Species‐level biodiversity assessment using marine environmental DNA metabarcoding requires protocol optimization and standardization

DNA extraction from environmental samples (environmental DNA; eDNA) for metabarcoding‐based biodiversity studies is gaining popularity as a noninvasive, time‐efficient, and cost‐effective monitoring tool. The potential benefits are promising for marine conservation, as the marine biome is frequently under‐surveyed due to its inaccessibility and the consequent high costs involved. With increasing numbers of eDNA‐related publications have come a wide array of capture and extraction methods. Without visual species confirmation, inconsistent use of laboratory protocols hinders comparability between studies because the efficiency of target DNA isolation may vary. We determined an optimal protocol (capture and extraction) for marine eDNA research based on total DNA yield measurements by comparing commonly employed methods of seawater filtering and DNA isolation. We compared metabarcoding results of both targeted (small taxonomic group with species‐level assignment) and universal (broad taxonomic group with genus/family‐level assignment) approaches obtained from replicates treated with the optimal and a low‐performance capture and extraction protocol to determine the impact of protocol choice and DNA yield on biodiversity detection. Filtration through cellulose‐nitrate membranes and extraction with Qiagen's DNeasy Blood & Tissue Kit outperformed other combinations of capture and extraction methods, showing a ninefold improvement in DNA yield over the poorest performing methods. Use of optimized protocols resulted in a significant increase in OTU and species richness for targeted metabarcoding assays. However, changing protocols made little difference to the OTU and taxon richness obtained using universal metabarcoding assays. Our results demonstrate an increased risk of false‐negative species detection for targeted eDNA approaches when protocols with poor DNA isolation efficacy are employed. Appropriate optimization is therefore essential for eDNA monitoring to remain a powerful, efficient, and relatively cheap method for biodiversity assessments. For seawater, we advocate filtration through cellulose‐nitrate membranes and extraction with Qiagen's DNeasy Blood & Tissue Kit or phenol‐chloroform‐isoamyl for successful implementation of eDNA multi‐marker metabarcoding surveys.     

Toward an ecoregion scale evaluation of eDNA metabarcoding primers: A case study for the freshwater fish biodiversity of the Murray–Darling Basin (Australia)

High‐throughput sequencing of environmental DNA (i.e., eDNA metabarcoding) has become an increasingly popular method for monitoring aquatic biodiversity. At present, such analyses require target‐specific primers to amplify DNA barcodes from co‐occurring species, and this initial amplification can introduce biases. Understanding the performance of different primers is thus recommended prior to undertaking any metabarcoding initiative. While multiple software programs are available to evaluate metabarcoding primers, all programs have their own strengths and weaknesses. Therefore, a robust in silico workflow for the evaluation of metabarcoding primers will benefit from the use of multiple programs. Furthermore, geographic differences in species biodiversity are likely to influence the performance of metabarcoding primers and further complicate the evaluation process. Here, an in silico workflow is presented that can be used to evaluate the performance of metabarcoding primers on an ecoregion scale. This workflow was used to evaluate the performance of published and newly developed eDNA metabarcoding primers for the freshwater fish biodiversity of the Murray–Darling Basin (Australia). To validate the in silico workflow, a subset of the primers, including one newly designed primer pair, were used in metabarcoding analyses of an artificial DNA community and eDNA samples. The results show that the in silico workflow allows for a robust evaluation of metabarcoding primers and can reveal important trade‐offs that need to be considered when selecting the most suitable primer. Additionally, a new primer pair was described and validated that allows for more robust taxonomic assignments and is less influenced by primer biases compared to commonly used fish metabarcoding primers.     

Enabling large-scale feather mite studies: an Illumina DNA metabarcoding pipeline

Feather mites are among the most common and diverse ectosymbionts of birds, yet basic questions such as the nature of their relationship remain largely unanswered. One reason for feather mites being understudied is that their morphological identification is often virtually impossible when using female or young individuals. Even for adult male specimens this task is tedious and requires advanced taxonomic expertise, thus hampering large-scale studies. In addition, molecular-based methods are challenging because the low DNA amounts usually obtained from these tiny mites do not reach the levels required for high-throughput sequencing. This work aims to overcome these issues by using a DNA metabarcoding approach to accurately identify and quantify the feather mite species present in a sample. DNA metabarcoding is a widely used molecular technique that takes advantage of high-throughput sequencing methodologies to assign the taxonomic identity to all the organisms present in a complex sample (i.e., a sample made up of multiple specimens that are hard or impossible to individualise). We present a high-throughput method for feather mite identification using a fragment of the COI gene as marker and Illumina Miseq technology. We tested this method by performing two experiments plus a field test over a total of 11,861 individual mites (5360 of which were also morphologically identified). In the first experiment, we tested the probability of detecting a single feather mite in a heterogeneous pool of non-conspecific individuals. In the second experiment, we made 2?×?2 combinations of species and studied the relationship between the proportion of individuals of a given species in a sample and the proportion of sequences retrieved to test whether DNA metabarcoding can reliably quantify the relative abundance of mites in a sample. Here we also tested the efficacy of degenerate primers (i.e., a mixture of similar primers that differ in one or several bases that are designed to increase the chance of annealing) and investigated the relationship between the number of mismatches and PCR success. Finally, we applied our DNA metabarcoding pipeline to a total of 6501 unidentified and unsorted feather mite individuals sampled from 380 European passerine birds belonging to 10 bird species (field test). Our results show that this proposed pipeline is suitable for correct identification and quantitative estimation of the relative abundance of feather mite species in complex samples, especially when dealing with a moderate number (>?30) of individuals per sample.     

Extraction and purification of DNA in rhizosphere soil samples for PCR-DGGE analysis of bacterial consortia

Application of DNA fingerprinting methods enables the detection of diverse members of soil bacterial consortia, even including those bacteria not yet cultivated. However, extraction and purification of DNA from soil samples without bias is difficult. We compared five different DNA isolation methods and three purification methods for rhizosphere soil samples. Purified DNA extracts were amplified in PCR using universal bacterial primers and the PCR products were analysed with denaturing gradient gel electrophoresis (DGGE) for the visualisation of DNA bands representing dominant bacterial species. Both the isolation and purification methods affected the apparent bacterial community structure of the samples.     

Detection of multiple mycetoma pathogens using fungal metabarcoding analysis of soil DNA in an endemic area of Sudan

Mycetoma is a tropical disease caused by several fungi and bacteria present in the soil. Fungal mycetoma and eumycetoma are especially challenging to treat; therefore, prevention, early diagnosis, and early treatment are important, but it is also necessary to understand the geographic distribution of these pathogenic fungi. In this study, we used DNA metabarcoding methodology to identify fungal species from soil samples. Soil sampling was implemented at seven villages in an endemic area of Sennar State in Sudan in 2019, and ten sampling sites were selected in each village according to land-use conditions. In total, 70 soil samples were collected from ground surfaces, and DNA in the soil was extracted with a combined method of alkaline DNA extraction and a commercial soil DNA extraction kit. The region for universal primers was selected to be the ribosomal internal transcribed spacer one region for metabarcoding. After the second PCR for DNA library preparation, the amplicon-based DNA analysis was performed using next-generation sequencing with two sets of universal primers. A total of twelve mycetoma-causative fungal species were identified, including the prime agent, Madurella mycetomatis, and additional pathogens, Falciformispora senegalensis and Falciformispora tompkinsii, in 53 soil samples. This study demonstrated that soil DNA metabarcoding can elucidate the presence of multiple mycetoma-causative fungi, which may contribute to accurate diagnosis for patient treatment and geographical mapping.     

A practical guide to DNA metabarcoding for entomological ecologists

1. DNA metabarcoding is a cost-effective species identification approach with great potential to assist entomological ecologists. This review presents a practical guide to help entomological ecologists design their own DNA metabarcoding studies and ensure that sound ecological conclusions can be obtained. 2. The review considers approaches to field sampling, laboratory work, and bioinformatic analyses, with the aim of providing the background knowledge needed to make decisions at each step of a DNA metabarcoding workflow. 3. Although most conventional sampling methods can be adapted to DNA metabarcoding, this review highlights techniques that will ensure suitable DNA preservation during field sampling and laboratory storage. The review also calls for a greater understanding of the occurrence, transportation, and deposition of environmental DNA when applying DNA metabarcoding approaches for different ecosystems. 4. Accurate species detection with DNA metabarcoding needs to consider biases introduced during DNA extraction and PCR amplification, cross-contamination resulting from inappropriate amplicon library preparation, and downstream bioinformatic analyses. Quantifying species abundance with DNA metabarcoding is in its infancy, yet recent studies demonstrate promise for estimating relative species abundance from DNA sequencing reads. 5. Given that bioinformatics is one of the biggest hurdles for researchers new to DNA metabarcoding, several useful graphical user interface programs are recommended for sequence data processing, and the application of emerging sequencing technologies is discussed.     

Establishing arthropod community composition using metabarcoding: Surprising inconsistencies between soil samples and preservative ethanol and homogenate from Malaise trap catches

DNA metabarcoding allows the analysis of insect communities faster and more efficiently than ever before. However, metabarcoding can be conducted through several approaches, and the consistency of results across methods has rarely been studied. We compare the results obtained by DNA metabarcoding of the same communities using two different markers – COI and 16S – and three different sampling methods: (a) homogenized Malaise trap samples (homogenate), (b) preservative ethanol from the same samples, and (c) soil samples. Our results indicate that COI and 16S offer partly complementary information on Malaise trap samples, with each marker detecting a significant number of species not detected by the other. Different sampling methods offer highly divergent estimates of community composition. The community recovered from preservative ethanol of Malaise trap samples is significantly different from that recovered from homogenate. Small and weakly sclerotized insects tend to be overrepresented in ethanol while strong and large taxa are overrepresented in homogenate. For soil samples, highly degenerate COI primers pick up large amounts of nontarget DNA and only 16S provides adequate analyses of insect diversity. However, even with 16S, very little overlap in molecular operational taxonomic unit (MOTU) content was found between the trap and the soil samples. Our results demonstrate that none of the tested sampling approaches is satisfactory on its own. For instance, DNA extraction from preservative ethanol is not a valid replacement for destructive bulk extraction but a complement. In future metabarcoding studies, both should ideally be used together to achieve comprehensive representation of the target community.     

Finding flies in the mushroom soup: Host specificity of fungus‐associated communities revisited with a novel molecular method

Fruiting bodies of fungi constitute an important resource for thousands of other taxa. The structure of these diverse assemblages has traditionally been studied with labour‐intensive methods involving cultivation and morphology‐based species identification, to which molecular information might offer convenient complements. To overcome challenges in DNA extraction and PCR associated with the complex chemical properties of fruiting bodies, we developed a pipeline applicable for extracting amplifiable total DNA from soft fungal samples of any size. Our protocol purifies DNA in two sequential steps: (a) initial salt–isopropanol extraction of all nucleic acids in the sample is followed by (b) an extra clean‐up step using solid‐phase reversible immobilization (SPRI) magnetic beads. The protocol proved highly efficient, with practically all of our samples—regardless of biomass or other properties—being successfully PCR‐amplified using metabarcoding primers and subsequently sequenced. As a proof of concept, we apply our methods to address a topical ecological question: is host specificity a major characteristic of fungus‐associated communities, that is, do different fungus species harbour different communities of associated organisms? Based on an analysis of 312 fungal fruiting bodies representing 10 species in five genera from three orders, we show that molecular methods are suitable for studying this rich natural microcosm. Comparing to previous knowledge based on rearing and morphology‐based identifications, we find a species‐rich assemblage characterized by a low degree of host specialization. Our method opens up new horizons for molecular analyses of fungus‐associated interaction webs and communities. Fruiting bodies of fungi constitute an important resource for thousands of other taxa. The structure of these diverse assemblages has traditionally been studied with labour‐intensive methods involving cultivation and morphology‐based species identification, to which molecular information might offer convenient complements. To overcome challenges in DNA extraction and PCR associated with the complex chemical properties of fruiting bodies, we developed a pipeline applicable for extracting amplifiable total DNA from soft fungal samples of any size. Our protocol purifies DNA in two sequential steps: (a) initial salt–isopropanol extraction of all nucleic acids in the sample is followed by (b) an extra clean‐up step using solid‐phase reversible immobilization (SPRI) magnetic beads. The protocol proved highly efficient, with practically all of our samples—regardless of biomass or other properties—being successfully PCR‐amplified using metabarcoding primers and subsequently sequenced. As a proof of concept, we apply our methods to address a topical ecological question: is host specificity a major characteristic of fungus‐associated communities, that is, do different fungus species harbour different communities of associated organisms? Based on an analysis of 312 fungal fruiting bodies representing 10 species in five genera from three orders, we show that molecular methods are suitable for studying this rich natural microcosm. Comparing to previous knowledge based on rearing and morphology‐based identifications, we find a species‐rich assemblage characterized by a low degree of host specialization. Our method opens up new horizons for molecular analyses of fungus‐associated interaction webs and communities.     

Efficacy of metabarcoding for identification of fish eggs evaluated with mock communities

There is urgent need for effective and efficient monitoring of marine fish populations. Monitoring eggs and larval fish may be more informative than that traditional fish surveys since ichthyoplankton surveys reveal the reproductive activities of fish populations, which directly impact their population trajectories. Ichthyoplankton surveys have turned to molecular methods (DNA barcoding & metabarcoding) for identification of eggs and larval fish due to challenges of morphological identification. In this study, we examine the effectiveness of using metabarcoding methods on mock communities of known fish egg DNA. We constructed six mock communities with known ratios of species. In addition, we analyzed two samples from a large field collection of fish eggs and compared metabarcoding results with traditional DNA barcoding results. We examine the ability of our metabarcoding methods to detect species and relative proportion of species identified in each mock community. We found that our metabarcoding methods were able to detect species at very low input proportions; however, levels of successful detection depended on the markers used in amplification, suggesting that the use of multiple markers is desirable. Variability in our quantitative results may result from amplification bias as well as interspecific variation in mitochondrial DNA copy number. Our results demonstrate that there remain significant challenges to using metabarcoding for estimating proportional species composition; however, the results provide important insights into understanding how to interpret metabarcoding data. This study will aid in the continuing development of efficient molecular methods of biological monitoring for fisheries management.     

Soil sampling and isolation of extracellular DNA from large amount of starting material suitable for metabarcoding studies

DNA metabarcoding refers to the DNA-based identification of multiple species from a single complex and degraded environmental sample. We developed new sampling and extraction protocols suitable for DNA metabarcoding analyses targeting soil extracellular DNA. The proposed sampling protocol has been designed to reduce, as much as possible, the influence of local heterogeneity by processing a large amount of soil resulting from the mixing of many different cores. The DNA extraction is based on the use of saturated phosphate buffer. The sampling and extraction protocols were validated first by analysing plant DNA from a set of 12 plots corresponding to four plant communities in alpine meadows, and, second, by conducting pilot experiments on fungi and earthworms. The results of the validation experiments clearly demonstrated that sound biological information can be retrieved when following these sampling and extraction procedures. Such a protocol can be implemented at any time of the year without any preliminary knowledge of specific types of organisms during the sampling. It offers the opportunity to analyse all groups of organisms using a single sampling/extraction procedure and opens the possibility to fully standardize biodiversity surveys.     

Genetic monitoring of open ocean biodiversity: An evaluation of DNA metabarcoding for processing continuous plankton recorder samples

DNA metabarcoding is an efficient method for measuring biodiversity, but the process of initiating long‐term DNA‐based monitoring programmes, or integrating with conventional programs, is only starting. In marine ecosystems, plankton surveys using the continuous plankton recorder (CPR) have characterized biodiversity along transects covering millions of kilometres with time‐series spanning decades. We investigated the potential for use of metabarcoding in CPR surveys. Samples (n = 53) were collected in two Southern Ocean transects and metazoans identified using standard microscopic methods and by high‐throughput sequencing of a cytochrome c oxidase subunit I marker. DNA increased the number of metazoan species identified and provided high‐resolution taxonomy of groups problematic in conventional surveys (e.g., larval echinoderms and hydrozoans). Metabarcoding also generally produced more detections than microscopy, but this sensitivity may make cross‐contamination during sampling a problem. In some samples, the prevalence of DNA from large plankton such as krill masked the presence of smaller species. We investigated adding a fixed amount of exogenous DNA to samples as an internal control to allow determination of relative plankton biomass. Overall, the metabarcoding data represent a substantial shift in perspective, making direct integration into current long‐term time‐series challenging. We discuss a number of hurdles that exist for progressing DNA metabarcoding from the current snapshot studies to the requirements of a long‐term monitoring programme. Given the power and continually increasing efficiency of metabarcoding, it is almost certain this approach will play an important role in future plankton monitoring.     

Replicate DNA metabarcoding can discriminate seasonal and spatial abundance shifts in river macroinvertebrate assemblages

The delivery of consistent and accurate fine-resolution data on biodiversity using metabarcoding promises to improve environmental assessment and research. Whilst this approach is a substantial improvement upon traditional techniques, critics note that metabarcoding data are suitable for establishing taxon occurrence, but not abundance. We propose a novel hierarchical approach to recovering abundance information from metabarcoding, and demonstrate this technique using benthic macroinvertebrates. To sample a range of abundance structures without introducing additional changes in composition, we combined seasonal surveys with fish-exclusion experiments at Catamaran Brook in northern New Brunswick, Canada. Five monthly surveys collected 31 benthic samples for DNA metabarcoding divided between caged and control treatments. A further six samples per survey were processed using traditional morphological identification for comparison. By estimating the probability of detecting a single individual, multispecies abundance models infer changes in abundance based on changes in detection frequency. Using replicate detections of 184 genera (and 318 species) from metabarcoding samples, our analysis identified changes in abundance arising from both seasonal dynamics and the exclusion of fish predators. Counts obtained from morphological samples were highly variable, a feature that limited the opportunity for more robust comparison, and emphasizing the difficulty standard methods also face to detect changes in abundance. Our approach is the first to demonstrate how quantitative estimates of abundance can be made using metabarcoding, both among species within sites as well as within species among sites. Many samples are required to capture true abundance patterns, particularly in streams where counts are highly variable, but few studies can afford to process entire samples. Our approach allows study of responses across whole communities, and at fine taxonomic resolution. We discuss how ecological studies can use additional sampling to capture changes in abundance at fine resolution, and how this can complement broad-scale biomonitoring using DNA metabarcoding.     

DNA metabarcoding of airborne pollen: new protocols for improved taxonomic identification of environmental samples

Metabarcoding is a promising DNA-based method for identifying airborne pollen from environmental samples with advantages over microscopic methods. Sample preparation and DNA extraction are of fundamental importance for obtaining an optimal DNA yield. Currently, there is no standard procedure for these steps, especially for gravimetric pollen samplers. Therefore, the aim of this study was to develop protocols for processing environmental samples for pollen DNA extraction and for metabarcoding analysis and to assess the efficacy of these protocols for the taxonomic assignment of airborne pollen collected by gravimetric (Tauber trap) and volumetric (Hirst-type trap) samplers. Protocols were tested across an increasing complexity of samples, from pure single-species pollen to environmental multi-species samples. A short fragment (about 150 base pairs) of the chloroplast trnL gene was amplified using universal primers for plants. After PCR amplification, amplicons were Sanger-sequenced and taxonomic assignment was accomplished by comparison with a custom-made reference database including chloroplast DNA sequences from most of the anemophilous taxa occurring in the study area (Trentino, northern Italy), representing 46 plant families. Using the classical morphological pollen analysis as a benchmark, we show that DNA metabarcoding is efficient and applicable even in complex samples, provided that protocols for sample preparation, DNA extraction, and metabarcoding analysis are carefully optimized.     

Comparing diversity levels in environmental samples: DNA sequence capture and metabarcoding approaches using 18S and COI genes

Environmental DNA studies targeting multiple taxa using metabarcoding provide remarkable insights into levels of species diversity in any habitat. The main drawbacks are the presence of primer bias and difficulty in identifying rare species. We tested a DNA sequence‐capture method in parallel with the metabarcoding approach to reveal possible advantages of one method over the other. Both approaches were performed using the same eDNA samples and the same 18S and COI regions, followed by high throughput sequencing. Metabarcoded eDNA libraries were PCR amplified with one primer pair from 18S and COI genes. DNA sequence‐capture libraries were enriched with 3,639 baits targeting the same gene regions. We tested amplicon sequence variants (ASVs) and operational taxonomic units (OTUs) in silico approaches for both markers and methods, using for this purpose the metabarcoding data set. ASVs methods uncovered more species for the COI gene, whereas the opposite occurred for the 18S gene, suggesting that clustering reads into OTUs could bias diversity richness especially using 18S with relaxed thresholds. Additionally, metabarcoding and DNA sequence‐capture recovered 80%–90% of the control sample species. DNA sequence‐capture was 8x more expensive, nonetheless it identified 1.5x more species for COI and 13x more genera for 18S than metabarcoding. Both approaches offer reliable results, sharing ca. 40% species and 72% families and retrieve more taxa when nuclear and mitochondrial markers are combined. eDNA metabarcoding is quite well established and low‐cost, whereas DNA‐sequence capture for biodiversity assessment is still in its infancy, is more time‐consuming but provides more taxonomic assignments.     

Construction,validation, and application of nocturnal pollen transport networks in an agro‐ecosystem: a comparison using light microscopy and DNA metabarcoding

1. Moths are globally relevant as pollinators but nocturnal pollination remains poorly understood. Plant–pollinator interaction networks are traditionally constructed using either flower‐visitor observations or pollen‐transport detection using microscopy. Recent studies have shown the potential of DNA metabarcoding for detecting and identifying pollen‐transport interactions. However, no study has directly compared the realised observations of pollen‐transport networks between DNA metabarcoding and conventional light microscopy. 2. Using matched samples of nocturnal moths, we constructed pollen‐transport networks using two methods: light microscopy and DNA metabarcoding. Focussing on the feeding mouthparts of moths, we developed and provide reproducible methods for merging DNA metabarcoding and ecological network analysis to better understand species interactions. 3. DNA metabarcoding detected pollen on more individual moths, and detected multiple pollen types on more individuals than microscopy, although the average number of pollen types per individual was unchanged. However, after aggregating individuals of each species, metabarcoding detected more interactions per moth species. Pollen‐transport network metrics differed between methods because of variation in the ability of each to detect multiple pollen types per moth and to separate morphologically similar or related pollen. We detected unexpected but plausible moth–plant interactions with metabarcoding, revealing new detail about nocturnal pollination systems. 4. The nocturnal pollination networks observed using metabarcoding and microscopy were similar yet distinct, with implications for network ecologists. Comparisons between networks constructed using metabarcoding and traditional methods should therefore be treated with caution. Nevertheless, the potential applications of metabarcoding for studying plant–pollinator interaction networks are encouraging, especially when investigating understudied pollinators such as moths.     

DNA metabarcoding and the cytochrome c oxidase subunit I marker: not a perfect match

DNA metabarcoding enables efficient characterization of species composition in environmental DNA or bulk biodiversity samples, and this approach is making significant and unique contributions in the field of ecology. In metabarcoding of animals, the cytochrome c oxidase subunit I (COI) gene is frequently used as the marker of choice because no other genetic region can be found in taxonomically verified databases with sequences covering so many taxa. However, the accuracy of metabarcoding datasets is dependent on recovery of the targeted taxa using conserved amplification primers. We argue that COI does not contain suitably conserved regions for most amplicon-based metabarcoding applications. Marker selection deserves increased scrutiny and available marker choices should be broadened in order to maximize potential in this exciting field of research.     

Molecular‐ and pollen‐based vegetation analysis in lake sediments from central Scandinavia

Plant and animal biodiversity can be studied by obtaining DNA directly from the environment. This new approach in combination with the use of generic barcoding primers (metabarcoding) has been suggested as complementary or alternative to traditional biodiversity monitoring in ancient soil sediments. However, the extent to which metabarcoding truly reflects plant composition remains unclear, as does its power to identify species with no pollen or macrofossil evidence. Here, we compared pollen‐based and metabarcoding approaches to explore the Holocene plant composition around two lakes in central Scandinavia. At one site, we also compared barcoding results with those obtained in earlier studies with species‐specific primers. The pollen analyses revealed a larger number of taxa (46), of which the majority (78%) was not identified by metabarcoding. The metabarcoding identified 14 taxa (MTUs), but allowed identification to a lower taxonomical level. The combined analyses identified 52 taxa. The barcoding primers may favour amplification of certain taxa, as they did not detect taxa previously identified with species‐specific primers. Taphonomy and selectiveness of the primers are likely the major factors influencing these results. We conclude that metabarcoding from lake sediments provides a complementary, but not an alternative, tool to pollen analysis for investigating past flora. In the absence of other fossil evidence, metabarcoding gives a local and important signal from the vegetation, but the resulting assemblages show limited capacity to detect all taxa, regardless of their abundance around the lake. We suggest that metabarcoding is followed by pollen analysis and the use of species‐specific primers to provide the most comprehensive signal from the environment.     

Environmental DNA metabarcoding: Transforming how we survey animal and plant communities

The genomic revolution has fundamentally changed how we survey biodiversity on earth. High‐throughput sequencing (“HTS”) platforms now enable the rapid sequencing of DNA from diverse kinds of environmental samples (termed “environmental DNA” or “eDNA”). Coupling HTS with our ability to associate sequences from eDNA with a taxonomic name is called “eDNA metabarcoding” and offers a powerful molecular tool capable of noninvasively surveying species richness from many ecosystems. Here, we review the use of eDNA metabarcoding for surveying animal and plant richness, and the challenges in using eDNA approaches to estimate relative abundance. We highlight eDNA applications in freshwater, marine and terrestrial environments, and in this broad context, we distill what is known about the ability of different eDNA sample types to approximate richness in space and across time. We provide guiding questions for study design and discuss the eDNA metabarcoding workflow with a focus on primers and library preparation methods. We additionally discuss important criteria for consideration of bioinformatic filtering of data sets, with recommendations for increasing transparency. Finally, looking to the future, we discuss emerging applications of eDNA metabarcoding in ecology, conservation, invasion biology, biomonitoring, and how eDNA metabarcoding can empower citizen science and biodiversity education.     

基于环境DNA宏条形码的洱海鱼类多样性研究

研究使用环境DNA宏条形码(eDNA metabarcoding)检测洱海鱼类多样性, 探索适用于洱海鱼类多样性监测和保护的新方法。通过水样采集、过滤、eDNA提取、遗传标记扩增、测序与生物信息分析的环境DNA宏条形码标准化分析流程, 从洱海16个采样点中获得可检测的9个采样点数据, 共检测出17种鱼类, 其中土著种5种、外来种12种; 鲫(Carassius auratus)、鳙(Hypophthalmichthys nobilis)、麦穗鱼(Pseudorasbora parva)、泥鳅(Misgurnus anguillicaudatus)和食蚊鱼(Gambusia affinis)为优势种。研究结果表明虽然环境DNA宏条形码无法完全替代传统的鱼类监测方法, 但作为一种新兴的生物多样性监测手段, 其可用于快速检测洱海鱼类多样性及其空间分布。     

Toward a standardized quantitative and qualitative insect monitoring scheme

The number of insect species and insect abundances decreased severely during the past decades over major parts of Central Europe. Previous studies documented declines of species richness, abundances, shifts in species composition, and decreasing biomass of flying insects. In this study, we present a standardized approach to quantitatively and qualitatively assess insect diversity, biomass, and the abundance of taxa, in parallel. We applied two methods: Malaise traps, and automated and active light trapping. Sampling was conducted from April to October 2018 in southern Germany, at four sites representing conventional and organic farming. Bulk samples obtained from Malaise traps were further analyzed using DNA metabarcoding. Larger moths (Macroheterocera) collected with light trapping were further classified according to their degree of endangerment. Our methods provide valuable quantitative and qualitative data. Our results indicate more biomass and higher species richness, as well as twice the number of Red List lepidopterans in organic farmland than in conventional farmland. This combination of sampling methods with subsequent DNA metabarcoding and assignments of individuals according depending on ecological characteristics and the degree of endangerment allows to evaluate the status of landscapes and represents a suitable setup for large‐scale long‐term insect monitoring across Central Europe, and elsewhere.