Harmful phytoplankton diversity and dynamics in an upwelling region (Sagres, SW Portugal) revealed by ribosomal RNA microarray combined with microscopy

Lipophilic marine toxins in sediments from Arrábida marine protected area, Portugal (NE Atlantic)

During the development and senescence of harmful algal blooms (HAB), most of the algae cells not ingested by grazers or filter-feeding organisms sink to the bottom, making sediments important reservoirs of algae toxins. In this study, lipophilic marine toxins were determined in the sediments collected from depths ranging from 5 to 145 m depth in the marine protected area of Arrábida (southwest Portuguese coast). Sediments were characterized in terms of granulometry, water and organic matter content. The toxins were determined by liquid chromatography with tandem mass spectrometry. Okadaic acid (OA), dinophysistoxin-2 (DTX2), and azaspiracid-2 (AZA2), reaching concentrations up to 3.4, 1.3, and 0.13 ng/g, respectively, were found. A trend in the occurrence of DTX2 and AZA2 with sediment water and organic matter content was observed, as well as with AZA2 and depth. This study highlights the need to further investigate sediment deposition of toxins and their availability for bottom-dwelling organisms and its contamination.

Variability patterns and phenology of harmful phytoplankton blooms off southern Portugal: Looking for region-specific environmental drivers and predictors

Harmful algal blooms (HABs) negatively impact coastal ecosystems, fisheries, and human health, and their prediction has become imperative for effective coastal management. This study aimed to evaluate spatial-temporal variability patterns and phenology for key toxigenic phytoplankton species off southern Portugal, during a 6-year period, and identify region-specific environmental drivers and predictors. Total abundance of species responsible for amnesic shellfish poisoning (Pseudo-nitzschia spp.), diarrhetic shellfish poisoning (Dinophysis spp.), and paralytic shellfish poisoning (G. catenatum) were retrieved, from the National Bivalve Mollusk Monitoring System public database. Contemporaneous environmental variables were acquired from satellite remote sensing, model-derived data, and in situ observations, and generalized additive models (GAMs) were used to explore the functional relationships between HABs and environmental variables and identify region-specific predictors. Pseudo-nitzschia spp. showed a bimodal annual cycle for most coastal production areas, with spring and summer maxima, reflecting the increase in light intensity during the mixed layer shoaling stage, and the later stimulatory effects of upwelling events, with a higher bloom frequency over coastal areas subjected to stronger upwelling intensity. Dinophysis spp. exhibited a unimodal annual cycle, with spring/summer maxima associated with stratified conditions, that typically promote dinoflagellates. Dinophysis spp. blooms were delayed with respect to Pseudo-nitzschia spp. spring blooms, and followed by Pseudo-nitzschia spp. summer blooms, probably reflecting upwelling-relaxation cycles. G. catenatum occurred occasionally, namely in areas more influenced by river discharges, under weaker upwelling. Statistical-empirical models (GAMs) explained 7-8%, and 21-54% of the variability in Pseudo-nitzschia spp. and Dinophysis spp., respectively. Overall, a set of four easily accessible environmental variables, surface photosynthetically available radiation, mixed layer depth, sea surface temperature, and chlorophyll-a concentration, emerged as the most influential predictors. Additionally, over the coastal production areas along the south coast, river discharges exerted minor negative effects on both HAB groups. Despite evidence supporting the role of upwelling intensity as an environmental driver of Pseudo-nitzschia spp., it was not identified as a relevant model predictor. Future model developments, such as the inclusion of additional environmental variables, and the implementation of species- and period-specific, and hybrid modelling approaches, may further support HAB operational forecasting and managing over complex coastal domains.

Advances in multiplex molecular detection technologies for harmful algae

As the eutrophication of natural water bodies becomes more and more serious, the frequency of outbreaks of harmful algal blooms (HABs) mainly formed by harmful algae also increases. HABs have become a global ecological problem that poses a serious threat to human health and food safety. Therefore, it is extremely important to establish methods that can rapidly detect harmful algal species for early warning of HABs. The traditional morphology-based identification method is inefficient and inaccurate. In recent years, the rapid development of molecular biology techniques has provided new ideas for the detection of harmful algae and has become a research hotspot. The current molecular detection methods for harmful algal species mainly include fluorescence in situ hybridization, sandwich hybridization, and quantitative PCR (qPCR), but all of these methods can only detect single harmful algal species at a time. The establishment of methods for the simultaneous detection of multiple harmful algal species has become a new trend in the development of molecular detection technology because various harmful algal species may coexist in the natural water environment. The established molecular techniques for multiple detections of harmful algae mainly include gene chip, multiplex PCR, multiplex qPCR, massively parallel sequencing, antibody chip, and multiple isothermal amplification. This review mainly focuses on the principles, advantages and disadvantages, application progress, and application prospects of these multiple detection technologies, aiming at providing effective references not only for the fisheries but also for economic activities, environment, and human health.

Unravelling the effects of treated wastewater discharges on the water quality in a coastal lagoon system (Ria Formosa, South Portugal): Relevance of hydrodynamic conditions

This study aimed to assess the influence of treated wastewater disposal on Ria Formosa coastal lagoon (South Portugal), the largest national producer of bivalve mollusks. Water quality was evaluated at two areas under different wastewater loads and hydrodynamic conditions, using physico-chemical variables, bacterial indicators of contamination, chlorophyll-a concentration, phytoplankton abundance and composition. Samples were collected monthly, between October 2018 and September 2019. Minor influence of effluent discharge was detected at the eastern Olhão area, exposed to stronger hydrodynamics and higher wastewater load than the northwestern Faro area (ca. 2-4-fold total nitrogen and phosphorus). The lower load weakly flushed area showed a poorer water quality, up to 500 m from the discharge point, more marked during the spring-summer period. The intensity, persistence, and spatial extent of the wastewater footprint, lower for the highest-loading area, reflected the role of local hydrodynamic conditions, modulating the influence of wastewater discharge on lagoonal water quality.

Using qPCR and high-resolution sensor data to model a multi-species Pseudo-nitzschia (Bacillariophyceae) bloom in southeastern Australia

Harmful algal blooms, including those caused by the toxic diatom Pseudo-nitzschia, can have significant impacts on human health, ecosystem functioning and ultimately food security. In the current study we characterized a bloom of species of Pseudo-nitzschia that occurred in a south-eastern Australian oyster-growing estuary in 2019. Using light microscopy, combined with molecular (ITS/5.8S and LSU D1-D3 rDNA regions) and toxicological evidence, we observed the bloom to consist of multiple species of Pseudo-nitzschia including P. cf. cuspidata, P. hasleana, P. fraudulenta and P. multiseries, with P. cf. cuspidata being the only species that produced domoic acid (3.1 pg DA per cell). As several species of Pseudo-nitzschia co-occurred, only one of which produced DA, we developed a rapid, sensitive and efficient quantitative real-time polymerase chain reaction (qPCR) assay to detect only species belonging to the P. pseudodelicatissima complex Clade I, to which P. cf. cuspidata belongs, and this indicated that P. cuspidata or closely related strains may have dominated the Pseudo-nitzschia community at this time. Finally, using high resolution water temperature and salinity sensor data, we modeled the relationship between light microscopy determined abundance of P. delicatissima group and environmental variables (temperature, salinity, rainfall) at two sites within the estuary. A total of eight General Linear Models (GLMs) explaining between 9 and 54% of the deviance suggested that the temperature (increasing) and/or salinity (decreasing) data were generally more predictive of high cell concentrations than the rainfall data at both sites, and that overall, cell concentrations were more predictive at the more oceanic site than the more upstream site, using this method. We conclude that the combination of rapid molecular methods such as qPCR and real-time sensor data modeling, can provide a more rapid and effective early warning of harmful algal blooms of species of Pseudo-nitzschia, resulting in more beneficial regulatory and management outcomes.

Development of 18S rRNA gene arrays for forensic detection of diatoms

Diatom test is the most commonly used method to diagnose drowning in forensic laboratories. However, microscopic examination and identification of diatom frustules is time-consuming and requires taxonomic expertise. At present, the identification of drowning is still a challenge in forensic casework. In this study, we developed a novel diatom microarray based on the detection of specific 18S rRNA gene fragments of diatom species. The array covers 169 diatom species which were documented as commonly found in a wide range of fresh waters in China. Diatom arrays were prepared from species specific oligonucleotide probes targeting to variable regions of the 18S rRNA gene. We also developed an auxiliary sample preparation method for isolation of diatom DNA from tissues, which enabled detection of diatom species in real forensic samples as well as environmental waters. We applied the diatom arrays to analyze six drowned cases and eight environmental samples. The diatom arrays showed much better sensitivity and more consistent results than those of the conventional SEM methods. We discovered major discrepancies between results generated by the diatom arrays and the routinely used SEM based diatom tests. We verified the results of our diatom arrays by species specific PCR and Sanger sequencing and found that the currently used SEM diatom test method has a serious deficiency in sensitivity due to high loss rate of frustules in the sample preparation procedure. We anticipate that the application of diatom arrays will transform current forensic practice of diagnosing drowning deaths.