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When selecting chemical treatment levels for behavioral toxicology studies, several factors must be considered. Caffeine treatment levels in the present study were selected based on upper centile values for predicted environmental exposure scenarios from wastewater effluent16. When possible, we routinely select treatment levels for aquatic toxicology studies using probabilistic exposure assessments of environmental observations19,20,21. A THV, which is calculable for medicines, was also included as a treatment level in the present study. THV values (Eq. 1)22,23 are defined as predicted water concentrations leading to human therapeutic doses (Cmax) of pharmaceuticals in fish23, are inspired from initial plasma modeling efforts24, and are calculated based on blood:water chemical partitioning coefficients (Eq. 2)25.
THV = Cmax / log PBW (Eq. 1)
log PBW = log [(100.73 . log Kow · 0.16)+0.84] (Eq. 2)
Here, we also select sublethal treatment levels relative to zebrafish and fathead minnow LC50 values. We consider this approach a useful benchmarking procedure for behavioral responses, particularly when comparing thresholds of specific behaviors with a fish model across multiple chemicals. It further facilitates calculations of acute to chronic ratios, which can be diagnostically useful in aquatic toxicology for mechanistic studies and assessments. LC50 values were obtained from preliminary toxicity bioassays following the standardized guidelines given in step 2.1.
In this protocol, we employ common experimental designs and statistical techniques recommended by the US EPA and OECD standardized methods for toxicology studies with fish models. Though we report p values (e.g., <0.01, <0.05, <0.10), significant differences (α = 0.10) in activity levels are identified among treatments using analysis of variance (ANOVA) if normality and equivalence of variance assumptions are met. Dunnett's or Tukey's HSD post hoc tests are performed to identify treatment level differences. We select this alpha (α = 0.10) value to reduce type II errors, particularly for early tier assays and when an understanding of biologically important effect size is limited for understudied behavioral endpoints and model organisms26, instead of employing procedures more common in the biomedical sciences for multiple comparisons (e.g., Bonferroni correction for RNA-Seq data)27. Future studies are needed to understand variability of these behavioral responses and potentially modify experimental designs (e.g., increase replication) accordingly.
A number of factors can influence behavior of larval fish in addition to chemical exposure. For example, time of day, age, well size, temperature, lighting condition, and volume of exposure solution in each well represent important considerations11,30. For these reasons, precautions should be taken to minimize the effects of external factors that could influence locomotor behavior of the larval fish during experimentation. Behavioral observations should be performed in narrow time windows (3 to 4 h) and across time periods when time of day effects are expected to have minimal influence on larval locomotor behavior11. Additionally, larval fish should be maintained at a consistent temperature (28 ± 1 °C for zebrafish and 24 ± 1 °C for FHM) and on a defined light/dark cycle in temperature-controlled incubators throughout the exposure period. In addition, the temperature of the laboratory where behaviors are recorded should be maintained to conditions approximating experimental conditions to avoid temperature influences on behaviors. Further, wells used during behavioral observations should be maintained at a consistent volume for each individual fish.
Larval and embryonic zebrafish PMRs have been previously used in the biomedical sciences to identify potential therapeutic targets for novel compounds12,13. This protocol expands on previous behavioral research with zebrafish by utilizing 38 endpoints to investigate chemical bioactivity of environmental contaminants. Although caffeine is a common aquatic contaminant with an understood mechanism of action (MoA), many compounds in commerce lack important mechanistic data. Therefore, this protocol can be employed to gain insight of MoAs for compounds lacking toxicity data, including commercial chemicals39. Furthermore, the protocol provides methods for two of the most commonly used fish models. As noted previously, whereas the zebrafish is a common biomedical fish model that is becoming increasingly popular in ecotoxicology, the fathead minnow is commonly used as an ecological model for environmental assessment applications but has received comparatively less attention in behavioral studies with automated systems compared to the zebrafish. Though there remains no standardized regulatory methods for fish behavioral toxicology studies, this protocol provides an approach to support future efforts.
Caffeine elicited behavioral responses in each of the fish models at levels that have been detected in the aquatic environment16. Rodriguez-Gil et al. 2018 developed global environmental exposure distributions in aquatic systems based on measured values of caffeine16. Specifically, 95% of predicted wastewater effluent concentrations would fall below the LOECs for the most sensitive behavioral endpoints of zebrafish and fathead minnow in the present study (Table 2). Though several behavioral effects of caffeine were observed in zebrafish (particularly in dark conditions) at environmentally relevant levels, it is unclear whether these behavioral modifications might occur in natural fish populations or result in ecologically important adverse outcomes. Though useful for sensitive, diagnostic screening purposes, larval fish behavioral thresholds may not be representative of other life history stages or of fish in natural populations. Further research is warranted to determine whether similar behavioral response thresholds would occur in nature and be indicative of adverse outcomes at the individual or population levels of biological organization.