Testing hypotheses about individual variation in plasma ... · At the time of blood collection, a small drop of blood was used to make a blood smear on a clean glass slide. Smears

RESEARCH ARTICLE

Testing hypotheses about individual variation in plasmacorticosterone in free-living salamandersJessica R. Thomas1, Andrew J. Magyan1, Peter E. Freeman2 and Sarah K. Woodley1,*

ABSTRACTIn vertebrates, many responses to stress as well as homeostaticmaintenance of basal metabolism are regulated by plasmaglucocorticoid hormones (GCs). Despite having crucial functions,levels of GCs are typically variable among individuals. We examinedthe contribution of several physiological factors to individual variation inplasma corticosterone (CORT) and the number of corticotropin-releasing hormone (CRH) neurons in the magnocellular preopticarea of the brain in free-living AlleghenyMountain dusky salamanders.We addressed three hypotheses: the current-condition hypothesis, thefacilitation hypothesis and the trade-off hypothesis. Differential whiteblood cell count was identified as a strong contributor to individualvariation in baseline CORT, stress-induced CORT and the number ofCRH neurons. In contrast, we found no relationship betweenCORT (orCRH) and body condition, energy stores or reproductive investment,providing no support for the current-condition hypothesis or the trade-off hypothesis involving reproduction. Because of the difficulties ofinterpreting the functional consequences of variation in differentialwhite blood cell counts, we were unable to distinguish between thefacilitation hypothesis or the trade-off hypothesis related to immunefunction. However, the strong association between differential whiteblood cell count and hypothalamic-pituitary–adrenal/interrenal (HPA/I)activation suggests that a more thorough examination of immuneprofiles is critical to understanding variation in HPA/I activation.

KEY WORDS: Amphibian, CRF, Glucocorticoid, Eco-immunology,Immune function, Leukocytes, Reproduction, Stress physiology

INTRODUCTIONAcross vertebrate taxa, activation of the hypothalamic-pituitary–adrenal/interrenal (HPA/I) axis leads to release of circulatingglucocorticoid (GC) hormones such as corticosterone (CORT). Inmost vertebrates, the HPA/I axis is activated by neural integration ofinternal and external stimuli that stimulates hypothalamic release ofcorticotropin-releasing hormone (CRH). CRH acts upon theanterior pituitary to release adrenocorticotropic hormone, whichin turn acts on the adrenal/interrenal gland to release GCs. Baselinecirculating levels of GCs are necessary for survival and have severalhomeostatic functions such as maintaining vascular tone and bloodglucose (Norris and Carr, 2013). The HPA/I axis is also activatedwhen encountering stressors and induces both behavioral andphysiological changes geared towards helping the animal avoid,

copewith or counter the original stressor (Sapolsky, 2002; Sapolskyet al., 2000).

Despite having many crucial roles, individual variation inactivation of the HPA/I axis is frequently observed. HPA/Iactivity fluctuates with both daily and life-history events likedevelopment, reproduction, migration, etc. (Breuner et al., 1999;Dallman et al., 1993; Kalsbeek et al., 2012; Landys et al., 2006;Thurmond et al., 1986). A review of GC concentrations in free-living vertebrates found that many species of amphibians, reptilesand birds seasonally modulate GC release, with both baseline andstress-induced levels being highest during times of breeding(Romero, 2002). Although far less studied than GCs in terms ofpatterns of variation, levels of CRH peptide are also variable (Crespiand Denver, 2005; Denver, 1996, 1997; Matsuda et al., 2010;Stengel and Tache, 2015).

There are many hypotheses for why the HPA/I axis, and, inparticular, GCs like CORT, is variable (Table 1). The hypothesescan be categorized as follows: the current-condition hypothesis(closely related to the fitness hypothesis), the facilitation hypothesis(also called the adaptation hypothesis) and the trade-off hypothesis(also called the energy re-allocation hypothesis) (reviewed inPatterson et al., 2014). Broadly, the current-condition hypothesisproposes that elevated baseline CORT levels are indicative of poorcondition that may translate into reduced performance or reducedfitness of either an individual or a population (Bonier et al., 2009a;Husak and Moore, 2008). This is supported by evidence fornegative correlations between baseline CORT and body condition/habitat quality in various birds and reptiles (Johnson, 2007; Mülleret al., 2007; Oppliger et al., 1998; Waye andMason, 2008;Williamset al., 2008). The facilitation hypothesis is based on the idea thatGCs such as CORT have a role in glucose metabolism at all times,not just during challenges (Moore and Jessop, 2003). In this way,fluctuations in baseline CORT are necessary to accommodate thechanging metabolic demands of various physiological processessuch as reproduction and immune function. For example, there isaccumulating evidence for positive relationships between GCs andsex steroid hormones, and GCs are elevated during breeding inmany species (Bonier et al., 2009a; Moore and Jessop, 2003; Mooreet al., 2000; Romero, 2002). Likewise, the HPA/I axis is intricatelylinked to the immune system and can both affect and be affected byimmune activity (Martin, 2009; Turnbull and Rivier, 1999; WebsterMarketon and Glaser, 2008). Thus, the facilitation hypothesispredicts that plasma CORT would be positively correlated withenergetically costly functions during non-challenging (baseline)times. Conversely, the relationship between CORT andenergetically costly functions that are not imperative to survivalmay shift to negative during times of stress, which is the basis for thetrade-off hypothesis, also sometimes called the re-allocationhypothesis (Almasi et al., 2013; Martin et al., 2012; McEwen andWingfield, 2003; Patterson et al., 2014; Wingfield and Sapolsky,2003). The trade-off hypothesis predicts that, during times of stress,Received 15 September 2016; Accepted 9 January 2017

1Department of Biological Sciences, Duquesne University, 600 Forbes Avenue,Pittsburgh, PA 15282, USA. 2Department of Statistics, Carnegie Mellon University,Pittsburgh, PA 15213, USA.

*Author for correspondence ([email protected])

S.K.W., 0000-0001-7877-6392

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plasma CORT levels are negatively correlated with functions likereproduction or immune processes that are both energetically costlyand not necessary for survival of the threat.Here, we tested predictions generated by the hypotheses for HPA/I

axis variation using data from free-living male and female AlleghenyMountain dusky salamanders (Desmognathus ochrophaeus)(Table 1). We included both sexes because the sexes often differin patterns of HPA/I activity (Astheimer et al., 1994; Grassman andHess, 1992a,b; Handa et al., 1994; Rhodes and Rubin, 1999;Tilbrook et al., 2000). These stream-side salamanders have strongseasonal cycles of reproductive activity, energy stores, bodycondition and plasma CORT (Fitzpatrick, 1973; Petranka, 2010;Ricciardella et al., 2010; Tilley and Tinkle, 1968). Specifically, weasked whether variation in physiological variables could explainpatterns of baseline CORT, stress-induced CORT and hypothalamicCRH neurons. We selected physiological variables known to beassociated with circulating GCs (Bonier et al., 2009a,b, 2011;Davis et al., 2008; Romero, 2002). We approximated reproductiveinvestment with gonad mass, corrected for body size. Weapproximated energy stores with abdominal fat body mass,corrected for body size. Finally, we approximated body conditionwith carcass mass, corrected for body size. To approximate immunefunction, we examined differential white blood cell counts. Therelative amounts of lymphocytes and neutrophils have been linked tocirculating CORT in many field and laboratory studies (Davis et al.,2008; Goessling et al., 2015). In general, increases in relative bloodneutrophil counts are interpreted as reflecting increased synthesis ofthese phagocytes in preparation for immune challenges. Likewise,decreases in relative lymphocyte counts are often interpreted asreflecting redistribution to the skin, sites of potential infection andinjury (Dhabhar et al., 1996). However, it should be noted thatdecreases could also reflect reduced cell synthesis or cell death,especially because laboratory studies have linkedGCs to lymphocyteapoptosis (Cidlowski et al., 1996).

MATERIALS AND METHODSAnimalsAll animal methods and procedures were approved by DuquesneUniversity’s Institutional Animal Care and Use Committee (1209-11). Collecting permits were obtained from the Pennsylvania Fishand Boat Commission. Allegheny Mountain dusky salamanders(Desmognathus ochrophaeus Cope 1859) are stream-sidesalamanders with a seasonal lifestyle, being active above groundfrom early spring to late autumn, and retreating underground duringthe winter. The mating season extends from autumn to spring withan interruption due to winter. Mating pauses in early summer,during which time females lay their eggs and brood their clutchesfor several months (Fitzpatrick, 1973; Petranka, 2010; Ricciardellaet al., 2010; Tilley and Tinkle, 1968).Adult male and female Allegheny Mountain dusky salamanders

were collected along Elk Rock Run in Fayette County, PA, USA

(39N°57′05.9″, 79W°34′43.4″). Collections took place acrossseveral months to acquire a multi-seasonal data set: spring(mating season) collection occurred from 15 to 30 May 2013;summer (non-mating season) collection occurred from 28 August to4 September 2013; and autumn (mating season) collection occurredfrom 30 September to 2 October 2013. Animals were collected byoverturning streamside rocks and logs and capturing animals byhand. Sexual maturity was verified by observing elongatedpremaxillary teeth in males and follicles (visible through the bodywall) in females. Initial sample sizes were approximately 10 animalsper sex per treatment (baseline versus 30 min after capture) for eachsampling season; however, final sample sizes varied as a result offactors such as insufficient plasma volume for measuring CORT,lost tissues, poor blood smear slide quality, poor brain tissuesectioning, etc. We chose a sample size of 10 animals per treatmentcombination based on a Monte Carlo simulation power analysis(Bolker, 2008) that indicated that samples sizes of 8–12 arenecessary to detect stress-induced increases in plasma CORT.

TreatmentAt each seasonal collection, we assessed baseline and stress-induced plasma CORT levels and the number of immunoreactiveCRH neurons in both males and females. For baseline CORT,animals were euthanized via decapitation and trunk blood(approximately 3–10 μl) was collected in a heparinized capillarytube within 3 min of capture. For stress-induced CORT, animalswere captured, individually placed in Ziploc bags, palpated for2 min, and contained in the Ziploc for 30 min. This method ofcapture and handling has been shown previously to increase plasmaCORT in Allegheny Mountain dusky salamanders (Woodley et al.,2014). Immediately afterwards, animals were euthanized viadecapitation and trunk blood was collected. Animals wereassigned to baseline or stress-induced treatments by alternatingbetween treatments in a sequential manner. All blood samples andcarcasses were kept on ice until they were processed in the lab,approximately 2–5 h later.

Hormone assaysTrunk blood was collected in heparinized capillary tubes andcentrifuged to collect plasma; plasma was frozen in heparinizedmicrocentrifuge tubes until being analyzed via radioimmunoassay(RIA). Plasma CORT was assayed at the Endocrine TechnologyServices Core at the Oregon National Primate Research Centerfollowing standard methods. Briefly, a double ether (100%Honeywell Burdick and Jackson, no. 107-4) extraction wasperformed on up to 3 μl of plasma, after which concentrations ofCORT were obtained via RIA using an anti-corticosterone antibody(ab77798 Abcam, 1:20,000 dilution, cross-reactivity withaldosterone is 0.06%). All samples were run in singlicate in asingle assay that had an intra-assay coefficient of variation of11.2%, a recovery of 86.4% and a sensitivity of 1.0 ng ml−1. The

Table 1. Summary of hypotheses and predictions for patterns of baseline and stress-induced corticosterone (CORT)

Hypothesis Explanation

Predictions

Baseline CORT Stress-induced CORT

Current condition CORT reflects health Negatively related to health (body condition) Positively related to health (body condition)Facilitation CORT primes/facilitates other systems Positively related to reproduction/immunity Positively related to reproduction/immunityTrade-off CORT allocates energy away from

reproduction/immunity toward survivalNegatively related to reproduction/immunity Negatively related to reproduction/immunity

Because release of corticotropin-releasing hormone (CRH) from the magnocellular preoptic area (mPOA) triggers increased plasma CORT, similar hypothesesand predictions explain patterns of variation in the number of CRH neurons.

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assay has been validated for Allegheny Mountain duskysalamanders by demonstrating parallelism from 0.5 to 4 μl at0.5 μl increments.

Leukocyte differentialsAt the time of blood collection, a small drop of blood was used tomake a blood smear on a clean glass slide. Smears were air-driedand stained using Wright–Giemsa stain (Polysciences, catalognumber 24985) as follows: 30 s methanol (100%) dip, 2 min inWright–Giemsa stain, rinse in phosphate buffer (pH 6.8,Polysciences, catalog number 24984), 4 min in Wright–Giemsa:buffer mixture, 2 min rinse in phosphate buffer. Slides were allowedto air dry completely before coverslipping with Permount. All slideswere observed using oil immersion (1000×) with a compound lightmicroscope. The investigator was blind to treatments. White bloodcell count differentials were determined according to standardmethods (Davis et al., 2008). Briefly, slides were incrementallyscanned in a zigzag pattern, and individual cell types (lymphocytes,neutrophils, monocytes, basophils and eosinophils) were tallieduntil a total of 100 white blood cells had been counted. Slides withpoor quality staining (grainy appearance or poorly delineated cells)were excluded from analyses prior to unblinding.

Tissue and carcass processingCarcasses were dissected to remove abdominal fat bodies. Both leftand right abdominal fat bodies were massed together on amicrogram balance. Carcasses were tagged and preserved with10% neutral buffered formalin for 24 h. Following a 24 h waterrinse, carcasses were stored in 70% ethanol. Gonads (testes orovaries) were later excised and weighed from each preservedcarcass. Also at this time, carcass mass (consisting primarily ofmuscle mass and gut, not including head, gonads and abdominal fatbodies) and length (forelimb to hindlimb) were recorded forcalculating body condition (see statistics below).

Brain processingImmediately following decapitation, the lower jaw was removedand each head (including the brain) was placed in a vial of freshlyprepared 4% paraformaldehyde to preserve the tissue. Vials wereagitated on a shaker overnight and then heads were rinsed withdistilled, deionized water for 24 h. Brains were dissected from theheads and placed in 15% sucrose in phosphate-buffered saline(PBS) for at least 24 h, or until they had sunk to the bottom of thevial. They were transferred into 30% sucrose in PBS for another24 h, followed by a final 24 h in a 1:1 solution of 30% sucrose andoptimal cutting temperature (OCT) compound (Tissue Tek, catalognumber 4583). Following cryoprotection, brains were embedded inOCT and snap-frozen using liquid nitrogen. Blocks were stored at−80°C until cryosectioning. Using a cryostat (InternationalEquipment Company Minotome, OM 2488), alternating coronalsections (26 μm) were collected in two series by thaw-mountingonto polylysine-coated Superfrost Plus slides. Slides were allowedto air dry before being stored at −80°C until immunohistochemicalanalysis for CRH.

CRH immunohistochemistryTo visualize cells that were immunoreactive for CRH, standardimmunohistochemistry was performed on one slide series using aprimary rabbit anti-human/rat CRH antibody (code no. PBL rC68from Dr Benedict Kolber, Duquesne University, originally from DrPaul Sawchenko, Salk Institute). At room temperature, slides werewashed in PBS containing 0.3% Triton X-100 (PBST), incubated in

PBS with 3.0% H2O2, and washed in PBST again. Slides wereincubated in a blocking solution of 5% non-fat dry milk in PBS for1 h. Incubation in primary antibody was conducted overnight at 4°Cwith slides lying flat in a humidified chamber. Antibody was firstreconstituted 1:50 in PBS to make a stock solution, and then dilutedan additional 1:1000 in PBS containing 5% non-fat dry milk and10% normal goat serum and applied directly to slides with amicropipette. Following incubation in primary antibody, slides werewashed in PBST before incubation in secondary antibody, whichconsisted of a 1:200 dilution of biotinylated goat anti-rabbit in PBScontaining 5% normal goat serum and 2% bovine serum albumin.Incubation occurred for 2 h at room temperature with slides lyingflat in a humidified chamber. Slides were then washed in PBSTbefore incubation in Vectastain Elite ABC (made according to kitinstructions, Vector Laboratories, catalog number PK-6100) for 1 h.Following a wash with PBS, slides were incubated in tyramidesignal amplification plus cyanine 3 (made according to kitinstructions, TSA Cy3, PerkinElmer, NEL744001KT) for 3 min.Following a final wash in PBS, slides were allowed to air dry beforecoverslipping with Prolong Gold antifade mountant with DAPI(ThermoFisher Scientific, catalog number P36931). Slides werestored at 4°C until viewed and photographed (no more than 1 weekpost-immunohistochemistry; see below).

We confirmed that the primary antibody was specific for CRHand not for related neuropeptides in Allegheny Mountain duskysalamanders by doing a preabsorption control. Briefly, the primaryCRH antibody was incubated overnight in a 50 μg ml−1 solution ofits immunogen, human/rat CRH (Sigma-Aldrich, CAS number86784-80-7). The preincubated primary antibody was then used forimmunohistochemistry on test slides containing sections fromanatomical regions where CRH immunoreactivity is known to bepresent. Adjacent slides were treated with CRH antibody that hadnot been preabsorbed with CRH. Preincubating the primary CRHantibody with its antigen (human/rat CRH) resulted in a loss offluorescence signal throughout the brain, observed in both fibers/puncta and cell bodies (Fig.1).

CRH analysisStained slides were viewed and photographed using a TRITC filteron an epifluorescence microscope at 200× magnification. Athorough examination of brain tissue sections was conducted withreference to a brain atlas for plethodontid salamanders (Labergeet al., 2008). Although immunoreactive fibers were broadlydistributed throughout the brain, most cells were observed in theventral preoptic area, the magnocellular preoptic area (mPOA) andthe locus coeruleus, with a small number of cells in the subpallialamygdala. While blind to treatment, neurons immunoreactive forCRH were counted. We limited our analyses to the mPOA CRHpopulation because it is the primary population of hypophysiotropicCRH neurons, homologous to the hypophysiotropic paraventricularnucleus in mammals (Fasolo et al., 1984; Tonon et al., 1986). Slideswith poor quality tissue and/or staining were excluded fromanalyses while blind to treatment.

IT-AIC modeling of HPA/I variationTo test the predictions generated by the hypotheses for variation inHPA/I activity (Table 1), we used information theory, specificallythe Akaike information criterion adjusted for small samples sizes(IT-AICc) (Burnham and Anderson, 2002, 2014; Symonds andMoussalli, 2011). IT-AIC is a statistical method based on linearregression that allows multiple models to be evaluated andcompared while avoiding over-fitting. Using R (https://www.r-

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project.org/), we modeled the response variables (baseline CORT,stress-induced CORT and the number of CRH neurons in themPOA) with predictor variables that reflect different physiologicalfunctions. We analyzed baseline and stress-induced CORTseparately because they were measured in separate animals, andthere are separate hypotheses and predictions for baseline versusstress-induced CORT. For CRH neurons, we pooled data frombaseline and stressed animals because there was no difference in thenumber of CRH neurons in baseline versus stress-induced samples(see Results). Note that only those subjects with complete data setscould be included in the modeling. Hence, sample sizes were 38 forbaseline CORT, 43 for stress-induced CORT and 66 for mPOACRH. To satisfy assumptions of the linear regression modelingapproach, CORT and mPOA CRH values were square roottransformed to achieve normality and homogeneous variance.To assess the impact of innate immune function on the response

variables, we used percentage lymphocyte (for baseline CORT,stress-induced CORT and CRH neurons) to reflect one aspect ofimmune function. We could not use both percentage lymphocyteand percentage neutrophil in our models because they co-vary, andcollinearity should be avoided for IT-AIC. We included percentagelymphocyte in the models rather than percentage neutrophil or the

neutrophil:lymphocyte ratio (NL ratio, a composite measurefrequently assessed in relation to stressors) because percentagelymphocyte was not altered by the handling stressor whereasneutrophils decreased with the handling stressor (see Results).

To reflect energy stores, we included fat body mass as a predictorvariable. To reflect reproductive investment, we included gonadmass. To reflect body condition, we included carcass mass (whichexcluded abdominal fat bodies and gonads) as a predictor. Becausefat body mass, gonad mass and carcass mass are related to overallbody size, we corrected these measures for body length usingANCOVA with body length as the covariate. To do so, we firsttransformed the mass variables to achieve normality andhomogeneity of variance using square root (fat body mass, gonadmass) or log (carcass mass) transformations. Next, we checked forlinearity using scatterplots. Finally, we confirmed that therelationship between the mass variable and body length was thesame for males and females by running an ANCOVAwith sex as afactor and body length as a covariate. Because slopes werehomogeneous (the sex × length interaction was non-significant)for fat body mass and carcass mass, we saved the unstandardizedresiduals as the size-corrected variables. For gonad mass, slopesdescribing the relationship between gonad mass and body length

A B C

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Fig. 1. Immunohistochemical localization of corticotropin-releasing hormone (CRH) in salamanders. (A,D) Anatomical illustration of a coronal brainsection and its location within the whole brain. Red boxes indicate the location of the section as well as the location of immunoreactive CRH neurons within thesection. (B) Section of striatum exposed to primary antibody that was preabsorbed with 50 μg ml−1 human/rat CRH (control). (C) Adjacent section of striatumexposed to non-preabsorbed primary antibody showing fluorescent puncta. (E) Section of magnocellular POA along the third ventricle exposed to preabsorbedprimary antibody (control). (F) Adjacent section of magnocellular POA exposed to non-preabsorbed primary antibody showing immunoreactive neurons along theventricle.

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differed between males and females. Therefore, we did separateANCOVA for gonad mass for males and females to obtain residualsto represent the size-adjusted gonad masses.Although males and females clearly differ in CORT levels, we

did not include sex alone as a predictor variable, because inclusionmight mask relationships between the physiological and endocrinevariables of interest. Instead, we assessed the impact of sex byincluding interaction terms of sex and the other predictor variablesto assess whether the effects of the predictor variables might differaccording to sex.As shown in the Results, use of IT-AIC did not identify clear ‘best’

models. Instead, many similar models were supported by the analysis.For example, in most cases the weight of the best model was muchless than 0.9, meaning that the probability that it was the best modelwas less than 90%. Also, several models had similar weights withΔAICc values less than 2. Models with ΔAICc values less than 2 areconsidered to be as good as the best model, and models with ΔAICcvalues up to 6 may also be valid (Symonds and Moussalli, 2011).Therefore, to better understand which predictor variables are mostlikely to be part of the best model, we performed full-modelaveraging, which allows inferences to be made from the full set ofcandidate models. Full-model averaging sums the Akaike weightsacross all the models that contain a particular predictor variable togive a measure of the probability that the predictor variable is in thebest model. It also provides an estimate of the mean (β) and error [se(β)] for each predictor variable; 95% confidence intervals were then

determined with the equation: β±1.96[se(β)], to assess the magnitudeof the estimate and whether it was distinguishable from zero.

Characterization of seasonal, sex and handling treatmenteffects using ANOVAThe IT-AICc approach described above specifically tested thehypotheses in Table 1, but we also graphed and analyzed how thevariables differed according to season, sex and handling to providecontext for the IT-AIC results. Hence, we performed 3-wayANOVA using IBM SPSS Statistics 22 to determine the effects ofseason, sex and handling after transforming data to meet parametricassumptions (normality and homogeneous variance). Analyses offat body mass, gonad mass and carcass mass included body length(forelimb to hindlimb length) as a covariate to correct for body size.

RESULTSIT-AICc – baseline CORTUsing IT-AICc, candidate models were generated from data from 38animals. The model containing percentage lymphocyte and thesex×percentage lymphocyte interaction was the best approximatingmodel for variation in baseline CORT (Table 2, weight=0.185). Thebest-fit model demonstrated goodness-of-fit (R2=0.788, adjustedR2=0.776). However, because the weight of the top model indicatedonly an 18.5% probability that it was the best among the set ofcandidate models, full-model averaging was calculated for allgenerated models. This identified percentage lymphocyte and thesex×percentage lymphocyte interaction as the strongest contributorsto variation in baseline CORT (Table 3, lymphocyte: w=0.999;

Table 2. Top models explaining variation in HPA/I activity

Model ΔAICc Weight Evidence ratio

Baseline CORTL, S×L 0 0.185 1L, S×L, G 1.8 0.075 2.456L, S×L, F 2.32 0.058 3.185L, S×L, S×G 2.34 0.057 3.215L, S×L, S×F 2.47 0.054 3.444L, S×L, C 2.49 0.053 3.47L, S×L, S×C 2.5 0.053 3.499L, S×L, G, S×G 2.84 0.045 4.146

Stress-induced CORTL, S×L 0 0.115 1L, S×L, F 1.03 0.067 1.67L, S×L, C 1.27 0.059 1.891L, S×L, S×F 1.36 0.057 1.971L, S×L, G 1.5 0.053 2.116L, S×L, S×C 1.57 0.051 2.194L, S×L, S×G 1.93 0.043 2.625L, S×L, F, C 2.55 0.031 3.577L, S×L, F, S×C 2.83 0.027 4.118L, S×L, C, G 2.84 0.027 4.129

mPOA CRHL, S×L, S×G, G, F 0 0.1357 1L, S×L, S×G, G, S×F 1.75 0.0566 2.397L, S×L, S×G, G, F, S×F 1.9 0.0525 2.586L, S×L, S×G, G, F, C 1.9 0.0525 2.586L, S×L, S×G, G, F, S×C 1.97 0.0508 2.673L, S×L, S×G, G 2.91 0.0317 4.276L, S×L, C, S×F 2.86 0.027 4.182

HPA/I, hypothalamic-pituitary–adrenal/interrenal. Top models were those witha ΔAICc less than 3. Predictions were generated using IT-AICc statisticalmethods; weight indicates the probability that themodel is the best model in theset of candidate models. Evidence ratios demonstrate the likelihood that agiven model is better than the best model. L, percentage lymphocyte; S×L,sex×percentage lymphocyte interaction; G, relative gonad mass; S×G,sex×relative gonad mass interaction; F, relative fat body mass; S×F,sex×relative fat body mass interaction; C, relative carcass mass; S×C,sex×relative carcass mass interaction.

Table 3. Model-averaged estimates for variables predicting baselineCORT, stress-induced CORT and the number of CRH neurons in themPOA

Predictor variable w β se(β) 95% CI

Baseline CORTL 0.999 −0.071 0.014 −0.098, −0.044S×L 0.999 0.036 0.004 0.03, 0.04G 0.311 1.809 4.845 −7.69, 11.31S×G 0.266 −0.86 3.898 −8.50, 6.78F 0.239 −1.124 5.2 −11.32, 9.07S×F 0.228 0.403 2.813 −5.11, 5.92C 0.216 0.372 3.06 −5.63, 6.37S×C 0.216 −0.185 1.669 −3.46, 3.09

Stress-induced CORTS×L 0.996 0.029 0.004 0.02, 0.04L 0.961 −0.036 0.013 −0.061, −0.011C 0.305 0.713 2.053 −3.31, 4.73F 0.293 1.109 3.459 −5.67, 7.89G 0.283 1.057 3.471 −5.74, 7.86S×C 0.273 0.2 1.309 −2.37, 2.77S×F 0.266 0.359 2.389 −4.32, 5.04S×G 0.25 −0.231 2.926 −5.96, 5.49

mPOA CRHS×L 0.969 0.017 0.006 0.005, 0.029L 0.853 −0.038 0.018 −0.073, −0.003S×G 0.724 −13.24 10.022 −32.88, 6.40G 0.653 13.32 11.445 −9.113, 35.751F 0.59 8.464 10.189 −11.51, 28.43S×F 0.406 −2.068 6.782 −15.36, 11.22C 0.289 0.665 2.64 −4.51, 5.84S×C 0.274 0.21 1.499 −2.73, 3.15

Full-model averaging was conducted for each of the three models with all AIC-ranked models. w is the sum of the Akaike weights of models that include thepredictor variable and is a measure of the probability that the predictor variableis a component of the best model; β is the average of the coefficients across allmodels; and se(β) is the error of the coefficient. CI, confidence interval.

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sex×lymphocyte interaction: w=0.999). Additionally, 95%confidence intervals for both predictors did not contain zero(percentage lymphocyte: −0.098, −0.044; sex×percentagelymphocyte interaction: 0.03, 0.04). Although it is difficult tovisualize multivariate relationships in 2-dimensional space, wepresent a scatterplot to help understand the sex×percentagelymphocyte interaction in Fig. 2. The scatterplot suggested thatthe negative relationship between baseline CORT and percentagelymphocyte was particularly evident in females (r=−0.749,P=0.001) but not males (r=0.195, P=0.398).

IT-AICc – stress-induced CORTCandidate models were generated using data from 43 animals. Datafrom one animal (male, stressed, spring sample) was a highlyinfluential point in model selection (Cook’s distance: D≈2.85)because of a very low plasma CORT and small carcass mass. Byconvention,D>1 is considered to be influential, so we removed datafor this animal from further analysis (Cook, 1977). For stress-induced CORT, a model containing percentage lymphocyte and asex×percentage lymphocyte interaction was identified as the bestapproximating model for variation (Table 2, weight=0.115).Regression analysis of the best-fit model (percentage lymphocyte,sex×percentage lymphocyte interaction) demonstrated goodness-of-fit (R2=0.673, adjusted R2=0.657). However, the overall probabilitythat this model was the best was 11.5%, and there were three modelswith ΔAICc<2. Because it was unclear which model was the best,we conducted full-model averaging to determine which predictorswere likely to be a part of the best model. This identified thesex×percentage lymphocyte interaction and percentage lymphocyteas the strongest contributors to variation in stress-induced plasmaCORT (Table 3, sex×percentage lymphocyte interaction: w=0.996;percentage lymphocyte: w=0.961). Additionally, 95% confidenceintervals for both variables did not contain zero (sex×percentagelymphocyte: 0.02, 0.04; percentage lymphocyte: −0.061, −0.011).A scatterplot of percentage lymphocyte and stress-induced CORTdid not provide insight for the sex×percentage lymphocyteinteraction because bivariate correlations were weak and non-significant in both sexes (males: r=0.299, P=0.2; females: r=0.034,P=0.875).

IT-AICc – magnocellular POA CRH neuronsFor CRH neurons in the mPOA, models were generated using datafrom 66 individuals. As with stress-induced CORT, the influentialmale observation was removed (see above). A model containingpercentage lymphocyte, a sex×percentage lymphocyte interaction,relative fat and relative gonad, and a sex×relative gonad interactionwas identified as the best-approximating model for the variation(Table 2, weight=0.1357). Linear regression analysis of the best-fitmodel (percentage lymphocyte, sex×percentage lymphocyteinteraction, sex×relative gonad interaction, relative gonad, relativefat) demonstrated goodness-of-fit (R2=0.301, adjusted R2=0.243).However, the overall probability that this model was the best was13.6%, and there were five models with ΔAICc<2. Because it wasunclear which model was the best, full-model averaging wasconducted, and this identified a sex×percentage lymphocyteinteraction and percentage lymphocyte as contributors to thevariation (Table 3, sex×percentage lymphocyte interaction:w=0.969; percentage lymphocyte: w=0.853). The sign of thecoefficient was negative, indicating a negative relationship betweenpercentage lymphocyte and mPOA CRH neurons. Additionally,95% confidence intervals for both predictors did not contain zero

log Lymphocyte1.65 1.70 1.75 1.80 1.85 1.90 1.95 2.00

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Fig. 3. Plasma CORT levels and number of CRH neurons in themagnocellular preoptic area (mPOA) under baseline and stress-inducedconditions. (A) Plasma CORT levels and (B) number of CRH neurons acrossthree seasons in both males and females (means+s.e.m.). Sample sizes aredisplayed in the bars. Plasma CORT levels were significantly higher in malesthan in females (F1,105=247.04, P<0.001), and handling significantly elevatedplasma CORT (F1,105=109.69,P<0.001). Therewas no overall effect of seasonon plasma CORT (F2,105=1.47, P=0.234). The number of CRH neurons in themPOA did not vary between treatments or across seasons, but males hadmore CRH neurons than females (treatment: F1,82=1.23, P=0.271; season:F2,82=0.56, P=0.574; sex: F1,82=14.27, P<0.001).

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(sex×percentage lymphocyte interaction: 0.005, 0.029; percentagelymphocyte: −0.073, −0.003). A scatterplot of percentagelymphocyte and CRH neurons in the mPOA did not provideinsight for the sex×percentage lymphocyte interaction becausebivariate correlations were weak and non-significant in both sexes(males: r=−0.093, P=0.578; females: r=−0.052, P=0.794).

Seasonal, sex and treatment patternsHere, we present results on how the variables differed according toseason, sex and handling. Although these results do not indicatewhich hypotheses (Table 1) are supported by the data, they providecontext for the IT-AIC results. Plasma CORT levels were higher inmales than in females, and handling significantly elevated plasmaCORT (Fig. 3A, sex: F1,105=247.04, P<0.001; treatment:F1,105=109.69, P<0.001). However, there was no overall effect ofseason on plasma CORT (season: F2,105=1.47, P=0.234). Thenumber of CRH neurons in the mPOA did not vary betweentreatments or across season, but males had more CRH neurons thanfemales (Fig. 3B, treatment: F1,82=1.23, P=0.271; F2,82=0.56,P=0.574; sex: F1,82=14.27, P<0.001). Plasma CORT and thenumber of CRH neurons in the mPOA were positively correlated(r=0.411, P<0.001).

The percentage lymphocyte of the white blood cell countdifferential varied according to season but not sex or treatment(Fig. 4C, season: F2,76=6.1, P=0.003; sex: F1,76=0.30, P=0.59;treatment: F1,76=0.32, P=0.86). The percentage neutrophil wassimilar between males and females and across season (Fig. 3D, sex:F1,76=0.85, P=0.36; season: F2,69=2.1, P=0.132), but decreasedwith treatment (treatment: F1,76=9.7, P=0.003). Similar to thepercentage neutrophil, the NL ratio was similar between males andfemales (Fig. 4A, sex: F1,76=0.86, P=0.36) and decreased withtreatment (treatment: F1,76=7.5, P=0.008). There was a trend for NLto vary across season, being lowest in the autumn (season:F2,76=2.96, P=0.058).

Body length, fat body mass, gonad mass and carcass mass did notdiffer between baseline and stress-induced treatments, so baselineand stress data were pooled (Fig. 5A, treatment: F1,111=1.741,P=0.190; Fig. 5B, treatment: F1,111=0.013, P=0.908; Fig. 5C,treatment: F1,111=0.848, P=0.359; Fig. 5D, treatment: F1,111=0.002,P=0.965). Body length was greater in the summer and autumn thanin the spring, and males were longer than females (season:F2,111=3.810, P=0.025; sex: F1,111=17.375, P<0.001). Overall, fatbody mass (corrected for body length by including body length as acovariate) increased from season to season, and females had more

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Fig. 4. Patterns of white blood cell count differentials under baseline conditions and 30 min after capture.Data were obtained across three seasons; maleand female data were pooled because values did not differ. Sample sizes are displayed in the bars. (A) Neutrophil:lymphocyte (NL) ratio (means+s.e.m.) wassimilar for males and females (F1,76=0.86, P=0.36) and decreased with treatment (F1,76=7.5, P=0.008), with a trend to vary across season (F2,76=2.96, P=0.058).(B) Photomicrograph of a Wright–Giemsa-stained blood smear showing a typical neutrophil, monocyte and lymphocyte (left to right, arrows). (C) Percentagelymphocyte (means+s.e.m.) changed with season (F2,76=6.1, P=0.003) but not sex (F1,76=0.30, P=0.59) or treatment (F1,76=0.32, P=0.86). (D) Percentageneutrophil (means+s.e.m.) was similar between males and females (F1,76=0.85, P=0.36) and across seasons (F2,69=2.1, P=0.132), but decreased with treatment(F1,76=9.7, P=0.003).

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fat than males (season: F2,111=35.95, P<0.001; sex: F1,111=74.545,P<0.001). Ovaries were heavier than testes (sex: F1,111=99.003,P<0.001) and ovarian mass was lowest in the summer while testesmass peaked in the summer (season: F2,111=3.56, P=0.032;sex×season: F2,111=18.772, P<0.001). Finally, both males andfemales increased in mass (corrected for body length by includingbody length as a covariate) over time, and males were heavier thanfemales throughout the year (season: F2,111=8.87, P<0.001; sex:F1,111=21.14, P<0.001).

DISCUSSIONWith this study, we amassed a large and variable data set onphysiological and endocrine variables from male and female free-living Allegheny Mountain dusky salamanders to distinguishamong alternative hypotheses explaining individual variation inpatterns of HPA/I activity. Specifically, we used IT-AICc statisticalmethods to determine which physiological variables were mostclosely associated with individual variation in baseline CORT,stress-induced CORT and mPOA CRH. The best-fit modelsexplained a substantial amount of the individual variation inbaseline CORT (78%) and stress-induced CORT (67%), albeitlower for mPOACRH (30%). All of the best-fit models, regardlessof the measure of HPA/I activity, included percentage lymphocyteand a sex×percentage lymphocyte interaction. The probabilities that

percentage lymphocyte and the sex×percentage lymphocyteinteraction were part of the best-fit model were greater than 96%in all cases, except for percentage lymphocyte in the model ofmPOA CRH neurons (85% probability). Furthermore, the 95%confidence intervals of the coefficients generated by modelaveraging did not overlap zero, further confirming that percentagelymphocyte and the sex×percentage lymphocyte interaction wereassociated with patterns of HPA/I activity. In contrast, measures ofbody condition, energy stores and reproductive investment did notcontribute to the variation in plasma CORT or CRH neurons.Below, we discuss our results in more detail.

No relationship between HPA/I activity and body conditionIn the field of conservation physiology, it has been proposed thatmeasurement of plasma CORT gives insight into the health andvigor of an individual or population (Tarlow and Blumstein, 2007;Wikelski and Cooke, 2006), with baseline CORT (and its releasinghormone, CRH) being negatively associated with body condition,and stress-induced CORT being positively associated with bodycondition. In Allegheny Mountain dusky salamanders, we foundno support for the current-condition hypothesis. Neither bodycondition nor abdominal fat body mass (a measure of energy stores,presumably reflective of condition) explained individual variationin plasma CORT, either baseline or stress induced. These results are

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Fig. 5. Changes in body length, fat body mass, gonad mass and carcass mass during treatment. (A) Body length (forelimb to hindlimb), (B) fat bodymass, (C) gonadmass and (D) carcassmass (means+s.e.m.) in male and female salamanders. Baseline and stress-induced data are pooled because values didnot differ. Sample sizes are displayed in the bars. Body length was greater in the summer and autumn than in the spring (F2,111=3.810, P=0.025) and maleswere longer than females (F1,111=17.375, P<0.001). Overall, relative fat body mass increased from season to season (F2,111=35.95, P<0.001) and females hadmore fat than males (F1,111=74.545, P<0.001). Ovaries were heavier than testes (F1,111=99.003, P<0.001) and ovarian mass was lowest in the summer whiletestes mass peaked in the summer (sex: F2,111=3.56, P=0.032; sex×season interaction: F2,111=18.772, P<0.001). Finally, both males and females increased inrelative mass over time, and males were heavier than females throughout the year (season: F2,111=8.87, P<0.001; sex: F1,111=21.14, P<0.001).

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consistent with a study in Allegheny Mountain dusky salamandersthat also found no relationship between body condition and CORT(Woodley et al., 2014). Thus, in Allegheny Mountain duskysalamanders, measurement of plasma CORT does not provideinsight into the health of an individual or population.Our lack of support for the current-condition hypothesis is

consistent with the literature, which has shown mixed support forthe CORT-fitness hypothesis, which is conceptually similar to thecurrent-condition hypothesis. In several studies, the correlationbetween CORT and fitness was highly context dependent (Bonieret al., 2007, 2009b; Dantzer et al., 2014; Lancaster et al., 2008;Magee et al., 2006). Other studies have found unpredicted positivecorrelations between CORT and indicators of fitness (Cyr andRomero, 2007; Silverin, 1998). Interestingly, a recent meta-analysisfound that integrated levels of CORT (such as can be measured infecal samples or water-borne hormone analyses) were betterassociated with measures of chronic stress than were moreinstantaneous, snapshot, measures of CORT like plasma CORT(Dantzer et al., 2014). Thus, future studies should use moreintegrated measures of GCs in relation to health and fitness.

No relationship of HPA/I activity with reproductiveinvestmentWe found no relationship between individual variation in HPA/Iactivity and relative gonadal mass, suggesting that baseline CORT(and mPOA CRH) does not facilitate investment in reproductiveeffort, and that patterns of stress-induced CORT do not reflect trade-offs related to reproduction. In some species, the CORT response toacute stressors like handling is suppressed during the breedingseason (reviewed in Wingfield and Sapolsky, 2003). Thisobservation suggests that high stress-induced CORT isincompatible with reproductive functions because the elevatedCORT would allocate energy away from reproduction, thusjeopardizing the reproductive effort. In our study of free-livingsalamanders, gonadal mass was not related to either baseline orstress-induced CORT, despite gonads representing a substantialportion of the total bodymass, especially in females. The disconnectbetween plasma CORT and reproductive effort extends toreproductive behaviors; dusky salamander mating behavior wasunaffected by endogenous or exogenous elevations in plasmaCORT in laboratory studies (Bliley and Woodley, 2012; Woodleyand Lacy, 2010).The disconnect between CORT and reproductive effort contrasts

with studies in other species. In white-crowned sparrows, a specieswhere females do the majority of nest building, incubating andfeeding of offspring, reproductive success was positively associatedwith baseline CORT and was negatively associated with stress-induced CORT (Patterson et al., 2014). Amphibians activelyengaged in reproductive behavior often have elevated plasmaCORT (Harvey et al., 1997; Leary et al., 2004; Mendonça et al.,1985; Orchinik et al., 1988; Reedy et al., 2014). One explanation forthe species differences might relate to the length of the breedingseason. In white-crowned sparrows, the breeding season is limitedto a few weeks. In the amphibian examples, mating is often limitedtemporally, with an explosive mating season. In dusky salamanders,the breeding season lasts most of the year, including the autumn–spring mating season and the summer brooding period whenfemales oviposit and guard egg clutches for several weeks. Giventhat physiological levels of CORT elevate metabolic rate (Wacket al., 2012), dusky salamanders may avoid elevating plasma CORTfor such a prolonged period as part of their low-energy lifestyle(Feder, 1983).

Strong relationship between HPA/I activity and percentagelymphocyteOur results indicated that percentage lymphocyte was negativelyassociated with variation in baseline plasma CORT levels. The best-fit models for baseline CORT included percentage lymphocyte and asex×percentage lymphocyte interaction and explained 78% of thevariation, indicating a good fit. However, interpretation of the declinein blood lymphocytes is unclear (for a review of the interpretation ofwhite blood cell count differentials, see Davis et al., 2008). On theone hand, the lower percentage lymphocyte could result from aredistribution from the blood to the periphery formonitoring potentialsites of infection (Viswanathan and Dhabhar, 2005). If so, this resultwould be consistent with the facilitation hypothesis, which posits thatelevated baseline CORT primes the immune systems for challenges.Interestingly, there was a clear sex difference, with females butnot males showing a negative relationship between percentagelymphocyte and baseline CORT. The strong negative correlation infemales may reflect up-regulation of immunity to protect femalesfrom infection during mating, which consists of a prolonged period ofmale–female physical contact during which the male scratches thefemale’s dorsum with hypertrophied premaxillary teeth (Houck andArnold, 2003). Indeed, the percentage lymphocyte in the blood islowest during the spring, which is the peak of the mating season.Infection is associated with lymphopenia in other vertebrates,including salamanders (Davis et al., 2008; Hopkins et al., 2016),suggesting that decreased blood lymphocytes are important forcombatting immune challenges.

On the other hand, the decrease in the percentage lymphocyte inthe blood could result from a reduced synthesis of lymphocytes ordeath of lymphocytes (Cidlowski et al., 1996). If so, the negativeassociation with lymphocytes is consistent with the trade-offhypothesis, whereby the immune system is suppressed to allocateenergy to other important processes related to survival. Related tothis, treatment of Allegheny Mountain dusky salamanders withphysiological levels of CORT suppressed wound healing (Thomasand Woodley, 2015), perhaps reflecting a trade-off between healingand survival. To distinguish among these hypotheses, moremeasures of immune function and determining health outcomesof animals with particular immune profiles are necessary tounderstand whether the immune system is primed or suppressedin association with elevated plasma CORT. For example, afterimmobilization restraint, cururu toads had decreased bacterialkilling ability along with increased plasma CORT and decreasedpercentage lymphocytes in the blood, suggesting suppression ofimmune function (de Assis et al., 2015). Study of additionalimmune factors would also indicate whether the relationshipsbetween HPA/I activity and white blood cell count differentialsextend to other measures of innate or cell-mediated immunity.

In addition to measuring baseline CORT, we also countednumbers of hypophysiotropic CRH neurons because in mostvertebrates, CRH is the primary releasing hormone for activationof the HPA/I axis. Hence, it was not surprising that mPOA CRHnumbers were positively correlated with baseline plasma CORT.Furthermore, we found that percentage lymphocyte was a strongcontributor to variation in the number of mPOA CRH, similar tobaseline CORT. Similarly, the value of the estimating coefficientwas negative, demonstrating a negative relationship between mPOACRH neurons and percentage lymphocyte. Thus, the CRH resultsprovided additional evidence that HPA/I activity is strongly relatedto immune factors.

White blood cells also contributed to variation in stress-inducedplasma CORT. As with baseline CORT, it is difficult to interpret this

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result. Our findings could support the facilitation hypothesis or thetrade-off hypothesis, depending on the functional consequences of adrop in percentage lymphocyte. Again, more measures of immunefunction and determining health outcomes of animals withparticular immune profiles would aid interpretation.The relationship between percentage lymphocyte and the

different measures of HPA/I activity (baseline CORT, stress-induced CORT and CRH) differed between males and females. Thesex difference was most evident for baseline CORT, where baselineCORT was negatively associated with percentage lymphocyte infemales but not males. However, the sex differences were moredifficult to assess for stress-induced CORT and CRH. Scatterplotsand simple correlations did not show strong sex differences,suggesting that the sex differences were relatively subtle, perhapsreflecting slight differences in slopes. Nonetheless, the consistentsex×percentage lymphocyte interaction results indicate thatadditional studies of sex differences in immune function arewarranted.It is important to note that the associations revealed by the IT-

AICc here do not indicate causality. In fact, interactions betweenHPA/I activity and immune function are bi-directional (Silvermanand Sternberg, 2012). Baseline circulating GCs stimulate earlyincreases in immune responses associated with a challenge, but theyinhibit immune function long-term, perhaps to prevent thedevelopment of morbidities associated with autoimmune diseases(Besedovsky and Sorkin, 1977; Hardy et al., 2012; Munck andNáray-Fejes-Tóth, 1994; Sapolsky, 2002). Also, white blood cellsand associated cytokines can influence GC variability via CRH-mediated pathways (Bethin et al., 2000; Chrousos, 1995; Dunn,2000).

Patterns in physiological variablesIt was not our goal to determine whether endocrine andphysiological variables changed on a seasonal basis, but to modelhow different physiological variables were associated with patternsof HPA/I activity. However, we graphed and analyzed the dataaccording to season to illustrate the broad range of variation that wecaptured for our physiological variables. Most variables differedseasonally, such as body and fat mass, body length, gonadmass, andbaseline percentage lymphocyte and percentage neutrophil.Although plasma CORT and the number of mPOA CRH neuronsdid not vary statistically across season, mean baseline CORT wasslightly higher in the spring than in summer and autumn, as wasfound in a previous study (Ricciardella et al., 2010). Also, males andfemales differed for many of the variables, justifying our rationale toinclude interactions with sex in the IT-AICc modeling.

ConclusionsThe simultaneous assessment of multiple physiological andendocrine variables in a free-living amphibian, including noveldata for CRH neurons and white blood cells, represents an importantcontribution to the field of environmental endocrinology. Withthese data, we tested predictions about the meaning of patterns ofHPA/I activity. Although it is often hypothesized that much of thevariation in CORT reflects animal or population health, we found nosupport for the current-condition hypothesis. We also found asurprising disconnect between plasma CORT and reproduction. Weidentified the percentage lymphocyte as the strongest predictor ofHPA/I axis variation compared with other physiological variables.We also found evidence for sex differences in the relationshipbetween percentage lymphocyte and measures of HPA/I activity.The next step is to examine more measures of immune function to

determine whether the relationships we found are reflective of otheraspects of immune function or are limited to white blood cell countdifferentials.

AcknowledgementsWe thank Woodley lab members for assistance with field work.

Competing interestsThe authors declare no competing or financial interests.

Author contributionsJ.R.T. and S.K.W. developed the concept and design of this study. Staining of bloodsmears and determination of white blood cell differentials were conducted by A.J.M.Statistical modeling was conducted by P.E.F. and S.K.W. J.R.T. performed themajority of the experimental methods. J.R.T. and S.K.W. wrote and revised themanuscript.

FundingThis study was funded by Duquesne University.

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