analysis streamlining, cost of analysis, and computational time consumption. This study can provide useful information for researchers approaching the bioinformatic analysis of metabarcoding data for the first time. In the field of food authentication, an effective and efficient use of BPs could be especially useful in the context of official controls performed by the Competent Authorities and companies' self-control in order to detect species substitution and counterfeit frauds.

Using eDNA to play whack-a-mole with invasive species in green yard waste

As large cities begin to overrun their landfill capacities, they begin to look for alternative locations to handle the waste stream. Seeing an opportunity to bring in revenue, rural communities offer to handle municipal waste in their landfills. However, many rural communities are also places of agricultural production, which are vulnerable to attacks by invasive insect species, which could be present in green yard waste, the component of municipal waste most likely to contain agriculturally harmful insect species. We used environmental DNA (eDNA) to determine whether green yard waste could be a pathway for invasive insect species to enter and establish in the landfill-receiving agricultural community. We identified several target species that could be in green yard waste coming from Vancouver, BC, Canada, to Central Washington State, USA. We sampled green yard waste from 3 sites every 2 weeks from June to October in 2019 and 2020. DNA was extracted from the nearly 400 samples and subjected to amplification with COI barcoding primers followed by sequencing to identify target insects in the samples. Sequence analyses identified 3 species from the target list: 2 species that are pests of deciduous tree fruits and a generalist root-feeding crop pest. This eDNA technique was useful in identifying potential invasive species in green yard waste and may prove to be an important tool informing policy on the movement of biological material across borders and stemming the spread of invasive species.

Novel foods, old issues: Metabarcoding revealed mislabeling in insect-based products sold by e-commerce on the EU market

Insects intended for human consumption are considered Novel Foods according to EU legislation. marketed in form of powders, bars, snacks are increasingly available on the EU market, especially on e-commerce. The commercial form and the way of distribution make IBPs particularly prone to mislabeling. Literature concerning the mislabeling occurrence in IBPs is extremely scarce. In this study, 46 processed IBPs were collected on nine EU e-commerce platforms (e-CO) to be authenticated by metabarcoding. A 200 bp region from 16S rRNA gene was used as molecular target. Sequencing data were processed using DADA2 R package, and sequences were taxonomically assigned through BLAST analysis against GenBank. Procedural blanks and positive controls were included in the analysis, and threshold values were established to filter the final data. The mislabeling rate (i. e. the mismatch between the species declared on the IBP label and the species identified by metabarcoding) was calculated. Overall, a high mislabeling rate (33.3 %) was observed, although this percentage is influenced by the e-CO platform and the insect species, with A. domesticus particularly involved. The use of species not listed in authorized Novel Food (e. g. Gryllus locorojo), and/or the partial replacement of high value species with lower value species was highlighted for the first time in processed IBPs. The presence of insect pests was also detected. Metabarcoding was confirmed as an effective tool for IBPs authentication. Also, outcomes from this study can provide useful data on the main issues involving the EU IBPs' market, that can represent an incentive to reinforce both official controls and FBO's self-controls on these poorly investigated products.

Diversity of Parasitoid Wasps and Comparison of Sampling Strategies in Rice Fields Using Metabarcoding

A comprehensive and precise evaluation of Arthropoda diversity in agricultural landscapes can enhance biological pest control strategies. We used Malaise traps and sweep nets to collect insects from three double-cropping paddy fields. DNA was extracted from the ethanol preservative of the Malaise traps and from tissue samples of selected parasitoid wasps. This was followed by amplification using DNA barcoding primers to prepare high-throughput sequencing libraries. We annotated a total of 4956 operational taxonomic units (OTUs), encompassing 174 genera and 32 families of parasitoid wasps. The ethanol filter method efficiently captured a wide range of information. However, the method has low resolution and may result in a reduced estimate of species abundance. Additional insect species were also identified in the parasitoid samples. This suggests that high throughput sequencing from adult parasitoid wasps can also detect host species, enabling a better understanding of host species and providing insights into food webs.

DNA Sequencing Technologies and DNA Barcoding

DNA barcodes are short, standardized DNA segments that geneticists can use to identify all living taxa. On the other hand, DNA barcoding identifies species by analyzing these specific regions against a DNA barcode reference library. In its initial years, DNA barcodes sequenced by Sanger's method were extensively used by taxonomists for the characterization and identification of species. But in recent years, DNA barcoding by next-generation sequencing (NGS) has found broader applications, such as quality control, biomonitoring of protected species, and biodiversity assessment. Technological advancements have also paved the way to metabarcoding, which has enabled massive parallel sequ.encing of complex bulk samples using high-throughput sequencing techniques. In future, DNA barcoding along with high-throughput techniques will show stupendous progress in taxonomic classification with reference to available sequence data.

Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin? A systematic review

Food authentication using molecular techniques is of great importance to fight food fraud. Metabarcoding, based on the next-generation sequencing (NGS) technologies, allowing large-scale taxonomic identification of complex samples via massive parallel sequencing of fragments (called DNA barcodes) simultaneously, has become increasingly popular in many scientific fields. A systematic review to answer the question "Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin?" is presented. The inclusion criteria were focused on the selection of scientific papers (SPs) only applying metabarcoding to foodstuff of animal origin collected on the market. The 23 included SPs were first analyzed with respect to the metabarcoding phases: library preparation (target genes, primer pairs, and fragment length), sequencing (NGS platforms), and final data analysis (bioinformatic pipelines). Given the importance of primer selection, the taxonomic coverage of the used primers was also evaluated. In addition, the SPs were scored based on the use of quality control measures (procedural blanks, positive controls, replicates, curated databases, and thresholds to filter the data). A lack of standardized protocols, especially with respect to the target barcode/s and the universal primer/s, and the infrequent application of the quality control measures, leads to answer that metabarcoding is not ripe enough for authenticating foodstuff of animal origin. However, the observed trend of the SP quality improvement over the years is encouraging. Concluding, a proper protocol standardization would allow a wider use of metabarcoding by both official and private laboratories, enabling this method to become the primary for the authentication of foodstuffs of animal origin.

CRISPR-based diagnostics detects invasive insect pests

Rapid identification of organisms is essential for many biological and medical disciplines, from understanding basic ecosystem processes, disease diagnosis, to the detection of invasive pests. CRISPR-based diagnostics offers a novel and rapid alternative to other identification methods and can revolutionize our ability to detect organisms with high accuracy. Here we describe a CRISPR-based diagnostic developed with the universal cytochrome-oxidase 1 gene (CO1). The CO1 gene is the most sequenced gene among Animalia, and therefore our approach can be adopted to detect nearly any animal. We tested the approach on three difficult-to-identify moth species (Keiferia lycopersicella, Phthorimaea absoluta and Scrobipalpa atriplicella) that are major invasive pests globally. We designed an assay that combines recombinase polymerase amplification (RPA) with CRISPR for signal generation. Our approach has a much higher sensitivity than real-time PCR assays and achieved 100% accuracy for identification of all three species, with a detection limit of up to 120 fM for P. absoluta and 400 fM for the other two species. Our approach does not require a sophisticated laboratory, reduces the risk of cross-contamination, and can be completed in less than 1 h. This work serves as a proof of concept that has the potential to revolutionize animal detection and monitoring.

Collective and harmonized high throughput barcoding of insular arthropod biodiversity: Toward a Genomic Observatories Network for islands

Current understanding of ecological and evolutionary processes underlying island biodiversity is heavily shaped by empirical data from plants and birds, although arthropods comprise the overwhelming majority of known animal species, and as such can provide key insights into processes governing biodiversity. Novel high throughput sequencing (HTS) approaches are now emerging as powerful tools to overcome limitations in the availability of arthropod biodiversity data, and hence provide insights into these processes. Here, we explored how these tools might be most effectively exploited for comprehensive and comparable inventory and monitoring of insular arthropod biodiversity. We first reviewed the strengths, limitations and potential synergies among existing approaches of high throughput barcode sequencing. We considered how this could be complemented with deep learning approaches applied to image analysis to study arthropod biodiversity. We then explored how these approaches could be implemented within the framework of an island Genomic Observatories Network (iGON) for the advancement of fundamental and applied understanding of island biodiversity. To this end, we identified seven island biology themes at the interface of ecology, evolution and conservation biology, within which collective and harmonized efforts in HTS arthropod inventory could yield significant advances in island biodiversity research.

Metabarcoding and applied ecology with hyperdiverse organisms: Recommendations for biological control research

Metabarcoding is revolutionizing fundamental research in ecology by enabling large-scale detection of species and producing data that are rich with community context. However, the benefits of metabarcoding have yet to be fully realized in fields of applied ecology, especially those such as classical biological control (CBC) research that involve hyperdiverse taxa. Here, we discuss some of the opportunities that metabarcoding provides CBC and solutions to the main methodological challenges that have limited the integration of metabarcoding in existing CBC workflows. We focus on insect parasitoids, which are popular and effective biological control agents (BCAs) of invasive species and agricultural pests. Accurately identifying native, invasive and BCA species is paramount, since misidentification can undermine control efforts and lead to large negative socio-economic impacts. Unfortunately, most existing publicly accessible genetic databases cannot be used to reliably identify parasitoid species, thereby limiting the accuracy of metabarcoding in CBC research. To address this issue, we argue for the establishment of authoritative genetic databases that link metabarcoding data to taxonomically identified specimens. We further suggest using multiple genetic markers to reduce primer bias and increase taxonomic resolution. We also provide suggestions for biological control-specific metabarcoding workflows intended to track the long-term effectiveness of introduced BCAs. Finally, we use the example of an invasive pest, Drosophila suzukii, in a reflective "what if" thought experiment to explore the potential power of community metabarcoding in CBC.

Towards exhaustive community ecology via DNA metabarcoding

Exhaustive biodiversity data, covering all the taxa in an environment, would be fundamental to understand how global changes influence organisms living at different trophic levels, and to evaluate impacts on interspecific interactions. Molecular approaches such as DNA metabarcoding are boosting our ability to perform biodiversity inventories. Nevertheless, even though a few studies have recently attempted exhaustive reconstructions of communities, holistic assessments remain rare. The majority of metabarcoding studies published in the last years used just one or two markers and analysed a limited number of taxonomic groups. Here, we provide an overview of emerging approaches that can allow all-taxa biological inventories. Exhaustive biodiversity assessments can be attempted by combining a large number of specific primers, by exploiting the power of universal primers, or by combining specific and universal primers to obtain good information on key taxa while limiting the overlooked biodiversity. Multiplexes of primers, shotgun sequencing and capture enrichment may provide a better coverage of biodiversity compared to standard metabarcoding, but still require major methodological advances. Here, we identify the strengths and limitations of different approaches, and suggest new development lines that might improve broad scale biodiversity analyses in the near future. More holistic reconstructions of ecological communities can greatly increase the value of metabarcoding studies, improving understanding of the consequences of ongoing environmental changes on the multiple components of biodiversity.

Black gold rush - Evaluating the efficiency of the Fractionator in separating Hymenoptera families in a meadow ecosystem over a two week period

In the face of insect decline, monitoring projects are launched widely to assess trends of insect populations. Collecting over long time periods results in large numbers of samples with thousands of individuals that are often just stored in freezers waiting to be further processed. As the time-consuming process of sorting and identifying specimens prevents taxonomists from working on mass samples, important information on species composition remains unknown and taxonomically neglected species remain undiagnosed. Size fractioning of bulk samples can improve sample handling and, thus, can help to overcome the taxonomic impediment. In this paper, we evaluate the efficiency of the fractionator in separating Hymenoptera families from a Malaise trap sample of a meadow ecosystem over a two week interval to make them available for further morphological identification. The fractionator system by Buffington and Gates (2008) was used to separate the sample in two size classes - a large (macro) and a small (micro) fraction - and Hymenoptera specimens were then counted and identified on family level. In total, 2,449 Hymenoptera specimens were found in the macro fraction and 3,016 in the micro fraction (5,465 specimens in total). For 24 out of 34 Hymenoptera families (71%), separation was significant. This study illustrates the efficiency of the fractionator and its potential to improve workflows dealing with specimen-rich Malaise trap samples.

Composition and diversity of bacterial communities associated with honey bee foragers from two contrasting environments

The honey bee is associated with a diverse community of microbes (viruses, bacteria, fungi, and protists), commonly known as the microbiome. Here, we present data on honey bee microbiota from two localities having different surrounding landscapes - mountain (the Rhodope Mountains) and lowland (the Danube plain). The bacterial communities of abdomen of adult bees were studied using amplicon sequencing of the 16S rRNA gene. The composition and dominance structure and their variability within and between localities, alpha and beta diversity, and core and differential taxa were compared at different hierarchical levels (operational taxonomic units to phylum). Seven genera (Lactobacillus, Gilliamella, Bifidobacterium, Commensalibacter, Bartonella, Snodgrassella, and Frischella), known to include core gut-associated phylotypes or species clusters, dominated (92-100%) the bacterial assemblages. Significant variations were found in taxa distribution across both geographical regions and within each apiary. Lactobacillus (Firmicutes) prevailed significantly in the mountain locality followed by Gilliamella and Bartonella (Proteobacteria). Bacteria of four genera, core (Bartonella and Lactobacillus) and non-core (Pseudomonas and Morganella), dominated the bee-associated assemblages of the Danube plain locality. Several ubiquitous bacterial genera (e.g., Klebsiella, Serratia, and Providencia), some species known also as potential and opportunistic bee pathogens, had been found in the lowland locality. Beta diversity analyses confirmed the observed differences in the bacterial communities from both localities. The occurrence of non-core taxa contributes substantially to higher microbial richness and diversity in bees from the Danube plain locality. We assume that the observed differences in the microbiota of honey bees from both apiaries are due to a combination of factors specific for each region. The surrounding landscape features of both localities and related vegetation, anthropogenic impact and land use intensity, the beekeeping management practices, and bee health status might all contribute to observed differences in bee microbiota traits.

Non-destructive insect metabarcoding for surveillance and biosecurity in citrus orchards: recording the good, the bad and the psyllids

Background

The Australian citrus industry remains one of the few in the world to be unaffected by the African and the Asian citrus psyllids, Trioza erytreae Del Guercio and Diaphorina citri Kuwayama, respectively, and the diseases their vectored bacteria can cause. Surveillance, early detection, and strict quarantine measures are therefore fundamental to safeguard Australian citrus. However, long-term targeted surveillance for exotic citrus pests can be a time-consuming and expensive activity, often relying on manually screening large numbers of trap samples and morphological identification of specimens, which requires a high level of taxonomic knowledge.

Methods

Here we evaluated the use of non-destructive insect metabarcoding for exotic pest surveillance in citrus orchards. We conducted an 11-week field trial, between the months of December and February, at a horticultural research farm (SuniTAFE Smart Farm) in the Northwest of Victoria, Australia, and processed more than 250 samples collected from three types of invertebrate traps across four sites.

Results

The whole-community metabarcoding data enabled comparisons between different trapping methods, demonstrated the spatial variation of insect diversity across the same orchard, and highlighted how comprehensive assessment of insect biodiversity requires use of multiple complimentary trapping methods. In addition to revealing the diversity of native psyllid species in citrus orchards, the non-targeted metabarcoding approach identified a diversity of other pest and beneficial insects and arachnids within the trap bycatch, and recorded the presence of the triozid Casuarinicola cf warrigalensis for the first time in Victoria. Ultimately, this work highlights how a non-targeted surveillance approach for insect monitoring coupled with non-destructive DNA metabarcoding can provide accurate and high-throughput species identification for biosecurity and biodiversity monitoring.

Haplotype-level metabarcoding of freshwater macroinvertebrate species: A prospective tool for population genetic analysis

Metabarcoding is a molecular-based tool capable of large quantity high-throughput species identification from bulk samples that is a faster and more cost-effective alternative to conventional DNA-sequencing approaches. Still, further exploration and assessment of the laboratory and bioinformatics strategies are required to unlock the potential of metabarcoding-based inference of haplotype information. In this study, we assessed the inference of freshwater macroinvertebrate haplotypes from metabarcoding data in a mock sample. We also examined the influence of DNA template concentration and PCR cycle on detecting true and spurious haplotypes. We tested this strategy on a mock sample containing twenty individuals from four species with known haplotypes based on the 658-bp Folmer region of the mitochondrial cytochrome c oxidase gene. We recovered fourteen zero-radius operational taxonomic units (zOTUs) of 421-bp length, with twelve zOTUs having a 100% match with the Sanger haplotype sequences. High-quality reads relatively increased with increasing PCR cycles, and the relative abundance of each zOTU was consistent for each cycle. This suggests that increasing the PCR cycles from 24 to 64 did not affect the relative abundance of each zOTU. As metabarcoding becomes more established and laboratory protocols and bioinformatic pipelines are continuously being developed, our study demonstrated the method's ability to infer intraspecific variability while highlighting the challenges that must be addressed before its eventual application for population genetic studies.

Nondestructive Methods of Pathogen Detection: Importance of Mosquito Integrity in Studies of Disease Transmission and Control

Mosquitoes are vectors of many pathogens, including viruses, protozoans, and helminths, spreading these pathogens to humans as well as to wild and domestic animals. As the identification of species and the biological characterization of mosquito vectors are cornerstones for understanding patterns of disease transmission, and the design of control strategies, we conducted a literature review on the current use of noninvasive and nondestructive techniques for pathogen detection in mosquitoes, highlighting the importance of their taxonomic status and systematics, and some gaps in the knowledge of their vectorial capacity. Here, we summarized the alternative techniques for pathogen detection in mosquitoes based on both laboratory and field studies. Parasite infection and dissemination by mosquitoes can also be obtained via analyses of saliva- and excreta-based techniques or of the whole mosquito body, using a near-infrared spectrometry (NIRS) approach. Further research should be encouraged to seek strategies for detecting target pathogens while preserving mosquito morphology, especially in biodiversity hotspot regions, thus enabling the discovery of cryptic or new species, and the determination of more accurate taxonomic, parasitological, and epidemiological patterns.

The pest sap beetle Carpophilus (Myothorax) truncatus Murray, 1864 (Coleoptera: Nitidulidae)-a new synonymy and a related new species of Carpophilus

Carpophilus truncatus Murray 1864, is a species of sap beetle which has been recorded from many countries worldwide, and has become recognised as an important pest of nuts. In this study, we present a re-description of C. truncatus including diagnostic photographic images of the adults and larvae, and demonstrate that Carpophilus jarijari Powell & Hamilton, 2019 is a junior subjective synonym of C. truncatus. Information about the species' distribution in Australia is updated. DNA barcode sequence data for C. truncatus is reviewed and augmented to enable differentiation from other morphologically similar Carpophilus species that are associated with nuts as hosts, including the cosmopolitan Carpophilus dimidiatus (Fabricius, 1792), for which C. truncatus has sometimes been misidentified. This analysis revealed that existing reference DNA sequences of "C. dimidiatus" consist of three highly genetically divergent lineages, representing three species: the cosmopolitan C. dimidiatus, the widespread C. truncatus, and a newly described species, Carpophilus imitatus sp. nov., known from south-eastern Asia and Australia.

CRISPR-based diagnostics detects invasive insect pests

Rapid identification of organisms is essential across many biological and medical disciplines, from understanding basic ecosystem processes and how organisms respond to environmental change, to disease diagnosis and detection of invasive pests. CRISPR-based diagnostics offers a novel and rapid alternative to other identification methods and can revolutionize our ability to detect organisms with high accuracy. Here we describe a CRISPR-based diagnostic developed with the universal cytochrome-oxidase 1 gene (CO1). The CO1 gene is the most sequenced gene among Animalia, and therefore our approach can be adopted to detect nearly any animal. We tested the approach on three difficult-to-identify moth species (Keiferia lycopersicella, Phthorimaea absoluta, and Scrobipalpa atriplicella) that are major invasive pests globally. We designed an assay that combines recombinase polymerase amplification (RPA) with CRISPR for signal generation. Our approach has a much higher sensitivity than other real time-PCR assays and achieved 100% accuracy for identification of all three species, with a detection limit of up to 120 fM for P. absoluta and 400 fM for the other two species. Our approach does not require a lab setting, reduces the risk of cross-contamination, and can be completed in less than one hour. This work serves as a proof of concept that has the potential to revolutionize animal detection and monitoring.

Dual-Band Infrared Scheimpflug Lidar Reveals Insect Activity in a Tropical Cloud Forest

We describe an entomological dual-band 808 and 980 nm lidar system which has been implemented in a tropical cloud forest (Ecuador). The system was successfully tested at a sample rate of 5 kHz in a cloud forest during challenging foggy conditions (extinction coefficients up to 20 km^-1). At times, the backscattered signal could be retrieved from a distance of 2.929 km. We present insect and bat observations up to 200 m during a single night with an emphasis on fog aspects, potentials, and benefits of such dual-band systems. We demonstrate that the modulation contrast between insects and fog is high in the frequency domain compared to intensity in the time domain, thus allowing for better identification and quantification in misty forests. Oscillatory lidar extinction effects are shown in this work for the first time, caused by the combination of dense fog and large moths partially obstructing the beam. We demonstrate here an interesting case of a moth where left- and right-wing movements induced oscillations in both intensity and pixel spread. In addition, we were able to identify the dorsal and ventral sides of the wings by estimating the corresponding melanization with the dual-band lidar. We demonstrate that the wing beat trajectories in the dual-band parameter space are complementary rather than covarying or redundant, thus a dual-band entomological lidar approach to biodiversity studies is feasible in situ and endows species specificity differentiation. Future improvements are discussed. The introduction of these methodologies opens the door to a wealth of possible experiments to monitor, understand, and safeguard the biological resources of one of the most biodiverse countries on Earth.

Monitoring insect biodiversity and comparison of sampling strategies using metabarcoding: A case study in the Yanshan Mountains, China

Insects are the richest and most diverse group of animals and yet there remains a lack, not only of systematic research into their distribution across some key regions of the planet, but of standardized sampling strategies for their study. The Yanshan Mountains, being the boundary range between the Inner Mongolian Plateau and the North China Plain, present an indispensable piece of the insect biodiversity puzzle: both requiring systematic study and offering opportunities for the development of standardized methodologies. This is the first use of DNA metabarcoding to survey the insect biodiversity of the Yanshan Mountains. The study focuses on differences of community composition among samples collected via different methods and from different habitat types. In total, 74 bulk samples were collected from five habitat types (scrubland, woodland, wetland, farmland and grassland) using three collection methods (sweep netting, Malaise traps and light traps). After DNA extraction, PCR amplification, sequencing and diversity analysis were performed, a total of 7427 Operational Taxonomic Units (OTUs) at ≥97% sequence similarity level were delimited, of which 7083 OTUs were identified as belonging to Insecta. Orthoptera, Diptera, Coleoptera and Hemiptera were found to be the dominant orders according to community composition analysis. Nonmetric multidimensional scaling (NMDS) analysis based on Bray-Curtis distances revealed highly divergent estimates of insect community composition among samples differentiated by the collection method (R = .524802, p = .001), but nonsignificant difference among samples differentiated according to habitat (R = .051102, p = .078). The study therefore appears to indicate that the concurrent use of varied collection methods is essential to the accurate monitoring of insect biodiversity.

The phylogeny and evolutionary ecology of hoverflies (Diptera: Syrphidae) inferred from mitochondrial genomes

Hoverflies (Diptera: Syrphidae) are a diverse group of pollinators and a major research focus in ecology, but their phylogenetic relationships remain incompletely known. Using a genome skimming approach we generated mitochondrial genomes for 91 species, capturing a wide taxonomic diversity of the family. To reduce the required amount of input DNA and overall cost of the library construction, sequencing and assembly was conducted on mixtures of specimens, which raises the problem of chimera formation of mitogenomes. We present a novel chimera detection test based on gene tree incongruence, but identified only a single mitogenome of chimeric origin. Together with existing data for a final set of 127 taxa, phylogenetic analysis on nucleotide and amino acid sequences using Maximum Likelihood and Bayesian Inference revealed a basal split of Microdontinae from all other syrphids. The remainder consists of several deep clades assigned to the subfamily Eristalinae in the current classification, including a clade comprising the subfamily Syrphinae (plus Pipizinae). These findings call for a re-definition of subfamilies, but basal nodes had insufficient support to allow such action. Molecular-clock dating placed the origin of the Syrphidae crown group in the mid-Cretaceous while the Eristalinae-Syrphinae clade likely originated near the K/Pg boundary. Transformation of larval life history characters on the tree suggests that Syrphidae initially had sap feeding larvae, which diversified greatly in diet and habitat association during the Eocene and Oligocene, coinciding with the diversification of angiosperms and the evolution of various insect groups used as larval host, prey, or mimicry models. Mitogenomes proved to be a powerful phylogenetic marker for studies of Syrphidae at subfamily and tribe levels, allowing dense taxon sampling that provided insight into the great ecological diversity and rapid evolution of larval life history traits of the hoverflies.

Future of DNA-based insect monitoring

Insects are crucial for ecosystem health but climate change and pesticide use are driving massive insect decline. To mitigate this loss, we need new and effective monitoring techniques. Over the past decade there has been a shift to DNA-based techniques. We describe key emerging techniques for sample collection. We suggest that the selection of tools should be broadened, and that DNA-based insect monitoring data need to be integrated more rapidly into policymaking. We argue that there are four key areas for advancement, including the generation of more complete DNA barcode databases to interpret molecular data, standardisation of molecular methods, scaling up of monitoring efforts, and integrating molecular tools with other technologies that allow continuous, passive monitoring based on images and/or laser imaging, detection, and ranging (LIDAR).

Development of a DNA Metabarcoding Method for the Identification of Insects in Food

Insects have the potential to become an efficient and reliable food source for humans in the future and could contribute to solving problems with the current food chain. Analytical methods to verify the authenticity of foods are essential for consumer acceptance. We present a DNA metabarcoding method that enables the identification and differentiation of insects in food. The method, developed on Illumina platforms, is targeting a 200 bp mitochondrial 16S rDNA fragment, which we found to be suitable for distinguishing more than 1000 insect species. We designed a novel universal primer pair for a singleplex PCR assay. Individual DNA extracts from reference samples, DNA extracts from model foods and food products commercially available were investigated. In all of the samples investigated, the insect species were correctly identified. The developed DNA metabarcoding method has a high potential to identify and differentiate insect DNA in the context of food authentication in routine analysis.

Maximizing the reliability and the number of species assignments in metabarcoding studies using a curated regional library and a public repository

Biodiversity assessments relying on DNA have increased rapidly over the last decade. However, the reliability of taxonomic assignments in metabarcoding studies is variable and affected by the reference databases and the assignment methods used. Species level assignments are usually considered as reliable using regional libraries but unreliable using public repositories. In this study, we aimed to test this assumption for metazoan species detected in the Gulf of St. Lawrence in the Northwest Atlantic. We first created a regional library (GSL-rl) by data mining COI barcode sequences from BOLD, and included a reliability ranking system for species assignments. We then estimated 1) the accuracy and precision of the public repository NCBI-nt for species assignments using sequences from the regional library and 2) compared the detection and reliability of species assignments of a metabarcoding dataset using either NCBI-nt or the regional library and popular assignment methods. With NCBI-nt and sequences from the regional library, the BLAST-LCA (least common ancestor) method was the most precise method for species assignments, but the accuracy was higher with the BLAST-TopHit method (>80% over all taxa, between 70% and 90% amongst taxonomic groups). With the metabarcoding dataset, the reliability of species assignments was greater using GSL-rl compared to NCBI-nt. However, we also observed that the total number of reliable species assignments could be maximized using both GSL-rl and NCBI-nt with different optimized assignment methods. The use of a two-step approach for species assignments, i.e., using a regional library and a public repository, could improve the reliability and the number of detected species in metabarcoding studies.

Development of a cost-effective, morphology-preserving method for DNA isolation from bulk invertebrate trap catches: Tephritid fruit flies as an exemplar

Insect identification and preservation of voucher specimens is integral to pest diagnostic and surveillance activities; yet bulk-trapped insects are a diagnostic challenge due to high catch numbers and the susceptibility of samples to environmental damage. Many insect trap catches rely on examination of morphological characters for species identifications, which is a time consuming and highly skilled task, hence there is a need for more efficient molecular approaches. Many bulk DNA extraction methods require destructive sampling of specimens, resulting in damaged, or fully destroyed, voucher specimens. We developed an inexpensive, rapid, bulk DNA isolation method that preserves specimens as pinned vouchers to a standard that allows for post-extraction morphological examination and inclusion in insect reference collections. Our protocol was validated using a group of insects that are time-consuming to identify when trapped in large numbers-the dacine fruit flies (Diptera: Tephritidae: Dacinae). In developing our method, we evaluated existing protocols against the following criteria: effect on morphology; suitability for large trap catches; cost; ease of handling; and application to downstream molecular diagnostic analyses such as real-time PCR and metabarcoding. We found that the optimum method for rapid isolation of DNA extraction was immersing flies in a NaOH:TE buffer at 75°C for 10 minutes, without the need for proteinase K or detergents. This HotSOAK method produced sufficient high-quality DNA whilst preserving morphological characters suitable for species-level identification with up to 20,000 flies in a sample. The lysates performed well in down-stream analyses such as loop-mediated isothermal amplification (LAMP) and real-time PCR applications, while for metabarcoding PCR the lysate required an additional column purification step. Development of this method is a key step required for upscaling our capacity to accurately detect insects captured in bulk traps, whether for biodiversity, biosecurity, or pest management objectives.

Non-destructive insect metabarcoding as a surveillance tool for the Australian grains industry: a first trial for the iMapPESTS smart trap

Surveillance and long-term monitoring of insect pest populations are of paramount importance to limit dispersal and inform pest management. Molecular methods have been employed in diagnostics, surveillance and monitoring for the past few decades, often paired with more traditional techniques relying on morphological examinations. Within this context, the ‘iMapPESTS: Sentinel Surveillance for Agriculture’ project was conceptualised to enhance on-farm pest management decision-making via development and deployment of smart traps, able to collect insects, as well as recording associated environmental data. Here, we compared an iMapPESTS ‘Sentinel’ smart trap to an alternative suction trap over a 10-week period. We used a non-destructive insect metabarcoding approach complemented by insect morphological diagnostics to assess and compare aphid species presence and diversity across trap samples and time. Furthermore, we paired this with environmental data recorded throughout the sampling period. This methodology recorded a total of 497 different taxa from 70 traps over a 10-week period in the grain-growing region in western Victoria. This included not only the 14 aphid target species, but an additional 12 aphid species, including a new record for Victoria. Ultimately, with more than 450 bycatch species detected, this highlighted the value of insect metabarcoding, not only for pest surveillance, but also at a broader ecosystem level, with potential applications in integrated pest management and biocontrol.

Metabarcoding of eDNA for tracking the floral and geographical origins of bee honey

Authentic honey products have a high commercial value and are often falsified via adulteration. Metabarcoding of environmental DNA (eDNA) from bacterial, floral, and entomological sources has recently been proposed as a useful tool for identifying and authenticating floral and geographical origins of bee honey. In this study, eDNA metabarcoding was applied to reveal the bacterial, plant, and honey bee DNA signatures of 48 commercial honey products from six different geographical origins. Bacterial DNA composition in commercial honey showed different relative abundance of Paenibacillus and Bacillus in geographically different samples, and high abundance of Methylobacterium in chestnut honey implying potential use of bacterial DNA composition for honey authentication. Using the chloroplast trnL (UAA) as a DNA marker, floral origins of commercial honey were investigated. Based on floral DNA signatures, 12 monofloral honey samples were identified among the 45 samples tested. Targeted amplicon sequencing of cytochrome oxidase I (COI) gene from entomological DNA identified three different Apis mellifera sequence variants, specific to geographic origin of honey, suggesting that COI can be implemented as a DNA marker to trace the origin of honey. Therefore, the current study demonstrated the potential of eDNA based metabarcoding as a robust tool for evaluating commercial bee honey by exploring their floral and geographical origins.

Forest Insect Biosecurity: Processes, Patterns, Predictions, Pitfalls

The economic and environmental threats posed by non-native forest insects are ever increasing with the continuing globalization of trade and travel; thus, the need for mitigation through effective biosecurity is greater than ever. However, despite decades of research and implementation of preborder, border, and postborder preventative measures, insect invasions continue to occur, with no evidence of saturation, and are even predicted to accelerate. In this article, we review biosecurity measures used to mitigate the arrival, establishment, spread, and impacts of non-native forest insects and possible impediments to the successful implementation of these measures. Biosecurity successes are likely under-recognized because they are difficult to detect and quantify, whereas failures are more evident in the continued establishment of additional non-native species. There are limitations in existing biosecurity systems at global and country scales (for example, inspecting all imports is impossible, no phytosanitary measures are perfect, knownunknowns cannot be regulated against, and noncompliance is an ongoing problem). Biosecurity should be a shared responsibility across countries, governments, stakeholders, and individuals.

Using DNA metabarcoding to assess insect diversity in citrus orchards

Background

DNA metabarcoding is rapidly emerging as a cost-effective approach for large-scale biodiversity assessment and pest monitoring. The current study employed metabarcoding to assess insect diversity in citrus orchards in Ganzhou City, Jiangxi, China in both 2018 and 2019. Insects were sampled using Malaise traps deployed in three citrus orchards producing a total of 43 pooled monthly samples.

Methods

The Malaise trap samples were sequenced following DNA metabarcoding workflow. Generated sequences were curated and analyzed using two cloud databases and analytical platforms, the barcode of life data system (BOLD) and multiplex barcode research and visualization environment (mBRAVE).

Results

These platforms assigned the sequences to 2,141 barcode index numbers (BINs), a species proxy. Most (63%) of the BINs were shared among the three sampling sites while BIN sharing between any two sites did not exceed 71%. Shannon diversity index (H') showed a similar pattern of BIN assortment at the three sampling sites. Beta diversity analysis by Jaccard similarity coefficient (J) and Bray-Curtis distance matrix (BC) revealed a high level of BIN similarity among the three sites (J = 0.67-0.68; BC = 0.19-0.20). Comparison of BIN records against all those on BOLD made it possible to identify 40% of the BINs to a species, 57% to a genus, 97% to a family and 99% to an order. BINs which received a species match on BOLD were placed in one of four categories based on this assignment: pest, parasitoid, predator, or pollinator. As this study provides the first baseline data on insect biodiversity in Chinese citrus plantations, it is a valuable resource for research in a broad range of areas such as pest management and monitoring beneficial insects in citrus gardens.

Enhanced Arbovirus Surveillance with High-Throughput Metatranscriptomic Processing of Field-Collected Mosquitoes

Surveillance programs are essential for the prevention and control of mosquito-borne arboviruses that cause serious human and animal diseases. Viral metatranscriptomic sequencing can enhance surveillance by enabling untargeted, high-throughput arbovirus detection. We used metatranscriptomic sequencing to screen field-collected mosquitoes for arboviruses to better understand how metatranscriptomics can be utilised in routine surveillance. Following a significant flood event in 2016, more than 56,000 mosquitoes were collected over seven weeks from field traps set up in Victoria, Australia. The traps were split into samples of 1000 mosquitoes or less and sequenced on the Illumina HiSeq. Five arboviruses relevant to public health (Ross River virus, Sindbis virus, Trubanaman virus, Umatilla virus, and Wongorr virus) were detected a total of 33 times in the metatranscriptomic data, with 94% confirmed using reverse transcription quantitative PCR (RT-qPCR). Analysis of metatranscriptomic cytochrome oxidase I (COI) sequences enabled the detection of 12 mosquito and two biting midge species. Screening of the same traps by an established public health arbovirus surveillance program corroborated the metatranscriptomic arbovirus and mosquito species detections. Assembly of genome sequences from the metatranscriptomic data also led to the detection of 51 insect-specific viruses, both known and previously undescribed, and allowed phylogenetic comparison to past strains. We have demonstrated how metatranscriptomics can enhance surveillance by enabling untargeted arbovirus detection, providing genomic epidemiological data, and simultaneously identifying vector species from large, unsorted mosquito traps.

Advances in understanding and predicting the spread of invading insect populations

Understanding and predicting the spread of invading insects is a critical challenge in management programs that aim to minimize ecological and economic harm to native ecosystems. Although efforts to quantify spread rates have been well studied over the past several decades, opportunities to improve our ability to estimate rates of spread, and identify the factors, such as habitat suitability and climate, that influence spread, remain. We review emerging sources of data that can be used to delineate distributional boundaries through time and thus serve as a basis for quantifying spread rates. We then address advances in modeling methods that facilitate our understanding of factors that drive invasive insect spread. We conclude by highlighting some remaining challenges in understanding and predicting invasive insect spread, such as the role of climate change and biotic similarity between the native and introduced ranges, particularly as it applies to decision-making in management programs.

Metagenomics versus total RNA sequencing: most accurate data-processing tools, microbial identification accuracy and perspectives for ecological assessments

Metagenomics and total RNA sequencing (total RNA-Seq) have the potential to improve the taxonomic identification of diverse microbial communities, which could allow for the incorporation of microbes into routine ecological assessments. However, these target-PCR-free techniques require more testing and optimization. In this study, we processed metagenomics and total RNA-Seq data from a commercially available microbial mock community using 672 data-processing workflows, identified the most accurate data-processing tools, and compared their microbial identification accuracy at equal and increasing sequencing depths. The accuracy of data-processing tools substantially varied among replicates. Total RNA-Seq was more accurate than metagenomics at equal sequencing depths and even at sequencing depths almost one order of magnitude lower than those of metagenomics. We show that while data-processing tools require further exploration, total RNA-Seq might be a favorable alternative to metagenomics for target-PCR-free taxonomic identifications of microbial communities and might enable a substantial reduction in sequencing costs while maintaining accuracy. This could be particularly an advantage for routine ecological assessments, which require cost-effective yet accurate methods, and might allow for the incorporation of microbes into ecological assessments.

The Invasive Mosquitoes of Canada: An Entomological, Medical, and Veterinary Review

Several invasive mosquitoes have become established in Canada, including important pathogen vectors such as Aedes albopictus, Ae. japonicus, and Culex pipiens. Some species have been present for decades, while others are recent arrivals. Several species present new health concerns and may result in autochthonous seasonal outbreaks of pathogens, particularly in southern Canada, that were previously restricted to imported cases. This review provides an overview of current knowledge of the biological, medical, and veterinary perspectives of these invasive species and highlights the need for increased monitoring efforts and information sharing.

Life barcoded by DNA barcodes

The modern concept of DNA-based barcoding for cataloguing biodiversity was proposed in 2003 by first adopting an approximately 600 bp fragment of the mitochondrial COI gene to compare via nucleotide alignments with known sequences from specimens previously identified by taxonomists. Other standardized regions meeting barcoding criteria then are also evolving as DNA barcodes for fast, reliable and inexpensive assessment of species composition across all forms of life, including animals, plants, fungi, bacteria and other microorganisms. Consequently, global DNA barcoding campaigns have resulted in the formation of many online workbenches and databases, such as BOLD system, as barcode references, and facilitated the development of mini-barcodes and metabarcoding strategies as important extensions of barcode techniques. Here we intend to give an overview of the characteristics and features of these barcode markers and major reference libraries existing for barcoding the planet’s life, as well as to address the limitations and opportunities of DNA barcodes to an increasingly broader community of science and society.

medna-metadata: an open-source data management system for tracking environmental DNA samples and metadata

MOTIVATION

Environmental DNA (eDNA), as a rapidly expanding research field, stands to benefit from shared resources including sampling protocols, study designs, discovered sequences, and taxonomic assignments to sequences. High-quality community shareable eDNA resources rely heavily on comprehensive metadata documentation that captures the complex workflows covering field sampling, molecular biology lab work, and bioinformatic analyses. There are limited sources that provide documentation of database development on comprehensive metadata for eDNA and these workflows and no open-source software.

RESULTS

We present medna-metadata, an open-source, modular system that aligns with Findable, Accessible, Interoperable, and Reusable guiding principles that support scholarly data reuse and the database and application development of a standardized metadata collection structure that encapsulates critical aspects of field data collection, wet lab processing, and bioinformatic analysis. Medna-metadata is showcased with metabarcoding data from the Gulf of Maine (Polinski et al., 2019).

AVAILABILITY AND IMPLEMENTATION

The source code of the medna-metadata web application is hosted on GitHub (https://github.com/Maine-eDNA/medna-metadata). Medna-metadata is a docker-compose installable package. Documentation can be found at https://medna-metadata.readthedocs.io/en/latest/?badge=latest. The application is implemented in Python, PostgreSQL and PostGIS, RabbitMQ, and NGINX, with all major browsers supported. A demo can be found at https://demo.metadata.maine-edna.org/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Toward global integration of biodiversity big data: a harmonized metabarcode data generation module for terrestrial arthropods

Metazoan metabarcoding is emerging as an essential strategy for inventorying biodiversity, with diverse projects currently generating massive quantities of community-level data. The potential for integrating across such data sets offers new opportunities to better understand biodiversity and how it might respond to global change. However, large-scale syntheses may be compromised if metabarcoding workflows differ from each other. There are ongoing efforts to improve standardization for the reporting of inventory data. However, harmonization at the stage of generating metabarcode data has yet to be addressed. A modular framework for harmonized data generation offers a pathway to navigate the complex structure of terrestrial metazoan biodiversity. Here, through our collective expertise as practitioners, method developers, and researchers leading metabarcoding initiatives to inventory terrestrial biodiversity, we seek to initiate a harmonized framework for metabarcode data generation, with a terrestrial arthropod module. We develop an initial set of submodules covering the 5 main steps of metabarcode data generation: (i) sample acquisition; (ii) sample processing; (iii) DNA extraction; (iv) polymerase chain reaction amplification, library preparation, and sequencing; and (v) DNA sequence and metadata deposition, providing a backbone for a terrestrial arthropod module. To achieve this, we (i) identified key points for harmonization, (ii) reviewed the current state of the art, and (iii) distilled existing knowledge within submodules, thus promoting best practice by providing guidelines and recommendations to reduce the universe of methodological options. We advocate the adoption and further development of the terrestrial arthropod module. We further encourage the development of modules for other biodiversity fractions as an essential step toward large-scale biodiversity synthesis through harmonization.

Emerging technologies revolutionise insect ecology and monitoring

Insects are the most diverse group of animals on Earth, but their small size and high diversity have always made them challenging to study. Recent technological advances have the potential to revolutionise insect ecology and monitoring. We describe the state of the art of four technologies (computer vision, acoustic monitoring, radar, and molecular methods), and assess their advantages, current limitations, and future potential. We discuss how these technologies can adhere to modern standards of data curation and transparency, their implications for citizen science, and their potential for integration among different monitoring programmes and technologies. We argue that they provide unprecedented possibilities for insect ecology and monitoring, but it will be important to foster international standards via collaboration.

Metabarcoding of Fish Larvae in the Merbok River Reveals Species Diversity and Distribution Along its Mangrove Environment

The Merbok River (north-west of Peninsular Malaysia) is a mangrove estuary that provides habitat for over 100 species of fish, which are economically and ecologically important. Threats such as habitat loss and overfishing are becoming a great concern for fisheries conservation and management. The identification of larval fish in this estuarine system is important to complement information on the adults. This is because the data could inform the spawning behaviour, reproductive biology, selection of nursery grounds and migration route of fish. Such information is invaluable for fisheries and aquatic environmental monitoring, and thus for their conservation and management. However, identifying fish larvae is a challenging task based only on morphology and even traditional DNA barcoding. To address this, DNA metabarcoding was utilised to detect the diversity of fish in the Merbok River. To complete the study, the fish larvae were collected at six sampling sites of the river. The extracted larval DNA was amplified for the Cytochrome Oxidase subunit 1 (COI) and 12S ribosomal RNA (12S rRNA) genes based on the metabarcoding approach using shotgun sequencing on the next-generation sequencing (NGS) Illumina MiSeq platform. Eighty-nine species from 65 genera and 41 families were detected, with Oryzias javanicus, Oryzias dancena, Lutjanus argentimaculatus and Lutjanus malabaricus among the most common species. The lower diversity observed from previous morphological studies is suggested to be mainly due to seasonal variation over the sampling period between the two methods and limited 12S rRNA sequences in current databases. The metabarcode data and a validation Sanger sequencing step using 15 species-specific primer pairs detected three species in common: Oryzias javanicus, Decapterus maruadsi and Pennahia macrocephalus. Several discrepancies observed between the two molecular approaches could be attributed to contaminants during sampling and DNA extraction, which could mask the presence of target species, especially when DNA from the contaminants is more abundant than the target organisms. In conclusion, this rapid and cost-effective identification method using DNA metabarcoding allowed the detection of numerous fish species from bulk larval samples in the Merbok River. This method can be applied to other sites and other organisms of interest.

A DNA Extraction Method for Insects From Sticky Traps: Targeting a Low Abundance Pest, Phthorimaea absoluta (Lepidoptera: Gelechiidae), in Mixed Species Communities

Invasive insects can cause catastrophic damage to ecosystems and cost billions of dollars each year due to management expenses and lost revenue. Rapid detection is an important step to prevent invasive insects from spreading, but improvements in detection capabilities are needed for bulk collections like those from sticky traps. Here we present a bulk DNA extraction method designed for the detection of Phthorimaea absoluta Meyrick (Lepidoptera: Gelechiidae), an invasive moth that can decimate tomato crops. We test the extraction method for insect specimens on sticky traps, subjected to different temperature and humidity conditions, and among mock insect communities left in the field for up to 21 d. We find that the extraction method yielded high success (>92%) in recovering target DNA across field and lab trials, without a decline in recovery after three weeks, across all treatments. These results may have a large impact on tomato growing regions where P. absoluta is in the early stages of invasion or not yet present. The extraction method can also be used to improve detection capabilities for other bulk insect collections, especially those using sticky traps, to the benefit of pest surveys and biodiversity studies.

A framework to integrate innovations in invasion science for proactive management

Invasive alien species (IAS) are a rising threat to biodiversity, national security, and regional economies, with impacts in the hundreds of billions of U.S. dollars annually. Proactive or predictive approaches guided by scientific knowledge are essential to keeping pace with growing impacts of invasions under climate change. Although the rapid development of diverse technologies and approaches has produced tools with the potential to greatly accelerate invasion research and management, innovation has far outpaced implementation and coordination. Technological and methodological syntheses are urgently needed to close the growing implementation gap and facilitate interdisciplinary collaboration and synergy among evolving disciplines. A broad review is necessary to demonstrate the utility and relevance of work in diverse fields to generate actionable science for the ongoing invasion crisis. Here, we review such advances in relevant fields including remote sensing, epidemiology, big data analytics, environmental DNA (eDNA) sampling, genomics, and others, and present a generalized framework for distilling existing and emerging data into products for proactive IAS research and management. This integrated workflow provides a pathway for scientists and practitioners in diverse disciplines to contribute to applied invasion biology in a coordinated, synergistic, and scalable manner.

DNA Metabarcoding Enables High-Throughput Detection of Spotted Wing Drosophila (Drosophila suzukii) Within Unsorted Trap Catches

The spotted wing drosophila (Drosophila suzukii, Matsumara) is a rapidly spreading global pest of soft and stone fruit production. Due to the similarity of many of its life stages to other cosmopolitan drosophilids, surveillance for this pest is currently bottlenecked by the laborious sorting and morphological identification of large mixed trap catches. DNA metabarcoding presents an alternative high-throughput sequencing (HTS) approach for multi-species identification, which may lend itself ideally to rapid and scalable diagnostics of D. suzukii within unsorted trap samples. In this study, we compared the qualitative (identification accuracy) and quantitative (bias toward each species) performance of four metabarcoding primer pairs on D. suzukii and its close relatives. We then determined the sensitivity of a non-destructive metabarcoding assay (i.e., which retains intact specimens) by spiking whole specimens of target species into mock communities of increasing specimen number, as well as 29 field-sampled communities from a cherry and a stone fruit orchard. Metabarcoding successfully detected D. suzukii and its close relatives Drosophila subpulchrella and Drosophila biarmipes in the spiked communities with an accuracy of 96, 100, and 100% respectively, and identified a further 57 non-target arthropods collected as bycatch by D. suzukii surveillance methods in a field scenario. While the non-destructive DNA extraction retained intact voucher specimens, dropouts of single species and entire technical replicates suggests that these protocols behave more similarly to environmental DNA than homogenized tissue metabarcoding and may require increased technical replication to reliably detect low-abundance taxa. Adoption of high-throughput metabarcoding assays for screening bulk trap samples could enable a substantial increase in the geographic scale and intensity of D. suzukii surveillance, and thus likelihood of detecting a new introduction. Trap designs and surveillance protocols will, however, need to be optimized to adequately preserve specimen DNA for molecular identification.

Disentangling bias for non-destructive insect metabarcoding

A fast and reliable method for obtaining a species-level identification is a fundamental requirement for a wide range of activities, from plant protection and invasive species management to biodiversity assessments and ecological studies. For insects, novel molecular techniques such as DNA metabarcoding have emerged as a rapid alternative to traditional morphological identification, reducing the dependence on limited taxonomic experts. Until recently, molecular techniques have required a destructive DNA extraction, precluding the possibility of preserving voucher specimens for future studies, or species descriptions. Here we paired insect metabarcoding with two recent non-destructive DNA extraction protocols, to obtain a rapid and high-throughput taxonomic identification of diverse insect taxa while retaining a physical voucher specimen. The aim of this work was to explore how non-destructive extraction protocols impact the semi-quantitative nature of metabarcoding, which alongside species presence/absence also provides a quantitative, but biased, representation of their relative abundances. By using a series of mock communities representing each stage of a typical metabarcoding workflow we were able to determine how different morphological (i.e., insect biomass and exoskeleton hardness) and molecular traits (i.e., primer mismatch and amplicon GC%), interact with different protocol steps to introduce quantitative bias into non-destructive metabarcoding results. We discuss the relevance of taxonomic bias to metabarcoding identification of insects and potential approaches to account for it.

New Sets of Primers for DNA Identification of Non-Indigenous Fish Species in the Volga-Kama Basin (European Russia)

Adequate species’ identification is critical for the detection and monitoring of biological invasions. In this study, we proposed and assessed the efficiency of newly created primer sets for the genetic identification of non-indigenous species (NIS) of fishes in the Volga basin based on: (a) a “long” fragment of cytochrome c oxidase subunit one of the mitochondrial gene (COI) (0.7 kb), used in “classical” DNA barcoding; (b) a short 3’-fragment (0.3 kb) of COI, suitable for use in high-throughput sequencing systems (i.e., for dietary analysis); (c) fragment of 16S mitochondrial rRNA, including those designed to fill the library of reference sequences for work on the metabarcoding of communities and eDNA studies; (d) a fragment of 18S nuclear rRNA, including two hypervariable regions V1-V2, valuable for animal phylogeny. All four sets of primers demonstrated a high amplification efficiency and high specificity for freshwater fish. Also, we proposed the protocols for the cost-effective isolation of total DNA and purification of the PCR product without the use of commercial kits. We propose an algorithm to carry out extremely cheap studies on the assessment of biological diversity without expensive equipment. We also present original data on the genetic polymorphism of all mass NIS fish species in the Volga-Kama region. The high efficiency of DNA identification based on our primers is shown relative to the traditional monitoring of biological invasions.

Inferring microbiota functions from taxonomic genes: a review

Deciphering microbiota functions is crucial to predict ecosystem sustainability in response to global change. High-throughput sequencing at the individual or community level has revolutionized our understanding of microbial ecology, leading to the big data era and improving our ability to link microbial diversity with microbial functions. Recent advances in bioinformatics have been key for developing functional prediction tools based on DNA metabarcoding data and using taxonomic gene information. This cheaper approach in every aspect serves as an alternative to shotgun sequencing. Although these tools are increasingly used by ecologists, an objective evaluation of their modularity, portability, and robustness is lacking. Here, we reviewed 100 scientific papers on functional inference and ecological trait assignment to rank the advantages, specificities, and drawbacks of these tools, using a scientific benchmarking. To date, inference tools have been mainly devoted to bacterial functions, and ecological trait assignment tools, to fungal functions. A major limitation is the lack of reference genomes-compared with the human microbiota-especially for complex ecosystems such as soils. Finally, we explore applied research prospects. These tools are promising and already provide relevant information on ecosystem functioning, but standardized indicators and corresponding repositories are still lacking that would enable them to be used for operational diagnosis.

Environmental DNA reveals diversity and abundance of Alternaria species in neighbouring heterogeneous landscapes in Worcester, UK

Alternaria is a pathogenic and allergenic fungus affecting 400 plant species and 334 million people globally. This study aimed at assessing the diversity of Alternaria species in airborne samples collected from closely located (7 km apart) and heterogeneous sites (rural, urban and unmanaged grassland) in Worcester and Lakeside, the UK. A secondary objective was to examine how the ITS1 subregion varies from ITS2 in Alternaria species diversity and composition. Airborne spores were collected using Burkard 7-day and multi-vial Cyclone samplers for the period 5 July 2016-9 October 2019. Air samples from the Cyclone were amplified using the ITS1and ITS2 subregions and sequenced using Illumina MiSeq platform whereas those from the Burkard sampler were identified and quantified using optical microscopy. Optical microscopy and eDNA revealed a high abundance of Alternaria in the rural, urban and unmanaged sites. ITS1 and ITS2 detected five and seven different Alternaria species at the three sampling sites, respectively. A. dactylidicola, A. metachromatica and A. infectoria were the most abundant. The rural, urban and unmanaged grassland sites had similar diversity (PERMANOVA) of the species due to similarity in land use and proximity of the sites. Overall, the study showed that heterogeneous and neighbouring sites with similar land uses can have similar Alternaria species. It also demonstrated that an eDNA approach can complement the classical optical microscopy method in providing more precise information on fungal species diversity in an environment for targeted management. Similar studies can be replicated for other allergenic and pathogenic fungi.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10453-022-09760-9.