TYPE Original Research PUBLISHED 06 March 2023 DOI 10.3389/fvets.2023.1089922 Tissue-specific assessment of OPEN ACCESS oxidative status: Wild boar as a case study EDITED BY Francesca Ciani, University of Naples Federico II, Italy REVIEWED BY Jiri Pikula, O. Alejandro Aleuy1† , Diana Gassó2† , Asta Tvarijonaviciute3 , University of Veterinary and Pharmaceutical Sciences Brno, Czechia David Risco4,5 , Waldo Garcia4 , Pilar Gonçalves4 , Richard Meitern, University of Tartu, Estonia Pedro Fernández-Llario4 , Gregorio Mentaberre2 , Roser Velarde6 , José Pérez, Emmanuel Serrano6* and Rafaela Cuenca6,7 Universidad de Córdoba, Spain 1 *CORRESPONDENCE Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, United States, 2 Wildlife Emmanuel Serrano Ecology and Health Group (WE&H), Departament de Ciència Animal, Escola Tècnica Superior d’Enginyeria emmanuel.serrano@uab.cat Agrària (ETSEA), Universitat de Lleida (UdL), Lleida, Spain, 3 Interdisciplinary Laboratory of Clinical Analysis (Interlab-UMU), Regional Campus of International Excellence “Campus Mare Nostrum”, University of Murcia, † These authors have contributed equally to this Murcia, Spain, 4 Innovación en Gestión y Conservación de Ungulados S.L., Cáceres, Spain, 5 Departamento de work Medicina Animal, Faculta de Veterinaria, Universidad de Extremadura, Cáceres, Spain, 6 Wildlife Health and Ecology Group (WE&H), Servei d’ Ecopatologia de Fauna Salvatge (SEFaS), Departament de Medicina i SPECIALTY SECTION Cirurgia Animals, Facultat de Veterinària, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, This article was submitted to Spain, 7 Servei d’Hematologia Clínica Veterinaria (SHCV) – Veterinary Clinical Hematology Service, Veterinary Experimental and Diagnostic Departament de Medicina i Cirurgia Animals, Facultat de Veterinària, Universitat Autònoma de Barcelona Pathology, (UAB), Bellaterra, Barcelona, Spain a section of the journal Frontiers in Veterinary Science RECEIVED 04 November 2022 In recent decades, there has been a fast-growing interest in using biomarkers ACCEPTED 30 January 2023 of oxidative stress (BOS) in conservation programs of many vertebrate species. PUBLISHED 06 March 2023 Biomarkers of oxidative stress can be measured in different biological samples (e.g., CITATION Aleuy OA, Gassó D, Tvarijonaviciute A, Risco D, body fluids and tissues). However, since comparisons of the same battery of BOS Garcia W, Gonçalves P, Fernández-Llario P, among tissues of the same individual are scarce in the literature, the chosen target Mentaberre G, Velarde R, Serrano E and tissues regularly rely on arbitrary decisions. Our research aimed to determine if Cuenca R (2023) Tissue-specific assessment of oxidative status: Wild boar as a case study. the oxidative status of free-ranging wild boar (Sus scrofa) naturally infected with Front. Vet. Sci. 10:1089922. Mycobacterium spp (etiological agent of tuberculosis, TB), varies depending on the doi: 10.3389/fvets.2023.1089922 sample where it was quantified. We compared antioxidant p-nitrophenyl esterase COPYRIGHT activity (EA), glutathione peroxidase (GPX) concentrations, and total oxidative status © 2023 Aleuy, Gassó, Tvarijonaviciute, Risco, (TOS) in serum, lung, spleen, kidney, and muscle of 63 wild boar hunter-harvested in Garcia, Gonçalves, Fernández-Llario, Mentaberre, Velarde, Serrano and Cuenca. This central Spain. Biomarkers of oxidative stress in serum had higher concentrations than is an open-access article distributed under the in other tissues. The poor agreement between serum and other tissues highlights the terms of the Creative Commons Attribution importance of running complete BOS assessments in the same fluid or tissue. Further, License (CC BY). The use, distribution or reproduction in other forums is permitted, low concentrations of BOS in tissues of TB-affected individuals were observed, and provided the original author(s) and the significant differences between healthy and sick boar were only detected in the serum copyright owner(s) are credited and that the of individuals developing mild TB and in the muscle of individuals with mild or severe original publication in this journal is cited, in accordance with accepted academic practice. disease status. However, all organs from wild boars affected with mild TB were not No use, distribution or reproduction is in oxidative imbalance compared to healthy control animals, suggesting that wild permitted which does not comply with these boars may cope well with TB. Our data indicate that serum and other tissues can be terms. used as BOS in field conservation programs to monitor wildlife population health. Still, context-specific validations are needed to determine the most appropriate samples to use. KEYWORDS glutathione peroxidase, Mycobacterium tuberculosis, physiological ecology, p-nitrophenyl esterase activity, Sus scrofa, oxidative stress 1. Introduction The loss of biodiversity due to anthropogenic disturbances like habitat loss, fragmentation, emerging infectious diseases, and climate change is one of the most critical environmental challenges affecting our planet (1). Assessing the physiological response of animals to these environmental disruptions is an essential component of management, monitoring, and Frontiers in Veterinary Science 01 frontiersin.org Aleuy et al. 10.3389/fvets.2023.1089922 GRAPHICAL ABSTRACT This drawing represents the concept of oxidative stress resulting from an imbalance arising as a consequence of the rate of production of reactive oxygen species exceeding the capacity of the antioxidant defence and repair mechanisms. Oxidative stress then leads to subsequent oxidative damage to biomolecules, tissue dysfunction and disease. Our work is intended to explore how the choice of a biological sample (e.g., muscle, serum, organs) influences oxidative status assessment in wild boar naturally infected with tuberculosis. conservation programs in wildlife populations [e.g., (2)]. Biomarkers to samples), and the clinical relevance in the selected subjects like stress hormones (glucocorticoids) (3) and immune response (24). Unfortunately, very little information is available to inform indicators (4) have regularly been used for this objective, achieving these decisions, specifically about the agreement between BOS results with different degrees of robustness [see this review measurements obtained from different tissues (25, 26). Consequently, Kalliokoski et al. (5)]. In recent years, there has been a growing there is a growing need for experimental and observational studies interest in incorporating oxidative stress biomarkers (BOS) to assess to evaluate the suitability of specific BOS and biological samples the physiological response of wildlife to environmental disturbances to assess vertebrates’ oxidant and antioxidant status. These studies due to their stability and easy quantification (6, 7). Oxidative stress are of significant importance when investigating animals facing (OS) is an imbalance between reactive oxygen species (ROS) and conservation issues due to reduced sample availability and in the case antioxidants in living systems. The ROS are unstable molecules (i.e., of animals infected with zoonotic pathogens, as biosafety measures free radicals) with potential to damage to cell structures, including need to be put in place before sampling occurs. lipids and membranes, proteins, and DNA (8). There is a rising body In this study, we investigated how BOS collected from various of research linking OS to reproduction (9), growth (10), survival (11), body tissues relates to OS in animals with different health statuses. To immune response (12), and particularly health/disease status (13–15). do this, we compared the concentrations of BOS, antioxidants, and Oxidative damage, and in consequence, OS, is generally higher the specific oxidative imbalance in serum, lung, spleen, kidney, and in cells, tissues, and organs suffering from inflammation or local muscle of wild boar (Sus scrofa) hunter-harvested from populations immune response [e.g., erythrocytes, (16); liver (17); intestines with endemic tuberculosis. The Graphical Abstract at the top of (18); kidneys (19) and lungs (20)]. This fact hampers sampling this page summarizes the aims of our work. Tuberculosis (TB) is opportunities for researchers working with live animals who prefer an infective zoonosis caused by Mycobacterium spp. This bacteria to collect sperm (7, 21) or blood serum (22) to avoid animal killing. produces chronic inflammation and systemic OS (27, 28), resulting in However, body fluids often fail to detect oxidative damage even lung fibrosis and dysfunction (27–29). Wild boar is the main reservoir in sick individuals (6, 23), making any attempt to monitor OS of TB in the Mediterranean basin (30), showing differential degrees of by non-invasive methods more complicated. Ideally, the choice of resistance to disease progression due to environmental factors (31), specific BOS and the biological samples to properly evaluate OS genetic characteristics (32), and concomitant infections (33). Boars should be determined on a system-specific basis, considering the can develop severe TB with gross lesions in lymph nodes (i.e., mild particular aims of the study, the experimental design (e.g., access TB) and the lungs, liver, and spleen (33). A more severe TB implies Frontiers in Veterinary Science 02 frontiersin.org Aleuy et al. 10.3389/fvets.2023.1089922 a more significant bacillary load (34) and lower survival probability samples were processed according to Renerre et al. (39). In (31). First, we compared BOS from different tissues and degrees of brief, tissue samples were homogenized in a 50 mM phosphate TB infection (i.e., negative, mild TB, severe TB). Then, we explored buffer, pH 7.0, and centrifuged at 1,000 g for 15 min at 4◦ C. whether BOS measurements are interchangeable among different The supernatant was transferred to Eppendorf tubes and used biological samples from the same individual. Finally, to define the for analyses. Highly hemolytic samples were identified by visual most reliable target tissue to assess OS caused by TB in wild boar, inspection and eliminated from the study due to their potential we compared BOS concentrations among different organs and the interference with the analytical methods (40). serum of diseased and healthy animals. Recent work has linked TB progression with OS in the serum of wild boar (35), but, as in most vertebrates, there is no previous information about the most reliable biological sample to assess OS in TB-infected animals. Likewise, no 2.3. Oxidative stress biomarkers analysis information exists regarding the oxidant-antioxidant imbalance in animals showing severe TB. We used the antioxidant p-nitrophenyl esterase activity (EA), glutathione peroxidase (GPX) concentrations, and total oxidative status (TOS) analysis to describe the overall picture of vertebrates’ 2. Materials and methods oxidant (TOS) and antioxidant (EA, GPX) balance. The EA (IU/mL) was analyzed by measuring the hydrolysis of p-nitrophenyl 2.1. Wild boar and study area acetate to p-nitrophenol as described elsewhere (41). The reaction was monitored at 405 nm. The non-enzymatic hydrolysis of A total of 63 wild boar (50 females and 13 males) aged from 5 phenylacetate, based on the hydrolysis rate in the absence of a sample, to 60 months were hunter-harvested in a private 2,000 ha hunting was subtracted from the total hydrolysis rate. The molar extinction state in Toledo (central Spain; 39◦ 55′ 15.55′′ N, 5 ◦ 10′ 32.33′′ E). coefficient used to calculate the rate of hydrolysis was 14,000 M−1 For each hunted animal, the objective was to cause the least animal cm−1 (41). When EA is measured in serum using this method, it welfare harm and the least impact in stress possible. This was done is named paraoxonase 1 (PON1, also in IU/ml) because, in serum, by attempting shoots that cause a short flight distance (i.e., the this enzyme has shown activity when p-nitrophenyl-acetate is used actual distance traveled by an animal from where it was initially as substrate (42). In other tissues, it is not well characterized yet; struck by the first bullet to where it fell recumbent, immobile, and thus, it is generally called EA. This enzyme has been considered in regarded as unconscious) and dead. The vegetation in this area is our study because it protects against bacterial infections and destroys a Mediterranean forest dominated by scattered holm oaks (Quercus oxidized lipids [wild boar stores large amounts of fat in tissues and ilex) and Mediterranean shrubs, primarily Cistus ladanifer, Erica spp., organs (37)]. and Genista anglica. Wild boar density in the study area was about The GPX (IU/L) was determined with a commercial kit (Randox 40 boars per 100 ha (unpublished data). Supplemental feeding (Jabalí Laboratories, UK). The method of GPX activity determination was Familia, Mercoguadiana, S.A., Spain) is regularly provided during based on the reaction by which GPX catalyzes glutathione oxidation summer when natural resources are scarce. Boars were legally hunted by cumene hydroperoxide. In the presence of glutathione reductase in their habitat by authorized hunters within the framework of an and NADPH, the oxidized glutathione was immediately converted annual hunting plan approved by the regional authority in charge of to the reduced form with concomitant oxidation of NADPH to livestock and wildlife management. No approvals were needed from NADP+, and the corresponding decrease in absorbance at 340 nm an animal ethic committee since the wild boars were not sacrificed for was measured. Previous work showed the changes in GPX due to M. research purposes. bovis infection in experimentally infected boars (35). The TOS (µmol/L) was measured as previously described by Erel (43), with some modifications (44). The method is based on 2.2. Tissue samples the reaction that the ferric ion makes a colored complex with xylenol orange in an acidic medium. The color intensity, measured After animal culling, sex was determined through a visual at 560 nm using 800 nm as the reference, is related to the total inspection of the genitalia area, while age was assessed by dental amount of oxidant molecules present in the sample. The assay was biometry (36). The positivity of wild boars to M. bovis was calibrated with hydrogen peroxide. The EA, GPX, and TOS analyses determined by microbiological cultures from intact submandibular were performed in an automatic analyzer (AU 600 automated or retropharyngeal lymph nodes and a piece of a caudal lung lobe biochemical analyzer, Olympus, Minneapolis, Minn) to minimize following the methods described in Gassó et al. (35). Animals were pipetting errors and execution time (44). The intra- and inter- classified into three groups: (i) TB-free boars (negative culture and no variation of coefficients among all the methods were below 15%, and signs of TB lesions), (ii) positive culture and localized gross lesions linearity under the dilution coefficient of variation was close to 1 in (mild TB), and (iii) positive culture and disseminated gross lesions all cases. (severe TB) (33, 37). In the present study, we decided not to correct tissue extracts Within the first 5 h after culling, blood, lung, spleen, kidney, for the total protein concentration of the sample. Such correction and muscle samples were collected, placed in cold boxes at 4◦ C, could result in situation-related bias (45) and additional expenses transported to the laboratory, and stored at −80◦ C. Blood was not necessarily contributing to accurate result interpretation. collected from the cavernous sinus (38) in plain tubes, and the Additionally, we performed a preliminary test with corrected and tubes were centrifugated at 3,500 rpm (1068 g) for 10 min to raw values of the BOS measured in lung tissues. We got identical obtain serum. Before analysis, lung, spleen, kidney, and muscle results to those shown throughout this work (the correlation Frontiers in Veterinary Science 03 frontiersin.org Aleuy et al. 10.3389/fvets.2023.1089922 FIGURE 1 Median and confidence intervals of the median (in brackets) concentrations of p-nitrophenyl esterase activity (EA, in IU/ml), paraoxonase 1 (PON1, in IU/ml) in serum, glutathione peroxidase (GPX, in IU/L), and TOS (total oxidative status, in µmol/L) measured in serum, lung, spleen, kidney and muscle from 63 wild boars hunter-harvested in Toledo, Central Spain. Different letters indicate significant differences in pairwise comparisons at alpha = 0.05. between corrected and raw pairs was over 0.8 in all cases, 3.2. Agreement between BOS measurements results not shown). There was a poor agreement among BOS measurements in boar serum and organs (Table 1). For example, the variation in the 2.4. Statistical analysis concentration of PON1 in serum differed between 118% in the lower range and 367% in the upper range compared to lung, spleen, kidney, Descriptive statistics (mean, standard deviation, minimum, and muscle. Similarly, GPX concentration in serum differed between and maximum) and Kruskal–Wallis tests were used to compare 80% in the lower range and 1182% in the upper range compared to EA/PON1, GPX, and TOS mean rank concentrations among other tissues. In line with the previous results, the upper and lower biological samples. The non-parametric statistic was used due to the limits of agreement for TOS concentrations were above 100%. The skewed distribution shown by our biomarkers. Later, a Bland–Altman large confidence intervals in all three tissues hamper any attempt at (BA) analysis was used to explore the agreement between enzyme an agreement with serum measurements. concentrations in the lung, spleen, kidney, muscle, and serum samples. This graphical method is the most popular for comparing two measurement techniques (46) using the representation of the 3.3. Effect of TB on BOS in different tissues mean differences (Y-axis) and magnitude of such measurements (X- axis). The limits of agreement (LoA) at 95% defined as the mean With very few exceptions (i.e., PON1 in serum or GPX in differences ± 1.96 x SD are also estimated and represented. Variables spleen), the BOS concentrations were low in tissues from TB-infected were log-transformed when differences were proportional to means individuals. Significant differences between healthy and diseased values (47). However, the BA plots do not distinguish between fixed boars were only detected in the serum and muscle of individuals and proportional bias (48). To control this, we explored plots of developing mild and severe TB disease status. In particular, p- differences between biomarker values, expressed as percentages of the nitrophenyl esterase activity (EA) in the muscle of healthy boar values on the Y-axis [e.g., (GPX in serum– GPX in Lungs)/mean%], was between 1.8 times to 2.7 times higher than in individuals vs. the mean of the two measurements. Finally, a t-test based on 1000 with mild (t = 2.41, p-value = 0.02) and severe (t = 3.7, p-value bootstrapped replications was used to compare the mean values of = 0.001) TB. Regarding GPX, statistically significant differences our BOS indicators between health and TB-affected boars (mild and between healthy and TB-affected individuals were only detected in severe TB). the muscle of severely affected boar (t = 3.41, p-value = 0.02). Finally, Bland-Altman analysis was performed in the “blandr” package statistically significant differences in TOS concentrations were only version 0.4.3 (49), whereas bootstrapping in the “boot” package observed in serum, particularly between healthy and mild TB-affected version 1.3–20 (50) of the R software 4.2.2 version (51). individuals (t = 2.92, p-value = 0.01). Mean and standard deviations of EA (PON1 in serum), GPX, and TOS concentrations in serum, 3. Results lung, spleen, kidney, and muscle from healthy and sick boars are summarized in Table 2. 3.1. Comparison of BOS values in different tissues 4. Discussion Among all the sample types, the highest concentration of GPX, PON1, and TOS was observed in boar serum. This difference was We investigated the most reliable biological sample to significantly higher in all the cases except when comparing TOS assess OS in TB-infected wild boar. The BOS concentrations in serum and lungs (p > 0.05, permutation test). The patterns of in serum were significantly higher than in other wild boar biomarkers concentration among different organs and serum were tissues such as lungs, spleen, kidney, or muscle. The poor specific for each biomarker (Figure 1). agreement between BOS measures in different samples difficult Frontiers in Veterinary Science 04 frontiersin.org Aleuy et al. 10.3389/fvets.2023.1089922 TABLE 1 Descriptive statistics for the Bland Altman analysis of selected oxidative stress biomarkers: p-nitrophenyl esterase activity (EA)/paraxonase 1 (PON1), glutathione peroxidase (GPX), and total oxidative status (TOS) simultaneously measured in serum, lung, spleen, kidney, and muscle from 63 wild boar hunter-harvested in Toledo, Central Spain. Analyte Sample pairs Parameter Unit (SD) 95% CI Antilog % EA/PON1 Serum-lung Mean differences (bias) 0.27 (0.24) (0.19–0.35) 1.86 – Upper limit 0.75 (0.61–0.89) 5.62 376 Lower limit −0.2 (−0.35 to 0.06) 0.63 123 Serum-spleen Mean differences (bias) 0.23 (0.26) (0.14–0.32) 1.7 – Upper limit 0.73 (0.58–0.88) 5.37 367 Lower limit −0.28 (−0.43 to 0.13) 0.52 118 Serum-kidney Mean differences (bias) 0.48 (0.27) (0.39–0.56) 3.02 – Upper limit 0.98 (0.83–1.13) 9.55 653 Lower limit −0.03 (−0.18 to 0.12) 0.93 209 Serum-muscle Mean differences (bias) 0.33 (0.32) (0.22–0.43) 2.14 – Upper limit 0.95 (0.76–1.13) 8.91 677 Lower limit −0.29 (−0.48 to 0.11) 0.51 163 GPX Serum-lung Mean differences (bias) 0.51 (0.27) (0.41–0.6) 3.24 – Upper limit 1.04 (0.88–1.2) 10.96 772 Lower limit −0.03 (−0.19 to 0.13) 0.93 231 Serum-spleen Mean differences (bias) 0.11 (0.21) (0.04–0.19) 1.29 – Upper limit 0.53 (0.41–0.66) 3.39 210 Lower limit −0.31 (−0.43 to 0.18) 0.49 80 Serum-kidney Mean differences (bias) 0.35 (0.3) (0.25–0.45) 2.24 – Upper limit 0.93 (0.76–1.11) 8.51 627 Lower limit −0.24 (−0.41 to 0.06) 0.58 166 Serum-muscle Mean differences (bias) 0.42 (0.38) (0.29–0.54) 2.63 – Upper limit 1.16 (0.94–1.38) 14.45 1182 Lower limit −0.33 (−0.55 to 0.11) 0.47 216 TOS Serum-lung Mean differences (bias) 2.19 (49.84) (−14.67 to 19.05) – – Upper limit 99.87 (70.78–128.96) – – Lower limit −95.49 (−124.58 to 66.41) – – Serum-spleen Mean differences (bias) 0.41 (0.28) (0.32–0.51) 2.57 – Upper limit 0.96 (0.8–1.12) 9.12 655 Lower limit −0.13 (−0.3 to 0.03) 0.74 183 Serum-kidney Mean differences (bias) 53.12 (35.74) (41.03–65.21) – – Upper limit 123.17 (102.31–144.02) – – Lower limit −16.92 (−37.78 to 3.94) – – Serum-muscle Mean differences (bias) 58 (35.12) (46.12–69.89) – – Upper limit 126.84 (106.34–147.34) – – Lower limit −10.84 (−31.34 to 9.66) – – Mean differences indicate the average differences of each analyte recorded in each pair of biological samples (e.g., serum-lung). In the case of total agreement, this value should be equal to zero, so a positive value indicates that on average, the analyte in the first biological sample (e.g., serum) measures 2.19 units (e.g., TOS) more than in the second (e.g., lung). The standard deviation (SD), and the upper and lower limits at 95% CI (Bias-1.96 SD and Bias +1.96 SD) have also been calculated. When differences were not normally distributed, the raw data was log-transformed and the antilog back-transformation is shown in the table. Upper and lower limits of the agreement have also been shown in %. the assessment of oxidative stress in the wild boar-TB systems. highlight the importance of refining our understanding of Only some tissues (e.g., TOS in serum and GPX or TOS in intraindividual differences in OS assessments, particularly, muscle) presented statistical differences in BOS concentrations when selecting appropriate samples for assessing specific animal between healthy and TB-affected individuals. These results populations’ stressors. Frontiers in Veterinary Science 05 frontiersin.org Aleuy et al. 10.3389/fvets.2023.1089922 TABLE 2 Mean ± standard deviation for PON1 (paraoxonase 1), EA (p-nitrophenyl esterase activity), GPX (glutathione peroxidase), and TOS (total oxidative serum) measured in serum, lung, spleen, kidney, and muscle from healthy and TB-infected (mild and severely affected) wild boar, hunter-harvested in central Spain. Biological sample Indicator Healthy Mild TB Severe TB Serum PON1 56.11 ± 23.81 60.6 ± 8.8 39.4 ± 13.4 GPX 2564.0 ± 1847.83 2547.4 ± 282.6 1393.6 ± 331.3 ∗ TOS 136.2 ± 36.1 69.2 ± 12.1 81.1 ± 58.9 Lungs EA 1.49 ± 0.11 1.43 ± 0.14 1.13 ± 0.31 GPX 339.34 ± 24.9 341.89 ± 33.21 302.66 ± 46.54 TOS 71.17 ± 11.41 68.49 ± 14.29 68.78 ± 26.93 Spleen EA 0.37 ± 0.02 0.36 ± 0.03 0.42 ± 0.04 GPX 1668.41 ± 134.05 1782.0 ± 191.23 1538 ± 252.31 TOS 23.12 ± 2.45 28.51 ± 3.67 30.51 ± 5.58 Kidney EA 4.51 ± 1.93 3.83 ± 1.67 5.24 ± 1.23 GPX 1036.60 ± 142.88 1126.85 ± 150.71 841.61 ± 145.21 TOS 12.41 ± 1.88 14.19 ± 3.13 12.8 ± 2.91 ∗ Muscle EA 0.41 ± 0.09 0.22 ± 0.01 0.15 ± 0.01 ∗ GPX 112.27 ± 14.54 91.37 ± 14.54 44.03 ± 11.62 ∗ TOS 8.24 ± 1.37 6.31 ± 1.22 4.85 ± 1.74 PON1, EA, and GPX have been measured in IU/L, and TOS in µmol/L. In all cases, we have used no hemolytic samples (n = 20 healthy, n = 16 mild-TB and n = 6 severe-TB). A t-test on 1000 bootstrapped replications has been used to compare the mean values of our ROS bioindicators between health and TB-affected boars. ∗ Indicates statistically significant differences at alpha = 0.05 after Bonferroni correction. Using OS biomarkers to evaluate chronic and acute stressors in a meta-analysis performed by Isaksson (60) to compare the in wildlife needs to consider potential quantitative intraindividual influence of sampling methods [i.e., invasive sampling (e.g., liver, differences among the biological samples collected. In our study, kidney, and lungs) and less-invasive sampling (blood and urine)] in the higher levels of TOS, EA/ PON1, and GPX observed in serum the OS of vertebrates and invertebrates exposed to environmental compared to other tissues might be the additive result of BOS activity pollution. Invasive sampling was more reliable in evaluating OS from different tissues transported and quantified in serum. More due to a smaller marker’s concentration variation than less-invasive specifically, the activity of GPX varies depending on intra-individual sampling. This result led to the hypothesis that in the case of characteristics like the tissues sampled (26, 52, 53), and time of contaminants and Eco toxicological studies, organs (e.g., the liver) sampling (54) and inter-individual factors like physiological status are likely to be a better source of BOS due to their direct role in and sex (54, 55). A similar intra- and inter-individual variation have detoxifying harmful metabolites and pollutants. Tuberculosis in wild also been described in the activity of PON1 (42, 56, 57) and a variety boar is characterized by causing a wide variety of pathophysiological of other BOS (24, 58). However, a higher BOS concentration in consequences, including non-specific inflammatory responses and serum or other specific tissue does not necessarily imply a better focalized gross lesions in lymph nodes, lungs, liver, mesenteric lymph sample for OS assessment. For instance, Gassó et al. (35) observed nodes, and spleen (33, 34). These multiple potential OS sources might that the variability of OS was correlated with disease status in boars influence the agreement among biological samples highlighting the experimentally infected with TB. In the same work, and in line with importance of context-specific consideration when assessing OS in our results, revealed that TB status was not the main factor explaining wildlife populations. This includes context-specific extrinsic factors the observed variability in OS biomarkers, probably because other like species and stressor stimulus and context-specific intrinsic factors intrinsic [e.g., co-infections (33)] and extrinsic factors (e.g., food like biological samples and the physiological mechanisms of the availability) may hide the TB effects. Our results highlight the need species of interest to deal with the stressor stimulus. for baseline experiments to confirm the association between specific Evidence of altered OS balance in wild boars infected with TB BOS and a stress source (e.g., disease) before their use as a proxy for was detected only in animals with mild disease presentation. This animal health (23). can be explained in part due to the ability of wild boars to cope The poor agreement between BOS observed in our study hampers with TB infection (62), supporting the role of wild boar as a TB the opportunity of interchange markers between sample origins reservoir in the Mediterranean basin (30), and by the specific role of when assessing OS in wildlife. Variations between conspecifics in OS during early stages of TB development in the host. An increase in BOS at the species and individual scales (e.g., sex, age) are well- OS is one of the main physiological mechanisms described in humans documented in different systems (59–61). However, intraindividual and rats to prevent the multiplication of Mycobacterium spp. and differences in BOS, like those observed in our study, have not TB-like gross lesions (63, 64). This mechanism is likely important received much attention despite their significant importance for in mild TB presentation, maintaining granulomatous lesions in a an adequate sampling plan. This problem was partially addressed latent form and directly increasing the OS imbalance. In addition, Frontiers in Veterinary Science 06 frontiersin.org Aleuy et al. 10.3389/fvets.2023.1089922 Gassó et al. (35) reported a similar difficulty detecting altered OS in of results: DG, AT, OA, RV, ES, RC, and GM. Drafted manuscript wild boar naturally infected with TB, hypothesizing that TB alone preparation: OA, DG, and ES. All authors reviewed the results and was not enough to trigger OS imbalance and that host intrinsic approved the final version of the manuscript. factors may also play an important role in OS levels. In this regard, special attention should be directed to the sex and age of the host as they have a direct influence on the immune and stress response of Funding mammals (59–61). ES is supported by the Spanish Ministerio de Ciencia Innovación y Universidades (MICINN) through a Ramon y Cajal agreement 5. Conclusions (RYC-2016-21120). GM is a Sierra Hunter Fellow. The BOS evaluated in this study were detected in higher concentrations in serum compared to samples from other tissues. Acknowledgments A poor agreement of BOS among samples was observed, making OS comparison among body fluids and tissue very difficult. In The authors would like to thank J.R.L.O and addition, organs from wild boars affected with mild TB (i.e., lung, members of INGULADOS for their assistance during wild spleen, kidney, muscle, and serum), were not in oxidative imbalance boar sampling. compared to healthy control animals. This suggests that wild boars may cope well with TB, developing an efficient antioxidant response to avoid OS. Our data indicate that more context-specific research on the association of BOS with stress factors like diseases is needed to Conflict of interest allow the use of these parameters in field conservation programs. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be Data availability statement construed as a potential conflict of interest. The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed Publisher’s note to the corresponding author/s. All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated Author contributions organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may Study conception and design: DG, ES, and RC. 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