Ecotoxicological Effects of Potassium Dichromate on the Tadpole Shrimp Triops longicaudatus.

The tadpole shrimp Triops longicaudatus is a freshwater crustacean with fast embryonic and larval development, short life cycle, and high fecundity. They are very active swimmers of a reasonable size, easy to spot and record. Such characteristics make it a promising candidate as an experimental model in ecotoxicology to evaluate the effects of aquatic pollutants, particularly using its locomotor behavior as an endpoint. To evaluate the sensitivity of T. longicaudatus and develop endpoints of interest, we conducted exposure experiments with lethal and sub-lethal concentrations of potassium dichromate, a compound known for its ecotoxicological importance and as a hexavalent chromium source. The endpoints evaluated were mortality, growth, sexual maturation, reproductive output, cholinesterase activity and locomotor/swimming behavior. The 96 h median lethal concentration was found to be 65 µg/L. Furthermore, exposure to potassium dichromate at higher concentrations had a significant negative impact on the growth rate of T. longicaudatus in terms of both body mass and length. The time for maturation was also delayed at higher concentrations. In addition, locomotor behavior allowed for the discrimination of all tested chromium concentrations and the control group and from each other, proving to be the most sensitive endpoint. Overall, the data support the potential of T. longicaudatus as a model for ecotoxicity testing, using apical endpoints with impact at the population level; in particular, results suggest that behavior assessments in this species might be useful for detecting hazardous compounds in environmental monitoring of freshwater ecosystems.

Environmental diagnosis with Raman Spectroscopy applied to diatoms.

Freshwater quality has been changing due to the ever greater use of water resources and the contamination load resulting from human activities. Management of these systems, thus, requires constant diagnose of water quality with fast and efficient methodologies. The conventional methods adopted are, however, time-consuming, often very expensive, and require specialised expertise. Raman spectroscopy (RS) is a simple, fast and label-free technique that can be applied to environmental diagnosis using diatoms. Here, we developed a diagnostic method based on Raman spectroscopy applied to freshwater diatoms. For this, Raman spectra were recorded from diatoms of three lakes of a natural city park. The data acquired was analysed by chemometrics methods to describe the data (Partial Least Squares Regression), infer relationships in the dataset (Cluster Analysis) and produce classification models (Artificial Neural Network). The classification models developed diagnosed the lakes with excellent accuracy (89%) without requiring taxonomic information about the diatom species recorded. This study provides a proof-of-concept for the application of diatom Raman spectroscopy to diagnosing water quality, laying an important foundation for future environmental studies aiming at assessing freshwater systems, to be replicated at larger scales and to varied geographic settings.

Microplastics as a vehicle of exposure to chemical contamination in freshwater systems: Current research status and way forward.

Contamination by microplastics is increasing steadily worldwide, affecting all environments. Additionally, aquatic organisms are often exposed to mixtures of other contaminants, including various chemicals. Numerous studies reported adsorption of chemicals to microplastics, raising concern about their possible role as vehicles of exposure through transfer to biota. Nevertheless, until recently, the studies on the topic were mostly focused on the marine environment. In the past five years, however, plenty of publications contributed empirical data about freshwater ecosystems, raising the need for a critical appraisal of the information. Herein the scientific literature was reviewed and multivariate data analysis was done. The analysed studies employed widely different experimental designs, endpoints, test species, shapes and concentrations of various polymer types and chemicals, often not relevant for the freshwater environment. Our integrated analytical approach revealed unfathomable research gaps, given the theoretical knowledge available and lessons learned from research about the marine environment. Greater harmonization of laboratory studies investigating this topic is needed, as well as testing conditions reflecting real exposure scenarios. Furthermore, standardized testing protocols are urgently required to guide such experiments and improve the comparability of the results obtained.

Raman spectroscopy applied to diatoms (microalgae, Bacillariophyta): Prospective use in the environmental diagnosis of freshwater ecosystems.

Diatom species are good pollution bioindicators due to their large distribution, fast response to changes in environmental parameters and different tolerance ranges. These organisms are used in ecological water assessment all over the world using autoecological indices. Such assessments commonly rely on the taxonomic identification of diatom species-specific shape and frustule ornaments, from which cell counts, species richness and diversity indices can be estimated. Taxonomic identification is, however, time-consuming and requires years of expertise. Additionally, though the diatom autoecological indices are region-specific, they are often applied indiscriminately across regions. Raman spectroscopy is a simpler, fast and label-free technique that can be applied to environmental diagnosis with diatoms. However, this approach has been poorly explored. This work reviews Raman spectroscopy studies involving the structure, location and conformation of diatom cell components and their variation under different conditions. A critical appreciation of the pros and cons of its application to environmental diagnosis is also given. This knowledge provides a strong foundation for the development of environmental protocols using Raman spectroscopy in diatoms. Our work aims at stimulating further research on the application of Raman spectroscopy as a tool to assess physiological changes and water quality under a changing climate.

Effects of norfluoxetine and venlafaxine in zebrafish larvae: Molecular data.

The data presented herein relates to the article entitled "Norfluoxetine and venlafaxine in zebrafish larvae: single and combined toxicity of two pharmaceutical products relevant for risk assessment" [1]. Recent studies have shown the occurrence of active metabolites of human and veterinary pharmaceuticals in surface and wastewaters. Besides their biological activity, some are predicted to interact with the same molecular targets of their parental compounds, thus showing the potential to elicit detrimental effects on animals. Despite this, limited investigation on their effects on aquatic animals has been done. Genomic material resulting from zebrafish (Danio rerio) larvae exposed to the psychoactive compounds norfluoxetine (main fluoxetine metabolite), venlafaxine, or their mixture was collected for gene expression analysis of a determined pool of genes potentially involved in their mode-of-action and metabolism. Molecular parameters are a cost-effective and reliable way to understand modes-of-action and the potential risk of micropollutants, such as pharmaceutical products, in non-target organisms. Moreover, gene expression patterns can provide crucial complementary information to improve risk assessment, and monitoring of affected systems. The data reported in this article was used to depict the effects of single or combined exposure to norfluoxetine and venlafaxine and identify biomarkers of exposure to these compounds of interest to diagnose exposure and routine monitoring.

Uptake and effects of different concentrations of spherical polymer microparticles on Artemia franciscana.

Artemia cysts have a huge economic importance for the aquaculture sector due to the fact that they are used as live feed for larviculture. Microplastics (MPs) are common and emergent pollutants in the aquatic environments, with unknown and potential long-term effects on planktonic species such as Artemia spp. When used as live feed, Artemia could transfer contaminants to fish along the food chain, with possible adverse effects on human health through their consumption. This study aims to assess the uptake of different concentrations of spherical polymer microparticles (FRM) (1-5 µm diameter) and their associated chronic effects on feeding, growth, mortality, and reproductive success from juvenile to adult stage of brine shrimp Artemia franciscana. Individuals were exposed for 44 days to 0.4, 0.8 and 1.6 mg.L-1 of FRM. No significant detrimental effects on growth, ingestion and mortality rates of A. franciscana were observed in all tested conditions. However, reproductive success was strongly affected by the increase of MP concentrations. The results of the present study showed that A. franciscana juveniles and adults were able to survive different experimental MP concentrations, but their reproductive success and progeny were significantly impacted by exposure to FRM particles.

Lymnaea stagnalis as a freshwater model invertebrate for ecotoxicological studies.

Lymnaea stagnalis, also referred to as great or common pond snail, is an abundant and widespread invertebrate species colonizing temperate limnic systems. Given the species importance, studies involving L. stagnalis have the potential to produce scientifically relevant information, leading to a better understanding of the damage caused by aquatic contamination, as well as the modes of action of toxicants. Lymnaea stagnalis individuals are easily maintained in laboratory conditions, with a lifespan of about two years. The snails are hermaphrodites and sexual maturity occurs about three months after egg laying. Importantly, they can produce a high number of offspring all year round and are considered well suited for use in investigations targeting the identification of developmental and reproductive impairments. The primary aims of this review were two-fold: i) to provide an updated and insightful compilation of established toxicological measures determined in both chronic and acute toxicity assays, as useful tool to the design and development of future research; and ii) to provide a state of the art related to direct toxicant exposure and its potentially negative effects on this species. Relevant and informative studies were analysed and discussed. Knowledge gaps in need to be addressed in the near future were further identified.

Data for the analysis of interactive multibiomarker responses of a marine crustacean to long-term exposure to aquatic contaminants.

The data presented herein relates to the article entitled "Multibiomarker interactions to diagnose and follow-up chronic exposure of a marine crustacean to hazardous and noxious substances (HNS)" (Abreu et al., 2018). Multibiomarker approaches, including molecular, biochemical, physiological and behaviour parameters, are recognised as valuable and cost-effective to employ in integrated chemical and biological effects monitoring of aquatic contamination. Many biomarkers assessed in such programmes share common physiological pathways, showing concomitant or interdependent responses, which can reflect in increased energy costs related to physiological acclimation. Though, routine single biomarker data analysis, and exploratory principal component analysis, limit information obtained from the data collected and their functional interpretation. Ultimately, this influences the type of management actions taken to protect an affected ecosystem. This article presents data employed to develop an analytical approach accounting for multibiomarker interactions. The method was useful to diagnose and follow-up long-term exposure of the marine green crab (Carcinus maenas) to Hazardous and Noxious Substances (HNS).

Multibiomarker interactions to diagnose and follow-up chronic exposure of a marine crustacean to Hazardous and Noxious Substances (HNS).

Integrated compensatory responses of physiological systems towards homeostasis are generally overlooked when it comes to analysing alterations in biochemical parameters indicative of such processes. Here an hypothesis-driven multivariate analysis accounting for interactive multibiomarker responses was used to investigate effects of long-term exposure of Carcinus maenas to Hazardous and Noxious Substances (HNS). Adult male crabs were exposed to low and high post-spill levels of acrylonitrile (ACN) or aniline (ANL) for 21d. Bioaccumulation, feeding behaviour, and biomarkers related to mode-of-action (MoA) (detoxification, neurotransmission and energy production) were evaluated over time. Distinct temporal patterns of response to low and high exposure concentrations were depicted, with a main set of interactive multibiomarker predictors identified for each HNS (five for ACN and three for ANL), useful to follow coupled evolvement of biomarker responses. ACN caused peripheral neurotoxic effects coupled with enhanced biotransformation and significant oxidative damage particularly relevant in gills. ANL elicited alterations in central neurotransmission affecting ventilation coupled with very low levels of oxidative damage in gills. Results indicate chronic toxicity data are determinant to improve HNS hazard assessment if the aim is to obtain reliable risk calculations, and develop effective predictive models avoiding overestimation but sufficiently protective. Accounting for multibiomarker interactions brought otherwise overlooked information about C. maenas responses and MoA of ACN and ANL.

Escherichia coli's water load affects zebrafish (Danio rerio) behavior.

Traditional physico-chemical sensors are becoming an obsolete tool for environmental quality assessment. Biomonitoring techniques, such as biological early warning systems present the advantage of being sensitivity, fast, non-invasive and ecologically relevant. In this work, we applied a video tracking system, developed with zebrafish (Danio rerio), to detect microbiological contamination in water. Using the fishs' behavior response, the system was able to detect the presence of a non-pathogenic environmental strain of Escherichia coli, at three different levels of contamination: 600, 1800 and 5000 CFU/100 mL (colony forming units/100 mL). Data was collected during 50 min of exposure and analyzed with the artificial neural networks Self-organizing Map and Multi-layer Perceptron. The behavior of exposed fish was more erratic, with pronounced and rapid changes on movement direction and with significant less exploratory activity. The accuracy, sensitivity and specificity values regarding the detection capability (distinction between presence or absence of contamination) ranged from 89 to 100%. Regarding the classification capability (distinction between experimental conditions), the values ranged from 67 to 89%. This research may be a valuable contribution to improve water monitoring and management strategies, by taking as reference the effects on biosensors, without a biased anthropocentric perspective.

Evaluation of the sensitivity spectrum of a video tracking system with zebrafish (Danio rerio) exposed to five different toxicants.

The aim of this study was to develop a biological early warning system for the detection of aquatic toxicity and test it with five toxicants with distinct chemical nature. This was done in order to verify the spectrum of sensitivities of the proposed system, as well as the potential identification capability of the tested contaminants, using only the analysis of zebrafish's behavior. Six experimental conditions were tested: negative control and five toxicants (bleach, lindane, tributyltin, mercury, and formaldehyde). The exposure time was 45 min, and the concentrations used corresponded to 9% of LC50's-96 h for the tested compounds, to ensure ecologically relevant results. A total of 108 fish were used, with each individual experimental condition being tested 18 times. A statistical model of diagnosis was used, combining self-organizing map and correspondence analysis. The values of sensitivity, specificity, accuracy, false positive, false negative, positive predictive value (PPV), and negative predictive value (NPV) were calculated. The objectives of the work were accomplished and the system showed a good overall diagnostic performance with 79% in accuracy, 77% in sensitivity, and 88% in specificity. The lowest result of the predictive values was 78% (lindane and mercury), in the case of the NPV, and 86% (bleach and lindane), in the case of the PPV. The best result of the predictive values was 100% (bleach and tributyltin), for the NPV, and 89% (tributyltin), for the PPV. Regarding the five tested toxicants, the system was able to correctly identify the agent responsible for the contamination in 40% of the positive diagnoses.

Stress test of a biological early warning system with zebrafish (Danio rerio).

The aim of this work was to develop a novel methodology to stress test the diagnostic capability of a video tracking system with zebrafish (Danio rerio), against two pre-established disturbances. Eight different treatments were tested varying the presence or absence of a toxicant (NaOCl) and two disturbances: the passing of a shadow (mimicking a predator) and entrapment of the fish. The concentration tested corresponded to a sublethal (1 % 24 h-LC50) and short term exposure (2 h). A total of 56 organisms were tested resulting in 112 diagnoses (before and after the contamination). A statistical model of diagnosis was developed using Self-organizing Map (SOM) and Correspondence Analysis (CA). Sensitivity, specificity, accuracy, false positive and false negative values were calculated to evaluate the diagnostic performance. The disturbances did not negatively affect the capability of the model. In the presence of at least one of these variables, the diagnostic performance was similar or even superior to the baseline results without disturbances. Furthermore, the system produced a large number of correct diagnoses, at an ecologically relevant concentration of exposure, in a non-invasive way.

Video-tracking of zebrafish (Danio rerio) as a biological early warning system using two distinct artificial neural networks: Probabilistic neural network (PNN) and self-organizing map (SOM).

Biological early warning systems (BEWS) are becoming very important tools in ecotoxicological studies because they can detect changes in the behavior of organisms exposed to toxic substances. In this work, a video tracking system was fully developed to detect the presence of commercial bleach (NaOCl) in water in three different concentrations (0.0005%; 0.0010% and 0.0020% (v/v)) during one hour of exposure. Zebrafish was selected as the test organism because it is widely used in many different areas and studies. Two distinct statistical models were developed, using probabilistic neural network (PNN) and correspondence analysis associated with self-organizing map (SOM-CA). The diagnosis was based only in the analysis of a few behavioral components of the fish, namely: mean angular velocity, mean linear velocity, spatial dispersion, mean value of the X coordinate and mean value of the Y coordinate. Both models showed good results in their diagnosis capabilities. However, the overall performance (accuracy) was always superior in the PNN model. The worst result was with the SOM-CA model, at the lowest concentration (0.0005% v/v), achieving only 65% of correct diagnosis. The best result was with the PNN model, at the highest concentration (0.0020% v/v), achieving 94% of correct diagnosis.