Biosurveillance for invasive insect pest species using an environmental DNA metabarcoding approach and a high salt trap collection fluid

Persisting roadblocks in arthropod monitoring using non-destructive metabarcoding from collection media of passive traps

Background

Broad-scale monitoring of arthropods is often carried out with passive traps (e.g., Malaise traps) that can collect thousands of specimens per sample. The identification of individual specimens requires time and taxonomic expertise, limiting the geographical and temporal scale of research and monitoring studies. DNA metabarcoding of bulk-sample homogenates has been found to be faster, efficient and reliable, but the destruction of samples prevents a posteriori validation of species occurrences and relative abundances. Non-destructive metabarcoding of DNA extracted from collection medium has been applied in a limited number of studies, but further tests of efficiency are required with different trap types and collection media to assess the consistency of the method.

Methods

We quantified the detection rate of arthropod species when applying non-destructive DNA metabarcoding with a short (127-bp) fragment of mitochondrial COI on two combinations of passive traps and collection media: (1) water with monopropylene glycol (H2O-MPG) used in window-flight traps (WFT, 53 in total); (2) ethanol with monopropylene glycol (EtOH-MPG) used in Malaise traps (MT, 27 in total). We then compared our results with those obtained for the same samples using morphological identification (for WFTs) or destructive metabarcoding of bulk homogenate (for MTs). This comparison was applied as part of a larger study of arthropod species richness in silver fir (Abies alba Mill., 1759) stands across a range of climate-induced tree dieback levels and forest management strategies.

Results

Of the 53 H2O-MPG samples from WFTs, 16 produced no metabarcoding results, while the remaining 37 samples yielded 77 arthropod MOTUs in total, of which none matched any of the 343 beetle species morphologically identified from the same traps. Metabarcoding of 26 EtOH-MPG samples from MTs detected more arthropod MOTUs (233) than destructive metabarcoding of homogenate (146 MOTUs, 8 orders), of which 71 were shared MOTUs, though MOTU richness per trap was similar between treatments. While we acknowledge the failure of metabarcoding from WFT-derived collection medium (H2O-MPG), the treatment of EtOH-based Malaise trapping medium remains promising. We conclude however that DNA metabarcoding from collection medium still requires further methodological developments and cannot replace homogenate metabarcoding as an approach for arthropod monitoring. It can be used nonetheless as a complementary treatment when enhancing the detection of soft-bodied arthropods like spiders and Diptera.

eDNA metabarcoding of avocado flowers: 'Hass' it got potential to survey arthropods in food production systems?

In the face of global biodiversity declines, surveys of beneficial and antagonistic arthropod diversity as well as the ecological services that they provide are increasingly important in both natural and agro-ecosystems. Conventional survey methods used to monitor these communities often require extensive taxonomic expertise and are time-intensive, potentially limiting their application in industries such as agriculture, where arthropods often play a critical role in productivity (e.g. pollinators, pests and predators). Environmental DNA (eDNA) metabarcoding of a novel substrate, crop flowers, may offer an accurate and high throughput alternative to aid in the detection of these managed and unmanaged taxa. Here, we compared the arthropod communities detected with eDNA metabarcoding of flowers, from an agricultural species (Persea americana-'Hass' avocado), with two conventional survey techniques: digital video recording (DVR) devices and pan traps. In total, 80 eDNA flower samples, 96 h of DVRs and 48 pan trap samples were collected. Across the three methods, 49 arthropod families were identified, of which 12 were unique to the eDNA dataset. Environmental DNA metabarcoding from flowers revealed potential arthropod pollinators, as well as plant pests and parasites. Alpha diversity levels did not differ across the three survey methods although taxonomic composition varied significantly, with only 12% of arthropod families found to be common across all three methods. eDNA metabarcoding of flowers has the potential to revolutionize the way arthropod communities are monitored in natural and agro-ecosystems, potentially detecting the response of pollinators and pests to climate change, diseases, habitat loss and other disturbances.

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.

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.

Non-Destructive Detection of Soybean Pest Based on Hyperspectral Image and Attention-ResNet Meta-Learning Model

Soybean plays an important role in food, medicine, and industry. The quality inspection of soybean is essential for soybean yield and the agricultural economy. However, soybean pest is an important factor that seriously affects soybean yield, among which leguminivora glycinivorella matsumura is the most frequent pest. Aiming at the problem that the traditional detection methods have low accuracy and need a large number of samples to train the model, this paper proposed a detection method for leguminivora glycinivorella matsumura based on an A-ResNet (Attention-ResNet) meta-learning model. In this model, the ResNet network was combined with Attention to obtain the feature vectors that can better express the samples, so as to improve the performance of the model. As well, the classifier was designed as a multi-class support vector machine (SVM) to reduce over-fitting. Furthermore, in order to improve the training stability of the model and the prediction performance on the testing set, the traditional Batch Normalization was replaced by the Layer Normalization, and the Label Smooth method was used to punish the original loss. The experimental results showed that the accuracy of the A-ResNet meta-learning model reached 94.57 ± 0.19%, which can realize rapid and accurate nondestructive detection, and provides theoretical support for the intelligent detection of soybean pests.

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.

Applications of environmental DNA (eDNA) in agricultural systems: Current uses, limitations and future prospects

Global food production, food supply chains and food security are increasingly stressed by human population growth and loss of arable land, becoming more vulnerable to anthropogenic and environmental perturbations. Numerous mutualistic and antagonistic species are interconnected with the cultivation of crops and livestock and these can be challenging to identify on the large scales of food production systems. Accurate identifications to capture this diversity and rapid scalable monitoring are necessary to identify emerging threats (i.e. pests and pathogens), inform on ecosystem health (i.e. soil and pollinator diversity), and provide evidence for new management practices (i.e. fertiliser and pesticide applications). Increasingly, environmental DNA (eDNA) is providing rapid and accurate classifications for specific organisms and entire species assemblages in substrates ranging from soil to air. Here, we aim to discuss how eDNA is being used for monitoring of agricultural ecosystems, what current limitations exist, and how these could be managed to expand applications into the future. In a systematic review we identify that eDNA-based monitoring in food production systems accounts for only 4 % of all eDNA studies. We found that the majority of these eDNA studies target soil and plant substrates (60 %), predominantly to identify microbes and insects (60 %) and are biased towards Europe (42 %). While eDNA-based monitoring studies are uncommon in many of the world's food production systems, the trend is most pronounced in emerging economies often where food security is most at risk. We suggest that the biggest limitations to eDNA for agriculture are false negatives resulting from DNA degradation and assay biases, as well as incomplete databases and the interpretation of abundance data. These require in silico, in vitro, and in vivo approaches to carefully design, test and apply eDNA monitoring for reliable and accurate taxonomic identifications. We explore future opportunities for eDNA research which could further develop this useful tool for food production system monitoring in both emerging and developed economies, hopefully improving monitoring, and ultimately food security.

Semi-Quantitative Detection of Drosophila suzukii (Diptera: Drosophilidae) From Bulk Trap Samples Using PCR Technology

Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) is a ubiquitous global pest of several fruit crops. Trapped adult numbers are used to monitor populations and make control decisions, but differentiating D. suzukii from other trapped Drosophila spp. is laborious. We developed a real-time PCR method for specific detection and semi-quantification of D. suzukii from trap samples. The PCR assay did not amplify DNA from 29 other Drosophilidae species tested. Drosophila suzukii was detected from ≥0.96 pg target DNA and from laboratory samples containing one D. suzukii in 2000 other Drosophila spp. flies. We tested DNA stability of one D. suzukii in 100 Drosophila spp. flies in water or ethanol at 20, 25, or 30°C for 1, 4, or 7 d. Only water at 30°C for 7 d fully impaired D. suzukii DNA detectability. Substituting mouthwash for water resulted in D. suzukii detection in all samples held for 7 d at 30°C or daily fluctuating temperatures of 33/23°C. Traps with mouthwash as a drowning liquid had D. suzukii captures equal to traps with water. A calibration curve was established using samples in mouthwash containing 1/1,000-100/1,000 D. suzukii/total Drosophila spp. flies and incubated at 25°C for 7 d. The curve had a coefficient of determination (R2) of 0.9279 between D. suzukii numbers from the PCR and the true D. suzukii numbers in samples prepared in 70% ethanol. Collecting samples in mouthwash is expected to improve detection accuracy, and the qPCR method can be a useful tool to support D. suzukii monitoring and management.

Reliability and Utility of Standard Gene Sequence Barcodes for the Identification and Differentiation of Cyst Nematodes of the Genus Heterodera

Difficulties inherent in the morphological identification of cyst nematodes of the genus Heterodera Schmidt, 1871, an important lineage of plant parasites, has led to broad adoption of molecular methods for diagnosing and differentiating species. The pool of publicly available sequence data has grown significantly over the past few decades, and over half of all known species of Heterodera have been characterized using one or more molecular markers commonly employed in DNA barcoding (18S, internal transcribed spacer [ITS], 28S, coxI). But how reliable are these data and how useful are these four markers for differentiating species? We downloaded all 18S, ITS, 28S, and coxI gene sequences available on the National Center for Biotechnology Information (NCBI) database, GenBank, for all species of Heterodera for which data were available. Using a combination of sequence comparison and tree-based phylogenetic methods, we evaluated this dataset for erroneous or otherwise problematic sequences and examined the utility of each molecular marker for the delineation of species. Although we find the rate of obviously erroneous sequences to be low, all four molecular markers failed to differentiate between at least one species pair. Our results suggest that while a combination of multiple markers is best for species identification, the coxI marker shows the most utility for species differentiation and should be favored over 18S, ITS, and 28S, where resources are limited. Presently, less than half the valid species of Heterodera have a sequence of coxI available, and only a third have more than one sequence of this marker.

Molecular Acquisition, Cleaning and Evaluation in R (MACER) - A tool to assemble molecular marker datasets from BOLD and GenBank

Molecular sequence data is an essential component for many biological fields of study. The strength of these data is in their ability to be centralised and compared across research studies. There are many online repositories for molecular sequence data, some of which are very large accumulations of varying data types like NCBI’s GenBank. Due to the size and the complexity of the data in these repositories, challenges arise in searching for data of interest. While data repositories exist for molecular markers, taxa and other specific research interests, repositories may not contain, or be suitable for, more specific applications. Manually accessing, searching, downloading, accumulating, dereplicating and cleaning data to construct project-specific datasets is time-consuming. In addition, the manual assembly of datasets presents challenges with reproducibility. Here, we present the MACER package to assist researchers in assembling molecular datasets and provide reproducibility in the process.

The evolutionary dynamics of biological invasions: A multi-approach perspective

Biological invasions, the establishment and spread of non-native species in new regions, can have extensive economic and environmental consequences. Increased global connectivity accelerates introduction rates, while climate and land-cover changes may decrease the barriers to invasive populations spread. A detailed knowledge of the invasion history, including assessing source populations, routes of spread, number of independent introductions, and the effects of genetic bottlenecks and admixture on the establishment success, adaptive potential, and further spread, is crucial from an applied perspective to mitigate socioeconomic impacts of invasive species, as well as for addressing fundamental questions on the evolutionary dynamics of the invasion process. Recent advances in genomics together with the development of geographic information systems provide unprecedented large genetic and environmental datasets at global and local scales to link population genomics, landscape ecology, and species distribution modeling into a common framework to study the invasion process. Although the factors underlying population invasiveness have been extensively reviewed, analytical methods currently available to optimally combine molecular and environmental data for inferring invasive population demographic parameters and predicting further spreading are still under development. In this review, we focus on the few recent insect invasion studies that combine different datasets and approaches to show how integrating genetic, observational, ecological, and environmental data pave the way to a more integrative biological invasion science. We provide guidelines to study the evolutionary dynamics of invasions at each step of the invasion process, and conclude on the benefits of including all types of information and up-to-date analytical tools from different research areas into a single framework.

Validation of an Effective Protocol for Culicoides Latreille (Diptera: Ceratopogonidae) Detection Using eDNA Metabarcoding

Simple Summary

All organisms shed genetic material into the environment, which is known as environmental DNA. Current molecular technologies allow for sequencing molecular markers in complex environmental samples. The use of these methods permits an effective identification and monitoring of flighted insects such as Culicoides species. These biting midges are agricultural pests of significant economic concern. This study identified Culicoides species using a novel molecular-based approach for this group and compared these results to morphological identifications of the specimens collected. There were forty-two Culicoides specimens collected in total, using a saturated salt solution as a collection fluid. Molecular identification detected four species. Using morphological identification, we identified two out of these four taxonomic ranks at the species level and one at the subgenus level. The inconsistency in identifying Culicoides specimens to the species level indicates the need for curated DNA reference libraries for molecular-based identification. The saturated salt solution used in the traps preserved the morphological characteristics and the organisms’ environmental DNA, which is an essential contribution of this study.

Abstract

eDNA metabarcoding is an effective molecular-based identification method for the biosurveillance of flighted insects. An eDNA surveillance approach maintains specimens for secondary morphological identification useful for regulatory applications. This study identified Culicoides species using eDNA metabarcoding and compared these results to morphological identifications of trapped specimens. Insects were collected using ultraviolet (UV) lighted fan traps containing a saturated salt (NaCl) solution from two locations in Guelph, Ontario, Canada. There were forty-two Culicoides specimens collected in total. Molecular identification detected four species, C. biguttatus, C. stellifer, C. obsoletus, and C. mulrennani. Using morphological identification, two out of these four taxonomic ranks were confirmed at the species level (C. biguttatus and C. stellifer) and one was confirmed at the subgenus level (Avaritia [C. obsoletus]). No molecular detection of Culicoides species occurred in traps with an abundance of less than three individuals per taxon. The inconsistency in identifying Culicoides specimens to the species level punctuates the need for curated DNA reference libraries for Culicoides. In conclusion, the saturated salt (NaCl) solution preserved the Culicoides’ morphological characteristics and the eDNA.

Optimization and validation of a cost-effective protocol for biosurveillance of invasive alien species

Environmental DNA (eDNA) metabarcoding has revolutionized biodiversity monitoring and invasive pest biosurveillance programs. The introduction of insect pests considered invasive alien species (IAS) into a non-native range poses a threat to native plant health. The early detection of IAS can allow for prompt actions by regulating authorities, thereby mitigating their impacts. In the present study, we optimized and validated a fast and cost-effective eDNA metabarcoding protocol for biosurveillance of IAS and characterization of insect and microorganism diversity. Forty-eight traps were placed, following the CFIA's annual forest insect trapping survey, at four locations in southern Ontario that are high risk for forest IAS. We collected insects and eDNA samples using Lindgren funnel traps that contained a saturated salt (NaCl) solution in the collection jar. Using cytochrome c oxidase I (COI) as a molecular marker, a modified Illumina protocol effectively identified 2,535 Barcode Index Numbers (BINs). BINs were distributed among 57 Orders and 304 Families, with the vast majority being arthropods. Two IAS (Agrilus planipennis and Lymantria dispar) are regulated by the Canadian Food Inspection Agency (CFIA) as plant health pests, are known to occur in the study area, and were identified through eDNA in collected traps. Similarly, using 16S ribosomal RNA and nuclear ribosomal internal transcribed spacer (ITS), five bacterial and three fungal genera, which contain species of regulatory concern across several Canadian jurisdictions, were recovered from all sampling locations. Our study results reaffirm the effectiveness and importance of integrating eDNA metabarcoding as part of identification protocols in biosurveillance programs.