Aquatic food webs in deep temperate lakes: Key species establish through their autecological versatility.

Microbial planktonic communities are the basis of food webs in aquatic ecosystems since they contribute substantially to primary production and nutrient recycling. Network analyses of DNA metabarcoding data sets emerged as a powerful tool to untangle the complex ecological relationships among the key players in food webs. In this study, we evaluated co-occurrence networks constructed from time-series metabarcoding data sets (12 months, biweekly sampling) of protistan plankton communities in surface layers (epilimnion) and bottom waters (hypolimnion) of two temperate deep lakes, Lake Mondsee (Austria) and Lake Zurich (Switzerland). Lake Zurich plankton communities were less tightly connected, more fragmented and had a higher susceptibility to a species extinction scenario compared to Lake Mondsee communities. We interpret these results as a lower robustness of Lake Zurich protistan plankton to environmental stressors, especially stressors resulting from climate change. In all networks, the phylum Ciliophora contributed the highest number of nodes, among them several in key positions of the networks. Associations in ciliate-specific subnetworks resembled autecological species-specific traits that indicate adaptions to specific environmental conditions. We demonstrate the strength of co-occurrence network analyses to deepen our understanding of plankton community dynamics in lakes and indicate biotic relationships, which resulted in new hypotheses that may guide future research in climate-stressed ecosystems.

Assessing Biotic and Abiotic Interactions of Microorganisms in Amazonia through Co-Occurrence Networks and DNA Metabarcoding.

Species may co-occur due to responses to similar environmental conditions, biological associations, or simply because of coincident geographical distributions. Disentangling patterns of co-occurrence and potential biotic and abiotic interactions is crucial to understand ecosystem function. Here, we used DNA metabarcoding data from litter and mineral soils collected from a longitudinal transect in Amazonia to explore patterns of co-occurrence. We compared data from different Amazonian habitat types, each with a characteristic biota and environmental conditions. These included non-flooded rainforests (terra-firme), forests seasonally flooded by fertile white waters (várzeas) or by unfertile black waters (igapós), and open areas associated with white sand soil (campinas). We ran co-occurrence network analyses based on null models and Spearman correlation for all samples and for each habitat separately. We found that one third of all operational taxonomic units (OTUs) were bacteria and two thirds were eukaryotes. The resulting networks were nevertheless mostly composed of bacteria, with fewer fungi, protists, and metazoans. Considering the functional traits of the OTUs, there is a combination of metabolism modes including respiration and fermentation for bacteria, and a high frequency of saprotrophic fungi (those that feed on dead organic matter), indicating a high turnover of organic material. The organic carbon and base saturation indices were important in the co-occurrences in Amazonian networks, whereas several other soil properties were important for the co-exclusion. Different habitats had similar network properties with some variation in terms of modularity, probably associated with flooding pulse. We show that Amazonian microorganism communities form highly interconnected co-occurrence and co-exclusion networks, which highlights the importance of complex biotic and abiotic interactions in explaining the outstanding biodiversity of the region.

Factors shaping community patterns of protists and bacteria on a European scale.

Factors shaping community patterns of microorganisms are controversially discussed. Physical and chemical factors certainly limit the survival of individual taxa and maintenance of diversity. In recent years, a contribution of geographic distance and dispersal barriers to distribution patterns of protists and bacteria has been demonstrated. Organismic interactions such as competition, predation and mutualism further modify community structure and maintenance of distinct taxa. Here, we address the relative importance of these different factors in shaping protists and bacterial communities on a European scale using high-throughput sequencing data obtained from lentic freshwater ecosystems. We show that community patterns of protists are similar to those of bacteria. Our results indicate that cross-domain organismic factors are important variables with a higher influence on protists as compared with bacteria. Abiotic physical and chemical factors also contributed significantly to community patterns. The contribution of these latter factors was higher for bacteria, which may reflect a stronger biogeochemical coupling. The contribution of geographical distance was similar for both microbial groups.

Improving eDNA-based protist diversity assessments using networks of amplicon sequence variants.

Effective and precise grouping of highly similar sequences remains a major bottleneck in the evaluation of high-throughput sequencing datasets. Amplicon sequence variants (ASVs) offer a promising alternative that may supersede the widely used operational taxonomic units (OTUs) in environmental sequencing studies. We compared the performance of a recently developed pipeline based on the algorithm DADA2 for obtaining ASVs against a pipeline based on the algorithm SWARM for obtaining OTUs. Illumina-sequencing of 29 individual ciliate species resulted in up to 11 ASVs per species, while SWARM produced up to 19 OTUs per species. To improve the congruency between species diversity and molecular diversity, we applied sequence similarity networks (SSNs) for second-level sequence grouping into network sequence clusters (NSCs). At 100% sequence similarity in SWARM-SSNs, NSC numbers decreased from 7.9-fold overestimation without abundance filter, to 4.5-fold overestimation when an abundance filter was applied. For the DADA2-SSN approach, NSC numbers decreased from 3.5-fold to 3-fold overestimation. Rand index cluster analyses predicted best binning results between 97% and 94% sequence similarity for both DADA2-SSNs and SWARM-SSNs. Depending on the ecological questions addressed in an environmental sequencing study with protists we recommend ASVs as replacement for OTUs, best in combination with SSNs.

A Comparison of Different Ciliate Metabarcode Genes as Bioindicators for Environmental Impact Assessments of Salmon Aquaculture.

Ciliates are powerful indicators for monitoring the impact of aquaculture and other industrial activities in the marine environment. Here, we tested the efficiency of four different genetic markers (V4 and V9 regions of the SSU rRNA gene, D1 and D2 regions of the LSU rRNA gene, obtained from environmental (e)DNA and environmental (e)RNA) of benthic ciliate communities for environmental monitoring. We obtained these genetic metabarcodes from sediment samples collected along a transect extending from below salmon cages toward the open sea. These data were compared to benchmark data from traditional macrofauna surveys of the same samples. In beta diversity analyses of ciliate community structures, the V4 and V9 markers had a higher resolution power for sampling sites with different degrees of organic enrichment compared to the D1 and D2 markers. The eDNA and eRNA V4 markers had a higher discriminatory power than the V9 markers. However, results obtained with the eDNA V9 marker corroborated better with the traditional macrofauna monitoring. This allows for a more direct comparison of ciliate metabarcoding with the traditional monitoring. We conclude that the ciliate eDNA V9 marker is the best choice for implementation in routine monitoring programs in marine aquaculture.

Transition boundaries for protistan species turnover in hypersaline waters of different biogeographic regions.

The identification of environmental barriers which govern species distribution is a fundamental concern in ecology. Even though salt was previously identified as a major transition boundary for micro- and macroorganisms alike, the salinities causing species turnover in protistan communities are unknown. We investigated 4.5 million high-quality protistan metabarcodes (V4 region of the SSU rDNA) obtained from 24 shallow salt ponds (salinities 4%-44%) from South America and Europe. Statistical analyses of protistan community profiles identified four salinity classes, which strongly selected for different protistan communities: 4-9%, 14-24%, 27-36% and 38-44%. The proportion of organisms unknown to science is highest in the 14-24% salinity class, showing that environments within this salinity range are an unappreciated reservoir of as yet undiscovered organisms. Distinct higher-rank taxon groups dominated in the four salinity classes in terms of diversity. As increasing salinities require different cellular responses to cope with salt, our results suggest that different evolutionary lineages of protists have evolved distinct haloadaptation strategies. Salinity appears to be a stronger selection factor for the structuring of protistan communities than geography. Yet, we find a higher degree of endemism in shallow salt ponds compared with less isolated ecosystems such as the open ocean. Thus, rules for biogeographic structuring of protistan communities are not universal, but depend on the ecosystem under consideration.

Testing ecological theories with sequence similarity networks: marine ciliates exhibit similar geographic dispersal patterns as multicellular organisms.

BACKGROUND: High-throughput sequencing technologies are lifting major limitations to molecular-based ecological studies of eukaryotic microbial diversity, but analyses of the resulting millions of short sequences remain a major bottleneck for these approaches. Here, we introduce the analytical and statistical framework of sequence similarity networks, increasingly used in evolutionary studies and graph theory, into the field of ecology to analyze novel pyrosequenced V4 small subunit rDNA (SSU-rDNA) sequence data sets in the context of previous studies, including SSU-rDNA Sanger sequence data from cultured ciliates and from previous environmental diversity inventories. RESULTS: Our broadly applicable protocol quantified the progress in the description of genetic diversity of ciliates by environmental SSU-rDNA surveys, detected a fundamental historical bias in the tendency to recover already known groups in these surveys, and revealed substantial amounts of hidden microbial diversity. Moreover, network measures demonstrated that ciliates are not globally dispersed, but are structured by habitat and geographical location at intermediate geographical scale, as observed for bacteria, plants, and animals. CONCLUSIONS: Currently available 'universal' primers used for local in-depth sequencing surveys provide little hope to exhaust the significantly higher ciliate (and most likely microbial) diversity than previously thought. Network analyses such as presented in this study offer a promising way to guide the design of novel primers and to further explore this vast and structured microbial diversity.

Marine protist diversity in European coastal waters and sediments as revealed by high-throughput sequencing.

Although protists are critical components of marine ecosystems, they are still poorly characterized. Here we analysed the taxonomic diversity of planktonic and benthic protist communities collected in six distant European coastal sites. Environmental deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) from three size fractions (pico-, nano- and micro/mesoplankton), as well as from dissolved DNA and surface sediments were used as templates for tag pyrosequencing of the V4 region of the 18S ribosomal DNA. Beta-diversity analyses split the protist community structure into three main clusters: picoplankton-nanoplankton-dissolved DNA, micro/mesoplankton and sediments. Within each cluster, protist communities from the same site and time clustered together, while communities from the same site but different seasons were unrelated. Both DNA and RNA-based surveys provided similar relative abundances for most class-level taxonomic groups. Yet, particular groups were overrepresented in one of the two templates, such as marine alveolates (MALV)-I and MALV-II that were much more abundant in DNA surveys. Overall, the groups displaying the highest relative contribution were Dinophyceae, Diatomea, Ciliophora and Acantharia. Also, well represented were Mamiellophyceae, Cryptomonadales, marine alveolates and marine stramenopiles in the picoplankton, and Monadofilosa and basal Fungi in sediments. Our extensive and systematic sequencing of geographically separated sites provides the most comprehensive molecular description of coastal marine protist diversity to date.

Molecular Diversity of Fungi from Marine Oxygen-Deficient Environments (ODEs).

Molecular diversity surveys of marine fungi have demonstrated that the species richness known to date is just the tip of the iceberg and that there is a large extent of unknown fungal diversity in marine habitats. Reports of novel fungal lineages at higher taxonomic levels are documented from a large number of marine habitats, including the various marine oxygen-deficient environments (ODEs). In the past few years, a strong focus of eukaryote diversity research has been on a variety of ODEs, as these environments are considered to harbor a large number of organisms, which are highly divergent to known diversity and could provide insights into the early eukaryotic evolution. ODEs that have been targeted so far include shallow water sediments, hydrothermal vent systems, deep-sea basins, intertidal habitats, and fjords. Most, if not all, molecular diversity studies in marine ODEs have shown, that contrary to previous assumptions, fungi contribute significantly to the micro-eukaryotic community in such habitats. In this chapter, we have reanalyzed the environmental fungal sequences obtained from the molecular diversity survey in 14 different sites to obtain a comprehensive picture of fungal diversity in these marine habitats. The phylogenetic analysis of the fungal environmental sequences from various ODEs have grouped these sequences into seven distinct clades (Clade 1-7) clustering with well-known fungal taxa. Apart from this, four environmental clades (EnvClade A, B, C, and D) with exclusive environmental sequences were also identified. This has provided information on the positioning of the environmental sequences at different taxonomic levels within the major fungal phylums. The taxonomic distribution of these environmental fungal sequences into clusters and clades has also shown that they are not restricted by geographical boundaries. The distribution pattern together with the reports on the respiratory abilities of fungi under reduced oxygen conditions shows that they are highly adaptive and may have a huge ecological role in these oxygen deficient habitats.

Global Trends of Benthic Bacterial Diversity and Community Composition Along Organic Enrichment Gradients of Salmon Farms.

The analysis of benthic bacterial community structure has emerged as a powerful alternative to traditional microscopy-based taxonomic approaches to monitor aquaculture disturbance in coastal environments. However, local bacterial diversity and community composition vary with season, biogeographic region, hydrology, sediment texture, and aquafarm-specific parameters. Therefore, without an understanding of the inherent variation contained within community complexes, bacterial diversity surveys conducted at individual farms, countries, or specific seasons may not be able to infer global universal pictures of bacterial community diversity and composition at different degrees of aquaculture disturbance. We have analyzed environmental DNA (eDNA) metabarcodes (V3-V4 region of the hypervariable SSU rRNA gene) of 138 samples of different farms located in different major salmon-producing countries. For these samples, we identified universal bacterial core taxa that indicate high, moderate, and low aquaculture impact, regardless of sampling season, sampled country, seafloor substrate type, or local farming and environmental conditions. We also discuss bacterial taxon groups that are specific for individual local conditions. We then link the metabolic properties of the identified bacterial taxon groups to benthic processes, which provides a better understanding of universal benthic ecosystem function(ing) of coastal aquaculture sites. Our results may further guide the continuing development of a practical and generic bacterial eDNA-based environmental monitoring approach.

Lake Ecosystem Robustness and Resilience Inferred from a Climate-Stressed Protistan Plankton Network.

Network analyses of biological communities allow for identifying potential consequences of climate change on the resilience of ecosystems and their robustness to resist stressors. Using DNA metabarcoding datasets from a three-year-sampling (73 samples), we constructed the protistan plankton co-occurrence network of Lake Zurich, a model lake ecosystem subjected to climate change. Despite several documentations of dramatic lake warming in Lake Zurich, our study provides an unprecedented perspective by linking changes in biotic association patterns to climate stress. Water temperature belonged to the strongest environmental parameters splitting the data into two distinct seasonal networks (October-April; May-September). The expected ecological niche of phytoplankton, weakened through nutrient depletion because of permanent thermal stratification and through parasitic fungi, was occupied by the cyanobacterium Planktothrix rubescens and mixotrophic nanoflagellates. Instead of phytoplankton, bacteria and nanoflagellates were the main prey organisms associated with key predators (ciliates), which contrasts traditional views of biological associations in lake plankton. In a species extinction scenario, the warm season network emerged as more vulnerable than the cold season network, indicating a time-lagged effect of warmer winter temperatures on the communities. We conclude that climate stressors compromise lake ecosystem robustness and resilience through species replacement, richness differences, and succession as indicated by key network properties.

Spatial and Annual Variation in Microbial Abundance, Community Composition, and Diversity Associated With Alpine Surface Snow.

Understanding microbial community dynamics in the alpine cryosphere is an important step toward assessing climate change impacts on these fragile ecosystems and meltwater-fed environments downstream. In this study, we analyzed microbial community composition, variation in community alpha and beta diversity, and the number of prokaryotic cells and virus-like particles (VLP) in seasonal snowpack from two consecutive years at three high altitude mountain summits along a longitudinal transect across the European Alps. Numbers of prokaryotic cells and VLP both ranged around 104 and 105 per mL of snow meltwater on average, with variation generally within one order of magnitude between sites and years. VLP-to-prokaryotic cell ratios spanned two orders of magnitude, with median values close to 1, and little variation between sites and years in the majority of cases. Estimates of microbial community alpha diversity inferred from Hill numbers revealed low contributions of common and abundant microbial taxa to the total taxon richness, and thus low community evenness. Similar to prokaryotic cell and VLP numbers, differences in alpha diversity between years and sites were generally relatively modest. In contrast, community composition displayed strong variation between sites and especially between years. Analyses of taxonomic and phylogenetic community composition showed that differences between sites within years were mainly characterized by changes in abundances of microbial taxa from similar phylogenetic clades, whereas shifts between years were due to significant phylogenetic turnover. Our findings on the spatiotemporal dynamics and magnitude of variation of microbial abundances, community diversity, and composition in surface snow may help define baseline levels to assess future impacts of climate change on the alpine cryosphere.

An integrative approach sheds new light onto the systematics and ecology of the widespread ciliate genus Coleps (Ciliophora, Prostomatea).

Species of the genus Coleps are one of the most common planktonic ciliates in lake ecosystems. The study aimed to identify the phenotypic plasticity and genetic variability of different Coleps isolates from various water bodies and from culture collections. We used an integrative approach to study the strains by (i) cultivation in a suitable culture medium, (ii) screening of the morphological variability including the presence/absence of algal endosymbionts of living cells by light microscopy, (iii) sequencing of the SSU and ITS rDNA including secondary structures, (iv) assessment of their seasonal and spatial occurrence in two lakes over a one-year cycle both from morphospecies counts and high-throughput sequencing (HTS), and, (v) proof of the co-occurrence of Coleps and their endosymbiotic algae from HTS-based network analyses in the two lakes. The Coleps strains showed a high phenotypic plasticity and low genetic variability. The algal endosymbiont in all studied strains was Micractinium conductrix and the mutualistic relationship turned out as facultative. Coleps is common in both lakes over the whole year in different depths and HTS has revealed that only one genotype respectively one species, C. viridis, was present in both lakes despite the different lifestyles (mixotrophic with green algal endosymbionts or heterotrophic without algae). Our results suggest a future revision of the species concept of the genus Coleps.

Obstetric Ultrasonography to Detect Fetal Abnormalities in a Mouse Model for Zika Virus Infection.

In 2015 Zika virus (ZIKV) emerged for the first time in South America. The following ZIKV epidemic resulted in the appearance of a clinical phenotype with microcephaly and other severe malformations in newborns. So far, mechanisms of ZIKV induced damage to the fetus are not completely understood. Previous data suggest that ZIKV may bypass the placenta to reach the fetus. Thus, animal models for ZIKV infection are important to facilitate studies about ZIKV infection during pregnancy. Here, we used ultrasound based imaging (USI) to characterize ZIKV induced pathogenesis in the pregnant Type I interferon receptor-deficient (IFNAR-/-) mouse model. Based on USI we suggest the placenta to be a primary target organ of ZIKV infection enabling ZIKV spreading to the fetus. Moreover, in addition to direct infection of the fetus, the placental ZIKV infection may cause an indirect damage to the fetus through reduced uteroplacental perfusion leading to intrauterine growth retardation (IUGR) and fetal complications as early as embryonic day (ED) 12.5. Our data confirmed the capability of USI to characterize ZIKV induced modifications in mouse fetuses. Data from further studies using USI to monitor ZIKV infections will contribute to a better understanding of ZIKV infection in pregnant IFNAR-/- mice.

Seasonality of Planktonic Freshwater Ciliates: Are Analyses Based on V9 Regions of the 18S rRNA Gene Correlated With Morphospecies Counts?

Ciliates represent central nodes in freshwater planktonic food webs, and many species show pronounced seasonality, with short-lived maxima of a few dominant taxa while many being rare or ephemeral. These observations are primarily based on morphospecies counting methods, which, however, have limitations concerning the amount and volume of samples that can be processed. For high sampling frequencies at large scales, high throughput sequencing (HTS) of freshwater ciliates seems to be a promising tool. However, several studies reported large discrepancy between species abundance determinations by molecular compared to morphological means. Therefore, we compared ciliate DNA metabarcodes (V9 regions of the 18S rRNA gene) with morphospecies counts for a 3-year study (Lake Zurich, Switzerland; biweekly sampling, n = 74). In addition, we isolated, cultivated and sequenced the 18S rRNA gene of twelve selected ciliate species that served as seeds for HTS analyses. This workflow allowed for a detailed comparison of V9 data with microscopic analyses by quantitative protargol staining (QPS). The dynamics of V9 read abundances over the seasonal cycle corroborated well with morphospecies population patterns. Annual successions of rare and ephemeral species were more adequately characterized by V9 reads than by QPS. However, numbers of species specific sequence reads only partly reflected rank orders seen by counts. In contrast, biomass-based assemblage compositions showed higher similarity to V9 read numbers, probably indicating a relation between cell sizes and numbers / sizes of macronuclei (or 18S rRNA operons). Full-length 18S rRNA sequences of ciliates assigned to certain morphospecies are urgently needed for barcoding approaches as planktonic taxa are still poorly represented in public databases and the interpretation of HTS data depends on profound reference sequences. Through linking operational taxonomic units (OTUs) with known morphospecies, we can use the deep knowledge about the autecology of these species.

Asymmetric synthesis of beta-nitro ketones via Michael addition of lithiated alpha-amino nitriles to nitroalkenes.

Alpha-amino nitriles, easily prepared from aldehydes, KCN, and an enantiopure secondary amine auxiliary, are metalated and used as nucleophiles in asymmetric Michael additions to nitroalkenes to afford the Michael adducts in good yields and good to excellent diastereoselectivities. After chromatographic purification, the diastereomerically pure 1,4-adducts are cleaved under acidic conditions to give the beta-nitro ketones in good yields and with two exceptions in good to excellent enantiomeric excesses (ee = 86-99%). The absolute configuration was determined by X-ray structure analysis.

Towards an eDNA metabarcode-based performance indicator for full-scale municipal wastewater treatment plants.

Knowledge-driven management for wastewater treatment plant (WWTP) performance becomes increasingly important considering the globally growing production of wastewater and the rising demand of clean water supply. Even though the potential of microbial organisms (bacteria and protists) as bioindicators for WWTP performance is well known, it is far from being fully exploited for routine monitoring programs. Therefore, we here used massive sequencing of environmental (e)DNA metabarcodes from bacterial (V3-V4 region of the SSU rRNA gene) and eukaryote (V9 region of the SSU rRNA gene) communities in 21 activated sludge samples obtained from full-scale municipal WWTPs in Germany. Microbial community patterns were compared to standard WWTP operating parameters and two traditionally used WWTP performance indicators (Sludge Biotic Index and Sludge Index). Both indices showed low concordance and hardly correlated with chemical WWTP performance parameters nor did they correlate with microbial community structures. In contrast, microbial community profiles significantly correlated with WWTP performance parameters and operating conditions of the plants under study. Therefore, eDNA metabarcode profiles of whole microbial communities indicate the performance of WWTP and can provide useful information for management strategies. We here suggest a strategy for the development of an eDNA metabarcode based bioindicator system, which can be implemented in future standard monitoring programs for WWTP performance and effluent quality.

Environmental status assessment using biological traits analyses and functional diversity indices of benthic ciliate communities.

In this study, we tested the hypothesis that the functional diversity of benthic ciliates has high potential to monitor marine ecological status. Therefore, we investigated the spatial and temporal variation of functional diversity of benthic ciliates in the Yangtze Estuary during one year using biological traits analyses and functional diversity indices. Traits and community compositions showed clear spatial and temporal variations. Among a variety of biological traits, feeding type and body size emerged as strongest predictable variables. Functional divergence (FDiv) had an advantage over two other functional diversity indices, as well as over classical diversity measures (i.e. richness, evenness, Shannon-Wiener) to infer environmental status. Significant correlations between biological traits, FDiv and environmental variables (i.e. nutrients, temperature, salinity) suggested that functional diversity of benthic ciliates might be used as a bio-indicator in environmental status assessments. Further mandatory researches need to implement functional diversity of ciliates in routine monitoring programs were discussed.

Environmental DNA metabarcoding of benthic bacterial communities indicates the benthic footprint of salmon aquaculture.

We evaluated benthic bacterial communities as bioindicators in environmental impact assessments of salmon aquaculture, a rapidly growing sector of seafood industry. Sediment samples (n=72) were collected from below salmon cages towards distant reference sites. Bacterial community profiles inferred from DNA metabarcodes were compared to reference data from standard macrofauna biomonitoring surveys of the same samples. Deltaproteobacteria were predominant in immediate vicinity of the salmon cages. Along the transect, significant shifts in bacterial community structures were observed with Gammaproteobacteria dominating the less-impacted sites. Alpha- and beta-diversity measures of bacterial communities correlated significantly with macrofauna diversity metrics and with five ecological status indices. Benthic bacterial communities mirror the reaction of macrofauna bioindicators to environmental disturbances caused by salmon farming. The implementation of bacterial eDNA metabarcoding in future Strategic Framework Directives is an alternative cost-effective high-throughput biomonitoring solution, providing a basis for management strategies in a matter of days rather than months.

Supervised machine learning outperforms taxonomy-based environmental DNA metabarcoding applied to biomonitoring.

Biodiversity monitoring is the standard for environmental impact assessment of anthropogenic activities. Several recent studies showed that high-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) could overcome many limitations of the traditional morphotaxonomy-based bioassessment. Recently, we demonstrated that supervised machine learning (SML) can be used to predict accurate biotic indices values from eDNA metabarcoding data, regardless of the taxonomic affiliation of the sequences. However, it is unknown to which extent the accuracy of such models depends on taxonomic resolution of molecular markers or how SML compares with metabarcoding approaches targeting well-established bioindicator species. In this study, we address these issues by training predictive models upon five different ribosomal bacterial and eukaryotic markers and measuring their performance to assess the environmental impact of marine aquaculture on independent data sets. Our results show that all tested markers are yielding accurate predictive models and that they all outperform the assessment relying solely on taxonomically assigned sequences. Remarkably, we did not find any significant difference in the performance of the models built using universal eukaryotic or prokaryotic markers. Using any molecular marker with a taxonomic range broad enough to comprise different potential bioindicator taxa, SML approach can overcome the limits of taxonomy-based eDNA bioassessment.