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Article
Application of Non-Destructive Methods: Biomarker Assays in
Blood of White Stork (Ciconia ciconia) Nestlings
Dora Bjedov 1, † , Alma Mikuška 1, †, Carina Lackmann 2,3, Lidija Begovi´c 1, Tibor Mikuška 4
and Mirna Velki 1, *
Citation: Bjedov, D.; Mikuška, A.;
Lackmann, C.; Begovi´c, L.; Mikuška,
T.; Velki, M. Application of
Non-Destructive Methods: Biomarker
Assays in Blood of White Stork
(Ciconia ciconia) Nestlings. Animals
2021,11, 2341. https://doi.org/
10.3390/ani11082341
Academic Editors: Camila
Peres Rubio and Breno Fernando
Martins de Almeida
Received: 26 July 2021
Accepted: 6 August 2021
Published: 8 August 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
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iations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1Department of Biology, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia;
dora.bjedov@gmail.com (D.B.); amikuska@biologija.unios.hr (A.M.); lbegovic@biologija.unios.hr (L.B.)
2Department of Evolutionary Ecology and Environmental Toxicology, Goethe University Frankfurt,
60438 Frankfurt am Main, Germany; lackmann@bio.uni-frankfurt.de
3Department of Ecosystem Analysis, Institute for Environmental Research, ABBt-Aachen Biology and
Biotechnology, RWTH Aachen University, 52074 Aachen, Germany
4Croatian Society for Birds and Nature Protection, 31000 Osijek, Croatia; tibor.kopacki.rit@gmail.com
*Correspondence: mirna.velki@gmail.com or mvelki@biologija.unios.hr; Tel.: +385-(0)31-399-935
† Share first authorship on this work.
Abstract:
White stork (Ciconia ciconia) nestlings can provide quantitative information on the quality
of the surrounding environment by indicating the presence of pollutants, as they depend on locally
foraged food. This study represents the first comparison of biomarkers in two fractions of white
stork nestling blood: plasma and S9 (the post-mitochondrial fraction). The aim of this study was to
evaluate acetylcholinesterase (AChE), carboxylesterase (CES), glutathione S-transferase (GST), and
glutathione reductase (GR), as well as to establish a novel fluorescence-based method for glutathione
(GSH) and reactive oxygen species (ROS) detection in plasma and S9. Considering the enzymatic
biomarkers, lower variability in plasma was detected only for AChE, as CES, GST, and GR had lower
variability in S9. Enzyme activity was higher in plasma for AChE, CES, and GST, while GR had
higher activity in S9. Regarding the fluorescence-based method, lower variability was detected in
plasma for GSH and ROS, although higher GSH detection was reported in S9, and higher ROS was
detected in plasma. The present study indicated valuable differences by successfully establishing
protocols for biomarker measurement in plasma and S9 based on variability, enzyme activity, and
fluorescence. For a better understanding of the environmental effects on nestlings’ physiological
condition, biomarkers can be measured in plasma and S9.
Keywords: non-destructive sampling; apex bird species; plasma; S9; biomarkers
1. Introduction
The white stork (Ciconia ciconia) is a large migratory bird species breeding in Europe
and wintering in Africa, associated with open wet grasslands and agriculture habitats [
1
].
However, in recent years, studies show that a high percentage of white storks also stay
in south-western Europe during winter [
2
,
3
]. As an apex bird species with opportunistic
feeding habits, their diet mostly comprises of various invertebrates (grasshopper, beetles,
earthworms, and crustaceans), amphibians, fish, snakes, lizards, small mammals (voles,
mice, rats, and shrews), and, occasionally, trash from landfills [
4
–
9
]. White stork nestlings
are fed on local food sources, foraged by their parents, making them suitable bioindicators
and sentinels of contaminants in a local environment [
10
,
11
]. A decline in the breeding
population of storks is related to decreasing availability of grasslands and wetlands and
increase in anthropogenic activities, especially intensive agriculture [12].
Various chemicals are used in agriculture with potential accumulation of toxins in
apex bird predators, such as the white stork [
12
]. Apex bird species are non-target organ-
isms to pesticide exposure in environments such as wetlands or agricultural ponds [
13
].
Animals 2021,11, 2341. https://doi.org/10.3390/ani11082341 https://www.mdpi.com/journal/animals
Animals 2021,11, 2341 2 of 17
Their health status is influenced by their dietary habits, and their body content reflects
pollutant concentrations in the food [
14
–
16
]. Nestling physiological condition is the ability
to maintain a stable homeostasis. This condition can be affected by local pollution. Changes
in the physiological condition can affect behaviour, cell metabolism, neuronal activity, etc.,
and therefore can provide useful information regarding local pollution and the effect it
has on the environment [
15
]. Biomarker analysis is utilized for evaluation of a pollutant’s
impact on non-target avian species as well as for ecological risk assessment [
12
]. Enzyme
activity measurements in blood can provide valuable information regarding environmental
impact on wildlife [
17
,
18
]. Enzymatic activity can be altered with various stressors and can
provide an early warning sign of pollution [
13
]. Although some studies still use destructive
sampling, such as capturing birds in traps and decapitation [
19
–
22
], blood sampling, if
done correctly, is a simple, non-destructive method for laboratory analysis [
23
] and should
be utilized over destructive methods. Non-invasive (e.g., collecting shed feathers [
24
] and
collection of addled eggs [
25
]) and non-destructive (e.g., blood sampling [
26
,
27
]) methods
should be employed for the purpose of animal welfare, to minimize the environmental
impact on birds, thus helping conserve avian biodiversity, especially when working with
near threatened and critically endangered species. For optimal assessment, biomarkers
in blood often need to be measured in parallel; therefore, it is recommended to draw a
maximum amount of blood at once [
28
]. Various biomarkers can be measurement in blood,
such as antioxidant enzymes, mixed-function oxidases, hormones, corticosteroids [
17
,
18
],
or environmental contaminants (e.g., lead [
29
,
30
]). So far, in avian blood, oxidative stress
and esterase biomarkers have been analysed for the purpose of assessing organophos-
phate and carbamate exposure, air and heavy metal pollution indicators, and genotoxic
damage [12,31–35].
Avian blood has diverse implementations in ecotoxicology; however, no data is
available assessing the esterase and oxidative stress biomarkers in white stork nestlings in
two blood fractions. For this purpose, the main goals of the study were to:
1.
Optimize protocols for measurement of the following biomarkers in the collected
blood samples, as well as adjust for the microplate reader: acetylcholinesterase, car-
boxylesterase, glutathione S-transferase and glutathione reductase activities, reactive
oxygen species and glutathione levels, as well as total protein content.
2.
Determine the basal activities of the measured biomarkers in the blood of white stork
nestlings from Croatia.
3. Determine the sex of the white stork nestlings from the sampled blood.
Optimization of biomarker protocols and sex determination in white stork nestlings’
blood will be useful for the purpose of obtaining information from small blood volume,
and will enable application of these biomarkers in future research, which will improve
the ecotoxicological investigations of birds without the need for destructive sampling.
Application of biomarker measurement gives insight into the physiological response to
stressors in apex predators and will provide information on early warning signs of possible
environmental pollution.
2. Materials and Methods
2.1. Field Procedure and Blood Extraction
Fieldwork was performed during the 2020 breeding season in villages along Drava
river in north-eastern Croatia. The area is influenced by industry near Osijek as well as
intensive agrochemical use in the surrounding area. Blood samples were taken from 16
nestlings in 7 nests. Protocols for monitoring the white stork population in Croatia [
36
,
37
]
were used for finding and approaching nests. All nests were accessed with a telescopic
crane. Nestlings were captured in their nest, placed in a bag, and lowered onto the
ground. Each nestling was put on its back, and its head covered with a cloth to avoid
additional stress. The beak was measured for age determination and all nestlings were
between 6 and 8 weeks old. All sampling procedures were done between 08:00 a.m. and
12:00 p.m. to avoid heat stress and to avoid disturbing feeding habits. Morphometric
Animals 2021,11, 2341 3 of 17
measurements were taken (beak measurement to determine the order of the hatching),
and blood samples were collected. A sterile 5 mL syringe and 0.8 mm (20 gauge) needle
were used to puncture the brachial vein and approximately 4 mL of blood was drawn and
transferred to lithium heparin collection tubes. Blood was stored under cold and dark
conditions until centrifugation within 6–8 h. The study was conducted under the permit of
The Ministry of Environment and Energy of the Republic of Croatia (Classification code:
UP/I-612-07/20-48/130; Registry number: 517-05-1-1-20-4).
2.2. Sample Preparation
Blood was centrifuged at 3000
×
gfor 10 min at 4
◦
C. The supernatant (plasma) was
transferred to the new sterile tube and kept at –80
◦
C until further analysis. The pellet was
dissolved with a 5 mL 0.1 M phosphate buffer (pH 7.2) and a sonicator was used for cell
disruption at 30% strength for 2 min. Samples were subsequently centrifuged at 9000
×
g
for 20 min at 4
◦
C to obtain the post-mitochondrial supernatant (S9). The S9 fraction was
kept at –80
◦
C until further analysis. All measurements were performed in both types of
samples: plasma and S9.
2.3. Chemicals
In the present study, the following chemicals (analytical grade) were used: acetonitrile
(C
2
H
3
N, CAS 75-05-8, 41.053 g mol
−1
),
β
-Nicotinamide adenine dinucleotide 2
0
-phosphate re-
duced tetrasodium salt hydrate (
β
-NADPH) (C
21
H
26
N
7
Na
4
O
17
P
3
x H
2
O, CAS
2646-71-1 (anhydrous), 833.35 g mol
−1
(anhydrous basis)), CellTracker
™
Green CMFDA Dye
(C
25
H
17
ClO
7
, CAS 136832-63-8, 464.86 g mol
−1
) (ThermoFisher Scientific, Waltham, MA,
USA), 1-chloro-2,4-dinitrobenzene (CDNB) (C
6
H
3
ClN
2
O
4
, CAS 97-00-7, 202.55 g mol
−1
), CM-
H
2
DCFDA (C
27
H
19
Cl
3
O
8
, CAS 1219794-09-8, 577.8013 g mol
−1
) (ThermoFisher Scientific,
Waltham, MA, USA), (2-Mercaptoethyl) trimethylammonium iodide acetate (acetylthio-
choline iodide) (CH
3
COSCH
2
CH
2
N(CH
3
)
3
I, CAS 1866-15-5, 289.18 g mol
−1
), disodium hy-
drogen phosphate (NaH
2
PO
4
, CAS 7558-79-4, 141.957 g mol
−1
), 5,5
0
-dithiobis-(2-nitrobenzoic
acid) (DTNB) ([-SC
6
H
3
(NO
2
)CO
2
H]
2
, CAS 69-78-3, 396.35 g mol
−1
), glutathione disulfide
(GSSG, C
20
H
32
N
6
O
12
S
2
, CAS 27025-41-8, 612.6 g mol
−1
), p-nitrophenyl acetate (C
8
H
7
NO
4
,
CAS 830-03-5, 181.147 g mol
−1
), (2S)-2-amino-4-{[(1R)-1-[(carboxymethyl)carbamoyl]-2-
sulfanylethyl]carbamoyl}butanoic acid (glutathione (GSH)) (C
10
H
17
N
3
O
6
S,CAS 70-18-8,
307.32 g mol
−1
), and sodium dihydrogen phosphate dihydrate (NaH
2
PO
4×
2H
2
O, CAS
13472-35-0, 156.006 g mol
−1
). For protein concentration measurements, the Pierce
™
BCA
Protein Assay Kit (Pierce Biotechnology, Waltham, MA, USA) was used.
2.4. Enzymatic Biomarkers
All biomarker measurements were adjusted for the Tecan Spark 10 M microplate
reader (Tecan Trading AG, Männedorf, Switzerland). The plasma and S9 samples as well
as blanks were measured in triplicate. Enzyme activity was calculated from the obtained
changes in the measured absorbance and expressed as specific enzyme activity.
2.4.1. Protocol for Measurement of Acetylcholinesterase (AChE) Activity
The activity of AChE in the plasma and S9 samples was determined according to
the method of Ellman et al. [
38
]. For the plasma samples, the reaction mixture contained
5
µ
L plasma diluted 5x with phosphate buffer (0.1 M, pH 7.2), 180
µ
L phosphate buffer
(0.1 M, pH 7.2), 10
µ
L DTNB (1.6 mM, prepared with phosphate buffer (0.1 M, pH 7.2)),
and 10
µ
L acetylthiocholine iodide (156 mM, prepared with distilled water). Increase in
absorbance was measured for 5 min at 412 nm. For the S9 samples, the reaction mixture
contained 25
µ
L S9 diluted 10x with phosphate buffer (0.1 M, pH 7.2), 180
µ
L phosphate
buffer (0.1 M, pH 7.2), 10
µ
L DTNB (1.6 mM prepared with phosphate buffer (0.1 M, pH
7.2)), and 10
µ
L acetylthiocholine iodide (156 mM, prepared with distilled water). Increase
in absorbance was measured for 10 min at 412 nm. Blank measurements of the plasma and
S9 were performed in parallel containing 180
µ
L phosphate buffer, 10
µ
L DTNB, and 10
µ
L
Animals 2021,11, 2341 4 of 17
acetylthiocholine iodide (all prepared in the same way as described previously). Specific
enzyme activity was calculated with the extinction coefficient (ε) = 13.6 ×103M−1cm−1.
2.4.2. Protocol for Measurement of Carboxylesterase (CES) Activity
The activity of carboxylesterase in plasma and S9 was determined according to the
Hosokawa and Satoh method [
39
]. For the plasma samples, the reaction mixture contained
10
µ
L plasma and 150
µ
Lp-nitrophenyl acetate (1 mM, dissolved in acetonitrile, diluted
with distilled water). Increase in absorbance was measured for 4 min at 405 nm. For the
S9 samples, the reaction mixture contained 20
µ
L S9 10x diluted with phosphate buffer
(0.1 M, pH 7.2) and 150
µ
Lp-nitrophenyl acetate (1 mM, prepared in acetonitrile, diluted
with distilled water). Blank measurements of the plasma and S9 were performed in parallel
containing 150
µ
Lp-nitrophenyl acetate (prepared in the same way as described previously).
Increase in absorbance was measured for 5 min at 405 nm. Specific enzyme activity was
calculated with ε= 16.4 ×103M−1cm−1.
2.4.3. Protocol for Measurement of Glutathione S-Transferase (GST) Activity
The activity of glutathione S-transferase in plasma and S9 was determined following
the Habig and Jakoby method [
40
]. For the plasma samples, the reaction mixture contained
5µL plasma, 160 µL CDNB (1 mM, dissolved in 96% ethanol and diluted with phosphate
buffer (0.1 M, pH 7.2)), and 40
µ
L GSH (25 mM, prepared in distilled water). Increase in
absorbance was measured for 2 min at 340 nm. For the S9 samples, the reaction mixture
contained 20
µ
L S9 homogenate diluted 10x with phosphate buffer (0.1 M, pH 7.2), 160
µ
L
CDNB (1 mM, dissolved in 96% ethanol and diluted with 0.1 M, pH 7.2 phosphate buffer),
and 40
µ
L GSH (25 mM, prepared in distilled water). Blank measurements of the plasma
and S9 were performed in parallel containing 160
µ
L CDNB and 40
µ
L GSH (all prepared
in the same way as described previously). Increase in absorbance was measured for 5 min
at 340 nm. For the plasma measurement, the first minute was needed for stabilization
and was omitted from the calculations. Specific enzyme activity was calculated with
ε= 9.6 ×103M−1cm−1.
2.4.4. Protocol for Measurement of Glutathione Reductase (GR) Activity
The activity of glutathione reductase in plasma and S9 was determined using the
Habig and Jakoby protocol [
40
]. For the plasma samples, the reaction mixture contained
20
µ
L plasma, 100
µ
L phosphate buffer (0.1 M, pH 7.2), 100
µ
L GSSG (2 mM, prepared in
phosphate buffer (0.1 M, pH 7.2)), and 10
µ
L
β
–NADPH (1 mM, prepared in phosphate
buffer (0.1 M, pH 7.2)). Decrease in absorbance was measured for 10 min at 340 nm.
For the S9 samples, the reaction mixture contained 10
µ
L S9, 100
µ
L phosphate buffer
(0.1 M, pH 7.2), 100
µ
L GSSG (2 mM, prepared in phosphate buffer (0.1 M, pH 7.2)), and
10
µ
L reduced
β
–NADPH (1 mM, prepared in phosphate buffer (0.1 M, pH 7.2)). Blank
measurements for plasma and S9 were performed in parallel containing 100
µ
L phosphate
buffer, 100
µ
L GSSG, and 10
µ
L reduced
β
–NADPH (all prepared in the same way as
described previously). Decrease in absorbance was measured for 10 min at 340 nm. Specific
enzyme activity was calculated with ε= 6.22 ×103M−1cm−1.
2.5. Fluorescent Dyes Protocols
Detection of GSH and ROS using the fluorescent dyes was conducted based on the
protocol previously developed for zebrafish larvae [
41
] and adjusted here for avian plasma
and S9 samples. Measurements were conducted using the Tecan Spark 10 M microplate
reader with the following settings: excitation wavelength—485 nm; emission wavelength—
530 nm; and gain—50. Each plasma, S9, blank, and positive control sample was performed
in parallel and measured in triplicate.
Animals 2021,11, 2341 5 of 17
2.5.1. CellTracker™ Green CMFDA (GSH) Dye
For the plasma samples, the reaction mixture contained 2
µ
L plasma, 90
µ
L phosphate
buffer (0.1 M, pH 7.2), and 5
µ
L CellTracker
™
Green CMFDA (9.78
µ
M, prepared in
DMSO). Fluorescence was measured every 5 min for 60 min. For the S9 samples, the
reaction mixture contained 2
µ
L S9, 90
µ
L phosphate buffer (0.1 M, pH 7.2) and 5
µ
L
CellTracker
™
Green CMFDA (9.78
µ
M, prepared in DMSO). Fluorescence was measured
every 5 min for 60 min. The blank reaction mixture contained 90
µ
L phosphate buffer and
5
µ
L CellTracker
™
Green CMFDA (prepared in the same way as described previously) and
the positive control reaction mixture contained 2
µ
L GSH (25 mM, prepared in distilled
water), 90
µ
L phosphate buffer, and 5
µ
L CellTracker
™
Green CMFDA (all prepared in the
same way as described previously) for both the plasma and S9 samples. The first 30 min
were used for calculations due to the optimal linear increase for plasma and S9.
2.5.2. CM-H2DCFDA (ROS) Dye
For plasma samples, the reaction mixture contained 10
µ
L plasma, 90
µ
L phosphate
buffer (0.1 M, pH 7.2), and 10
µ
L CM-H
2
DCFDA dye (7.87
µ
M, prepared in DMSO).
Fluorescence was measured every 5 min for 30 min. For the S9 samples, the reaction mixture
contained 10
µ
L S9, 90
µ
L phosphate buffer (0.1 M, pH 7.2), and 5
µ
L CM-H
2
DCFDA dye
(7.87
µ
M, prepared in DMSO). Fluorescence was measured every 5 min for 120 min. The
blank reaction mixture contained 90
µ
L phosphate buffer and 5
µ
L CM-H
2
DCFDA dye
(prepared in the same way as described previously), and the positive control reaction
mixture contained 2
µ
L H
2
O
2
(0.019 M, prepared in distilled water), 90
µ
L phosphate
buffer, and 5
µ
L CM-H
2
DCFDA dye (prepared the same way as described previously) for
both plasma and S9.
2.6. Protein Quantification Assay
Protein quantification was performed using the Pierce
TM
BCA Protein Assay Kit and
measurements were performed using the Tecan Spark 10 M microplate reader. The working
solution was prepared as described in the protocol provided in the kit, with bovine serum
albumin as a standard. Each plasma, S9, blank, and standard sample was performed in
parallel and measured in triplicate. For the plasma samples, the reaction mixture contained
2.5
µ
L diluted plasma (5x with phosphate buffer, 0.1 M, pH 7.2), 22.5
µ
L phosphate buffer
(0.1 M, pH 7.2), and 200
µ
L working solution. For the S9 samples, the reaction mixture
contained 2.5
µ
L diluted S9 (10x diluted with phosphate buffer, 0.1 M, pH 7.2), 22.5
µ
L
phosphate buffer (0.1 M, pH 7.2), and 200
µ
L working solution. The microplate with
reaction mixture was shaken for 30 s in Tecan Spark 10 M microplate reader, incubated at
room temperature for 2 h, and the protein concentration was determined at 562 nm.
2.7. Sex Determination
DNA was isolated using an extraction buffer containing 10 mM EDTA, 10 mM Tris-Cl
(pH 8.0), 100 mM NaCl, 2% sodium dodecyl sulphate (SDS, Carl Roth GmbH, Karlsruhe,
Germany), and ultrapure water in final concentrations. In a sterile tube, 125
µ
L S9, 360
µ
L
extraction buffer, 10
µ
L proteinase K (10 mg mL
−1
stock concentration), and 16
µ
L 1 M
dithiothreitol (DTT, Carl Roth GmbH) were added. Following incubation on a thermo-
shaker for 30 min, 56
◦
C at 1000 rpm, 200
µ
L 3 M sodium acetate (Carl Roth GmbH) was
added, vortexed, and incubated for 5 min on ice. The samples were centrifuged for 10 min
at 16,000
×
g, at 4
◦
C, after which the supernatant was transferred to a new tube. Ice-cold
isopropanol was added to the supernatant 1:1 (v:v) for DNA precipitation. The samples
were briefly shaken and then incubated for 30 min at –20
◦
C. Afterwards, the samples
were centrifuged at 18,000
×
gfor 20 min at 4
◦
C, the supernatant was discarded, and
the pellet was washed with 1 mL 70% ethanol. Samples were centrifuged at 18,000
×
g,
at 4
◦
C, for 90 s and the supernatant was discarded. DNA was air-dried and dissolved
in 10
µ
L of nuclease-free water, vortexed, and centrifuged. For DNA quantification, a
NanoPhotometer (Implen GmbH, München, Germany) was used. For the sex-specific CHD
Animals 2021,11, 2341 6 of 17
gene [
42
], the amplification and visualising PCR products protocol by Begovi´c et al. [
43
]
was followed.
2.8. Data Analysis
Data analyses were performed using GraphPad Prism software version 8.4.3 [
44
].
Normality of the data was confirmed with a Shapiro–Wilk test. To compare the difference
between the means of the biomarker response in plasma and S9, Welch’s t-test was used
as unequal variances were confirmed with the F-test. The level of statistical significance
(p) was 0.05. Response variability in plasma and S9 for each parameter was calculated by
dividing the standard deviation of the obtained data with the mean of the obtained data.
All results are expressed as the mean ±SD and presented as bar plots.
3. Results and Discussion
3.1. Sex Determination
Sex was determined from S9 using the CHD gene. Sex-typing showed 8 males and
8 females (Figure S1). There were no statistical differences in biomarker response regarding
sex. Various volumes of S9 were used, and the optimal protocol was determined based
on DNA quantity and quality, as shown in Table S1. DNA quality was determined from
A
260/280
and A
260/230
, indicating purity [
45
–
47
]. The average A
260/280
was 1.99
±
0.06.
A ratio of
≥
1.8 is accepted and considered uncontaminated DNA [
48
]. A ratio of
≤
1.6
may indicate presence of protein, phenols, or other impurities absorbing at 280 nm [
49
].
The average A
260/230
was 2.02
±
0.18. A ratio of 2.00–2.20 is considered uncontaminated
DNA. If A
260/230
is lower, salt, lipid, protein, phenol, guanidinium chloride, or EDTA
contamination is suspected [
50
,
51
]. If the two samples have the same A
260/280
, but different
A260/230, this may be due to different sample concentrations [52]. During blood sampling,
blood coagulation is possible, decreasing the sample concentration. During the sonication
process, there are less available cells, as the samples do not have equal homogeneity;
therefore, the DNA yield will be lower. Although coagulated samples cannot be used
for enzyme assays, they can be used for DNA analysis, e.g., sex determination or DNA
methylation [53].
3.2. Enzymatic Biomarkers
3.2.1. Overview of the Results
Results of the enzymatic biomarkers and fluorescent dyes analysed in plasma and S9
of white stork nestlings are presented in Table 1. Enzymatic biomarkers were analysed
in either plasma or S9; however, when measuring several parameters in blood, there are
certain limitations due to sample volume. Therefore, the enzymatic response in plasma and
S9 samples was investigated. In case of a limited sample volume, the results of this study
will help in deciding which biomarker should be chosen for measurement in which sample
type. Enzymatic biomarkers from blood could be used to identify changes in biomarker
response regarding geographical differences, weather conditions, environmental pollution
gradient, age differences (nestlings, fledglings, juvenile, and adults), and clutch and brood
size. Furthermore, results of the study could be implemented and help in the monitoring
of the white stork population health status in the future.
Table 1.
Results (sample size (n), mean
±
SD, and variability) of the enzymatic parameters and fluorescent dyes measured
in plasma and S9 of white stork (C. ciconia) nestlings.
Parameter nPlasma S9
- - Mean SD Variability (%) Mean SD Variability (%)
AChE [nmol min−1
mgPR OT
−1]16 14.79 5.12 34.60 3.13 1.26 40.21
CES [nmol min−1
mgPR OT
−1]16 21.53 9.59 44.54 5.85 1.96 33.53
GST [nmol min−1
mgPR OT
−1]16 18.26 7.84 42.93 14.41 2.94 20.37
Animals 2021,11, 2341 7 of 17
Table 1. Cont.
Parameter nPlasma S9
- - Mean SD Variability (%) Mean SD Variability (%)
GR [pmol min−1
mgPR OT
−1]16 98.11 65.67 66.94 840.55 235.42 28.01
CellTrackerTM Green
CMFDA (RFU) 16 7246.07 1571.19 21.68 24683.10 7603.60 30.80
CM-H2DCFDA (RFU) 16 76.29 5.09 6.68 33.04 11.55 34.94
SD: standard deviation; AChE: acetylcholinesterase; CES: carboxylesterase; GST: glutathione S-transferase; GR: glutathione reductase;
CellTrackerTM Green CMFDA: dye for glutathione detection; CM-H2DCFDA: dye for ROS detection; RFU: relative fluorescence unit.
3.2.2. Acetylcholinesterase and Carboxylesterase Activity
An increase in absorbance for acetylcholinesterase (AChE) plasma and S9 (Figure S2)
were observed for 5- and 10-min periods, respectively. Different sample concentrations and
measurement times were used and determined based on a linear absorbance increase and
R
2≥
0.95. Due to high AChE activity, plasma and S9 were diluted prior to measurement.
Plasma samples were diluted 5 times, whereas the S9 samples were diluted 10 times
because avian erythrocytes contain haemoglobin that interferes in the absorbance spectrum
400–415 nm. To obtain satisfactory results, the S9 samples had to be more diluted and the
measurement times were prolonged, to reduce the haemoglobin influence on the assay, as
shown in AChE activity in rat erythrocytes [54].
The results of AChE activity in plasma and S9 are shown in Figure 1. Significantly
higher specific AChE activity was reported in plasma than in S9 (p< 0.0001). However,
lower variability among samples was observed in plasma than S9 (Table 1). AChE, as a
transmitter hydrolysing acetylcholine, is primarily found in the central and peripheral
nervous system as well as muscular system [
55
]. There is no data available for AChE
activity in the blood of white stork nestlings. However, blood AChE histochemistry was
assessed [
56
], and AChE activity was analysed for the purpose of determining the effects
of daily photoperiods, a behaviour biomarker of organophosphate (OP) exposure, to estab-
lish the basal levels, compare the response to organophosphate and carbamate exposure,
and compare the age-dependent changes in plasma [
19
–
21
,
57
–
60
]. Furthermore, plasma
cholinesterases were characterised to establish the basal activities [
34
,
61
]. There is wide
variation in AChE activity interspecies [
57
] and between matrices, pointing out the need to
determine the basal AChE activity in plasma and S9 in white stork nestlings. Lower AChE
activity in S9 may be due to AChE localization—bound to erythrocyte membranes [
62
,
63
]
that are destroyed with sonication and centrifugation. After S9 preparation, the pellet
containing cell membranes is usually discarded.
An increase in carboxylesterase (CES) absorbance (OD) was observed for plasma
and S9 samples (Figure S3) for 2- and 5-min time periods, respectively. Different sample
concentrations and measurement times were tested, and the final values used are based
on a linear absorbance increase and R
2≥
0.95. In the S9 samples, the measurement time
was prolonged due to a high haemoglobin concentration, interfering with the assay [
54
].
Nevertheless, a linear increase could be observed.
The results of CES activity in plasma and S9 are shown in Figure 2. Significantly
higher specific CES activity was reported in plasma than in S9 (p< 0.0001). Moreover,
higher variability among samples was observed in plasma than S9 (Table 1). CES is a
ubiquitous enzyme, with the main function being the hydrolysation of carboxylic acid
esters to acid and alcohol, a detoxification mechanism for various xenobiotics [
64
,
65
]. CES
activity has previously been measured in blood of pigeons (Columba livia) and several
bird of prey species for the purpose of evaluating CES activity as a potential biomarker
of OP exposure [
31
]. CES and cholinesterase activity was determined in the muscle and
liver of yellow-legged gull (Larus michahellis) for the purpose of monitoring environmental
pollution [
66
]. Furthermore, CES activity was measured in blood of white storks (C.
ciconia), black storks (Ciconia nigra), vultures, and diurnal and nocturnal predatory birds
Animals 2021,11, 2341 8 of 17
for the purpose of evaluating CES activity as a potential biomarker of OP and carbamate
exposure [
67
]. Specific CES activity was higher in plasma than in S9, due to low esterase
activity in avian erythrocytes [68].
Animals 2021, 11, x 8 of 17
Figure 1. Specific activity of acetylcholinesterase (AChE) in plasma and S9 (nmol min
–1
mg
PROT–1
) of
white stork (C. ciconia) nestlings (n = 16), presented as the mean ± SD. Statistical difference is indi-
cated with **** (Welch’s t-test, p < 0.0001).
An increase in carboxylesterase (CES) absorbance (OD) was observed for plasma and
S9 samples (Figure S3) for 2- and 5-min time periods, respectively. Different sample con-
centrations and measurement times were tested, and the final values used are based on a
linear absorbance increase and R
2
≥ 0.95. In the S9 samples, the measurement time was
prolonged due to a high haemoglobin concentration, interfering with the assay [54]. Nev-
ertheless, a linear increase could be observed.
The results of CES activity in plasma and S9 are shown in Figure 2. Significantly
higher specific CES activity was reported in plasma than in S9 (p < 0.0001). Moreover,
higher variability among samples was observed in plasma than S9 (Table 1). CES is a ubiq-
uitous enzyme, with the main function being the hydrolysation of carboxylic acid esters
to acid and alcohol, a detoxification mechanism for various xenobiotics [64,65]. CES activ-
ity has previously been measured in blood of pigeons (Columba livia) and several bird of
prey species for the purpose of evaluating CES activity as a potential biomarker of OP
exposure [31]. CES and cholinesterase activity was determined in the muscle and liver of
yellow-legged gull (Larus michahellis) for the purpose of monitoring environmental pollu-
tion [66]. Furthermore, CES activity was measured in blood of white storks (C. ciconia),
black storks (Ciconia nigra), vultures, and diurnal and nocturnal predatory birds for the
purpose of evaluating CES activity as a potential biomarker of OP and carbamate expo-
sure [67]. Specific CES activity was higher in plasma than in S9, due to low esterase activity
in avian erythrocytes [68].
Figure 1.
Specific activity of acetylcholinesterase (AChE) in plasma and S9 (nmol min
−1
mg
PROT−1
)
of white stork (C. ciconia) nestlings (n= 16), presented as the mean
±
SD. Statistical difference is
indicated with **** (Welch’s t-test, p< 0.0001).
Animals 2021, 11, x 9 of 17
Figure 2. Specific activity of carboxylesterase (CES) in plasma and S9 (nmol min
–1
mg
PROT–1
) of white
stork (C. ciconia) nestlings (n = 16), presented as the mean ± SD. Statistical difference is indicated
with **** (Welch’s t-test, p < 0.0001).
AChE and CES have possible applications in avian species for environmental bio-
monitoring, as exposure biomarkers to diverse environmental pollutants. AChE is usually
regarded as a destructive biomarker, since it is analysed in brain tissue [69], which is not
suitable for endangered species, making this non-destructive evaluation essential. Alt-
hough CES is usually analysed in serum, and therefore is considered a non-destructive
biomarker (e.g., [70]), certain limitations exist, e.g., the blood volume that could be taken
without harming the bird. Due to esterase’s variability between avian species, it is im-
portant to determine the basal activity for each species, as well as to determine activity in
plasma and S9.
3.2.3. Glutathione S-Transferase and Glutathione Reductase Activity
The increase in glutathione S-transferase (GST) absorbance (OD) was observed for
plasma and S9 samples (Figure S4) for 1- and 5-min time periods, respectively. Different
sample concentrations and measurement times were tested, and the final values used are
based on a linear absorbance increase and R
2
≥ 0.95. For S9, due to haemoglobin interfer-
ence [54], the measurement was prolonged.
The results of GST activity in plasma and S9 are shown in Figure 3. There was no
statistical difference between specific GST activity in plasma and S9, although higher var-
iability among samples was observed in plasma than S9 (Table 1). GST is an enzyme cat-
alysing GSH to xenobiotic substrate conjugates, as a detoxification mechanism [71,72]. As
shown in Figure 3, specific GST activity was similar in plasma and S9 of white stork nest-
lings due to the enzyme distribution in these two blood fractions. Since GST’s primary
function is xenobiotic metabolism, it can be found intra- and extracellular [73]. Plasma
GST detection and its activity reflects de novo synthesis in the liver [74]. So far, GST has
been analysed in the blood of various avian species for the purpose of assessing oxidative
stress caused by metal pollution and persistent organic pollutants as well as evaluating
physiological conditions due to environmental stress [35,75,76–85]. When comparing GST
activity in S9 between nestling, juvenile, and adult storks, Oropesa et al. [35] reports 877.72
nmol min
–1
mg
PROT–1
in juveniles, and 964.61 nmol min
–1
mg
PROT–1
in adults, considerably
higher than reported in this study for nestlings.
Figure 2.
Specific activity of carboxylesterase (CES) in plasma and S9 (nmol min
−1
mg
PROT−1
)
of white stork (C. ciconia) nestlings (n= 16), presented as the mean
±
SD. Statistical difference is
indicated with **** (Welch’s t-test, p< 0.0001).
AChE and CES have possible applications in avian species for environmental biomon-
itoring, as exposure biomarkers to diverse environmental pollutants. AChE is usually
regarded as a destructive biomarker, since it is analysed in brain tissue [
69
], which is not
suitable for endangered species, making this non-destructive evaluation essential. Al-
though CES is usually analysed in serum, and therefore is considered a non-destructive
biomarker (e.g., [
70
]), certain limitations exist, e.g., the blood volume that could be taken
without harming the bird. Due to esterase’s variability between avian species, it is impor-
Animals 2021,11, 2341 9 of 17
tant to determine the basal activity for each species, as well as to determine activity in
plasma and S9.
3.2.3. Glutathione S-Transferase and Glutathione Reductase Activity
The increase in glutathione S-transferase (GST) absorbance (OD) was observed for
plasma and S9 samples (Figure S4) for 1- and 5-min time periods, respectively. Different
sample concentrations and measurement times were tested, and the final values used
are based on a linear absorbance increase and R
2≥
0.95. For S9, due to haemoglobin
interference [54], the measurement was prolonged.
The results of GST activity in plasma and S9 are shown in Figure 3. There was no
statistical difference between specific GST activity in plasma and S9, although higher
variability among samples was observed in plasma than S9 (Table 1). GST is an enzyme
catalysing GSH to xenobiotic substrate conjugates, as a detoxification mechanism [
71
,
72
].
As shown in Figure 3, specific GST activity was similar in plasma and S9 of white stork
nestlings due to the enzyme distribution in these two blood fractions. Since GST’s primary
function is xenobiotic metabolism, it can be found intra- and extracellular [
73
]. Plasma
GST detection and its activity reflects de novo synthesis in the liver [
74
]. So far, GST has
been analysed in the blood of various avian species for the purpose of assessing oxidative
stress caused by metal pollution and persistent organic pollutants as well as evaluating
physiological conditions due to environmental stress [
35
,
75
–
85
]. When comparing GST
activity in S9 between nestling, juvenile, and adult storks, Oropesa et al. [
35
] reports
877.72 nmol min
−1
mg
PROT−1
in juveniles, and 964.61 nmol min
−1
mg
PROT−1
in adults,
considerably higher than reported in this study for nestlings.
Animals 2021, 11, x 10 of 17
Figure 3. Specific activity of glutathione S-transferase (GST) in plasma and S9 (nmol min
–1
mg
PROT–1
)
of white stork (C. ciconia) nestlings (n = 16), presented as the mean ± SD.
A decrease in glutathione reductase (GR) absorbance (OD) was observed in plasma
and S9 (Figure S5) for the 10-min time period. Different sample concentrations and meas-
urement times were tested, and the final values used are based on a linear absorbance
increase and R
2
≥ 0.95.
The results of GR activity in plasma and S9 are shown in Figure 4. Significantly higher
specific GR activity was reported in S9 than in plasma (p < 0.0001). Furthermore, higher
variability among samples was observed in plasma samples compared to S9 samples (Ta-
ble 1). GR is an enzyme catalysing the NADPH-dependent reduction of GSSG to GSH.
GSSG reduction is an essential reaction for the preservation of GSH levels, since GSH has
a primary function in processes regarding oxidation and reduction, as well as cellular de-
toxification [86]. GR has been measured in avian blood for the purpose of assessing eco-
physiological determination and antioxidant defences as a response to environmental pol-
lution, in addition to evaluating the effect of oxidized fat and selenium on GR activity
[35,78,79,83,84,87–91]. Oropesa et al. [35] reports that the GR activity in S9 of juvenile and
adult storks (C. ciconia) is substantially lower (410 pmol min
–1
mg
PROT–1
and 380 pmol min
–
1
mg
PROT–1
, respectively) than reported in this study for white stork nestlings. This could
be due to production of free radicals and depletion of antioxidant defences, both related
to aging and age-related diseases [92,93]. Considering that older storks loose function to
regulate physiological homeostasis and depletion of some blood enzymatic antioxidants,
as a consequence of aging [94–96], nestlings might be a more suitable age group for bio-
monitoring assessments. As shown in Figure 4, higher GR activity was found in S9 than
plasma. That being said, GR is a cellular enzyme that accumulates in cellular regions with
high electron flux, resulting in high ROS production [97].
Figure 3.
Specific activity of glutathione S-transferase (GST) in plasma and S9
(nmol min−1mg PROT−1) of white stork (C. ciconia) nestlings (n= 16), presented as the mean ±SD.
A decrease in glutathione reductase (GR) absorbance (OD) was observed in plasma
and S9 (Figure S5) for the 10-min time period. Different sample concentrations and mea-
surement times were tested, and the final values used are based on a linear absorbance
increase and R2≥0.95.
The results of GR activity in plasma and S9 are shown in Figure 4. Significantly higher
specific GR activity was reported in S9 than in plasma (p< 0.0001). Furthermore, higher
variability among samples was observed in plasma samples compared to S9 samples
(Table 1). GR is an enzyme catalysing the NADPH-dependent reduction of GSSG to
GSH. GSSG reduction is an essential reaction for the preservation of GSH levels, since
GSH has a primary function in processes regarding oxidation and reduction, as well
Animals 2021,11, 2341 10 of 17
as cellular detoxification [
86
]. GR has been measured in avian blood for the purpose
of assessing ecophysiological determination and antioxidant defences as a response to
environmental pollution, in addition to evaluating the effect of oxidized fat and selenium
on GR activity [
35
,
78
,
79
,
83
,
84
,
87
–
91
]. Oropesa et al. [
35
] reports that the GR activity in S9
of juvenile and adult storks (C. ciconia) is substantially lower (410 pmol min
−1
mg
PROT−1
and 380 pmol min
−1
mg
PROT−1
, respectively) than reported in this study for white stork
nestlings. This could be due to production of free radicals and depletion of antioxidant
defences, both related to aging and age-related diseases [
92
,
93
]. Considering that older
storks loose function to regulate physiological homeostasis and depletion of some blood
enzymatic antioxidants, as a consequence of aging [
94
–
96
], nestlings might be a more
suitable age group for biomonitoring assessments. As shown in Figure 4, higher GR activity
was found in S9 than plasma. That being said, GR is a cellular enzyme that accumulates in
cellular regions with high electron flux, resulting in high ROS production [97].
Animals 2021, 11, x 11 of 17
Figure 4. Specific activity of glutathione reductase (GR) in plasma and S9 (pmol min
–1
mg
PROT–1
) of
white stork (C. ciconia) nestlings (n = 16), presented as the mean ± SD. Statistical difference is indi-
cated with **** (Welch’s t-test, p < 0.0001).
Measuring oxidative stress parameters in blood has certain restrictions, e.g., field-
work limitations and small sample volumes. Our work demonstrates that oxidative stress
biomarker measurements could be performed by using either plasma or S9 if there is lim-
itation of the sample volume. When interpreting the results, it is also important to take
into account that oxidative stress might not originate in the circulation system but in other
tissue; therefore, it is necessary to analyse several biomarkers in different matrices for a
broad view of the physiological condition. For this purpose, we evaluated GST and GR in
two blood fractions, giving insight into their activity in plasma and S9.
3.3. Fluorescent Dyes
The fluorescence-based assay for GSH detection has been successfully established in
avian plasma and S9, confirmed by a positive control in which a substrate (GSH) was
added resulting in 17 times higher fluorescence detection in the positive control than the
blanks for plasma, and 19 times higher fluorescence detection in the positive control than
blanks in S9. Furthermore, the fluorescence-based assay for ROS detection was also suc-
cessfully established in avian plasma and S9, confirmed by a positive control in which a
substrate (H
2
O
2
) was added, resulting in 12 times higher fluorescence detection in the pos-
itive control than blanks for plasma, and 3 times higher fluorescence detection in the pos-
itive control than blanks in S9.
CellTracker
TM
Green CMFDA dye was used for GSH detection. Different sample con-
centrations and measurement times were tested, and the final values used are based on a
linear fluorescence increase and R
2
≥ 0.95 (Figure S6). Increase in fluorescence (RFU) was
observed in plasma for 60 min. Fluorescence (RFU) in S9 was measured for 120 min, and
an optimal linear increase was observed in the first 30 min, after which GSH saturation
was observed, resulting in a stagnation line.
The results of fluorescent GSH detection in plasma and S9 for 30 min are shown in
Figure 5. Significantly higher GSH fluorescence was reported in S9 than in plasma (p <
0.0001). When comparing the variability between responses in these two types of samples,
it can be observed that lower variability was observed in plasma compared to S9 (Table
1). Until now, the CellTracker
TM
Green CMFDA dye for GSH detection was not used in
avian blood. However, it was used in zebrafish (Danio rerio) embryo and larvae, as well as
mouse (Mus musculus) embryonic fibroblasts for the purpose of assessing cytotoxicity,
Figure 4.
Specific activity of glutathione reductase (GR) in plasma and S9 (pmol min
−1
mg
PROT−1
)
of white stork (C. ciconia) nestlings (n= 16), presented as the mean
±
SD. Statistical difference is
indicated with **** (Welch’s t-test, p< 0.0001).
Measuring oxidative stress parameters in blood has certain restrictions, e.g., fieldwork
limitations and small sample volumes. Our work demonstrates that oxidative stress
biomarker measurements could be performed by using either plasma or S9 if there is
limitation of the sample volume. When interpreting the results, it is also important to take
into account that oxidative stress might not originate in the circulation system but in other
tissue; therefore, it is necessary to analyse several biomarkers in different matrices for a
broad view of the physiological condition. For this purpose, we evaluated GST and GR in
two blood fractions, giving insight into their activity in plasma and S9.
3.3. Fluorescent Dyes
The fluorescence-based assay for GSH detection has been successfully established
in avian plasma and S9, confirmed by a positive control in which a substrate (GSH) was
added resulting in 17 times higher fluorescence detection in the positive control than
the blanks for plasma, and 19 times higher fluorescence detection in the positive control
than blanks in S9. Furthermore, the fluorescence-based assay for ROS detection was also
successfully established in avian plasma and S9, confirmed by a positive control in which
a substrate (H
2
O
2
) was added, resulting in 12 times higher fluorescence detection in the
positive control than blanks for plasma, and 3 times higher fluorescence detection in the
positive control than blanks in S9.
Animals 2021,11, 2341 11 of 17
CellTracker
TM
Green CMFDA dye was used for GSH detection. Different sample
concentrations and measurement times were tested, and the final values used are based on
a linear fluorescence increase and R
2≥
0.95 (Figure S6). Increase in fluorescence (RFU) was
observed in plasma for 60 min. Fluorescence (RFU) in S9 was measured for 120 min, and
an optimal linear increase was observed in the first 30 min, after which GSH saturation
was observed, resulting in a stagnation line.
The results of fluorescent GSH detection in plasma and S9 for 30 min are shown
in Figure 5. Significantly higher GSH fluorescence was reported in S9 than in plasma
(p< 0.0001). When comparing the variability between responses in these two types of
samples, it can be observed that lower variability was observed in plasma compared to S9
(Table 1). Until now, the CellTracker
TM
Green CMFDA dye for GSH detection was not used
in avian blood. However, it was used in zebrafish (Danio rerio) embryo and larvae, as well
as mouse (Mus musculus) embryonic fibroblasts for the purpose of assessing cytotoxicity,
apoptosis, and oxidative stress caused by pesticides and silver nanoparticles [
41
,
98
,
99
].
Higher GSH detection was observed in S9, as shown in Figure 5. As S9 contains cellular
and subcellular fractions, it was rich with GSH. Most of the GSH is found in the cytoplasm,
mitochondria, nucleus, and peroxisomes [
100
]. Extracellular concentrations of GSH are
low [
101
,
102
], as shown in Figure 5. In case of smaller sample sizes, usage of plasma for
GSH detection is recommended due to the observed lower variability.
Animals 2021, 11, x 12 of 17
apoptosis, and oxidative stress caused by pesticides and silver nanoparticles [41,98,99].
Higher GSH detection was observed in S9, as shown in Figure 5. As S9 contains cellular
and subcellular fractions, it was rich with GSH. Most of the GSH is found in the cytoplasm,
mitochondria, nucleus, and peroxisomes [100]. Extracellular concentrations of GSH are
low [101,102], as shown in Figure 5. In case of smaller sample sizes, usage of plasma for
GSH detection is recommended due to the observed lower variability.
Figure 5. Relative fluorescence (RFU) of reduced glutathione (GSH) in plasma and S9 of white stork
(C. ciconia) nestlings (n = 16), presented as the mean ± SD. Statistical difference is indicated with ****
(Welch’s t-test, p < 0.0001).
CM-H
2
DCFDA dye was used for ROS detection. Different sample concentrations and
measurement times were tested, and the final values used were determined based on a
linear fluorescence increase and R
2
≥ 0.95 (Figure S7). An increase in fluorescence (RFU)
was observed in plasma and S9 for 30- and 120-min time periods, respectively. For plasma,
an optimal linear increase was observed for 10 min, after which ROS saturation was ob-
served. In the S9 samples, a linear increase was observed for 120 min.
The results of using a fluorescent dye for measuring ROS detection in plasma and S9
for 10 min are shown in Figure 6. Significantly higher ROS fluorescence was reported in
plasma than in S9 (p < 0.0001). Lower variability among samples was observed in plasma
than S9 (Table 1). Until now, CM-H
2
DCFDA dye was not used in avian blood for ROS
detection. However, it was used in zebrafish (D. rerio) for the purpose of detecting oxida-
tive stress induced by pesticide exposures [41,99]. Avian erythrocytes have functional mi-
tochondria in terms of ROS production and respiratory activity [103]. Higher ROS detec-
tion was observed in plasma compared to S9, as shown in Figure 6. This may be due to
extracellular ROS production, induced by external sources (e.g., drugs, pollutants, and
radiation) [104]. In case of small sample sizes, using plasma for ROS detection is recom-
mended due to the observed lower variability.
Figure 5.
Relative fluorescence (RFU) of reduced glutathione (GSH) in plasma and S9 of white stork
(C. ciconia) nestlings (n= 16), presented as the mean
±
SD. Statistical difference is indicated with
**** (Welch’s t-test, p< 0.0001).
CM-H
2
DCFDA dye was used for ROS detection. Different sample concentrations
and measurement times were tested, and the final values used were determined based
on a linear fluorescence increase and R
2≥
0.95 (Figure S7). An increase in fluorescence
(RFU) was observed in plasma and S9 for 30- and 120-min time periods, respectively. For
plasma, an optimal linear increase was observed for 10 min, after which ROS saturation
was observed. In the S9 samples, a linear increase was observed for 120 min.
The results of using a fluorescent dye for measuring ROS detection in plasma and
S9 for 10 min are shown in Figure 6. Significantly higher ROS fluorescence was reported
in plasma than in S9 (p< 0.0001). Lower variability among samples was observed in
plasma than S9 (Table 1). Until now, CM-H
2
DCFDA dye was not used in avian blood for
ROS detection. However, it was used in zebrafish (D. rerio) for the purpose of detecting
oxidative stress induced by pesticide exposures [
41
,
99
]. Avian erythrocytes have functional
mitochondria in terms of ROS production and respiratory activity [
103
]. Higher ROS
Animals 2021,11, 2341 12 of 17
detection was observed in plasma compared to S9, as shown in Figure 6. This may be
due to extracellular ROS production, induced by external sources (e.g., drugs, pollutants,
and radiation) [
104
]. In case of small sample sizes, using plasma for ROS detection is
recommended due to the observed lower variability.
Animals 2021, 11, x 13 of 17
Figure 6. Relative fluorescence (RFU) of the reactive oxygen species (ROS) in plasma and S9 of white
stork (C. ciconia) nestlings (n = 16), presented as the mean ± SD. Statistical difference is indicated
with **** (Welch’s t-test, p < 0.0001).
Fluorescence-based oxidative stress detection in blood is a simple, non-destructive
method for ROS and GSH detection. Fluorescent detection of GSH and ROS production
have never been reported in white stork nestlings. Moreover, to the best of our knowledge,
the fluorescent dyes CellTracker
TM
Green CMFDA and CM-H
2
DCFDA have not been used
in avian blood before. However, fluorescent dyes have been successfully used in other
model organisms for the purpose of evaluating pesticide exposure and oxidative stress
response [41,99]. Fluorescent dyes for GSH and ROS can be used in both plasma and S9
of white stork nestlings for the purpose of evaluating oxidative stress.
4. Conclusions
The blood sampling of white stork nestlings is a non-destructive method that can be
easily obtained when performed in parallel with ringing. The present study successfully
used enzymatic (AChE, CES, GR, and GST) and non-enzymatic (GSH and ROS) bi-
omarkers for determining the basal values in white stork chicks. Fluorescent-based assays,
as a novel method for oxidative stress detection in birds, were developed in this study. To
get better overall insight into oxidative stress, using enzymatic antioxidants and fluores-
cence-based oxidative stress detection in two blood fractions will give a better overview
of a nestling’s physiological condition. The established protocols can be expanded to other
avian species as well. Assessment of the relationship between the biomarkers in the two
blood fractions is paramount in order to understand the usefulness of both plasma and S9.
This research indicated valuable differences in enzyme activity and oxidative stress detec-
tion with fluorescent-based probes for the first time in plasma and S9. Responses for each
biomarker in the two blood fractions provide useful information in case of a small sample
volume as well as providing overall information about physiological condition. Therefore,
we conclude that both plasma and S9 can be used for biomarker analysis.
Supplementary Materials: The following are available online at www.mdpi.com/xxx/s1, Table S1.
DNA concentration; Figure S1. Sex determination results; Figure S2. AChE absorbance; Figure S3.
CES absorbance; Figure S4. GST absorbance; Figure S5. GR absorbance; Figure S6. CellTracker
TM
Green CMFDA dye for GSH detection; Figure S7. CM-H
2
DCFDA dye for ROS detection.
Author Contributions: Conceptualization: D.B., A.M., and M.V.; investigations: D.B., A.M., C.L.,
L.B., and T.M.; data analysis and curation: D.B., A.M., and M.V.; writing: D.B. and A.M.; review and
Figure 6.
Relative fluorescence (RFU) of the reactive oxygen species (ROS) in plasma and S9 of white
stork (C. ciconia) nestlings (n= 16), presented as the mean
±
SD. Statistical difference is indicated
with **** (Welch’s t-test, p< 0.0001).
Fluorescence-based oxidative stress detection in blood is a simple, non-destructive
method for ROS and GSH detection. Fluorescent detection of GSH and ROS production
have never been reported in white stork nestlings. Moreover, to the best of our knowledge,
the fluorescent dyes CellTracker
TM
Green CMFDA and CM-H
2
DCFDA have not been used
in avian blood before. However, fluorescent dyes have been successfully used in other
model organisms for the purpose of evaluating pesticide exposure and oxidative stress
response [
41
,
99
]. Fluorescent dyes for GSH and ROS can be used in both plasma and S9 of
white stork nestlings for the purpose of evaluating oxidative stress.
4. Conclusions
The blood sampling of white stork nestlings is a non-destructive method that can be
easily obtained when performed in parallel with ringing. The present study successfully
used enzymatic (AChE, CES, GR, and GST) and non-enzymatic (GSH and ROS) biomarkers
for determining the basal values in white stork chicks. Fluorescent-based assays, as a
novel method for oxidative stress detection in birds, were developed in this study. To get
better overall insight into oxidative stress, using enzymatic antioxidants and fluorescence-
based oxidative stress detection in two blood fractions will give a better overview of a
nestling’s physiological condition. The established protocols can be expanded to other
avian species as well. Assessment of the relationship between the biomarkers in the two
blood fractions is paramount in order to understand the usefulness of both plasma and
S9. This research indicated valuable differences in enzyme activity and oxidative stress
detection with fluorescent-based probes for the first time in plasma and S9. Responses for
each biomarker in the two blood fractions provide useful information in case of a small
sample volume as well as providing overall information about physiological condition.
Therefore, we conclude that both plasma and S9 can be used for biomarker analysis.
Animals 2021,11, 2341 13 of 17
Supplementary Materials:
The following are available online at https://www.mdpi.com/article/10
.3390/ani11082341/s1, Table S1. DNA concentration; Figure S1. Sex determination results; Figure S2.
AChE absorbance; Figure S3. CES absorbance; Figure S4. GST absorbance; Figure S5. GR absorbance;
Figure S6. CellTracker
TM
Green CMFDA dye for GSH detection; Figure S7. CM-H
2
DCFDA dye for
ROS detection.
Author Contributions:
Conceptualization: D.B., A.M., and M.V.; investigations: D.B., A.M., C.L.,
L.B., and T.M.; data analysis and curation: D.B., A.M., and M.V.; writing: D.B. and A.M.; review and
editing: D.B., A.M., C.L., L.B., T.M., M.V. All authors have read and agreed to the published version
of the manuscript.
Funding:
This research was funded by Student Council of Josip Juraj Strossmayer University of Osijek
as part of a student project “Heavy metal bioaccumulation in white stork nestlings in Osijek-Baranja
county”. The Tecan Spark microplate reader was purchased with the Alexander von Humboldt
Foundation equipment grant awarded to Mirna Velki.
Institutional Review Board Statement:
Samples and data were collected according to Institute of Or-
nithology, Croatian Academy of Science, protocols, under the supervision of certified ringer/researcher.
Samples and data were collected as part of routine White Stork ringing and monitoring scheme
in Croatia. All procedures were conducted in accordance with the Croatian Nature Protection Act
(Official Gazette no. 80/13, 15/18 and 14/19) and approved by Croatian Ministry of Economy and
Sustainable Development (reference no: 517-05-1-1-20-4 from 27 August 2020). No extra animal
discomfort was caused for sample collection for the purpose of this study.
Data Availability Statement: All data was included in the manuscript.
Conflicts of Interest: The authors declare no conflict of interest.
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