Using DNA metabarcoding to characterize national scale diatom-environment relationships and to develop indicators in streams and rivers of the United States

Recent advancements in DNA techniques, metabarcoding, and bioinformatics could help expand the use of benthic diatoms in monitoring and assessment programs by providing relatively quick and increasingly cost-effective ways to quantify diatom diversity in environmental samples. However, such applications of DNA-based approaches are relatively new, and in the United States, unknowns regarding their applications at large scales exist because only a few small-scale studies have been done. Here, we present results from the first nationwide survey to use DNA metabarcoding (rbcL) of benthic diatoms, which were collected from 1788 streams and rivers across nine ecoregions spanning the conterminous USA. At the national scale, we found that diatom assemblage structure (1) was strongly associated with total phosphorus and total nitrogen concentrations, conductivity, and pH and (2) had clear patterns that corresponded with differences in these variables among the nine ecoregions. These four variables were strong predictors of diatom assemblage structure in ecoregion-specific analyses, but our results also showed that diatom-environment relationships, the importance of environmental variables, and the ranges of these variables within which assemblage changes occurred differed among ecoregions. To further examine how assemblage data could be used for biomonitoring purposes, we used indicator species analysis to identify ecoregion-specific taxa that decreased or increased along each environmental gradient, and we used their relative abundances of gene reads in samples as metrics. These metrics were strongly correlated with their corresponding variable of interest (e.g., low phosphorus diatoms with total phosphorus concentrations), and generalized additive models showed how their relationships compared among ecoregions. These large-scale national patterns and nine sets of ecoregional results demonstrated that diatom DNA metabarcoding is a robust approach that could be useful to monitoring and assessment programs spanning the variety of conditions that exist throughout the conterminous United States.

The voice of the little giants: Arcellinida testate amoebae in environmental DNA-based bioindication, from taxonomy free to haplotypic level

Bioindication, evaluating biological responses to environmental disturbances, is crucial for assessing the ecological status of an ecosystem. While historical bioindication relied on macroscopic organisms, the introduction of environmental DNA (eDNA) techniques allows the application of protists without the necessity of morphological identification. In this study, we propose a novel bioindication methodology utilizing Arcellinida, a group of top predators among protists, as bioindicators of freshwater ecosystems. For that purpose, we first characterized the Arcellinida diversity over 1 year at three different points of Lake Sanabria, an ancient glacier lake known to be subjected to anthropogenic disturbances. We compared this diversity with an undisturbed control site. Second, we characterized the Arcellinida diversity in other ecosystems to generate the ecological background to test the connectivity between them. Results indicate limited connectivity between the different ecosystems and an edge effect between terrestrial and aquatic ecosystems. Disturbed freshwater ecosystems exhibited reduced Arcellinida diversity at both specific and infraspecific levels, providing valuable insight into recent disturbances. Arcellinida-based bioindication provides a sensitive, accurate and easy-to-interpret protocol for monitoring disturbances in freshwater ecosystems. It represents a valuable tool for environmental assessments and conservation strategies.

Comparison of Metabarcoding and Microscopy Methodologies to Analyze Diatom Communities in Five Estuaries Along the Southern Coast of the Korean Peninsula

The study of microalgal communities is critical for understanding aquatic ecosystems. These communities primarily comprise diatoms (Heterokontophyta), with two methods commonly used to study them: Microscopy and metabarcoding. However, these two methods often deliver different results; thus, their suitability for analyzing diatom communities is frequently debated and evaluated. This study used these two methods to analyze the diatom communities in identical water samples and compare the results. The taxonomy of the species constituting the diatom communities was confirmed, and both methods showed that species belonging to the orders Bacillariales and Naviculales (class Bacillariophyceae) are the most diverse. In the lower taxonomic levels (family, genus, and species), microscopy tended to show a bias toward detecting diatom species (Nitzschia frustulum, Nitzschia inconspicua, Nitzschia intermedia, Navicula gregaria, Navicula perminuta, Navicula recens, Navicula sp.) belonging to the Bacillariaceae and Naviculaceae families. The results of the two methods differed in identifying diatom species in the communities and analyzing their structural characteristics. These results are consistent with the fact that diatoms belonging to the genera Nitzschia and Navicula are abundant in the communities; furthermore, only the Illumina MiSeq data showed the abundance of the Melosira and Entomoneis genera. The results obtained from microscopy were superior to those of Illumina MiSeq regarding species-level identification. Based on the results obtained via microscopy and Illumina MiSeq, it was revealed that neither method is perfect and that each has clear strengths and weaknesses. Therefore, to analyze diatom communities effectively and accurately, these two methods should be combined.

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.

A taxonomy-free diatom eDNA-based technique for assessing lake trophic level using lake sediments

Anthropogenic eutrophication is one of the most pressing issues facing lakes globally. Our ability to manage lake eutrophication is hampered by the limited spatial and temporal extents of monitoring records, stemming from the time-consuming and expensive nature of physiochemical and biological monitoring. Diatom-based biomonitoring presents an alternative to traditional eutrophication monitoring, yet it is restricted by the high degree of taxonomic expertise required. Environmental DNA metabarcoding, while providing a promising substitute for diatom community enumeration, is plagued by inadequate taxonomic coverage of reference databases and methodological bias, limiting its use for biomonitoring. Here we show that taxonomy-free diatom-biomonitoring, in which environmental DNA metabarcoding data is utilised but not assigned to specific taxonomic classes, presents an accurate, fast, and relatively automated alternative to taxonomically assigned eutrophication biomonitoring. Our taxonomy-free index accounted for 85% of trophic level variability across 89 lakes and had the lowest average prediction error of the three approaches tested. By not relying on taxonomic identification or metabarcoding reference databases, taxonomy-free biomonitoring maintains diatom diversity that is lost in taxonomic assignment using molecular approaches. Furthermore, by utilising lake sediments, the approach outlined here presents a time-integrated estimation of lake trophic level and thus does not require time-consuming seasonal sampling. Taxonomy-free biomonitoring addresses the limitations of traditional physicochemical eutrophication monitoring and taxonomic biomonitoring alternatives and can be used to extend the spatial and temporal extents of eutrophication monitoring.

Unlocking secrets of microbial ecotoxicology: recent achievements and future challenges

Environmental pollution is one of the main challenges faced by humanity. By their ubiquity and vast range of metabolic capabilities, microorganisms are affected by pollution with consequences on their host organisms and on the functioning of their environment. They also play key roles in the fate of pollutants through the degradation, transformation, and transfer of organic or inorganic compounds. Thus, they are crucial for the development of nature-based solutions to reduce pollution and of bio-based solutions for environmental risk assessment of chemicals. At the intersection between microbial ecology, toxicology, and biogeochemistry, microbial ecotoxicology is a fast-expanding research area aiming to decipher the interactions between pollutants and microorganisms. This perspective paper gives an overview of the main research challenges identified by the Ecotoxicomic network within the emerging One Health framework and in the light of ongoing interest in biological approaches to environmental remediation and of the current state of the art in microbial ecology. We highlight prevailing knowledge gaps and pitfalls in exploring complex interactions among microorganisms and their environment in the context of chemical pollution and pinpoint areas of research where future efforts are needed.

A combination of machine-learning and eDNA reveals the genetic signature of environmental change at the landscape levels

The current advances of environmental DNA (eDNA) bring profound changes to ecological monitoring and provide unique insights on the biological diversity of ecosystems. The very nature of eDNA data is challenging yet also revolutionizing how biological monitoring information is analysed. In particular, new metrics and approaches should take full advantage of the extent and detail of molecular data produced by genetic methods. In this perspective, machine learning algorithms are particularly promising as they can capture complex relationships between the multiple environmental pressures and the diversity of biological communities. We investigated the potential of a new generation of biomonitoring tools that implement machine-learning techniques to fully exploit eDNA datasets. We trained a machine learning model to discriminate between reference and impacted communities of freshwater macroinvertebrates and assessed its performances using a large eDNA dataset collected at 64 standard federal monitoring sites across Switzerland. We show that a model trained on eDNA is significantly better than a naive model and performs similarly to a model trained on traditional data. Our proof-of-concept shows that such a combination of eDNA and machine learning approaches has the potential to complement or even replace traditional environmental monitoring, and could be scaled along temporal or spatial dimensions.

Climate Change Causes Salinity To Become Determinant in Shaping the Microeukaryotic Spatial Distribution among the Lakes of the Inner Mongolia-Xinjiang Plateau

Climate change greatly affects lake microorganisms in arid and semiarid zones, which alters ecosystem functions and the ecological security of lakes. However, the responses of lake microorganisms, especially microeukaryotes, to climate change are poorly understood. Here, using 18S ribosomal RNA (rRNA) high-throughput sequencing, we investigated the distribution patterns of microeukaryotic communities and whether and how climate change directly or indirectly affected the microeukaryotic communities on the Inner Mongolia-Xinjiang Plateau. Our results showed that climate change, as the main driving force of lake change, drives salinity to become a determinant of the microeukaryotic community among the lakes of the Inner Mongolia-Xinjiang Plateau. Salinity shapes the diversity and trophic level of the microeukaryotic community and further affects lake carbon cycling. Co-occurrence network analysis further revealed that increasing salinity reduced the complexity but improved the stability of microeukaryotic communities and changed ecological relationships. Meanwhile, increasing salinity enhanced the importance of deterministic processes in microeukaryotic community assembly, and the dominance of stochastic processes in freshwater lakes transformed into deterministic processes in salt lakes. Furthermore, we established lake biomonitoring and climate sentinel models by integrating microeukaryotic information, which would provide substantial improvements to our predictive ability of lake responses to climate change. IMPORTANCE Our findings have important implications for understanding the distribution patterns and the driving mechanisms of microeukaryotic communities among the lakes of the Inner Mongolia-Xinjiang Plateau and whether and how climate change directly or indirectly affects microeukaryotic communities. Our study also establishes the groundwork to use the lake microbiome for the assessment of aquatic ecological health and climate change, which is critical for ecosystem management and for projecting the ecological consequences of future climate warming.

Characterization of the Rhizosphere Bacterial Microbiome and Coffee Bean Fermentation in the Castillo-Tambo and Bourbon Varieties in the Popayán-Colombia Plateau

BACKGROUND

The microbial biodiversity and the role of microorganisms in the fermentation of washed coffee in Colombia were investigated using the Bourbon and Castillo coffee varieties. DNA sequencing was used to evaluate the soil microbial biota and their contribution to fermentation. The potential benefits of these microorganisms were analyzed, including increased productivity and the need to understand the rhizospheric bacterial species to optimize these benefits.

METHODS

This study used coffee beans for DNA extraction and 16 S rRNA sequencing. The beans were pulped, samples were stored at 4ºC, and the fermentation process was at 19.5ºC and 24ºC. The fermented mucilage and root-soil samples were collected in duplicate at 0, 12, and 24 h. DNA was extracted from the samples at a concentration of 20 ng/µl per sample, and the data obtained were analyzed using the Mothur platform.

RESULTS

The study demonstrates that the coffee rhizosphere is a diverse ecosystem composed primarily of microorganisms that cannot be cultured in the laboratory. This suggests that the microbial community may vary depending on the coffee variety and play an essential role in fermentation and overall coffee quality.

CONCLUSIONS

The study highlights the importance of understanding and optimizing the microbial diversity in coffee production, which could have implications for the sustainability and success of coffee production. DNA sequencing techniques can help characterize the structure of the soil microbial biota and evaluate its contribution to coffee fermentation. Finally, further research is needed to fully understand the biodiversity of coffee rhizospheric bacteria and their role.

Environmental DNA metabarcoding reveals the impact of different land use on multitrophic biodiversity in riverine systems

Human-induced changes in land use drive an alarming decline in river biodiversity and related ecosystem services worldwide. However, how different land use shapes aquatic multitrophic communities is still not well understood. Here, we used the biodiversity dataset from bacteria to fish captured by the environmental DNA (eDNA) approach in the four riverine systems with spatially different land use (i.e., Slightly disturbed group, Upstream disturbed group, Downstream disturbed group, and Strongly disturbed group) to reveal the changes in multitrophic biodiversity in relation to human land use. Firstly, our data showed that spatially different land use determined the pollutant loads of the riverine systems, most pollutants (e.g., TN and NH₃-N) had significant differences among the four riverine systems. Secondly, taxonomic α diversity across multitrophic levels did not necessarily change significantly, yet the change in community structure can be considered as a more sensitive indicator to reflect different land use, because different land use shaped the unique structure of multitrophic communities, and the dissimilarity of community structure was closely associated with land use gradient (e.g., positive relationships in the Slightly disturbed group, negative relationships in the Strongly disturbed group). Thirdly, different land use induced the shifts of key taxa, resulting in the variation of community structure and the change of co-occurrence network. Overall, these findings suggest that spatially different land use plays a critical role in shaping aquatic multitrophic communities, and an in-depth understanding of the interdependences between biodiversity and land use is a critical prerequisite for formulating river management strategies.

Environmental filtering and mass effect are two important processes driving lake benthic diatoms: Results of a DNA metabarcoding study in a large lake

Environmental filtering is often found to dominate assembly rules in diatoms. These microalgae are diverse, especially at subspecies level, and tend to exhibit a niche phylogenetic conservatism. Therefore, other rules, such as competition or mass effects, should be detectable when environmental gradients and dispersal barriers are limited. We used metabarcoding to analyse benthic littoral diatom communities in 153 sites in a large lake (Geneva) exhibiting weak geographical barriers and weak environmental gradients outside river estuaries. We assessed assembly rules using variance partitioning, phylogenetic and source tracking analyses. No phylogenetic over-dispersion of communities, indicative of exclusive competition, was detected. Instead, we found these communities to be phylogenetically over-clustered, indicating environmental filtering, which was even stronger near river estuaries where environmental gradients are stronger. Finally, using a Bayesian method (SourceTracker), we found that rivers flowing into the lake bring communities that settle, especially in sites close to estuaries. Rivers with the highest discharges are primarily responsible for immigration, explaining 27% of lake composition. Therefore, despite favourable conditions to observe other rules, our results support that diatom communities are prominently assembled by environmental filtering and immigration processes, in particular from rivers. However, this does not exclude that other assembly rules may be at play at a finer spatial, temporal and/or phylogenetic scale.

Methodological 'lenses' influence the characterization of phytoplankton dynamics in a coastal upwelling ecosystem

New technologies enable the opportunity to improve our monitoring and understanding of marine phytoplankton communities. However, careful consideration for how different methodological approaches, or 'lenses', influence our interpretation of phytoplankton ecology is important, particularly when drawing conclusions about change over time or space. Using both high-throughput 18S rRNA gene sequencing and microscopy, we explored how phytoplankton community structure varied over the course of a year within a nearshore semi-enclosed coastal embayment along the Central Coast of California. The seasonal shift in the relative community dominance (i.e., diatom vs. dinoflagellate dominance) was captured in the microscopy results but not effectively captured in the molecular-based findings. However, the molecular approach explained more of the variability in composition across seasons relative to the microscopy approach. Temporal dynamics of specific bloom-forming taxa also differed between the molecular and microscopy results. Overall, the observed differences between the molecular- and microscopy-derived characterization of phytoplankton dynamics suggest that the approaches are best suited to answer different research questions. Moreover, the approaches complement each other for a more comprehensive perspective of a coastal phytoplankton ecosystem. Therefore, identifying the biases of each approach within natural communities is necessary to effectively and accurately characterize phytoplankton communities.

Recommendations for the preservation of environmental samples in diatom metabarcoding studies

Implementation of DNA metabarcoding for diatoms for environmental monitoring is now moving from a research to an operational phase, requiring rigorous guidelines and standards. In particular, the first steps of the diatom metabarcoding process, which consist of sampling and storage, have been addressed in various ways in scientific and pilot studies and now need to be rationalised. The objective of this study was to compare three currently applied preservation protocols through different storage durations (ranging from one day to one year) for phytobenthos and phytoplankton samples intended for diatom DNA metabarcoding analysis. The experimental design used samples from four freshwater and two marine sites of diverse ecological characteristics. The impact of the sample preservation and storage duration was assessed through diatom metabarcoding endpoints: DNA quality and quantity, diversity and richness, diatom assemblage composition and ecological index values (for freshwater samples). The yield and quality of extracted DNA only decreased for freshwater phytobenthos samples preserved with ethanol. Diatom diversity was not affected and their taxonomic composition predominantly reflected the site origin. Only rare taxa (< 100 reads) differed among preservation methods and storage durations. For biomonitoring purposes, freshwater ecological index values were not affected by the preservation method and storage duration tested (including ethanol preservation), all treatments returning the same ecological status for a site. This study contributes to consolidating diatom metabarcoding. Thus, accompanied by operational standards, the method will be ready to be confidently deployed and prescribed in future regulatory monitoring.

Evaluation of two short overlapping rbcL markers for diatom metabarcoding of environmental samples: Effects on biomonitoring assessment and species resolution

Two short diatom rbcL barcodes, 331 bp and 263 bp in length, have frequently been used in diatom metabarcoding studies. They overlap in a common 263-bp region but differ in the presence or absence of a 68-bp tail at the 5' end. Though the effectiveness of both has been demonstrated in separate biomonitoring and diversity studies, the impact of the 68-bp non-shared region has not been evaluated. Here we compare the two barcodes in terms of the values of a biotic index (IPS) and the ecological status classes derived from their application to an extensive metabarcoding dataset from United Kingdom rivers; this comprised 1703 samples and was produced using the 331-bp primers. In addition, we assess the effectiveness of each barcode for discrimination of genetic variants around and below the species level. The strong correlation found in IPS values between barcodes (Pearson's R = 0.98) indicates that the choice of the barcode does not have major implications for current WFD ecological assessments, although a very few sites (55: 3.23% of those analysed) were downgraded from an acceptable WFD class ("Good") to an unacceptable one ("Moderate"). Analyses of the taxonomic resolution of the two barcodes indicate that for many ASVs, the use of either marker - 263-bp and 331-bp - gives unambiguous assignations at species level though with differences in bootstrap confidence values. Such differences are caused by the stochasticity involved in the naïve Bayesian classifier used and by the fact that genetic distance, regarding closely related species, is increased when using the 331-bp barcode. However, in three cases, species differentiation fails with the shorter marker, leading to underestimates of species diversity. Finally, two ASVs from Nitzschia species evidenced that the use of the shorter marker can sometimes lead to false positives when the extent and nature of infraspecific variation are poorly known.

Diatoms as indicators in running waters: trends of studies on biological assessment and monitoring

Despite the biodiversity and ecosystem services provided by lotic ecosystems, they are strongly affected by anthropogenic activities. Therefore, biological monitoring and assessment strategies are crucial in helping maintain these ecosystems and developing mitigation policies. We provide a global overview of the use of benthic diatoms as bioindicators in lotic environments, by analyzing 764 articles published in the past 20 years. We analyzed the influence of substrate type on samplings, which species have been highlighted as indicators and for which type of impacts, which anthropogenic impacts have been most commonly evaluated, and which metrics have been commonly used in studies using diatoms to assess and monitor the quality of lotic environments. We found that the most studied anthropogenic impact is artificial eutrophication and that some species, especially Nitzschia palea, have been thoroughly mentioned as indicators of this impact. Indicator species related to other types of impact are less common, demonstrating the need for studies on this issue. Moreover, we verified that traditional taxonomic metrics, such as diversity and diatom indices, have been widely used. Some alternative metrics have been used recently, such as those based on teratological valves, lipid bodies, valve size, and DNA metabarcoding. The number of biomonitoring and assessment studies based on diatoms has increased considerably in the past 20 years. Nonetheless, the demand for natural resources and consequently the degradation of lotic ecosystems have accelerated significantly. Thus, the development of low-cost and time-efficient biological assessment and monitoring strategies is essential for evaluating the health of lotic environments.

Quantifying spatial and temporal relationships between diatoms and nutrients in streams strengthens evidence of nutrient effects from monitoring data

Observational data are frequently used to better understand the effects of changes in P and N on stream biota, but nutrient gradients in streams are usually associated with gradients in other environmental factors, a phenomenon that complicates efforts to accurately estimate the effects of nutrients. Here, we propose a new approach for analyzing observational data in which we compare the effects of changes in nutrient concentrations in time within individual sites and in space among many sites. Covarying relationships between other, potentially confounding environmental factors and nutrient concentrations are unlikely to be the same in both time and space, and, therefore, estimated effects of nutrients that are similar in time and space are more likely to be accurate. We applied this approach to diatom rbcL metabarcoding data collected from streams in the East Fork of the Little Miami River watershed, Ohio, USA. Changes in diatom assemblage composition were consistently associated with changes in the concentration of total reactive P in both time and space. In contrast, despite being associated with spatial differences in ammonia and urea concentrations, diatom assemblage composition was not associated with temporal changes in these nitrogen species. We suggest that the results of this analysis provide evidence of a causal effect of increased P on diatom assemblage composition. We further analyzed the effects of temporal variability in measurements of total reactive P and found that averaging periods greater than ~1 wk prior to sampling best represented the effects of P on the diatom assemblage. Comparisons of biological responses in space and time can sharpen insights beyond those that are based on analyses conducted on only 1 of the 2 dimensions.

Comparing microscopy and DNA metabarcoding techniques for identifying cyanobacteria assemblages across hundreds of lakes

Accurately identifying the species present in an ecosystem is vital to lake managers and successful bioassessment programs. This is particularly important when monitoring cyanobacteria, as numerous taxa produce toxins and can have major negative impacts on aquatic ecosystems. Increasingly, DNA-based techniques such as metabarcoding are being used for measuring aquatic biodiversity, as they could accelerate processing time, decrease costs and reduce some of the biases associated with traditional light microscopy. Despite the continuing use of traditional microscopy and the growing use of DNA metabarcoding to identify cyanobacteria assemblages, methodological comparisons between the two approaches have rarely been reported from a wide suite of lake types. Here, we compare planktonic cyanobacteria assemblages generated by inverted light microscopy and DNA metabarcoding from a 379-lake dataset spanning a longitudinal and trophic gradient. We found moderate levels of congruence between methods at the broadest taxonomic levels (i.e., Order, RV=0.40, p < 0.0001). This comparison revealed distinct cyanobacteria communities from lakes of different trophic states, with Microcystis, Aphanizomenon and Dolichospermum dominating with both methods in eutrophic and hypereutrophic sites. This finding supports the use of either method when monitoring eutrophication in lake surface waters. The biggest difference between the two methods was the detection of picocyanobacteria, which are typically underestimated by light microscopy. This reveals that the communities generated by each method currently are complementary as opposed to identical and promotes a combined-method strategy when monitoring a range of trophic systems. For example, microscopy can provide measures of cyanobacteria biomass, which are critical data in managing lakes. Going forward, we believe that molecular genetic methods will be increasingly adopted as reference databases are routinely updated with more representative sequences and will improve as cyanobacteria taxonomy is resolved with the increase in available genetic information.

Consideration of Multitrophic Biodiversity and Ecosystem Functions Improves Indices on River Ecological Status

Biological quality elements have been developed worldwide to assess whether a water body is in a good status or not. However, current studies mainly focus on a single taxonomic group or a small set of species, often limited by methods of morphological identification, and lack further aspects of biodiversity (e.g., across taxa and multiple attributes) and ecosystem functions. Here, we advance a framework for assessing the river's ecological status based on complete biodiversity data measured by environmental DNA (eDNA) metabarcoding and measurements of ecosystem functions in addition to physicochemical elements across a large riverine system in China. We identified 40 indicators of biodiversity and ecosystem functions, covering five taxonomic groups from bacteria to invertebrates, and associated with multiple attributes of biodiversity and ecosystem functions. Our data show that human impact on ecosystems could be accurately predicted by these eDNA-based indicators and ecosystem functions, using cross-validation with a known stressor gradient. Moreover, indices based on these indicators of biodiversity and ecosystem functions not only distinguish the physicochemical characteristics of the sites but also improve the assessment accuracy of 20-30% for the river's ecological status. Overall, by incorporating eDNA-based biodiversity with physicochemical and ecosystem functional elements, the multidimensional perspectives of ecosystem states provide additional information to protect and maintain a good ecological status of rivers.

Finding needles in a haystack-Extensive diversity in the eustigmatophyceae revealed by community metabarcode analysis targeting the rbcL gene using lineage-directed primers

Sequences from the Stramenopile class Eustigmatophyceae are rarely reported in metabarcoding studies, and when they have been reported, there are very few haplotypes. We hypothesized that the paucity of eustigmatophyte species detected in these studies may be a result of the metabarcoding techniques used, which have primarily employed universal ribosomal RNA gene regions. In this study, we examined environmental DNA samples from 22 sites in southwestern Virginia, some of which had previously been studied using ribosomal RNA analysis. We used metabarcoding techniques targeting the plastid rbcL gene with new primers designed to produce a 370 bp amplicon from all lineages of the Eustigmatophyceae in a reference collection. The amplicons were then analyzed with DADA2 to produce amplicon sequence variants (ASVs). Our results revealed 184 rbcL haplotypes that can be tentatively assigned to the Eustigmatophyceae from these sites, representing much higher diversity than has been detected by ribosomal DNA-based studies. The techniques employed can be used for future studies of population structure, ecology, distribution, and diversity of this class. With these techniques, it should be possible to make realistic estimates of the species-level diversity of the Eustigmatophyceae on local, regional, and perhaps global scales.

Epiphytic Diatom-Based Biomonitoring in Mediterranean Ponds: Traditional Microscopy versus Metabarcoding Approaches

Benthic diatoms have traditionally been used as bioindicators of aquatic ecosystems. Because diatom-based monitoring of water quality is required by European legislation, molecular-based methods had emerged as useful alternatives to classical methods based on morphological identification using light microscopy. The aim of this study was to test the reliability of DNA metabarcoding combined with High-Throughput Sequencing (HTS) techniques in the bioassessment of the trophic status of 22 Mediterranean shallow ponds in NW Spain. For each pond, the Trophic Diatom Index (TDI) was calculated from inventories obtained by identification using light microscopy (LM) followed by high-throughput sequencing (HTS) at the molecular level. Ponds were subsequently classified into five water quality classes. The results showed a good correspondence between both methods, especially after applying a correction factor that depended on the biovolume of the cells. This correspondence led to the assignment to the same quality class in 59% of the ponds. The determination and quantification of valves or DNA sequences was one of the main pitfalls, which mainly included those related to the variability in the relative abundances of some species. Accordingly, ponds with similar relative abundances for the dominant species were assigned to the same quality class. Moreover, other difficulties leading the discrepancies were the misidentification of some species due to the presence of semi-cryptic taxa, the incompleteness of the reference database and the bioinformatic protocol. Thus, the validation of DNA-based methods for the identification of freshwater diatoms represents an important goal, as an alternative to using traditional methods in Mediterranean shallow ponds.

To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography

BACKGROUND

The recent blooming of metabarcoding applications to biodiversity studies comes with some relevant methodological debates. One such issue concerns the treatment of reads by denoising or by clustering methods, which have been wrongly presented as alternatives. It has also been suggested that denoised sequence variants should replace clusters as the basic unit of metabarcoding analyses, missing the fact that sequence clusters are a proxy for species-level entities, the basic unit in biodiversity studies. We argue here that methods developed and tested for ribosomal markers have been uncritically applied to highly variable markers such as cytochrome oxidase I (COI) without conceptual or operational (e.g., parameter setting) adjustment. COI has a naturally high intraspecies variability that should be assessed and reported, as it is a source of highly valuable information. We contend that denoising and clustering are not alternatives. Rather, they are complementary and both should be used together in COI metabarcoding pipelines.

RESULTS

Using a COI dataset from benthic marine communities, we compared two denoising procedures (based on the UNOISE3 and the DADA2 algorithms), set suitable parameters for denoising and clustering, and applied these steps in different orders. Our results indicated that the UNOISE3 algorithm preserved a higher intra-cluster variability. We introduce the program DnoisE to implement the UNOISE3 algorithm taking into account the natural variability (measured as entropy) of each codon position in protein-coding genes.  This correction increased the number of sequences retained by 88%. The order of the steps (denoising and clustering) had little influence on the final outcome.

CONCLUSIONS

We highlight the need for combining denoising and clustering, with adequate choice of stringency parameters, in COI metabarcoding. We present a program that uses the coding properties of this marker to improve the denoising step. We recommend researchers to report their results in terms of both denoised sequences (a proxy for haplotypes) and clusters formed (a proxy for species), and to avoid collapsing the sequences of the latter into a single representative. This will allow studies at the cluster (ideally equating species-level diversity) and at the intra-cluster level, and will ease additivity and comparability between studies.

Exploring the capacity of aquatic biofilms to act as environmental DNA samplers: Test on macroinvertebrate communities in rivers

Aquatic biofilms are heterogeneous assemblages of microorganisms surrounded by a matrix of extracellular polymeric substances (EPS). Recent studies suggest that aquatic biofilms can physically act as sorptive sponges of DNA. We took the opportunity from already available samples of stone biofilms and macroinvertebrates specimens collected in parallel at the same sites to test the capacity of biofilms to act as DNA samplers of macroinvertebrate communities in streams. Macroinvertebrate communities are usually studied with metabarcoding using the DNA extracted from their bodies bulk samples, which remains a time-consuming approach and involves the destruction of all individual specimens from the samples. The ability of biofilms to capture DNA was explored on 19 rivers sites of a tropical island (Mayotte Island, France). First, macroinvertebrate specimens were identified based on their morphological characteristics. Second, DNA was extracted from biofilms, and macroinvertebrate communities were targeted using a standard COI barcode. The resulting morphological and molecular inventories were compared. They provided comparable structures and diversities for macroinvertebrate communities when one is working with the unassigned OTU data. After taxonomic assignment of the OTU data, diversity and richness were no longer correlated. The ecological assessment derived from morphological bulk samples was conserved by the biofilms samples. We also showed that the biofilm method allows to detect a higher diversity for some organisms (Cnidaria), that is hardly accessible with the morphological method. The results of this study exploring the DNA signal captured by natural biofilms are encouraging. However, a more detailed study integrating more replicates and comparing the biodiversity signal based on both morphological and molecular bulk macroinvertebrate samples to the one captured by biofilms will be necessary. Better understanding how the DNA signal captured by natural biofilms represents the biodiversity of a given sampling site is necessary before considering its use for bioassessment applications.

Expanding ecological assessment by integrating microorganisms into routine freshwater biomonitoring

Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems.

Benthic Diatoms in River Biomonitoring—Present and Future Perspectives within the Water Framework Directive

The European Water Framework Directive 2000/60/EC (WFD) has been implemented over the past 20 years, using physicochemical, biological and hydromorphological elements to assess the ecological status of surface waters. Benthic diatoms (i.e., phytobenthos) are one of the most common biological quality elements (BQEs) used in surface water monitoring and are particularly successful in detecting eutrophication, organic pollution and acidification. Herein, we reviewed their implementation in river biomonitoring for the purposes of the WFD, highlighting their advantages and disadvantages over other BQEs, and we discuss recent advances that could be applied in future biomonitoring. Until now, phytobenthos have been intercalibrated by the vast majority (26 out of 28) of EU Member States (MS) in 54% of the total water bodies assessed and was the most commonly used BQE after benthic invertebrates (85% of water bodies), followed by fish (53%), macrophytes (27%) and phytoplankton (4%). To meet the WFD demands, numerous taxonomy-based quality indices have been developed among MS, presenting, however, uncertainties possibly related to species biogeography. Recent development of different types of quality indices (trait-based, DNA sequencing and predictive modeling) could provide more accurate results in biomonitoring, but should be validated and intercalibrated among MS before their wide application in water quality assessments.

18S rRNA Analysis Reveals High Diversity of Phytoplankton with Emphasis on a Naked Dinoflagellate Gymnodinium sp. at the Han River (Korea)

Biomonitoring of phytoplankton communities in freshwater ecosystems is imperative for efficient water quality management. In the present study, we present the seasonal diversity of phytoplankton from the non-reservoir area of the Han River (Korea), assessed using the 18S rRNA amplicon sequencing. Our results uncovered a considerably high eukaryotic diversity, which was predominantly represented by phytoplankton in all the seasons (38–63%). Of these, the diatoms, Cyclostephanos tholiformis, Stephanodiscus hantzschii, and Stephanodiscus sp., were frequently detected in spring and winter. Interestingly, for the first time in the Han River, we detected a large number of operational taxonomic unit (OTU) reads belonging to the naked dinoflagellate Gymnodinium sp., which dominated in autumn (15.8%) and was observed only in that season. Molecular cloning and quantitative real-time polymerase chain reaction (PCR) confirmed the presence of Gymnodinium sp. in the samples collected in 2012 and 2019. Moreover, a comparison of the present data with our previous data from a reservoir area (Paldang Dam) revealed similar patterns of phytoplankton communities. This molecular approach revealed a prospective toxic species that was not detected through microscopy. Collectively, resolving phytoplankton communities at a level relevant for water quality management will provide a valuable reference for future studies on phytoplankton for environmental monitoring.

Diatom DNA metabarcoding for ecological assessment: Comparison among bioinformatics pipelines used in six European countries reveals the need for standardization

Ecological assessment of lakes and rivers using benthic diatom assemblages currently requires considerable taxonomic expertise to identify species using light microscopy. This traditional approach is also time-consuming. Diatom metabarcoding is a promising alternative and there is increasing interest in using this approach for routine assessment. However, until now, analysis protocols for diatom metabarcoding have been developed and optimised by research groups working in isolation. The diversity of existing bioinformatics methods highlights the need for an assessment of the performance and comparability of results of different methods. The aim of this study was to test the correspondence of outputs from six bioinformatics pipelines currently in use for diatom metabarcoding in different European countries. Raw sequence data from 29 biofilm samples were treated by each of the bioinformatics pipelines, five of them using the same curated reference database. The outputs of the pipelines were compared in terms of sequence unit assemblages, taxonomic assignment, biotic index score and ecological assessment outcomes. The three last components were also compared to outputs from traditional light microscopy, which is currently accepted for ecological assessment of phytobenthos, as required by the Water Framework Directive. We also tested the performance of the pipelines on the two DNA markers (rbcL and 18S-V4) that are currently used by the working groups participating in this study. The sequence unit assemblages produced by different pipelines showed significant differences in terms of assigned and unassigned read numbers and sequence unit numbers. When comparing the taxonomic assignments at genus and species level, correspondence of the taxonomic assemblages between pipelines was weak. Most discrepancies were linked to differential detection or quantification of taxa, despite the use of the same reference database. Subsequent calculation of biotic index scores also showed significant differences between approaches, which were reflected in the final ecological assessment. Use of the rbcL marker always resulted in better correlation among molecular datasets and also in results closer to these generated using traditional microscopy. This study shows that decisions made in pipeline design have implications for the dataset's structure and the taxonomic assemblage, which in turn may affect biotic index calculation and ecological assessment. There is a need to define best-practice bioinformatics parameters in order to ensure the best representation of diatom assemblages. Only the use of similar parameters will ensure the compatibility of data from different working groups. The future of diatom metabarcoding for ecological assessment may also lie in the development of new metrics using, for example, presence/absence instead of relative abundance data.

Translational Molecular Ecology in practice: Linking DNA-based methods to actionable marine environmental management

Molecular-based approaches can provide timely biodiversity assessments, showing an immense potential to facilitate decision-making in marine environmental management. However, the uptake of molecular data into environmental policy remains minimal. Here, we showcase a selection of local to global scale studies applying molecular-based methodologies for environmental management at various stages of implementation. Drawing upon lessons learned from these case-studies, we provide a roadmap to facilitate applications of DNA-based methods to marine policies and to overcome the existing challenges. The main impediment identified is the need for standardized protocols to guarantee data comparison across spatial and temporal scales. Adoption of Translational Molecular Ecology - the sustained collaboration between molecular ecologists and stakeholders, will enhance consensus with regards to the objectives, methods, and outcomes of environmental management projects. Establishing a sustained dialogue among stakeholders is key to accelerating the adoption of molecular-based approaches for marine monitoring and assessment.

Freshwater diatom biomonitoring through benthic kick-net metabarcoding

Biomonitoring is an essential tool for assessing ecological conditions and informing management strategies. The application of DNA metabarcoding and high throughput sequencing has improved data quantity and resolution for biomonitoring of taxa such as macroinvertebrates, yet, there remains the need to optimise these methods for other taxonomic groups. Diatoms have a longstanding history in freshwater biomonitoring as bioindicators of water quality status. However, multi-substrate periphyton collection, a common diatom sampling practice, is time-consuming and thus costly in terms of labour. This study examined whether the benthic kick-net technique used for macroinvertebrate biomonitoring could be applied to bulk-sample diatoms for metabarcoding. To test this approach, we collected samples using both conventional multi-substrate microhabitat periphyton collections and bulk-tissue kick-net methodologies in parallel from replicated sites with different habitat status (good/fair). We found there was no significant difference in community assemblages between conventional periphyton collection and kick-net methodologies or site status, but there was significant difference between diatom communities depending on site (P = 0.042). These results show the diatom taxonomic coverage achieved through DNA metabarcoding of kick-net is suitable for ecological biomonitoring applications. The shift to a more robust sampling approach and capturing diatoms as well as macroinvertebrates in a single sampling event has the potential to significantly improve efficiency of biomonitoring programmes that currently only use the kick-net technique to sample macroinvertebrates.

Monitoring the ecological status of rivers with diatom eDNA metabarcoding: A comparison of taxonomic markers and analytical approaches for the inference of a molecular diatom index

Recently, several studies demonstrated the usefulness of diatom eDNA metabarcoding as an alternative to assess the ecological quality of rivers and streams. However, the choice of the taxonomic marker as well as the methodology for data analysis differ between these studies, hampering the comparison of their results and effectiveness. The aim of this study was to compare two taxonomic markers commonly used in diatom metabarcoding and three distinct analytical approaches to infer a molecular diatom index. We used the values of classical morphological diatom index as a benchmark for this comparison. We amplified and sequenced both a fragment of the rbcL gene and the V4 region of the 18S rRNA gene for 112 epilithic samples from Swiss and French rivers. We inferred index values using three analytical approaches: by computing it directly from taxonomically assigned sequences, by calibrating de novo the ecovalues of all metabarcodes, and by using a supervised machine learning algorithm to train predictive models. In general, the values of index obtained using the two "taxonomy-free" approaches, encompassing molecular assignment and machine learning, were closer correlated to the values of the morphological index than the values based on taxonomically assigned sequences. The correlations of the three analytical approaches were higher in the case of rbcL compared to the 18S marker, highlighting the importance of the reference database which is more complete for the rbcL marker. Our study confirms the effectiveness of diatom metabarcoding as an operational tool for rivers ecological quality assessment and shows that the analytical approaches by-passing the taxonomic assignments are particularly efficient when reference databases are incomplete.

A taxonomy-free approach based on machine learning to assess the quality of rivers with diatoms

Diatoms are a compulsory biological quality element in the ecological assessment of rivers according to the Water Framework Directive. The application of current official indices requires the identification of individuals to species or lower rank under a microscope based on the valve morphology. This is a highly time-consuming task, often susceptible of disagreements among analysts. In alternative, the use of DNA metabarcoding combined with High-Throughput Sequencing (HTS) has been proposed. The sequences obtained from environmental DNA are clustered into Operational Taxonomic Units (OTUs), which can be assigned to a taxon using reference databases, and from there calculate biotic indices. However, there is still a high percentage of unassigned OTUs to species due to the incompleteness of reference libraries. Alternatively, we tested a new taxonomy-free approach based on diatom community samples to assess rivers. A combination of three machine learning techniques is used to build models that predict diatom OTUs expected in test sites, under reference conditions, from environmental data. The Observed/Expected OTUs ratio indicates the deviation from reference condition and is converted into a quality class. This approach was never used with diatoms neither with OTUs data. To evaluate its efficiency, we built a model based on OTUs lists (HYDGEN) and another based on taxa lists from morphological identification (HYDMORPH), and also calculated a biotic index (IPS). The models were trained and tested with data from 81 sites (44 reference sites) from central Portugal. Both models were considered accurate (linear regression for Observed and Expected richness: R² ≈ 0.7, interception ≈ 0.8) and sensitive to global anthropogenic disturbance (Rs² > 0.30 p < 0.006 for global disturbance). Yet, the HYDGEN model based on molecular data was sensitive to more types of pressures (such as, changes in land use and habitat quality), which gives promising insights to its use for bioassessment of rivers.

Assessing pollution of aquatic environments with diatoms’ DNA metabarcoding: experience and developments from France water framework directive networks

Ecological status assessment of watercourses is based on the calculation of quality indices using pollution sensitivity of targeted biological groups, including diatoms. The determination and quantification of diatom species is generally based on microscopic morphological identification, which requires expertise and is time-consuming and costly. In Europe, this morphological approach is legally imposed by standards and regulatory decrees by the Water Framework Directive (WFD). Over the past decade, a DNA-based molecular biology approach has newly been developed to identify species based on genetic criteria rather than morphological ones (i.e. DNA metabarcoding). In combination with high throughput sequencing technologies, metabarcoding makes it possible both to identify all species present in an environmental sample and to process several hundred samples in parallel. This article presents the results of two recent studies carried out on the WFD networks of rivers of Mayotte (2013–2018) and metropolitan France (2016–2018). These studies aimed at testing the potential application of metabarcoding for biomonitoring in the context of the WFD. We discuss the various methodological developments and optimisations that have been made to make the taxonomic inventories of diatoms produced by metabarcoding more reliable, particularly in terms of species quantification. We present the results of the application of this DNA approach on more than 500 river sites, comparing them with those obtained using the standardised morphological method. Finally, we discuss the potential of metabarcoding for routine application, its limits of application and propose some recommendations for future implementation in WFD.