Monitoring of the toxic dinoflagellate Alexandrium catenella in Osaka Bay, Japan using a massively parallel sequencing (MPS)-based technique

Two novel glutathione S-transferase (GST) genes in the toxic marine dinoflagellate Alexandrium pacificum and their transcriptional responses to environmental contaminants

The present study identified two novel glutathione S-transferase (GST) genes from the toxic dinoflagellate Alexandrium pacificum and examined their molecular characteristics and transcriptional responses to algicides and environmental contaminants. Bioinformatic analysis revealed that both ApGSTs are cytosolic, belonging to the chi-like class (ApGST1) and an undefined class (ApGST2). The overall expression of ApGSTs showed similar patterns depending on the exposed contaminants, while they were differently regulated by polychlorinated biphenyl (PCB). Copper treatments (CuCl2 and CuSO4) did not significantly induce the expression of ApGSTs. The highest up-regulations of ApGST1 and ApGST2 were under 6-h treatments of 0.10 and 0.50 mg L-1 NaOCl. Interestingly, only ApGST1 increased significantly after 0.10, 0.50, and 1.00 mg L-1 of PCB exposure (6 h). Intracellular reactive oxygen species (ROS) increased considerably under NaOCl; however, it was not significantly higher in the PCB-treated cells. GST activity was increased by NaOCl and PCB treatments, but only PCB caused apoptosis. These results suggest that GSTs are involved in the first line of phase II detoxification, protecting dinoflagellate cells against oxidative damage.

A comparison between the FlowCam 8100, microscopy, and sandwich hybridization assay for quantifying abundances of the saxitoxin-producing dinoflagellate, Alexandrium catenella

Light microscopy, FlowCam, and sandwich hybridization assay (SHA) are three approaches that facilitate the monitoring of harmful algal bloom (HAB) forming phytoplankton. Yet, cross-comparisons among these techniques have not been conducted. This study addressed that gap using the saxitoxin-producing 'red tide' dinoflagellate Alexandrium catenella, a species responsible for blooms and paralytic shellfish poisoning worldwide. To achieve this goal, the dynamic ranges of each technique were compared using A. catenella cultures spanning low (pre-bloom), moderate (bloom), and high (dense bloom) levels. To assess field detection, water samples containing very low (<3 cells mL^-1) A. catenella levels were collected from Long Island Sound, USA (Jun-Aug 2021) and evaluated using each method. Field samples were also spiked with A. catenella to high (160 cells mL^-1) or low (40 cells mL^-1) concentrations. In general, microscopy, FlowCam, and SHA returned comparable A. catenella cell concentrations for all tests. Mean cell concentrations from laboratory intercalibration experiments were not significantly different for any method or concentration (ANOVA, p > 0.05). However, relative to microscopy at times SHA produced non-detect signals <2 cells mL^-1 in field samples and the FlowCam slightly underestimated cell concentrations when A. catenella abundances were high in laboratory and field samples. Mean cell concentrations of spike experiments were not significantly different for any test date, sampling location, or method, despite variability among methods within the high concentration treatment (ANOVA, p > 0.05 for all treatments). Findings are relevant to HAB researchers, managers, and public health officials because they help reconcile disparate cell abundance datasets that inform numerical models and enhance HAB monitoring and prediction. Results are also likely broadly applicable to several HAB species.

The toxic cosmopolitan cyanobacteria Moorena producens: insights into distribution, ecophysiology and toxicity

Moorena producens is a benthic filamentous cyanobacteria that has been widely documented for its toxicity. This cyanobacterium colonizes both temperate (37%) and tropical (63%) regions, making it a cosmopolitan cyanobacterium with a global distribution. M. producens grows across coral reefs in multiple locations but recurringly blooms in Queensland, Australia. Today, nuisance blooms of M. producens have resulted in major disruptions to recreational activities along coastal areas and are known to cause adverse effects on organism and human health upon contact or ingestion. Specifically, marine organisms such as the green turtle Chelonia mydas and hawksbill turtle Eretmochelys imbricata were fatally poisoned by M. producens after consumption of this cyanobacterium. Reports record a range of effects on human health, from pain and blistering or even death upon ingestion of contaminated seafood. Blooms of M. producens are triggered by influxes of nitrogen, phosphate and iron, from surrounding coastal runoffs or sewage effluents. Additions of these nutrients can result in an increase in growth rate by 4-16 times. Iron bioavailability also plays a crucial role in bloom formation. A total of 231 natural products from 66 groups were identified from M. producens, with the three dominant groups: malyngamides, microcolins and dolastatins. These bioactive secondary metabolites have displayed toxicities against a range of carcinoma cell lines and organisms such as brine shrimp Artemia salina and goldfish Carassius auratus. This review provides a thorough insight to the distribution, ecophysiology and toxicity of M. producens, with reports on bloom events and implications on organism and human health.

Projecting Future Climate Change-Mediated Impacts in Three Paralytic Shellfish Toxins-Producing Dinoflagellate Species

Simple Summary

Harmful algal blooms present a particular risk for marine ecosystems and human health alike. In this sense, it is important to accurately predict how toxin-producing microalgae could be affected by future climate change. The present study applied species distribution models (SDMs) to project the potential changes in the habitat suitability and distribution of three key paralytic shellfish toxin (PST)-producing dinoflagellate species (i.e., Alexandrium catenella, A. minutum, and Gymnodinium catenatum), up to 2040/50 and 2090/2100, across four different greenhouse gas emission scenarios, and using four abiotic predictors (i.e., sea surface temperature, salinity, current velocity, and bathymetry). In general, considerable contractions were observed for all three species in the lower latitudes of their distribution, together with projected expansions into higher latitudes, particularly in the Northern Hemisphere. This study aims to entice further research on the future biogeographical impacts of climate change in toxin-producing microalgae species while, at the same time, helping to advise the correct environmental management of coastal habitats and ecosystems.

Abstract

Toxin-producing microalgae present a significant environmental risk for ecosystems and human societies when they reach concentrations that affect other aquatic organisms or human health. Harmful algal blooms (HAB) have been linked to mass wildlife die-offs and human food poisoning episodes, and climate change has the potential to alter the frequency, magnitude, and geographical extent of such events. Thus, a framework of species distribution models (SDMs), employing MaxEnt modeling, was used to project changes in habitat suitability and distribution of three key paralytic shellfish toxin (PST)-producing dinoflagellate species (i.e., Alexandrium catenella, A. minutum, and Gymnodinium catenatum), up to 2050 and 2100, across four representative concentration pathway scenarios (RCP-2.6, 4.5, 6.0, and 8.5; CMIP5). Despite slightly different responses at the regional level, the global habitat suitability has decreased for all the species, leading to an overall contraction in their tropical and sub-tropical ranges, while considerable expansions are projected in higher latitudes, particularly in the Northern Hemisphere, suggesting poleward distributional shifts. Such trends were exacerbated with increasing RCP severity. Yet, further research is required, with a greater assemblage of environmental predictors and improved occurrence datasets, to gain a more holistic understanding of the potential impacts of climate change on PST-producing species.

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 &lt; 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.

Comparing PCR-generated artifacts of different polymerases for improved accuracy of DNA metabarcoding

Accuracy of PCR amplification is vital for obtaining reliable amplicon-sequencing results by metabarcoding. Here, we performed a comparative analysis of error profiles in the PCR products by 14 different PCR kits using a mock eukaryotic community DNA sample mimicking metabarcoding analysis. To prepare a mock eukaryotic community from the marine environment, equal amounts of plasmid DNA from 40 microalgal species were mixed and used for amplicon-sequencing by a high-throughput sequencing approach. To compare the differences in PCR kits used for this experiment, we focused on the following seven parameters: 1) Quality, 2) Chimera, 3) Blast top hit accuracy, 4) Deletion, 5) Insertion, 6) Base substitution and 7) Amplification bias amongst species. The results showed statistically significant differences (p &lt; 0.05) for all of the seven parameters depending on the PCR kits used. These differences may result from the different DNA polymerases included in each kit, although the result can also be influenced by PCR reaction conditions. Simultaneous analysis of several parameters suggested that kits containing KOD plus Neo (TOYOBO) and HotStart Taq DNA polymerase (BiONEER, CA, US) at the annealing temperature of 65 °C displayed better results in terms of parameters associated with chimeras, top hit similarity and deletions.

Zooplankton Population and Community Structure Changes in Response to a Harmful Algal Bloom Caused by Prorocentrum donghaiense in the East China Sea

Blooms of the dinoflagellate Prorocentrum donghaiense have had adverse impacts on marine ecosystems. However, ecological details, particularly the impacts and processes of the P. donghaiense bloom on the zooplankton community structure are poorly known. We investigated the changes of zooplankton communities in situ within the whole process of a P. donghaiense bloom in the coastal waters in southern Zhejiang Province, China, in May 2016. Results showed that ecological changes during the blooms of P. donghaiense could be divided into three major phases, namely the growth, maintenance, and dissipation phases with regard to the cell abundance of P. donghaiense by bottle sampling of plankton. A total of 42 species of zooplankton were identified. The average abundance and species number of zooplankton in the growth phase were significantly higher than those in the maintenance and dissipation phases. It is shown that the top-two highest proportions of zooplankton in the growth phase were small jellyfishes and copepods, while small jellyfishes and chaetognaths, and copepoda larvae and chaetognaths were the top-two highest in the maintenance and dissipation phases respectively. However, the values of biodiversity index have no statistically significant differences between the three phases. The present results suggested that P. donghaiense bloom produced significant negative impacts on the abundance and species composition of zooplankton with particular reference to copepods.

Temporal Prediction of Paralytic Shellfish Toxins in the Mussel Mytilus galloprovincialis Using a LSTM Neural Network Model from Environmental Data

Paralytic shellfish toxins (PSTs) are produced mainly by Alexandrium catenella (formerly A. tamarense). Since 2000, the National Institute of Fisheries Science (NIFS) has been providing information on PST outbreaks in Korean coastal waters at one- or two-week intervals. However, a daily forecast is essential for immediate responses to PST outbreaks. This study aimed to predict the outbreak timing of PSTs in the mussel Mytilus galloprovincialis in Jinhae Bay and along the Geoje coast in the southern coast of the Korea Peninsula. We used a long-short-term memory (LSTM) neural network model for temporal prediction of PST outbreaks from environmental data, such as water temperature (WT), tidal height, and salinity, measured at the Geojedo, Gadeokdo, and Masan tidal stations from 2006 to 2020. We found that PST outbreaks is gradually accelerated during the three years from 2018 to 2020. Because the in-situ environmental measurements had many missing data throughout the time span, we applied LSTM for gap-filling of the environmental measurements. We trained and tested the LSTM models with different combinations of environmental factors and the ground truth timing data of PST outbreaks for 5479 days as input and output. The LSTM model trained from only WT had the highest accuracy (0.9) and lowest false-alarm rate. The LSTM-based temporal prediction model may be useful as a monitoring system of PSP outbreaks in the coastal waters of southern Korean.

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.

Metabarcoding dissection of harmful algal bloom species in the East China Sea off Southern Zhejiang Province in late spring

The coastal region of the East China Sea (ECS) is a famous "hotspot" for harmful algal blooms (HABs) in China. We hypothesize that such frequent occurrences of diverse HABs in the ECS are determined by the presence of unique HAB species in this region. In this project, we identified 3966 amplicon sequence variants (ASVs) representing 35 classes in six protist phyla/divisions. Among the 237 annotated protist species, we identified 58 HAB species, of which 23 HAB species had never been previously reported in the ECS. Many HAB species also displayed unique spatial distribution patterns in the ECS. Notably, we identified three HAB species Prorocentrum donghaiense, Lebouridinium glaucum and Noctiluca scintillans in the site S05-1 with substantially elevated abundance, suggesting that this sampling site was experiencing a multiple-species HAB event. This study was the first attempt in applying ASV-based metabarcoding analysis in studying protist and HAB species in the ECS.

Development of an absolute quantification method for ribosomal RNA gene copy numbers per eukaryotic single cell by digital PCR

Recent increase of Harmful Algal Blooms (HAB) causes world-wide ecological, economical, and health issues, and more attention is paid to frequent coastal monitoring for the early detection of HAB species to prevent or reduce such impacts. Use of molecular tools in addition to traditional microscopy-based observation has become one of the promising methodologies for coastal monitoring. However, as ribosomal RNA (rRNA) genes are commonly targeted in molecular studies, variability in the rRNA gene copy number within and between species must be considered to provide quantitative information in quantitative PCR (qPCR), digital PCR (dPCR), and metabarcoding analyses. Currently, this information is only available for a limited number of species. The present study utilized a dPCR technology to quantify copy numbers of rRNA genes per single cell in 16 phytoplankton species, the majority of which are toxin-producers, using a newly developed universal primer set accompanied by a labeled probe with a fluorophore and a double-quencher. In silico PCR using the newly developed primers allowed the detection of taxa from 8 supergroups, demonstrating universality and broad coverage of the primer set. Chelex buffer was found to be suitable for DNA extraction to obtain DNA fragments with suitable size to avoid underestimation of the copy numbers. The study successfully demonstrated the first comparison of absolute quantification of 18S rRNA copy numbers per cell from 16 phytoplankton species by the dPCR technology.

Identification of influencing factors of A. catenella bloom using machine learning and numerical simulation

Alexandrium catenella (A. catenella) is a notorious algal species known to cause paralytic shellfish poisoning (PSP) in Korean coastal waters. There have been numerous studies on its temporal and spatial blooms in Korea. However, its bloom dynamics have not been fully understood because of the complexity in physical, chemical, and biological environments. This study aims to identify the factors that influence A. catenella blooms by applying a numerical model and machine learning. Intensive monitoring of A. catenella was conducted to investigate temporal variations in its population and its spatial distribution in the area with frequent occurrences of PSP bloom initiation. Moreover, a numerical model was built to analyze the ocean physical factors related to the bloom of A. catenella. Based on the information obtained from the monitored and simulated results, the decision tree (DT) method was applied to identify factors that caused the bloom. The outbreak of A. catenella was observed in the eastern coastal water of Geoje Island in 2017, recording a peak density of 4 × 10⁴ (cell L^-1). Retention time and particle scattering demonstrated that the physical force in 2017 was weaker than that in 2018, as shown by the smaller effects of advection and dispersion in 2017. The decision tree model showed that (1) water temperature below 17.21 °C was ideal for the growth of A. catenella, (2) phosphate influenced the growth of the species, and (3) cell density was accelerated with increasing retention time. The results from DT can contribute to the prediction of A. catenella blooms by determining the conditions that cause bloom initiation. Further, they can be used as a practical approach for mitigating HABs. Thus, machine learning and numerical simulation in this study can be a potential approach for effectively managing the bloom of A. catenella.

Centrodinium punctatum (Dinophyceae) produces significant levels of saxitoxin and related analogs

Centrodinium punctatum is a fusiform dinoflagellate with a global marine distribution. Due to a close phylogenetic relationship of one C. punctatum strain to Alexandrium species, toxin production of this C. punctatum strain was assessed using liquid chromatography coupled to tandem mass spectrometry. The paralytic shellfish toxin (PST) profile of C. punctatum was dominated by six analogs, i.e. STX (30%), GTX-1 (20%) and neoSTX (24%), followed by GTX-2 (9%), GTX-4 (9%) and GTX-3 (8%); deoxy-STX was also putatively identified while no gymnodimines, spirolides or goniodomins were detected. This is the first record of C. punctatum producing saxitoxins. The estimated cellular toxicity was rather elevated, between 91 and 212 pg cell^-1 (or 259 and 601 fmol cell^-1). When considering the toxicity equivalent factors, results suggest that this species can produce high cellular toxicity compared to other STX-producing dinoflagellates. Morphological details of the sulcal area and the hypotheca of Centrodinium punctatum were re-examined by scanning electron microscopy (SEM); this revealed that in the sulcal area, the left posterior sulcal plate (Ssp) is larger and longer than the left posterior sulcal plate and extended into the hypotheca. Based on the morphological observation, a revised interpretation of the sulcus and hypotheca is proposed.

Morphological and phylogenetic data do not support the split of Alexandrium into four genera

A recently published study analyzed the phylogenetic relationship between the genera Centrodinium and Alexandrium, confirming an earlier publication showing the genus Alexandrium as paraphyletic. This most recent manuscript retained the genus Alexandrium, introduced a new genus Episemicolon, resurrected two genera, Gessnerium and Protogonyaulax, and stated that: "The polyphyly [sic] of Alexandrium is solved with the split into four genera". However, these reintroduced taxa were not based on monophyletic groups. Therefore this work, if accepted, would result in replacing a single paraphyletic taxon with several non-monophyletic ones. The morphological data presented for genus characterization also do not convincingly support taxa delimitations. The combination of weak molecular phylogenetics and the lack of diagnostic traits (i.e., autapomorphies) render the applicability of the concept of limited use. The proposal to split the genus Alexandrium on the basis of our current knowledge is rejected herein. The aim here is not to present an alternative analysis and revision, but to maintain Alexandrium. A better constructed and more phylogenetically accurate revision can and should wait until more complete evidence becomes available and there is a strong reason to revise the genus Alexandrium. The reasons are explained in detail by a review of the available molecular and morphological data for species of the genera Alexandrium and Centrodinium. In addition, cyst morphology and chemotaxonomy are discussed, and the need for integrative taxonomy is highlighted.

Species specific gene expression dynamics during harmful algal blooms

Harmful algal blooms are caused by specific members of microbial communities. Understanding the dynamics of these events requires comparing the strategies developed by the problematic species to cope with environmental fluctuations to the ones developed by the other members of the community. During three consecutive years, the meta-transcriptome of micro-eukaryote communities was sequenced during blooms of the toxic dinoflagellate Alexandrium minutum. The dataset was analyzed to investigate species specific gene expression dynamics. Major shifts in gene expression were explained by the succession of different species within the community. Although expression patterns were strongly correlated with fluctuation of the abiotic environment, and more specifically with nutrient concentration, transcripts specifically involved in nutrient uptake and metabolism did not display extensive changes in gene expression. Compared to the other members of the community, A. minutum displayed a very specific expression pattern, with lower expression of photosynthesis transcripts and central metabolism genes (TCA cycle, glucose metabolism, glycolysis…) and contrasting expression pattern of ion transporters across environmental conditions. These results suggest the importance of mixotrophy, cell motility and cell-to-cell interactions during A. minutum blooms.

Harmful algal blooms significantly reduce the resource use efficiency in a coastal plankton community

Harmful algal blooms (HABs) have been investigated for their catastrophic effects on public health and aquaculture intensively, but the research about HABs effects on the diversity patterns and intrinsic functions of the plankton community based on a species identification with high resolution and accuracy has been scarce. We therefore investigated the shifts of plankton diversity via pyrosequencing during and around a natural dinoflagellate (Prorocentrum donghaiense) bloom and analyzed the effect of P. donghaiense abundance on the operationally-defined resource use efficiency (RUE) of plankton community to test our hypothesis that outbreaks of HABs will reduce RUE of the plankton community via shifting the plankton community structure, species composition in particular. We found that the species diversity of eukaryotic plankton community was significantly decreased during the bloom, as reflected in OTU (operational taxonomic unit) richness, and Pielou's evenness index. Principal coordinates analysis indicated significant difference in plankton community structure between blooming and non-blooming periods. As hypothesized, the species richness was positively correlated to RUE (defined as the ratio of phytoplankton biomass to total phosphorus), and more importantly, the cell density of P. donghaiense exhibited significant negative correlation with RUE. Our results explicitly demonstrated HABs reduce RUE via reducing species richness (corresponding to a less occupancy of the trophic niches), which supports the previously documented notion that niche partitioning enhances RUE (a key ecosystem function). Also, our work provides striking evidence for the relationship between plankton species richness (or diversity) and community function (resource use efficiency) via studying on HABs, a natural but exceptional phenomenon, in addition to revealing a profound consequence of HABs.

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.