Comprehensive biodiversity analysis via ultra-deep patterned flow cell technology: a case study of eDNA metabarcoding seawater

Assembly mechanism and stability of zooplankton communities affected by China's south-to-north water diversion project

Water diversion can effectively alleviate water resource shortages and improve water environmental conditions, while also causing unknown ecological consequences, in particular, the assembly mechanism of zooplankton communities in the affected areas will become more complex after long-term water transfer. Taking Nansi Lake, the second largest impounded lake along the eastern route of China's South to North Water Diversion Project (SNWDP), as an example, the composition and diversity of zooplankton communities in the lake area and estuaries during the water diversion period (WDP) and non-water diversion period (NWDP) were studied. The potential assembly process of zooplankton communities was further explored, and the stability of communities in different regions during different periods was compared. The related results indicated that the changes in water quality conditions induced by water diversion had a relatively weak impact on the zooplankton communities. In the assembly mechanism of zooplankton communities, stochastic process played a more important role during both WDP or NWDP, and the proportion of deterministic process was relatively higher during NWDP, which may be related to the greater role of total nitrogen (TN) in the assembly of the zooplankton communities. The network analysis and cohesion calculation results showed that the stability of the zooplankton communities in the lake area sites was higher than that in the estuary sites, and the stability during NWDP was higher than that during WDP. In sum, the stability of zooplankton communities displayed a degree of change affected by water diversion activities, but the community assembly was not significantly influenced by the water quality fluctuations after about relatively long-term water diversion. This study provides an in-depth understanding of the ecological effects of water diversion on the biological communities in the affected lake, which is beneficial to the management and regulation of long-term water diversion projects.

Using low volume eDNA methods to sample pelagic marine animal assemblages

Environmental DNA (eDNA) is an increasingly useful method for detecting pelagic animals in the ocean but typically requires large water volumes to sample diverse assemblages. Ship-based pelagic sampling programs that could implement eDNA methods generally have restrictive water budgets. Studies that quantify how eDNA methods perform on low water volumes in the ocean are limited, especially in deep-sea habitats with low animal biomass and poorly described species assemblages. Using 12S rRNA and COI gene primers, we quantified assemblages comprised of micronekton, coastal forage fishes, and zooplankton from low volume eDNA seawater samples (n = 436, 380-1800 mL) collected at depths of 0-2200 m in the southern California Current. We compared diversity in eDNA samples to concurrently collected pelagic trawl samples (n = 27), detecting a higher diversity of vertebrate and invertebrate groups in the eDNA samples. Differences in assemblage composition could be explained by variability in size-selectivity among methods and DNA primer suitability across taxonomic groups. The number of reads and amplicon sequences variants (ASVs) did not vary substantially among shallow (<200 m) and deep samples (>600 m), but the proportion of invertebrate ASVs that could be assigned a species-level identification decreased with sampling depth. Using hierarchical clustering, we resolved horizontal and vertical variability in marine animal assemblages from samples characterized by a relatively low diversity of ecologically important species. Low volume eDNA samples will quantify greater taxonomic diversity as reference libraries, especially for deep-dwelling invertebrate species, continue to expand.

Comparison of the performance of MiSeq and NovaSeq in oral microbiome study

Objective

Next generation sequencing is commonly used to characterize the microbiome structure. MiSeq is most commonly used to analyze the microbiome due to its relatively long read length. Illumina also introduced the 250 × 2 chip for NovaSeq. The purpose of this study was to compare the performance of MiSeq and NovaSeq in the context of oral microbiome study.

Methods

Total read count, read quality score, relative bacterial abundance, community diversity, and correlation between two platforms were analyzed. Phylogenetic trees were analyzed for Streptococcus and periodontopathogens.

Results

NovaSeq produced significantly more read counts and assigned more operational taxonomic units (OTUs) compared to MiSeq. Community diversity was similar between MiSeq and NovaSeq. NovaSeq were able to detect more unique OTUs compared to MiSeq. When phylogenetic trees were constructed for Streptococcus and periodontopathogens, both platforms detected OTUs for most of the clades.

Conclusion

Taken together, while both MiSeq and NovaSeq platforms effectively characterize the oral microbiome, NovaSeq outperformed MiSeq in terms of read counts and detection of unique OTUs, highlighting its potential as a valuable tool for large scale oral microbiome studies.

Analysing the effects of distance, taxon and biomass on vertebrate detections using bulk-collected carrion fly iDNA

Invertebrate-derived DNA (iDNA) metabarcoding from carrion flies is a powerful, non-invasive tool that has value for assessing vertebrate diversity. However, unknowns exist around the factors that influence vertebrate detections, such as spatial limits to iDNA signals or if detections are influenced by taxonomic class or estimated biomass of the vertebrates of interest. Using a bulk-collection method, we captured flies from within a zoo and along transects extending 4 km away from this location. From 920 flies, we detected 28 vertebrate species. Of the 28 detected species, we identified 9 species kept at the zoo, 8 mammals and 1 bird, but no reptiles. iDNA detections were highly geographically localized, and only a few zoo animals were detected outside the zoo setting. However, due to the low number of detections in our dataset, we found no influence of the taxonomic group or the estimated biomass of animals on their detectability. Our data suggest that iDNA detections from bulk-collected carrion flies, at least in urban settings in Australia, are predominantly determined by geographic proximity to the sampling location. This study presents an important step in understanding how iDNA techniques can be used in biodiversity monitoring.

Fishing eDNA in One of the World's Largest Rivers: A Case Study of Cross-Sectional and Depth Profile Sampling in the Yangtze

The world's largest rivers are home to diverse, endemic, and threatened fish species. However, their sheer sizes make large-scale biomonitoring challenging. While environmental DNA (eDNA) metabarcoding has become an established monitoring approach in smaller freshwater ecosystems, its suitability for large rivers may be challenged by the sheer extent of their cross sections (>1 km wide and tens of meters deep). Here, we sampled fish eDNA from multiple vertical layers and horizontal locations from two cross sections of the lower reach of the Yangtze River in China. Over half of the ASVs (amplicon sequence variants) were detected in only a single combination of the vertical layers and horizontal locations, with ∼7% across all combinations. We estimated the need to sample >100 L of water across the cross-sectional profiles to achieve ASV richness saturation, which translates to ∼60 L of water at the species level. No consistent pattern emerged for prioritizing certain depth and horizontal samples, yet we underline the importance of sampling and integrating different layers and locations simultaneously. Our study highlights the significance of spatially stratified sampling and sampling volumes when using eDNA approaches. Specifically, we developed and tested a scalable and broadly applicable strategy that advances the monitoring and conservation of large rivers.

Mock community experiments can inform on the reliability of eDNA metabarcoding data: a case study on marine phytoplankton

Environmental DNA metabarcoding is increasingly implemented in biodiversity monitoring, including phytoplankton studies. Using 21 mock communities composed of seven unicellular diatom and dinoflagellate algae, assembled with different composition and abundance by controlling the number of cells, we tested the accuracy of an eDNA metabarcoding protocol in reconstructing patterns of alpha and beta diversity. This approach allowed us to directly evaluate both qualitative and quantitative metabarcoding estimates. Our results showed non-negligible rates (17-25%) of false negatives (i.e., failure to detect a taxon in a community where it was included), for three taxa. This led to a statistically significant underestimation of metabarcoding-derived alpha diversity (Wilcoxon p = 0.02), with the detected species richness being lower than expected (based on cell numbers) in 8/21 mock communities. Considering beta diversity, the correlation between metabarcoding-derived and expected community dissimilarities was significant but not strong (R2 = 0.41), indicating suboptimal accuracy of metabarcoding results. Average biovolume and rDNA gene copy number were estimated for the seven taxa, highlighting a potential, though not exhaustive, role of the latter in explaining the recorded biases. Our findings highlight the importance of mock communities for assessing the reliability of phytoplankton eDNA metabarcoding studies and identifying their limitations.

Investigations of Fish Assemblages Using Two Methods in Three Terminal Reservoirs of the East Route of South-to-North Water Transfer Project, China

The terminal reservoirs of water transfer projects directly supply water for domestic, agricultural, and industrial applications, and the water quality of these reservoirs produce crucial effects on the achievement of project targets. Typically, fish assemblages are monitored as indicators of reservoir water quality, and can also be regulated for its improvement. In the present study, we compared traditional fish landing (TFL) and environmental DNA (eDNA) metabarcoding methods for monitoring fish assemblages in three terminal reservoirs of the East Route of the South-to-North Water Transfer Project, China. Results of TFL and eDNA showed similar assemblage structures and patterns of diversity and spatial distribution with obvious differences in fish composition across three examined reservoirs. Demersal and small fish were dominant in all reservoirs. In addition, a strong association between water transfer distance and assemblages and distribution of non-native fish was found. Our findings highlight the necessity of the fish assemblage monitoring and managing for water quality and revealed the impact of water diversion distance on the structure of fish assemblages and dispersal of alien species along the water transfer project.

DNA High-Throughput Sequencing for Arthropod Gut Content Analysis to Evaluate Effectiveness and Safety of Biological Control Agents

The search for effective biological control agents without harmful non-target effects has been constrained by the use of impractical (field direct observation) or imprecise (cage experiments) methods. While advances in the DNA sequencing methods, more specifically the development of high-throughput sequencing (HTS), have been quickly incorporated in biodiversity surveys, they have been slow to be adopted to determine arthropod prey range, predation rate and food web structure, and critical information to evaluate the effectiveness and safety of a biological control agent candidate. The lack of knowledge on how HTS methods could be applied by ecological entomologists constitutes part of the problem, although the lack of expertise and the high cost of the analysis also are important limiting factors. In this review, we describe how the latest HTS methods of metabarcoding and Lazaro, a method to identify prey by mapping unassembled shotgun reads, can serve biological control research, showing both their power and limitations. We explain how they work to determine prey range and also how their data can be used to estimate predation rates and subsequently be translated into food webs of natural enemy and prey populations helping to elucidate their role in the community. We present a brief history of prey detection through molecular gut content analysis and also the attempts to develop a more precise formula to estimate predation rates, a problem that still remains. We focused on arthropods in agricultural ecosystems, but most of what is covered here can be applied to natural systems and non-arthropod biological control candidates as well.

Screening Salamanders for Symbionts

Microbial symbionts are broadly categorized by their impacts on host fitness: commensals, pathogens, and mutualists. However, recent investigations into the physiological basis of these impacts have revealed nuanced microbial influences on a wide range of host developmental, immunological, and physiological processes, including regeneration. Exploring these impacts begins with knowing which microbes are present. This methodological pipeline contains both targeted assays using PCR and culturing, as well as culture-independent approaches, to survey host salamander tissues for common and unknown microbial symbionts.

Benthic invertebrates in Svalbard fjords-when metabarcoding does not outperform traditional biodiversity assessment

To protect and restore ecosystems and biodiversity is one of the 10 challenges identified by the United Nations's Decade of the Ocean Science. In this study we used eDNA from sediments collected in two fjords of the Svalbard archipelago and compared the taxonomic composition with traditional methods through metabarcoding, targeting mitochondrial CO1, to survey benthos. Clustering of 21.6 mill sequence reads with a d value of 13 in swarm, returned about 25 K OTU reads. An identification search with the BOLD database returned 12,000 taxonomy annotated sequences spanning a similarity range of 50% to 100%. Using an acceptance filter of minimum 90% similarity to the CO1 reference sequence, we found that 74% of the ca 100 taxon identified sequence reads were Polychaeta and 22% Nematoda. Relatively few other benthic invertebrate species were detected. Many of the identified sequence reads were extra-organismal DNA from terrestrial, planktonic, and photic zone sources. For the species rich Polychaeta, we found that, on average, only 20.6% of the species identified from morphology were also detected with DNA. This discrepancy was not due to missing reference sequences in the search database, because 90-100% (mean 96.7%) of the visually identified species at each station were represented with barcodes in Boldsystems. The volume of DNA samples is small compared with the volume searched in visual sorting, and the replicate DNA-samples in sum covered only about 2% of the surface area of a grab. This may considerably reduce the detection rate of species that are not uniformly distributed in the sediments. Along with PCR amplification bias and primer mismatch, this may be an important reason for the limited congruence of species identified with the two approaches. However, metabarcoding also identified 69 additional species that are usually overlooked in visual sample sorting, demonstrating how metabarcoding can complement traditional methodology by detecting additional, less conspicuous groups of organisms.

A manager's guide to using eDNA metabarcoding in marine ecosystems

Environmental DNA (eDNA) metabarcoding is a powerful tool that can enhance marine ecosystem/biodiversity monitoring programs. Here we outline five important steps managers and researchers should consider when developing eDNA monitoring program: (1) select genes and primers to target taxa; (2) assemble or develop comprehensive barcode reference databases; (3) apply rigorous site occupancy based decontamination pipelines; (4) conduct pilot studies to define spatial and temporal variance of eDNA; and (5) archive samples, extracts, and raw sequence data. We demonstrate the importance of each of these considerations using a case study of eDNA metabarcoding in the Ports of Los Angeles and Long Beach. eDNA metabarcoding approaches detected 94.1% (16/17) of species observed in paired trawl surveys while identifying an additional 55 native fishes, providing more comprehensive biodiversity inventories. Rigorous benchmarking of eDNA metabarcoding results improved ecological interpretation and confidence in species detections while providing archived genetic resources for future analyses. Well designed and validated eDNA metabarcoding approaches are ideally suited for biomonitoring applications that rely on the detection of species, including mapping invasive species fronts and endangered species habitats as well as tracking range shifts in response to climate change. Incorporating these considerations will enhance the utility and efficacy of eDNA metabarcoding for routine biomonitoring applications.

Saint Peter and Saint Paul Archipelago barcoded: Fish diversity in the remoteness and DNA barcodes reference library for metabarcoding monitoring

In order to monitor the effects of anthropogenic pressures in ecosystems, molecular techniques can be used to characterize species composition. Among molecular markers capable of identifying species, the cytochrome c oxidase I (COI) is the most used. However, new possibilities of biodiversity profiling have become possible, in which molecular fragments of medium and short-length can now be analyzed in metabarcoding studies. Here, a survey of fishes from the Saint Peter and Saint Paul Archipelago was barcoded using the COI marker, which allowed the identification of 21 species. This paved the way to further investigate the fish biodiversity of the archipelago, transitioning from barcoding to metabarcoding analysis. As preparatory steps for future metabarcoding studies, the first extensive COI library of fishes listed for these islands was constructed and includes new data generated in this survey as well as previously available data, resulting in a final database with 9,183 sequences from 169 species and 63 families of fish. A new primer specifically designed for those fishes was tested in silico to amplify a region of 262 bp. The new approach should guarantee a reliable surveillance of the archipelago and can be used to generate policies that will enhance the archipelago’s protection.

The power, potential, benefits, and challenges of implementing high-throughput sequencing in food safety systems

The development and application of modern sequencing technologies have led to many new improvements in food safety and public health. With unprecedented resolution and big data, high-throughput sequencing (HTS) has enabled food safety specialists to sequence marker genes, whole genomes, and transcriptomes of microorganisms almost in real-time. These data reveal not only the identity of a pathogen or an organism of interest in the food supply but its virulence potential and functional characteristics. HTS of amplicons, allow better characterization of the microbial communities associated with food and the environment. New and powerful bioinformatics tools, algorithms, and machine learning allow for development of new models to predict and tackle important events such as foodborne disease outbreaks. Despite its potential, the integration of HTS into current food safety systems is far from complete. Government agencies have embraced this new technology, and use it for disease diagnostics, food safety inspections, and outbreak investigations. However, adoption and application of HTS by the food industry have been comparatively slow, sporadic, and fragmented. Incorporation of HTS by food manufacturers in their food safety programs could reinforce the design and verification of effectiveness of control measures by providing greater insight into the characteristics, origin, relatedness, and evolution of microorganisms in our foods and environment. Here, we discuss this new technology, its power, and potential. A brief history of implementation by public health agencies is presented, as are the benefits and challenges for the food industry, and its future in the context of food safety.

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.

Comparing eDNA metabarcoding primers for assessing fish communities in a biodiverse estuary

Metabarcoding of environmental DNA is increasingly used for biodiversity assessments in aquatic communities. The efficiency and outcome of these efforts are dependent upon either de novo primer design or selecting an appropriate primer set from the dozens that have already been published. Unfortunately, there is a lack of studies that have directly compared the efficacy of different metabarcoding primers in marine and estuarine systems. Here we evaluate five commonly used primer sets designed to amplify rRNA barcoding genes in fishes and compare their performance using water samples collected from estuarine sites in the highly biodiverse Indian River Lagoon in Florida. Three of the five primer sets amplify a portion of the mitochondrial 12S gene (MiFish_12S, 171bp; Riaz_12S, 106 bp; Valentini_12S, 63 bp), one amplifies 219 bp of the mitochondrial 16S gene (Berry_16S), and the other amplifies 271 bp of the nuclear 18S gene (MacDonald_18S). The vast majority of the metabarcoding reads (> 99%) generated using the 18S primer set assigned to non-target (non-fish) taxa and therefore this primer set was omitted from most analyses. Using a conservative 99% similarity threshold for species level assignments, we detected a comparable number of species (55 and 49, respectively) and similarly high Shannon’s diversity values for the Riaz_12S and Berry_16S primer sets. Meanwhile, just 34 and 32 species were detected using the MiFish_12S and Valentini_12S primer sets, respectively. We were able to amplify both bony and cartilaginous fishes using the four primer sets with the vast majority of reads (>99%) assigned to the former. We detected the greatest number of elasmobranchs (six species) with the Riaz_12S primer set suggesting that it may be a suitable candidate set for the detection of sharks and rays. Of the total 76 fish species that were identified across all datasets, the combined three 12S primer sets detected 85.5% (65 species) while the combination of the Riaz_12S and Berry_16S primers detected 93.4% (71 species). These results highlight the importance of employing multiple primer sets as well as using primers that target different genomic regions. Moreover, our results suggest that the widely adopted MiFish_12S primers may not be the best choice, rather we found that the Riaz_12S primer set was the most effective for eDNA-based fish surveys in our system.

Applying convolutional neural networks to speed up environmental DNA annotation in a highly diverse ecosystem

High-throughput DNA sequencing is becoming an increasingly important tool to monitor and better understand biodiversity responses to environmental changes in a standardized and reproducible way. Environmental DNA (eDNA) from organisms can be captured in ecosystem samples and sequenced using metabarcoding, but processing large volumes of eDNA data and annotating sequences to recognized taxa remains computationally expensive. Speed and accuracy are two major bottlenecks in this critical step. Here, we evaluated the ability of convolutional neural networks (CNNs) to process short eDNA sequences and associate them with taxonomic labels. Using a unique eDNA data set collected in highly diverse Tropical South America, we compared the speed and accuracy of CNNs with that of a well-known bioinformatic pipeline (OBITools) in processing a small region (60 bp) of the 12S ribosomal DNA targeting freshwater fishes. We found that the taxonomic labels from the CNNs were comparable to those from OBITools, with high correlation levels for the composition of the regional fish fauna. The CNNs enabled the processing of raw fastq files at a rate of approximately 1 million sequences per minute, which was about 150 times faster than with OBITools. Given the good performance of CNNs in the highly diverse ecosystem considered here, the development of more elaborate CNNs promises fast deployment for future biodiversity inventories using eDNA.

Impacts of dietary exposure to pesticides on faecal microbiome metabolism in adult twins

BACKGROUND

Dietary habits have a profound influence on the metabolic activity of gut microorganisms and their influence on health. Concerns have been raised as to whether the consumption of foodstuffs contaminated with pesticides can contribute to the development of chronic disease by affecting the gut microbiome. We performed the first pesticide biomonitoring survey of the British population, and subsequently used the results to perform the first pesticide association study on gut microbiome composition and function from the TwinsUK registry.

METHODS

Dietary exposure of 186 common insecticide, herbicide, or fungicide residues and the faecal microbiome in 65 twin pairs in the UK was investigated. We evaluated if dietary habits, geographic location, or the rural/urban environment, are associated with the excretion of pesticide residues. The composition and metabolic activity of faecal microbiota was evaluated using shotgun metagenomics and metabolomics respectively. We performed a targeted urine metabolomics analysis in order to evaluate whether pesticide urinary excretion was also associated with physiological changes.

RESULTS

Pyrethroid and/or organophosphorus insecticide residues were found in all urine samples, while the herbicide glyphosate was found in 53% of individuals. Food frequency questionnaires showed that residues from organophosphates were higher with increased consumption of fruit and vegetables. A total of 34 associations between pesticide residue concentrations and faecal metabolite concentrations were detected. Glyphosate excretion was positively associated with an overall increased bacterial species richness, as well as to fatty acid metabolites and phosphate levels. The insecticide metabolite Br2CA, reflecting deltamethrin exposure, was positively associated with the phytoestrogens enterodiol and enterolactone, and negatively associated with some N-methyl amino acids. Urine metabolomics performed on a subset of samples did not reveal associations with the excretion of pesticide residues.

CONCLUSIONS

The consumption of conventionally grown fruit and vegetables leads to higher ingestion of pesticides with unknown long-term health consequences. Our results highlight the need for future dietary intervention studies to understand effects of pesticide exposure on the gut microbiome and possible health consequences.

Managing human-mediated range shifts: understanding spatial, temporal and genetic variation in marine non-native species

The use of molecular tools to manage natural resources is increasingly common. However, DNA-based methods are seldom used to understand the spatial and temporal dynamics of species' range shifts. This is important when managing range shifting species such as non-native species (NNS), which can have negative impacts on biotic communities. Here, we investigated the ascidian NNS Ciona robusta, Clavelina lepadiformis, Microcosmus squamiger and Styela plicata using a combined methodological approach. We first conducted non-molecular biodiversity surveys for these NNS along the South African coastline, and compared the results with historical surveys. We detected no consistent change in range size across species, with some displaying range stability and others showing range shifts. We then sequenced a section of cytochrome c oxidase subunit I (COI) from tissue samples and found genetic differences along the coastline but no change over recent times. Finally, we found that environmental DNA metabarcoding data showed broad congruence with both the biodiversity survey and the COI datasets, but failed to capture the complete incidence of all NNS. Overall, we demonstrated how a combined methodological approach can effectively detect spatial and temporal variation in genetic composition and range size, which is key for managing both thriving NNS and threatened species.

This article is part of the theme issue ‘Species’ ranges in the face of changing environments (part I)’.

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.

Non-Invasive Fetal K Status Prediction: 7 Years of Experience

Introduction

In the Kell blood group system, the K and k antigens are the clinically most important ones. Maternal anti-K IgG antibodies can lead to the demise of a K-positive fetus in early pregnancy. Intervention can save the fetus. Prenatal K status prediction of the fetus in early pregnancy is desirable and gives a good basis for pregnancy risk management. We present the results from 7 years of clinical experience in predicting fetal K status as well as some theoretical considerations relevant for design of the assay and evaluation of results.

Methods

Blood was collected from 43 women, all immunized against K, at a mean gestational age of 18 weeks (range 10–38). A total of 56 consecutive samples were tested. The KEL *01.01 /KEL *02 single nucleotide variant that determines K status was amplified from maternal plasma DNA by PCR without allele specificity. The PCR product was sequenced by NGS technology, and the number of sequenced KEL *01.01 and KEL *02 reads were counted. Prediction of the fetal K status was based on this count and was compared with the serologically determined K status of the newborns.

Results

All fetal K predictions were in accordance with postnatal serology where available (n = 34), using our current data analysis.

Conclusion

We have developed an NGS-based method for the non-invasive prediction of fetal K status. This approach requires special considerations in terms of primer design, stringent preanalytical sample handling, and careful analytical procedures. We analyzed samples starting at GA 10 weeks and demonstrated the correct prediction of fetal K status. This assay enables timely clinical intervention in pregnancies at risk of hemolytic disease of the fetus and newborn caused by maternal anti-K IgG antibodies.

Best practices for generating and analyzing 16S rRNA amplicon data to track coral microbiome dynamics

Over the past two decades, researchers have searched for methods to better understand the relationship between coral hosts and their microbiomes. Data on how coral-associated bacteria are involved in their host's responses to stressors that cause bleaching, disease, and other deleterious effects can elucidate how they may mediate, ameliorate, and exacerbate interactions between the coral and the surrounding environment. At the same time tracking coral bacteria dynamics can reveal previously undiscovered mechanisms of coral resilience, acclimatization, and evolutionary adaptation. Although modern techniques have reduced the cost of conducting high-throughput sequencing of coral microbes, to explore the composition, function, and dynamics of coral-associated bacteria, it is necessary that the entire procedure, from collection to sequencing, and subsequent analysis be carried out in an objective and effective way. Corals represent a difficult host with which to work, and unique steps in the process of microbiome assessment are necessary to avoid inaccuracies or unusable data in microbiome libraries, such as off-target amplification of host sequences. Here, we review, compare and contrast, and recommend methods for sample collection, preservation, and processing (e.g., DNA extraction) pipelines to best generate 16S amplicon libraries with the aim of tracking coral microbiome dynamics. We also discuss some basic quality assurance and general bioinformatic methods to analyze the diversity, composition, and taxonomic profiles of the microbiomes. This review aims to be a generalizable guide for researchers interested in starting and modifying the molecular biology aspects of coral microbiome research, highlighting best practices and tricks of the trade.

Environmental DNA (eDNA) Metabarcoding in the Fish Market and Nearby Seafood Restaurants in Taiwan Reveals the Underestimation of Fish Species Diversity in Seafood

Seafood, especially the traditional one in Taiwan, is rarely sourced from a fixed species and routinely from similar species depending on their availability. Hence, the species composition of seafood can be complicated. While a DNA-based approach has been routinely utilized for species identification, a large scale of seafood identification in fish markets and restaurants could be challenging (e.g., elevated cost and time-consuming only for a limited number of species identification). In the present study, we aimed to identify the majority of fish species potentially consumed in fish markets and nearby seafood restaurants using environmental DNA (eDNA) metabarcoding. Four eDNA samplings from a local fish market and nearby seafood restaurants were conducted using Sterivex cartridges. Nineteen universal primers previously validated for fish species identification were utilized to amplify the fragments of mitochondrial DNA (12S, COI, ND5) of species in eDNA samples and sequenced with NovaSeq 6000 sequencing. A total of 153 fish species have been identified based on 417 fish related operational taxonomic units (OTUs) generated from 50,534,995 reads. Principal Coordinate Analysis (PCoA) further showed the differences in fish species between the sampling times and sampling sites. Of these fish species, 22 chondrichthyan fish, 14 Anguilliformes species, and 15 Serranidae species were respectively associated with smoked sharks, braised moray eels, and grouper fish soups. To our best knowledge, this work represents the first study to demonstrate the feasibility of a large scale of seafood identification using eDNA metabarcoding approach. Our findings also imply the species diversity in traditional seafood might be seriously underestimated and crucial for the conservation and management of marine resources.

Pooling size sorted Malaise trap fractions to maximize taxon recovery with metabarcoding

Background

Small and rare specimens can remain undetected when metabarcoding is applied on bulk samples with a high specimen size heterogeneity. This is especially critical for Malaise trap samples, where most of the biodiversity is contributed by small taxa with low biomass. The separation of samples in different size fractions for downstream analysis is one possibility to increase detection of small and rare taxa. However, experiments systematically testing different size sorting approaches and subsequent proportional pooling of fractions are lacking, but would provide important information for the optimization of metabarcoding protocols. We set out to find a size sorting strategy for Malaise trap samples that maximizes taxonomic recovery but remains scalable and time efficient.

Methods

Three Malaise trap samples were sorted into four size classes using dry sieving. Each fraction was homogenized and lysed. The corresponding lysates were pooled to simulate unsorted samples. Pooling was additionally conducted in equal proportions and in four different proportions enriching the small size fraction of samples. DNA from the individual size classes as well as the pooled fractions was extracted and metabarcoded using the FwhF2 and Fol-degen-rev primer set. Additionally, alternative wet sieving strategies were explored.

Results

The small size fractions harboured the highest diversity and were best represented when pooling in favour of small specimens. Metabarcoding of unsorted samples decreases taxon recovery compared to size sorted samples. A size separation into only two fractions (below 4 mm and above) can double taxon recovery compared to not size sorting. However, increasing the sequencing depth 3- to 4-fold can also increase taxon recovery to levels comparable with size sorting, but remains biased towards biomass rich taxa in the sample.

Conclusion

We demonstrate that size fractionation of Malaise trap bulk samples can increase taxon recovery. While results show distinct patterns, the lack of statistical support due to the limited number of samples processed is a limitation. Due to increased speed and lower risk of cross-contamination as well as specimen damage we recommend wet sieving and proportional pooling of the lysates in favour of the small size fraction (80–90% volume). However, for large-scale projects with time constraints, increasing sequencing depth is an alternative solution.

A comprehensive evaluation of single-end sequencing data analyses for environmental microbiome research

Illumina sequencing platforms have been widely used for amplicon-based environmental microbiome research. Analyses of amplicon data of environmental samples, generated from Illumina MiSeq platform illustrate the reverse (R2) reads in the PE datasets to have low quality towards the 3' end of the reads which affect the sequencing depth of samples and ultimately impact the sample size which may possibly lead to an altered outcome. This study evaluates the usefulness of single-end (SE) sequencing data in microbiome research when the Illumina MiSeq PE dataset shows significantly high number of low-quality reverse reads. In this study, the amplicon data (V1V3, V3V4, V4V5 and V6V8) from 128 environmental (soil) samples, downloaded from SRA, demonstrate the efficiency of single-end (SE) sequencing data analyses in microbiome research. The SE datasets were found to infer the core microbiome structure as comparable to the PE dataset. Conspicuously, the forward (R1) datasets inferred a higher number of taxa as compared to PE datasets for most of the amplicon regions, except V3V4. Thus, analyses of SE sequencing data, especially R1 reads, in environmental microbiome studies could ameliorate the problems arising on sample size of the study due to low quality reverse reads in the dataset. However, care must be taken while interpreting the microbiome structure as few taxa observed in the PE datasets were absent in the SE datasets. In conclusion, this study demonstrates the availability of choices in analyzing the amplicon data without having the need to remove samples with low quality reverse reads.

Capture by hybridization for full-length barcode-based eukaryotic and prokaryotic biodiversity inventories of deep sea ecosystems

Biodiversity inventory of marine systems remains limited due to unbalanced access to the three ocean dimensions. The use of environmental DNA (eDNA) for metabarcoding allows fast and effective biodiversity inventory and is forecast as a future biodiversity research and biomonitoring tool. However, in poorly understood ecosystems, eDNA results remain difficult to interpret due to large gaps in reference databases and PCR bias limiting the detection of some major phyla. Here, we aimed to circumvent these limitations by avoiding PCR and recollecting larger DNA fragments to improve assignment of detected taxa through phylogenetic reconstruction. We applied capture by hybridization (CBH) to enrich DNA from deep-sea sediment samples and compared the results with those obtained through an up-to-date metabarcoding PCR-based approach (MTB). Originally developed for bacterial communities and targeting 16S rDNA, the CBH approach was applied to 18S rDNA to improve the detection of species forming benthic communities of eukaryotes, with a particular focus on metazoans. The results confirmed the possibility of extending CBH to metazoans with two major advantages: (i) CBH revealed a broader spectrum of prokaryotic, eukaryotic, and particularly metazoan diversity, and (ii) CBH allowed much more robust phylogenetic reconstructions of full-length barcodes with up to 1900 base pairs. This is particularly important for taxa whose assignment is hampered by gaps in reference databases. This study provides a database and probes to apply 18S CBH to diverse marine systems, confirming this promising new tool to improve biodiversity assessments in data-poor ecosystems such as those in the deep sea.

Biases in bulk: DNA metabarcoding of marine communities and the methodology involved

With the growing anthropogenic pressure on marine ecosystems, the need for efficient monitoring of biodiversity grows stronger. DNA metabarcoding of bulk samples is increasingly being implemented in ecosystem assessments and is more cost-efficient and less time-consuming than monitoring based on morphology. However, before raw sequences are obtained from bulk samples, a profound number of methodological choices must be made. Here, we critically review the recent methods used for metabarcoding of marine bulk samples (including benthic, plankton and diet samples) and indicate how potential biases can be introduced throughout sampling, preprocessing, DNA extraction, marker and primer selection, PCR amplification and sequencing. From a total of 64 studies evaluated, our recommendations for best practices include to (a) consider DESS as a fixative instead of ethanol, (b) use the DNeasy PowerSoil kit for any samples containing traces of sediment, (c) not limit the marker selection to COI only, but preferably include multiple markers for higher taxonomic resolution, (d) avoid touchdown PCR profiles, (e) use a fixed annealing temperature for each primer pair when comparing across studies or institutes, (f) use a minimum of three PCR replicates, and (g) include both negative and positive controls. Although the implementation of DNA metabarcoding still faces several technical complexities, we foresee wide-ranging advances in the near future, including improved bioinformatics for taxonomic assignment, sequencing of longer fragments and the use of whole-genome information. Despite the bulk of biases involved in metabarcoding of bulk samples, if appropriate controls are included along the data generation process, it is clear that DNA metabarcoding provides a valuable tool in ecosystem assessments.

Evaluating sediment and water sampling methods for the estimation of deep-sea biodiversity using environmental DNA

Despite representing one of the largest biomes on earth, biodiversity of the deep seafloor is still poorly known. Environmental DNA metabarcoding offers prospects for fast inventories and surveys, yet requires standardized sampling approaches and careful choice of environmental substrate. Here, we aimed to optimize the genetic assessment of prokaryote (16S), protistan (18S V4), and metazoan (18S V1-V2, COI) communities, by evaluating sampling strategies for sediment and aboveground water, deployed simultaneously at one deep-sea site. For sediment, while size-class sorting through sieving had no significant effect on total detected alpha diversity and resolved similar taxonomic compositions at the phylum level for all markers studied, it effectively increased the detection of meiofauna phyla. For water, large volumes obtained from an in situ pump (~ 6000 L) detected significantly more metazoan diversity than 7.5 L collected in sampling boxes. However, the pump being limited by larger mesh sizes (> 20 µm), only captured a fraction of microbial diversity, while sampling boxes allowed access to the pico- and nanoplankton. More importantly, communities characterized by aboveground water samples significantly differed from those characterized by sediment, whatever volume used, and both sample types only shared between 3 and 8% of molecular units. Together, these results underline that sediment sieving may be recommended when targeting metazoans, and aboveground water does not represent an alternative to sediment sampling for inventories of benthic diversity.

PPIT: an R package for inferring microbial taxonomy from nifH sequences

MOTIVATION

Linking microbial community members to their ecological functions is a central goal of environmental microbiology. When assigned taxonomy, amplicon sequences of metabolic marker genes can suggest such links, thereby offering an overview of the phylogenetic structure underpinning particular ecosystem functions. However, inferring microbial taxonomy from metabolic marker gene sequences remains a challenge, particularly for the frequently sequenced nitrogen fixation marker gene, nitrogenase reductase (nifH). Horizontal gene transfer in recent nifH evolutionary history can confound taxonomic inferences drawn from the pairwise identity methods used in existing software. Other methods for inferring taxonomy are not standardized and require manual inspection that is difficult to scale.

RESULTS

We present Phylogenetic Placement for Inferring Taxonomy (PPIT), an R package that infers microbial taxonomy from nifH amplicons using both phylogenetic and sequence identity approaches. After users place query sequences on a reference nifH gene tree provided by PPIT (n = 6317 full-length nifH sequences), PPIT searches the phylogenetic neighborhood of each query sequence and attempts to infer microbial taxonomy. An inference is drawn only if references in the phylogenetic neighborhood are: (1) taxonomically consistent and (2) share sufficient pairwise identity with the query, thereby avoiding erroneous inferences due to known horizontal gene transfer events. We find that PPIT returns a higher proportion of correct taxonomic inferences than BLAST-based approaches at the cost of fewer total inferences. We demonstrate PPIT on deep-sea sediment and find that Deltaproteobacteria are the most abundant potential diazotrophs. Using this dataset we show that emending PPIT inferences based on visual inspection of query sequence placement can achieve taxonomic inferences for nearly all sequences in a query set. We additionally discuss how users can apply PPIT to the analysis of other marker genes.

AVAILABILITY

PPIT is freely available to non-commercial users at https://github.com/bkapili/ppit. Installation includes a vignette that demonstrates package use and reproduces the nifH amplicon analysis discussed here. The raw nifH amplicon sequence data have been deposited in the GenBank, EMBL, and DDBJ databases under BioProject number PRJEB37167.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Integration of DNA-Based Approaches in Aquatic Ecological Assessment Using Benthic Macroinvertebrates

Benthic macroinvertebrates are among the most used biological quality elements for assessing the condition of all types of aquatic ecosystems worldwide (i.e., fresh water, transitional, and marine). Current morphology-based assessments have several limitations that may be circumvented by using DNA-based approaches. Here, we present a comprehensive review of 90 publications on the use of DNA metabarcoding of benthic macroinvertebrates in aquatic ecosystems bioassessments. Metabarcoding of bulk macrozoobenthos has been preferentially used in fresh waters, whereas in marine waters, environmental DNA (eDNA) from sediment and bulk communities from deployed artificial structures has been favored. DNA extraction has been done predominantly through commercial kits, and cytochrome c oxidase subunit I (COI) has been, by far, the most used marker, occasionally combined with others, namely, the 18S rRNA gene. Current limitations include the lack of standardized protocols and broad-coverage primers, the incompleteness of reference libraries, and the inability to reliably extrapolate abundance data. In addition, morphology versus DNA benchmarking of ecological status and biotic indexes are required to allow general worldwide implementation and higher end-user confidence. The increased sensitivity, high throughput, and faster execution of DNA metabarcoding can provide much higher spatial and temporal data resolution on aquatic ecological status, thereby being more responsive to immediate management needs.

Status and prospects of marine NIS detection and monitoring through (e)DNA metabarcoding

In coastal ecosystems, non-indigenous species (NIS) are recognized as a major threat to biodiversity, ecosystem functioning and socio-economic activities. Here we present a systematic review on the use of metabarcoding for NIS surveillance in marine and coastal ecosystems, through the analysis of 42 publications. Metabarcoding has been mainly applied to environmental DNA (eDNA) from water samples, but also to DNA extracted from bulk organismal samples. DNA extraction kits have been widely used and the 18S rRNA and the COI genes the most employed markers, but less than half of the studies targeted more than one marker loci. The Illumina MiSeq platform has been used in >50% of the publications. Current weaknesses include potential occurrence of false negatives due to the primer-biased or faulty DNA amplification and the incompleteness of reference libraries. This is particularly concerning in the case of NIS surveillance, where proficiency in species level detection is critical. Until these weaknesses are resolved, ideally NIS metabarcoding should be supported by complementary approaches, such as morphological analysis or more targeted molecular approaches (e.g. qPCR, ddPCR). Even so, metabarcoding has already proved to be a highly sensitive tool to detect small organisms or undifferentiated life stages across a wide taxonomic range. In addition, it also seems to be very effective in ballast water management and to improve the spatial and temporal sampling frequency of NIS surveillance in marine and coastal ecosystems. Although specific protocols may be required for species-specific NIS detection, for general monitoring it would be vital to settle on a standard protocol able to generate comparable results among surveillance campaigns and regions of the globe, seeking the best approach for detecting the broadest range of species, while minimizing the chances of a false positive or negative detection.

Use of Shotgun Metagenomics and Metabolomics to Evaluate the Impact of Glyphosate or Roundup MON 52276 on the Gut Microbiota and Serum Metabolome of Sprague-Dawley Rats

BACKGROUND

There is intense debate on whether glyphosate can inhibit the shikimate pathway of gastrointestinal microorganisms, with potential health implications.

OBJECTIVES

We tested whether glyphosate or its representative EU herbicide formulation Roundup MON 52276 affects the rat gut microbiome.

METHODS

We combined cecal microbiome shotgun metagenomics with serum and cecum metabolomics to assess the effects of glyphosate [0.5, 50, 175 mg / kg  body weight  ( BW )  per day ] or MON 52276 at the same glyphosate-equivalent doses, in a 90-d toxicity test in rats.

RESULTS

Glyphosate and MON 52276 treatment resulted in ceca accumulation of shikimic acid and 3-dehydroshikimic acid, suggesting inhibition of 5-enolpyruvylshikimate-3-phosphate synthase of the shikimate pathway in the gut microbiome. Cysteinylglycine, γ -glutamylglutamine , and valylglycine levels were elevated in the cecal microbiome following glyphosate and MON 52276 treatments. Altered cecum metabolites were not differentially expressed in serum, suggesting that the glyphosate and MON 52276 impact on gut microbial metabolism had limited consequences on physiological biochemistry. Serum metabolites differentially expressed with glyphosate treatment were associated with nicotinamide, branched-chain amino acid, methionine, cysteine, and taurine metabolism, indicative of a response to oxidative stress. MON 52276 had similar, but more pronounced, effects than glyphosate on the serum metabolome. Shotgun metagenomics of the cecum showed that treatment with glyphosate and MON 52276 resulted in higher levels of Eggerthella spp., Shinella zoogleoides, Acinetobacter johnsonii, and Akkermansia muciniphila. Shinella zoogleoides was higher only with MON 52276 exposure. In vitro culture assays with Lacticaseibacillus rhamnosus strains showed that Roundup GT plus inhibited growth at concentrations at which MON 52276 and glyphosate had no effect.

DISCUSSION

Our study highlights the power of multi-omics approaches to investigate the toxic effects of pesticides. Multi-omics revealed that glyphosate and MON 52276 inhibited the shikimate pathway in the rat gut microbiome. Our findings could be used to develop biomarkers for epidemiological studies aimed at evaluating the effects of glyphosate herbicides on humans. https://doi.org/10.1289/EHP6990.

Metabarcoding From Microbes to Mammals: Comprehensive Bioassessment on a Global Scale

Global biodiversity loss is unprecedented, and threats to existing biodiversity are growing. Given pervasive global change, a major challenge facing resource managers is a lack of scalable tools to rapidly and consistently measure Earth's biodiversity. Environmental genomic tools provide some hope in the face of this crisis, and DNA metabarcoding, in particular, is a powerful approach for biodiversity assessment at large spatial scales. However, metabarcoding studies are variable in their taxonomic, temporal, or spatial scope, investigating individual species, specific taxonomic groups, or targeted communities at local or regional scales. With the advent of modern, ultra-high throughput sequencing platforms, conducting deep sequencing metabarcoding surveys with multiple DNA markers will enhance the breadth of biodiversity coverage, enabling comprehensive, rapid bioassessment of all the organisms in a sample. Here, we report on a systematic literature review of 1,563 articles published about DNA metabarcoding and summarize how this approach is rapidly revolutionizing global bioassessment efforts. Specifically, we quantify the stakeholders using DNA metabarcoding, the dominant applications of this technology, and the taxonomic groups assessed in these studies. We show that while DNA metabarcoding has reached global coverage, few studies deliver on its promise of near-comprehensive biodiversity assessment. We then outline how DNA metabarcoding can help us move toward real-time, global bioassessment, illustrating how different stakeholders could benefit from DNA metabarcoding. Next, we address barriers to widespread adoption of DNA metabarcoding, highlighting the need for standardized sampling protocols, experts and computational resources to handle the deluge of genomic data, and standardized, open-source bioinformatic pipelines. Finally, we explore how technological and scientific advances will realize the promise of total biodiversity assessment in a sample—from microbes to mammals—and unlock the rich information genomics exposes, opening new possibilities for merging whole-system DNA metabarcoding with (1) abundance and biomass quantification, (2) advanced modeling, such as species occupancy models, to improve species detection, (3) population genetics, (4) phylogenetics, and (5) food web and functional gene analysis. While many challenges need to be addressed to facilitate widespread adoption of environmental genomic approaches, concurrent scientific and technological advances will usher in methods to supplement existing bioassessment tools reliant on morphological and abiotic data. This expanded toolbox will help ensure that the best tool is used for the job and enable exciting integrative techniques that capitalize on multiple tools. Collectively, these new approaches will aid in addressing the global biodiversity crisis we now face.

Harnessing the power of eDNA metabarcoding for the detection of deep-sea fishes

The deep ocean is the largest biome on Earth and faces increasing anthropogenic pressures from climate change and commercial fisheries. Our ability to sustainably manage this expansive habitat is impeded by our poor understanding of its inhabitants and by the difficulties in surveying and monitoring these areas. Environmental DNA (eDNA) metabarcoding has great potential to improve our understanding of this region and to facilitate monitoring across a broad range of taxa. Here, we evaluate two eDNA sampling protocols and seven primer sets for elucidating fish diversity from deep sea water samples. We found that deep sea water samples (> 1400 m depth) had significantly lower DNA concentrations than surface or mid-depth samples necessitating a refined protocol with a larger sampling volume. We recovered significantly more DNA in large volume water samples (1.5 L) filtered at sea compared to small volume samples (250 mL) held for lab filtration. Furthermore, the number of unique sequences (exact sequence variants; ESVs) recovered per sample was higher in large volume samples. Since the number of ESVs recovered from large volume samples was less variable and consistently high, we recommend the larger volumes when sampling water from the deep ocean. We also identified three primer sets which detected the most fish taxa but recommend using multiple markers due the variability in detection probabilities and taxonomic resolution among fishes for each primer set. Overall, fish diversity results obtained from metabarcoding were comparable to conventional survey methods. While eDNA sampling and processing need be optimized for this unique environment, the results of this study demonstrate that eDNA metabarcoding can facilitate biodiversity surveys in the deep ocean, require less dedicated survey effort per unit identification, and are capable of simultaneously providing valuable information on other taxonomic groups.

Marine biomonitoring with eDNA: Can metabarcoding of water samples cut it as a tool for surveying benthic communities?

In the marine realm, biomonitoring using environmental DNA (eDNA) of benthic communities requires destructive direct sampling or the setting-up of settlement structures. Comparatively much less effort is required to sample the water column, which can be accessed remotely. In this study we assess the feasibility of obtaining information from the eukaryotic benthic communities by sampling the adjacent water layer. We studied two different rocky-substrate benthic communities with a technique based on quadrat sampling. We also took replicate water samples at four distances (0, 0.5, 1.5, and 20 m) from the benthic habitat. Using broad range primers to amplify a ca. 313 bp fragment of the cytochrome oxidase subunit I gene, we obtained a total of 3,543 molecular operational taxonomic units (MOTUs). The structure obtained in the two environments was markedly different, with Metazoa, Archaeplastida and Stramenopiles being the most diverse groups in benthic samples, and Hacrobia, Metazoa and Alveolata in the water. Only 265 MOTUs (7.5%) were shared between benthos and water samples and, of these, 180 (5.1%) were identified as benthic taxa that left their DNA in the water. Most of them were found immediately adjacent to the benthos, and their number decreased as we moved apart from the benthic habitat. It was concluded that water eDNA, even in the close vicinity of the benthos, was a poor proxy for the analysis of benthic structure, and that direct sampling methods are required for monitoring these complex communities via metabarcoding.

The human T-cell receptor repertoire in health and disease and potential for omics integration

The adaptive immune system arose 600 million years ago in a cold-blooded fish. Over countless generations, our antecedents tuned the function of the T-cell receptor (TCR). The TCR system is arguably the most complex known to science. The TCR evolved hypervariability to fight the hypervariability of pathogens and cancers that look to consume our resources. This review describes the genetics and architecture of the human TCR and highlights surprising new discoveries over the past years that have disproved very old dogmas. The standardization of TCR sequencing data is discussed in preparation for big data bioinformatics and predictive analysis. We next catalogue new signatures and phenomenon discovered by TCR next generation sequencing (NGS) in health and disease and work that remain to be done in this space. Finally, we discuss how TCR NGS can add to immunodiagnostics and integrate with other omics platforms for both a deeper understanding of TCR biology and its use in the clinical setting.

High throughput shotgun sequencing of eRNA reveals taxonomic and derived functional shifts across a benthic productivity gradient

Benthic macrofauna is regularly used in monitoring programmes, however the vast majority of benthic eukaryotic biodiversity lies mostly in microscopic organisms, such as meiofauna (invertebrates < 1 mm) and protists, that rapidly responds to environmental change. These communities have traditionally been hard to sample and handle in the laboratory, but DNA sequencing has made such work less time consuming. While DNA sequencing captures both alive and dead organisms, environmental RNA (eRNA) better targets living organisms or organisms of recent origin in the environment. Here, we assessed the biodiversity of three known bioindicator microeukaryote groups (nematodes, foraminifera, and ciliates) in sediment samples collected at seven coastal sites along an organic carbon (OC) gradient. We aimed to investigate if eRNA shotgun sequencing can be used to simultaneously detect differences in (i) biodiversity of multiple microeukaryotic communities; and (ii) functional feeding traits of nematodes. Results showed that biodiversity was lower for nematodes and foraminifera in high OC (6.2%-6.9%), when compared to low OC sediments (1.2%-2.8%). Dissimilarity in community composition increased for all three groups between Low OC and High OC, as well as the classified feeding type of nematode genera (with more nonselective deposit feeders in high OC sediment). High relative abundant genera included nematode Sabatieria and foraminifera Elphidium in high OC, and Cryptocaryon-like ciliates in low OC sediments. Considering that future sequencing technologies are likely to decrease in cost, the use of eRNA shotgun sequencing to assess biodiversity of benthic microeukaryotes could be a powerful tool in recurring monitoring programmes.

Molecular ecology as a tool for understanding pollination and other plant-insect interactions

Advances in molecular ecology offer unprecedented opportunities to understand the ecology and evolution of insects, the complex ways in which they interact and their role in ecosystem functioning. Rapidly developing DNA sequencing technologies are resolving previously intractable questions in taxonomic and functional biodiversity and provide significant potential to determine formerly difficult to observe plant-insect interactions. We provide an overview of the state-of-the-art and critically appraise the range of molecular approaches currently available for the study of insect pollination, host-parasitoid interactions and/or wider food-web studies. Species-interaction data are increasingly being incorporated into ecological network analyses. DNA metabarcoding offers opportunities to scale-up efforts to create large, highly resolved, phylogenetically structured networks within an exciting framework to study pressing questions in ecology and evolution.

Validating metabarcoding-based biodiversity assessments with multi-species occupancy models: A case study using coastal marine eDNA

Environmental DNA (eDNA) metabarcoding is an increasingly popular method for rapid biodiversity assessment. As with any ecological survey, false negatives can arise during sampling and, if unaccounted for, lead to biased results and potentially misdiagnosed environmental assessments. We developed a multi-scale, multi-species occupancy model for the analysis of community biodiversity data resulting from eDNA metabarcoding; this model accounts for imperfect detection and additional sources of environmental and experimental variation. We present methods for model assessment and model comparison and demonstrate how these tools improve the inferential power of eDNA metabarcoding data using a case study in a coastal, marine environment. Using occupancy models to account for factors often overlooked in the analysis of eDNA metabarcoding data will dramatically improve ecological inference, sampling design, and methodologies, empowering practitioners with an approach to wield the high-resolution biodiversity data of next-generation sequencing platforms.

Holistic pelagic biodiversity monitoring of the Black Sea via eDNA metabarcoding approach: From bacteria to marine mammals

As the largest semi-closed marine ecosystem in the world, the Black Sea has been heavily affected by human activities for a long time. Describing the biodiversity of multi-trophic biota in pelagic zone of the Black Sea and identifying the dominant environmental factors are prerequisites for protecting the sustainability of ecosystems. However, up to now, the taxonomic and distributional information about the Black Sea biota is not clear. Here, we employed a Tree-of-Life metabarcoding to analyze the biodiversity of eight communities in the Black Sea, investigated their biogeographical distribution, and further analyzed the influence of biological and abiotic factors on biota on large scales. We found that, (1) Over 8900 OTUs were detected in the Black Sea, of which 630 species were identified, covering the holistic biota from single-celled (bacteria 5620 OTUs 141 species; algae 1096 OTUs 185 species; protozoa 546 OTUs 146 species) to multicellular organisms (invertebrate metazoans 150 OTUs 34 species; fishes 1369 OTUs 76 species; large marine mammals 39 OTUs 5 species). (2) Higher trophic organisms (fishes and large mammals) distributed more evenly in space than the lower (microorganisms, protozoa and invertebrates). For lower trophic organisms, the vertical stratification was more obvious than the horizontal stratification (vertical p < 0.02, horizontal p < 0.05). (3) The bottom trophic organisms (bacteria and algae) of the food web significantly affected the distribution and composition of the others through biological interactions (Mantel p < 0.05). (4) At the level of abiotic factors, the effect of local species sorting on the composition of communities was 15% higher than that of mass dispersal effect. For the first time, this study monitored and profiled the holistic biodiversity in the pelagic zone of the Black Sea, and provided technological advances and preliminary knowledge for the ongoing Black Sea ecosystem protection efforts.

Validation of COI metabarcoding primers for terrestrial arthropods

Metabarcoding can rapidly determine the species composition of bulk samples and thus aids biodiversity and ecosystem assessment. However, it is essential to use primer sets that minimize amplification bias among taxa to maximize species recovery. Despite this fact, the performance of primer sets employed for metabarcoding terrestrial arthropods has not been sufficiently evaluated. This study tests the performance of 36 primer sets on a mock community containing 374 insect species. Amplification success was assessed with gradient PCRs and the 21 most promising primer sets selected for metabarcoding. These 21 primer sets were also tested by metabarcoding a Malaise trap sample. We identified eight primer sets, mainly those including inosine and/or high degeneracy, that recovered more than 95% of the species in the mock community. Results from the Malaise trap sample were congruent with the mock community, but primer sets generating short amplicons produced potential false positives. Taxon recovery from both mock community and Malaise trap sample metabarcoding were used to select four primer sets for additional evaluation at different annealing temperatures (40-60 °C) using the mock community. The effect of temperature varied by primer pair but overall it only had a minor effect on taxon recovery. This study reveals the weak performance of some primer sets employed in past studies. It also demonstrates that certain primer sets can recover most taxa in a diverse species assemblage. Thus, based our experimental set up, there is no need to employ several primer sets targeting the same gene region. We identify several suitable primer sets for arthropod metabarcoding, and specifically recommend BF3 + BR2, as it is not affected by primer slippage and provides maximal taxonomic resolution. The fwhF2 + fwhR2n primer set amplifies a shorter fragment and is therefore ideal when targeting degraded DNA (e.g., from gut contents).

COI metabarcoding primer choice affects richness and recovery of indicator taxa in freshwater systems

Mixed community or environmental DNA marker gene sequencing has become a commonly used technique for biodiversity analyses in freshwater systems. Many cytochrome c oxidase subunit I (COI) primer sets are now available for such work. The purpose of this study is to test whether COI primer choice affects the recovery of arthropod richness, beta diversity, and recovery of target assemblages in the benthos kick-net samples typically used in freshwater biomonitoring. We examine six commonly used COI primer sets on samples collected from six freshwater sites. Biodiversity analyses show that richness is sensitive to primer choice and the combined use of multiple COI amplicons recovers higher richness. Thus, to recover maximum richness, multiple primer sets should be used with COI metabarcoding. In ordination analyses based on community dissimilarity, samples consistently cluster by site regardless of amplicon choice or PCR replicate. Thus, for broadscale community analyses, overall beta diversity patterns are robust to COI marker choice. Recovery of traditional freshwater bioindicator assemblages such as Ephemeroptera, Trichoptera, Plectoptera, and Chironomidae as well as Arthropoda site indicators were differentially detected by each amplicon tested. This work will help future biodiversity and biomonitoring studies develop not just standardized, but optimized workflows that either maximize taxon-detection or the selection of amplicons for water quality or Arthropoda site indicators.