High-throughput environmental DNA analysis informs a biological assessment of an urban stream

The metabarcoding of Grubs: Traditional herbal medicine of Scarabaeidae larvae

Grubs, called Qicao in China, have a long tradition as herbal medicine in East Asia. These larvae belong to the diverse family Scarabaeidae and are typically harvested from the wild during their immature stage based on morphological characteristics. However, rapid and accurate identification becomes challenging when relying solely on external morphological features, as the lack of clarity on biological sources raises safety concerns for clinical applications. The application of DNA metabarcoding provides a solution by enabling the determination of the biological source of a large sample. In the current study, we collected 19 batches of Grubs, consisting of 11,539 individuals, from the market and analyzed their biological composition through metabarcoding. We identified 49 Amplicon Sequence Variants (ASVs), 21 of which were Grubs. The 21 ASVs were classified into seven Molecular Operational Taxonomic Units (MOTUs) through species delimitation, which revealed that commercially available Grubs are predominantly sourced from Protaetia brevitarsis seulensis, while species of Rutelinae, Anomala, and Holotrichia were also abundant in some commercial batches. Among the identified ASVs, 28 belonged to non-Grub species and indicated adulteration from different animal families; high abundances of these ASVs were detected for Bombycidae, Tabanidae, and Viviparidae. Our findings underscore the complexity of Grubs' species composition and advocate for a deeper understanding of the wildlife sources contributing to herbal products. This research contributes valuable insights into the molecular identification of Grubs, paving the way for enhanced quality assurance in traditional medicine applications to provide safe and effective medicines for humanity.

Periodic Addition of Glucose Suppressed Cyanobacterial Abundance in Additive Lake Water Samples during the Entire Bloom Season

Previously, we showed that prophylactic addition of glucose to Harsha Lake water samples could inhibit cyanobacteria growth, at least for a short period of time. The current study tested cyanobacterial control with glucose for the entire Harsha Lake bloom season. Water samples (1000 ml) were collected weekly from Harsha Lake during the algal-bloom season starting June 9 and lasting until August 24, 2022. To each of two 7-liter polypropylene containers, 500 ml of Harsha Lake water was added, and the containers were placed in a controlled environment chamber. To one container labeled "Treated," 0.15 g of glucose was added, and nothing was added to the container labeled "Control." After that, three 25 ml samples from each container were collected and used for 16S rRNA gene sequencing each week. Then 1000 ml of Harsha Lake water was newly collected each week, with 500 ml added to each container, along with the addition of 0.15 g glucose to the "Treated" container. Sequencing data were used to examine differences in the composition of bacterial communities between Treated and Control containers. Treatment with glucose altered the microbial communities by 1) reducing taxonomic diversity, 2) largely eliminating cyanobacterial taxa, and 3) increasing the relative abundance of subsets of non-cyanobacterial taxa (such as Proteobacteria and Actinobacteriota). These effects were observed across time despite weekly inputs derived directly from Lake water. The addition of glucose to a container receiving weekly additions of Lake water suppressed the cyanobacterial populations during the entire summer bloom season. The glucose appears to stimulate the diversity of certain bacterial taxa at the expense of the cyanobacteria.

Environmental DNA, hydrochemistry and stable water isotopes as integrative tracers of urban ecohydrology

Urbanization and the persistent environmental changes present a major challenge for urban freshwaters and availability of water for humans and wildlife. In order to increase understanding of urban ecohydrology, we investigated the variability of planktonic bacteria and benthic diatoms - as two key biological indicators - coupled with insights from hydrochemistry and stable water isotopes across four urban streams characterized by different dominant water sources in Berlin, the German capital, over a period of one year (2021-2022). DNA metabarcoding results show that substantial spatio-temporal variability exists across urban streams in terms of microbial diversity and richness, with clear links to abiotic factors and nutrient concentrations. Bacterial communities showed clear distinction between effluent-impacted and non-effluent impacted streams as well as clear seasonal turnover. In-stream benthic diatom assemblages also showed robust seasonal variation as well as high species diversity. Our multiple-tracer approach is relevant for emerging questions regarding the increased use of treated effluent to supplement declining baseflows, the assessment of stream restoration projects and the impact of storm drainage and surface pollution on aquatic ecosystem health. eDNA analysis allows analysis of spatial and temporal patterns not feasibly studied with traditional analyses of macroinvertebrates. This can ultimately be leveraged for future water resource management and restoration planning and monitoring of urban freshwater systems across metropolitan areas.

Spatial and Temporal Variability of Saxitoxin-Producing Cyanobacteria in U.S. Urban Lakes

Harmful cyanobacterial blooms (HCBs) are of growing global concern due to their production of toxic compounds, which threaten ecosystems and human health. Saxitoxins (STXs), commonly known as paralytic shellfish poison, are a neurotoxic alkaloid produced by some cyanobacteria. Although many field studies indicate a widespread distribution of STX, it is understudied relative to other cyanotoxins such as microcystins (MCs). In this study, we assessed eleven U.S. urban lakes using qPCR, sxtA gene-targeting sequencing, and 16S rRNA gene sequencing to understand the spatio-temporal variations in cyanobacteria and their potential role in STX production. During the blooms, qPCR analysis confirmed the presence of the STX-encoding gene sxtA at all lakes. In particular, the abundance of the sxtA gene had a strong positive correlation with STX concentrations in Big 11 Lake in Kansas City, which was also the site with the highest quantified STX concentration. Sequencing analysis revealed that potential STX producers, such as Aphanizomenon, Dolichospermum, and Raphidiopsis, were present. Further analysis targeting amplicons of the sxtA gene identified that Aphanizomenon and/or Dolichospermum are the primary STX producer, showing a significant correlation with sxtA gene abundances and STX concentrations. In addition, Aphanizomenon was associated with environmental factors, such as conductivity, sulfate, and orthophosphate, whereas Dolichospermum was correlated with temperature and pH. Overall, the results herein enhance our understanding of the STX-producing cyanobacteria and aid in developing strategies to control HCBs.

Monitoring of multiple fish species by quantitative environmental DNA metabarcoding surveys over two summer seasons

Periodic monitoring can provide important information for the protection of endangered fish, sustainable use of fishery resources and management of alien species. Previous studies have attempted to monitor fish using non-invasive environmental DNA (eDNA) technology, generally employing quantitative PCR to quantify the eDNA concentration. However, the throughput was limited. High-throughput metabarcoding technology can detect the DNA of multiple species simultaneously in a single experiment but does not provide sufficient quantification. In this study, we applied a quantitative metabarcoding approach to simultaneously quantify the eDNA concentration of an entire fish assemblage in a small reservoir over two summer seasons. Traditional surveys were also conducted to investigate the individuals of fish. The eDNA concentrations were quantified using quantitative metabarcoding, and the fish species detected using this approach were highly consistent with the results of traditional fish monitoring. A significant positive relationship was observed between the eDNA concentration and fish species abundance. Seasonal changes in fish community structure were estimated using eDNA concentrations, which may reveal the activity seasons of different fish. The eDNA concentrations of different fish species peaked at different water temperatures, reflecting the differential responses of fish species to this environmental factor. Finally, by detecting outlier eDNA concentrations, the spawning activities of 13 fish species were estimated, 12 of which were roughly consistent with the current knowledge of fish spawning periods. These results indicate that quantitative eDNA metabarcoding with dozens of sampling times is useful for the simultaneous ecological monitoring of multiple fish species.

Supervised machine learning improves general applicability of eDNA metabarcoding for reservoir health monitoring

Effective and standardized monitoring methodologies are vital for successful reservoir restoration and management. Environmental DNA (eDNA) metabarcoding sequencing offers a promising alternative for biomonitoring and can overcome many limitations of traditional morphological bioassessment. Recent attempts have even shown that supervised machine learning (SML) can directly infer biotic indices (BI) from eDNA metabarcoding data, bypassing the cumbersome calculation process of BI regardless of the taxonomic assignment of eDNA sequences. However, questions surrounding the general applicability of this taxonomy-free approach to monitoring reservoir health remain unclear, including model stability, feature selection, algorithm choice, and multi-season biomonitoring. Here, we firstly developed a novel biological integrity index (Me-IBI) that integrates multitrophic interactions and environmental information, based on taxonomy-assigned eDNA metabarcoding data. The Me-IBI can better distinguish the actual health status of the Three Gorges Reservoir (TGR) than physicochemical assessments and have a clear response to human activity. Then, taking this reliable Me-IBI as a supervised label, we compared the impact of selecting different numbers of features and SML algorithms on the stability and predictive performance of the model for predicting ecological conditions in multiple seasons using taxonomy-free eDNA metabarcoding data. We discovered that even with a small number of features, different SML algorithms can establish a stable model and obtain excellent predictive performance. Finally, we proposed a four-step strategy for standardized routine biomonitoring using SML tools. Our study firstly explores the general applicability problem of the taxonomy-free eDNA-SML approach and establishes a solid foundation for the large-scale and standardized biomonitoring application.

Assessing arthropod diversity metrics derived from stream environmental DNA: spatiotemporal variation and paired comparisons with manual sampling

Background

Benthic invertebrate (BI) surveys have been widely used to characterize freshwater environmental quality but can be challenging to implement at desired spatial scales and frequency. Environmental DNA (eDNA) allows an alternative BI survey approach, one that can potentially be implemented more rapidly and cheaply than traditional methods.

Methods

We evaluated eDNA analogs of BI metrics in the Potomac River watershed of the eastern United States. We first compared arthropod diversity detected with primers targeting mitochondrial 16S (mt16S) and cytochrome c oxidase 1 (cox1 or COI) loci to that detected by manual surveys conducted in parallel. We then evaluated spatial and temporal variation in arthropod diversity metrics with repeated sampling in three focal parks. We also investigated technical factors such as filter type used to capture eDNA and PCR inhibition treatment.

Results

Our results indicate that genus-level assessment of eDNA compositions is achievable at both loci with modest technical noise, although database gaps remain substantial at mt16S for regional taxa. While the specific taxa identified by eDNA did not strongly overlap with paired manual surveys, some metrics derived from eDNA compositions were rank-correlated with previously derived biological indices of environmental quality. Repeated sampling revealed statistical differences between high- and low-quality sites based on taxonomic diversity, functional diversity, and tolerance scores weighted by taxon proportions in transformed counts. We conclude that eDNA compositions are efficient and informative of stream condition. Further development and validation of scoring schemes analogous to commonly used biological indices should allow increased application of the approach to management needs.

Metagenomic mapping of cyanobacteria and potential cyanotoxin producing taxa in large rivers of the United States

Cyanobacteria and cyanotoxin producing cyanobacterial blooms are a trending focus of current research. Many studies focus on bloom events in lentic environments such as lakes or ponds. Comparatively few studies have explored lotic environments and fewer still have examined the cyanobacterial communities and potential cyanotoxin producers during ambient, non-bloom conditions. Here we used a metagenomics-based approach to profile non-bloom microbial communities and cyanobacteria in 12 major U.S. rivers at multiple time points during the summer months of 2019. Our data show that U.S. rivers possess microbial communities that are taxonomically rich, yet largely consistent across geographic location and time. Within these communities, cyanobacteria often comprise significant portions and frequently include multiple species with known cyanotoxin producing strains. We further characterized these potential cyanotoxin producing taxa by deep sequencing amplicons of the microcystin E (mcyE) gene. We found that rivers containing the highest levels of potential cyanotoxin producing cyanobacteria consistently possess taxa with the genetic potential for cyanotoxin production and that, among these taxa, the predominant genus of origin for the mcyE gene is Microcystis. Combined, these data provide a unique perspective on cyanobacteria and potential cyanotoxin producing taxa that exist in large rivers across the U.S. and can be used to better understand the ambient conditions that may precede bloom events in lotic freshwater ecosystems.

Prophylactic Addition of Glucose Suppresses Cyanobacterial Abundance in Lake Water

To mitigate harmful cyanobacterial blooms (HCBs), toxic algicides have been used, but alternative methods of HCB prevention are needed. Our goal was to test the prophylactic addition of glucose to inhibit HCB development, using Microcystis and the toxin microcystin as the HCB model. Water samples were collected weekly, from 4 June to 2 July, from Harsha Lake in southwestern Ohio during the 2021 algal bloom season. From each weekly sample, a 25 mL aliquot was frozen for a 16S rRNA gene sequencing analysis. Then, 200 mL of Harsha Lake water was added to each of the three culture flasks, and glucose was added to create concentrations of 0 mM (control), 1.39 mM, or 13.9 mM glucose, respectively. The microcystin concentration in each flask was measured after 1 and 2 weeks of incubation. The results showed an 80 to 90% reduction in microcystin concentrations in glucose-treated water compared to the control. At the end of the second week of incubation, a 25 mL sample was also obtained from each of the culture flasks for molecular analysis, including a 16S rRNA gene sequencing and qPCR-based quantification of Microcystis target genes. Based on these analyses, the glucose-treated water contained significantly lower Microcystis and microcystin producing gene (mcy) copy numbers than the control. The 16S rRNA sequencing analysis also revealed that Cyanobacteria and Proteobacteria were initially the most abundant bacterial phyla in the Harsha Lake water, but as the summer progressed, Cyanobacteria became the dominant phyla. However, in the glucose-treated water, the Cyanobacteria decreased and the Proteobacteria increased in weekly abundance compared to the control. This glucose-induced proteobacterial increase in abundance was driven primarily by increases in two distinct families of Proteobacteria: Devosiaceae and Rhizobiaceae. In conclusion, the prophylactic addition of glucose to Harsha Lake water samples reduced Cyanobacteria’s relative abundance, Microcystis numbers and microcystin concentrations and increased the relative abundance of Proteobacteria compared to the control.

Monitoring newt communities in urban area using eDNA metabarcoding

Newts are amphibians commonly present in small ponds or garden pools in urban areas. They are protected in many countries and their presence is monitored through visual observation and/or trapping. However, newts are not easy to spot as they are small, elusive and often hidden at the bottom of water bodies. In recent years, environmental DNA (eDNA) has become a popular tool for detecting newts, with a focus on individual species using qPCR assays. Here, we assess the effectiveness of eDNA metabarcoding compared to conventional visual surveys of newt diversity in 45 ponds within urban areas of Geneva canton, Switzerland. We designed newt-specific mitochondrial 16S rRNA primers, which assign the majority of amplicons to newts, and were able to detect four species known to be present in the region, including the invasive subspecies Lissotriton vulgaris meridionalis, native to the Italian peninsula, that has been introduced in the Geneva area recently. The obtained eDNA results were congruent overall with conventional surveys, confirming the morphological observations in the majority of cases (67%). In 25% of cases, a species was only detected genetically, while in 8% of cases, the observations were not supported by eDNA metabarcoding. Our study confirms the usefulness of eDNA metabarcoding as a tool for the effective and non-invasive monitoring of newt community and suggests its broader use for the survey of newt diversity in urban area at larger scales.

eDNA metabarcoding revealed differential structures of aquatic communities in a dynamic freshwater ecosystem shaped by habitat heterogeneity

Freshwater ecosystems have been threatened by complicated disturbances from both natural and anthropogenic variables, especially in dynamic and complex river basins. The environmental DNA (eDNA)-based approach provides a broader spectrum and higher throughput way of biomonitoring for biodiversity assessment compared with traditional morphological survey. Most eDNA metabarcoding studies have been limited to a few specific taxa/groups and habitat scopes. Here we applied the eDNA metabarcoding to characterize the structures and spatial variations of zooplankton and fish communities among different habitat types in a highly dynamic and complex freshwater ecosystem of the Daqing River basin (DRB). The results showed that varied species spectra of zooplankton and fish communities were identified and unique dominant species occurred across habitats. Additionally, markedly spatial distributions of biotic community structures were observed in areas with different habitat characteristics. Natural variables, including geographic distances and gradient ratio, as well as anthropogenic factors of chemical oxygen demand (COD) and organic chemicals demonstrated significant effects but different outcomes on the structures of zooplankton and fish communities. Moreover, the relative abundances of specific aquatic taxa were associated with the gradient of particular environmental variables. This case study verified the distribution patterns and differentiation mechanisms of biotic communities under habitat heterogeneity could be captured by application of eDNA biomonitoring. And habitat-specific and even species-specific environmental stressors would be diagnosed for improving management of complex river basins.

Ecosystems monitoring powered by environmental genomics: A review of current strategies with an implementation roadmap

A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or "in development", hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics-based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (a) Taxonomy-based analyses focused on identification of known bioindicators or described taxa; (b) De novo bioindicator analyses; (c) Structural community metrics including inferred ecological networks; and (d) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programmes that leverage recent analytical advancements, while pointing out current limitations and future research needs.

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.

Can metabarcoding resolve intraspecific genetic diversity changes to environmental stressors? A test case using river macrozoobenthos

Genetic diversity is the most basal level of biodiversity and determines the evolutionary capacity of species to adapt to changing environments, yet it is typically neglected in routine biomonitoring and stressor impact assessment. For a comprehensive analysis of stressor impacts on genetic diversity, it is necessary to assess genetic variants simultaneously in many individuals and species. Such an assessment is not as straightforward and usually limited to one or few focal species. However, nowadays species diversity can be assessed by analysing thousands of individuals of a community simultaneously with DNA metabarcoding. Recent bioinformatic advances also allow for the extraction of exact sequence variants (ESVs or haplotypes) in addition to Operational Taxonomic Units (OTUs). By using this new capability, we here evaluated if the analysis of intraspecific mitochondrial diversity in addition to species diversity can provide insights into responses of stream macrozoobenthic communities to environmental stressors. For this purpose, we analysed macroinvertebrate bulk samples of three German river systems with different stressor levels using DNA metabarcoding. While OTU and haplotype number were negatively correlated with stressor impact, this association was not as clear when studying haplotype diversity across all taxa. However, stressor responses were found for sensitive EPT (Ephemeroptera, Plecoptera, Trichoptera) taxa and those exceedingly resistant to organic stress. An increase in haplotype number per OTU and haplotype diversity of sensitive taxa was observed with an increase in ecosystem quality and stability, while the opposite pattern was detected for pollution resistant taxa. However, this pattern was less prominent than expected based on the strong differences in stressor intensity between sites. To compare genetic diversity among communities in river systems, we focussed on OTUs, which were present in all systems. As OTU composition differed strongly between rivers, this led to the exclusion of a high number of OTUs, especially in diverse river systems of good quality, which potentially diminished the increase in intraspecific diversity. To better understand responses of intraspecific genetic diversity to environmental stressors, for example in river ecosystems, it would be important to increase OTU overlap between compared sites, e.g. by sampling a narrower stressor gradient, and to perform calibrated studies controlling for the number of individuals and their haplotypes. However, this pioneer study shows that the extraction of haplotypes from DNA metabarcoding datasets is a promising source of information to simultaneously assess intraspecific diversity changes in response to environmental impacts for a metacommunity.