Unveiling distribution patterns of freshwater phytoplankton by a next generation sequencing based approach

Phytoplankton ecology in the early years of a boreal oil sands end pit lake

BACKGROUND

Base Mine Lake (BML) is the first full-scale end pit lake for the oil sands mining industry in Canada. BML sequesters oil sands tailings under a freshwater cap and is intended to develop into a functional ecosystem that can be integrated into the local watershed. The first stage of successful reclamation requires the development of a phytoplankton community supporting a typical boreal lake food web. To assess the diversity and dynamics of the phytoplankton community in BML at this reclamation stage and to set a baseline for future monitoring, we examined the phytoplankton community in BML from 2016 through 2021 using molecular methods (targeting the 23S, 18S, and 16S rRNA genes) and microscopic methods. Nearby water bodies were used as controls for a freshwater environment and an active tailings pond.

RESULTS

The phytoplankton community was made up of diverse bacteria and eukaryotes typical of a boreal lake. Microscopy and molecular data both identified a phytoplankton community comparable at the phylum level to that of natural boreal lakes, dominated by Chlorophyta, Cryptophyta, and Cyanophyta, with some Bacillariophyta, Ochrophyta, and Euglenophyta. Although many of the same genera were prominent in both BML and the control freshwater reservoir, there were differences at the species or ASV level. Total diversity in BML was also consistently lower than the control freshwater site, but consistently higher than the control tailings pond. The phytoplankton community composition in BML changed over the 5-year study period. Some taxa present in 2016-2019 (e.g., Choricystis) were no longer detected in 2021, while some dinophytes and haptophytes became detectable in small quantities starting in 2019-2021. Different quantification methods (qPCR analysis of 23S rRNA genes, and microscopic estimates of populations and total biomass) did not show a consistent directional trend in total phytoplankton over the 5-year study, nor was there any consistent increase in phytoplankton species diversity. The 5-year period was likely an insufficient time frame for detecting community trends, as phytoplankton communities are highly variable at the genus and species level.

CONCLUSIONS

BML supports a phytoplankton community composition somewhat unique from control sites (active tailings and freshwater lake) and is still changing over time. However, the most abundant genera are typical of natural boreal lakes and have the potential to support a complex aquatic food web, with many of its identified major phytoplankton constituents known to be primary producers in boreal lake environments.

Genetic Markers for Metabarcoding of Freshwater Microalgae: Review

The metabarcoding methods for studying the diversity of freshwater microalgae and routine biomonitoring are actively used in modern research. A lot of experience has been accumulated already, and many methodological questions have been solved (such as the influence of the methods and time of sample conservation, DNA extraction and bioinformatical processing). The reproducibility of the method has been tested and confirmed. However, one of the main problems-choosing a genetic marker for the study-still lacks a clear answer. We analyzed 70 publications and found out that studies on eukaryotic freshwater microalgae use 12 markers (different nuclear regions 18S and ITS and plastids rbcL, 23S and 16S). Each marker has its peculiarities; they amplify differently and have various levels of efficiency (variability) in different groups of algae. The V4 and V9 18S and rbcL regions are used most often. We concentrated especially on the studies that compare the results of using different markers and microscopy. We summarize the data on the primers for each region and on how the choice of a marker affects the taxonomic composition of a community.

Trends in digital image processing of isolated microalgae by incorporating classification algorithm

Identification of microalgae species is of importance due to the uprising of harmful algae blooms affecting both the aquatic habitat and human health. Despite this occurence, microalgae have been identified as a green biomass and alternative source due to its promising bioactive compounds accumulation that play a significant role in many industrial applications. Recently, microalgae species identification has been conducted through DNA analysis and various microscopy techniques such as light, scanning electron, transmission electron, and atomic force -microscopy. The aforementioned procedures have encouraged researchers to consider alternate ways due to limitations such as costly validation, requiring skilled taxonomists, prolonged analysis, and low accuracy. This review highlights the potential innovations in digital microscopy with the incorporation of both hardware and software that can produce a reliable recognition, detection, enumeration, and real-time acquisition of microalgae species. Several steps such as image acquisition, processing, feature extraction, and selection are discussed, for the purpose of generating high image quality by removing unwanted artifacts and noise from the background. These steps of identification of microalgae species is performed by reliable image classification through machine learning as well as deep learning algorithms such as artificial neural networks, support vector machines, and convolutional neural networks. Overall, this review provides comprehensive insights into numerous possibilities of microalgae image identification, image pre-processing, and machine learning techniques to address the challenges in developing a robust digital classification tool for the future.

National eDNA-based monitoring of Batrachochytrium dendrobatidis and amphibian species in Norway

Freshwaters represent the most threatened environments with regard to biodiversity loss and, therefore, there is a need for national monitoring programs to effectively document species distribution and evaluate potential risks for vulnerable species. The monitoring of species for effective management practices is, however, challenged by insufficient data acquisition when using traditional methods. Here we present the application of environmental DNA (eDNA) metabarcoding of amphibians in combination with quantitative PCR (qPCR) assays for an invasive pathogenic chytrid species (Batrachochytrium dendrobatidis -Bd), a potential threat to endemic and endangered amphibian species. Statistical comparison of amphibian species detection using either traditional or eDNA-based approaches showed weak correspondence. By tracking the distribution of Bd over three years, we concluded that the risk for amphibian extinction is low since Bd was only detected at five sites where multiple amphibians were present over the sampled years. Our results show that eDNA-based detection can be used for simultaneous monitoring of amphibian diversity and the presence of amphibian pathogens at the national level in order to assess potential species extinction risks and establish effective management practices. As such our study represents suggestions for a national monitoring program based on eDNA.

Bacterial composition in Swedish raw drinking water reveals three major interacting ubiquitous metacommunities

BACKGROUND

Surface raw water used as a source for drinking water production is a critical resource, sensitive to contamination. We conducted a study on Swedish raw water sources, aiming to identify mutually co-occurring metacommunities of bacteria, and environmental factors driving such patterns.

METHODS

The water sources were different regarding nutrient composition, water quality, and climate characteristics, and displayed various degrees of anthropogenic impact. Water inlet samples were collected at six drinking water treatment plants over 3 years, totaling 230 samples. The bacterial communities of DNA sequenced samples (n = 175), obtained by 16S metabarcoding, were analyzed using a joint model for taxa abundance.

RESULTS

Two major groups of well-defined metacommunities of microorganisms were identified, in addition to a third, less distinct, and taxonomically more diverse group. These three metacommunities showed various associations to the measured environmental data. Predictions for the well-defined metacommunities revealed differing sets of favored metabolic pathways and life strategies. In one community, taxa with methanogenic metabolism were common, while a second community was dominated by taxa with carbohydrate and lipid-focused metabolism.

CONCLUSION

The identification of ubiquitous persistent co-occurring bacterial metacommunities in freshwater habitats could potentially facilitate microbial source tracking analysis of contamination issues in freshwater sources.

Monitoring harmful microalgal species and their appearance in Tokyo Bay, Japan, using metabarcoding

During the recent decade, high-throughput sequencing (HTS) techniques, in particular, DNA metabarcoding, have facilitated increased detection of biodiversity, including harmful algal bloom (HAB) species. In this study, the presence of HAB species and their appearance patterns were investigated by employing molecular and light microscopy-based monitoring in Tokyo Bay, Japan. The potential co-appearance patterns between the HAB species, as well as with other eukaryotes and prokaryotes were investigated using correlation and association rule-based time-series analysis. In total, 40 unique HAB species were detected, including 12 toxin-producing HAB species previously not reported from the area. More than half of the HAB species were present throughout the sampling season (summer to autumn) and no structuring or succession patterns associated with the environmental conditions could be detected. Statistically significant (p < 0.05, rS ranging from −0.88 to 0.90) associations were found amongst the HAB species and other eukaryotic and prokaryotic species, including genera containing growth-limiting bacteria. However, significant correlations between species differed amongst the years, indicating that variability in environmental conditions between the years may have a stronger influence on the microalgal community structure and interspecies interactions than the variability during the sampling season. The association rule-based time-series analysis allowed the detection of a previously reported negative relationship between Synechococcus sp. and Skeletonema sp. in nature. Overall, the results support the applicability of metabarcoding and HTS-based microalgae monitoring, as it facilitates more precise species identification compared to light microscopy, as well as provides input for investigating potential interactions amongst different species/groups through simultaneous detection of multiple species/genera.

DNA sequence and taxonomic gap analyses to quantify the coverage of aquatic cyanobacteria and eukaryotic microalgae in reference databases: Results of a survey in the Alpine region

The taxonomic identification of organisms based on the amplification of specific genetic markers (metabarcoding) implicitly requires adequate discriminatory information and taxonomic coverage of environmental DNA sequences in taxonomic databases. These requirements were quantitatively examined by comparing the determination of cyanobacteria and microalgae obtained by metabarcoding and light microscopy. We used planktic and biofilm samples collected in 37 lakes and 22 rivers across the Alpine region. We focused on two of the most used and best represented genetic markers in the reference databases, namely the 16S rRNA and 18S rRNA genes. A sequence gap analysis using blastn showed that, in the identity range of 99-100%, approximately 30% (plankton) and 60% (biofilm) of the sequences did not find any close counterpart in the reference databases (NCBI GenBank). Similarly, a taxonomic gap analysis showed that approximately 50% of the cyanobacterial and eukaryotic microalgal species identified by light microscopy were not represented in the reference databases. In both cases, the magnitude of the gaps differed between the major taxonomic groups. Even considering the species determined under the microscope and represented in the reference databases, 22% and 26% were still not included in the results obtained by the blastn at percentage levels of identity ≥95% and ≥97%, respectively. The main causes were the absence of matching sequences due to amplification and/or sequencing failure and potential misidentification in the microscopy step. Our results quantitatively demonstrated that in metabarcoding the main obstacles in the classification of 16S rRNA and 18S rRNA sequences and interpretation of high-throughput sequencing biomonitoring data were due to the existence of important gaps in the taxonomic completeness of the reference databases and the short length of reads. The study focused on the Alpine region, but the extent of the gaps could be much greater in other less investigated geographic areas.

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.

Trophic states regulate assembly processes and network structures of small chromophytic phytoplankton communities in estuarine and coastal ecosystem

Small chromophytic phytoplankton (SCP) are anticipated to be more important for a significant proportion of primary production in estuarine-coastal ecosystems. However, responses of SCP community to coastal eutrophication are still unclear. In this study, we investigated diversity, co-occurrence and assembly features of SCP communities, as well as relationship with environmental factors in subtropical Beibu Gulf. The results exhibited that the alpha diversity and beta diversity of SCP communities were significantly different among eutrophic states. Co-occurrence network revealed a complex interaction that most amplicon sequence variants (ASVs) in modules of the network were specific to trophic states. Further, phylogenetic based β-nearest taxon distance analyses revealed that stochastic processes mainly provided 69.26% contribution to SCP community assembly, whereas deterministic processes dominated community assembly in heavy eutrophic state. Overall, our findings elucidate the mechanism of diversity and assembly in SCP community and promote the understanding of SCP ecology related to subtropical coastal eutrophication.

Meta-analysis shows both congruence and complementarity of DNA and eDNA metabarcoding to traditional methods for biological community assessment

DNA metabarcoding is increasingly used for the assessment of aquatic communities, and numerous studies have investigated the consistency of this technique with traditional morpho‐taxonomic approaches. These individual studies have used DNA metabarcoding to assess diversity and community structure of aquatic organisms both in marine and freshwater systems globally over the last decade. However, a systematic analysis of the comparability and effectiveness of DNA‐based community assessment across all of these studies has hitherto been lacking. Here, we performed the first meta‐analysis of available studies comparing traditional methods and DNA metabarcoding to measure and assess biological diversity of key aquatic groups, including plankton, microphytobentos, macroinvertebrates, and fish. Across 215 data sets, we found that DNA metabarcoding provides richness estimates that are globally consistent to those obtained using traditional methods, both at local and regional scale. DNA metabarcoding also generates species inventories that are highly congruent with traditional methods for fish. Contrastingly, species inventories of plankton, microphytobenthos and macroinvertebrates obtained by DNA metabarcoding showed pronounced differences to traditional methods, missing some taxa but at the same time detecting otherwise overseen diversity. The method is generally sufficiently advanced to study the composition of fish communities and replace more invasive traditional methods. For smaller organisms, like macroinvertebrates, plankton and microphytobenthos, DNA metabarcoding may continue to give complementary rather than identical estimates compared to traditional approaches. Systematic and comparable data collection will increase the understanding of different aspects of this complementarity, and increase the effectiveness of the method and adequate interpretation of the results.

Disentangling the drivers of phytoplankton community composition in a heavily sediment-laden transcontinental river

Phytoplankton play a crucial role in energy flow and carbon cycling in aquatic ecosystems; however, exploring the driving factors influencing phytoplankton, especially in heavily sediment-laden rivers, is challenging. We analyzed 704 samples from 44 sampling sites along the Yellow River to investigate the biogeographic, environmental, and anthropogenic impacts on the phytoplankton community composition. Using cluster analysis, we identified three different phytoplankton community compositions in Regions Ⅰ, Ⅱ, and Ⅲ, which were consistent with the three primary changes in the water-surface slope across the three regions. The sampling results showed that the Bacillariophyta primarily consisted of Navicula, Cyclotella, Synedra, Fragilaria, Gyrosigma, Diatoma, and Asterionella. In addition, representation by Chlorophyta was dominated by Chlamydomonas, Pandorina, Closteriopsis, and Closterium, while Phormidium was the dominant Cyanophyta genus. The variation partitioning results indicated that spatial factors (geographic distance) were the most important determinants of phytoplankton community succession. Additionally, our results highlighted that the influence of spatial and climatic factors on the succession of the phytoplankton community structure was much greater than that of the water quality. Compared to that in the free-flowing river, the phytoplankton biomass in the impoundment was much higher, and the phytoplankton community was dominated by Dinophyta, Chlorophyta, and Cyanophyta, primarily because of anthropogenic impacts. Based on the composition and biomass of phytoplankton communities in different regions, the phytoplankton community composition in the Yellow River was found to be primarily influenced by the erosion of the watershed and the inflow of tributaries rather than by limited in situ algae growth.

Plankton biodiversity and species co-occurrence based on environmental DNA – a multiple marker study

Metabarcoding in combination with high-throughput sequencing (HTS) allows simultaneous detection of multiple taxa by targeting single or several taxonomically informative gene regions from environmental DNA samples. In this study, a multiple-marker HTS approach was applied to investigate the plankton diversity and seasonal succession in the Baltic Sea from winter to autumn. Four different markers targeting the 16S, 18S, and 28S ribosomal RNA genes were employed, including a marker for more efficient dinoflagellate detection. Typical seasonal changes were observed in phyto- and bacterioplankton communities. In phytoplankton, the appearance patterns of selected common, dominant, or harmful species followed the patterns also confirmed based on 20 years of phytoplankton monitoring data. In the case of zooplankton, both macro- and microzooplankton species were detected. However, no seasonal patterns were detected in their appearance. In total, 15 and 2 new zoo- and phytoplankton species were detected from the Baltic Sea. HTS approach was especially useful for detecting microzooplankton species as well as for investigating the co-occurrence and potential interactions of different taxa. The results of this study further exemplify the efficiency of metabarcoding for biodiversity monitoring and the advantage of employing multiple markers through the detection of species not identifiable based on a single marker survey and/or by traditional morphology-based methods.

Geo-climatic factors weaken the effectiveness of phytoplankton diversity as a water quality indicator in a large sediment-laden river

The study aims to determine whether phytoplankton diversity can be used as an indicator of water quality in large-scale sediment-laden rivers with heterogeneous environmental conditions. We hypothesized that environmental factors, such as sediment load, water surface slope, and precipitation, may impact the effectiveness of using phytoplankton diversity as a water quality indicator. To test this hypothesis, the Yellow River was selected for phytoplankton diversity and water quality assessments. We measured water quality parameters, calculated phytoplankton diversity indices, and collected data on geo-climatic variables at 130 sampling points in the Yellow River mainstream over two seasons (spring and autumn) in 2019. The results of the water quality assessment based on phytoplankton diversity indices were compared with those based on water quality index (WQI). Correlation analysis, multiple stepwise regression, distance-based redundancy analysis, and regression modeling were used to explore the biogeographical patterns and drivers of phytoplankton diversity. According to the WQI, the water quality gradually deteriorated from the source to the estuary of the river. Three biodiversity indices (Margalef, Pielou, and Shannon-Wiener) indicated that the water quality varied dynamically in the middle reaches of the river. The actual relationships between the biodiversity indices and WQI did not fit well with the standard curves of water quality classification based on the respective biodiversity indices and WQI. Variation partitioning analysis indicated that water quality parameters, such as sediment and nutrient load, were the dominant drivers of variation in phytoplankton diversity in most cases, with the contribution ranging from 11.0% to 25.7%. Geo-climatic factors, such as water surface slope and annual mean precipitation, also affected phytoplankton diversity, with the contribution reaching 27.8%. Therefore, in sediment-laden rivers with a large geographical span and complex environment, phytoplankton diversity cannot be used as a suitable water quality indicator, albeit it can reflect habitat changes to a certain extent.

Comparative analysis of freshwater phytoplankton communities in two lakes of Burabay National Park using morphological and molecular approaches

We analyzed phytoplankton assemblages' variations in oligo-mesotrophic Shchuchie and Burabay lakes using traditional morphological and next-generation sequencing (NGS) approaches. The total phytoplankton biodiversity and abundance estimated by both microscopy and NGS were significantly higher in Lake Burabay than in Lake Shchuchie. NGS of 16S and 18S rRNA amplicons adequately identify phytoplankton taxa only on the genera level, while species composition obtained by microscopic examination was significantly larger. The limitations of NGS analysis could be related to insufficient coverage of freshwater lakes phytoplankton by existing databases, short algal sequences available from current instrumentation, and high homology of chloroplast genes in eukaryotic cells. However, utilization of NGS, together with microscopy allowed us to perform a complete taxonomic characterization of phytoplankton lake communities including picocyanobacteria, often overlooked by traditional microscopy. We demonstrate the high potential of an integrated morphological and molecular approach in understanding the processes of organization in aquatic ecosystem assemblages.

Dumpster diving for diatom plastid 16S rRNA genes

High throughput sequencing is improving the efficiency of monitoring diatoms, which inhabit and support aquatic ecosystems across the globe. In this study, we explored the potential of a standard V4 515F-806RB primer pair in recovering diatom plastid 16S rRNA sequences. We used PhytoREF to classify the 16S reads from our freshwater biofilm field sampling from three stream segments across two streams in south-eastern Australia and retrieved diatom community data from other, publicly deposited, Australian 16S amplicon datasets. When these diatom operational taxonomic units (OTUs) were traced using the default RDPII and NCBI databases, 68% were characterized as uncultured cyanobacteria. We analysed the 16S rRNA sequences from 72 stream biofilm samples, separated the chloroplast OTUs, and classified them using the PhytoREF database. After filtering the reads attributed to Bacillariophyta (relative abundance >1%), 71 diatom OTUs comprising more than 90% of the diatom reads in each stream biofilm sample were identified. Beta-diversity analyses demonstrated significantly different diatom assemblages and discrimination among river segments. To further test the approach, the diatom OTUs from our biofilm sampling were used as reference sequences to identify diatom reads from other Australian 16S rRNA datasets in the NCBI-SRA database. Across the three selected public datasets, 67 of our 71 diatom OTUs were detected in other Australian ecosystems. Our results show that diatom plastid 16S rRNA genes are readily amplified with existing 515F-806RB primer sets. Therefore, the volume of existing 16S rRNA amplicon datasets initially generated for microbial community profiling can also be used to detect, characterize, and map diatom distribution to inform phylogeny and ecological health assessments, and can be extended into a range of ecological and industrial applications. To our knowledge, this study represents the first attempt to classify freshwater samples using this approach and the first application of PhytoREF in Australia.

Distribution and diversity of eukaryotic microalgae in Kuwait waters assessed using 18S rRNA gene sequencing

The microbial communities play a crucial role in ecosystem functioning through interactions among individuals and taxonomic groups in a highly dynamic marine ecosystem. The structure and functioning of the microbial communities are often influenced by the changes in the surrounding environment. Monitoring the microbial diversity of the marine ecosystem helps to understand spatial patterns of microbial community and changes due to season, climate, and various drivers of biological diversity. Kuwait is characterized by an arid environment with a high degree of temperature variation during summer and winter. Our understanding of spatial distribution patterns of microbial communities, their diversity, and the influence of human activities on the degree of changes in the diversity of the microbial community in Kuwait territorial waters remain unclear. In this study, we employed 18S rRNA sequencing to explore marine microalgal community composition and dynamics in seawater samples collected from Kuwait waters over two seasonal cycles across six locations. A total of 448,184 sequences across 36 replicates corresponding to 12 samples from six stations were obtained. The quality-filtered sequences were clustered into 1,293 representative sequences, which were then classified into different eukaryotic taxa. This study reveals that the phytoplankton community in Kuwait waters is diverse and shows significant variations among different taxa during summer and winter. Dinoflagellates and diatoms were the most abundant season-dependent microalgae taxa in Kuwait waters. Alexandrium and Pyrophacus were abundant in summer, whereas Gonyaulax was abundant during the winter. The abundance of Coscinodiscus and Navicula, of the diatom genera, were also dependent upon both seasonal and possible anthropogenic factors. Our results demonstrate the effectiveness of a sequencing-based approach, which could be used to improve the accuracy of quantitative eukaryotic microbial community profiles.

Next generation sequencing approaches to evaluate water and wastewater quality

The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.

Changes in the Community Structure of Under-Ice and Open-Water Microbiomes in Urban Lakes Exposed to Road Salts

Salinization of freshwater is increasingly observed in regions where chloride de-icing salts are applied to the roads in winter, but little is known about the effects on microbial communities. In this study, we analyzed the planktonic microbiomes of four lakes that differed in degree of urbanization, eutrophication and salinization, from an oligotrophic reference lake with no surrounding roads, to a eutrophic, salinized lake receiving runoff from a highway. We tested the hypothesis that an influence of road salts would be superimposed on the effects of season and trophic status. We evaluated the microbial community structure by 16S rRNA sequencing for Bacteria, and by four methods for eukaryotes: 16S rRNA chloroplast analysis, 18S rRNA sequencing, photosynthetic pigment analysis and microscopy. Consistent with our hypothesis, chloride and total nitrogen concentrations were among the most important statistical factors explaining the differences in taxonomic composition. These factors were positively correlated with the abundance of cryptophytes, haptophytes, and cyanobacteria. Ice-cover was also a major structuring factor, with clear differences between the winter communities and those of the open-water period. Nitrifying and methane oxidizing bacteria were more abundant in winter, suggesting the importance of anaerobic sediment processes and release of reduced compounds into the ice-covered water columns. The four methods for eukaryotic analysis provided complementary information. The 18S rRNA observations were strongly influenced by the presence of ribosome-rich ciliates, but revealed a much higher degree of taxonomic richness and greater separation of lakes, seasonal changes and potential salinity effects than the other methods.

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.

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.

Space-time dynamics in monitoring neotropical fish communities using eDNA metabarcoding

The biodiverse Neotropical ecoregion remains insufficiently assessed, poorly managed, and threatened by unregulated human activities. Novel, rapid and cost-effective DNA-based approaches are valuable to improve understanding of the biological communities and for biomonitoring in remote areas. Here, we evaluate the potential of environmental DNA (eDNA) metabarcoding for assessing the structure and distribution of fish communities by analysing water and sediment from 11 locations along the Jequitinhonha River catchment (Brazil). Each site was sampled twice, before and after a major rain event in a five-week period and fish diversity was estimated using high-throughput sequencing of 12S rRNA amplicons. In total, 252 Molecular Operational Taxonomic Units (MOTUs) and 34 fish species were recovered, including endemic, introduced, and previously unrecorded species for this basin. Spatio-temporal variation of eDNA from fish assemblages was observed and species richness was nearly twice as high before the major rain event compared to afterwards. Yet, peaks of diversity were primarily associated with only four of the locations. No correlation between β-diversity and longitudinal distance or presence of dams was detected, but low species richness observed at sites located near dams might that these anthropogenic barriers may have an impact on local fish diversity. Unexpectedly high α-diversity levels recorded at the river mouth suggest that these sections should be further evaluated as putative "eDNA reservoirs" for rapid monitoring. By uncovering spatio-temporal changes, unrecorded biodiversity components, and putative anthropogenic impacts on fish assemblages, we further strengthen the potential of eDNA metabarcoding as a biomonitoring tool, especially in regions often neglected or difficult to access.

Environmental DNA metabarcoding reveals estuarine benthic community response to nutrient enrichment - Evidence from an in-situ experiment

Nutrient loading is a major threat to estuaries and coastal environments worldwide, therefore, it is critical that we have good monitoring tools to detect early signs of degradation in these ecologically important and vulnerable ecosystems. Traditionally, bottom-dwelling macroinvertebrates have been used for ecological health assessment but recent advances in environmental genomics mean we can now characterize less visible forms of biodiversity, offering a more holistic view of the ecosystem and potentially providing early warning signals of disturbance. We carried out a manipulative nutrient enrichment experiment (0, 150 and 600 g N fertilizer m^-2) in two estuaries in New Zealand to assess the effects of nutrient loading on benthic communities. After seven months of enrichment, environmental DNA (eDNA) metabarcoding was used to examine the response of eukaryotic (18S rRNA), diatom only (rbcL) and bacterial (16S rRNA) communities. Multivariate analyses demonstrated changes in eukaryotic, diatom and bacterial communities in response to nutrient enrichment at both sites, despite differing environmental conditions. These patterns aligned with changes in macrofaunal communities identified using traditional morphological techniques, confirming concordance between disturbance indicators detected by eDNA and current monitoring approaches. Clear shifts in eukaryotic and bacterial indicator taxa were seen in response to nutrient loading while changes in diatom only communities were more subtle. Community changes were discernible between 0 and 150 g N m^-2 treatments, suggesting that estuary health assessment tools could be developed to detect early signs of degradation. Increasing variation in community structure associated with nutrient loading could also be used as an indicator of stress or approaching tipping points. This work represents a first step towards the development of molecular-based estuary monitoring tools, which could provide a more holistic and standardized approach to ecosystem health assessment with faster turn-around times and lower costs.

Comparative analysis of morphological and molecular approaches integrated into the study of the dinoflagellate biodiversity within the recently deposited Black Sea sediments - benefits and drawbacks

One of the assets, assigned to the phytoplankton resting stages, is that of serving as the “memory” of the aquatic ecosystems and preserved biodiversity in the course of time. However, an accurate cyst identification proves to be a more difficult and extremely challenging process, even today. In order to gain a better taxonomic coverage of cyst assemblages in the Black Sea, an integrated approach of the classical morphological identification with metabarcoding methods (MySeq sequencing of V7-V9 regions of the 18S rDNA) was applied on thirteen surface sediment samples collected from different sites. A total number of 112 dinoflagellate taxa was detected at the species level and ascribed to 51 genera. In general, it is the molecular analysis that yields a higher number of taxa as compared to those obtained through the morphological taxonomy (66 taxa based on the DNA sequences versus 56 morphologically-identified taxa). Besides, it should be pointed out that the integrated dataset includes 14 potentially toxic dinoflagellate species. Discerned, subsequently, was a good dataset consistency for ten species, followed by some discrepancies as to a number of taxa, identified with one of the methods only, due to specific methodological biases. On the whole, it could be concluded that the combination of morphological and molecular methods is likely to increase the potential for a more reliable taxonomic assessment of phytoplankton diversity in marine sediments which, in turn, proves conclusively the utmost importance of the integrated approach.

Consistency of Targeted Metatranscriptomics and Morphological Characterization of Phytoplankton Communities

The composition of phytoplankton community is the basis for environmental monitoring and assessment of the ecological status of aquatic ecosystems. Community composition studies of phytoplankton have been based on time-consuming and expertise-demanding light microscopy analyses. Molecular methods have the potential to replace microscopy, but the high copy number variation of ribosomal genes and the lack of universal primers for simultaneous amplification of prokaryotic and eukaryotic genes complicate data interpretation. In this study, we used our previously developed directional primer-independent high-throughput sequencing (HTS) approach to analyze 16S and 18S rRNA community structures. Comparison of 83 boreal lake samples showed that the relative abundances of eukaryotic phytoplankton at class level and prokaryotic cyanobacteria at order level were consistent between HTS and microscopy results. At the genus level, the results had low correspondence, mainly due to lack of sequences in the reference library. HTS was superior to identify genera that are extensively represented in the reference databases but lack specific morphological characteristics. Targeted metatranscriptomics proved to be a feasible method to complement the microscopy analysis. The metatranscriptomics can also be applied without linking the sequences to taxonomy. However, direct indexing of the sequences to their environmental indicator values needs collections of more comprehensive sample sets, as long as the coverage of molecular barcodes of eukaryotic species remains insufficient.

Comparing metabarcoding and morphological approaches to identify phytoplankton taxa associated with harmful algal blooms

Molecular techniques are expected to be highly useful in detecting taxa causing harmful algal blooms (HABs). This is the first report in Canada evaluating HABs-related species identification using a combination of morphological and molecular approaches. Microscopy, quantitative polymerase chain reaction (qPCR), and metabarcoding with multiple markers (i.e., 16S, 18S-dinoflagellate and 18S-diatom, large subunit (28S) rDNA) were applied on samples ( n = 54) containing suspected harmful algae (e.g., Alexandrium spp., Chattonella sp., Chrysochromulina spp., Dictyocha spp., Heterosigma akashiwo, Protoceratium reticulatum, Pseudochattonella verruculosa, Pseudo-nitzschia spp., Pseudopedinella sp.). Owing to methodology limitations, qPCR result interpretation was limited, although good detectability occurred using previously published assays for Alexandrium tamarense, H. akashiwo, and P. verruculosa. Overall, the multiple-marker metabarcoding results were superior to the morphology-based methods, with the exception of taxa from the silicoflagellate group. The combined results using both 18S markers and the 28S marker together closely corresponded with morphological identification of targeted species, providing the best overall taxonomic coverage and resolution. The most numerous unique taxa were identified using the 18S-dinoflagellate amplicon, and the best resolution to the species level occurred using the 28S amplicon. Molecular techniques are therefore promising for HABs taxa detection but currently depend on deploying multiple markers for metabarcoding.

Very Low Phytoplankton Diversity in a Tropical Saline-Alkaline Lake, with Co-dominance of Arthrospira fusiformis (Cyanobacteria) and Picocystis salinarum (Chlorophyta)

Lake Dziani Dzaha (Mayotte Island, Indian Ocean) is a tropical thalassohaline lake which geochemical and biological conditions make it a unique aquatic ecosystem considered as a modern analogue of Precambrian environments. In the present study, we focused on the diversity of phytoplanktonic communities, which produce very high and stable biomass (mean_2014-2015 = 652 ± 179 μg chlorophyll a L^-1). As predicted by classical community ecology paradigms, and as observed in similar environments, a single species is expected to dominate the phytoplanktonic communities. To test this hypothesis, we sampled water column in the deepest part of the lake (18 m) during rainy and dry seasons for two consecutive years. Phytoplanktonic communities were characterized using a combination of metagenomic, microscopy-based and flow cytometry approaches, and we used statistical modeling to identify the environmental factors determining the abundance of dominant organisms. As hypothesized, the overall diversity of the phytoplanktonic communities was very low (15 OTUs), but we observed a co-dominance of two, and not only one, OTUs, viz., Arthrospira fusiformis (Cyanobacteria) and Picocystis salinarum (Chlorophyta). We observed a decrease in the abundance of these co-dominant taxa along the depth profile and identified the adverse environmental factors driving this decline. The functional traits measured on isolated strains of these two taxa (i.e., size, pigment composition, and concentration) are then compared and discussed to explain their capacity to cope with the extreme environmental conditions encountered in the aphotic, anoxic, and sulfidic layers of the water column of Lake Dziani Dzaha.

Environmental DNA: A New Low-Cost Monitoring Tool for Pathogens in Salmonid Aquaculture

Environmental DNA (eDNA) metabarcoding is a relatively new monitoring tool featuring in an increasing number of applications such as the facilitation of the accurate and cost effective detection of species in environmental samples. eDNA monitoring is likely to have a major impact on the ability of salmonid aquaculture industry producers and their regulators to detect the presence and abundance of pathogens and other biological threats in the surrounding environment. However, for eDNA metabarcoding to develop into a useful bio-monitoring tool it is necessary to (a) validate that sequence datasets derived from amplification of metabarcoding markers reflect the true species' identity, (b) test the sensitivity under different abundance levels and environmental noise and (c) establish a low-cost sequencing method to enable the bulk processing of field samples. In this study, we employed an elaborate experimental design whereby different combinations of five biological agents were crossed at three abundance levels and exposed to sterile pre-filtered and unfiltered seawater, prior to coarse filtering and then eDNA ultrafiltration of the resultant material. We then benchmarked the low-cost, scalable, Ion Torrent sequencing method against the current gold-standard Illumina platform for eDNA surveys in aquaculture. Based on amplicon-seq of the 18S SSU rDNA v9 region, we were able to identify two parasites (Lepeophtheirus salmonis and Paramoeba perurans) to species level, whereas the microalgae species Prymnesium parvum, Pseudo-nitzschia seriata, and P. delicatissima could be assigned correctly only to the genus level. Illumina and Ion Torrent provided near identical results in terms of community composition in our samples, whereas Ion Torrent was more sensitive in detecting species richness when the medium was unfiltered seawater. Both methods were able to reflect the difference in relative abundance between treatments in 4 out of 5 species when samples were exposed to the unfiltered seawater, despite the significant amount of background noise from both bacteria and eukaryotes. Our findings indicate that eDNA metabarcoding offers significant potential in the monitoring of species harmful to aquaculture and for this purpose, the low-cost Ion Torrent sequencing is as accurate as Illumina in determining differences in their relative abundance between samples.

The future of biotic indices in the ecogenomic era: Integrating (e)DNA metabarcoding in biological assessment of aquatic ecosystems

The bioassessment of aquatic ecosystems is currently based on various biotic indices that use the occurrence and/or abundance of selected taxonomic groups to define ecological status. These conventional indices have some limitations, often related to difficulties in morphological identification of bioindicator taxa. Recent development of DNA barcoding and metabarcoding could potentially alleviate some of these limitations, by using DNA sequences instead of morphology to identify organisms and to characterize a given ecosystem. In this paper, we review the structure of conventional biotic indices, and we present the results of pilot metabarcoding studies using environmental DNA to infer biotic indices. We discuss the main advantages and pitfalls of metabarcoding approaches to assess parameters such as richness, abundance, taxonomic composition and species ecological values, to be used for calculation of biotic indices. We present some future developments to fully exploit the potential of metabarcoding data and improve the accuracy and precision of their analysis. We also propose some recommendations for the future integration of DNA metabarcoding to routine biomonitoring programs.

Response of Microbial Communities to Changing Climate Conditions During Summer Cyanobacterial Blooms in the Baltic Sea

Frequencies and biomass of Baltic Sea cyanobacterial blooms are expected to be higher in future climate conditions, but also of longer duration as a result of increased sea surface temperature. Concurrently, climate predictions indicate a reduced salinity in the Baltic Sea. These climate-driven changes are expected to alter not solely the phytoplankton community but also the role of microbial communities for nutrient remineralization. Here, we present the response of summer plankton communities (filamentous cyanobacteria, picocyanobacteria, and heterotrophic bacteria) to the interplay of increasing temperature (from 16 to 18°C and 20°C) and reduced salinity (from salinity 6.9 to 5.9) in the Baltic Proper (NW Gotland Sea) using a microcosm approach. Warmer temperatures led to an earlier peak of cyanobacterial biomass, while yields were reduced. These conditions caused a decrease of nitrogen-fixers (Dolichospermum sp.) biomass, while non nitrogen-fixers (Pseudanabaena sp.) increased. Salinity reduction did not affect cyanobacterial growth nor community composition. Among heterotrophic bacteria, Actinobacteria showed preference for high temperature, while Gammaproteobacteria thrived at in situ temperature. Heterotrophic bacteria community changed drastically at lower salinity and resembled communities at high temperature. Picocyanobacteria and heterotrophic bacterial biomass had a pronounced increase associated with the decay of filamentous cyanobacteria. This suggests that shifts in community composition of heterotrophic bacteria are influenced both directly by abiotic factors (temperature and salinity) and potentially indirectly by cyanobacteria. Our findings suggest that at warmer temperature, lower yield of photosynthetic cyanobacteria combined with lower proportion of nitrogen-fixers in the community could result in lower carbon export to the marine food web with consequences for the decomposer community of heterotrophic bacteria.

Rapid detection and quantification of the potentially toxic cyanobacterium Planktothrix rubescens by in-vivo fluorometry and flow cytometry

We combined profiling of the bloom-forming and potentially toxigenic cyanobacterium Planktothrix rubescens using a multiparameter probe equipped with a phycoerythrin sensor (in vivo fluorometry, IVL) in Lake Mondsee, Austria, with flow cytometric live analyses of discrete samples taken from several depths in the upper 20 m of the water column. Results obtained by IVL and acoustic flow cytometry (AFC) were compared to microscopic analyses of integrated (0-21 m) water samples using fixed material. This comparison was made because the integrated samples are used for the Austrian monitoring programme according to the EU Water Framework Directive. We demonstrate that AFC provides quantitative analyses of the filaments of P. rubescens that are significantly correlated to IVF and microscopic analyses, allowing rapid (within hours) and more precise calculation of P. rubescens biomass than estimates derived from IVL. Our analysis shows that vertically integrated water samples provide unreliable information on the concentration of P. rubescens in the upper surface waters and on the peak concentration of P. rubescens within the water column. We conclude that the protocol that we developed is superior to the current monitoring practice.

Microbial Diversity and Toxin Risk in Tropical Freshwater Reservoirs of Cape Verde

The Cape Verde islands are part of the African Sahelian arid belt that possesses an erratic rain pattern prompting the need for water reservoirs, which are now critical for the country&rsquo;s sustainability. Worldwide, freshwater cyanobacterial blooms are increasing in frequency due to global climate change and the eutrophication of water bodies, particularly in reservoirs. To date, there have been no risk assessments of cyanobacterial toxin production in these man-made structures. We evaluated this potential risk using 16S rRNA gene amplicon sequencing and full metagenome sequencing in freshwater reservoirs of Cape Verde. Our analysis revealed the presence of several potentially toxic cyanobacterial genera in all sampled reservoirs. Faveta potentially toxic and bloom-forming Microcystis sp., dominated our samples, while a Cryptomonas green algae and Gammaproteobacteria dominated Saquinho and Poil&atilde;o reservoirs. We reconstructed and assembled the Microcystis genome, extracted from the metagenome of bulk DNA from Faveta water. Phylogenetic analysis of Microcystis cf. aeruginosa CV01&rsquo;s genome revealed its close relationship with other Microcystis genomes, as well as clustering with other continental African strains, suggesting geographical coherency. In addition, it revealed several clusters of known toxin-producing genes. This survey reinforces the need to better understand the country&rsquo;s microbial ecology as a whole of water reservoirs on the rise.

People, pollution and pathogens - Global change impacts in mountain freshwater ecosystems

Mountain catchments provide for the livelihood of more than half of humankind, and have become a key destination for tourist and recreation activities globally. Mountain ecosystems are generally considered to be less complex and less species diverse due to the harsh environmental conditions. As such, they are also more sensitive to the various impacts of the Anthropocene. For this reason, mountain regions may serve as sentinels of change and provide ideal ecosystems for studying climate and global change impacts on biodiversity. We here review different facets of anthropogenic impacts on mountain freshwater ecosystems. We put particular focus on micropollutants and their distribution and redistribution due to hydrological extremes, their direct influence on water quality and their indirect influence on ecosystem health via changes of freshwater species and their interactions. We show that those changes may drive pathogen establishment in new environments with harmful consequences for freshwater species, but also for the human population. Based on the reviewed literature, we recommend reconstructing the recent past of anthropogenic impact through sediment analyses, to focus efforts on small, but highly productive waterbodies, and to collect data on the occurrence and variability of microorganisms, biofilms, plankton species and key species, such as amphibians due to their bioindicator value for ecosystem health and water quality. The newly gained knowledge can then be used to develop a comprehensive framework of indicators to robustly inform policy and decision making on current and future risks for ecosystem health and human well-being.

Sample Preservation, DNA or RNA Extraction and Data Analysis for High-Throughput Phytoplankton Community Sequencing

Phytoplankton is the basis for aquatic food webs and mirrors the water quality. Conventionally, phytoplankton analysis has been done using time consuming and partly subjective microscopic observations, but next generation sequencing (NGS) technologies provide promising potential for rapid automated examination of environmental samples. Because many phytoplankton species have tough cell walls, methods for cell lysis and DNA or RNA isolation need to be efficient to allow unbiased nucleic acid retrieval. Here, we analyzed how two phytoplankton preservation methods, three commercial DNA extraction kits and their improvements, three RNA extraction methods, and two data analysis procedures affected the results of the NGS analysis. A mock community was pooled from phytoplankton species with variation in nucleus size and cell wall hardness. Although the study showed potential for studying Lugol-preserved sample collections, it demonstrated critical challenges in the DNA-based phytoplankton analysis in overall. The 18S rRNA gene sequencing output was highly affected by the variation in the rRNA gene copy numbers per cell, while sample preservation and nucleic acid extraction methods formed another source of variation. At the top, sequence-specific variation in the data quality introduced unexpected bioinformatics bias when the sliding-window method was used for the quality trimming of the Ion Torrent data. While DNA-based analyses did not correlate with biomasses or cell numbers of the mock community, rRNA-based analyses were less affected by different RNA extraction procedures and had better match with the biomasses, dry weight and carbon contents, and are therefore recommended for quantitative phytoplankton analyses.

Revealing higher than expected meiofaunal diversity in Antarctic sediments: a metabarcoding approach

An increasing number of studies are showing that Antarctic mega- and macrofauna are highly diverse, however, little is known about meiofaunal biodiversity in sediment communities, which are a vital part of a healthy and functional ecosystem. This is the first study to analyse community DNA (targeting meiofauna) using metabarcoding to investigate biodiversity levels in sediment communities of the Antarctic Peninsula. The results show that almost all of the meiofaunal biodiversity in the benthic habitat has yet to be characterised, levels of biodiversity were higher than expected and similar to temperate regions, albeit with the existence of potentially new and locally adapted species never described before at the molecular level. The Rothera meiofaunal sample sites showed four dominant eukaryotic groups, the nematodes, arthropods, platyhelminthes, and the annelids; some of which could comprise species complexes. Comparisons with deep-sea data from the same region suggest little exchange of Operational Taxonomic Units (OTUs) between depths with the nematodes prevalent at all depths, but sharing the shallow water benthos with the copepods. This study provides a preliminary analysis of benthic Antarctic Peninsula meiofauna using high throughput sequencing which substantiates how little is known on the biodiversity of one of the most diverse, yet underexplored communities of the Antarctic: the benthos.

Characterization of bacterial community associated with phytoplankton bloom in a eutrophic lake in South Norway using 16S rRNA gene amplicon sequence analysis

Interactions between different phytoplankton taxa and heterotrophic bacterial communities within aquatic environments can differentially support growth of various heterotrophic bacterial species. In this study, phytoplankton diversity was studied using traditional microscopic techniques and the bacterial communities associated with phytoplankton bloom were studied using High Throughput Sequencing (HTS) analysis of 16S rRNA gene amplicons from the V1-V3 and V3-V4 hypervariable regions. Samples were collected from Lake Akersvannet, a eutrophic lake in South Norway, during the growth season from June to August 2013. Microscopic examination revealed that the phytoplankton community was mostly represented by Cyanobacteria and the dinoflagellate Ceratium hirundinella. The HTS results revealed that Proteobacteria (Alpha, Beta, and Gamma), Bacteriodetes, Cyanobacteria, Actinobacteria and Verrucomicrobia dominated the bacterial community, with varying relative abundances throughout the sampling season. Species level identification of Cyanobacteria showed a mixed population of Aphanizomenon flos-aquae, Microcystis aeruginosa and Woronichinia naegeliana. A significant proportion of the microbial community was composed of unclassified taxa which might represent locally adapted freshwater bacterial groups. Comparison of cyanobacterial species composition from HTS and microscopy revealed quantitative discrepancies, indicating a need for cross validation of results. To our knowledge, this is the first study that uses HTS methods for studying the bacterial community associated with phytoplankton blooms in a Norwegian lake. The study demonstrates the value of considering results from multiple methods when studying bacterial communities.

Novel Primer Sets for Next Generation Sequencing-Based Analyses of Water Quality

Next generation sequencing (NGS) has rapidly become an invaluable tool for the detection, identification and relative quantification of environmental microorganisms. Here, we demonstrate two new 16S rDNA primer sets, which are compatible with NGS approaches and are primarily for use in water quality studies. Compared to 16S rRNA gene based universal primers, in silico and experimental analyses demonstrated that the new primers showed increased specificity for the Cyanobacteria and Proteobacteria phyla, allowing increased sensitivity for the detection, identification and relative quantification of toxic bloom-forming microalgae, microbial water quality bioindicators and common pathogens. Significantly, Cyanobacterial and Proteobacterial sequences accounted for ca. 95% of all sequences obtained within NGS runs (when compared to ca. 50% with standard universal NGS primers), providing higher sensitivity and greater phylogenetic resolution of key water quality microbial groups. The increased selectivity of the new primers allow the parallel sequencing of more samples through reduced sequence retrieval levels required to detect target groups, potentially reducing NGS costs by 50% but still guaranteeing optimal coverage and species discrimination.

Trophic state and geographic gradients influence planktonic cyanobacterial diversity and distribution in New Zealand lakes

Cyanobacteria are commonly associated with eutrophic lakes, where they often form blooms and produce toxins. However, they are a ubiquitous component of phytoplankton in lakes of widely varying trophic status. We hypothesised that cyanobacterial diversity would vary among lakes of differing trophic status, but that the relative importance of geographical and hydromorphological characteristics driving these patterns would differ across trophic groups. DNA from 143 New Zealand lakes that spanned a range of geographic, hydromorphological and trophic gradients was analysed using automated rRNA intergenic spacer analysis and screened for genes involved in cyanotoxin production. Statistical analysis revealed significant delineation among cyanobacterial communities from different trophic classes. Multivariate regression indicated that geographical features (latitude, longitude and altitude) were significant in driving cyanobacterial community structure; however, partitioning of their effects varied among trophic categories. High-throughput sequencing was undertaken on selected samples to investigate their taxonomic composition. The most abundant and diverse (71 operational taxonomic units) taxon across all lake types was the picocyanobacteria genus Synechococcus Cyanotoxins (microcystins n = 23, anatoxins n = 1) were only detected in eutrophic lowland lakes. Collectively, these data infer that increasing eutrophication of lakes will have broad-scale impacts on planktonic cyanobacteria diversity and the prevalence of cyanotoxins.

Design and Evaluation of Illumina MiSeq-Compatible, 18S rRNA Gene-Specific Primers for Improved Characterization of Mixed Phototrophic Communities

The use of high-throughput sequencing technologies with the 16S rRNA gene for characterization of bacterial and archaeal communities has become routine. However, the adoption of sequencing methods for eukaryotes has been slow, despite their significance to natural and engineered systems. There are large variations among the target genes used for amplicon sequencing, and for the 18S rRNA gene, there is no consensus on which hypervariable region provides the most suitable representation of diversity. Additionally, it is unclear how much PCR/sequencing bias affects the depiction of community structure using current primers. The present study amplified the V4 and V8-V9 regions from seven microalgal mock communities as well as eukaryotic communities from freshwater, coastal, and wastewater samples to examine the effect of PCR/sequencing bias on community structure and membership. We found that degeneracies on the 3' end of the current V4-specific primers impact read length and mean relative abundance. Furthermore, the PCR/sequencing error is markedly higher for GC-rich members than for communities with balanced GC content. Importantly, the V4 region failed to reliably capture 2 of the 12 mock community members, and the V8-V9 hypervariable region more accurately represents mean relative abundance and alpha and beta diversity. Overall, the V4 and V8-V9 regions show similar community representations over freshwater, coastal, and wastewater environments, but specific samples show markedly different communities. These results indicate that multiple primer sets may be advantageous for gaining a more complete understanding of community structure and highlight the importance of including mock communities composed of species of interest.

IMPORTANCE

The quantification of error associated with community representation by amplicon sequencing is a critical challenge that is often ignored. When target genes are amplified using currently available primers, differential amplification efficiencies result in inaccurate estimates of community structure. The extent to which amplification bias affects community representation and the accuracy with which different gene targets represent community structure are not known. As a result, there is no consensus on which region provides the most suitable representation of diversity for eukaryotes. This study determined the accuracy with which commonly used 18S rRNA gene primer sets represent community structure and identified particular biases related to PCR amplification and Illumina MiSeq sequencing in order to more accurately study eukaryotic microbial communities.

Phenology of cryptomonads and the CRY1 lineage in a coastal brackish lagoon (Vistula Lagoon, Baltic Sea)

Cryptomonadales have acquired their plastids by secondary endosymbiosis. A novel clade-CRY1-has been discovered at the base of the Cryptomonadales tree, but it remains unknown whether it contains plastids. Cryptomonadales are also an important component of phytoplankton assemblages. However, they cannot be readily identified in fixed samples, and knowledge on dynamics and distribution of specific taxa is scarce. We investigated the phenology of the CRY1 lineage, three cryptomonadales clades and a species Proteomonas sulcata in a brackish lagoon of the Baltic Sea (salinity 0.3-3.9) using fluorescence in situ hybridization. A newly design probe revealed that specimens of the CRY1 lineage were aplastidic. This adds evidence against the chromalveolate hypothesis, and suggests that the evolution of cryptomonadales' plastids might have been shorter than is currently assumed. The CRY1 lineage was the most abundant cryptomonad clade in the lagoon. All of the studied cryptomonads peaked in spring at the most freshwater station, except for P. sulcata that peaked in summer and autumn. Salinity and concentration of dissolved inorganic nitrogen most significantly affected their distribution and dynamics. Our findings contribute to the ecology and evolution of cryptomonads, and may advance understanding of evolutionary relationships within the eukaryotic tree of life.

Development of a cost-effective metabarcoding strategy for analysis of the marine phytoplankton community

We developed a cost-effective metabarcoding strategy to analyze phytoplankton community structure using the Illumina MiSeq system. The amplicons (404-411 bp) obtained by end-pairing of two reads were sufficiently long to distinguish algal species and provided barcode data equivalent to those generated with the Roche 454 system, but at less than 1/20th of the cost. The original universal primer sequences targeting the 23S rDNA region and the PCR strategy were both modified, and this resulted in higher numbers of eukaryotic algal sequences by excluding non-photosynthetic proteobacterial sequences supporting effectiveness of this strategy. The novel strategy was used to analyze the phytoplankton community structure of six water samples from the East/Japan Sea: surface and 50 m depths at coastal and open-sea sites, with collections in May and July 2014. In total, 345 operational taxonomic units (OTUs) were identified, which covered most of the prokaryotic and eukaryotic algal phyla, including Dinophyta, Rhodophyta, Ochrophyta, Chlorophyta, Streptophyta, Cryptophyta, Haptophyta, and Cyanophyta. This highlights the importance of plastid 23S primers, which perform better than the currently used 16S primers for phytoplankton community surveys. The findings also revealed that more efforts should be made to update 23S rDNA sequences as well as those of 16S in the databases. Analysis of algal proportions in the six samples showed that community structure differed depending on location, depth and season. Across the six samples evaluated, the numbers of OTUs in each phylum were similar but their relative proportions varied. This novel strategy would allow laboratories to analyze large numbers of samples at reasonable expense, whereas this has not been possible to date due to cost and time. In addition, we expect that this strategy will generate a large amount of novel data that could potentially change established methods and tools that are currently used in the realms of oceanography and marine ecology.