Journal of Aquatic Animal Health 25:53–65, 2013  C American Fisheries Society 2013 ISSN: 0899-7659 print / 1548-8667 online DOI: 10.1080/08997659.2012.747450

ARTICLE

Effects of Aquarium-Related Stressors on the Zebrafish: A Comparison of Behavioral, Physiological, and Biochemical Indicators David Gronquist and John A. Berges* Downloaded by [University of Wisconsin-Milwaukee] at 11:59 22 January 2013

Department of Biological Sciences, University of Wisconsin–Milwaukee, Lapham Hall, 3209 North Maryland Avenue, Milwaukee, Wisconsin 53211, USA

Abstract Fishes in aquaria and aquaculture settings may experience a variety of stressors including crowding, different lighting, periods of food deprivation, and vibrations from sources including pumps and tapping of tank sides. The effects of such low-level chronic stress are poorly explored. We used replicate sets of six Zebrafish Danio rerio in four series of experiments to compare the effects of (1) stocking densities ranging from 0.13 to 1.2 fish/L, (2) cool white (6,500 K), warm white (4,100 K), and ultraviolet-enhanced (420 actinic) fluorescent lighting, (3) food deprivation for up to 9 d, and (4) random mechanical tapping on the tank side sufficient to induce a startle response on specific behaviors (fin display, body fluttering, aggression, mouth gaping, and chattering), dissolved cortisol released into aquarium water (collected on a chromatography column and analyzed with an immunoassay), and heat-shock proteins (HSPs 27, 40, 60, and 70) detected immunochemically in western blots of muscle tissue. Of all the treatments, only food deprivation resulted in significant differences between control and treatment fish; dissolved cortisol declined after 120 h of starvation and HSP40 and HSP60 in muscle tissue increased significantly after 216 h. High variability in behaviors and HSP measurements was noted within all controls and treatments, suggesting that effects of treatments were experienced unequally by individuals within a treatment. Social stressors resulting from dominance hierarchies may play a critical role in modifying the effects of aquarium and aquaculture stressors on captive fish.

Fish on display in public or in home aquaria, retail pet stores, and aquaculture production systems may be subject to a number of environmental factors known to induce stress, including high stocking densities (Haukenes and Barton 2004; Ramsay et al. 2006), various types of artificial lighting (Head and Malison 2000; Karakatsouli et al. 2010), periods of food deprivation (Cara et al. 2005; Weber and Bosworth 2005), and varying levels of noise (Smith et al. 2004; Wysocki et al. 2004). However, despite recognition of these issues in the industry (e.g., Bartelme 2004), relatively few systematic studies have been carried out using chronic low-level stressful conditions rather than acute conditions (e.g., Ashley 2007). Stress is most generally defined in terms of effects on organism function to the point where chances of survival are reduced (Brett 1958; Barton 1997). Fish responses to

stress occur at many different levels including changes in stress hormones, metabolic changes such as an increase of the amount of glucose and a decrease of tissue glycogen, cellular changes such as heat-shock protein production, changes in immune function, hematological features, and osmoregulatory disturbance, as well as tertiary responses in behavior, growth, swimming, and disease resistance (Barton 2002; Iwama et al. 2006). Considerable emphasis has been placed on diagnosing stress using changes in cortisol levels in the fish (Iwama et al. 2006), while understanding behavioral responses in aquaculture has been increasingly favored for assessing stress and fish welfare (Ashley 2007). However, given the multiple levels of response, a comparison of measurements made at different levels seems a valuable approach (e.g., Anderson et al. 2011).

*Corresponding author: [email protected] Received March 14, 2012; accepted November 4, 2012

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Direct observation of fish behavior is a relatively straightforward and noninvasive means to assess the effect of a stressor. Fish in aquaria generally respond to disturbances by altering frequency of behaviors such as erratic movements, chasing other fish, nipping at fins, different fin displays, or gaping of the mouth (e.g., Chervova 1997; Haukenes and Barton 2004). As a means of quantifying the stress response, levels of cortisol in the bloodstream are commonly accepted as reliable (Wendelaar Bonga 1997; Scott et al. 2001; Ramsay et al. 2006), though the response can be transient, so care needs to be taken in interpretation (e.g., Wendelaar Bonga 1997; Davis and Small 2006). However, such a measurement is highly invasive and sampling can induce stress itself. Scott and Sorensen (1994) developed the alternative of measuring steroids excreted into the water; subsequent work has demonstrated good correlations between steroid concentration in the water and in plasma (Scott et al. 2001), and the method has now been used in several species (Scott and Ellis 2007). Transient responses in cortisol remain a concern for interpretation, however. Measurements of tissue proteins may provide a longer-term and more integrative measure of stress. One group of proteins that has received particular attention are the so-called heat-shock proteins (HSPs), a set of highly conserved proteins defined by their molecular masses (e.g., HSP70s have molecular masses near 70 KDa) that have diverse functions and are expressed at increased levels under stress (e.g., Ackerman et al. 2000; Basu et al. 2002; Iwama et al. 2004). Measurements of HSPs are most commonly made at the level of transcription (i.e., messenger RNAs) or at the protein level (immunochemically). These methods are necessarily invasive and typically involve dissection of the organism. There are concerns about the interpretability of tissue levels of HSPs with respect to stress (Iwama et al. 1999, 2004), but they continue to be widely used. Surprisingly few studies have attempted to monitor stress at more than one or two different levels of biological organization and to compare the responses. In the present study, we chose to monitor behavior, a physiological response (cortisol release), and a biochemical response (tissue HSP levels). Zebrafish Danio rerio is a species that represents a convenient model fish system for studying aquarium and aquaculture stress, is easy to rear and work with experimentally, and has a well-established biochemical and genetic background. Zebrafish are kept in home and public aquaria worldwide and there is a well-developed commercial trade for them (Westerfield 1993; Lawrence 2007). The commercial stocks originate from fish collected in rice fields and quiet streams in the Ganges River watershed of India and Bangladesh (Lawrence 2007). Although relatively little is known about their ecology and behavior in nature (Spence et al. 2008), Zebrafish have been used extensively in fields ranging from toxicology and biochemistry to medicine, genetics, and even social behavior (Ton et al. 2002; Airaksinen et al. 2003; Bosworth et al. 2005; Chizinski et al. 2008; Saverino and Gerlai 2008).

In this study, we examined four potential stressors that would be commonly experienced by fish in aquaria: different stocking densities, variations in tank lighting spectrum, deprivation of food, and effects of sound (pressure) waves created by tapping on the side of the tank. Three responses were measured: fish behavior, cortisol released into aquarium water, and levels of four HSP proteins in muscle tissue. Fishes in display aquaria and aquaculture settings are often stocked at higher densities than found in nature (Bartelme 2004). The aquaculture literature is rich with studies of stocking density for optimized growth, and some of these have also assessed stress measures (see Ellis et al. 2002; Aksakal et al. 2011; Castranova et al. 2011). Based on results from this literature, we hypothesized that increasing stocking densities in Zebrafish would result in alterations in behavior, increased cortisol release, and elevated tissue HSPs. Lighting spectra for aquaria differ from that of natural environments. In particular, display aquaria lighting can be enhanced at the ultraviolet (UV) end of the spectrum. Zebrafish are highly visual fish and have sensitivity to light in the UV range (Robinson et al. 1993). We hypothesized that there would be no differences in responses between fish in aquaria lighted with typical “cool white” spectrum fluorescent indoor bulbs (color temperature, 4,100 K) and enhanced daylight-spectrum lamps (color temperature, 6,500 K), but that UV-enhanced bulbs (color temperature, 7,100 K) would result in changes in behaviors and elevated cortisol and HSPs. Fishes in aquaria may be fed to maximize growth rate (Jobling 1981) or minimize aquarium maintenance (Ashley 2007); it seems likely that in home aquaria, delayed and missed feedings are common. Food deprivation is correlated with stress responses in the literature (e.g., Br¨ann¨as et al. 2003; Bayir et al. 2011); thus, we hypothesized that depriving Zebrafish of food over a 10-d period would result in changes in behavior and an increase in cortisol levels in water and HSPs in tissues with longer deprivation. Finally, to judge from the prevalence of signs in pet shops asking customers to refrain from touching aquaria, it seems likely that fishes are subject to the intermittent low-frequency vibrations that “tapping” on aquarium glass would produce (cf., Leong et al. 2009). The issue of acoustic and vibrational stress due to factors like pump noise and tank echoes is well appreciated in aquaculture (Craven et al. 2009), though there are also positive aspects to sound (Papoutsoglou et al. 2010). Zebrafish do exhibit clear startle responses to acoustic stimuli (Colwill et al. 2011) and we hypothesized that fish experiencing tapping on aquarium glass would exhibit changes in behavior and elevated cortisol and HSPs relative to those that did not. METHODS Fish and General Maintenance Adult Zebrafish (90–120 d old) were obtained from a commercial supplier (Fish2U.com, Gibsonton, Florida). To

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minimize fungal infections or parasites, the fish were treated with Paracide-F (Argent Chemical Laboratories, Redmond, Washington) for 1 h at 175 mg/L for three consecutive days (Francis-Floyd 1996). Zebrafish were maintained in a 450-L aquarium under a 12 h light : 12 h dark photoperiod in a flow-through system with dechlorinated water at 28◦ C and fed Grower BioDiet fish food (Bio-Oregon, Warrenton, Oregon) daily until satiation. Fish were held for a minimum of 3 weeks after the Paracide-F treatment before use in experiments and were used only once for each experiment. Experimental Design Four different series of experiments (manipulating stocking density, tank-lighting spectra, time of food deprivation, and tapping), each lasting 10 d, were conducted sequentially using similar experimental designs. In each series, sets of six Zebrafish were randomly assigned to each of nine 45-L aquaria, which were divided into three treatments (sets A, B, and C; Figure 1). Flow into each aquarium was adjusted to 3.0 L/min. Fish were acclimated in aquaria for 48 h before the experiments began. Stocking density.—To examine the effects of stocking density, water volumes in which Zebrafish were free to move were restricted using fine-mesh tank dividers (cat. no. 10600, Lee’s Aquarium and Pet Products, San Marcos, California) and aquarium gravel at the base of the divider. Volumes included the full tank (45 L for set C, for a density of 0.13 fish/L), approximately one-half the tank (20 L for set B, 0.30 fish/L), and approximately one-eighth of the tank (5 L for set A, 1.2 fish/L). Tank dividers were present in all tanks; they were placed against one wall of the aquaria in the 45-L treatment. Tank lighting.—To examine the effects of different light qualities, each group of three aquaria (series A, B, and C) was exposed to different lighting by suspending separate fluorescent fixtures (part no. 758485, Lithonia Lighting MWDC, Hanover Park, Illinois) with different tubes over each tank. Photoperiods

FIGURE 1. General experimental design of experiments, consisting of nine 45-L aquaria in three series (A, B, and C), all fed from a common header tank. Flow-through of water was controlled independently for each tank using a valve, and water level was maintained by a drain standpipe. Each tank contained six Zebrafish. Water temperature was maintained at 28◦ C using aquarium immersion heaters, and lighting was provided from above. Each tank series was isolated from each other using hanging dividers of heavy black felt.

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were the same in all cases (12 h light : 12 h dark). Hanging dividers of thick black felt were used to isolate treatments. Series A used enhanced daylight-spectrum lighting (813152, Philips, Philips Electronics, Markham, Ontario; color temperature of 6,500 K), series B used lamps more strongly weighted to a shorter wavelength, typical of those used in display aquaria to enhance fish colors (TL 40W/03RS, Philips, Philips Electronics; color temperature of 7,100 K, 420 actinic), and series C had cool white fluorescent lighting, typical of many public buildings (813157, Philips, Philips Electronics; (color temperature of 4,100 K). Spectra of the lamps used, in terms of relative radiant power, are shown in Figure 2. In all cases, quantum irradiance was measured (Li-Cor LI-250A with a 2 pi sensor, LI-COR Biosciences, Lincoln, Nebraska) and adjusted to an average of 210 µmol quanta·m−2·s−1 for all treatments. Food deprivation.—To examine the effects of withholding food, Zebrafish were acclimated to the experimental tank for 48 h on the same feeding regime as in the common holding tank, and then feeding was suspended. Series A were sampled after 24 h without food, series B after 72 h, and series C after 216 h without food. Tapping.—To examine the effects of percussion on the tank wall, “tapping” devices (Figure 3) were designed and constructed (T. Consi and K. Verhein, University of Wisconsin– Milwaukee, unpublished). The computer-controlled, programmable devices consisted of a microcontroller chip (PIC18F1320-I/P-ND, Digi-key Corporation, Thief River Falls, Minnesota), programmed through an RS232 serial converter (MAX233CPP-ND, Digi-key Corporation), that controlled a 12-V DC, pull-type solenoid (2137941, Jameco Electronics, Belmont, California) with a rubber stopper fixed to the end.

FIGURE 2. Relative spectra of fluorescence lamps used in lighting experiments. These include enhanced daylight-spectrum lighting (color temperature, 6,500 K), lamps strongly weighted to shorter wavelength to enhance fish colors (color temperature, 7,100 K, 420 actinic), and cool white fluorescent lighting, typical of many public buildings (color temperature, 4,100 K). Data obtained from http://www.usa.lighting.philips.com/connect/tools literature/

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FIGURE 3. Design of tank tapping devices (K. Verhein, University of Wisconsin–Milwaukee, unpublished). The computer-controlled, programmable units consisted of a Microchip PIC18F1320 microcontroller, an RS232 serial converter (operated at 9,600 baud 8N1), and a 12-V DC pull-type solenoid (“tapper”) with a rubber stopper fixed to the tapping end. Each tapper was mounted to the plastic frame of an aquarium and the distance adjusted to provide the minimum force needed to evoke a startle response in the Zebrafish.

Power was provided by a regulated DC supply (PSR-10, Speco Technologies, Amityville, New York). The solenoid allowed a spring-driven piston to strike the tank at specified intervals and frequency. The force of each “tap” was controlled by adjusting distance from the tank to provide the minimum needed to induce a startle response in the fish. The tappers were controlled using a computer and custom software written in BASIC (J. A. Berges, unpublished). Series A had 10-s bursts of 1 tap/s delivered randomly for a total of 10 min in every 24 h. Series B had 10-s bursts of 2 taps/s delivered randomly for a total of 20 min in 24 h. Tank series C received no tapping. Care was taken to ensure that vibrations were not transmitted among tank series; we verified that taps on one series of tanks evoked no detectible response in other tank series. Observations and Sampling Behavioral observations were made for 5-min periods sequentially for each tank, midafternoon on each day of the experiments (essentially the “sampling all occurrences of some behaviors” described by Altmann 1974). Black felt dividers hung between tanks kept disturbance to a minimum. The most frequent behaviors were identified based on initial observations during acclimation at the beginning of the experiment. During each 5-min period, each occurrence of each of the behaviors was counted with no attempt made to assign behaviors to

individual fish. Statistical analyses were performed on these counts of behavior, as described below. Water samples for analysis of excreted cortisol were collected on days 5 and 10 of each experiment, except in the case of the feeding experiments where samples were collected at the end of the experiments for series A and B (24 and 72 h, respectively) and at two points (120 h and 216 h) for series C. One hour before collection of water, the main valve on the header tank was turned off to stop the flow of water and allow excreted cortisol to accumulate in each aquarium. During this time, water temperature was monitored and did not change by more than 0.2◦ C. After 1 h, 2 L of water was collected from each tank by siphon. Cortisol in the water was extracted following Scott and Sorensen (1994) and Scott et al. (2001). Briefly, water samples were prefiltered through glass fiber filters (25 mm, type A/E, Pall, Ann Arbor, Michigan) to remove particulates and then pumped at a rate of 1 L/h using a peristaltic pump (Masterflex 7553-70, Cole-Parmer Instrument, Vernon Hills, Illinois) through September-Pak Plus C-18 cartridges (WAT020515, Waters, Milford, Massachusetts), which had been activated immediately before use with 5 mL of 100% methanol followed by 5 mL of distilled water. Cartridges were rinsed with 5 mL of distilled water and excess water was removed by forcing 5 mL of air though samples with a syringe. Cartridges were stored at −70◦ C for later analysis. In order to quantify cortisol recovery from aquarium water four control aquaria were set up with additions of 0, 0.5, 5, or 50 ng/L of cortisol solution (H6909, hydrocortisone, SigmaAldrich, St. Louis, Missouri). Water samples were taken and processed as described above. Tissue samples were taken on the final day of the experiments. Zebrafish were removed from their treatment tanks, rapidly anesthetized with an overdose of tricaine methanesulfonate (MS-222, Argent Chemical Laboratories; (>100 mg/L, neutralized with 1 M NaOH), flash-frozen in cryotubes in liquid nitrogen, and stored at −70◦ C for later analysis. Cortisol Analysis Cortisol analysis followed that of Scott and Sorensen (1994) with some modifications. Cortisol was extracted from thawed C18 cartridges in 4 mL of ethyl acetate, followed by a purge with 10 mL of air to ensure complete collection. Ethyl acetate was evaporated by placing samples in a 45◦ C water bath and drying under a stream of N2 gas. Dried samples were frozen (−70◦ C) and accumulated for enzyme immunoassays (EIA). Cortisol was quantified using a Cortisol EIA kit based on a 96-well microplate (58212, Cayman Chemical, Ann Arbor, Michigan) according to manufacturer’s directions and using the kit standard. Dried samples (including recovery controls) were redissolved in 100 µL of the provided EIA buffer. Samples and standards were analyzed using a VERSAmax microplate reader (Molecular Devices, Sunnyvale, California) and Softmax Pro software (version 4.8, Molecular Devices). Calculations of cortisol concentrations were performed as described in the kit instructions. Where samples produced results that were out of

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range, a 100-fold dilution of the extracts were performed and the samples rerun. HSP Analysis Frozen Zebrafish were thawed on ice and bilaterally dissected, and muscle tissue was removed and placed into tared microcentrifuge tubes. Extraction buffer, consisting of tris-SDS buffer (50 mM tris-HCl, 4% [w/v] sodium dodecyl sulfate, pH 7.5; Fisher Scientific, Fairlawn, New Jersey) with protease inhibitor (78415, HaltTM EDTA-free, Pierce Chemical, Rockford, Illinois; 100 µL inhibitor to 10 mL buffer) was added in the proportion 1 mL buffer : 0.2 g tissue. Samples were homogenized on ice using a rotor-stator-type blender (PRO 200, Pro Scientific, Oxford, Connecticut) for three cycles of 20 s, then centrifuged for 2 min at 16,000 × g. From each supernatant, subsamples were aliquoted for electrophoresis and protein determinations and frozen (−70◦ C) for later analysis. Protein content of homogenates was measured using a BCA Protein Assay Kit (23225, Pierce, Rockford, Illinois) and the recommended 37◦ C microplate protocol, and absorbance was corrected using blanks for the buffer. Homogenate samples were prepared for electrophoresis following Greene et al. (1991) adding one volume of 0.2 M dithiothreitol and two volumes of 4% (w/v) SDS, 15% (v/v) glycerol, and 0.05% (w/v) bromothymol blue. Samples were boiled for 5 min and centrifuged at 16,000 × g for 1 min. For analyses, four fish from each treatment (out of a set of three tanks × six fish = 18 fish exposed to each treatment) were randomly selected for analysis. Homogenates were loaded on an equal protein basis (20 µg) alongside a blank, a molecular mass standard (product no. 26681, Blue Ranger Pre-stained Protein Molecular Weight Marker Mix, Pierce) and an HSP standard on 15-well 10% Precise Protein gels (25241, Pierce). The HSP standard consisted of a mixture of 100 ng each of the following proteins: HSP27 (spp-715), HSP40 (spp-400), HSP60 (spp-741), and HSP70 (nsp-555), all obtained from Stressgen Bioreagents, Victoria, British Columbia. Proteins were separated by polyacrylamide gel electrophoresis in a HEPES-tris buffer solution (recommended by the gel manufacturer) in a Mini Protean 3 system (Bio-Rad Laboratories, Hercules, California). In each case, duplicate gels were run, one for staining and one for blotting. Gels were run at 130 V for approximately 45 min or until tracking buffer reached the bottom of the gel. One of the gels was stained with Coomassie Blue R-250, detained, and imaged using a Kodak 1D Digital Analysis system (version 4.0, Eastman Kodak, Rochester, New York). The second gel was blotted onto 0.2-µm nitrocellulose membrane (162-0212, Bio-Rad Laboratories, Hercules, California) using a Mini Trans-blot cell (Bio-Rad Laboratories) and Towbin buffer (Towbin et al. 1979) and blotting at 100 V for 60 min using a Powerpac 200 power supply (Bio-Rad Laboratories). To verify complete transfer, membranes were immersed in Ponceau S stain agitated on a rocker table for 5 min and then rinsed with distilled water until bands could be visualized. Membranes were allowed to dry overnight before being probed with antibodies.

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Probing and detection followed guidelines in the Pierce Supersignal West Pico Chemiluminescent Substrate kit (Pierce). Membranes were blocked with 5% (w/v) skim milk powder in tris-buffered saline (TBS) for 1 h. Each membrane was probed sequentially with rabbit polyclonal antibodies in the following order: anti-HSP70 (spa-812), anti-HSP60 (spa-805), antiHSP40 (spa-400), and anti-HSP27 (spa-803) (Stressgen Bioreagent, Victoria, British Columbia). In order to ensure proper scaling of HSP signals, replicate samples were also blotted and probed with an anti-actin antibody (A 2066, Sigma Chemical, St. Louis, Missouri); this provided a specific index of muscle tissue. Between antibodies, blots were stripped of immunoglobins (21062, Restore Western Blot Stripping Buffer, Pierce). In each case, single antibodies were diluted 1:2,000 with skim milkTBS block and incubated with membranes for 1 h. After washing, secondary antibodies (31460, HRP-conjugated goat antirabbit immunoglobin, Pierce) were applied at 1:50,000 dilution in skim milk-TBS block and incubated for 1 h. After a second washing series, membranes were rinsed in TBS and detection performed using a chemiluminescent substrate (34080, Supersignal West Pico Chemiluminescent Substrate, Pierce) prepared according to manufacturer’s directions. Chemiluminescence was detected by exposure to CL-Xposure Film (34090, Pierce) and film was imaged and quantified using Kodak 1D Digital Analysis system (version 4.0, Eastman Kodak). Areadensity values were determined for each band and scaled to convenient numerical values (0–50); because all treatments were run on a single gel or blot, variation between exposures was minimized. Because antibody standards were derived from different species, no attempt was made to scale blots to absolute protein or to compare quantity of protein among different HSPs. Statistical Analyses Analyses were carried out using SigmaPlot (version 12.0, Systat Software, San Jose, California). We used two approaches to analyze results. First, using mean responses, results were compared among treatments within each experimental series for each parameter using ANOVA techniques, followed by Tukey’s tests to identify which treatments differed from each other. In the case of behavioral data, where multiple measurements were made over time, we used two-way, repeated-measures (RM) ANOVA in which treatment and time were used as factors, and aquarium tanks as observation units (comparable to the model used for ethological data in Anderson et al. 2011). Secondly, recognizing the importance of changing variance of measurements as indicators (Orlando and Guillette 2001), we tested for heterogeneity of variance by calculating the absolute values of the difference of each individual measurement from the mean and running ANOVA on these data (as in Anderson et al. 2011). Where possible (i.e., where assumptions of normality and equal variance were met), raw data were used; otherwise, data were transformed using square-root or common-logarithm transformations. In cases where transformed data still did not meet the

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requirements for parametric tests, Kruskal–Wallis ANOVA on ranks was performed instead. RESULTS

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Behavioral Measurements Five discrete behaviors were used in analyses after the ethogram was developed from initial observations (Table 1). Behaviors were consistent among experimental series and we did not observe novel behaviors under particular treatments. Cortisol Measurements Using the column extraction method and EIA kit, cortisol was readily detected in the tank water; the effective detection limit of the method for aquarium water was approximately 10 pg/L. Based on tanks with known additions of cortisol, the recovery of cortisol was complete (i.e., 100%) within the range 0.5–50 ng/L, and no cortisol was detected in the water in the tank without additions (data not shown). Across all controls, cortisol in tank water averaged about 0.53 ng/L. Since this represented the amount accumulated in 1 h with an average biomass of 2.5 g/45-L tank, and since no cortisol was detected in the inflowing water (i.e., the tank without cortisol additions), we estimated an average rate of cortisol release of 9.6 ng·g−1·h−1. This rate was an overestimate, since it neglected residual cortisol, but for a 45-L tank with an inflow of 3.0 L/min, the error should be less than 10%. Stocking Density Behaviors did not differ among stocking densities (two-way RM ANOVA: fin display, P > 0.9; flutter, P > 0.7; aggression, P > 0.4; gape, P > 0.1; chatter, P > 0.8; Figure 4A); there was no effect of time on behavior (P > 0.1 in all cases) and no interaction between treatment and time (P > 0.3 in all cases). For each behavior, there was high variability among replicate tanks. Gaping was least displayed, while chattering was seen most often overall. When analysis was carried out to examine heterogeneity of variance, no differences between treatment and time and no interactions were found (P > 0.1 in all cases). TABLE 1. Ethogram of Zebrafish observed in experiments.

Behavior Fin display Flutter Aggression Gape Chatter

Description Fish extends pelvic and pectoral fins outward to the limit of motion. Propagation of a waving motion along the entire body. Chasing or nipping at the fins of another fish, or both. Opening the mouth for a period of more than 2 s. Rapid and repeated opening and closing of the mouth.

FIGURE 4. Effects of three stocking densities of Zebrafish on (A) behavior, (B) cortisol measured in aquarium water, and (C) HSPs measured in muscle tissue. In each series of three 45-L aquaria, volumes were manipulated using mesh dividers resulting in six Zebrafish in 45 L (0.13 fish/L), 20 L (0.30 fish/L), or 5 L (1.2 fish/L). Aquaria were maintained at 28◦ C on a 12 h light : 12 h dark photoperiod, and fish were fed once a day ad libitum. Average occurrence of behaviors is based on daily 5-min observations over a 10-d period; definitions of behaviors are given in the Methods and in Table 1. Cortisol was measured in 2-L water samples, concentrated using C-18 cartridges, and assayed using enzyme immunoassay following methods of Scott and Sorensen (1994). The HSPs (27, 40, 60, and 70) were extracted, separated using polyacrylamide gel electrophoresis, blotted onto nitrocellulose membranes, probed sequentially with anti-HSP27, HSP40, HSP60, and HSP70 anti-bodies, and quantified using chemiluminescent methods as described in Methods. Bars indicate relative HSP present in four fish randomly selected from each treatment. In each case, error bars represent SD.

Cortisol averaged 0.53 ng/L across all tanks and no significant differences were found among treatments or between sampling times (two-way RM ANOVA: P > 0.8 for treatment, P > 0.5 for time, and P > 0.8 for interaction of treatment and time; Figure 4B). No differences in variability were detected

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(P > 0.2 for treatment, time, and interaction). The 0.13-fish/L density tanks were not sampled on day 5. Relative protein did not differ among treatments for any of the HSPs tested (one-way ANOVA: HSP27, P > 0.2; HSP40, P > 0.8; HSP60, P > 0.2; HSP70, P > 0.7; Figure 4C). Variability among individual fish, both within and among replicate tanks, was high, but no systematic differences related to treatment were found (one-way ANOVA: P > 0.3 in all cases, except in the case of HSP40 where Kruskal–Wallis ANOVA on ranks was performed). Tank Lighting Behaviors did not differ among lighting treatments (two-way RM ANOVA: fin display, P > 0.8; flutter, P > 0.06; aggression, P > 0.3; gape, P > 0.9; chatter, P > 0.8; Figure 5A); however,

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there were some differences in behaviors over time. Frequencies of fin display and flutter were significantly lower for the first three versus the later days, and frequency of aggression was lower on the first day compared with other days (P < 0.05 in all cases). However, these differences were consistent across treatments; no interactions were observed between treatment and time (P > 0.2 in all cases). In terms of relative frequencies, gaping was not observed as often and fin display and chattering appeared to be the most common. Variability of behaviors did not differ with treatment, and in general did not change with time (P > 0.07 in all cases), though in the case of the fluttering, frequencies on the first day were higher only for the 4,100-K lighting treatment (P < 0.05). As was the case for stocking density, cortisol in tank water averaged approximately 24 ng/L and no differences were found among treatments (two-way RM ANOVA: P > 0.3; Figure 5B), though cortisol levels on day 10 were significantly lower than on day 5 (P < 0.03). No changes in variability of data among treatments or over time were detected (P > 0.2 in all cases). Similar to the stocking density experiment, no significant differences were found among HSPs (one-way ANOVA: HSP27, P > 0.7; HSP40, P > 0.9; HSP60, P > 0.7; HSP70, P > 0.6; Figure 5C). Variability was high among individual fish and treatments, but no differences in variability could be attributed to treatment for any HSP (P > 0.4 in all cases; HSP60 and HSP70 required analyses with Kruskal–Wallis ANOVA on ranks). Food Deprivation Most behaviors did not differ among treatments (two-way RM ANOVA: fin display, P > 0.3; aggression, P > 0.2; gape, P > 0.1; chatter, P > 0.2; Figure 6A). However, fluttering increased significantly in frequency for fish deprived of food for 72 or 216 h versus 24 h (Tukey’s test: P < 0.04). In terms of relative frequencies of behaviors, aggression was least common and fin display most common overall. There were no changes in frequencies of behavior with time (P > 0.06 in all cases), and variability did not change with treatment or time (P > 0.05 in all cases), except in the case of gaping where frequencies on the final day of the experiments were significantly higher across all treatments (P < 0.03). There were significant differences in cortisol concentrations found in the water, with lower cortisol at 120 and 216 h versus 24 or 72 h (Tukey’s tests: P < 0.001; Figure 6B). All HSPs except HSP70 showed differences among treatments (one-way ANOVA: HSP27, P < 0.04; HSP40, P < 0.001; HSP60, P < 0.01; HSP70, P > 0.5; Figure 6C). Tukey’s tests generally showed that HSPs at 216 h were higher than at 24 or 72 h. No differences in variability were seen across treatments (P > 0.3 in all cases; HSP27 required analysis with Kruskal–Wallis ANOVA on ranks).

FIGURE 5. Effects of three different tank lighting systems (6,500-K bulbs, 420 actinic bulbs, and 4,100-K bulbs) for Zebrafish on (A) behavior, (B) cortisol measured in aquarium water, and (C) HSPs measured in muscle tissue. All tanks received equal quantum irradiance. Other details are as in Figure 3.

Tapping Frequency of behaviors did not differ among treatments (two-way RM ANOVA: fin display, P > 0.6; flutter, P > 0.07;

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FIGURE 6. Effects of food deprivation on Zebrafish for 24, 72, and 216 h on (A) behavior, (B) cortisol measured in aquarium water, and (C) HSPs measured in muscle tissue. Other details are as in Figure 3.

aggression, P > 0.4; gape, P > 0.1; chatter, P > 0.3; Figure 7A). In general, fin display was more frequent than the other behaviors, while gaping appeared to be the least displayed. However, there were some differences in behaviors over time. Frequencies of fin display were higher in the last 4 d compared with the first 3 d (P < 0.05), and both chattering and fluttering frequencies were greater on the fourth day of the experiment compared with other days (P < 0.05). No changes in variability of behaviors were observed related to treatment or time (P > 0.1 in all cases). Cortisol averaged 0.54 ng/L over all tanks and no differences were apparent among treatments or over time (two-way ANOVA: P > 0.13, P > 0.06; Figure 7B). No changes in variability were found with respect to treatment or time (P > 0.7 in all cases). Only HSP40 showed differences among treatments (one-way ANOVA: HSP27, P > 0.16; HSP40, P < 0.05; HSP60, P > 0.9;

FIGURE 7. Effects of random tapping of aquaria of Zebrafish on (A) behavior, (B) cortisol measured in aquarium water, and (C) HSPs measured in muscle tissue. Aquaria were tapped using a custom-built programmable device (see Methods). Tanks tapped at a “low rate” received a total of 10 min in every 24 h of random taps, delivered in 10-s bursts at a rate of 1 tap/s. Tanks tapped at a “high rate” received a total of 20 min in every 24 h of random taps, delivered in 10-s bursts at a rate of 2 taps/s. The final series of tanks did not receive tapping. Other details are as in Figure 3.

HSP70, P > 0.12; Figure 7C). Levels of HSP40 were higher in fish from tanks exposed to high tapping rates versus low or no tapping (Tukey’s test). No differences in variability among treatments were found for any HSP (P > 0.05 in all cases).

DISCUSSION Effects of Specific Stressors Remarkably few significant differences were found between treatments and controls for any of the aquarium-related stressors investigated; only food deprivation showed consistent results.

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The hypothesis that increasing stocking densities in Zebrafish would result in alterations in behavior, increased cortisol release, and elevated tissue HSPs was rejected, suggesting that the stocking densities used were not stressful to Zebrafish. These results contrast with some in the literature. For example, Moretz et al. (2007) found Zebrafish showed increases in aggression behaviors at a density of 1.4 fish/L (though more fish were used in their study; 30 fish in 21-L tanks), and Spence and Smith (2005) found male Zebrafish displayed increased territorial behaviors at a density of 0.25 fish/L (just twice our lowest density of 0.13 fish/L). Larson et al. (2006) demonstrated development of dominant–subordinate behaviors in Zebrafish at densities of only 0.025 fish/L (though the frequencies of such behaviors in their study were an order of magnitude greater than in the present study; “bites” and “chases,” contained in our aggression category, were observed at an equivalent frequency of between 27 and 90 events per 5-min observation; we averaged only eight at the highest stocking densities). For other indicators, much higher densities may be required for effects to be seen. For example, Castranova et al. (2011) saw no effects on Zebrafish reproduction or viability until densities of 12 fish/L were reached, and Goolish et al. (1998) did not observe changes in egg production, percentage hatch, or larval length until densities reached 60 fish/L. Ramsay et al. (2006) found that whole-body cortisol responses (four-fold increases) were observed at 40 fish/L. Few data are available for HSP responses to stocking density in Zebrafish, but results for other species are variable. Zarate and Bradley (2003) found HSP70 was not an indicator of crowding stress in Atlantic Salmon Salmo salar, but Gornati et al. (2005) did see increased HSP in Sea Bass Dicentrarchus labrax (also known as European Bass Morone labrax) at high stocking densities. Aksakal et al. (2011) saw increases in muscle HSP70 in Rainbow Trout Oncorhynchus mykiss in response to increased fish densities, but this only occurred at densities two orders of magnitude higher than the densities used in the present study. It is worth noting that for laboratory work, stocking densities of Zebrafish are typically much greater (2–20 fish/L; Goolish et al. 1998; Ramsay et al. 2009; Parker et al. 2012) than normally used in commercial or home aquaria. Fish welfare concerns at high density typically focus on water quality, but lower densities may also constitute social stressors (Larson et al. 2006; Parker et al. 2012). We hypothesized that there would be no differences in responses between fish in aquaria lighted with typical “cool white” spectrum fluorescent indoor bulbs (color temperature, 4,100 K) and enhanced daylight-spectrum lamps (color temperature, 6,500 K), but that UV-enhanced bulbs (color temperature, 7,100 K) would result in changes in behaviors and in elevated cortisol and HSPs. In fact, no evidence was found to support any effect of lighting. De Oliveira Mesquita et al. (2008) reported that stroboscopic light had a deterrent effect on Zebrafish behavior, but also noted that fish acclimated to the treatment within an hour. Ultraviolet radiation can elicit stress responses in developing Zebrafish (Behrendt et al. 2010), but such effects occur at

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much higher doses than are feasible using commercially available lighting. For other species, light spectra appear to have inconsistent effects that include red light spectra decreasing oxidative stress relative to white light (in Yellowtail Clownfish Amphiprion clarkii, Shin et al. 2011), red light spectra or darkness decreasing plasma cortisol relative to white light in Tench Tinca tinca (Owen et al. 2010), blue light spectra increasing growth and size heterogeneity and lowering cortisol (in Rainbow Trout and Common Carp Cyprinus carpio, Karakatsouli et al. 2008, 2010), blue light spectra increasing plasma cortisol (in Atlantic Salmon postsmolts, Migaud et al. 2007), or no effects of spectra on cortisol (in Red Porgy Pagrus pagrus, Szisch et al. 2002). Head and Malison (2000) report a synergistic effect of blue light and handling stress on plasma cortisol and growth rate in Yellow Perch Perca flavescens. We hypothesized that depriving Zebrafish of food over a 10-d period would cause changes in behavior and uniformly increase cortisol in water and HSPs in tissues. Elements of the hypothesis were supported, but while tissue HSP40 and HSP60 increased in response to deprivation, cortisol in tank water actually decreased. Reports in the literature of the effects of food deprivation on stress in fishes vary considerably. In terms of behavior, Novak et al. (2005) found fasting Zebrafish had an increase in physical activity after 2 d followed by a sharp drop until fish were fed after 15 d; this was not reflected in frequency of behaviors in the present study, though both “flutter” and “aggression” behaviors, while not significantly different among treatments, were qualitatively more variable than what was seen in other experimental series (Figure 6). Food deprivation can increase cortisol; for example, Olsen et al. (2005) found cortisol increased detectibly in Rainbow Trout after 3 d of food deprivation, which contrasts with results of the present study. A common pattern in fishes in response to stress is for cortisol levels to first increase from prestress levels, then acclimate and return to prestress levels (Wendelaar Bonga 1997; Barton 2002), but the changes in in-water cortisol observed in the present study actually represent a decline in cortisol released relative to other experiments as well. Few data are available for HSP responses in Zebrafishes. Drew et al. (2008) found little evidence of changes in Zebrafish transcriptomes (including HSPs) after 21 d of starvation. In other species, there is little consensus: Cara et al. (2005) found that HSP70 and HSP90 expression increased after 7 d in response to food deprivation in Rainbow Trout and Gilthead Seabream Sparus aurata, but Weber and Bosworth (2005) studied food deprivation in Channel Catfish Ictalurus punctatus and saw no changes in HSPs despite reduced growth. It is clear that some responses may take place over a longer period than what was allowed in the present study. Oxidative responses in Brown Trout Salmo trutta did not become detectible until after 49 d of starvation (Bayir et al. 2011). Importantly, Lee et al. (2011), working with cichlids, pointed out that there is high variability among fishes in their response to feeding and food deprivation due to their relative dominance; nondominant fish are likely to get less than their share of food and thus store less,

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and so incur an additional “cost of stress” (see below). However, such issues may not actually arise in a case of food deprivation; Br¨ann¨as et al. (2003), working with Brown Trout, found that more aggressive behaviors occurred with limited food rather than no food. We hypothesized that fish experiencing tapping on aquarium glass would exhibit changes in behavior and elevated cortisol and HSPs relative to those that did not. This hypothesis was rejected, although significantly higher HSP40 was seen in fish subjected to the highest tapping rate. It seems odd there were no differences detected in behaviors because during observations when a tank tapper began a tapping cycle, the fish displayed a marked startle response, typically a “jump” followed by accelerated swimming for approximately 3–5 s. This response did not decrease noticeably over the course of the experiment. The tapping treatment differed from the other treatments in that it was applied in clear “pulses” versus continuously. We considered the irregular and unpredictable tapping as a “chronic background” condition in aquaria, but this is clearly distinct from stimuli like pump noise (e.g., Anderson et al. 2011). In this sense, tapping might be described as a “repeated acute stressor” (cf., handling stress, Barton 2002) and it might have been more reasonable to monitor fish immediately before and after tapping. However, such an approach would have had two weaknesses. Firstly, fish are capable of cumulative responses to repeated stressors (see discussion in Barton 2002) and so a summative measurement is useful, and secondly, the random nature of the tapping effectively prevented making observations and measurements at fixed points after the tapping occurred. Purser et al. (2011) reported that Threespined Sticklebacks Gasterosteus aculeatus exposed to acoustic noise showed declines in foraging efficiency and alterations in specific behaviors. Anderson et al. (2011) demonstrated elevated cortisol in seahorses in tanks exposed to high levels of noise. Smith et al. (2004) found Goldfish Carassius auratus exposed to noise did not have a long-term physiological stress response, but there was a short-term increase in plasma cortisol, suggesting rapid acclimation. Wysocki et al. (2006) found elevated cortisol in aquarium water of Common Carp, Gudgeon Gobio gobio, and Eurasian Perch Perca fluviatilis exposed to the underwater sound recorded in the presence of a ship, relative to control fish. Other studies have failed to find effects. Leong et al. (2009) exposed Mozambique Tilapia Oreochromis mossambicus to “knocking” on tank walls over 7 d and observed effects on locomotory activity and oxygen consumption, but not on cortisol. Davidson et al. (2009) found little difference in growth and condition between Rainbow Trout exposed to noises typical in an aquaculture setting and control fish after 5 months. Usefulness of Specific Methods and Potential Refinements Behavioral monitoring of Zebrafish was conceptually simple, though labor intensive. A problem noted from the start was that, while total numbers of behaviors of the six fish could be tallied, these behaviors could not be associated with individ-

uals. Thus, potentially important information was being lost. This limitation of this type of observation has been noted for some time (Altmann 1974). Video-tracking systems for behavior are now available (e.g., Fontaine et al. 2008), and processor capability is up to the task of distinguishing multiple targets. Moreover, such tracking can identify more subtle or aggregate behaviors (e.g., “freezing” or “reduced exploration,” see Cachat et al. 2010) that are impossible to quantify using the methods of the present study. In-water cortisol measurements proved relatively straightforward; herein, we report another species, Zebrafish, to which this method has been successfully applied (cf., Scott et al. 2008). Cortisol recoveries are in the range previously reported (Scott and Ellis 2007), and though the average release rates of the present study are higher than the range quoted in Scott et al. (2008), we are using fish that are substantially smaller than those used in most previous work; there is a recognized inverse relationship between release rates and fish size (Scott et al. 2008). Measurement of HSPs was terminal and labor intensive, and results were highly variable among individuals in the present study. It was, however, the only truly individual measurement made. Though widely used, concerns have been expressed about whether HSPs can actually serve as stress indicators in fish, considering their variation with developmental stage, specific tissue, and the lack of information of differences between acute and chronic stressors (see Iwama et al. 2004). As we gain better understanding of the identity and roles of HSPs, some of these issues may become clearer. For example, Marvin et al. (2008) demonstrated that of 13 small HSPs found in Zebrafish, seven were developmentally regulated in a tissue-specific manner, but five appeared to show clear heat-shock responses. Having the ability to target specific genes or protein isoforms may improve interpretation substantially. Evolution of transcriptomic and proteomic microarrays may offer hope for this approach in Zebrafish (e.g., Ton et al. 2002; Bosworth et al. 2005). Complicating Issues In the present study, we chose to work with fish in small groups rather than singly as is done in some cases (e.g., toxicological testing). Small groups represent the situation in most aquaria, and there is good evidence of positive effects of maintenance of fish in groups on welfare in aquaculture settings (e.g., Saxby et al. 2010). However, such an approach introduces additional social aspects to the experiments. We randomized selection of fish for experiments to minimize handling stress and did not attempt to control aspects like sex ratio. It is clear that this is an issue for behavior; sex ratio clearly affects male territoriality and specific behaviors such as aggression and courtship (Darrow and Harris 2004; Spence and Smith 2005; Moretz et al. 2007). The relatively small number of fish used may also have prevented some social behaviors such as shoaling; Zebrafish show a preference for shoaling in larger numbers, which is more likely to occur in groups where

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females predominate (Spence et al. 2008). Zebrafish develop dominance hierarchies (Gerlach and Lysiak 2006; Gerlach et al. 2007), and so stress in the environment is not simply a function of physical and chemical factors, but can also be due to the social environment. Indeed, while there are positive aspects to social groupings (e.g., improvement of growth and stress reduction in the presence of “kin”; Gerlach et al. 2007), it is also clear that subordinate animals experience measureable stress (including elevated plasma cortisol) as a result of aggression experiences because of their lower status (e.g., Filby et al. 2010). Moreover, Parker et al. (2012) demonstrated that housing Zebrafish alone or in groups could modify their behavioral responses to stressors. It is unclear the extent to which social hierarchies established themselves in our experiments, but according to Larson et al. (2006) subordinate Zebrafish are paler in color, and color intensity variations were noted among tanks in the present study. Interestingly, in cichlids, Fox et al. (1997) observed that social and reproductive statuses interact to affect stress responses. Finally, environmental complexity may play a role. In order to maximize observation ability and minimize interfering chemicals, we chose the simplest possible tank architecture; tanks did not contain shelters or plants, for example. Aggressive behaviors in social fishes, including Zebrafish, are reduced in vegetated versus nonvegetative habitats, which are more typical of display aquaria (Basquill and Grant 1998; Fox et al. 1997). The failure to control these aspects in the present study is most likely to result in high variability among individuals; this was indeed observed in the HSP data. In summary, despite concerns about aquarium-related stressors such as crowding, food deprivation, lighting spectra, and tapping on tanks, these appeared to have relatively little detectible effect on Zebrafish. Part of the explanation may have to do with the overriding effects of intrinsic factors like social stressors, but it also appears that Zebrafish are hardy and adaptable to aquarium conditions.

ACKNOWLEDGMENTS We thank Fred Binkowski for advice and assistance in setting up and maintaining aquaria, Tom Consi and Kory Verhein for designing and building the tank tappers, and Mike Carvan, Harvey Bootsma, and Rick Goetz for valuable discussions of experimental design and results.

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