Chemiluminescent assay as an alternative to radioimmunoassay for the measurement of cortisol in plasma and skin mucus of Oncorhynchus mykiss

Ecological Indicators 98 (2019) 634–640

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Original Articles

Chemiluminescent assay as an alternative to radioimmunoassay for the measurement of cortisol in plasma and skin mucus of Oncorhynchus mykiss L. Franco-Martineza, A. Tvarijonaviciutea, S. Martinez-Subielaa, M. Telesb,

⁎,1

, L. Tortc,

T

⁎,1

a

Interdisciplinary Laboratory of Clinical Analysis Interlab-UMU, Regional Campus of International Excellence Mare Nostrum, University of Murcia, Espinardo, Murcia 30100, Spain b CIIMAR-Interdisciplinary Centre of Marine and Environmental Research, Terminal de Cruzeiros do Porto de Leixões, Avenida General Norton de Matos, S/N, 4450-208 Matosinhos, Portugal c Dpt. Cell Biology, Physiology and Immunology, Universitat Autonoma de Barcelona, 08193 Bellaterra, Spain

A R T I C LE I N FO

A B S T R A C T

Keywords: Automated chemiluminescence assay Validation Cortisol Stress Fish

The aims of the present study were to validate an automated chemiluminescence assay (CIA) for cortisol determination in plasma and skin mucus of fish, to compare the results produced with those obtained by radioimmunoassay (RIA), and to evaluate the assay capacity to differentiate between stressed and non-stressed fish. Cortisol hormone was measured using both CIA and RIA in plasma and skin mucus of 36 rainbow trout (Oncorhynchus mykiss) at different time points after 3 min of air exposure. For CIA, analytical validation consisting of intra- and inter-assay coefficient of variation (CV), limit of detection, and linearity studies were performed. In addition, correlation and agreement between the CIA and RIA were evaluated. In all cases, intra- and inter-assay CV for CIA measurements were lower than 10 and 11%, respectively. Cortisol results with CIA were statistically significantly higher than those obtained with RIA in both tissues (p < 0.001). Strong positive correlation was observed between the two methods (r = 0.999, p < 0.001 and r = 0.993, p = 0.03 for plasma and skin mucus, respectively). The agreement between the two techniques was examined by Bland-Altman plots, which identified wide confidence intervals and outliers for cortisol (plasma n = 3, skin mucus n = 2) results. Both assays were able to differentiate between pre- and post-stressed fish in both biological matrices. In conclusion, CIA assay is precise and accurate for measuring cortisol in plasma and skin mucus of fish and is able to discriminate among stressed and control animals, showing a strong correlation with RIA, making it a reliable method for stress assessment in fish.

1. Introduction Cortisol is the most commonly employed corticosteroid to assess quantitative stress in fish exposed to, among others, pollutants, transport, acute crowding, or hypoxia (Ellis et al., 2004; Mormède et al., 2007). Cortisol has receptors in all tissues and is able to regulate metabolism, immune functions and hydromineral homeostasis (Hontela, 1997), including gluconeogenic activation and mobilization of substrates as fuel energy (Teles et al., 2005). Elevation of cortisol as response to acute stressors such as handling, transport, confinement, and xenobiotics has been described in most fish species (Teles et al., 2013; Hontela et al., 1996; Hautanen et al., 1994; Schreck and Tort, 2016). In comparison to other candidate biomarkers of stress (e.g. adrenaline or adrenocorticotropic hormone), cortisol offers several advantages such

as (1) marked response to acute stress, allowing to discriminate among stressed and non-stressed status (Mommsen et al., 1999); (2) response proportional to the intensity of the stressor (Gesto et al., 2015); (3) relatively fast response to stressors, which allows to evaluate the impact of recent stressful events avoiding interferences due to sampling-related procedures (Mommsen et al., 1999; Ellis et al., 2012; Marino et al., 2001). In fish, blood plasma sampling is mostly used for systemic cortisol determinations because of it is a non-lethal procedure (Herrera et al., 2017). However, this is an invasive technique, being painful and stressful itself (Guardiola et al., 2016), and the use of non-invasive matrices for stress determination is helpful both for reducing physiological disturbance and to preserve animal welfare (Bertotto et al., 2010; Kittilsen et al., 2009). For this reason, in the last years non-

⁎

Corresponding authors. E-mail address: [email protected] (M. Teles). 1 Equal contribution. https://doi.org/10.1016/j.ecolind.2018.11.046 Received 28 August 2018; Received in revised form 8 November 2018; Accepted 15 November 2018 1470-160X/ © 2018 Published by Elsevier Ltd.

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invasive methods to evaluate stress in fish as in other animal species and humans are gaining attention. For instance, analysis of fish faeces (Lupica and Turner, 2009) or visual inspection of the skin (Kittilsen et al., 2009) have been described to be useful non-invasive methodologies for stress evaluation. Skin mucus was also described as useful noninvasive sample in fish, since it contains many biologically active molecules (Huang et al., 2011; Fast et al., 2002). Skin mucus sampling has several advantages when compared with other biological matrices since the technique is simple, fast, relatively inexpensive, can be used postmortem, and can be applied in both relatively large and small fish (Guardiola et al., 2016; Bertotto et al., 2010). In addition, as fish are in permanent contact with water (i.e. a surrounding environment rich in microorganisms), the interactions water-skin are much higher than in terrestrial animals and therefore skin mucus becomes a key surface to assess these interactions. For instance, mucus from skin and other mucosal surfaces of fish contain numerous substances poorly studied that act as the first line defense against a broad spectrum of chemical, physical and biological stressors (Guardiola et al., 2014). In a number of fish species, cortisol levels measured in skin mucus have been considered as good stress indicators and a promising alternative to invasive sampling, with high correlation rates with other stress biomarkers in blood (Bertotto et al., 2010; Sánchez-Nuño et al., 2018). Cortisol is mostly measured in fish by radioimmunoassay (RIA) or enzyme-linked immunosorbent assay (ELISA) (Gesto et al., 2015; Sink et al., 2008). RIA uses 125I or 3H-labeled hormones, being highly sensitive methods for the measurement of cortisol in human and animal samples (Singh et al., 1997). The use of these radioactive isotopes, however, presents a series of requisites such as appropriate installations, licences, storage facilities, safety devices, waste management, and record keeping, increasing the operating costs (Singh et al., 1997). Therefore, many fish research institutions lack of resources to perform or maintain RIA facilities due to these limitations (Sink et al., 2008). In contrast, the use of nonradioactive methods supports the so-called “green chemistry”, being more environmental friendly (Anastas and Eghbali, 2010; Kerton and Marriott, 2013). Chemiluminescent immunoassays (CIA) methods, instead of RIA, presents several advantages such as non-exposure to radioisotopes, easier integration into laboratory functions, rapid turnaround and economic savings, and they have been reported to be at least comparable to RIA methods in other samples (Risch et al., 2006; Babson et al., 1991). Therefore, the use of chemiluminescent immunoassays methods for the measurement of cortisol in the context of pollution in aquaculture, ecosystems, or fishing discards, among other situations, could be beneficial from an ecological point of view. CIA are widely used for the measurement of cortisol levels in humans and animals since it is considered to be specific and interference-free (Russell et al., 2007). Furthermore, CIA automatic analysers could contribute with some additional advantages when compared with other techniques such as ELISA or RIA. They provide a higher speed of process and low sample manipulation, resulting in fewer errors due to pipetting and human manipulation (Franco-Martínez et al., 2016). Automatic chemiluminescent methods also decrease costs since they are rapid and easy to prepare samples and allow measuring individual samples and biomarkers. Those advantages could be of special importance when a high number of samples has to be measured, as occurs in national and international biomonitoring programs. However, to the best of the authors’ knowledge, no validation studies of CIA based methods for cortisol determination have been reported so far in plasma and skin mucus samples of fish. Since cortisol is highly homologous among vertebrates (Sink et al., 2008), we hypothesise that CIA assay could be used for cortisol determination in fish, which could provide with important savings of time, resources and economic advantages in biomonitoring programs. The aims of the study were (1) to validate automated CIA (Immulite, Siemens) for the determination of cortisol in plasma and skin mucus in fish, and (2) to compare the results generated by CIA with those obtained by a previously validated RIA as reference method. For this, fish

were submitted to air exposure for three minutes in order to induce stress. 2. Material and methods 2.1. Animals and experimental set-up Eighteen sexually immature rainbow trout (Oncorhynchus mykiss) (185 ± 5 g mean weight) were obtained from a local fish farm, Trout Farm (Oliana, Spain). The fish were initially kept at 14 °C recirculating freshwater, under a 12 h light per 12 h dark photoperiod for 2 weeks. The fish density in the aquaria was 8.4 kg/m3 and the dissolved oxygen above 90%. During acclimation, fish were daily fed with a commercial diet (Trouw T6 Classics 3P, Trouw España, Spain). The amount of oxygen dissolved in water was less than 9 mg/L with a pH range of 6.0–8.5. Nitrate and nitrite contents were less than1.0 mg/L and 0.05 mg/L, respectively. The level of ammonia was less than 0.07 mg/L. All experimental procedures involving fish were carried out according to the 3 R's principles of Animal Experimentation following Spanish legislation (law 32/2007 and RD53/2013) that agrees with the International Guiding Principles for Biomedical Research Involving Animals (EU 2010/63). All animal handling was performed with accredited researchers. After the acclimation period, one group of nine fish were maintained under controlled conditions (non-stressed fish), and the remaining nine fish were quickly captured with a net and maintained in an air-exposed net for 3 min and then released back into the holding tanks (250 L tanks). The fish were maintained in resting conditions in their respective holding tanks and sampled 1, 6, and 24 h post stress. Each experimental condition consisted of two replicate tanks. At the end of the post-stress period, 9 fish per sampling time were sacrificed by anesthetic overdose with MS222 and skin mucus and blood was sampled. 2.2. Blood and skin mucus collection and sample preparation Skin mucus was collected following the methods described by Guardiola et al. (2014). Briefly, skin mucus was collected by carefully rasping the dorsolateral surface of the fish, using cell scrapers with enough care to avoid any skin damage and contamination with blood or excretions. Skin mucus samples were homogenized with 1 vol of Trisbuffered saline (TBS, 50 mM Tris-HCl, pH 8.0, 150 mM NaCl), vigorously shaken and centrifuged (3000 rpm, 10 min, 4 °C). For statistical analysis, skin mucus data were not corrected by dilution factor or protein content because the same sample was analysed with both RIA and CIA methods and the data correction would not be necessary in terms of method comparison. Blood was collected from the caudal vein with heparinized syringes and used for plasma isolation (1500 rpm, 10 min, 4 °C). Skin mucus and plasma samples were immediately stored at −80 °C until analysis. 2.3. Cortisol measurement 2.3.1. Chemiluminescence-based method Solid-phase, competitive chemiluminescence enzyme immunoassay for cortisol determination (COR Cortisol, REF LKC01, Siemens Health Diagnostics, Deerfield, IL) was used. The method employs test units coated with polyclonal rabbit anti-cortisol antibodies and reagent (alkaline phosphatase (bovine calf intestine) conjugated to cortisol in buffer, with preservative). The reaction was performed, incubated and read automatically in the analyzer (Immulite® 1000 analyser; Immulite System; Siemens Health Diagnostics, Deerfield, USA). Routine maintenance, instrument preparation, setup, adjustment, assay and quality control procedures were performed as defined in the Operator’s Manual. Plasma and skin mucus samples (110 µL) were placed in the test cup and the first results were available after 30 min. The validated human 635

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assays were employed for measuring cortisol. According to manufacturer instruction, the limit of detection of the assay is 0.2 µg/dL.

Table 1 Intra- and inter-assay precision using plasma and skin mucus samples with high and low concentrations of cortisol measured with chemiluminescence.

2.3.2. Radioimmunoassay Cortisol was measured in the plasma and skin mucus by radioimmunoassay (Rotllant et al., 2001). The antibody for the assay was purchased from M.P. Biomedicals LLC (OH, USA) and used in a final dilution of 1:4500. Anti-cortisol antibody was used for the assay at a final dilution of 1:4500. Antibody cross-reactivity with cortisol is 100% and the lower detection limit of the assay was 0.016 µg/dL. Cross-reactivity with other steroid hormones varied from 1.6% for corticosterone and was inferior to 0.7% for 17α-hydroxyprogesterone, desoxycorticosterone, 17α-hydroxypregnenolone, dexamethasone, cortisone, progesterone, aldosterone, cholesterol, estradiol and testosterone. Precision was analyzed by determining the intra-assay coefficient of variation (CV) and was found to be 4.5% and the inter-assay CV 5.3%. The radioactivity was quantified using a liquid scintillation counter (Scintillation Counter Wallac 1409, PerkinElmer).

Sample

Plasma high Plasma Low Skin mucus high Skin mucus low

Intra-assay

Inter-assay

Mean (µg/ dL)

SD (µg/ dL)

CV (%)

Mean (µg/ dL)

SD (µg/ dL)

CV (%)

26.35 1.00 1.10

0.61 0.07 0.04

2.32 7.13 3.86

26.42 1.08 1.12

0.45 0.09 0.08

1.71 7.91 6.74

0.08

0.01

9.69

0.1

0.01

10.23

A receiver operation characteristic (ROC) analysis was performed to evaluate the diagnostic value of CIA measurements of cortisol in fish after air exposure. For this, the data of controls and fish 1- and 6-hours after air exposure were plotted against SS data. For the experimental set-up, results were evaluated for approximate normality of distribution using the D'Agostino & Pearson omnibus normality test. To determine which values differ significantly between controls and air-exposed groups, Kruskal-Wallis ANOVA test was performed since data were not normally distributed. Statistical analyses were performed with the statistical package GraphPad 6 and p values equal or less than 0.05 were considered as statistically significant.

2.4. Analytical validation The analytical validation of the chemiluminescent assay was assessed through precision, accuracy, and limit of detection calculations, according to protocols described previously (CVM, 2001). For analytical validation, plasma and skin mucus samples with high and low cortisol values were employed. Intra- and inter-assay coefficients of variation (CV) were assessed in order to determine the assay precision. For this, cortisol was measured in one sample with high and low cortisol concentration 4 times in the same run (intra-assay) or in four separated runs, carried out on different days (inter-assay). Accuracy was evaluated indirectly by performing linearity under dilution (Al, 2006). For this, plasma and skin mucus samples with high cortisol concentration were serially diluted using ultrapure water (Millipore) as diluent (neat, ½, ¼ and 1/8) and analysed. Limit of detection was calculated on the basis of data from 10 replicate determinations of the zero standards (ultrapure water, Millipore) (Tvarijonaviciute et al., 2010). All samples used for repetitive analysis were frozen in aliquots, and only the vials needed for each run were used, to avoid possible changes due to repetitive thawing and freezing.

3. Results 3.1. Analytical validation of CIA method The mean intra- and inter-assay CV values for plasma and skin mucus samples were below 11%, as shown in Table 1. Linearity under dilution of the plasma and skin mucus samples resulted in a linear regression equation with R2 close to 1 in both cases (Fig. 1). Limit of detection of the assay was 0.05 µg/dL. 3.2. Method comparison between RIA and CIA Cortisol concentration measured in plasma and skin mucus with CIA and RIA are showed in Table 2. Mean cortisol concentration was 2.38 and 2.52-fold higher in CIA than in RIA for plasma and skin mucus, respectively. Correlation coefficients between both methods were r = 0.93 (p < 0.001) for plasma, and r = 0.95 (p < 0.001) for skin mucus. A Bland-Altman plot revealed a proportional error between the two evaluated methods, showing that the differences between both methods increase proportionally to mean cortisol value (Fig. 2). The 95% CI for the bias were wide and five results (three for plasma and two for skin mucus) were characterised as outliers. Positive correlation coefficients between plasma and skin mucus were observed with both methods (r = 0.584, p < 0.001 for CIA; r = 0.606, p < 0.001 for RIA).

2.5. Statistical analysis Results are expressed as median (25–75th percentile). For chemiluminescence assay, when a result was lower than the measurable limit and reported as “less than,” the value that was used for statistical analysis was the lower limit of measurement. Intra- and inter-assay run precisions were expressed as CV (%) following calculation of the mean and standard deviation (SD) for each set of results. Linearity was evaluated by plotting measured against expected cortisol concentrations, and determining the slope and intercept using simple linear regression. Limit of detection was calculated as the mean of the value of the zero standards plus 3 standard deviations. To determine the correlation between the two methods in both biological matrices (plasma and skin mucus), the data distribution was evaluated using D'Agostino & Pearson omnibus normality test. As data did not follow a Gaussian distribution, Spearman’s correlation test was performed. The correlation was considered excellent if r ≥ 0.93; good if r was = 0.80 to 0.92; fair if r = 0.59 to 0.79; or poor if r was below 0.59 (Dewhurst et al., 2003). Bland–Altman difference plot analysis was performed to determine the degree of agreement between the two analysers and to reveal any bias. Bias was computed as the mean difference between scores for the 2 methods. Values for 95% limits of agreement (LOA) were computed as the mean difference ± 1.96 standard deviations of the difference.

3.3. Experimental set-up Cortisol concentrations in plasma and skin mucus from all groups with both methods are represented in Table 3. In plasma samples, a 4.8- and 10.4-fold higher cortisol concentrations at T1 in comparison with T0 were observed with RIA and CIA, respectively, (p < 0.01 in both cases). At T6, cortisol levels were higher than at T0 with both methods (3.1- and 6.8-fold higher with RIA and CIA, respectively), although it was statistical significant only with CIA. No statistically significant differences were found between T0 and T24 in plasma with none of the two methods. When skin mucus cortisol concentrations were evaluated, 6.7- and 6.2-fold higher cortisol concentrations at T1 in comparison to T0 were 636

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a

Plasma

b

Skin mucus

1.5

Measured cortisol

Measured cortisol

30

20 2

R = 10

0.9993

Y = 1.041*X - 0.9932

0

1.0 2

R = 0.5

0.9933

Y = 0.9633*X + 0.05240

0.0

0

10

20

30

0.0

Expected cortisol ( g/dL)

0.5

1.0

1.5

Expected cortisol ( g/dL)

Fig. 1. Representative graphs of linearity under dilution study with plasma (a) and skin mucus (b) samples using chemiluminescence method.

content was not necessary in order to detect stress in fish. These results were in accordance with a previously reported study (Guardiola et al., 2016). And although future studies are needed to confirm these observations, the avoidable protein determination could be considered as an advantage since it allows saving time, sample, and resources. The use of human assays to analyse other animal samples could involve economic savings and more availability; however, the assays should be adequately validated prior to their use (Muñoz Prieto et al., 2017). Validation studies performed in plasma and skin mucus of rainbow trout showed that the analytical method can detect the corresponding analyte and provide repeatedly accurate results in these samples (Tecles et al., 2007). In the present study, intra- and inter-assays showed adequate precision with CVs lower than 15% in all cases, according to previous guidelines (CVM, 2001). The accuracy of the cortisol assay with CIA in plasma and skin mucus was indirectly evaluated by linearity under dilution. The linearity under dilution test and regression analysis revealed a high accuracy of the assay, with r > 0.99 for both biological matrices. Limits of detection were much lower than the range of values found in all plasma samples. However, skin mucus cortisol concentrations collected from nine out of 18 fish at T0 and T24 were below the limit of detection. Nonetheless, CIA allowed discriminating stress levels in fish, at least under the circumstances of this experimental set-up. Overall, the results of the present study confirm that the CIA assay was repeatable and accurate for the measurement of cortisol concentrations in plasma and skin mucus of rainbow trout. Excellent correlation between the two evaluated methods was observed in both plasma and skin mucus. The slope value generated by regression analysis showed that CIA results were higher than those obtained by RIA in all skin mucus samples, and in 28 out of 36 plasma samples analysed. This observation was confirmed by examination of the Bland-Altman data for cortisol, which although revealed a significant mean bias between the two methods, a wide 95% CI and the presence of proportional error were detected. This data would suggest that the degree of disagreement between the two techniques would not affect the capacity of each method to discriminate stressed and stressfree fish. Therefore, the values generated by the two techniques should

observed when using RIA and CIA, respectively (p < 0.01 in both cases). Cortisol concentrations at T6 were statistically higher than those observed at T0 (5.0- fold for RIA and 7.0-fold for CIA measurements, p < 0.05). Cortisol concentrations between T0 and T24 did not show any difference of statistical relevance. The ROC curve analysis performed to evaluate cortisol measurements by CIA value in fish plasma and skin mucus after air exposure is shown in Fig. 3. In plasma, the area under the curve was of 0.9198 (95% confidence interval, 0.818 to 1.022; standard error, 0.052; p < 0.001). At the cut-off value of > 7.515 µg/dL, the sensitivity and specificity for this marker were 83.33% and 100%, respectively. In skin mucus, the area under the curve was of 0.9317 (95% confidence interval, 0.830 to 1.033; standard error, 0.052; p < 0.001). At the cut-off value of > 0.114 µg/dL, the sensitivity and specificity for this marker were 88.24% and 100%, respectively. 4. Discussion Fish welfare is influenced by management practices which could lead to substantial increases in stress (Guardiola et al., 2016), being cortisol a widely recognized biomarker for stress assessment in these animals (Adams, 1990). However, one of the most routinely used methods for cortisol determination in fish is based on RIA, implying several disadvantages as stated in the introduction section. In this sense, the use of a chemiluminescence method for the measurement of cortisol in fish could represent a substantial progress from the technologic, ecologic, and economic viewpoint (Tvarijonaviciute et al., 2010). This study is the first report in which cortisol is measured by both RIA and CIA using the same plasma and skin mucus samples of rainbow trout. Additionally for CIA, analytical validation was performed in both biological matrices and the clinical utility was analysed by comparing cortisol levels at different time points after 3 min of air exposure. It is important to point out that in the present study cortisol levels in skin mucus were not corrected by total protein content as it was suggested for other analytes such as lysozyme and peroxidase activities in fish (Guardiola et al., 2014). Cortisol values observed at different time points of the present study suggest that data correction by proteins

Table 2 Comparison of results obtained using RIA and CIA methods for plasma and skin mucus cortisol determination in 36 fishes with different stress levels. Sample

Method

Mean

SD

95% CI

Median

Minimum

Maximum

25%

75%

Plasma

RIA CIA

4.34 10.31

4.40 11.69

2.85–5.82 6.35–14.26

3.00 3.29

0.11 0.06

21.27 35.50

0.78 0.69

7.45 20.58

Skin mucus

RIA CIA

0.10 0.26

0.10 0.38

0.07–0.14 0.13–0.39

0.05 0.01

0.02 0.05

0.36 1.84

0.03 0.05

0.15 0.31

637

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a

b

Scatter Plot for plasma

Scatter Plot for skin mucus

2.0

r=

Y = 2.077*X + 1.302

30 20

Y = 1.497*X + 0.08845

1.5

0.7811 CIA (μg/dL)

CIA (μg/dL)

40

0.6556

r=

50

1.0

0.5 10

0.0

0 0

5

10

15

20

0 .0

25

0 .2

0 .4

RIA (μg/dL)

0 .8

1 .0

d Difference vs. average: Bland-Altman of Skin mucus

c Difference vs. average: Bland-Altman of Plasma

2.0

30 95%

1.5 Difference

20

Difference

0 .6

RIA (μg/dL)

10 0

1.0 95%

0.5 0.0

-10

95% 95%

-20

0.0 0

5

10

15

20

0.5

1.0

1.5

25

Average

Average

Fig. 2. Scatter plot with linear trend line and Bland-Altman Plot (difference vs average) of RIA and CIA cortisol measurements in 36 plasma and skin mucus samples. (a) Scatter plot for plasma, (b) scatter plot for skin mucus, (c) Bland-Altman Plot for plasma, (d) Bland-Altman Plot for skin mucus.

reported using RIA in fish (Bertotto et al., 2010). This correlation can be explained because the lipophilic nature of cortisol, allowing its diffusion through cell membranes into several tissues (Bertotto et al., 2010). Since cortisol diffusion is expected to be different between biological matrices, those in which hormones diffuse slowly could be of help to avoid potential false basal hormone levels due to sampling stress (Bertotto et al., 2010). These results reinforce the usefulness of the use of skin mucus in stress assessment in fish. In the air-exposed experimental set-up, rainbow trout showed increased cortisol concentrations in T1 and T6 when compared to T0 in both tissues when samples were analysed by CIA; however, plasma cortisol concentrations obtained by RIA at T6 did not significantly differ than those measured at T0. This finding, although could be attributed to the low sample size, could suggest that CIA is more effective in detecting air-exposure-related stress after 6 h in plasma than RIA. And, although in 9 out of 18 stress-free fish the cortisol levels in skin mucus were below the limit of detection, CIA method could be of high utility for stress screening in fish, being rapid and economic.

be interpreted by comparing them to values obtained in control group. The differences observed between the two methods could be attributed mainly to two facts: (1) The potential cross-reactivity of CIA assay in fish samples with other steroids such as prednisolone, corticosterone, and prednisone, among others. (2) The possible interaction of other substances different than steroids in fish plasma or skin mucus with cortisol determinations by CIA. These factors have not yet been established and should be evaluated in further studies. However, even if there is cross-reactivity with other steroids and compounds, CIA measurements have probed its value in detecting stress (Aerts, n.d.). Examination of the data revealed that in 66 samples (91.6%) cortisol values obtained with CIA were higher than those obtained with RIA. In CIA, 10 (27.8%) skin mucus samples were below the reference interval; however, nine out of them corresponded to T0 and T24 in which cortisol is expected to be in low concentrations due to the short and long time between stress and sampling, respectively. The correlation of cortisol levels in plasma and skin mucus was quite evident and significant with both methods, being similar to those

Table 3 Median (25th–75th percentile) cortisol concentrations in plasma and skin mucus of rainbow trout immediately after air exposure for 3 min (T0) and after 1, 6 and 24 h (T1, T6 and T24, respectively). Statistical significant differences with its respective controls are indicated with *(p < 0.05), **(p < 0.01), and ***(p < 0.001). Sample

Method

T0

T1

T6

T24

Plasma

RIA (µg/dL)

1.71 (0.26–3.08) 2.09 (0.15–3.94)

8.18 (7.39–9.40)*** 21.70 (16.10–31.60)**

5.27 (2.37–7.01) 14.10 (2.44–35.5)*

0.75 (0.16–1.34) 0.64 (0.12–1.80)

0.03 (0.02–0.04) 0.05 (0.05–0.09)

0.17 (0.12–0.23)*** 0.31 (0.19–0.49)**

0.13 (0.05–0.34)** 0.35 (0.10–0.8)*

0.03 (0.02–0.05) 0.06 (0.05–0.93)

CIA (µg/dL) Skin mucus

RIA (µg/dL) CIA (µg/dL)

638

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a

b

ROC curve: ROC of Plasma 150

Sensitivity%

150

Sensitivity%

ROC curve: ROC of skin mucus

100

50

100

50

0

0 0

50

100

0

150

50

100

150

100% - Specificity%

100% - Specificity%

Fig. 3. Receiver operator characteristic (ROC) curves of CIA cortisol measurements in plasma (A) and skin mucus (B) of rainbow trout for discriminating controls (T0, n = 9) and fish after 3 min air exposure (T1 and T6, n = 18).

In agreement with our findings, increased cortisol levels few hours after stress were also reported by other authors in blood and skin mucus in fish exposed to acute crowding, anaesthetic agents, air-exposure, hypoxia and transport stress (Guardiola et al., 2016; Bertotto et al., 2010; van Raaij et al., 1996), and in plasma of fish 30 min after the same experimental set-up used in the present study (Arends et al., 1999). This increase is the response of the activation of the hypothalamus–pituitary–interrenal (HPI) axis and the resulting secretion of cortisol into blood as a primary response to stress in fish (Holloway and Leatherland, 1997). However, in another study cortisol concentrations in plasma and skin mucus did not increase after air exposure (Guardiola et al., 2016). This could be attributed to the early sampling after stress (0, 1 and 3 min), which could have been insufficient time for cortisol release, as the release of cortisol to blood needs some time in order to activate each step of the HPI axis elements. In our study, one day after applying the stressor, cortisol levels showed no differences of statistical relevance when compared to pre-stress concentrations. In a recent study (Skrzynska et al., 2018), significant increases in plasma cortisol levels were observed in Sparus aurata 15 and 30 min after air exposure for 3 min, decreasing gradually over time and describing similar values than pre-stress conditions after 8 h. Our findings are also in concordance with other studies in which cortisol decreases after 24 h and 48 h of crowding acute stress, suggesting the adaptation of the stressful situation as the most probable explanation, together with the feedback action of cortisol in the up-stream axis at hypothalamic and pituitary level (Guardiola et al., 2016). For the ROC analysis, we included T0 as controls and only T1 and T6 as test groups, since no statistical differences were observed between T0 and T24 in any case. The ROC analysis showed that the values of CIA-measured cortisol above 7.515 and 0.9317 µg/dL (for plasma and skin mucus, respectively) were indicative of the effect of air exposureinduced stress in fish. In the present study, the magnitude of the response may be considered moderate, taking into account that acute stressors may induce 20 fold increases in cortisol levels (Teles et al., 2016), and we observed a limited 4–10 fold increase between different time points. Thus, it is well known that the severity of the response is dependent on the intensity of the stressor and time lapse (Schreck and Tort, 2016). Besides, since handling and sampling protocols were consistent among all animals, the increased cortisol concentrations observed are expected to be a consequence of the stress caused by the air-exposure experimental setup. Some limitations were observed in the present study. (1) There were potential preanalytic limitations such as the presence of haemolysis in plasma samples, although haemolysis did not affect cortisol levels in

other species using this method (Reimers et al., 1991). (2) Even if cortisol is stable at −80 °C (Garde and Hansen, 2005) and aliquots were made in order to avoid frozen and thawing cycles, analysis with RIA and CIA were performed on different days. Although no changes would be expected in terms of analytics due to the thermal stability and specificity of the molecule of cortisol, further studies may be desirable to establish the potential effects of that preanalytical factor and others such as cross-reactivity of other steroids and compounds when utilising CIA for the measurement of cortisol in fish samples. (3) Although it was not the aim of this study, ideally, a further reference method such as mass spectrometry analysis for cortisol determination could have been employed in order to determine the correct concentration of hormone.

5. Conclusions This study provides the first step toward determining the utility of CIA for cortisol measurement in rainbow trout samples. Cortisol measurement in plasma and skin mucus from fish with CIA is easier to use, more economical, faster, and safer than the use of radioimmunoassays, which are considered as key points in biomonitoring, research and welfare programs. The precision, accuracy and correlation studies indicate that CIA is accurate for measuring cortisol in these samples. However, the agreement studies between the CIA and RIA indicate that the values generated by the two techniques cannot be used fully interchangeable.

Acknowledgments This research was partially funded by the projects AGL2016-76069C2-2-R and AGL2016-81808-REDT of AEI-MINECO (Spain) with the support of Regional Development Funds (European Union). LFM was granted with predoctoral contract “FPU” of the University of Murcia, Spain. MT has a post-doctoral fellowship from FCT (SFRH/BPD/ 109219/2015) supported by the European Social Fund and national funds from the “Ministério da Educação e Ciência (POPH – QREN – Tipologia 4.1)” of Portugal. AT has a post-doctoral fellowshisp “Juan de la Cierva Incorporación” supported by the “Ministerio de Economía y Competitividad” (IJCI-2015-26301), Spain.

Disclosure statement The authors report no other conflicts of interest. The authors alone are responsible for the content and writing of the paper. 639

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