A lipocalin mediates unidirectional heme biomineralization in malaria parasites.

During blood-stage development, malaria parasites are challenged with the detoxification of enormous amounts of heme released during the proteolytic catabolism of erythrocytic hemoglobin. They tackle this problem by sequestering heme into bioinert crystals known as hemozoin. The mechanisms underlying this biomineralization process remain enigmatic. Here, we demonstrate that both rodent and human malaria parasite species secrete and internalize a lipocalin-like protein, PV5, to control heme crystallization. Transcriptional deregulation of PV5 in the rodent parasite Plasmodium berghei results in inordinate elongation of hemozoin crystals, while conditional PV5 inactivation in the human malaria agent Plasmodium falciparum causes excessive multidirectional crystal branching. Although hemoglobin processing remains unaffected, PV5-deficient parasites generate less hemozoin. Electron diffraction analysis indicates that despite the distinct changes in crystal morphology, neither the crystalline order nor unit cell of hemozoin are affected by impaired PV5 function. Deregulation of PV5 expression renders P. berghei hypersensitive to the antimalarial drugs artesunate, chloroquine, and atovaquone, resulting in accelerated parasite clearance following drug treatment in vivo. Together, our findings demonstrate the Plasmodium-tailored role of a lipocalin family member in hemozoin formation and underscore the heme biomineralization pathway as an attractive target for therapeutic exploitation.

Seeded Heteroepitaxial Growth of Crystallizable Collagen Triple Helices: Engineering Multifunctional Two-Dimensional Core-Shell Nanostructures.

Engineering free-standing 2D nanomaterials with compositional, spatial, and functional control across size regimes from the nano- to mesoscale represents a significant challenge. Herein, we demonstrate a straightforward strategy for the thermodynamically controlled fabrication of multicomponent sectored nanosheets in which each sector can be chemically and spatially addressed independently and orthogonally. Collagen triple helices, comprising collagen-mimetic peptides (CMPs), are employed as molecularly programmable crystallizable units. Modulating their thermodynamic stability affords the controlled synthesis of 2D core-shell nanostructures via thermally driven heteroepitaxial growth. Structural information, gathered from SAXS and cryo-TEM, reveals that the distinct peptide domains maintain their intrinsic lattice structure and illuminates various mechanisms employed by CMP triple helices to alleviate the elastic strain associated with the interfacial lattice mismatch. Finally, we demonstrate that different sectors of the sheet surface can be selectively functionalized using bioorthogonal conjugation chemistry. Altogether, we establish a robust platform for constructing multifunctional 2D nanoarchitectures in which one can systematically program their compositional, spatial, and functional properties, which is a significant step toward their deployment into functional nanoscale devices.

2D Crystal Engineering of Nanosheets Assembled from Helical Peptide Building Blocks.

The successful integration of 2D nanomaterials into functional devices hinges on developing fabrication methods that afford hierarchical control across length scales of the entire assembly. We demonstrate structural control over a class of crystalline 2D nanosheets assembled from collagen triple helices. By lengthening the triple helix unit through sequential additions of Pro-Hyp-Gly triads, we achieved sub-angstrom tuning over the 2D lattice. These subtle changes influence the overall nanosheet size, which can be adjusted across the mesoscale size regime. The internal structure was observed by cryo-TEM with direct electron detection, which provides real-space high-resolution images, in which individual triple helices comprising the lattice can be clearly discerned. These results establish a general strategy for tuning the structural hierarchy of 2D nanomaterials that employ rigid, cylindrical structural units.

Characterization at the Level of Individual Crystals: Single-Crystal MFI Type Zeolite Grains.

Electron-diffraction data on the zeolites Silicalite-1 and ZSM-5 (both MFI framework type) were collected from individual grains of about 150×100×50 nm3 . Crystals were synthesized with tetrapropylammonium as structure-directing agent. The resolution extended to about 0.8 Šfor Silicalite-1 and about 0.9-1.0 Šfor ZSM-5 crystals. Analysis of several data sets showed that at the nanometre-scale, these zeolite crystals are single crystals and not intergrown.

A Molecular Level Approach To Elucidate the Supramolecular Packing of Light-Harvesting Antenna Systems.

The molecular geometry and supramolecular packing of two bichromophoric prototypic light harvesting compounds D1A2 and D2A2, consisting of two naphthylimide energy donors that were attached to the 1,7 bay positions of a perylene monoimide diester energy acceptor, have been determined by a hybrid approach using magic angle spinning NMR spectroscopy and electron nano-crystallography (ENC), followed by modelling. NMR shift constraints, combined with the P 1 ‾ space group obtained from ENC, were used to generate a centrosymmetric dimer of truncated perylene fragments. This racemic packing motif is used in a biased molecular replacement approach to generate a partial 3D electrostatic scattering potential map. Resolving the structure of the bay substituents is guided by the inversion symmetry, and the distance constraints obtained from heteronuclear correlation spectra. The antenna molecules form a pseudocrystalline lattice of antiparallel centrosymmetric dimers with pockets of partially disordered bay substituents. The two molecules in a unit cell form a butterfly-type arrangement. The hybrid methodology that has been developed is robust and widely applicable for critical structural underpinning of self-assembling structures of large organic molecules.

Rapid Structure Determination of Microcrystalline Molecular Compounds Using Electron Diffraction.

Chemists of all fields currently publish about 50 000 crystal structures per year, the vast majority of which are X-ray structures. We determined two molecular structures by employing electron rather than X-ray diffraction. For this purpose, an EIGER hybrid pixel detector was fitted to a transmission electron microscope, yielding an electron diffractometer. The structure of a new methylene blue derivative was determined at 0.9 Šresolution from a crystal smaller than 1×2 µm2 . Several thousand active pharmaceutical ingredients (APIs) are only available as submicrocrystalline powders. To illustrate the potential of electron crystallography for the pharmaceutical industry, we also determined the structure of an API from its pill. We demonstrate that electron crystallography complements X-ray crystallography and is the technique of choice for all unsolved cases in which submicrometer-sized crystals were the limiting factor.

Sub-Lethal Effects of Copper on Salmonids: An Avoidance Evaluation Using a Direct Test Method.

Avoidance of copper (Cu) by rainbow trout (Oncorhynchus mykiss) was evaluated using a Y-maze exposure system, with data collected over a 1-h exposure period using a digital camcorder. In exposures to five measured concentrations of dissolved copper (<0.3, 1.2, 9.8, 48.3, and 98.6 µg Cu/L), plus control, significant avoidance behavior (p < 0.05) relative to the control was observed at ≥9.8 µg Cu/L, but not at 1.2 µg Cu/L. The chronic value (i.e., geometric mean of these concentrations) was 3.43 µg Cu/L. Estimates of EC50 values for avoidance of Cu ranged from 4.81 to 9.15 µg Cu/L over four 15-min time intervals of exposure to the metal. Based on water quality characterization of the control/diluent water, the U.S. Environmental Protection Agency (USEPA) water hardness- and biotic ligand model (BLM)-based chronic criteria for dissolved Cu were 8.03 and 2.26 µg Cu/L, respectively. This study suggested that enforcement of the BLM-based criterion would provide a higher level of protection of trout for this sensitive response than the hardness-based criterion.

A Medipix quantum area detector allows rotation electron diffraction data collection from submicrometre three-dimensional protein crystals.

When protein crystals are submicrometre-sized, X-ray radiation damage precludes conventional diffraction data collection. For crystals that are of the order of 100 nm in size, at best only single-shot diffraction patterns can be collected and rotation data collection has not been possible, irrespective of the diffraction technique used. Here, it is shown that at a very low electron dose (at most 0.1 e(-) Å(-2)), a Medipix2 quantum area detector is sufficiently sensitive to allow the collection of a 30-frame rotation series of 200 keV electron-diffraction data from a single ∼100 nm thick protein crystal. A highly parallel 200 keV electron beam (λ = 0.025 Å) allowed observation of the curvature of the Ewald sphere at low resolution, indicating a combined mosaic spread/beam divergence of at most 0.4°. This result shows that volumes of crystal with low mosaicity can be pinpointed in electron diffraction. It is also shown that strategies and data-analysis software (MOSFLM and SCALA) from X-ray protein crystallography can be used in principle for analysing electron-diffraction data from three-dimensional nanocrystals of proteins.

Machine learning for classifying narrow-beam electron diffraction data.

As an alternative approach to X-ray crystallography and single-particle cryo-electron microscopy, single-molecule electron diffraction has a better signal-to-noise ratio and the potential to increase the resolution of protein models. This technology requires collection of numerous diffraction patterns, which can lead to congestion of data collection pipelines. However, only a minority of the diffraction data are useful for structure determination because the chances of hitting a protein of interest with a narrow electron beam may be small. This necessitates novel concepts for quick and accurate data selection. For this purpose, a set of machine learning algorithms for diffraction data classification has been implemented and tested. The proposed pre-processing and analysis workflow efficiently distinguished between amorphous ice and carbon support, providing proof of the principle of machine learning based identification of positions of interest. While limited in its current context, this approach exploits inherent characteristics of narrow electron beam diffraction patterns and can be extended for protein data classification and feature extraction.

Development and Validation of Multiple Linear Regression Models for Predicting Chronic Zinc Toxicity to Freshwater Microalgae.

Multiple linear regression (MLR) models were developed for predicting chronic zinc toxicity to a freshwater microalga, Chlorella sp., using three toxicity-modifying factors (TMFs): pH, hardness, and dissolved organic carbon (DOC). The interactive effects between pH and hardness and between pH and DOC were also included. Models were developed at three different effect concentration (EC) levels: EC10, EC20, and EC50. Models were independently validated using six different zinc-spiked Australian natural waters with a range of water chemistries. Stepwise regression found hardness to be an influential TMF in model scenarios and was retained in all final models, while pH, DOC, and interactive terms had variable influence and were only retained in some models. Autovalidation and residual analysis of all models indicated that models generally predicted toxicity and that there was little bias based on individual TMFs. The MLR models, at all effect levels, performed poorly when predicting toxicity in the zinc-spiked natural waters during independent validation, with models consistently overpredicting toxicity. This overprediction may be from another unaccounted for TMF that may be present across all natural waters. Alternatively, this consistent overprediction questions the underlying assumption that models developed from synthetic laboratory test waters can be directly applied to natural water samples. Further research into the suitability of applying synthetic laboratory water-based models to a greater range of natural waters is needed. Environ Toxicol Chem 2023;42:2630-2641. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Natural organic matter source, concentration, and pH influences the toxicity of zinc to a freshwater microalga.

Zinc is a contaminant of concern in aquatic environments and is a known toxicant to many aquatic organisms. Dissolved organic matter (DOM) is a toxicity modifying factor for zinc and is an important water chemistry parameter. This study investigated the influence of DOM concentration, source, and water pH on the chronic toxicity of zinc to a freshwater microalga, Chlorella sp. The influence of DOM on zinc toxicity was dependent on both concentration and source. In the absence of DOM, the 72-h EC50 was 112 µg Zn.L-1. In the presence of a DOM high in fulvic-like components, zinc toxicity was either slightly decreased (<4-fold increase in EC10s across 15 mg C.L-1 range) or unchanged (minimal difference in EC50s). In the presence of a DOM high in humic-like (aromatic and high molecular weight) components, zinc toxicity was slightly decreased at the EC10 level and strongly increased at the EC50 level. The influence of pH on zinc toxicity was dependent on the source of DOM present in the water. In the presence of DOM high in humic-like components pH did not influence toxicity. In the presence of DOM high in fulvic-like components, pH had a significant effect on EC50 values. Labile zinc (measured by diffusive gradients in thin-films) followed linear relationships with dissolved zinc but could not explain the changes in observed toxicity, with similar DGT-labile zinc relationships shown for the two DOMs despite each DOM influencing toxicity differently. This indicates changes in toxicity may be unrelated to changes in zinc lability. The results suggest that increased toxicity of zinc in the presence of DOM may be due to direct uptake of Zn-DOM complexes. This study highlights the importance of considering DOM source and characteristics when incorporating DOM into water quality guidelines through bioavailability models.

Applicability of Chronic Multiple Linear Regression Models for Predicting Zinc Toxicity in Australian and New Zealand Freshwaters.

Bioavailability models, for example, multiple linear regressions (MLRs) of water quality parameters, are increasingly being used to develop bioavailability-based water quality criteria for metals. However, models developed for the Northern Hemisphere cannot be adopted for Australia and New Zealand without first validating them against local species and local water chemistry characteristics. We investigated the applicability of zinc chronic bioavailability models to predict toxicity in a range of uncontaminated natural waters in Australia and New Zealand. Water chemistry data were compiled to guide a selection of waters with different zinc toxicity-modifying factors. Predicted toxicities using several bioavailability models were compared with observed chronic toxicities for the green alga Raphidocelis subcapitata and the native cladocerans Ceriodaphnia cf. dubia and Daphnia thomsoni. The most sensitive species to zinc in five New Zealand freshwaters was R. subcapitata (72-h growth rate), with toxicity ameliorated by high dissolved organic carbon (DOC) or low pH, and hardness having a minimal influence. Zinc toxicity to D. thomsoni (reproduction) was ameliorated by both high DOC and hardness in these same waters. No single trophic level-specific effect concentration, 10% (EC10) MLR was the best predictor of chronic toxicity to the cladocerans, and MLRs based on EC10 values both over- and under-predicted zinc toxicity. The EC50 MLRs better predicted toxicities to both the Australian and New Zealand cladocerans to within a factor of 2 of the observed toxicities in most waters. These findings suggest that existing MLRs may be useful for normalizing local ecotoxicity data to derive water quality criteria for Australia and New Zealand. The final choice of models will depend on their predictive ability, level of protection, and ease of use. Environ Toxicol Chem 2023;42:2614-2629. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The influence of hardness at varying pH on zinc toxicity and lability to a freshwater microalga, Chlorella sp.

Zinc is an essential element for aquatic organisms, however, activities such as mining and refining, as well as zinc's ubiquitous role in modern society can contribute to elevated environmental concentrations of zinc. Water hardness is widely accepted as an important toxicity modifying factor for metals in aquatic systems, though other factors such as pH are also important. This study investigated the influence of increasing water hardness, at three different pH values (6.7, 7.6 and 8.3), on the chronic toxicity of zinc to the growth rate of a microalgae, Chlorella sp. Zinc toxicity decreased with increasing hardness from 5 to 93 mg CaCO3 L-1 at all three pH values tested. The 72 h growth rate inhibition EC50 values ranged from 6.2 µg Zn L-1 (at 5 mg CaCO3 L-1, pH 8.3) to 184 µg Zn L-1 (at 92 mg CaCO3 L-1, pH 6.7). Increases in hardness from 93 to 402 mg CaCO3 L-1 generally resulted in no significant (p > 0.05) reduction in zinc toxicity. DGT-labile zinc measurements did not correspond with the observed changes in zinc toxicity as hardness was varied within a pH treatment. This suggests that cationic competition from increased hardness is decreasing zinc toxicity, rather than changes in metal lability. This study highlighted that current hardness algorithms used in water quality guidelines may not be sufficiently protective of sensitive species, such as Chlorella sp., in high hardness waters.

Effects of Zinc in an Outdoor Freshwater Microcosm System.

A long-term exposure outdoor microcosm study was conducted to evaluate the effects of zinc (Zn) on zooplankton, phytoplankton, and periphyton in a freshwater system. Five Zn treatment concentrations (nominal: 8, 20, 40, 80, and 160 µg/L Zn) and an untreated control with 3 replicates each were used. Various physical and chemical characteristics of the microcosms and biological assessment endpoints (e.g., total abundance, group abundance, species richness, chlorophyll a, etc.) were measured to determine the effects of Zn over time. In general, physical and chemical characteristics (e.g., total dissolved solids, total suspended solids, dissolved oxygen, pH, dissolved organic carbon) of water fluctuated over time, but they were not significantly different within treatments and controls during the study. Zinc significantly affected the population dynamics and community structure of plankton. The effects occurred 7 d after initial treatment exposures began and continued to the end of the treatment phase, especially at the high treatment concentrations. Total and group abundance, species richness, the Shannon index, and chlorophyll a concentrations for high Zn treatment concentrations were significantly lower than the controls during the treatment phase. The no-observed-effect, lowest-observed-effect, and median effect concentrations were generally lower than the literature-reported results from single-species toxicity tests for fish and invertebrates, suggesting that plankton are more sensitive to Zn than planktivores. Although primary producers play an important role in the ecosystem, they have not been consistently incorporated into numerical environmental quality criteria for freshwater organisms, at least in the United States. The results of the present study are useful for development of environmental quality guidelines for freshwater ecosystems and ecological risk assessment. Environ Toxicol Chem 2021;40:2053-2072. © 2021 SETAC.

The Influence of pH on Zinc Lability and Toxicity to a Tropical Freshwater Microalga.

Increased focus on the development and application of bioavailability-based metal water quality guideline values requires increased understanding of the influence of water chemistry on metal bioavailability and toxicity. Development of empirical models, such as multiple linear regression models, requires the assessment of the influence of individual water quality parameters as toxicity-modifying factors. The present study investigated the effect of pH on the lability and toxicity of zinc (Zn) to a tropical green microalga (Chlorella sp.). Zinc speciation and lability were explored using the Windermere Humic Aqueous Model (WHAM7), ultrafiltration, and diffusive gradients in thin films (DGT). Zinc toxicity increased significantly with increasing pH from 6.7 to 8.3, with 50% growth inhibition effect concentrations decreasing from 185 to 53 µg l-1 across the pH range. Linear relationships between DGT-labile Zn and dissolved Zn did not vary across the tested pH range, nor did the linear relationship between dissolved (<0.45 µm) and ultrafiltered (<3 kDa) Zn. Our findings show that Zn toxicity to this freshwater alga is altered as a function of pH across environmentally realistic pH ranges and that these toxicity changes could not be explained by Zn speciation and lability as measured by DGT and WHAM7. Environ Toxicol Chem 2021;40:2836-2845. © 2021 SETAC.

Development of Quantitative Ion Character-Activity Relationship Models to Address the Lack of Toxicological Data for Technology-Critical Elements.

Recent industrial developments have resulted in an increase in the use of so-called technology-critical elements (TCEs), for which the potential impacts on aquatic biota remain to be evaluated. In the present study, quantitative ion character-activity relationships (QICARs) have been developed to relate intrinsic metal properties to their toxicity toward freshwater aquatic organisms. In total, 23 metal properties were tested as predictors of acute median effect concentration (EC50) values for 12 data-rich metals, for algae, daphnids, and fish (with and without species distinction). Simple and multiple linear regressions were developed using the toxicological data expressed as a function of the total dissolved metal concentrations. The best regressions were then tested by comparing the predicted EC50 values for the TCEs (germanium, indium, gold, and rhenium) and platinum group elements (iridium, platinum, palladium, rhodium, and ruthenium) with the few measured values that are available. The 8 "best" QICAR models (adjusted r2 > 0.6) used the covalent index as the predictor. For a given metal ion, this composite parameter is a measure of the importance of covalent interactions relative to ionic interactions. Toxicity was reasonably well predicted for most of the TCEs, with values falling within the 95% prediction intervals for the regressions of the measured versus predicted EC50 values. Exceptions included Au(I) (all test organisms), Au(III) (algae and fish), Pt(II) (algae, daphnids), Ru(III) (daphnids), and Rh(III) (daphnids, fish). We conclude that QICARs show potential as a screening tool to review toxicity data and flag "outliers," which might need further scrutiny, and as an interpolating or extrapolating tool to predict TCE toxicity. Environ Toxicol Chem 2021;40:1139-1148. © 2020 SETAC.

Statistically correcting dynamical electron scattering improves the refinement of protein nanocrystals, including charge refinement of coordinated metals.

Electron diffraction allows protein structure determination when only nanosized crystals are available. Nevertheless, multiple elastic (or dynamical) scattering, which is prominent in electron diffraction, is a concern. Current methods for modeling dynamical scattering by multi-slice or Bloch wave approaches are not suitable for protein crystals because they are not designed to cope with large molecules. Here, dynamical scattering of nanocrystals of insulin, thermolysin and thaumatin was limited by collecting data from thin crystals. To accurately measure the weak diffraction signal from the few unit cells in the thin crystals, a low-noise hybrid pixel Timepix electron-counting detector was used. The remaining dynamical component was further reduced in refinement using a likelihood-based correction, which was introduced previously for analyzing electron diffraction data of small-molecule nanocrystals and was adapted here for protein crystals. The procedure is shown to notably improve the structural refinement, in one case allowing the location of solvent molecules. It also allowed refinement of the charge states of bound metal atoms, an important element in protein function, through B-factor analysis of the metal atoms and their ligands. These results clearly increase the value of macromolecular electron crystallography as a complementary structural biology technique.

Modeling the Bioavailability of Nickel and Zinc to Ceriodaphnia dubia and Neocloeon triangulifer in Toxicity Tests with Natural Waters.

We studied biotic ligand model (BLM) predictions of the toxicity of nickel (Ni) and zinc (Zn) in natural waters from Illinois and Minnesota, USA, which had combinations of pH, hardness, and dissolved organic carbon (DOC) more extreme than 99.7% of waters in a nationwide database. We conducted 7-day chronic tests with Ceriodaphnia dubia and 96-hour acute and 14-day chronic tests with Neocloeon triangulifer and estimated median lethal concentrations and 20% effect concentrations for both species. Toxicity of Ni and Zn to both species differed among test waters by factors from 8 (Zn tests with C. dubia) to 35 (Zn tests with N. triangulifer). For both species and metals, tests with Minnesota waters (low pH and hardness, high DOC) showed lower toxicity than Illinois waters (high pH and high hardness, low DOC). Recalibration of the Ni BLM to be more responsive to pH-related changes improved predictions of Ni toxicity, especially for C. dubia. For the Zn BLM, we compared several input data scenarios, which generally had minor effects on model performance scores (MPS). A scenario that included inputs of modeled dissolved inorganic carbon and measured Al and Fe(III) produced the highest MPS values for tests with both C. dubia and N. triangulifer. Overall, the BLM framework successfully modeled variation in toxicity for both Zn and Ni across wide ranges of water chemistry in tests with both standard and novel test organisms. Environ Toxicol Chem 2021;40:3049-3062. © 2021 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Acute and Chronic Toxicity of Nickel and Zinc to a Laboratory Cultured Mayfly (Neocloeon triangulifer) in Aqueous but Fed Exposures.

Aquatic insects are poorly represented in water quality criteria, and previous studies have suggested a lack of sensitivity in acute toxicity tests despite observational studies demonstrating the contrary. Our objectives were to determine the toxicity of nickel (Ni) and zinc (Zn) to the mayfly Neocloeon triangulifer in fed acute (96-h) and chronic exposures to estimate aqueous effect concentrations while acknowledging the importance of dietary exposure for these insects. For the chronic tests, we conducted preliminary full-life cycle (~25-30 d) and subchronic (14 d) exposures to compare the relative sensitivity of the 2 test durations under similar conditions (i.e., feeding rates). Observing similar sensitivity, we settled on 14 d as the definitive test duration. Furthermore, we conducted experiments to determine how much food could be added to a given volume of water while minimally impacting dissolved metal recovery; a ratio of food dry mass to water volume (<0.005) achieved this. In the 14-d tests, we obtained a median lethal concentration and most sensitive chronic endpoint of 147 and 23 µg/L dissolved Ni (acute to chronic ratio [ACR] = 6.4), respectively, and 81 (mean value) and 10 µg/L dissolved Zn (ACR = 8.1), respectively. The acute values are orders of magnitude lower than previously published values for mayflies, probably most importantly due to the presence of dietary exposure but also potentially with some influence of organism age and test temperature. Environ Toxicol Chem 2020;39:1196-1206. © 2020 SETAC.

Acute and Chronic Toxicity of Cobalt to Freshwater Organisms: Using a Species Sensitivity Distribution Approach to Establish International Water Quality Standards.

Water quality standards for cobalt (Co) have not been developed for the European Union or United States. The objective of the present study was to produce freshwater Co toxicity data that could be used by both the European Union and the United States to develop appropriate regulatory standards (i.e., environmental quality standards or predicted-no-effect concentrations in Europe and ambient water quality criteria or state water quality standards in the United States). Eleven species, including algae, an aquatic plant, and several invertebrate and fish species, were used in the performance of acute and chronic Co toxicity tests. Acute median lethal or median effective concentration (LC50 or EC50) values ranged from 90.1 µg Co/L for duckweed (Lemna minor) to 157 000 µg Co/L for midges (Chironomus tentans). Chronic 10% effect concentration (EC10) values ranged from 4.9 µg Co/L for duckweed to 2170 µg Co/L for rainbow trout (Oncorhynchus mykiss). Chronic 20% effect concentration (EC20) values ranged from 11.1 µg Co/L for water flea (Ceriodaphnia dubia) to 2495 µg Co/L for O. mykiss. Results indicated that invertebrate and algae/plant species are more sensitive to chronic Co exposures than fish. Acute-to-chronic ratios (derived as acute LC50s divided by chronic EC20s) were lowest for juvenile O. mykiss (0.6) and highest for the snail Lymnaea stagnalis (2670). Following the European-based approach and using EC10 values, species sensitivity distributions (SSDs) were developed and a median hazardous concentration for 5% of the organisms of 1.80 µg Co/L was derived. Chronic EC20 values were used, also in an SSD approach, to derive a US Environmental Protection Agency-style final chronic value of 7.13 µg Co/L. Environ Toxicol Chem 2020;39:799-811. © 2020 SETAC.