Experimental Protocol for Examining Behavioral Response Profiles in Larval Fish: Application to the Neuro-stimulant Caffeine

Fish models and behaviors are increasingly used in the biomedical sciences; however, fish have long been the subject of ecological, physiological and toxicological studies. Using automated digital tracking platforms, recent efforts in neuropharmacology are leveraging larval fish locomotor behaviors to identify potential therapeutic targets for novel small molecules. Similar to these efforts, research in the environmental sciences and comparative pharmacology and toxicology is examining various behaviors of fish models as diagnostic tools in tiered evaluation of contaminants and real-time monitoring of surface waters for contaminant threats. Whereas the zebrafish is a popular larval fish model in the biomedical sciences, the fathead minnow is a common larval fish model in ecotoxicology. Unfortunately, fathead minnow larvae have received considerably less attention in behavioral studies. Here, we develop and demonstrate a behavioral profile protocol using caffeine as a model neurostimulant. Though photomotor responses of fathead minnows were occasionally affected by caffeine, zebrafish were markedly more sensitive for photomotor and locomotor endpoints, which responded at environmentally relevant levels. Future studies are needed to understand comparative behavioral sensitivity differences among fish with age and time of day, and to determine whether similar behavioral effects would occur in nature and be indicative of adverse outcomes at the individual or population levels of biological organization.


Introduction
Though fish models are increasingly used for biomedical studies, fish have been routinely employed for ecology and physiology studies, to examine contamination of surface waters, and to understand toxicological thresholds of chemicals. Such efforts are important because chemical contamination can impair aquatic ecosystems and jeopardize the quality of source water supplies 1,2 . Most of the chemicals in commerce, however, lack even basic toxicology information 3 .
Animal model assays traditionally used in regulatory toxicity testing are resource intensive and cannot provide the high throughput, early tier screening needed for toxicity testing in the 21st century 4 . Subsequently, there is a growing impetus to adopt and utilize in vitro models that can more rapidly and efficiently screen compounds for biological activities 3,5 . Though cell based models present many opportunities, they often lack biological complexity, and thus do not account for many important whole organism processes, including metabolism 6 . The zebrafish is a common biomedical animal model that is gaining popularity as an alternative model in aquatic toxicology and ecotoxicology 7,8 . Given their small size, rapid development, and high fecundity, fish models can be used to rapidly and efficiently screen chemicals for bioactivity and toxicity at the whole organism scale 9 . With the aid of automated tracking software, larval zebrafish behaviors provide enhanced diagnostic utility in screening contaminants for toxicity 10,11 . Studies in the pharmaceutical sciences have demonstrated that locomotor endpoints are informative of chemical mechanisms of action, can be used to phenotype behaviors, and then may tentatively identify subcellular targets for novel molecules 12,13 . Whereas the zebrafish is a popular larval fish model in the biomedical sciences, the fathead minnow is a common, ecologically important fish model that is used for ecotoxicology studies and during prospective (e.g., new chemical evaluations) and retrospective (e.g., ambient surface water or wastewater effluent discharge monitoring) environmental assessments. Unfortunately, behavioral responses of larval fathead minnows have received markedly less attention than zebrafish. Our ongoing research with two common larval fish models, the zebrafish and fathead minnow, suggests that larval fish swimming patterns appear unique to anticipated modes or mechanisms of action for diverse chemicals. Thus, behavioral endpoints provide the potential to rapidly and sensitively examine chemicals for toxicity and to identify subcellular targets for industrial chemical and other contaminants, particularly during early tier assessments.
Here, we report a protocol for examining behavioral response profiles in larval fish. We demonstrate these methods using caffeine, a model neurostimulant and a common aquatic contaminant that is introduced to aquatic systems through discharge from wastewater treatments plants following human consumption of foods, beverages, and pharmaceuticals formulated with caffeine . We further identify effects of caffeine across several locomotor endpoints to develop chemical response profiles for each fish model. Caffeine treatment levels used in this study represent the upper centiles of exposure distributions based on measured environmental values of caffeine 16 . We also include treatments benchmarked to larval fish LC 50 values, and the therapeutic hazard value (THV), a pharmaceutical concentration in water that is anticipated to result in plasma levels in fish consistent with a human therapeutic plasma dose.

Protocol
Studies in this protocol generally follow standardized experimental design and recommended statistical analysis guidelines from the US Environmental Protection Agency (EPA no. 2000.0) for fathead minnows and the Organization for Economic Cooperation and Development (OECD no. 236) for zebrafish. These experimental designs (e.g., increasing replication) can be modified within the current protocol for future studies. Fish culture conditions follow previously published literature 17 . All experimental procedures and fish culture protocols followed Institutional Animal Care and Use Committee protocols approved at Baylor University.   1. To ensure that each well contains an equal volume of solution, transfer zebrafish larvae to 48 well plates using a 5,000 µL autopipette for a 1,000 µL volume per well. Use the autopipette to withdraw and transfer both the zebrafish larvae and exposure solution simultaneously. 2. Due to their larger size, transfer fathead minnow larvae using a transfer pipette with the tip cut off. Prior to transferring fathead minnow larvae to individual wells, fill each well to 2,000 µL using an autopipette. When transferring individual fathead larvae to wells, place the tip of the transfer pipette in the well solution and allow the fish to swim from the pipette tip into the well.

Exposing Fish to Chemical Treatment
5. Use the cursor to delineate the circular video tracking area in the top left well of the well plate. Select "Top-Right Mark" and then outline the viewing area of the top right well. Then, select "Bottom Mark" to outline the bottom right well. NOTE: After drawing the circular outline, its position will likely need to be adjusted. To adjust the position of the outline, click "select" and then use the cursor to move the outlined area. Also, outlines can be replicated by clicking "Copy" and then "Paste". 6. After the top left, top right, and bottom right well tracking areas have been defined, click "Build" to prompt the software to automatically delineate the viewing areas of the remaining wells. 7. In the area labeled "Calibration", click "Draw Scale". Use the cursor to draw a horizontal line across the plate. Once the line is drawn, a dialogue box labeled "Calibration measurement" will appear. Enter the well plate length and click "OK". 8. Exit the drawing manager by clicking the "Draw Areas" icon. 9. Click the "Tiles" icon. Using the cursor, highlight all the boxes that appear on the viewing screen so that each box is green.
NOTE: The Tiles icon appears as a group of six individual small squares 10. "Click View| Full Screen". To the right of the plate viewing area, click "Bkg" in the box labeled "Detection Threshold". Use the threshold adjustment bar to set the pixel detection threshold. Once, the appropriate pixel detection threshold is selected, click "Apply to Group". NOTE: This protocol sets the detection threshold at 13 in black mode for zebrafish observations and at 110 in transparent mode for fathead minnow observations. 11. In the box labeled "Movement Threshold", enter the desired movement speed tracking parameters. Once speed parameters are set, click "Apply to Group". NOTE: This protocol sets small/large movements at 20 mm/s and inactive/small movements at 5 mm/s. These selections program the software to track larval fish movement at three different speed levels: inactive (freezing) = <5 mm/s, small (cruising) = 5-20 mm/s, and large (bursting) = >20 mm/s. 12. Click "Parameters | Protocol Parameters" from the drop-down menu. In the dialogue box, select the "Time" tab. Enter the observation time and the integration time. After parameters are entered click "Ok". 13. To set the light/dark photoperiod times and light intensity for each photoperiod open the light driver settings dialogue box by selecting "Light Driving" from the "Parameters" drop down menu. NOTE: See protocol video for setting multiple light-dark photoperiods. 14. After the video tracking parameters have been set, save the observation protocol.
NOTE: This protocol observes fish behavior over a 50 min period that includes a 10 min acclimation phase followed by 4 altering light/ dark phases consisting of two 10 min light periods and two 10 min dark periods. The integration time is set to measure behavior for each minute of the 50 min behavioral trial.    In addition to measuring larval PMRs, light and dark locomotor activity was analyzed across three speed thresholds for distance moved, number of movements, and duration of movements. This data is used to develop behavioral response profiles for caffeine (Figure 3, Supplemental  Figure 1). In both of the fish models, caffeine inhibited activity at all significantly affected locomotor endpoints. Both fish models demonstrated increased activity at the bursting speed thresholds following exposure to caffeine, though not significantly. Similar to the results of the PMR observations, caffeine effected a greater number of zebrafish locomotor endpoints. In fact, caffeine significantly altered several locomotor responses under dark conditions at environmentally realistic levels below the THV. However, fathead minnow locomotor activity was not significantly affected under light conditions by any treatment level.

Discussion
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 effluent 16 . When possible, we routinely select treatment levels for aquatic toxicology studies using probabilistic exposure assessments of environmental observations 19,20,21 . 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 fish 23 , are inspired from initial plasma modeling efforts 24 , and are calculated based on blood:water chemical partitioning coefficients (Eq. 2) 25 . 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 organisms . 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 considerations 11,30 . 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 behavior 11 . 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 compounds 12,13 . 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 chemicals 39 . 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 environment 16 . Rodriguez-Gil et al. 2018 developed global environmental exposure distributions in aquatic systems based on measured values of caffeine 16 . 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.

Disclosures
The authors have nothing to disclose.