Measuring circulating antioxidants in wild birds

Comparative Biochemistry and Physiology, Part B 147 (2007) 110 – 121 www.elsevier.com/locate/cbpb

Measuring circulating antioxidants in wild birds Alan Cohen a,⁎, Kirk Klasing b , Robert Ricklefs a a

Department of Biology, R223 Research Building, University of Missouri-St. Louis, 8001 Natural Bridge Rd., St. Louis, MO 63121-4499, USA b Department of Animal Science, University of California, Davis, CA, USA Received 10 September 2006; received in revised form 16 December 2006; accepted 31 December 2006 Available online 16 January 2007

Abstract Antioxidants protect against free radical damage, which is associated with various age-related pathologies. Antioxidants are also an important buffer against the respiratory burst of the immune system. This protection presumably has costs and therefore might underlie important life-history trade-offs. Studying such trade-offs in a comparative context requires field-applicable methods for assessing antioxidant capacity in wild animals. Here, we present modifications to a simple spectrophotometric assay (the TEAC or TAS assay) that can be applied to miniscule amounts of blood plasma to determine circulating antioxidant capacity. Additionally, uric acid, the most abundant circulating antioxidant, should be measured independently. Uric acid in birds is derived from amino acid catabolism, perhaps incidentally to its antioxidant function. The assay was validated in experimental studies on chickens showing effects of diet on antioxidant capacity, and in field measurements on 92 species of birds, which demonstrate substantial species differences in constitutive antioxidant capacity. Furthermore, most wild birds demonstrate a dramatic change in antioxidant capacity due to stress. These results show that this technique detects variation appropriate for both interspecific and intraspecific studies, and that antioxidants and uric acid change in response to conditions of interest to field ecologists, such as diet and stress. © 2007 Elsevier Inc. All rights reserved. Keywords: Antioxidant; Bird; Life-history; Physiology; Stress; TAS; TEAC; Uric acid

1. Introduction A major goal of physiological ecology has been to characterize physiological bases for life-history and behavioral traits (Wikelski and Ricklefs, 2001; Ricklefs and Wikelski, 2002). Measurements of hormones, metabolic rate, and immunity have become standard tools of field ecologists (e.g. Hau, 2001; Wikelski et al., 2003; Matson et al., 2006). One missing component of physiological ecology has been the measurement of antioxidant defenses, which would provide a measure of protection against free radicals. Although carotenoids, a type of antioxidant, have been looked at in the context of sexual selection and immune defense, overall studies of antioxidants in wild animals are basically non-existent (Surai et al., 2001; McGraw and Ardia, 2003; Blount, 2004). Free radicals, produced in tissue mitochondria during respiration or by the immune system to fight infectious agents, can damage ⁎ Corresponding author. Tel.: +39 346 524 7026; fax: +1 314 516 6033. E-mail address: [email protected] (A. Cohen). 1096-4959/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.cbpb.2006.12.015

tissues, eventually leading to cancer, atherosclerosis, and other pathologies (Graff et al., 1999). Extrinsic free radicals such as nitric oxide from pollution can also cause damage. Many aging researchers believe that free radical damage is a primary cause of the aging process (Harman, 1956; Barja et al., 1994; Beckman and Ames, 1998). Measuring free radical balance could indicate investment in future versus current reproduction: higher immediate metabolic investment might result in tissue damage, and better protection against damage is expected to be costly. Antioxidants are also involved in the immune system, possibly with multiple functions, including quenching free radicals produced during the respiratory burst used to lyse foreign cells (Konjufca et al., 2004; McGraw and Ardia, 2004). There are three important components to free radical balance: free radical production, antioxidant defenses, and repair mechanisms (Surai, 2002). Free radical production is hard to measure in field studies. In one method, mitochondria must be isolated from fresh tissue using a high-power centrifuge, which might alter free radical production as a result (Miwa et al., 2004). Another method, electron spin resonance

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spectroscopy, also requires tissue sampling (Garlick et al., 1987). Tissue sampling is generally impractical for nonterminal studies, especially in the field. Although the activity of repair enzymes can be measured, these enzymes are not present in plasma, and so their measurement requires terminal sampling or biopsy. Antioxidant capacity is also difficult to measure, but is the most feasible component for field studies. Although enzymatic antioxidants within mitochondria, such as superoxide dismutase and catalase, are the first line of defense (Godin and Garnett, 1992), antioxidant capacity in circulating blood can be readily assessed through spectrophotometric assays on plasma or serum. Circulating antioxidants are non-enzymatic, and include micromolecular components such as uric acid, vitamin E, vitamin C, and carotenoids, as well as proteins such as albumin that have some antioxidant function, though perhaps only incidentally so (Miller et al., 1993; Miller and Rice-Evans, 1996; Peters, 1996; Miller and Rice-Evans, 1997). Although circulating antioxidants might or might not correlate with enzymatic antioxidant levels in tissues, even circulating levels alone have been shown to be important in protection against atherosclerosis (Neuzil and Stocker, 1994; Woodford and Whitehead, 1998), and the non-enzymatic antioxidants are also known to have critical overall roles in physiology and perhaps aging (Lopez-Torres et al., 1993; Pérez-Campo et al., 1994). The two most relevant factors that can be measured in plasma or serum are antioxidant capacity, i.e., the ability of the sample to quench free radicals, and sustained damage, generally measured as lipid peroxidation levels. The latter is readily measured through an oft-used and oft-criticized method called TBARS (thiobarbituric acid-reactive substances) (Gaál et al., 1997). This may be a useful measure for field studies, but it has so far been used mostly in the context of aquatic toxicology (Hoffman, 2002; Torres et al., 2002; Oakes and Van Der Kraak, 2003; Almroth et al., 2005); since lipid peroxidation is not the focus of this study, it will not be discussed further here. Several assays measure antioxidant capacity, including TRAP, ORAC, FRAP, and TAS/TEAC (Wayner et al., 1985; Benzie and Strain, 1996; Ou et al., 2001). Each method has advantages and disadvantages. TAS (Total Antioxidant Status) is the commercially available version of TEAC (Troloxequivalent Antioxidant Capacity), also called TAC (Total Antioxidant Capacity). In this study we have modified the TEAC assay because the non-commercial version is inexpensive, quick, and as reliable as any of the assays available. The assay works by H2O2 activation of a blue-green chromogenic free radical. Antioxidants in the sample quench the radical, reverting it to its clear form. Measurement of light absorption at the appropriate wavelength over a specified period indicates the antioxidant capacity of the sample (Miller et al., 1993). This approach has the advantage that it is a functional measure rather than a measure of individual antioxidant concentrations. Some antioxidants such as vitamin C and uric acid are produced endogenously, while others such as vitamin E, carotenoids, and phenolics, are derived solely from the diet, though they may be modified endogenously (Surai, 2002). The

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concentrations of the various antioxidants (both relative and absolute) vary across individuals and species (AAC, unpublished data). It is not feasible to measure every antioxidant simultaneously, and even if it were, total antioxidant capacity is not additive because of synergistic and antagonistic interactions. For example, high levels of vitamin E in the absence of sufficient vitamin C or bilirubin can have a pro-oxidant effect (Neuzil and Stocker, 1994; Niki, 2004). Indeed, different antioxidants have different kinetics in the TEAC reaction, which makes calculation of antioxidant activity somewhat complicated and interpretation difficult (Schofield and Braganza, 1996). We circumvent this problem to some degree by changing the calculation method to exclude contributions of albumin and other proteins, isolating the effects of micromolecular antioxidants. Thus the assay we describe measures micromolecular antioxidant capacity of serum or plasma. In this study, we present modifications to the commercially available TEAC assay that both improve its interpretability and make it appropriate for field studies. Additionally, we present results from experimental studies on chickens examining the effects of immune stimulus and changes in diet on antioxidant capacity. Lastly, we present results from preliminary field studies showing that species do differ in antioxidant capacity and that antioxidant capacity often drops dramatically after stress induction. Implications of these results will be explored in subsequent publications; our purpose here is to demonstrate the usefulness of this technique. We also measure uric acid, an important and easily measured component of circulating antioxidants, accounting for as much as 90% of the variation in antioxidant capacity across samples in this study. Uric acid is the main form of nitrogen excretion in birds, produced by amino acid and purine catabolism, and is also present in reptiles, primates, Dalmatian dog and at lower levels in other mammals due to purine catabolism (Klasing, 1998; Kolmstetter and Ramsay, 2000; Waring et al., 2002). Uric acid may also be an indicator of stress (AAC, unpublished data). This confounds interpretation of antioxidant level because a high level of circulating antioxidants could be an indication of incidental amino acid catabolism rather than regulated antioxidant protection. To partition antioxidant activity into components due to uric acid and to other micromolecules, we measure uric acid simultaneously with antioxidant capacity using another spectrophotometric assay and statistically distinguish uric acid and non-uric acid contributions. We show that all three measures – uric acid level, total antioxidant level, and non-uric acid antioxidant level – correlate with variables of interest in experimental and wild birds. 2. Methods 2.1. Sample collection and storage We have successfully used both serum and plasma for this assay. Serum was initially preferred because the absence of clotting proteins was expected to provide a clearer measure and simplify interpretation, and because heparinized capillary tubes were not completely successful at preventing clotting. However,

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plasma is preferable in studies using small volumes of blood because the absence of clotting produces greater yield per volume whole blood and obviates practical issues with small, clotted samples. With serum, many samples were lost due to premature clotting or hemolysis. Equivalence of plasma and serum was assayed, and although no statistical difference was found across many samples, some individual samples that were subdivided into serum and plasma portions showed statistically significant differences (data not shown), so equivalence cannot be assumed. This is consistent with differences found in other metabolites (Hrubec et al., 2002; Miles et al., 2004). Both serum and plasma were used in components of this study, specified in each case. In general, our results tended to show greater statistical significance with serum, so we recommend using serum for studies allowing large-volume blood samples (> 1 ml). Practical difficulties make plasma much better for small-volume samples, and therefore also for studies that contain samples of various sizes. Samples must be collected within 5 min of capture to avoid stress effects on baseline measurements (see below). Whole blood is taken from birds through puncture of the brachial vein and collected in microcapillary tubes, heparinized for plasma or non-heparinized for serum. One full capillary tube yields ideally 30 μl serum or plasma, barely enough for the assays as described here (two assays in triplicate, 5 μl each). Blood is spun within 30 min of extraction to prevent hemolysis. A small centrifuge can be hooked to a car battery for use in the field if necessary. After spinning, serum or plasma is siphoned off using a Hamilton syringe or another microcapillary tube, kept on ice for up to a few hours, and then frozen as soon as possible at − 80 °C. Published guidelines for the TAS assay indicate that samples are only stable for 2 weeks at − 20 °C, so all samples described herein were stored at − 80 °C; however, experimentation with freeze–thaw cycles showed no change relative to fresh serum after four cycles, and samples stored for 2 years at − 20 °C showed no degradation of antioxidants relative to 1 year (data not shown). Considering that the assay only measures micromolecules, most of which should be more stable than proteins or DNA, we recommend keeping samples at − 20 °C as much as possible, but the more rigorous − 80 °C protocol is probably unnecessary and several freeze–thaw cycles are not expected to invalidate samples. 2.2. Experimental studies A series of controlled experiments on chickens (Gallus domesticus) was designed to measure the effects on serum antioxidant capacity of diet (by adjusting vitamin E and lutein levels), caloric stress (by adding cellulose to the diet), and immune response (by LPS [lipopolysaccharide] injections). LPS is a component of bacterial cell walls that induces systemic inflammation and the subsequent acute-phase response (Leshchinsky and Klasing, 2001). For all experiments except those on lutein effects (see below), broiler chicks (Cobb strain) were used. All birds were housed in standard wire cages with four to six birds per pen. Food and water were available ad libitum. Chicks were started

on a standard rice-based, vitamin E and carotenoid-free diet at 2 days of age (Koutsos et al., 2003a). Six chicks were maintained on this diet for the duration of the experiment. In order to restrict calorie intake, on day 4, six chicks were placed on the same diet supplemented with 40% cellulose. Because chicks eat as much as their gut can process to maximize growth rate, this was expected to reduce caloric intake by close to 40%. Indeed, the difference in weight was nearly significant after only 2 days (p = 0.07), and was highly significant (p = 0.0005) by the end of the experiment. We added 40 mg vitamin E/kg (the standard level for normal nutrition) to the diets of all remaining birds on day 7, except for the six control birds from the caloric restriction experiment and six birds with three times standard vitamin E (120 mg/kg diet) supplemented. Thus, three levels of vitamin E were available for analysis. Effects of LPS on antioxidant capacity were assessed using 32 birds fed the standard vitamin E diet. In the morning of day 14, 16 birds were subcutaneously injected with 1 ml of LPS at concentration 1 mg/ml. Since birds were approximately 400 g at this point, this was approximately 2.5 mg LPS/kg body mass, a relatively high dose (Leshchinsky and Klasing, 2001). Eight birds – four controls and four injected – were sampled at 2, 7, 12, and 24 h after injection. Blood was collected from all birds on day 14 by heart puncture. Blood for serum and plasma was divided between two microcentrifuge tubes, the latter with a drop of heparin to prevent clotting. Blood was spun for 10 min at 8000×g, and supernatant (plasma or serum) was removed and frozen at − 80 °C. Samples were analyzed on a VersaMax microplate reader (Molecular Devices, Sunnyvale, CA) with reagents and proportions from the commercial TAS kit (Randox Corp, Crumlin, UK) at one-quarter the specified volume, not with the reagents in the refined proportions specified below. In order to assess the effect of lutein in the diet, laying hens (housed individually in adjoining wire cages) were fed diets with two different levels of lutein. Adult birds were fed a standard rice/soy diet (Koutsos et al., 2003a) with 0 mg/kg or 40 mg/kg lutein (Oroglo Dry, Kemin Industries Inc, Des Moines, IA) from March 22, 2004, until blood was collected by wing venipuncture on October 13, 2004. Five birds on the lowlutein diet and four on the high-lutein diet were sampled by wing venipuncture. Previous work has shown that the birds with more lutein in the diet have more lutein in the blood stream (Koutsos et al., 2003a). 2.3. Preliminary field data Individuals of 92 bird species under 200 g were caught in mist nets and blood samples were taken through standard wing venipuncture and collection in un-heparinized microcapillary tubes. Species caught were mostly passerine (19 families represented, 14 oscine and 5 sub-oscine), but also included four dove species, Blue-crowned Motmots (Momotus momota), a Slaty-tailed Trogon (Trogon massena), a Long-tailed Hermit hummingbird (Phaethornis superciliosus), two woodpecker species, and a Killdeer (Charadrius vociferous). A full list is

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available in the online supplement. Samples were centrifuged in a Zip-spin portable centrifuge and serum was removed and kept on ice until it could be frozen at −80 °C (1 to 6 h). In order to assess potential effects of stress on antioxidant capacity, when possible, two samples were taken from each bird, the first immediately upon capture (i.e., within 5 min) and the second after the subject was held for 1 h in a cloth bag. Netting was conducted at several locations in and around Gamboa, Panama, in March 2004 and March 2005, and at Kellogg Biological Station near Kalamazoo, Michigan, in June and July 2004 and July 2005. The sample included 526 individuals. 2.4. Antioxidant measurement The TEAC assay was modified from Miller et al. (1993) (Table 1). Standard PBS buffer (Sigma) was used. Metmyoglobin was generated by mixing equal volumes of 400 μM myoglobin (from horse, Sigma) and 740 μM potassium ferricyanate, then passing the mixture through a column of sephadex (G15-120, Sigma). The metmyoglobin is stable for about 5 days at 4 °C. The chromogen, 2,2′-azinobis-(3ethylbenzothiazoline-6-sulphonic acid) (ABTS, Sigma), was mixed in buffer to 153 μM, and can be stored at 4 °C for up to a month. Standard was made by dissolving a water-soluble αtocopherol derivative, Trolox (Aldrich), in buffer to 1.7 mM, and can be frozen at − 20 °C for several months. The assay was run in 96-well flat-bottomed clear microplates on a VersaMax spectrophotometer (Molecular Devices, Sunnyvale, CA, USA). Temperature must be maintained at 37 °C, and readings were taken at 734 nm. Because it is critical to measure the duration of the reaction and this machine measures one column of wells at a time, only one 8-well column can be used from the plate at a time. 5 μl of sample were put in each of six wells, and 5 μl Trolox standard were put in the remaining two.

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Next, 10 μl metmyoglobin and 250 μl ABTS were added to each well. The plate was allowed to incubate for 5 min in the plate reader to bring reagents to 37 °C. A multi-channel pipette was used to simultaneously inject 50 μl of 75 mM H2O2 into the wells, starting the reaction. The concentration of the H2O2 can be adjusted to maximize detection of variation within a particular data set. Kinetic measurements using the spectrophotometer were started as soon as possible and taken at short intervals (i.e., 2 s); readings must be synchronized to the actual start of the reaction (i.e., injection of H2O2) manually using a timer. The reaction should run at least until the absorbance of all wells has started to plateau, generally around 10 m. The modified reagent proportions above were applied only to the field samples; chicken samples were run with the commercial kit (TAS, Randox Laboratories, Crumlin, UK) before development of this protocol. In all aspects except reagent proportions and origin, field and chicken samples were analyzed identically. The advantage of the modified reagent proportions is better detection across the wide range of values observed in wild birds, but values are not comparable across methodologies. 2.5. Calculation of antioxidant capacity The method for calculating TEAC values specified in the commercial kit is inadequate for most serum and plasma samples because it assumes that the sample kinetics are identical to those of the standard and blank; this is rarely the case for serum and plasma because blood proteins, especially albumin, exhibit antioxidant activity. The kinetics of a typical reaction run with the commercial kit are shown in Fig. 1. The blank, with no antioxidants, shows a linear increase in absorbance until a plateau is reached. The standard, with only a micromolecular antioxidant, shows a delay in the start of the reaction while the antioxidants quench newly formed free radicals, but then

Table 1 Differences in TEAC methodologies Miller et al. (1993)

Commercial TAS

This study

Reason for change

36 μL 70 μM metmyoglobin 300 μL 500 μM ABTS 489 μL of additional buffer

1 mL 6.1 μM metmyoglobin

10 μL 70 μM metmyoglobin

Accurate measurement across wide range of values

1 mL 610 μM ABTS Buffer included with ABTS, metmyoglobin 200 μL of 450 μM H2O2 20 μL sample/standard Spectrophotometer

250 μL 153 μM ABTS Buffer included with ABTS

Accurate measurement across wide range of values NA

50 μL of 75 mM H2O2 5 μL sample/standard Microplate reader

Not specified

Read at 600 nm 3-min reaction time Read only at 180 s Calculate TEAC from absorbance at fixed time-point 1 standard, 1 blank

Read at 734 nm >10-min reaction time Read at 2-s intervals Calculate TEAC from time to absorbance increase 2 standards, no blank

Accurate measurement across wide range of values Works with small sample volume Works with small sample volume, multiple samples simultaneously 734 nm is best absorbance maximum for ABTSU+ Measures values for high-TAC samples Kinetics important for understanding reaction Albumin effect problematic with TAS calculation

Not specified

Each sample run once

Each sample run twice

Not specified

Not specified

Measure uric acid, calculate residual

167 μL of 450 μM H2O2 8.4 μL sample/standard Spectrophotometer Read at 734 nm 12-min reaction time Read at 90-s intervals Not specified

Blank unnecessary with our calculation method; 2 standards improves accuracy Improves accuracy per unit sample volume, can detect aberrant reads UA accounts for much of TEAC, especially in birds, and must be controlled for

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Fig. 1. Kinetics of the TEAC antioxidant assay. Absorbance increases over time U as free radical (ABTS +) concentration increases. The delay in the start of increase in the serum and positive standard is attributable to micromolecular antioxidants, which are consumed in the reaction. The decline in rate of increase in the actual serum is attributable to albumin. The figure makes clear the difficulty of standardizing an assay with multiple kinetic components: at 180 s, the serum sample appears to have antioxidant capacity midway between the standard and the blank, but at 330 s the sample appears to have higher antioxidant capacity (lower absorbance) than the standard.

follows a parallel linear increase once the antioxidants are used. This can be attributed to the more-or-less immediate quenching of any newly formed free radicals by micromolecular antioxidants, which ceases upon exhaustion of antioxidants, allowing the reaction to proceed as in the blank from that time forward (Lightbody et al., 1998). Thus, the time until start of absorbance increase is a direct measure of micromolecular antioxidant capacity. The serum sample also shows this delay, but the increase in absorbance is only momentarily parallel to the blank and the standard before starting to plateau, apparently because sloweracting proteins such as albumin quench or inhibit formation of the free radical when its concentration increases. Spiking samples with albumin confirms that albumin concentration is proportional to the speed at which the absorbance plateaus, but does not affect time to initial increase in absorbance (Fig. 2). The commercial kit methodology for calculating TEAC is based on a comparison of a blank, standard, and sample at an arbitrary time after the start of the absorbance increase; however, because the standard and sample curves do not increase in parallel, the choice of this time point greatly affects the calculated antioxidant capacity. If the rate at which measurements reached a plateau were constant, a standardized time of measurement would be valid. However the rate at which measurements approach a plateau was found to vary widely among samples (probably dependent on albumin concentration). In fact, because some samples plateau more quickly than others, a sample that is lower than another when measured at 180 s can be higher when measured at 330 s (Fig. 1), so with the commercial kit method even the relative ranking of antioxidant level is highly dependent on reaction conditions and time of measurement. This problem is not just hypothetical; we were consistently experiencing it with actual samples.

To account for the different kinetics of different samples, we attempted to partition antioxidant capacity into micromolecular and albumin-like portions. Theoretically, this should be possible: a model that provides a good fit to the kinetics of actual samples can be parameterized to indicate the time until start of absorbance increase and rate at which the absorbance plateaus. Unfortunately, all the models we tried failed to yield a robust parameter for rate of approaching the plateau reading, and we therefore settled for measuring only the micromolecular component of antioxidants as indicated by time until onset of the increase in absorbance. It is simple to measure albumin concentration or total protein as an alternative, but we caution that the albumin-like kinetics may be attributable to various proteins, each with a different molar contribution to antioxidant function, so neither albumin nor total protein is expected to be an exact proxy for the unmeasured portion of antioxidant capacity. To calculate time to absorbance increase, we collected data in 2-s intervals and determined the time at which the difference between the current absorbance and the one 8 s earlier consistently began to exceed a specified threshold. This threshold is easily adjusted depending on the total amount of absorbance increase in the sample; we used 0.002 for most samples from the experimental data set and 0.001 for most samples from the field data set, due to differences in the reagents used. Slight variation here makes little difference; we recommend choosing one level and adjusting it only if it fails to agree with visual inspection of the absorbance curve. After calculating the point of absorbance increase, we calibrated samples against the average of the two standards run concomitantly using the formula TEAC ¼ Cs TTu =ðTs1 þ Ts2 Þ=2

ð1Þ

where Cs is the concentration of the standard, Tu is the time at increase of the unknown, and Ts1 and Ts2 are the times at

Fig. 2. Increasing albumin concentration lowers maximal absorbance in the TEAC assay. As concentration of albumin increases, there is no change in the time of start of absorbance increase, in contrast to the micromolecular standard. However, rate at which absorbance plateaus increase with increasing albumin levels, demonstrating the difference in kinetics between micromolecular and macromolecular antioxidants. The first 35 s of the 0.5 mM sample are omitted due to procedural abnormalities.

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Uric acid concentration was measured with a spectrophotometric kit based on uricase and a chromogen (Sterling Diagnostics, Sterling Heights, MI). The samples can be run alongside the antioxidant samples in the same microplate, and we found the assay to be simple, reliable, cost-effective, and repeatable. On field samples, serum hemolysis was visually assessed prior to analysis using a four-point scale for redness. Hemolysis was thought to be problematic because hemoglobin could interfere with absorbance readings and because enzymes released from the burst cells could affect assay kinetics. In particular, it was thought hemoglobin might bias uric acid readings upwards because the wavelength of hemoglobin absorbance (local maximum at 542 nm) interferes with the uric acid reading (520 nm). All samples were analyzed regardless of hemolysis level, and effect of hemolysis on antioxidant and uric acid measurements was assessed.

conducted in SAS v. 9.1 (SAS Institute). For the experimental data, singular effects of treatments on uric acid and antioxidant level were analyzed using t-tests where appropriate (PROC TTEST). ANCOVAs (PROC GLM) were used to determine whether treatments affected uric acid and TEAC measurements independently of each other. Methodological results (e.g., weight differences for calorically restricted birds and serum versus plasma differences) were calculated using PROC TTEST. For the field data, we used PROC GLM to assess whether differences among species, site and year were significant. We do not address here what characteristics of species explain variation in antioxidants (a large topic for later), but only whether or not species differ in antioxidant capacity and uric acid level. “Species” was thus used as a class variable. Additionally, PROC NESTED was used to partition the variance between species level and individual–within-species level. Presence of a large amount of variation at either level indicates that future studies conducted at that level may be productive. The stress response for both total antioxidant capacity (ΔTAC) and uric acid (ΔUA) was transformed to log (60 min/baseline). In order to assess whether degree or direction of stress response was associated with initial value, correlation between stress response and baseline was calculated using PROC CORR.

2.7. Data analysis

3. Results

For both antioxidants and uric acid, all samples were run in duplicate on separate plates. If the coefficient of variation between the two runs exceeded 0.15, the sample was run a third time when enough serum remained. In this case, coefficients of variation were calculated for each of the three pairs of runs. If the coefficient of variation between the two closest runs was less than half that of the next closest pair, the aberrant reading was discarded; otherwise all three readings were kept. Samples where the discrepancy among runs seemed particularly problematic were flagged, and subsequent analyses were run with and without these samples. After culling aberrant reads, average within-sample coefficient of variation was 0.069 for antioxidants and 0.051 for uric acid. First and second runs were compared to determine whether results were biased with respect to order. Data were found to be lognormal, so log transformations were used on all variables. In addition, a residual antioxidant value was calculated by using the FORECAST function in MS Excel to predict TEAC based on the uric acid value, given the other TEAC and uric acid values in the data set. The forecast value was then subtracted from the actual TEAC value to calculate the residual. The residual, while normally distributed in the middle of the distribution, tended to have extreme values at the tails that no transformation could account for. Accordingly, we used non-parametric statistics or rank values when dealing with this variable. Normality of data was assesses using Q–Q plots and the Shapiro–Wilk test in R, but all subsequent analyses were

3.1. Experimental studies

increase for the two standards. In general, there are strong run effects and also error in the standard, so it is important to run two standards with each run. Ideally, all samples should be run in duplicate on separate runs. 2.6. Uric acid measurement and hemolysis

Uric acid (UA) was always highly correlated (p < 0.0001) with antioxidant capacity (TAC). In chicken serum r = 0.70 and in chicken plasma r = 0.80. The residual (RES hereafter) was also correlated with TAC: in chicken serum r = 0.65 and in chicken plasma r = 0.63. Similar results were found in field samples (see below). Results of dietary treatments are summarized in Table 2. There was no effect of caloric restriction on either TAC (p = 0.51) or UA (p = 0.35) in serum when controlling for the effect of the other variable; similar results were obtained in a simple t-test (p = 0.51 and p = 0.34, respectively), and with plasma, showing that there is no effect on overall antioxidants, on uric acid alone, or on non-uric acid antioxidants. TAC and UA were each independently predicted by level of vitamin E in the diet. Both serum and plasma samples showed positive correlations between treatment and TAC (p = 0.0002 and p = 0.0056, respectively) and treatment and UA (p = 0.0008 and p = 0.0034, respectively). In serum, controlling for UA, TAC was associated with vitamin E level at p = 0.0005. Controlling for TAC, UA was associated with vitamin E level at p = 0.02. Interestingly, the independent associations with dietary vitamin E only held true for the serum samples; statistical tests on parallel plasma samples were insignificant (p = 0.89 and p = 0.57, respectively). Surprisingly, lutein supplementation produced a small but significant decrease rather than increase in TAC (p = 0.015 for plasma, p = 0.06 for serum) but not UA (p = 0.14 for plasma,

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Table 2 Means and standard errors of dietary treatments Lutein supplementation (laying hens)

Serum

Plasma

Treatment

Variable

Mean ± S.E.M. n Mean ± S.E.M. n

High carotenoid Low carotenoid High carotenoid Low carotenoid High carotenoid Low carotenoid

log TAC log TAC log UA log UA TAC–UA residual TAC–UA residual

−0.398 ± 0.039 −0.216 ± 0.067 0.658 ± 0.145 0.813 ± 0.072 −0.153 ± 0.102 −0.016 ± 0.034

4 5 4 5 4 5

− 0.538 ± 0.037 − 0.279 ± 0.067 0.618 ± 0.14 0.868 ± 0.043 − 0.181 ± 0.121 − 0.089 ± 0.044

4 5 4 5 4 5

Vitamin E supplementation (broiler chicks)

Serum

Treatment

Variable

Mean ± S.E.M. n Mean ± S.E.M. n

No vitamin E Normal vitamin E 3× vitamin E No vitamin E Normal vitamin E 3× vitamin E No vitamin E Normal vitamin E 3× vitamin E

log TAC log TAC log TAC log UA log UA log UA TAC–UA residual TAC–UA residual TAC–UA residual

−0.28 ± 0.041 −0.144 ± 0.015 −0.034 ± 0.04 0.737 ± 0.041 0.964 ± 0.03 1.021 ± 0.018 −0.038 ± 0.025 −0.078 ± 0.015 0.137 ± 0.087 Serum

Caloric restriction (broiler chicks) Treatment

Variable

Regular diet 40% fiber added Regular diet 40% fiber added Regular diet 40% fiber added

log TAC −0.28 ± 0.041 log TAC −0.208 ± 0.098 log UA 0.737 ± 0.041 log UA 0.827 ± 0.08 TAC–UA residual −0.038 ± 0.024 TAC–UA residual 0.022 ± 0.100

Plasma

6 7 6 6 7 6 6 7 6

− 0.278 ± 0.053 − 0.167 ± 0.049 − 0.075 ± 0.067 0.797 ± 0.061 0.913 ± 0.023 0.986 ± 0.045 − 0.030 ± 0.015 0.017 ± 0.044 0.094 ± 0.070

6 7 6 6 7 6 6 7 6

Plasma

Mean ± S.E.M. n Mean ± S.E.M. n 6 − 0.278 ± 0.053 5 0.218 ± 0.082 6 0.797 ± 0.061 5 0.853 ± 0.11 6 − 0.030 ± 0.015 5 − 0.024 ± 0.021

6 6 6 6 6 6

p = 0.37 for serum) as measured by a two-tailed t-test. This significance level fell below typical thresholds when uric acid was factored out of TAC with an ANCOVA (p = 0.14 for serum, p = 0.068 for plasma), but given the small sample size and loss of power in the ANCOVA it is still suggestive. The residual here showed no difference between treatments (p = 0.42 for serum, p = 0.9 for plasma with a Wilcoxon test) as would have been expected for a real difference in TAC but not UA. After Bonferroni corrections for four time points with both serum and plasma, LPS injection had no significant effect on TAC or UA at any time point. In serum only, for all time points pooled there was a nearly significant (p = 0.06) lowering of TAC, but not UA, with LPS injection. This was also true for TAC when covariation with UA was removed (p = 0.12), but this variation seems completely due to a difference in serum TAC at the 2-h time point, and given the lack of significance for this difference after Bonferroni corrections, the overall pattern should not be over-interpreted. 3.2. Field validation Simple correlations across all samples show a very weak relationship between hemolysis and TAC (r = 0.09, p = 0.02), UA (r = 0.17, p < 0.0001) and RES (r = − 0.15, p = 0.0001).

However, degree of hemolysis is associated with ease of the bleeding process, so associations are expected with species, stress (first bleed is cleaner), and perhaps site and year. Controlling for these variables, the significance of the TAC relationship completely disappeared (r = 0.004, p = 0.89), but the relationship with RES remained. The relationship with UA remained, with slightly less variance explained (r = 0.10, p < 0.0001). First runs of samples were significantly higher in a two-tailed paired t-test for TAC (p < 0.0001) but not UA (p = 0.81). The mean magnitude of the run order effect on TAC was small, 1% of the untransformed value and less than 0.1% of the total TAC variance in an ANOVA. Untransformed TAC ranged from 0.2 TEAC units (a Claycolored Thrush, Turdus grayii) to 8.14 TEAC units (a Blackcapped Chickadee, Parus atricapilla), and UA ranged from 0.93 mg/dl (a Crimson-backed Tanager, Ramphocelus dimidiatus) to 110.4 mg/dl (a Blue-winged Warbler, Vermivora pinus). Percent change in TAC after stress ranged from a 93% drop (a Thick-billed Euphonia, Euphonia laniirostris) to a 230% increase (an American Robin, Turdus migratorius). Change in UA in response to stress ranged from an 87% drop (a Northern Waterthrush, Seiurus noveboracensis) to a 632% increase (a Gray Catbird, Dumetella carolinensis). It should be noted that most of the birds showing very large percentage increases had very low initial values and thus low post-stress values as well; the post-stress UA value of the Gray Catbird, for example, was only 11.7 mg/dl, one-tenth that of the highest value recorded. These data are shown in the online supplement; stress response values there are in the normally distributed log(60 min/baseline) form rather than percentage change. Among the 526 individuals from 92 species caught in Michigan and Panama, TAC was significantly correlated with UA (r = 0.79, p < 0.0001). For 204 birds, pre- and post-stress TAC samples were available, and for 222 birds pre- and poststress UA samples were available. For both TAC and UA, a two-tailed paired t-test showed that levels fell significantly after stress (p < 0.0001 for both), and this result was robust for TAC controlling for UA with an ANCOVA (p = 0.0023). However, not all birds showed a drop. For TAC, 71% of the individuals showed some drop, and 59% showed a large drop (> 15%). Conversely, 22% showed an increase of > 15%. The numbers are similar for UA: 69%, 61%, and 24%, respectively. The distribution appears to be a single continuous distribution rather than two overlapping patterns (Fig. 3). The stress response in both TAC and UA shows a strong negative correlation with baseline TAC and UA, respectively (Fig. 4); in other words, birds with high baseline measurements usually show a big drop, and birds with low baseline measurements usually show an increase. Species differences in TAC, UA, RES, ΔTAC, and ΔUA as assessed by ANCOVA were all highly significant (p < 0.0001). For all variables, both species and individual level variation were significant in a nested analysis of variance, with neither falling below 23% in a nested analysis of variance. Additionally, TAC, UA, and RES but not ΔTAC or ΔUA showed a significant association with site (Michigan versus

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expensive; reagents can be purchased separately at a fraction of the cost and mixed following Miller et al. (1993). Because of differences in reagent concentrations, results from the commercial assay, the Miller method, and the method described above cannot be directly compared. All antioxidant assays of this sort have several weaknesses that should be taken into consideration when interpreting results. Most importantly, in field studies the assay will generally be applied only to serum or plasma; it is not known how this value correlates with tissue antioxidant capacity, and because tissue antioxidant protection is mostly enzymatic rather than micromolecular, results should be interpreted as reflecting only circulating antioxidants, though there is likely a correlation with some forms of protection in tissues. Attempts were made in this study to compare tissue and serum antioxidant capacity in chickens using this assay, but the kinetics of the tissue samples were like that of albumin except at very high concentration, suggesting that tissue antioxidant capacity is primarily macromolecular and making comparison with serum impossible. This fits with the highly enzymatic nature of tissue defenses, though micromolecular antioxidants are known to play an important role as well (Piercy et al., 2000; Dhanasekaran et al., 2004;

Fig. 3. Antioxidant and uric acid stress response distributions. For both antioxidants and uric acid, the stress of 1 h in a cloth bag causes levels to increase dramatically in some birds and drop dramatically in others. More birds show a drop than an increase, but there appears to be one continuous distribution rather than two distinct patterns. Panel b was truncated at a 400% increase to best show other variation.

Panama, controlling for year). These data are summarized in Table 3. 4. Discussion 4.1. Advantages and disadvantages of the TEAC assay The TEAC assay is one of several assays for measuring antioxidant capacity based on ability to quench a free radical. Each assay has advantages and disadvantages, and results are not always consistent across assays because each measures a slightly different phenomenon. No single assay is an ideal measure of antioxidants (Prior and Cao, 1999; Bohm, 2000; Frankel and Meyer, 2000; Del Rio et al., 2002; Bartosz, 2003). The TEAC assay is preferred in this case because it is quick and easy to learn, it can be performed with only a spectrophotometer or microplate reader, and it is available commercially. It is cautioned, however, that if the commercial assay is used, the above modifications should be followed, especially for calculation of final values. Also, the commercial assay is

Fig. 4. Antioxidant and uric acid stress response correlates negatively with baseline level. (a) Antioxidant capacity, mmol/L Trolox equivalents. (b) Uric acid, dg/mL.

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Table 3 Effects of species and site on antioxidant parameters Variable

Significance of species effect, controlling for site and year

Partitioning of variance among and within species, respectively

Significance of site effect controlling for year

Percentage of variance explained by site (Michigan vs. Panama)

Correlation with TAC (r, p)

Total antioxidant capacity (TAC) Uric acid level (UA) Non-uric acid antioxidants (RES) Antioxidant stress response (ΔTAC) Uric acid stress response (ΔUA)

p < 0.0001 p < 0.0001 p < 0.0001 p < 0.0001 p < 0.0001

59%/41% 59%/41% 23%/77% 29%/71% 35%/65%

p < 0.0001 p < 0.0001 p < 0.0001 p = 0.78 p = 0.55

39% 49% 19% 21% 27%

– 0.79, <0.0001 0.37, <0.0001 − 0.83, <0.0001 − 0.63, <0.0001

Rafique et al., 2004; Vatassery et al., 2004). α-Tocopherol does appear to correlate across tissues in rats, and to be present at greater concentration in plasma than other tissues (Kamzalov and Sohal, 2004). An additional caveat is that antioxidant capacity is measured with respect to a specific free radical (in this case ABTSU+); actual functionality may vary depending on the free radical challenge. This is a particular concern for enzymatic antioxidants, but its importance for micromolecular antioxidants is not known. Despite these caveats, the TEAC assay gives meaningful results. First, supplementation with vitamin E in chickens produces a higher TEAC value as expected. Second, TEAC correlates with some (but not all) clinically meaningful measures in humans, including breast cancer risk and protection against free radical damage following surgery (McColl et al., 1998; Ching et al., 2002). Third, there is a clear biochemical understanding of why circulating albumin and micromolecular antioxidants are important for overall health independent of tissue antioxidants: among other functions, they protect against oxidation of circulating lipids such as LDL, which can lead to atherosclerosis (Hahn and Subbiah, 1994; Godin et al., 1995; Niki, 2004). Fourth, the data presented here show that TEAC correlates with other physiologically or ecologically meaningful variables. Correlations among some physiological measures obtained from wild animals are difficult to interpret (Adamo, 2004); in the case of TEAC, the correlations are present, and the interpretation is clear but limited. That is, as long as TEAC is not regarded as a generalized measure for free radical balance in all tissues, it is a useful first step toward integrating free radical biology into physiological ecology. 4.2. Experimental results An increase in vitamin E in the diet of chickens produces an increase in TEAC levels relative to controls, indicating that diet can affect antioxidant capacity. Although this in not surprising and TEAC increased even when uric acid was controlled for, uric acid also increased, suggesting either that regulatory mechanisms account for a large part of the overall increase in TEAC or that increased oxidation of vitamin E protected uric acid from oxidation. This could be addressed by measuring levels of allantoin, the oxidation product of uric acid (Simoyi et al., 2003; Tsahar et al., 2006). Similar synergistic effects of carotenoid supplementation on other antioxidants have also been observed in wild passerines (Ewen et al., 2006). It is also worth noting that the variation in diet-induced TEAC is small

(treatment average range = − 0.27 to − 0.03 log Trolox equivalents) compared to cross-species differences (species average range = − 0.32 to 0.69 log Trolox equivalents for wild birds with more than three individuals caught). The chickens are also at the extreme low end of the distribution of wild birds. There are a number of reasons for this – chickens are much larger than any wild species we sampled, and have lower metabolic rates, different diets, less exercise, and have undergone generations of artificial selection. Surprisingly, dietary lutein supplementation decreased TEAC; since lutein is a carotenoid and carotenoids are generally considered antioxidants, a positive effect was expected. However, under certain conditions (high oxygen and low levels of other antioxidants), carotenoids have been shown to have pro-oxidant properties, and may also decrease levels of vitamin E (Surai, 2002). This result in particular deserves further investigation. Much of the sexual selection literature suggests that in birds, plumage coloration is an honest signal of individual quality, as reflected by carotenoid levels (Blount et al., 2003a; McGraw et al., 2003). Birds with higher carotenoids have been shown to have stronger immune function by several measures (Blount et al., 2003b; McGraw and Ardia, 2004), but if positive health effects of carotenoids are due to their antioxidant properties as proposed, a positive correlation should have been found here. Lutein is one of the more abundant carotenoids but is considered a weak antioxidant, and is the dietary supplement that has been used in much of the sexual selection literature. The lack of an effect of caloric restriction is not particularly surprising, because the chicks were growing and any difference in caloric intake was more likely apparent in changes in growth rate than metabolic rate; metabolic rate might have correlated with antioxidants, but growth rate would not necessarily have been. The data on LPS suggest that TEAC levels do not change dramatically with induction of acute-phase response. However, one might make two contradictory predictions about this: that the acute-phase response induced by LPS consumes (via respiratory burst) and/or redistributes antioxidants; or that the lower metabolic rate of sick birds might reduce antioxidant demand. Perhaps these two effects cancel each other, at least statistically, or perhaps the immune system contributes only modestly to overall oxidative balance. It is known that LPS induces acute phase response, which in turn lowers circulating carotenoid levels in chickens on high carotenoid diets (Koutsos et al., 2003b).

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4.3. Field data Hemolysis was shown to affect readings. We are not the first to note effects of hemolysis on physiological assays, including uric acid (Brady and O'Leary, 1998). This effect is not surprising, since release of cytosol into serum can affect any number of factors. Although the effect on antioxidant capacity appeared to be attributable to covariation with stress, species, and site, there was a consistent effect on uric acid readings and the TAC–UA residual. The direction of the effect on the TAC–UA residual was the opposite of that on uric acid, suggesting that any antioxidant effect reflects the balance between these two. The effects of hemolysis had previously been observed in a controlled experiment only for extremely hemolyzed samples, but the effect observed here in a much larger data set was robust even with the removal of the most extreme samples, though the magnitude weakened (data not shown). The effect is not large (r2 = 0.01 for UA), but hemolysis of samples should be minimized nonetheless, and if it appears problematic, data should be adjusted to account for hemolysis level. Additionally, first runs of samples produced slightly higher TAC than second readings. The average effect was highly significant but miniscule; the lack of an effect in UA suggests that there is some minor degradation of non-uric acid antioxidants over the 20 min or so between runs. There was no trend between second and third runs, so it would appear that any degradation occurs quickly. This effect is probably unavoidable; we followed a rigorous preservation protocol and avoided additional freeze–thaw cycles, and the improved accuracy with a second run outweighs any bias introduced. Samples from 92 species of wild birds revealed large interspecific differences in antioxidant and uric acid levels, an important result if the assay is to be used in comparative studies. Owing to their different avifaunas, site differences between Panama and Michigan are not separable from the different species compositions. There is also important variation within species, as evidenced by the chicken data above and other results not shown here, so the assay is valid for both intra- and inter-specific comparisons. In addition to variation in baseline antioxidant capacity, antioxidant capacity decreased following stress in some birds, often 40% or more within an hour. This implies either that antioxidants are being used up or that they are being shunted out of the bloodstream. The former would be possible if an increase in metabolic rate induced by stress resulted in a burst of free radicals; the latter would be possible if corticosterone released during the stress response caused antioxidants to be shunted to tissues in anticipation of a metabolic burst in a fight-or-flight response. The fact that the response occurs in both uric acid and non-uric acid antioxidants suggests that the process is related to antioxidant function rather to some incidental process affecting protein metabolism and uric acid; if so, we should see increases in allantoin after stress. Response of antioxidant levels to acute stress has been demonstrated for enzymatic antioxidants in rats following immobilization. Effects vary depending on tissue, enzyme, and experimental conditions. However, to our knowl-

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edge, this is the first demonstration in any species of a response to acute stress in circulating levels of micromolecular antioxidants (Liu et al., 1994; Oishi et al., 1999; Gümüslü et al., 2002). In fact, a recent study by Costantini et al. (in press) failed to find an effect of capture stress on a similar measure of antioxidant activity. However, timing relative to capture was different in that study, and individuals some individuals within the study showed large increases and decreases, despite the lack of an average effect. Future research will look at antioxidants and uric acid in relation to corticosterone levels, and will incorporate specific effects of vitamin E and carotenoids in relation to total antioxidant capacity and uric acid levels. Acknowledgements We thank the numerous laboratory and field assistants in the Klasing and Ricklefs labs, and Martin Wikelski and Michaela Hau and their labs. Thanks also to two anonymous reviewers for insightful comments. Research was supported by NSF IBN0212587. AAC is supported by a pre-doctoral fellowship from the Howard Hughes Medical Institute. References Adamo, S.A., 2004. How should behavioural ecologists interpret measurements of immunity? Anim. Behav. 68, 1443–1449. Almroth, B.C., Sturve, J., Berglund, A., Forlin, L., 2005. Oxidative damage in eelpout (Zoarces viviparus), measured as protein carbonyls and TBARS, as biomarkers. Aquat. Toxicol. (Amsterdam) 73, 171–180. Barja, G., Cadenas, S., Rojas, C., López-Torres, M., Pérez-Campo, R., 1994. A decrease of free radical production near critical targets as a cause of maximum longevity in animals. Comp. Biochem. Physiol. B 108, 501–512. Bartosz, G., 2003. Total antioxidant capacity. Adv. Clin. Chem. 37, 219–292. Beckman, K.B., Ames, B.N., 1998. The free radical theory of aging matures. Physiol. Rev. 78, 541–581. Benzie, I.F.F., Strain, J.J., 1996. The ferric reducing ability of plasma (FRAP) as a measure of “antioxidant power”: the FRAP assay. Anal. Biochem. 239, 70–76. Blount, J.D., 2004. Carotenoids and life-history evolution in animals. Arch. Biochem. Biophys. 430, 10–15. Blount, J.D., Metcalfe, N.B., Arnold, K.E., Surai, P.F., Devevey, G.L., Monaghan, P., 2003a. Neonatal nutrition, adult antioxidant defences, and sexual attractiveness in the zebra finch. Proc. R. Soc. Lond., B 270, 1691–1696. Blount, J.D., Metcalfe, N.B., Birkhead, T.R., Surai, P.F., 2003b. Carotenoid modulation of immune function and sexual attractiveness in zebra finches. Science 300, 125–127. Bohm, V., 2000. Measuring of antioxidative capacity – methods and assessment. Ernahrungs-Umschau 47, 372. Brady, J., O'Leary, N., 1998. Interference due to haemolysis in routine photometric analysis: a survey. Ann. Clin. Biochem. 35, 128–134. Ching, S., Ingram, D., Hahnel, R., Beilby, J., Rossi, E., 2002. Serum levels of micronutrients, antioxidants and total antioxidant status predict risk of breast cancer in a case control study. J. Nutr. 132, 303–306. Costantini, D., Cardinale, M., Carere, C., in press. Oxidative damage and antioxidant capacity in two migratory bird species at a stop-over site. Comparative Biochemistry and Physiology, Part C. doi:10.1016/j. cbpc.2006.11.005. Del Rio, D., Serafini, M., Pellegrini, N., 2002. Selected methodologies to assess oxidative/antioxidant status in vivo: a critical review. Nutr. Metab. Cardiovasc. Dis. 12, 343–351. Dhanasekaran, A., Kotamraju, S., Kalivendi, V., Matsunaga, T., Shang, T., Keszler, A., Joseph, J., Kalyanaraman, B., 2004. Supplementation of

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