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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

In this paper, standardized ecotoxicological methods for the evaluation of biomarkers in neotropical anuran species are presented. Specifically, this paper details several methodologies at different scales of ecotoxicological evaluation, such as the genetic, cellular-histological, biochemical, morphological, and individual levels.

Abstract

The new questions in ecotoxicology highlight the importance of applying a battery of biomarkers, as this results in ecotoxicological predictions that improve not only the interpretation of the effects of environmental stressors on organisms but also the determination of their possible impact. It is well known that the use of ecotoxicological biomarkers at different levels of organization allows for the prediction of the biological responses of organisms to environmental stressors, which is useful in environmental risk assessment.

Nevertheless, it is necessary to consider the optimization of basic procedures, to generate historical data in control groups, and to employ specific bioassays to evaluate responses in organs and tissues in order to elucidate the nature and variation of the effects observed. Therefore, the present work aims to describe several ecotoxicological methodologies employed in all stages of neotropical anurans at different ecological levels and to validate them as useful biomarkers to be used both in wildlife and in laboratory conditions. In this work, these biomarkers were applied at the individual/organismic level (body condition index), histological/physiological level (histopathology, histometric, and pigmentary analyses), biochemical level (oxidative stress enzymes), and genetic level (direct and oxidative damage in DNA by comet assay).

Although these methodologies have small variations or modifications depending on the species, these techniques provide effective biomarkers for evaluating the effect of xenobiotics on anurans, which possess certain characteristics that make them useful indicator species of aquatic and terrestrial ecosystems. In conclusion, the battery of biomarkers employed in the present study has proven to be adequate for estimating toxic responses in Neotropical anurans and can be further recommended as bioindicators for identifying the impact of pollutants on the aquatic ecosystems of the region. Finally, it is recommended to achieve the standardization of these important biomarkers for anurans in specific regions as well as to possibly include them in risk assessments and decision-making.

Introduction

The input of environmental stressors into natural water bodies can affect the health of the aquatic ecosystem1. Exposure to these environmental stressors can affect the survival or fitness of aquatic organisms through different toxicity mechanisms, including direct exposure (both short- and long-term)2. Hence, standardized laboratory bioassays to assess toxicological endpoints related to fitness and survival may be an unreliable estimate of the many indirect effects of stress in the field. Furthermore, alterations in normal physiological levels and effects on individuals, such as in terms of prey capture, may be better long-term indicators of the impact on survival and reproductive fitness in organisms and, ultimately, on the health of the ecosystem1,3. Predicting changes in ecosystem composition and function, as well as organism health, based on a known set of environmental parameters and contaminant concentrations, is important for improving pollution management1.

Biomarkers are defined as biochemical, physiological, or histological changes due to either exposure to or the effects of xenobiotic chemicals4,5. Biomarkers have proven to be very useful as early warning signals4,5. An important question that biomarkers help answer is whether certain stressors are present in high enough concentrations in the environment to cause adverse effects. This information contributes to the assessment of whether it is worth investigating the nature and extent of the damage and the causative agents or whether no more resources should be invested in that case6,7,8. Moreover, since the concept of evaluating a single biomarker as a bioindicator may not be adequate5,7,8,9,10, there is a growing trend toward performing a comprehensive evaluation of multiple biomarkers in order to detect early warning signs and, thus, prevent irreversible effects on ecosystems.

It is very important to note that all toxic effects begin with the interaction of a stressor with biomolecules. In this sense, effects can cascade through the biochemical, subcellular, cellular, tissue, organ, individual, population, community, ecosystem, landscape, and biospheric levels of organization. Cells are the primary site of interaction between environmental stressors and biological systems. Thus, understanding molecular and genetic effects allows researchers to associate low and high levels of ecological organization and helps them to predict the effect of environmental pollutants, for example, on human health, that have not yet been tested5. Moreover, due to the high specificity of cells, they are not only useful for evaluating environmental pollutants but also human health5,11. Therefore, understanding the effects of stressors at the biochemical level may provide insights into the causes of the observed effects and allow them to be connected with those at the next higher level5. In addition, by understanding the biochemical mechanisms of stressors, the effects of new stressors that have not yet been toxicologically evaluated may be predicted with respect to other well-known contaminants based on their similarities in function. In the presence of various environmental stressors, genetic and biochemical biomarkers may provide valuable information on the specific effects observed. In addition to this, histochemical evaluations related to biochemical changes can provide information on toxicodynamics5. In short, a comprehensive analysis of cellular, biochemical, and histological biomarkers is necessary10,12, and this type of analysis, in turn, should be included in biomonitoring programs for local species5,13,14.

The study of biomarkers under laboratory conditions may, nonetheless, present some difficulties, including difficulties in the detection of sublethal effects and chronic impacts after exposure to pollutants and in the validation and standardization of the methods employed, as well as the complex time- or dose-dependent responses, the unclear or undetermined links to fitness, and the lack of integrated mechanistic models1,4. To solve these problems, the solution is not to increase the number of biomarkers measured but to carefully design studies and testable hypotheses that contribute to explaining the mechanistic bases of chemical effects on whole organisms4.

The new questions in ecotoxicology highlight the importance of applying a battery of biomarkers to generate ecotoxicological predictions that improve the interpretation of the effects of environmental stressors on organisms, as well as decision-making about their possible impact. Moreover, the importance of combining both concepts-biomarkers and bioindicators-in environmental risk assessments and biomonitoring is that this will allow researchers to determine whether organisms in a specific environment of interest are physiologically normal or stressed. The approach taken in this study resembles that of the biochemical analysis that is carried out in humans. In this sense, a battery of biomarkers may be analyzed to see if an organism is healthy both in the field and in the laboratory6. Finally, biomarkers will contribute to ecological risk assessments in two ways: (1) assessing the exposure of rare and/or long-lived species, and (2) testing hypotheses about the mechanisms of chemical impacts at different levels of biological organization4.

In the last decade, biomarkers have been used in anurans for biomonitoring the exposure to cytotoxic and genotoxic contaminants. Among these, the techniques that have been used most frequently are the micronucleus (MN) assay and the comet assay or the induction of single-stranded DNA breaks by single-cell gel electrophoresis (SCGE) assay. In addition, those techniques have been successfully used to estimate the DNA damage induced by various environmental stressors in several neotropical anurans14,15,16,17,18,19. Other biomarkers can used to examine changes in the oxidative status in organisms exposed to environmental pollutants16,17,18,19. Oxidative stress is a response to exposure to different xenobiotics, leading to several detrimental effects, including on the antioxidant capacity of the exposed individuals5,6,7,19,20.

In ecotoxicological studies, bioindicator species are used because they are organisms that identify the long-term interactions and adverse effects of environmental stressors at higher organizational levels (e.g., organism, population, community, and ecosystem levels)10,20,21. By integrating the two concepts-biomarkers and bioindicators-species can be screened to broadly define biochemical, physiological, or ecological structures or processes that are correlated or linked with measured biological effects at one or more levels of biological organization. Finally, the great challenge of utilizing both concepts to improve the estimates of the toxicity of a stressor relates to analyzing biomarkers and bioindicators that have high utility in the evaluation of ecological risks20. In this sense, there is consensus on the relevance of employing biomarkers and bioindicators as early warning signs, as they offer relevant information about the response of a test organism to environmental stressors12,20,21.

Amphibians are one of the most threatened and rapidly declining groups of organisms worldwide. One of the main reasons for this decline is pollutants that enter their habitat, such as pesticides, metals, and emerging pollutants22,23,24,25. Anurans have several characteristics that make them useful as bioindicator species, such as their permeable skin, close relationship with water, and sensitivity to environmental pollution2,23,24. These characteristics make amphibians effective bioindicators of environmental health7,8,22,23,24,26.

Nevertheless, it is necessary not only to consider the optimization of basic procedures and the generation of historical data in control groups but also to employ specific bioassays to evaluate responses in organs and tissues to elucidate the nature and variation of effects observed in bioindicators. In this sense, the present work aims to describe several ecotoxicological methodologies to be employed in all stages of neotropical anurans at different ecological levels and validate them as useful biomarkers to be employed both in wildlife and laboratory conditions. This work presents a battery of biomarkers that may be integrated and that have been proven for laboratory and wildlife biomonitoring in anurans exposed to environmental stressors.

Protocol

The following techniques include the previous sacrifice of the animal, which was carried out in accordance with international ethical standards46,47,48, and the subsequent dissection and ablation of the organs. The animals were captured under the authorization of the Ministry of Environment, Agriculture and Production of San Luis Province (Resolution 49-PMA2019). The methods of sacrifice and euthanasia of the animals were duly approved by the protocols of the Institutional Animal Care and Use Committee (CICUA, protocol Q-322/19) from the National University of San Luis. The procedures with anuran organisms were carried out according to guidelines detailed in Garber et al.46, CONICET47, and INTA48. In addition, all the protocols presented here are for neotropical anuran species in their larval and adult life stages; they have already been widely accepted by local researchers and are carried out under a strict protocol and with authorization from the "Comité Institucional de Cuidado y Uso de Animales (CICUA)" of each university involved. A list of the materials and solutions used is presented in the Table of Materials and Table 1.

1. Individual level: Body condition and hepatic and gonadal indexes

  1. Body condition index: Scaled mass index
    NOTE: This index can be used both with adults and with juveniles and larvae. This methodology is based on Peig and Green27, with minor modifications for anurans according to Brodeur et al.28,30and MacCracken and Stebbings29.
    1. Record the body mass of each specimen using a precision analytical scale.
    2. Place each specimen on a millimeter sheet, and take a photograph at a distance of ~15 cm.
      NOTE: It is important to always take photographs from the same distance.
    3. Photograph analysis:
      NOTE: The photographs can be analyzed with the ImageJ program, which is freely available online (https://imagej.nih.gov/ij/index.html), or with any other image analysis program that allows measurements to be made from a scale included in the photograph.
      1. Measure the snout-vent length (SVL) of each specimen using the measure tool from the ImageJ program, and first refer to a known measure in the millimeter sheet.
        NOTE: In tadpoles, the measurement of the body length must be made up to the cloacal tube, disregarding the caudal fin.
    4. Scaled mass index (S)
      1. With the data obtained from the body mass and SVL of each anuran, construct a non-linear power function regression line of body mass (y-axis) against SVL (x-axis).
      2. Calculate the mean length with the SVL data of all the individuals measured from the studied population.
      3. Finally, calculate the scaled mass index (S) according to Peig and Green27 and Brodeur et al.28 using equation (1):
        S = Mi(L0/Li)b    (1)
        where Mi and Li are body mass and SVL from the individual i, respectively; b is the scaling exponent estimated by a non-linear power function regression28; L0 is the mean length for the studied population; and S is the predicted body mass for the individual i when its SVL is standardized to the L0 value.
        ​NOTE: It is important to note that b is a species-specific constant that could also be sex-specific in sexually dimorphic species.
  2. Hepatosomatic index: Scaled liver index
    NOTE: As for the body condition index, this index can be used with individuals at all stages of development. The methodology is based on Brodeur et al.28.
    1. Record the SVL of each specimen according to step 1.1.2 and step 1.1.3.
    2. Euthanize individuals according to ethical standards for anuran amphibians46,47,48.
    3. Remove the entire liver, and record its mass on a precision analytical scale to the nearest milligram.
    4. With the data obtained from the liver mass and SVL of each anuran, construct a non-linear power function regression line of liver mass (y-axis) against SVL (x-axis).
    5. Calculate the mean length with the SVL data of all the individuals measured from the studied population.
    6. Calculate the scaled liver index (SLI) according to Brodeur et al.28 using equation (2):
      SLI = Lmi (L0/Li)b    (2)
      where Lmi and Li are the liver mass and SVL from the individual i, respectively; b is the scaling exponent estimated by a non-linear power function regression28; L0 is the mean length for the studied population; and SLI is the predicted liver mass for the individual i when its SVL is standardized to the L0.
  3. Gonadal index: Scaled gonadal index
    NOTE: This methodology is based on Brodeur et al.30 and is useful only with adult individuals. It is important to note that male and female indices must be analyzed separately as they vary on distinct scales.
    1. Record the SVL of each specimen according to step 1.1.2 and step 1.1.3.
    2. Euthanize individuals according to ethical standards for anuran amphibians46,47,48.
    3. Remove the right and left gonads, and record the mass on a precision analytical scale to the nearest milligram.
    4. With the data obtained from the gonad mass and SVL of each anuran, construct a non-linear power function regression line of gonad mass (y-axis) against SVL (x-axis), similar to step 1.1.4.1 and step 1.2.3.
    5. Calculate the mean length with the SVL data of all the individuals measured from the studied population.
    6. Estimate the scaled gonadal index (SGI) according to Brodeur et al.30 for each animal using equation (3):
      SGI = Gmi(L0/Li)b    (3)
      where Gmi and Li are the gonad mass and SVL from the individual i, respectively, b is the scaling exponent estimated by a non-linear power function regression by Brodeur et al.30, L0 is the mean length for the studied population, and SGI is the predicted gonad mass for an individual i when its SVL is standardized to the L0.

2. Morphological-histological level

NOTE: For this analysis, it is necessary to use histological sections. The first step is to collect the tissue.

  1. Fixing and dehydration
    1. Use a fixative solution to preserve the structures. For anuran tissues, preferably use methacarn or Bouin solution, recommended over the rest of the fixing solutions (Table 1).
      NOTE: All substances must be mixed at the time of use.
    2. Place tadpoles or a tissue fragment of 50-100 mg in a conical tube with 1-2 mL of fixative solution at 4 °C for 3 h. Wash the tissue in the same volume of 70% ethyl alcohol for 30 min.
    3. Place the tissue in a fresh 70% ethyl alcohol solution.
      NOTE: It is possible to stop the procedure at this point for some days before continuing with the dehydration.
    4. Dehydrate the tissue in a series of alcohol solutions: ethyl alcohol 80% (10 min), alcohol 90% (10 min), ethyl alcohol 100% (10 min), and ethyl alcohol 100% (10 min).
    5. Perform diaphanization (clearing) 2 x 10 min in xylene.
    6. Melt the paraffin in a beaker. Soak the tissue for 10 min. Remove the tissue, and place in a histological mold with melted paraffin. Wait for it to solidify at room temperature.
    7. Place 3 µm sections made on a rotating microtome on a glass slide.
  2. Histometric analysis
    1. Stain the tissue sections in hematoxylin-eosin31.
    2. Use 10-20 photomicrographs for measurement with a 100x objective in a light microscope. Analyze 5-10 hepatic cells in each photomicrograph.
      NOTE: Here, liver was used as a model to describe the technique. It is possible to use other tissues; ensure that the objective of the light microscope to be used is suitable for the type of tissue. It is necessary to be able to see and identify the cells to be measured.
  3. Histopathology
    1. After staining the tissue sections in hematoxylin-eosin32, examine 5-10 histological sections under 10x, 20x, 40x, and 100x objectives.
    2. Look for tissue changes and estimate the degree of tissue changes (DTC) index as described by Bernet et al.32 using equation (4):
      DTC =Σalt.(a × w)    (4)
      where Σalt is the sum of alteration; a represents the damage stage (0, absent; 1, low; 2, moderate; 3, high); and w represents the degree of damage reversibility (1, reversible; 2, partially reversible; 3, irreversible).
      ​NOTE: Here, liver was used as a model to describe the technique. It is possible to use other tissues; ensure that the objective of the light microscope to be used is suitable for the type of tissue.
  4. Pigmentary system
    1. After staining the slides in hematoxylin-eosin, examine 10-20 photomicrographs with a 20x objective.
    2. Quantify the area occupied by melanin by measuring differences in the staining intensity using Image Pro-Plus software according to Santos et al.33.
    3. Open the software Image Pro Plus 6.0®.
    4. Select Menu and Toolbar: Biological.
    5. Select the Spatial calibration of magnification used to take the photomicrographs.
    6. Open a histological image.
    7. Select Tool count | Measure objects.
    8. Click on the Select colors button.
    9. Select the dropper tool, and mark the coloring to be measured in the image.
    10. Close the window, and click on Count.
    11. Select View | Statistics to see the results.

3. Biochemical level: Reactive oxygen species (ROS) and cholinergic enzymes

  1. Sample homogenization
    NOTE: Once the experiment is over, preserve the samples (tissues or tadpoles) in phosphate-buffered saline (PBS) if they are not going to be processed at that time by freezing at −20 °C (for 2 months) or −80 °C (for 6 months). Alternatively, they can be homogenized at the time according to the recommendations proposed below.
    1. Tadpoles
      1. Weigh 1 g of a tadpole or pool of tadpoles on a precision analytical balance.
      2. Place the 1 g of tadpoles in a 15 mL conical tube containing 1 mL of PBS, and immerse it in an ice bath (4 °C).
      3. Homogenize with a teflon-tipped homogenizer adapted to a conical tube, and work in cold conditions (4 °C).
        CAUTION: Avoid using a high number of revolutions, as this may destroy proteins and raise the temperature.
      4. Transfer the same volume of the liquid homogenate of each sample into two labeled 2 mL microcentrifuge tubes, and work in cold conditions (4 °C).
      5. Centrifuge the samples with the liquid homogenate for 10 min at 4 °C and 9,520 × g.
      6. Finally, extract the supernatant, place it in microcentrifuge tubes, label it in aliquots of 0.5 mL to 1 mL, and preserve in a freezer at −80 °C (for 6 months) or −20 °C (for 2 months) until the enzyme assay.
    2. Adults
      1. Remove the tissue of interest (e.g., liver, muscle, kidney), and weigh 1 g on a precision analytical balance.
      2. Place the tissue in a 50 mL conical tube containing 1 mL of PBS, and immerse it in an ice bath (4 °C).
      3. Homogenize with a teflon-tipped homogenizer adapted to a conical tube, and work cold (4 °C).
        CAUTION: Avoid using a high rpm, as this may destroy proteins and raise the temperature.
      4. Transfer the same volume of the liquid homogenate of each sample into two labeled 2 mL microcentrifuge tubes, and work cold (4 °C).
      5. Centrifuge the tubes with the liquid homogenate for 10 min at 4 °C and 9,520 × g.
      6. Finally, extract the supernatant, place it in microcentrifuge tubes, label in aliquots of 0.5 mL to 1 mL, and preserve in a freezer at −80 °C (for 6 months) or −20 °C (for 2 months) until the enzyme assay.
  2. Protein determination
    NOTE: The protein value is obtained to estimate the enzymatic activity in relation to the total amount of protein while avoiding the underestimation or overestimation of the enzymatic activity values. This methodology is based on Bradford34 with minor modifications for anurans:
    1. Prepare Bradford reagent (see Table 1).
    2. Add 100 mL of H3PO4 at 85% (p/v) to Coomassie G-250 + ethanol, and bring to a volume of 1 L with distilled water.
    3. Prepare the calibration curve with bovine serum albumin (BSA) as a known protein standard (Table 1).
    4. Prepare albumin standards in increasing concentrations for a 3 mL spectrophotometer cuvette. For an example of the standard curve, see Table 2.
    5. Measure the absorbance using a spectrophotometer at 590 nm (this is the wavelength at which the complex of the reagent and the protein is formed).
      NOTE: Performing the Bradford reaction with the sample for reading in the spectrophotometer using a glass cuvette with a maximum volume of 3 mL and an optical path of 1 cm helps the protein determination.
    6. Place the following reactants in a cuvette in this order: 2,000 µL of the Bradford reagent + X µL of the sample (X = 20 µL of the homogenate sample of the organ of interest from an adult anuran, or 40 µL of the homogenate sample from a tadpole).
    7. Finally, measure the absorbance in the spectrophotometer at 590 nm.
      NOTE: It is not necessary to work at 4 °C.
  3. Catalase
    NOTE: This methodology is based on Aebi35 with minor modifications for anurans.
    1. Incubate 1,900 µL of PBS + 40 µL of hydrogen peroxide (H202) + 20 µL of the sample (pure in tadpoles and diluted 1/25 for adult tissue) in a 3 mL quartz cuvette with a 1 cm path length.
      CAUTION: Follow the order given above for the addition of the reagents and the sample during the incubation. The reactants can be incubated at room temperature (25 °C) since anurans are physiologically ectothermic.
    2. Read the catalase kinetics at 240 nm for 2 min in a UV spectrophotometer.
    3. Calculate the enzyme activity with the following equation (5)35:
      k (mmol∙min-1∙mg-1 Prt) = (Δ absorbance/1,000)/protein concentration    (5)
      ​NOTE: In studies with purified enzyme preparations, the specific activity k'0 is obtained by dividing k by the molar extinction coefficient, (e = 43,6); k' = (k/e).
  4. Glutathione S-transferase (GST)
    NOTE: This methodology is based on Habig et al.36 with minor modifications for anurans.
    1. Incubate 300 µL of GST + 10 µL of 1-choro-2, 4-dinitrobenzeno (CDNB) (0.1 M) + 10 µL of the sample (pure in tadpoles and diluted 1/25 for adult tissue) in the cuvette.
      CAUTION: Respect the order of addition of the reagents and the sample given above during the incubation. The reagents can be incubated at room temperature (25 °C) since anurans are physiologically ectothermic.
    2. Prepare the GST (Table 1).
    3. Read the GST kinetics at 340 nm for 2 min in the spectrophotometer.
    4. Calculate the enzyme activity with the following equation (6):
      Activity rate of GST (mmol/per minute/mg protein) = ([Δ absorbance/1,000]/9.6 × 104)/protein concentration    (6)
      ​Where 9.6 mM−1 cm−1 = molar extinction coefficient.
  5. Lipid peroxidation (TBARS)
    NOTE: This methodology is based on Buege and Aust37 with minor modifications for anurans.
    1. Construct a calibration curve with MDA as the standard and 0.7% TBA (Table 3).
    2. Prepare the standard MDA solution (10 mM) (Table 1). Carry out THP hydrolysis to MDA by placing the solution in a 50 °C water bath for 1 h.
    3. Prepare a 0.7% (w/v) solution of TBA (Table 1) using a magnetic hot plate stirrer.
    4. Then, centrifuge the sample homogenates for 30 min at 9,520 × g and 4 °C.
    5. Extract 500 µL of the supernatant, add 100 µL of 6 M NaOH, and place in a thermal bath at 60 °C for 30 min.
    6. After the thermal bath, add 250 µL of 35% HClO4, and then place in an ice bath (4 °C) for 30 min.
    7. After that time, centrifuge at 9,520 × g for 12 min, and extract 300 µL of the supernatant.
    8. Add 300 µL of 0.7% TBA to the supernatant (sample), and place in a thermal bath (97.5 °C) for 30 min.
    9. Read the absorbance of the complex formed by the sample and TBA at 532 nm, and determine the MDA concentration in the samples by substituting the absorbance values in the equation of the curve (Figure 1).
  6. Acetylcholinesterase (AChE)
    NOTE: This methodology is based on that proposed by Ellman et al.38 with minor modifications for anurans.
    1. At the moment of measurement, set up the DTNB and acetylthiocholine iodide (ATCh) reagents.
    2. Prepare the DTNB reaction (Table 1).
    3. Prepare the AChE reaction (Table 1).
    4. In a glass cell with an optical path of 1 cm, prepare the AChE reaction by placing these reagents in the following order: 150 µL of PBS buffer (pH = 8) + 150 µL of DTNB + 50 µL of ATCh + 10 µL of the sample (pure in tadpoles and diluted 1/10 in adult anurans).
    5. Read the AChE kinetics at 412 nm for 2 min at room temperature.
    6. Obtain the value of AChE activity using the following equation (7):
      Activity rate of AChE (mmol∙min-1∙mg-1 protein) = ([Δ absorbance/1,000]/1.36)/protein concentration    (7)

4. Genetic and cellular level: Micronucleus and comet assay

  1. Micronucleus (MN) assay
    NOTE: The methodology is in agreement with that proposed by Fenech39 with slight modifications for neotropical anurans.
    1. Anesthetize the specimens by immersion in ice water (4 °C), and obtain blood samples by sectioning behind the operculum in tadpoles or by cardiac puncture in adults.
    2. Smear two drops of peripheral blood from the specimens onto precleaned slides.
    3. Afterward, air-dry the slides, fix with 100% (v/v) cold methanol (4 °C) for 20 min, and then stain with 5% Giemsa solution for 12 min.
    4. Have one researcher code and blind-code the slides at 1,000x magnification.
    5. Determine the frequency of MNs by analyzing 1,000 mature erythrocytes from each specimen, and express as the total number of MNs per 1,000 cells.
    6. Use the following criteria for the correct identification of MNs:
      1. Look for MNs that have diameters smaller than 1/3 of that of the main nucleus.
      2. Ensure that the coloration of the MN is not refractable but has a staining intensity that is the same or lighter than that of the main nucleus.
      3. Look for an MN boundary that is distinguishable from the main nucleus boundary without any connection to the core or overlapping with the main nucleus.
      4. Ensure that the number of MNs in the cells does not exceed more than four MNs associated with the nucleus.
  2. Comet assay or single-cell gel electrophoresis (SCGE)
    1. Anesthetize specimens by immersion in ice water, and obtain blood samples by sectioning behind the operculum in tadpoles or by cardiac puncture in adults.
    2. Dilute the blood with 1 mL of PBS, centrifuge (381 × g, 9 min), and resuspend in a final volume of 50 mL of PBS.
    3. Mix 30 µL of the blood sample in 70 µL of low-melting point agarose (LMPA) at a 0.5% concentration of agarose to form layer 2. Subsequently, place 50 µL of layer 2 on a slide previously coated with layer 1 containing 100 µL of 0.5% normal-melting point agarose.
    4. Cover the slide with a coverslip, and place in the cold (4 °C) for 10 min to solidify layer 2.
    5. After solidification, remove the coverslip, and form the third layer by laying down 100 µL of 0.5% LMPA.
    6. When the third layer solidifies, remove the coverslip, and immerse each slide in a 100 mL Coplin jar containing lysis solution (Table 1) that has been prepared on the same day and kept at 4 °C. Place the Coplin jars in a cold bath for 1 h in the dark (4 °C) for lysis to occur.
      NOTE: The experiment can be paused and restarted later. The lysis period has been reported to last from 1 h to 1 month.
    7. At the end of the lysis, remove the slides, and immerse in the electrophoresis buffer solution (Table 1) in the electrophoresis tank. Perform this step in the dark for 15 min at 4 °C to allow the DNA to unwind. After nuclear DNA unwinding, perform electrophoresis on the same buffer at a temperature of 4 °C for 10 min at 25 V and 250 mA.
    8. At the end of the electrophoresis, neutralize the samples contained in the slides 3 x 5 min by adding 2 mL of Tris-HCl solution (Table 1).
    9. In the last step of the comet assay technique, dehydrate the samples by placing the samples in 100 mL Coplin jars containing alcohol (95%) at 4 °C.
    10. Finally, stain the samples by placing 10 µL of 4′,6-diamino-2-phenylindole (DAPI) in the center of the slide, and place a coverslip that spreads the dye throughout the samples. Examine the slides under a fluorescence photomicroscope with a WB filter.
      CAUTION: The whole process must be carried out in the dark to avoid DNA photodegradation.
    11. Quantify the DNA damage by evaluating the length of DNA migration from the nucleoid. In this case, visually determine it on 100 randomly selected cells without overlap. Classify the DNA damage into four classes: 0-I (no damage), II (minimum damage), III (medium damage), and IV (maximum damage). Express the data as the mean number of damaged cells (sum of classes II-IV) and the mean comet score for each treatment group. From these data, calculate the genetic damage index (GDI) for each test organism using the following equation (8):
      GDI = (1[I] + 2[II] + 3[III] + 4[IV])/N[I-IV])     (8)
      where I-IV represent the type of nucleoid damage, and NI-NIV represent the total number of nucleoids scored according to Pitarque et al.40.

5. Correlated biomarkers

NOTE: In recent times, biomarkers can be integrated at all levels by using the biomarker response (IBR) index proposed by Beliaeff and Burgeot49 and adapted for neotropical anurans. The IBR provides a numeric value that integrates all biomarker responses; higher IBR values indicate higher stress levels49. In terms of the IBR estimation for a given station or treatment of a given survey, the successive data-processing steps to determine the final score are as follows:

  1. Compute the mean estimate (X) when individual results are available; otherwise, use the value from the pooled sample at each sampling station.
  2. For each biomarker, compute the general mean (m) and standard deviation (s) of X for all the stations and/or surveys, depending on the comparisons to be made.
  3. Standardize X to obtain Y. Calculate a value called Y: Y = (X- m)/s.
  4. Compute the Z value as follows: Z = Y or Z = −Y, in the case of a biological effect corresponding, respectively, to inhibition or activation in response to a stressor.
  5. Finally, compute the score (S), with S = Z + |Min|, where S ≥ 0 and |Min| is the minimum absolute value determined.
  6. Plot a spider or star diagram after calculating the value of S for each biomarker (Si) and performing the summatory to obtained the IBR.
    NOTE: refer to the original paper49 for any details of the calculations.

Results

All the biomarker techniques presented here are simple, rapid, convenient, sensitive, low cost, and accurate methods. For each biomarker, it is important to note the following.

Individual level
Scaled mass index
Taking photographs on the millimeter scale is of great importance since this value will be used to calibrate the software, and this results in better objectivity with respect to the caliper measurement when taking the SVL variable. In addit...

Discussion

The biomarkers at the individual level are very simple to determine and very low-cost, as examining these biomarkers requires only a few pieces of equipment that are usually available in any research laboratory. In addition, these biomarkers provide general information on the health and fitness of the animals. The number of animals employed in each protocol is critical for obtaining reliable results. Due to the variability of data, a minimum of five animals (N = 5) is necessary for each treatment. In detail, a critical s...

Disclosures

The authors declare no competing interests.

Acknowledgements

The authors gratefully acknowledge Instituto de Química de San Luis "Dr. Roberto Olsina"- Consejo Nacional de Investigaciones Científicas y Tecnológicas (INQUISAL-CONICET), Universidad Nacional de San Luis (Project PROICO 2-1914), Laboratório de Patologia Experimental (LAPEx) - Instituto de Biociências (INBIO) - Universidade Federal de Mato Grosso do Sul (UFMS), Cátedra de Citología - Universidad Nacional de La Plata (UNLP), and Agencia Nacional de Promoción Científica (FONCYT; PICT-2018-02570 and PICT-2018-01067) for financial support. We would also like to thank native speaker Lidia Unger and GAECI-UNSL (scientific writing assistance center) from the National University of San Luis for the proofreading of the manuscript.

Materials

NameCompanyCatalog NumberComments
Analytical scale
Electrophoresis power supply Enduro E0203-250V 
Eosin Merck
Fluorescence photomicroscope Olympus BX50Equipped with an appropriate filter combination
Hematoxylin of HarrisMerck
High resolution photo camera  >16 megapixels
Homogenizer
Horizontal electrophoresis chamber Sigma
MicrocentrifugeDenver Instrument
MicroscopeLeicaDM4000 BEquipped with image capture system Leica DFC 280
MicrotomeLeica2265
ParaplastSigmaP3558
Personal Computer Eqquiped with Mac OS X, Lynux or Windows
Refrigerated centrifuge
UV–Vis spectrophotometerRayleigh723GWith UV-lamp

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