Aquaculture 293 (2009) 164–171

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Spawning-dependent stress responses in pacific oysters Crassostrea gigas:A simulated bacterial challenge in oysters

Yan Li a, Jian G. Qin a, Xiaoxu Li b, Kirsten Benkendorff a,⁎a School of Biological Sciences, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australiab South Australian Research and Development Institute (SARDI), PO Box 120, Henley Beach, SA 5022, Australia

⁎ Corresponding author.E-mail address: Kirsten.benkendorff@flinders.edu.au

0044-8486/$ – see front matter © 2009 Elsevier B.V. Adoi:10.1016/j.aquaculture.2009.04.044

a b s t r a c t

a r t i c l e i n f o

Article history:Received 2 October 2008Received in revised form 30 April 2009Accepted 30 April 2009

Keywords:Oyster mortalitySimulated bacterial challengeSpawningStress responseImmunosuppressionEnergy reserveAdenylate energy charge

This study investigated the effect of spawning activity on the ability of oysters to respond to a simulatedbacterial challenge, as a possible explanation for summer mortality. Using injection with a nonviablebacterial solution (NBS) of Vibrio harveyi, comparisons of immune parameters and biochemical stressresponses were made between pre- and post-spawning Crassostrea gigas. Oyster mortality was alsoexamined with extracellular products injection from V. harveyi cultures, with post-spawning oysterssuffering significantly greater mortality than pre-spawning oysters. Oyster cellular immune defence to NBSwas not influenced by spawning, indicated by comparable phagocytosis rates in pre- and post-spawningoysters. However, hemolymph antimicrobial activity was significantly diminished in post-spawning oysters,coincident with a reduction of hemolymph protein. The analysis of glycogen reserves demonstrated that therecovery process of post-spawning oysters was impaired by NBS challenge, resulting in a suppressedmetabolic activity, indicated by lower adenylate energy charge. These results suggest that the energy cost ofspawning compromises the immune and metabolic responses of oysters, leaving them more vulnerable topathogenic challenge.

© 2009 Elsevier B.V. All rights reserved.

1. Introduction

As a sessile bivalve living in the intertidal zone, oysters are frequentlysubject to various environmental stresses. Although oysters havedeveloped physiological adaptation for survival (Colombo et al., 1990),stress can suppress their immunocompetence and substantially com-promise the ability to defend against parasites and pathogens (Harvellet al., 1999; Li et al., 2007). There is some evidence that reduction ofdefence efficiency has led to high bacterial loads, disease outbreaks andmass mortality in oysters (Cheng, 2000; Chu, 2000). Snieszko (1974)proposed thatmortality in fish occurs as a result of complex interactionsbetween the host, environmental factors and disease agents. This isfurther emphasized by Le Roux et al. (2002) in a mortality study on thePacific oyster (Crassostrea gigas) with Vibrio bacteria. So far, research hasconcentrated on how environmental factors can regulate defencefunction in oysters. However, less attention has been paid to whetherthe physiological status of oysters can alter their defence ability.

In recent years, summermortality has become amajor challenge totheworldwide oyster industry (Cheney et al., 2000). One hypothesis isthat oyster spawning maybe a key contributing factor to summermortality (Berthelin et al., 2000; Pouvreau et al., 2003; Li et al., 2007).This is because oyster spawning occurs concurrentlywith an increasedwater temperature and warm water facilitates the growth of marine

(K. Benkendorff).

ll rights reserved.

pathogens. This naturally leads to the question of whether spawningactivity can impair oysters' stress responses to bacterial challenge.Therefore, we aimed to gather evidence from immunology and energymetabolism to identify discrepant responses to simulated bacterialchallenges between pre-spawning and post-spawning oysters, andthus assess the biological mechanisms leading to summer mortality.

Upon pathogen invasion, bivalves are sometimes able to clear theseinvaders by hemocyte phagocytosis, or by extracellular lysis in thehemolymph, without the direct involvement of hemocytes (Glinski andJarosz,1997). However, both cellular and humoral immune defences areassociated with hemocytes (Rasmussen et al., 1985; Arala-Chaves andSequeira, 2000). Antimicrobial factors in the hemolymph are mostlyproteinaceous or activated by proteins synthesised by hemocytes(Cheng, 2000). Spawning has been observed to reduce the overallhemocyte density (Cho and Jeong, 2005), but it is unclear whether theabundance or function of hemocytes is altered by the spawning activity.Similarly, it is suspected that spawning dependent fluctuation inhemocyte density may influence the immune response of oystersunder bacterial challenge, but this is yet to be experimentally tested.

In addition to immunological deficiency, energetic dysfunctions alsolead to mortality in Pacific oysters C. gigas (Huvet et al., 2004). Whenexposed to stressful stimuli, oysters divert bioenergetic resources awayfrom non-essential functions, and redirect resources to combat, adaptand overcome the stress (Lacoste et al., 2001). In oysters, glycogenreserve plays a central role in the energy supply for mobilisation ofenergetic reserves and gametogenesis (Ruiz et al., 1992; Takuji et al.,

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2002). However, the glycogen content reaches a minimum afterspawning (Berthelin et al., 2000). It has been reported that oystermortality is associatedwith a low level of glycogen reserve (Perdueet al.,1981; Li et al., 2007, 2009a). As energy is also required for the synthesisand mobilisation of immunological defence factors, it is hypothesizedthat the low energy reserves could compromise the ability to combatbacterial challenge in post-spawning oysters. Determination of adeny-late energycharge (AEC)will alsohelp establishwhetherpost-spawningoysters are in a fragile metabolic condition when faced with bacterialchallenge. Impairment of the balance between adenosine nucleotidescan be detrimental to energy synthesis leading to physiological stress(Isani et al., 1995). The more stressed an animal becomes, the moreenergy it uses to counteract the stress, thus lowering the AEC value(Verschraegen et al., 1985).

Vibrio spp. have been identified as a common pathogen for bivalves,andhave consequentlyattractedmuchattention forhealthmanagementin aquaculture (Labreuche et al., 2006b; Garnier et al., 2007). However,the immunological response and physiological regulation duringvibriosis infection in oysters are poorly understood (Gay et al., 2004).Vibrio splendidus and Vibrio aestuarianus have been linked to Pacificoyster summer mortality (Garnier et al., 2007; Samain et al., 2007),although these Vibrios have not been reported in South Australia (SARDIfood safety group, personal communication). However, Vibrio harveyi isa common marine bacterium that does occur in southern Australianwaters and is known to cause disease in awide range of marine animals(Austin, 1988; Zhang and Austin, 2000). V. harveyi has been shown tocause mortality in pearl oysters (Pass et al., 1987) and its abundance ispositively correlated to temperature (Origosa et al., 1989). In this study,therefore,V. harveyiwasused as a representative pathogen to investigatethe discrepant stress response betweenpre- and post-spawningoysters.

In the past decades, studies on pathogenic impacts in oysters havemainly focused on responses in the immune system. It has been elicitedthat most invading pathogens will be cleared from the hemolymph bythe immune system as they are recognised as foreign particles (Glinskiand Jarosz,1997; Cheng, 2000). Althoughdirect contact or injectionwitha virulent pathogen is commonly undertaken amongprevious studies inoysters (Romestand et al., 2002; Gay et al., 2004), the interference frombacterial growth, large inter-animal variability and highmortality of theinfected oysters are unavoidable and will limit the ability to detectstatistically significant sub-lethal effects on the immune system andmetabolic reserves. Considering the virulence of pathogenic Vibrio spp.is primarily due to the extracellular products (ECP) (Labreuche et al.,2006b), nonviable bacterial and pathogenic ECP injectionswere used asmodels to simulate bacteria challenge to oysters in this study. We alsoincubated live V. harveyi with oyster hemolymph to assess the directeffects of humoral factors on bacterial cell viability in vitro. Overall, weaimed to test the hypothesis that energy expended for spawning com-promises the immune and metabolic response of oysters, leaving post-spawning oysters more vulnerable to pathogen infection. With ECPinjection, we aimed to observe the direct lethal response of pre- andpost-spawning oysters to bacterial challenge and evaluate the likelyconsequence of spawning under the stress of ambient pathogen chal-lenge. This study builds on our previouswork examining the changes inthe metabolic resources and immune defence of C. gigas in relation toenvironmental factors in the field (Li et al., 2009a), as well as thesynergistic impacts of spawning and heat stress (Li et al., 2007) andstarvation (Li et al., 2009b) in the laboratory, thus contributing to ourunderstanding of the underlying factors contributing to summermortality.

2. Materials and methods

2.1. Experimental animals

Ripe oysters with shell length of 9–10 cm were obtained from anoyster farm in Ceduna, South Australia in December, 2005. The animals

were acclimatized for a week in 15 °C flow-through seawater tanks andfed daily, at the South Australia Aquatic Sciences Centre. Half of theoysterswere then stimulated to spawn by increasingwater temperaturefrom 15 to 28 °C. This half was treated as the post-spawning populationandkept in 15 °C seawaterafter spawning. Theotherhalfwasused as thepre-spawningpopulation. The simulated bacterial challenge trial started3 days after spawning. The oysters were fed daily throughout the trial,with a mixture of three microalgal species, Isochrysis sp., Pavlova lutheriand Chaetoceros calcitrans (2×109 cells per oyster per day).

2.2. Bacterial solutions

Cultures of the marine pathogen V. harveyi (obtained from the FishHealth Unit, Tasmania Department of Primary Industries and Fisheriesand maintained at −80 °C in 15% glycerol) were prepared by streakingonto nutrient agar plates and incubated overnight at 37 °C. The singlebacterial colonies from the culture plates were inoculated intoMcCartney bottles containing either filtered seawater (0.2 µm, FSW) orsterile nutrient broth (1 g NaCl, 2 g yeast extract and 1 g peptone per100mL distilled H2O). Bacterial cultures were all incubated for 2 days at37 °C on an orbital mixer shaker (Ratek) at 200 rpm. In a pilot study,0.2 mL of the live exponentially growing bacteria was injected intooysters, resulting inN80%mortality (unpublisheddata). Thiswasused asa guide for the doses in the simulated bacterial challenge. To prepare thenonviable bacterial suspension (NBS), the nutrient broth cultures wereheat-killed in an autoclave (101 kPa and 121 °C for 15min) and collectedas a pellet after centrifugation (×500 g for 5 min). The nonviablebacterial pellets were spectrophometrically diluted with FSW to anoptical density of 0.20 at 600 nm (1.3×109 cells mL−1; NBS). To preparethe bacterial extracellular products solution (BEPS), the FSW cultureswere centrifuged directly and the supernatant were taken for proteinquantification. The protein concentration of bacterial BEPS (mg protein/mL) was quantified using the Bio-Rad Protein Assay Kit (Bio-RadLaboratories,Hercules) at 590nmwithbovine serumalbumin standards.Both NBS and BEPS were kept at 4 °C for the following challenge trials.

2.3. Simulated bacterial challenge trials

To facilitate shell opening for injection, all oysters were anaes-thetized in an MgCl2 bath at a final concentration of 50 g L−1 (2:3 v:vseawater:freshwater) for 3 h by the method of Gay et al. (2004). Then0.2 mL per oyster of NBS (~2.6×108 cells) or filtered seawater (FSW)was injected into the adductor muscles using a 1-mL sterilized syringewith a 29 gauge needle.

A total of 405 pre-spawning and 405 post-spawning oysters wasrandomly divided into three groups; one group received NBS injection,another received FSW injection (injection control), and the thirdsynchronously received no injection and they were treated as theexperimental control. The 135 oysters from each treatment combina-tion were then divided into three replicate batches of 45 oysters eachand placed into separate tanks. On days 2, 4 and 7, twelve oysters wererandomly sampled from each replicate tank, with six oysters forhemolymph analyses and the other six oysters for mantle tissueanalyses. An extra nine oysters were included in each tank to accountfor unintentional mortality. The mortality was counted on each daythen accumulated over the duration of the experiment to give a totalmortality for each tank after injection. Hemolymphwas collected fromthe pericardial cavity of oysters using a sterilized syringe with a 29gauge needle, according to previous studies (Xue et al., 2001; Gagnaireet al., 2004; Aladaileh et al., 2007). Mantle tissues were dissectedquickly and preserved in liquid nitrogen for subsequent analyses (totalsampling time b30 s). The samples from six animals were pooled fromeach replicate for immune and metabolic analysis, to minimize theinter-animal variation. Consequently, the replicate tanks are theminimum sampling unit for each treatment combination and thesewere repeatedly sampled over time.

166 Y. Li et al. / Aquaculture 293 (2009) 164–171

Parallel to NBS injection, the effects of V. harveyi extracellularproducts on oyster mortality was tested using a separate batch of 180pre- and 180 post-spawning oysters. Half of these oysters were given aBEPS injection and the other half were not injected and treated as thecontrol. Treatment and control groups were randomly divided intothree replicate tanks, with 30 individuals per replicate. Each treatedoyster was injected with 0.2 mL of BEPS, equivalent to a dose of 2.5 µgBEPSper g oyster, as this dose induced oystermortality in a preliminarytrial. The oyster mortality was checked on day 7 after injection and ispresented as the mean percentage of dead individuals out of the total30 oysters per replicate tank (n=3).

2.4. Hemolymph analysis

Hemolymph from each replicate on each sampling day was storedin a test tube on ice. After 30 s vortex, 0.2 mL hemolymph waspippetted into a pre-cooled Eppendorf tube for the hemocyte densityanalysis. Hemocyte densitywas determined on a hemocytometer fromthe mean of three replicates under a microscope (Olympus). To assessthe phagocytic activity of hemocytes, another subsample (300 µL) wasmixed with an equal volume of FSW in a flow-cytometer tube (n=3).Fluorescent beads (Fluoresbrite® YG Microspheres, 1.75 µm; Poly-sciences), as 4 µL of a stock suspension of 2.5% solids permL FSW,wereadded to each tube. The samples were then analysed on the FACScanflow cytometer after 60 min incubation at 20 °C in the dark (Xue et al.,2001). A total of 200000 cells was counted in each sample. Phagocyticactivity was expressed as the percentage of hemocytes ingesting atleast threefluorescent beads. The remaining hemolymphwas frozen inliquid nitrogen for the antimicrobial activity and protein assays.

V. harveyi colonies growing on nutrient agar were inoculated intoMcCartney bottles containing nutrient broth and incubated overnight at37 °C on an orbital shaker (Ratek) at 200 rpm. The cultures werereturned to the exponential growth phase prior to antimicrobial assays,as described by Li et al. (2007). In brief, 2 mL thawed hemolymph wascentrifuged at ×500 g for 5 min to separate the cell debris and three90 µL aliquots of supernatantwere pippetted into a 96well plate, beforeadding 10 µL of the V. harveyi culture into eachwell (final concentration~108 cells per mL). Negative controls consisted of 90 µL hemolymphincubated with 10 µL nutrient broth while positive controls comprised10 µL of the V. harveyi in 90 µL of the nutrient broth. After 30 minincubation, 20 µL of CellTitre 96® Aqueous One Solution (Promega) wasadded to each well, then the plates were returned to the incubator(37 °C) for 2 h or until development of the red formazan product incontrol wells. The absorbance was measured at 492 nm using a 96 wellplate reader (Spectra Max 250). The background absorbance from thehemolymph broth control was subtracted from the treatmentwells andthen cell viability was calculated as a percentage of the absorbance inpositive control cultures. Antimicrobial activity was expressed by theformula: 100−cell viability.

Protein was measured in the remaining thawed hemolymph. A10 µL sample of hemolymphwas used to determine protein content at590 nm using a 96 well plate reader (Spectra Max 250) by the Bio-RadProtein Assay Kit (n=3). The protein content was expressed in mgprotein per mL of hemolymph relative to a standard curve developedfrom bovine serum albumin.

2.5. Glycogen and adenylate energy charge (AEC) assays

Before theglycogenanalysis andadenylate energycharge (AEC) assay,the pooled mantle tissues were ground into a fine powder on dry ice.Then,1 gfinepowderofmantle tissuewasadded to5mLof 0.6M ice-coldperchloric acid (n=3). Sampleswere vortexed for 30 s and left on ice for10 min, followed by centrifugation at ×1500 g for 10 min at 4 °C. Then1 mL supernatant was removed for glycogen analysis. Another 1 mL wasretained forAECanalysis, prepared according to themethodof Shofer andTjeerdema (1998). All samples were stored at−80 °C prior to analysis.

Glycogen analyses were conducted using the iodine glycogenmethod (Kristman, 1962). This procedure involved adding 1.3 mLiodine solution (1.92 mL I2KI to 500 mL saturated CaCl2 solution) to0.2 mL of sample solution in a micro cuvette. The samples wereincubated at 25 °C for 20 min before reading at 460 nm on a UnicamUV–visible spectrometer. Purified oyster glycogen (MP Biomedicals,NSW, AUS) (0, 0.1, 0.4 and 0.7 mgmL−1) was used to create a standardcurve. The final glycogen concentrationwas expressed in mg per gramof wet tissue weight.

The AEC analyses were carried out on HPLC using a Waters 2695separation module (with Waters 2487 dual λ absorbance detector)equipped with a reverse-phase C18 column (25×4.6 mm, 4.6 µmparticle size fitted with a C18 guard cartridge-20 mm×4.6 mm, 4.6 µmparticle size). The mobile phase consisted of 200 mM phosphate buffer(5.23 g of K2HPO4 and 2.72 g of KH2PO4 in 1 L of distilled H2O; pH 7.0)and methanol (99.8%). Each sample (20 µL) was injected into thecolumnand allowed to run for 15minwith a 1mLmin−1

flow rate. Aftersample injection, the column was eluted with a linear gradient ofphosphate buffer, starting at 95% down to 40% over 10min and thenwasheld steady for an additional 1 min, before returning to the startingcondition over 4 min. The detector wavelength was set to 260 nm fornucleotide detection. A 5 min delay was added between analyses topermit column equilibration. Nucleotides were identified by theirretention times and quantified by peak areas relative to those of theexternal standards of AMP, ADP and ATP (Sigma, St. Louis, MO).Adenylate energy charge (AEC) was calculated as defined by Atkinsons(1968) using the formula:

AEC =ATP + 0:5 × ADPATP + ADP + AMP

2.6. Statistical analysis

The statistical analyseswere conducted on SPSS (14.0 forWindows).The total oyster mortality accumulated from each treatment in the twoseparate experiments was analysed using two-way ANOVAs, withspawning status and simulated bacterial challenge as the two factors.The immuneandphysiological parameterswere analysedwith repeatedmeasures ANOVA in a general linear model according to Li et al. (2007).The dayswere selected aswithin-subjects repeated variables. Simulatedbacterial challenge (injection treatments and controls), and spawningstatus were selected as between-subjects factors. Least SignificantDifference (LSD) test was used for multiple comparisons of thesignificant treatment effects. Data were transformed by square root orlogarithm when necessary, to satisfy the assumptions of normaldistribution and homogeneity of variance. However, the data presentedin the table andfigures are non-transformed values. A significant level of0.05 was used for all tests.

3. Results

3.1. Oyster mortality

ANOVA indicated that the mortality of oysters was not significantlyaffected in the first experiment by either spawning (PN0.05) or NBS(nonviable bacterial suspension) injections, relative to FSW (filteredseawater) injections or non-injected controls (PN0.05, Fig. 1A). How-ever, in the second experiment, mortality was influenced by the inter-action of spawning status and simulated bacterial challenge after 7 days(Pb0.001, Fig. 1B). The bacterial BEPS (V. harveyi extracellular products)caused significantly higher mortality than observed in the controlgroups, for both pre- and post-spawning oysters (Pb0.05, Fig. 1B).Spawning did not impact mortality in the control (PN0.05), whereaspost-spawning oysters suffered nearly double the mortality of pre-spawning oysters injected with V. harveyi BEPS (Pb0.05).

Fig. 1. Mortality of pre-spawning oysters (pre) and post-spawning oysters (post) in oneweek after injection with: A) heat-killed Vibrio harveyi (NBS), filtered seawater (FSW)andwithout injection (Control); B) V. harveyi extracellular products (BEPS) andwithoutinjection. Values are the mean±SE (n=3). Small letters indicate the significantdifference in pre-spawning oysters between Control and BEPS injections. Capital lettersrepresent the significant difference in post-spawning oysters between Control and BEPSinjections. The asterisk indicates significant difference between pre- and post-spawningoysters with BEPS injection. The significant level is set at Pb0.05.

Fig. 2. Cell-mediated immune responses in Crassostrea gigaswith respect to a simulatedbacterial challenge and spawning status: A) hemocyte densities from hemocytometercounts with a light microscope; and B) phagocytosis rate from flow cytometric analysis.‘pre’ represents pre-spawning oysters; ‘post’ represents post-spawning oysters. ‘NBS’represents nonviable bacterial injection challenge; ‘FSW’ represents seawater injection.Values are mean±SE (n=3).

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3.2. Hemolymph analysis

ANOVA confirmed that the impact of spawning was independentof treatment in all immune and metabolic parameters sampled in theoysters (PN0.05, Table 1). The hemocyte density was not affected byspawning (PN0.05), whereas the interaction between treatment andday was significant (P=0.03, Table 1). Compared to the non-injectedcontrol, both the NBS and FSW challenges significantly increased thehemocyte density in the pericardial cavity (Pb0.05, Fig. 2A). Thehemocyte density upon NBS challenge increased dramatically on day 4reaching double that in FSW injection (Pb0.05), but then dropped tothe level of FSW on day 7 (PN0.05).

Hemocyte phagocytosis was significantly influenced by interac-tions between spawning and day, and between treatment and day(P=0.048 and Pb0.001, Table 1), respectively. The phagocytosis ratein post-spawning oysters was generally less than that in pre-spawningoysters (Fig. 2B), as seen across all days in non-injected controls andon day 2 for both injection treatments (Pb0.05). However, by day 4,the phagocytic rate of post-spawning became similar to that of pre-

Table 1Probability of differences derived from repeated measures ANOVA in testing the impact of spaof Crassostrea gigas over time.

Between-subjects effects

Spawning (SP) Bacterial challenge (BC)

Hemocyte density 0.161 0.029Phagocytosis 0.116 0.004Antimicrobial activity b0.001 b0.001Hemolymph protein 0.002 0.002Mantle glycogen 0.082 0.019Adenylate energy charge (AEC) b0.001 0.008

The significant level was set at Pb0.05.

spawning oysters (PN0.05, Fig. 2B). Phagocytosis in both pre- andpost-spawning oysters was initially suppressed by both NBS and FSWinjection, but it exceeded the control level on day 7 (Pb0.05). Thephagocytosis rate after NBS challenge was also significantly higherthan that with FSW injection (Pb0.05).

ANOVA demonstrated that the hemolymph antimicrobial activitywas significantly affected by both the interaction between spawningand day, as well as by the simulated bacterial challenge (Pb0.001,Table 1). On day 2, there was no difference between pre- and post-spawning oysters (PN0.05, Fig. 3A). But the hemolymph antimicrobialactivity in post-spawning oysters significantly decreased and becameless than that in pre-spawning oysters across all the treatments by day4 (Pb0.05). The antimicrobial activity was also significantly reducedby injection with NBS, when compared to both the control and FSWinjection (Fig. 3A, Pb0.05). There was no significant differencebetween FSW and non-injected control (PN0.05).

The hemolymph protein was significantly affected by spawning,and the interaction between treatment and day (P=0.002 and 0.021

wning and simulated bacterial challenge on various immune andmetabolic parameters

Within-subjects effects

SP⁎BC Day Day⁎SP Day⁎BC Day⁎SP⁎BC

0.918 b0.001 0.686 0.003 0.3130.458 b0.001 0.048 b0.001 0.6780.727 b0.001 0.001 0.196 0.1470.744 0.364 0.248 0.021 0.9570.361 0.154 0.393 0.145 0.4880.361 0.154 0.393 0.145 0.488

Fig. 3. Humoral immune responses in Crassostrea gigas with respect to a simulatedbacterial challenge and spawning status: A) antimicrobial activity; and B) protein in oysterhemolymph. ‘pre’ represents pre-spawning; ‘post’ presents post-spawning oysters; ‘NBS’represents nonviable bacterial suspension injection challenge; ‘FSW’ represents seawaterinjection. Values are mean±SE (n=3).

Fig. 4. The impact of simulated bacterial challenge and spawning on the metabolicresources in Crassostrea gigas: A)mantle glycogen; and B) adenylate energy charge. ‘pre’represents pre-spawning; ‘post’ represents post-spawning oysters; ‘NBS’ representsnonviable bacterial suspension injection challenge; ‘FSW’ represents seawater injection.Values are mean±SE (n=3). The dashed line represents the critical threshold (0.5) foroyster AEC values (Shofer and Tjeerdema, 1998).

168 Y. Li et al. / Aquaculture 293 (2009) 164–171

respectively, Table 1). The hemolymph protein in post-spawningoysters was significantly lower than that in pre-spawning oysters(Fig. 3B). In the NBS and FSW injection treatments, hemolymphprotein in the oysters increased from day 2 to day 7 post-injection(Pb0.05). In contrast, the hemolymph protein declined over time inthe control (Fig. 3B). In the first 4 days, hemolymph proteinwas lowerin both injection treatments relative to controls (Pb0.05, Fig. 3B), butwere not significantly different on day 7 (PN0.05). There was nosignificant difference between NBS and FSW in hemolymph protein onany day (PN0.05).

3.3. Glycogen and adenylate energy charge (AEC)

The mean value of mantle glycogen in post-spawning oystersincreased over time and became higher than in pre-spawning oystersin the control on days 4 and7,whereas itwas less than inpre-spawningoysters by day 7 after injection (Fig. 4A). The mantle glycogenwas notsignificantly influenced by spawning status or time (PN0.05, Table 1),although it was significantly affected by injection treatments(P=0.019, Table 1). Both injection treatments had significantly lessglycogen that the non-injected control (Pb0.05), but there was nosignificant difference between NBS and FSW injections in mantleglycogen (PN0.05).

Adenylate energy charge (AEC) in oysters was significantly alteredby spawning and treatment (Pb0.001 and P=0.007 respectively,Table 1). Post-spawning oysters have significantly lower AEC valuesthan pre-spawning oysters across all treatments (Fig. 4B). The AECwas significantly reduced by NBS challenge (Pb0.05), but not by FSWinjection (PN0.05), relative to the non-injected controls (Fig. 4B).After NBS challenge, the AEC values in post-spawning oysters wereclose to 0.5 as indicated by the dashed line in Fig. 4B. AEC values in

post-spawning oysters remained low throughout the study period,whereas pre-spawning oysters showed some recovery towardscontrol levels by day 7 after NBS challenge (Fig. 4B).

4. Discussion

This study revealed that the humoral immune and energymetabolicresponses of oysters are affected by simulated bacterial challenge andspawning activity, but the effects appear to be independent rather thansynergistic. In contrast, the cellular immune responses were onlyinitiated by simulated bacterial challenge, but not spawning status inthis study. The nonviable bacterial challenge used in this study provideda good model for assessing sub-lethal effects on the immune and met-abolic system of oysters, as it did not cause significantmortality, but didsignificantly affect hemocyte density, phagocytosis, antimicrobialactivity, hemolymph protein, mantle glycogen and adenylate energycharge. The observed reductions of hemolymph antibacterial activityand energymetabolic activityafter nonviable bacterial injection indicatethat post-spawning oysters are likely to bemore vulnerable to the stresscaused by bacterial invasion than pre-spawning oysters.

This is further supported by the high mortality in post-spawningcompared to pre-spawning oysters after injection with bacterial(V. harveyi) extracellular products. The mortality observed in thisstudy is consistent with Labreuche et al. (2006b), who reported thatvirulence of pathogenic Vibrio spp. is related to the bacterialextracellular products. As these products can degrade host proteinsto cause extensive host physiological damage (Maeda and Yamamoto,1996), the reduction in hemolymph protein after simulated bacterialchallenge and the inability of post-spawning oysters to recover to

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control levels within 7 days are consequently relevant to the highmortality in these oysters. Reduction in hemolymph protein wasobserved in moribund oysters infected by Perkinsus marinus (La Peyreet al., 1995). The apparent added stress of bacterial challenge to theimmune system in cultured oysters that are already physiologicallystressed after spawning provides a valid explanation contributing tomass mortality in summer.

Being an important component of the immune system, thehemocytes can be mobilised and/or may proliferate in response tobacterial infection (Anderson et al., 1992; Labreuche et al., 2006a).Consistent with this, after simulated bacterial challenge, both pre- andpost-spawning oysters possessed significantly more hemocytes in theirpericardial cavity than seawater injected and non-injected controls. Asoysters have an open circulatory system where hemocytes are free tomove between sinuses among connective tissue (Bachère et al., 2004), itis uncertainwhether the observed increases in hemocyte density 4 daysafter the simulated bacterial challenge are simply due to cell prolifera-tion, migration or accumulation of hemocytes in the pericardial cavity.Although there is suspicion regarding the cellular immune function inthis cavity (Gagnaire et al., 2008), changes in hemocyte density andphagocytosis in this region clearly indicate that the challenged oystershave undergone a stress response. This implies that the injectednonviable bacteria are recognised by hemocytes as foreign particles,even though they were no longer pathogenic. As foreign microorgan-isms normally interact directly with pattern recognition proteins on thesurface of hemocytes in bivalves (Gagnaire et al., 2003), these foreignsignals must remain on the surface of nonviable bacteria to enableefficient clearance from the hemolymph.

Interestingly, despite a decline of the total hemocyte density byday7,hemocyte phagocytosis was still high. Therefore, differential changes inthe proportion of specific types of hemocytes may regulate phagocy-tosis, as suggested by Xue et al. (2001). Much of the initial phagocyticresponse observed in this study appeared to be stimulated by theinjection process rather than the specific presence of foreign bacterialparticles, as both the nonviable bacteria and seawater injection resultedin an initial depression of phagocytosis relative to non-injected controls.This could result from a migration of phagocytes out of the pericardialcavity towards the wound site to prevent the spread of infection. Thisinitial depression was then followed by an apparent stimulation ofphagocytic cells in the pericardial cavity. By day 7, phagocytic rates weresignificantly higher after injection with nonviable bacteria relative toseawater injection controls. This implies the recognition of foreignparticles does further stimulate the activation of cell-mediated immunedefence in oysters, even in the pericardial cavity where the hemocytesare considered more related to excretion (Hine, 1999).

As no significant differences were observed between pre- and post-spawning oysters in the total hemocyte abundance and the phagocyticrate, spawning does not appear to have a direct effect on cell-mediatedimmunity. However, previous investigations into the effects of spawningon hemocyte activity and density have yielded different outcomes.Unlike this study, Cho and Jeong (2005) reported differences inhemocyte density between pre- and post-spawning oysters. This maybe due to the different sampling times used, as Cho and Jeong (2005)detected an effect immediately after spawning, whereaswe determinedhemocyte density 5 days after oyster spawning. Nevertheless, we didobserve lower phagocytosis in post-spawning oysters than that in pre-spawning oysters in the control groups throughout the study period.Despite seasonal variation, a reduction of phagocytosis has also beenobserved during spawning in field populations (Duchemin et al., 2007).However, this effect of spawning was over-ridden by the impact ofsimulated bacterial challenge, as all challenged oysters had double thephagocytic rate of the controls by day 7, irrespective of spawning status.Consequently, post-spawning oysters appear to be capable of eliciting asimilar cellular immune response as pre-spawning oysters, to copewithinvasion by foreign particles. This finding is coincident with previousobservations that hemocyte phagocytosis is similar between summer

mortality-susceptible oysters and summer mortality-resistant oysters(Delaporte et al., 2007). Therefore, Lambert et al. (2007) concluded thatrelevant indicators other than hemocyte profiles are required to helpexplain oyster survival during summer mortality events.

Unlike the cellular immune response, the humoral immunefunction was not only influenced by simulated bacterial challenge,but was also suppressed by spawning. Antimicrobial agents aresynthesised by the hemocytes (Pipe and Coles,1995) and stored in thecells as reserves, then released only after stimulation by microbialinfection or other similar challenges (Cheng, 2000; Anderson andBeaven, 2001). Consequently, the nonviable bacterial injection wasexpected to increase the antimicrobial activity in comparison toseawater injection, by stimulating the release of active factors.However, the opposite effect was observed, whereby the antimicrobialactivity was reduced upon simulated bacterial challenge, despite anincrease in hemocyte numbers and phagocytosis. Therefore, thechanges in antimicrobial activity are not directly synchronized withthe shifts in cellular immune functions. This could be related to the useof nonviable bacteria, which may not have the right cues to stimulaterelease and upregulate the synthesis of new antimicrobial factors.Therefore the patterns observed in this study may simply result fromchanges in the basal levels of constitutively expressed antimicrobialresources in the hemolymph. These constitutive factors appear to beutilised within 2–4 days after the injection of nonviable bacteria andare not replenished to the level of the controls by 7 days aftersimulated bacterial challenge. The basal levels of antimicrobial activityare also generally lower in post-spawning oysters, suggesting trade-offs in the humoral immune system under physiological stress.

Concomitant with the decrease in antimicrobial activity, an initialreduction in hemolymph protein was found upon simulated bacterialchallenge, suggesting the participation of hemolymph protein inantimicrobial activity. However, in this case the response was mostlydue to the stress of seawater injection rather than the specific presenceof nonviable bacteria. In pre-spawning oysters, the hemolymph proteinrecovered to basal levels seen in the control oysters by 7 days afterinjection. In post-spawning oysters, the hemolymph protein declinedover time in controls and although it increased slightly after injection,this occurred at a much slower rate than observed in pre-spawningoysters. As a range of plasma antibacterial peptides and bacteriolyticenzymes are involved in bivalve immune defence (Montes et al., 1995,1997; Anderson and Beaven, 2001), it is likely that these proteinaceoussubstances were rapidly mobilised in response to simulated woundingby injection in both pre- and post-spawning oysters. However, theability to recover humoral immune function after simulated bacterialchallenge is clearly impacted by spawning. This implies that afterexhausting the basal levels of humoral antimicrobial proteins, post-spawning oysters have insufficient metabolic resources to initiate theexpression of new proteins and peptides to continue fighting infection.Therefore, the humoral immune function may not be maintainedeffectively in post-spawning oysters exposed to prolonged or repeatedinfections. Coupled with the degradation of host proteins by bacterialextracellular products, this may weaken the oysters to a point of norecovery. Therefore, despite the apparently normal cellular immunefunction in post-spawning oysters, the spawning-suppressed humoralimmune function could be fatal to oysters when facing opportunisticpathogens in the environment, particularly in warm environmentswhere the growth rate of Vibrio spp. is high. These findings support ourhypothesis that low immunocompetence in post-spawning oysterscompromises their ability to combat bacterial challenge.

As the cost of protein synthesis is 18–26% of the energy budget inmost ectotherms (Houlihua, 1991), the lag of hemolymph proteinsynthesis might be related to energy metabolism in post-spawningoysters. In a previous study, a rapid accumulation of glycogenwas foundin oysters during the post-spawning recovery period (Ren et al., 2003).In our study, fast recovery ofmantle glycogenwas also observed in post-spawning oysters with daily feeding. However, this recovery process

170 Y. Li et al. / Aquaculture 293 (2009) 164–171

was significantly reduced by the injection challenge with low mantleglycogen observed in challenged post-spawning oysters by day 7,indicative of a suppressed energymetabolism. This explains the inabilityof post-spawning oysters to recover their antimicrobial activity andhemolymph protein within a week after injection. However, in theabsence of any injection, the increased glycogen reserve was stillconcomitant with decreased hemolymph protein in post-spawningoysters. Consequently, although post-spawning oysters commencedrestoration of their energy reserves, it seems that their utilisation ofmetabolic energy to repair humoral immune function is inferior to pre-spawningoysters. In lownutrient conditions, the recoveryphase inpost-spawning oysters is much slower thus greatly prolonging the period ofvulnerability to bacterial infection (Li et al., 2009b).

The use of adenylate energy charge (AEC) as a stress indicator inthis study was based on the principle that stressed animals requiremore energy to combat additional stressors (Verschraegen et al., 1985;Cattani et al., 1996; Maguire et al., 1999). This study revealed that bothspawning and simulated bacterial challenge diminished the AECvalue. Simulated bacterial challenge reduced the AEC value in bothpre- and post-spawning oysters, but only post-spawning oysterschallenged with NBS reached an AEC value close to 0.5, a suggestedlow critical limit for survival (Widdows, 1978; Shofer and Tjeerdema,1998). Despite the quick glycogen synthesis during the recoveryprocess, the low AEC value indicates that post-spawning oysters arestill under stress. A similar phenomenonwas observed in the study byDelaporte et al. (2006), where a low AEC value was maintained for amonth after spawning, concomitant with a simultaneous increase incarbohydrates. Thus, due to energy output, post-spawning oysters areat a physiological edge to combat pathogen stress under simulatedbacterial challenge, consistent with the mortality results in this study.

This study on the bivalve C. gigas, agrees with the findings fromMalham et al. (2003) in abalone (Haliotis tuberculata, Gastropoda), thatstress can provoke a priority redirection of bioenergetic resourcestowards adaptive physiological functions, and this unbalance in energyhomeostasis could necessitate a down regulation of immune functions.Although these results were achieved by nonviable bacterial challenge,they were testified by the mortality caused by the challenge ofextracellular products of V. harveyi. Irrespective of spawning status,simulated bacterial challenge also has complicated effects on oystercellular immune responses over time, leading to increased phagocyticrates, but decreased antimicrobial activity. Thereby, examination of bothimmunity and energy metabolism provides an appropriate approach toevaluate the integrative health condition in oysters under bacterialchallenge. Although the massive summer mortality reported in Franceand USA was found during the pre-spawning period (Soletchnik et al.,1999; Burge et al., 2007), it more typically occurs in post-spawning inSouth Australia (Li et al., 2009a), reinforcing that the cause for summermortality is a complex combination of environmental and biologicalfactors (Samain et al., 2007). The present study provides insight into theunderlying biological factors contributing to incidental mass mortalityin marine molluscs, such as abalone, mussels and clams, for whichmortality has been observed in association with spawning and pre-vailing bacteria in summer.

Acknowledgments

We are grateful to Dr Jeremy Carson from the Fish Health Unit,Department of Primary Industry and Fisheries, Tasmania for kindlyproviding the strain ofmarine bacteria andMrGary Zippel from Zippel'sEnterprise in Ceduna, South Australia for supplying Pacific oysters. DrDaniel Jardine from Flinders Analytical Laboratory facilitated the HPLCanalysis of adenylates. Thanks to Mr Liang Song and Ms Ting Wang forhelping with the oyster injection. We acknowledge Ms. Kylie Lange andProf Peter Fairweather from Flinders University for the statistical adviceand we appreciate the constructive comments from two anonymousmanuscript reviewers. This work was supported by an International

Postgraduate Research Scholarship, Flinders University Research Scho-larship (to Yan Li) and the Marine Innovation South Australia Initiative(to Dr Xiaoxu Li).

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