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Standard metabolic rate of juvenile triploid brook charr, Salvelinus fontinalis
Aquaculture 479 (2017) 85–90
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Short communication
Standard metabolic rate of juvenile triploid brook charr, Salvelinus fontinalis Kathleen M. O'Donnell Tillmann J. Benfeya,⁎ a b
a,1
, Krista L. MacRae
a,1
b
MARK
a
, Christine E. Verhille , Charles F.D. Sacobie ,
Department of Biology, University of New Brunswick, P.O. Box 4400, Fredericton, New Brunswick E3B 5A3, Canada Department of Ecology, Montana State University, PO Box 173460, Bozeman, MT 59717-3460, USA
A R T I C L E I N F O
A B S T R A C T
Keywords: Triploidy Cell size Standard metabolic rate Aerobic scope Specific dynamic action
The standard metabolic rates of similarly sized juvenile diploid and triploid brook charr were estimated by using intermittent-flow respirometry to measure oxygen uptake over a 10-day fasting period. Initial oxygen uptake rates did not differ between ploidies, but the rate of decline was slower in triploids, resulting in higher final oxygen uptake rates and, therefore, higher estimated standard metabolic rates. Based on other studies that have shown no effect of triploidy on maximum metabolic rate, this implies reduced aerobic scope in triploids.
1. Introduction Triploid organisms have three sets of chromosomes in their nuclear genomes, rather than the more common two sets in diploids. Among fishes, triploid individuals are occasionally observed within diploid populations as well as within a handful of naturally occurring hybrid complexes that have evolved unique parthenogenetic reproductive strategies (Leggatt and Iwama, 2003). Triploidy can also readily be induced in fish, and the performance of such artificially produced triploids has been studied extensively for the sake of obtaining reproductively sterile populations for aquaculture and fisheries management (Piferrer et al., 2009; Benfey, 2016). In addition to their practical relevance in this regard, artificially produced triploids are also ideal models for studying the effects of cell size and number on basic physiological processes because nuclear volume is increased in proportion to genome size in polyploids, generally with a concomitant increase in cell volume and decrease in cell number (Benfey, 1999). Laboratory studies and larger scale evaluations of triploid performance under aquaculture conditions indicate a reduced tolerance of chronic stress compared to conspecific diploids (Benfey, 1999; Maxime, 2008; Fraser et al., 2012). For instance, Ojolick et al. (1995) observed higher mortality rates in triploid rainbow trout (Oncorhynchus mykiss) compared to diploids following acclimation from 14 to 21 °C, as did Hyndman et al. (2003) in triploid brook charr (Salvelinus fontinalis) following exhaustive exercise in fish that had been acclimated to 19 °C. In both cases, test temperatures exceeded diploid optima (Jobling et al., 2010), suggesting reduced tolerance of high temperature and/or the associated hypoxic conditions that arise from the inverse relationship
⁎
1
Corresponding author. E-mail address: [email protected] (T.J. Benfey). Equal first authors.
http://dx.doi.org/10.1016/j.aquaculture.2017.05.018 Received 31 October 2016; Received in revised form 10 May 2017; Accepted 16 May 2017 Available online 17 May 2017 0044-8486/ © 2017 Elsevier B.V. All rights reserved.
between water temperature and oxygen solubility. This theory has gained support from a number of more recent studies with salmonid species, showing that triploids have maximal routine metabolic rates at lower temperatures than diploids in both Atlantic salmon (Salmo salar) and brook charr (Atkins and Benfey, 2008), triploidy affects the temperature at loss of equilibrium under hypoxia in brook charr (Ellis et al., 2013), cardiac arrhythmia develops at lower temperatures in triploid rainbow trout compared to diploids (Verhille et al., 2013), triploid Atlantic salmon have lower survival, feed intake and growth rate compared to diploids at elevated temperatures, especially under hypoxia, and they modify their swimming behaviour to favour ram irrigation accordingly (Hansen et al., 2015), and triploid rainbow trout have a shorter time to loss of equilibrium than diploids under hypoxia (Scott et al., 2015). Taken together, these prior studies suggest that triploids have reduced aerobic scope, leaving them less able to cope with high metabolic demands (high temperature, exercise, etc.) when oxygen availability is reduced (high temperature, hypoxia, etc.) in comparison to diploids. This same conclusion was drawn from studies of respiratory gas transport in the blood of Chinook salmon (O. tshawytscha) during exhaustive exercise in the absence of a temperature challenge (Bernier et al., 2004). Given that aerobic scope represents the excess aerobic capacity beyond that required to meet basic needs, the aim of this study was to test the hypothesis that triploidy affects standard metabolic rate. This was done by measuring oxygen uptake rates of diploid and triploid brook charr during a 10-day fasting period in the absence of exercise, knowing that this is longer than necessary to bring diploid brook charr to a post-absorptive state (Benfey, 1992). The data obtained using this
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PreSens) that was moved between respirometers. Twenty DO readings were taken for each respirometer at 1-s intervals at the beginning of this closed-system phase and again after an approximate 15-min time interval, and their mean was used to calculate initial and final DO, respectively, for each respirometer for the measured time interval. This was followed by a 10-min open period which started with ⅓ of each respirometer's water being drained and allowing the respirometers to refill three times to flush out any waste and return the DO to saturation levels (~ 10 mg L− 1). The respirometers were then left to overflow until the last minute of the open period, when they were drained by ⅓ again and allowed to refill before being closed. This procedure was repeated 20 times per day, with the last measurement completed at 18:45; this resulted in 20 metabolic rate measurements per day for most fish but, due to equipment malfunctions or human error, some measurements were missed. After the tenth day of testing, fish were removed from their respirometers, anesthetized (as above), measured (body mass and volume) and, once recovered, transferred to a new holding tank in order to keep them separate from the fish that had yet to be tested. A total of 18 fish (9 of each ploidy) were tested in this way, but measurements for three were discarded: one diploid that died on day 8 of the first trial, one triploid that was removed on day 9 of the second trial because it was showing abnormal behaviour, and one triploid from the third trial because of extremely high and variable metabolic rate estimates throughout the 10-day trial, suggesting high levels of spontaneous activity. In the end, full data analysis, as described below, was therefore performed on eight diploid and seven triploid fish. Initial condition factor (K) of each fish (10 days before the first respirometry trial) was calculated as:
approach also allowed an estimation of the metabolic cost of processing each fish's last meal (i.e., specific dynamic action; SDA). 2. Materials and methods All aspects of the following protocol were approved by the UNB Animal Care Committee, adhering to guidelines established by the Canadian Council on Animal Care. Fish were progeny of stock populations reared through multiple generations at the University of New Brunswick's aquatic facilities (Fredericton, NB, Canada). Diploids and triploids were derived from a single fertilization of the pooled eggs from 5 females with the pooled milt from 5 males. Approximately half of the fertilized eggs were maintained as diploid controls and the remainder were treated for triploidy induction by holding them at 65,500 kPa for 5 min in a water-filled pressure chamber (TRC-APVM, TRC Hydraulics Inc., Dieppe, NB, Canada), beginning 29.5 min post-fertilization at an incubation temperature of 6.8 °C. Controls and presumptive triploids were reared under the same conditions, but in separate stage-specific rearing units, using standard husbandry conditions for this species (Jobling et al., 2010) in dechlorinated municipal water that was first passed through degassing/oxygenation columns. Following yolk absorption, fish were fed a standard salmonid grower diet (Corey Nutrition Co., Fredericton, NB, Canada) and maintained under artificial lighting with a seasonally adjusted photoperiod. Ten days prior to the first respirometry trial, all fish were anesthetized in 1% tert-amyl alcohol (A730, Fisher Scientific, Nepean, ON, Canada), measured (body mass to 0.01 g and fork length to 0.1 cm), and tagged with Nonatec RFID transponders (Lutronic International, Luxembourg) inserted into the peritoneal cavity through a hole made using an 18 gauge (1.2 mm) needle. Blood was collected at this time by caudal puncture and used to prepare blood smears for later ploidy analysis based on red blood cell dimensions (Benfey et al., 1984; all fish used for this experiment were subsequently confirmed to be of the assumed ploidy). Fish were then sorted by body mass to minimize size as a confounding factor among test fish, and 24 similarly sized fish (12 per ploidy) transferred to a single 70 L circular tank (50 cm diameter) in order to avoid possible tank effects. Flow rates in this holding tank were maintained at approximately 2 L min− 1 and fish were fed to satiation twice daily, once in the morning and again in the evening, in order to minimize the establishment of feeding hierarchies within the tank. Prior research has shown that feed intake and growth rate are not affected by mixed-ploidy rearing in diploid and triploid brook charr under similar conditions (O'Keefe and Benfey, 1999). Fish were exposed to artificial lighting with a photoperiod appropriate for the latitude and time of year (14 h light, 10 h dark). The fish were 7 months post-fertilization at this time and could not be sexed due to the absence of secondary sexual characteristics in juveniles of this species. Three consecutive respirometry trials were conducted in the same room as the holding tank, each following the same experimental protocol and using the same six identical 180 mL glass intermittentflow respirometers. All measurements were done during daylight hours, with the respirometers isolated from external disturbance by a black plastic barrier. Mean water temperature increased slightly over the course of the trials, from 16.2 ± 0.1 °C (standard error of the mean; SEM) in trial 1 to 16.4 ± 0.2 °C in trial 2 and 17.4 ± 0.2 °C in trial 3. These were identical to the temperature in the holding tank at the time of the trials. At 10:00 on the starting day of a trial, all fish in the holding tank were fed to satiation. Six fish (3 per ploidy) were then haphazardly selected from the tank and each transferred to a separate respirometer, where they were held for the next 10 days. Fish remaining in the holding tank were maintained on the twice-daily feeding regime. All 6 respirometers were closed at 10:30 and the measurement of dissolved oxygen (DO) concentration began using oxygen sensor spots (SP-PSt3NAU-D5-YOP, PreSens Precision Sensing GmbH, Regensburg, Germany) within each respirometer and a fiber optic oxygen transmitter (Fibox 3,
K=
⎛w⎞ ⎜ ⎟ ∗100 ⎝ l3 ⎠
where w is body mass (g) and l is fork length (cm). Mass-specific oxygen uptake rate (MO2) was calculated for each fish for each closed-respirometer period as:
MO2 =
Δ [O2 ] ∗ (VR − VF ) t∗w
where Δ[O2] is change in DO (mg L− 1) during the closed period, VR and VF are respirometer and fish volumes (L), respectively, t is time that the respirometer was closed (h), and w is body mass at the end of the trial (kg). Standard metabolic rate (SMR) was estimated by quantile analysis of MO2 data from days 6 to 10. Previous researchers have used the 0.2 quantile to estimate SMR (Chabot et al., 2016a). However, given that visual inspection showed a high degree of variation in metabolic rates for individual fish within individual days, suggestive of spontaneous activity and/or stress, a range of quantiles (0.10, 0.15, 0.20, and 0.25) was used to estimate SMR. The mean of the lowest normal distribution (MLND) was also considered for determining SMR, but was deemed inappropriate because MLND coefficients of variation ranged from 13 to 35, which are higher than the advised limit of 5.4 (Chabot et al., 2016a). Routine metabolic rate (RMR) was estimated in two ways: by quantile analysis of MO2 data using the 0.50 quantile from days 6 to 10 and by averaging all MO2 measurements from days 6 to 10 and days 8 to 10. Quantiles and MLNDs were calculated using the calcSMR function of the fishMO2 package (Chabot, 2016) in R (R Core Team, 2017). As with SMR and RMR quantification, the relationships between metabolic rate and post-prandial time and the associated variables related to SDA were quantified from analyses of metabolic rate quantiles as well as the full dataset. Metabolic rate response to postprandial times was modelled with no a priori assumptions regarding the shape of the relationship. For both approaches, total post-prandial metabolic cost (SDA; mg O2 kg− 1) was determined by subtracting the area under the SMR curve over the post-prandial duration from the area 86
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Combining the higher triploid SMR and RMR estimates with similar MRpeak estimates during the post-prandial period resulted in reduced MRfactscope for triploids relative to diploids for all analyses, with significant ploidy effects for the same quantile regressions as for MRscope.
under the MO2 model curve. Post-prandial duration (SDAduration; h) was estimated as the time elapsed since feeding until the point where metabolic rate and SMR no longer differed. Peak post-prandial metabolic rate (MRpeak; mg O2 kg− 1 h− 1) and net peak post-prandial metabolic rate (MRscope; mg O2 kg− 1 h− 1) were determined as the highest metabolic rate predicted by the model during the post-prandial duration and this peak value minus SMR (or RMR), respectively. Finally, the factorial increase in metabolic rate at MRpeak (MRfactscope) was calculated as MRpeak divided by SMR (or RMR). For the quantile analyses, quantile regression modelling (Wood, 2011) of SDA, SDAduration, MRpeak, MRscope and MRfactscope was performed using the calcSDA function of the fishMO2 package in R. The my.smr and tau arguments of the calcSDA function specify the SMR and the quantile of metabolic rate data upon which to perform the quantile regression of post-prandial time versus MO2. Combinations of my.smr and tau analyzed, respectively, were 0.15 and 0.10, 0.15 and 0.25, 0.25 and 0.10, 0.25 and 0.25, 0.5 and 0.4, and 0.5 and 0.5. The lambda argument, which is a penalty parameter applied to the quantile regression to control the flexibility of the fitted curve, was set to 100. The postfeed.acclim argument, which assigns the duration after feeding, where SDA analysis is not performed on metabolic rate due to persistence of feeding-related excitement, was set to 5 h. The tol argument, which sets the tolerance around SMR (or RMR) dictating determination of SDAduration, was assigned a value of 5, and the tol.type argument was used to specify the tol as a proportion of SMR (or RMR), i.e., 5%. The MO2.time.unit and X.time.unit arguments, which respectively specify the time units for the metabolic rate values and the SDAduration values, were both set to ‘hour’. The calcSDA function identifies SDAduration as the latest time point after feeding where metabolic rate falls to SMR (or RMR). For three fish, post-prandial metabolic rate dropped to SMR rates and remained low for two or more days, but subsequently increased to exceed SMR rates, presumably due to spontaneous activity or stress rather than SDA. For these three fish, the SDA-related variables were recalculated manually to reflect the first time metabolic rate dropped to SMR and remained there for ≤ 2 days. General additive modelling of the full data set for SDA, SDAduration, MRpeak, MRscope and MRfactscope used the gam function of the mgcv package (Wood, 2011) in R. For these analyses, estimates of basic metabolic (i.e., SMR or RMR) requirements included analysis of all metabolic rates measured from days 8 to 10. As these estimates likely include periods of spontaneous activity and/or stress, they have been referred to as RMR. The effect of ploidy on initial body mass, fork length and condition factor was analyzed by 1-factor ANOVA. Ploidy effects on SMR, RMR, SDA, SDAduration, MRpeak, MRscope, and MRfactscope were analyzed using 1-factor ANOVA with trial as an error term as well as a top down comparison of nested mixed effects models using a chi square test. The full mixed effect model included ploidy as a fixed factor and trial as a random factor. The reduced mixed effect model included only trial as a random factor. For all statistical analyses, alpha values of 0.05 were used to determine significance.
4. Discussion The aim of this study was to determine whether triploidy affects standard metabolism in fish, as estimated from metabolic rate measurements made over a 10-day period without feeding. Although initial measurements would have included the energetic costs of processing the last meal and of responding to the stress of being transferred to the respirometers, previous studies using juvenile brook charr have shown that 10 days without feeding is sufficient to bring these fish to a postabsorptive state (Benfey, 1992), and that triploidy does not affect primary or secondary stress responses to capture and confinement in smaller tanks (Biron and Benfey, 1994; Benfey and Biron, 2000). However, determination of standard metabolism was complicated in this study for two reasons: firstly, although fish were in static respirometers, they were not prevented from swimming, and secondly, measurements were only made during daylight hours. Multiple approaches were therefore used to estimate SMR from these data, ranging from very conservative (i.e., using just the lowest 0.1 quantile of MO2 data) to exceedingly liberal (i.e., using the lowest 0.5 quantile or even all data for the last few days, and therefore more appropriately defined as RMR). Although there was no significant effect of ploidy on measured MO2 in any single analysis, the overall pattern was consistent: triploids always had the higher SMR or RMR estimate. Furthermore, both the absolute and factorial scopes of increase from SMR to peak post-prandial MO2 were always lower for triploids than for diploids, and significantly so for several of the quantile analyses. The temperature which the fish were acclimated to and tested at for this experiment (16–17 °C) was higher than the optimum for juvenile diploids of this size (13 °C; Dwyer et al., 1983) and, by extension, likely even higher than optimum for the triploids (Atkins and Benfey, 2008). The observed effects of triploidy on metabolic rate were therefore likely exacerbated by thermal stress. Taken together with earlier studies showing no effect of triploidy on maximum metabolic rate (Small and Randall, 1989; Stillwell and Benfey, 1997; Lijalad and Powell, 2009; Scott et al., 2015), but reduced thermal tolerance (Ojolick et al., 1995; Hyndman et al., 2003; Verhille et al., 2013; Hansen et al., 2015), these results imply that triploids have reduced aerobic scope due to higher standard metabolism under thermal stress. Triploids differ from diploids in three fundamental ways: their gonadal development is disrupted, they have the potential for greater allelic diversity at every locus, and they have smaller numbers of larger cells in most tissues and organs (Benfey, 1999). Small juvenile fish from a limited gene pool were specifically chosen for this experiment in order to diminish the effects of ploidy on gonadal development and heterozygosity, respectively, and so the higher standard metabolic rate observed in triploids is likely an outcome of their larger cell size or reduced cell numbers. In the absence of a change in cell shape, larger cells have reduced cellular surface area per unit volume, thus affecting surface-limited processes (Choleva and Janko, 2013; Schoenfelder and Fox, 2015). Furthermore, reductions in cell numbers likely affect cell turnover rates and, therefore, tissue/organ maintenance. Triploids may therefore need to maintain higher standard metabolic rates to compensate for a reduced ability to transfer nutrients and metabolites across their cell membranes and to replace (or function with) senescent cells under normal conditions, and this situation may be worsened under conditions that disrupt optimal protein structure or function. In the absence of any changes in metabolic efficiency in triploids, higher standard metabolism could be expected to result in a reduced ability to accumulate energy reserves, and indeed this was recently shown in juvenile brook charr (Sacobie et al., 2016). This may explain
3. Results Although mean body mass and condition factor were noticeably lower for triploids than for diploids when the fish were initially sorted, these differences were not statistically significant (Table 1). Both SMR and RMR were higher for triploids than diploids in all analyses (e.g., Fig. 1), but never significantly so (Table 1). SDA (all analyses) and SDAduration (quantile analyses) were consistently lower and longer, respectively, for triploids than diploids, but again never significantly so. MRpeak values were similar for diploids and triploids, but MRscope was reduced in triploids across all analyses, with significant ploidy effects when using the 0.25 quantile for the quantile regression with the 0.15 and 0.25 quantiles of the SMR estimate, and the 0.4 quantile for the quantile regression with the 0.5 quantile of the RMR estimate. 87
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Table 1 Diploid and triploid juvenile brook charr (Salvelinus fontinalis) size at initial sorting and characterization of metabolic rate (MR) and specific dynamic action (SDA) following a single feeding. Values are mean ± standard error of the mean, with sample sizes of 9 for size measurements, and 8 and 7 (diploids and triploids, respectively) for MR and SDA. Bolded p-values indicate significant differences at an alpha level of 0.05. ANOVA Variable Body mass Fork length Condition factor SMR
RMR
Analysis
q
Quantile
0.1 0.15 0.2 0.25 0.5
SDA
Quantile ALLd6to10 ALLd8to10 Quantile
SDAduration
GAM Quantile
MRpeak
GAM Quantile
MRscope
GAM Quantile
MRfactscope
GAM Quantile
GAM
tau
0.15 0.15 0.25 0.25 0.5 0.5
0.1 0.25 0.1 0.25 0.4 0.5
0.15 0.15 0.25 0.25 0.5 0.5
0.1 0.25 0.1 0.25 0.4 0.5 0.1 0.15 0.2 0.25 0.4 0.5
0.15 0.15 0.25 0.25 0.5 0.5
0.1 0.25 0.1 0.25 0.4 0.5
0.15 0.15 0.25 0.25 0.5 0.5
0.1 0.25 0.1 0.25 0.4 0.5
Diploid 2.93 ± 0.07 6.3 ± 0.2 1.22 ± 0.12 175.1 ± 12.8 187.6 ± 12.7 197.5 ± 13.6 205.7 ± 14.2 240.7 ± 16.8 253.0 ± 18.1 239.3 ± 15.6 8049 ± 2024 13,998 ± 2047 5890 ± 1437 10,483 ± 1608 8912 ± 1170 11,407 ± 1356 13,671 ± 2572 121.0 ± 14.3 188.6 ± 9.3 95.8 ± 15.9 141.6 ± 19.5 127.7 ± 18.1 141.5 ± 17.9 147.7 ± 15.3 320.3 ± 33.4 350.0 ± 32.9 320.3 ± 33.4 398.1 ± 37.1 441.4 ± 41.7 456.7 ± 38.8 510.0 ± 54.3 132.7 ± 28.2 210.5 ± 27.6 114.7 ± 26.0 192.4 ± 24.3 200.7 ± 27.0 216.0 ± 23.8 270.7 ± 45.1 1.71 ± 0.14 2.11 ± 0.11 1.56 ± 0.12 1.92 ± 0.07 1.82 ± 0.08 1.89 ± 0.06 2.12 ± 0.17
Triploid 2.65 ± 0.13 6.4 ± 0.2 1.03 ± 0.08 206.9 ± 18.3 222.4 ± 20.3 234.6 ± 21.4 243.0 ± 21.4 281.5 ± 23.6 291.7 ± 24.7 279.8 ± 26.0 6802 ± 706 12,957 ± 1189 4191 ± 1652 9118 ± 999 7458 ± 1253 10,116 ± 1490 12,468 ± 1904 146.6 ± 18.4 194.2 ± 10.6 107.2 ± 16.3 170.4 ± 8.9 129.8 ± 16.3 160.6 ± 19.8 142.4 ± 16.1 328.4 ± 37.2 354.3 ± 34.6 328.4 ± 37.2 378.7 ± 32.1 430.6 ± 37.5 464.7 ± 42.3 513.9 ± 46.8 106.0 ± 21.0 156.2 ± 19.4 85.5 ± 20.1 135.7 ± 19.6 149.0 ± 27.2 183.1 ± 34.8 234.1 ± 40.1 1.47 ± 0.06 1.72 ± 0.13 1.34 ± 0.06 1.58 ± 0.09 1.55 ± 0.12 1.68 ± 0.16 1.88 ± 0.20
F-ratio 3.42 0.140 1.70 1.738 2.033 2.195 2.261 2.465 1.877 2.479 0.332 0.331 1.417 0.530 1.257 0.737 0.367 0.867 0.065 0.028 1.557 0.019 0.577 0.310 0.041 0.290 0.000 0.096 0.814 0.013 0.003 0.416 2.005 0.659 2.744 2.099 0.831 0.697 1.839 5.478 2.331 8.199 5.593 2.573 1.817
Mixed effect model p-Value 0.083 0.711 0.207 0.212 0.179 0.164 0.159 0.142 0.196 0.141 0.575 0.516 0.257 0.481 0.284 0.407 0.556 0.370 0.803 0.869 0.236 0.894 0.462 0.588 0.844 0.869 1.000 0.762 0.385 0.192 0.960 0.531 0.182 0.433 0.124 0.173 0.380 0.420 0.200 0.037 0.153 0.014 0.036 0.135 0.203
AIC (full/reduced)
χ2-Value
p-Value
159/159 160/161 161/162 161/162 164/165 167/168 165/167 300/298 134/133 291/290 295/294 290/290 295/294 311/309 162/162 304/305 161/159 162/161 164/162 160/159 161/159 184/182 182/180 183/181 179/178 194/193 181/180 189/187 176/174 174/172 174/172 170/173 174/176 177/177 188/187 14/14 12/16 8/9 3/9 7/10 13/13 26/26
2.292 2.726 2.986 3.187 3.461 2.402 2.237 0.344 0.399 1.188 0.736 1.779 0.951 0.268 1.367 0.264 0.134 1.782 0.008 0.897 0.111 0.006 0.0001 0.064 0.799 0.950 0.061 0.249 0.619 4.087 0.844 4.841 4.199 1.865 1.613 2.335 5.989 2.589 7.746 5.155 2.129 1.936
0.130 0.099 0.084 0.074 0.063 0.121 0.072 0.558 0.528 0.276 0.391 0.182 0.329 0.604 0.242 0.605 0.715 0.182 0.928 0.343 0.739 0.936 0.993 0.800 0.371 0.330 0.805 0.618 0.431 0.043 0.358 0.028 0.040 0.172 0.204 0.126 0.014 0.108 0.005 0.023 0.145 0.164
SMR: standard MR; RMR: routine MR; SDAduration: time elapsed since feeding until MR and SMR (or RMR) no longer differed; SDA: total post-prandial metabolic cost; MRpeak: peak postprandial MR; MRscope: increase in MR from SMR (or RMR) to MRpeak; MRfactscope: factorial increase in SMR (or RMR) at MRpeak; q: quantile of the day 8 to 10 MR data used to determine SMR or RMR; tau: quantile of SDA data used to perform the additive quantile regression analysis (i.e., the relationship between MR and time after feeding); ANOVA: one-way ANOVA test with ploidy as the factor and trial as an error term; Mixed effect model: top down χ2 comparisons including ploidy as a fixed effect and trial as a random effect with a nested model including only trial as a random effect; ALLd6to10 and ALLd8to10: RMR using all data for days 6 to 10 and days 8 to 10, respectively, after feeding; GAM: general additive model with a gamma distribution to determine the relationship between MR and time after the meal.
triploids required less energy to process their last meal than diploids, but they took longer to do so. The only other study to estimate SDA in triploid salmonids found no effect of ploidy (rainbow trout; Oliva-Teles and Kaushik, 1987). Conducted properly, SDA measurements are made by feeding previously food-deprived fish within the respirometer, thereby both minimizing the metabolic cost of the stress of transferring fish to the respirometer and also measuring the initial cost of ingesting and processing food (Chabot et al., 2016b). Thus, SDA measurements should include the integrated area under the curve bound by standard metabolism for both increasing and decreasing MO2 following the meal. There was no observable increase in metabolic rate at the start of the current study, likely due to the combination of initial handling stress and not starting measurements at the time of feeding. As a result, only the decreasing phase of SDA was measured. The SDA data in this study thus represent just a crude estimation of true SDA.
the frequent observation of lower condition factor in triploids (Piferrer et al., 2009), and supports the suggestion that triploids should have diets tailored to meet their specific nutritional requirements (Tibbetts et al., 2013; Benfey, 2016; Smedley et al., 2016). Higher standard metabolism would also imply trade-offs with respect to directing limited energy reserves towards specific functions, thus providing an explanation for lower titres of heat shock proteins in triploids (Saranyan et al., 2017). Under optimum conditions, a diminished capacity to mount an HSP-mediated stress response may not be of any significance, but coupling this with lower aerobic scope – itself an outcome of higher standard metabolism – provides a testable hypothesis for why triploids have a diminished ability to withstand high temperature and hypoxia. Although not a goal of this study, the experimental design also allowed for the estimation of SDA. Similar to SMR and RMR, the various analyses that were conducted showed a consistent effect of ploidy, i.e., 88
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Metabolic Rate (mg O2 kg -1 h -1)
K.M. O'Donnell et al.
600
2N Metabolic Rate 2N SMR 3N Metabolic Rate 3N SMR
A
500
SEM 400
300
200
100
0 0
50
100
150
200
Metabolic Rate (mg O2 kg -1 h -1)
Time after Feeding (h) 600
B
500
400
300
200
100
0 0
50
100
150
200
Time after Feeding (h) Fig. 1. Predicted metabolic rate of diploid (2N) and triploid (3N) juvenile brook charr (Salvelinus fontinalis) following a single feeding (solid lines) and estimated standard metabolic rate (SMR; dashed lines) with 95% confidence intervals (in A) or standard errors (in B) around the means (dotted lines). The metabolic response to feeding was predicted by analyzing the relationship between time after feeding and metabolic rate, with the two ploidies analyzed separately. In A, SDA was modelled as an additive quantile regression using the rqss function of the quantreg package and with time after feeding as an additive nonparametric component (Wood, 2011) in R. Arguments specified within the rqss function included a tau of 0.25, lambda value of 100, and SMR was estimated as the 0.15 quantile of metabolic rate data from days 6 to 10 after feeding. In B, SDA was modelled as a general additive model using the gam function of the mgcv R package (Wood, 2011). Arguments included a k value of 3 and a ‘tp’ bases, and SMR was estimated as the average of all metabolic rate measurements on days 8 through 10 after feeding.
undergraduate Honours thesis project in Biology at UNB (KMO), and was supported financially by the Natural Sciences and Engineering Research Council of Canada (46180-2011), through both a Discovery Grant (TJB) and an Undergraduate Student Research Award (KMO), and by the New Brunswick Innovation Fund, through the Research Assistantships Initiative (KLM).
In conclusion, triploid brook charr were shown by multiple analyses to have a higher standard metabolic rate than diploids at above optimum temperature, although not significantly so by any single analysis. This suggests that they (a) have lower aerobic scope and (b) divert proportionately more dietary energy to maintenance than to growth compared to diploids at this temperature. Optimizing triploid performance at elevated temperatures should therefore focus on minimizing aerobic stresses on the animals and providing them with diets that favour energy storage in forms that are readily mobilized. Followup experiments to assess aerobic scope at a range of temperatures around the optimum are warranted.
References Atkins, M.E., Benfey, T.J., 2008. Effect of temperature on routine metabolic rate in triploid salmonids. Comp. Biochem. Physiol. 149A, 157–161. Benfey, T.J., 1992. Hepatic ornithine decarboxylase activity during short-term starvation and refeeding in brook trout, Salvelinus fontinalis. Aquaculture 102, 105–113. Benfey, T.J., 1999. The physiology and behavior of triploid fishes. Rev. Fish. Sci. 7, 39–67. Benfey, T.J., 2016. Effectiveness of triploidy as a management tool for reproductive containment of farmed fish: Atlantic salmon (Salmo salar) as a case study. Rev. Aquac. 8, 264–282.
Acknowledgements This study was designed to build upon concepts developed and results obtained in partial fulfillment of the requirements for an 89
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salar L. Aquaculture 290, 145–154. Maxime, V., 2008. The physiology of triploid fish: current knowledge and comparisons with diploid fish. Fish Fish. 9, 67–78. Ojolick, E.J., Cusack, R., Benfey, T.J., Kerr, S.R., 1995. Survival and growth of all-female diploid and triploid rainbow trout (Oncorhynchus mykiss) reared at chronic high temperature. Aquaculture 131, 177–187. O'Keefe, R.A., Benfey, T.J., 1999. Comparative growth and food consumption of diploid and triploid brook trout (Salvelinus fontinalis) monitored by radiography. Aquaculture 175, 111–120. Oliva-Teles, A., Kaushik, S.J., 1987. Metabolic utilization of diets by polyploid rainbow trout (Salmo gairdneri). Comp. Biochem. Physiol. 88A, 45–47. Piferrer, F., Beaumont, A., Falguière, J.C., Flajšhans, M., Haffray, P., Colombo, L., 2009. Polyploid fish and shellfish: production, biology and applications to aquaculture for performance improvement and genetic containment. Aquaculture 293, 125–156. R Core Team, 2017. R a language and environment for statistical computing. https:// www.r-project.org/. Sacobie, C.F.D., Burke, H.A., Lall, S.P., Benfey, T.J., 2016. The effect of dietary energy level on growth and nutrient utilization by juvenile diploid and triploid brook charr, Salvelinus fontinalis. Aquac. Nutr. 22, 1091–1100. Saranyan, P.V., Ross, N.W., Benfey, T.J., 2017. Erythrocyte heat shock protein responses to chronic (in vivo) and acute (in vitro) temperature challenge in diploid and triploid salmonids. Comp. Biochem. Physiol. 206A, 95–104. Schoenfelder, K.P., Fox, D.T., 2015. The expanding implications of polyploidy. J. Cell Biol. 209, 485–491. Scott, M.A., Dhillon, R.S., Schulte, P.M., Richards, J.G., 2015. Physiology and performance of wild and domestic strains of diploid and triploid rainbow trout (Oncorhynchus mykiss) in response to environmental challenges. Can. J. Fish. Aquat. Sci. 72, 125–134. Small, S.A., Randall, D.J., 1989. Effects of triploidy on the swimming performance of coho salmon (Oncorhynchus kisutch). Can. J. Fish. Aquat. Sci. 46, 243–245. Smedley, M.A., Clokie, B.G.J., Migaud, H., Campbell, P., Walton, J., Hunter, D., Corrigan, D., Taylor, J.F., 2016. Dietary phosphorous and protein supplementation enhances seawater growth and reduces severity of vertebral malformation in triploid Atlantic salmon (Salmo salar L.). Aquaculture 451, 357–368. Stillwell, E.J., Benfey, T.J., 1997. The critical swimming velocity of diploid and triploid brook trout (Salvelinus fontinalis). J. Fish Biol. 51, 650–653. Tibbetts, S.M., Wall, C.L., Barbosa-Solomieu, V., Bryenton, M.D., Plouffe, D.A., Buchanan, J.T., Lall, S.P., 2013. Effects of combined ‘all-fish’ growth hormone transgenics and triploidy on growth and nutrient utilization of Atlantic salmon (Salmo salar L.) fed a practical grower diet of known composition. Aquaculture 406-407, 141–152. Verhille, C., Anttila, K., Farrell, A.P., 2013. A heart to heart on temperature: impaired temperature tolerance of triploid rainbow trout (Oncorhynchus mykiss) due to early onset of cardiac arrhythmia. Comp. Biochem. Physiol. 164A, 653–657. Wood, S.N., 2011. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. Roy. Stat. Soc. 73B, 3–36.
Benfey, T.J., Biron, M., 2000. Acute stress response in triploid rainbow trout (Oncorhynchus mykiss) and brook trout (Salvelinus fontinalis). Aquaculture 184, 167–176. Benfey, T.J., Sutterlin, A.M., Thompson, R.J., 1984. Use of erythrocyte measurements to identify triploid salmonids. Can. J. Fish. Aquat. Sci. 41, 980–984. Bernier, N.J., Brauner, C.J., Heath, J.W., Randall, D.J., 2004. Oxygen and carbon dioxide transport during sustained exercise in diploid and triploid Chinook salmon (Oncorhynchus tshawytscha). Can. J. Fish. Aquat. Sci. 61, 1797–1805. Biron, M., Benfey, T.J., 1994. Cortisol, glucose and hematocrit changes during acute stress, cohort sampling, and the diel cycle in diploid and triploid brook trout (Salvelinus fontinalis Mitchill). Fish Physiol. Biochem. 13, 153–160. Chabot, D., 2016. Calculate and plot the standard metabolic rate (SMR), the critical oxygen level (O2crit) and the specific dynamic action (SDA) and related variables in fishes and crustaceans. https://www.researchgate.net/publication/308888209_ fishMO2_Calculate_and_plot_the_standard_metabolic_rate_SMR_the_critical_oxygen_ level_O2crit_and_the_specific_dynamic_action_SDA_and_related_variables_in_fishes_ and_crustaceans. Chabot, D., Steffensen, J.F., Farrell, A.P., 2016a. The determination of standard metabolic rate in fishes. J. Fish Biol. 88, 81–121. Chabot, D., Koenker, R., Farrell, A.P., 2016b. The measurement of specific dynamic action in fishes. J. Fish Biol. 88, 152–172. Choleva, L., Janko, K., 2013. Rise and persistence of animal polyploidy: evolutionary constraints and potential. Cytogenet. Genome Res. 140, 151–170. Dwyer, W.P., Piper, R.G., Smith, C.E., 1983. Brook trout growth efficiency as affected by temperature. Prog. Fish-Cult. 45, 161–163. Ellis, L.E., Sacobie, C.F.D., Kieffer, J.D., Benfey, T.J., 2013. The effects of dissolved oxygen and triploidy on critical thermal maximum in brook charr (Salvelinus fontinalis). Comp. Biochem. Physiol. 166A, 426–433. Fraser, T.W.K., Fjelldal, P.G., Hansen, T., Mayer, I., 2012. Welfare considerations of triploid fish. Rev. Fish. Sci. 20, 192–211. Hansen, T.J., Olsen, R.E., Stien, L., Oppedal, F., Torgersen, T., Breck, O., Remen, M., Vågseth, T., Fjelldal, P.G., 2015. Effect of water oxygen level on performance of diploid and triploid Atlantic salmon post-smolts reared at high temperature. Aquaculture 435, 354–360. Hyndman, C.A., Kieffer, J.D., Benfey, T.J., 2003. The physiological response of diploid and triploid brook trout to exhaustive exercise. Comp. Biochem. Physiol. 134A, 167–179. Jobling, M., Arnesen, A.-M., Benfey, T., Carter, C., Hardy, R., Le François, N., O'Keefe, R., Koskela, J., Lamarre, S., 2010. The salmonids. In: Le François, N., Jobling, M., Carter, C., Blier, P. (Eds.), Finfish Aquaculture Diversification. CABI Publishing, Wallingford, UK, pp. 234–289. Leggatt, R.A., Iwama, G.K., 2003. Occurrence of polyploidy in the fishes. Rev. Fish Biol. Fish. 13, 237–246. Lijalad, M., Powell, M.D., 2009. Effects of lower jaw deformity on swimming performance and recovery from exhaustive exercise in triploid and diploid Atlantic salmon Salmo
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Short communication
Standard metabolic rate of juvenile triploid brook charr, Salvelinus fontinalis Kathleen M. O'Donnell Tillmann J. Benfeya,⁎ a b
a,1
, Krista L. MacRae
a,1
b
MARK
a
, Christine E. Verhille , Charles F.D. Sacobie ,
Department of Biology, University of New Brunswick, P.O. Box 4400, Fredericton, New Brunswick E3B 5A3, Canada Department of Ecology, Montana State University, PO Box 173460, Bozeman, MT 59717-3460, USA
A R T I C L E I N F O
A B S T R A C T
Keywords: Triploidy Cell size Standard metabolic rate Aerobic scope Specific dynamic action
The standard metabolic rates of similarly sized juvenile diploid and triploid brook charr were estimated by using intermittent-flow respirometry to measure oxygen uptake over a 10-day fasting period. Initial oxygen uptake rates did not differ between ploidies, but the rate of decline was slower in triploids, resulting in higher final oxygen uptake rates and, therefore, higher estimated standard metabolic rates. Based on other studies that have shown no effect of triploidy on maximum metabolic rate, this implies reduced aerobic scope in triploids.
1. Introduction Triploid organisms have three sets of chromosomes in their nuclear genomes, rather than the more common two sets in diploids. Among fishes, triploid individuals are occasionally observed within diploid populations as well as within a handful of naturally occurring hybrid complexes that have evolved unique parthenogenetic reproductive strategies (Leggatt and Iwama, 2003). Triploidy can also readily be induced in fish, and the performance of such artificially produced triploids has been studied extensively for the sake of obtaining reproductively sterile populations for aquaculture and fisheries management (Piferrer et al., 2009; Benfey, 2016). In addition to their practical relevance in this regard, artificially produced triploids are also ideal models for studying the effects of cell size and number on basic physiological processes because nuclear volume is increased in proportion to genome size in polyploids, generally with a concomitant increase in cell volume and decrease in cell number (Benfey, 1999). Laboratory studies and larger scale evaluations of triploid performance under aquaculture conditions indicate a reduced tolerance of chronic stress compared to conspecific diploids (Benfey, 1999; Maxime, 2008; Fraser et al., 2012). For instance, Ojolick et al. (1995) observed higher mortality rates in triploid rainbow trout (Oncorhynchus mykiss) compared to diploids following acclimation from 14 to 21 °C, as did Hyndman et al. (2003) in triploid brook charr (Salvelinus fontinalis) following exhaustive exercise in fish that had been acclimated to 19 °C. In both cases, test temperatures exceeded diploid optima (Jobling et al., 2010), suggesting reduced tolerance of high temperature and/or the associated hypoxic conditions that arise from the inverse relationship
⁎
1
Corresponding author. E-mail address: [email protected] (T.J. Benfey). Equal first authors.
http://dx.doi.org/10.1016/j.aquaculture.2017.05.018 Received 31 October 2016; Received in revised form 10 May 2017; Accepted 16 May 2017 Available online 17 May 2017 0044-8486/ © 2017 Elsevier B.V. All rights reserved.
between water temperature and oxygen solubility. This theory has gained support from a number of more recent studies with salmonid species, showing that triploids have maximal routine metabolic rates at lower temperatures than diploids in both Atlantic salmon (Salmo salar) and brook charr (Atkins and Benfey, 2008), triploidy affects the temperature at loss of equilibrium under hypoxia in brook charr (Ellis et al., 2013), cardiac arrhythmia develops at lower temperatures in triploid rainbow trout compared to diploids (Verhille et al., 2013), triploid Atlantic salmon have lower survival, feed intake and growth rate compared to diploids at elevated temperatures, especially under hypoxia, and they modify their swimming behaviour to favour ram irrigation accordingly (Hansen et al., 2015), and triploid rainbow trout have a shorter time to loss of equilibrium than diploids under hypoxia (Scott et al., 2015). Taken together, these prior studies suggest that triploids have reduced aerobic scope, leaving them less able to cope with high metabolic demands (high temperature, exercise, etc.) when oxygen availability is reduced (high temperature, hypoxia, etc.) in comparison to diploids. This same conclusion was drawn from studies of respiratory gas transport in the blood of Chinook salmon (O. tshawytscha) during exhaustive exercise in the absence of a temperature challenge (Bernier et al., 2004). Given that aerobic scope represents the excess aerobic capacity beyond that required to meet basic needs, the aim of this study was to test the hypothesis that triploidy affects standard metabolic rate. This was done by measuring oxygen uptake rates of diploid and triploid brook charr during a 10-day fasting period in the absence of exercise, knowing that this is longer than necessary to bring diploid brook charr to a post-absorptive state (Benfey, 1992). The data obtained using this
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PreSens) that was moved between respirometers. Twenty DO readings were taken for each respirometer at 1-s intervals at the beginning of this closed-system phase and again after an approximate 15-min time interval, and their mean was used to calculate initial and final DO, respectively, for each respirometer for the measured time interval. This was followed by a 10-min open period which started with ⅓ of each respirometer's water being drained and allowing the respirometers to refill three times to flush out any waste and return the DO to saturation levels (~ 10 mg L− 1). The respirometers were then left to overflow until the last minute of the open period, when they were drained by ⅓ again and allowed to refill before being closed. This procedure was repeated 20 times per day, with the last measurement completed at 18:45; this resulted in 20 metabolic rate measurements per day for most fish but, due to equipment malfunctions or human error, some measurements were missed. After the tenth day of testing, fish were removed from their respirometers, anesthetized (as above), measured (body mass and volume) and, once recovered, transferred to a new holding tank in order to keep them separate from the fish that had yet to be tested. A total of 18 fish (9 of each ploidy) were tested in this way, but measurements for three were discarded: one diploid that died on day 8 of the first trial, one triploid that was removed on day 9 of the second trial because it was showing abnormal behaviour, and one triploid from the third trial because of extremely high and variable metabolic rate estimates throughout the 10-day trial, suggesting high levels of spontaneous activity. In the end, full data analysis, as described below, was therefore performed on eight diploid and seven triploid fish. Initial condition factor (K) of each fish (10 days before the first respirometry trial) was calculated as:
approach also allowed an estimation of the metabolic cost of processing each fish's last meal (i.e., specific dynamic action; SDA). 2. Materials and methods All aspects of the following protocol were approved by the UNB Animal Care Committee, adhering to guidelines established by the Canadian Council on Animal Care. Fish were progeny of stock populations reared through multiple generations at the University of New Brunswick's aquatic facilities (Fredericton, NB, Canada). Diploids and triploids were derived from a single fertilization of the pooled eggs from 5 females with the pooled milt from 5 males. Approximately half of the fertilized eggs were maintained as diploid controls and the remainder were treated for triploidy induction by holding them at 65,500 kPa for 5 min in a water-filled pressure chamber (TRC-APVM, TRC Hydraulics Inc., Dieppe, NB, Canada), beginning 29.5 min post-fertilization at an incubation temperature of 6.8 °C. Controls and presumptive triploids were reared under the same conditions, but in separate stage-specific rearing units, using standard husbandry conditions for this species (Jobling et al., 2010) in dechlorinated municipal water that was first passed through degassing/oxygenation columns. Following yolk absorption, fish were fed a standard salmonid grower diet (Corey Nutrition Co., Fredericton, NB, Canada) and maintained under artificial lighting with a seasonally adjusted photoperiod. Ten days prior to the first respirometry trial, all fish were anesthetized in 1% tert-amyl alcohol (A730, Fisher Scientific, Nepean, ON, Canada), measured (body mass to 0.01 g and fork length to 0.1 cm), and tagged with Nonatec RFID transponders (Lutronic International, Luxembourg) inserted into the peritoneal cavity through a hole made using an 18 gauge (1.2 mm) needle. Blood was collected at this time by caudal puncture and used to prepare blood smears for later ploidy analysis based on red blood cell dimensions (Benfey et al., 1984; all fish used for this experiment were subsequently confirmed to be of the assumed ploidy). Fish were then sorted by body mass to minimize size as a confounding factor among test fish, and 24 similarly sized fish (12 per ploidy) transferred to a single 70 L circular tank (50 cm diameter) in order to avoid possible tank effects. Flow rates in this holding tank were maintained at approximately 2 L min− 1 and fish were fed to satiation twice daily, once in the morning and again in the evening, in order to minimize the establishment of feeding hierarchies within the tank. Prior research has shown that feed intake and growth rate are not affected by mixed-ploidy rearing in diploid and triploid brook charr under similar conditions (O'Keefe and Benfey, 1999). Fish were exposed to artificial lighting with a photoperiod appropriate for the latitude and time of year (14 h light, 10 h dark). The fish were 7 months post-fertilization at this time and could not be sexed due to the absence of secondary sexual characteristics in juveniles of this species. Three consecutive respirometry trials were conducted in the same room as the holding tank, each following the same experimental protocol and using the same six identical 180 mL glass intermittentflow respirometers. All measurements were done during daylight hours, with the respirometers isolated from external disturbance by a black plastic barrier. Mean water temperature increased slightly over the course of the trials, from 16.2 ± 0.1 °C (standard error of the mean; SEM) in trial 1 to 16.4 ± 0.2 °C in trial 2 and 17.4 ± 0.2 °C in trial 3. These were identical to the temperature in the holding tank at the time of the trials. At 10:00 on the starting day of a trial, all fish in the holding tank were fed to satiation. Six fish (3 per ploidy) were then haphazardly selected from the tank and each transferred to a separate respirometer, where they were held for the next 10 days. Fish remaining in the holding tank were maintained on the twice-daily feeding regime. All 6 respirometers were closed at 10:30 and the measurement of dissolved oxygen (DO) concentration began using oxygen sensor spots (SP-PSt3NAU-D5-YOP, PreSens Precision Sensing GmbH, Regensburg, Germany) within each respirometer and a fiber optic oxygen transmitter (Fibox 3,
K=
⎛w⎞ ⎜ ⎟ ∗100 ⎝ l3 ⎠
where w is body mass (g) and l is fork length (cm). Mass-specific oxygen uptake rate (MO2) was calculated for each fish for each closed-respirometer period as:
MO2 =
Δ [O2 ] ∗ (VR − VF ) t∗w
where Δ[O2] is change in DO (mg L− 1) during the closed period, VR and VF are respirometer and fish volumes (L), respectively, t is time that the respirometer was closed (h), and w is body mass at the end of the trial (kg). Standard metabolic rate (SMR) was estimated by quantile analysis of MO2 data from days 6 to 10. Previous researchers have used the 0.2 quantile to estimate SMR (Chabot et al., 2016a). However, given that visual inspection showed a high degree of variation in metabolic rates for individual fish within individual days, suggestive of spontaneous activity and/or stress, a range of quantiles (0.10, 0.15, 0.20, and 0.25) was used to estimate SMR. The mean of the lowest normal distribution (MLND) was also considered for determining SMR, but was deemed inappropriate because MLND coefficients of variation ranged from 13 to 35, which are higher than the advised limit of 5.4 (Chabot et al., 2016a). Routine metabolic rate (RMR) was estimated in two ways: by quantile analysis of MO2 data using the 0.50 quantile from days 6 to 10 and by averaging all MO2 measurements from days 6 to 10 and days 8 to 10. Quantiles and MLNDs were calculated using the calcSMR function of the fishMO2 package (Chabot, 2016) in R (R Core Team, 2017). As with SMR and RMR quantification, the relationships between metabolic rate and post-prandial time and the associated variables related to SDA were quantified from analyses of metabolic rate quantiles as well as the full dataset. Metabolic rate response to postprandial times was modelled with no a priori assumptions regarding the shape of the relationship. For both approaches, total post-prandial metabolic cost (SDA; mg O2 kg− 1) was determined by subtracting the area under the SMR curve over the post-prandial duration from the area 86
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Combining the higher triploid SMR and RMR estimates with similar MRpeak estimates during the post-prandial period resulted in reduced MRfactscope for triploids relative to diploids for all analyses, with significant ploidy effects for the same quantile regressions as for MRscope.
under the MO2 model curve. Post-prandial duration (SDAduration; h) was estimated as the time elapsed since feeding until the point where metabolic rate and SMR no longer differed. Peak post-prandial metabolic rate (MRpeak; mg O2 kg− 1 h− 1) and net peak post-prandial metabolic rate (MRscope; mg O2 kg− 1 h− 1) were determined as the highest metabolic rate predicted by the model during the post-prandial duration and this peak value minus SMR (or RMR), respectively. Finally, the factorial increase in metabolic rate at MRpeak (MRfactscope) was calculated as MRpeak divided by SMR (or RMR). For the quantile analyses, quantile regression modelling (Wood, 2011) of SDA, SDAduration, MRpeak, MRscope and MRfactscope was performed using the calcSDA function of the fishMO2 package in R. The my.smr and tau arguments of the calcSDA function specify the SMR and the quantile of metabolic rate data upon which to perform the quantile regression of post-prandial time versus MO2. Combinations of my.smr and tau analyzed, respectively, were 0.15 and 0.10, 0.15 and 0.25, 0.25 and 0.10, 0.25 and 0.25, 0.5 and 0.4, and 0.5 and 0.5. The lambda argument, which is a penalty parameter applied to the quantile regression to control the flexibility of the fitted curve, was set to 100. The postfeed.acclim argument, which assigns the duration after feeding, where SDA analysis is not performed on metabolic rate due to persistence of feeding-related excitement, was set to 5 h. The tol argument, which sets the tolerance around SMR (or RMR) dictating determination of SDAduration, was assigned a value of 5, and the tol.type argument was used to specify the tol as a proportion of SMR (or RMR), i.e., 5%. The MO2.time.unit and X.time.unit arguments, which respectively specify the time units for the metabolic rate values and the SDAduration values, were both set to ‘hour’. The calcSDA function identifies SDAduration as the latest time point after feeding where metabolic rate falls to SMR (or RMR). For three fish, post-prandial metabolic rate dropped to SMR rates and remained low for two or more days, but subsequently increased to exceed SMR rates, presumably due to spontaneous activity or stress rather than SDA. For these three fish, the SDA-related variables were recalculated manually to reflect the first time metabolic rate dropped to SMR and remained there for ≤ 2 days. General additive modelling of the full data set for SDA, SDAduration, MRpeak, MRscope and MRfactscope used the gam function of the mgcv package (Wood, 2011) in R. For these analyses, estimates of basic metabolic (i.e., SMR or RMR) requirements included analysis of all metabolic rates measured from days 8 to 10. As these estimates likely include periods of spontaneous activity and/or stress, they have been referred to as RMR. The effect of ploidy on initial body mass, fork length and condition factor was analyzed by 1-factor ANOVA. Ploidy effects on SMR, RMR, SDA, SDAduration, MRpeak, MRscope, and MRfactscope were analyzed using 1-factor ANOVA with trial as an error term as well as a top down comparison of nested mixed effects models using a chi square test. The full mixed effect model included ploidy as a fixed factor and trial as a random factor. The reduced mixed effect model included only trial as a random factor. For all statistical analyses, alpha values of 0.05 were used to determine significance.
4. Discussion The aim of this study was to determine whether triploidy affects standard metabolism in fish, as estimated from metabolic rate measurements made over a 10-day period without feeding. Although initial measurements would have included the energetic costs of processing the last meal and of responding to the stress of being transferred to the respirometers, previous studies using juvenile brook charr have shown that 10 days without feeding is sufficient to bring these fish to a postabsorptive state (Benfey, 1992), and that triploidy does not affect primary or secondary stress responses to capture and confinement in smaller tanks (Biron and Benfey, 1994; Benfey and Biron, 2000). However, determination of standard metabolism was complicated in this study for two reasons: firstly, although fish were in static respirometers, they were not prevented from swimming, and secondly, measurements were only made during daylight hours. Multiple approaches were therefore used to estimate SMR from these data, ranging from very conservative (i.e., using just the lowest 0.1 quantile of MO2 data) to exceedingly liberal (i.e., using the lowest 0.5 quantile or even all data for the last few days, and therefore more appropriately defined as RMR). Although there was no significant effect of ploidy on measured MO2 in any single analysis, the overall pattern was consistent: triploids always had the higher SMR or RMR estimate. Furthermore, both the absolute and factorial scopes of increase from SMR to peak post-prandial MO2 were always lower for triploids than for diploids, and significantly so for several of the quantile analyses. The temperature which the fish were acclimated to and tested at for this experiment (16–17 °C) was higher than the optimum for juvenile diploids of this size (13 °C; Dwyer et al., 1983) and, by extension, likely even higher than optimum for the triploids (Atkins and Benfey, 2008). The observed effects of triploidy on metabolic rate were therefore likely exacerbated by thermal stress. Taken together with earlier studies showing no effect of triploidy on maximum metabolic rate (Small and Randall, 1989; Stillwell and Benfey, 1997; Lijalad and Powell, 2009; Scott et al., 2015), but reduced thermal tolerance (Ojolick et al., 1995; Hyndman et al., 2003; Verhille et al., 2013; Hansen et al., 2015), these results imply that triploids have reduced aerobic scope due to higher standard metabolism under thermal stress. Triploids differ from diploids in three fundamental ways: their gonadal development is disrupted, they have the potential for greater allelic diversity at every locus, and they have smaller numbers of larger cells in most tissues and organs (Benfey, 1999). Small juvenile fish from a limited gene pool were specifically chosen for this experiment in order to diminish the effects of ploidy on gonadal development and heterozygosity, respectively, and so the higher standard metabolic rate observed in triploids is likely an outcome of their larger cell size or reduced cell numbers. In the absence of a change in cell shape, larger cells have reduced cellular surface area per unit volume, thus affecting surface-limited processes (Choleva and Janko, 2013; Schoenfelder and Fox, 2015). Furthermore, reductions in cell numbers likely affect cell turnover rates and, therefore, tissue/organ maintenance. Triploids may therefore need to maintain higher standard metabolic rates to compensate for a reduced ability to transfer nutrients and metabolites across their cell membranes and to replace (or function with) senescent cells under normal conditions, and this situation may be worsened under conditions that disrupt optimal protein structure or function. In the absence of any changes in metabolic efficiency in triploids, higher standard metabolism could be expected to result in a reduced ability to accumulate energy reserves, and indeed this was recently shown in juvenile brook charr (Sacobie et al., 2016). This may explain
3. Results Although mean body mass and condition factor were noticeably lower for triploids than for diploids when the fish were initially sorted, these differences were not statistically significant (Table 1). Both SMR and RMR were higher for triploids than diploids in all analyses (e.g., Fig. 1), but never significantly so (Table 1). SDA (all analyses) and SDAduration (quantile analyses) were consistently lower and longer, respectively, for triploids than diploids, but again never significantly so. MRpeak values were similar for diploids and triploids, but MRscope was reduced in triploids across all analyses, with significant ploidy effects when using the 0.25 quantile for the quantile regression with the 0.15 and 0.25 quantiles of the SMR estimate, and the 0.4 quantile for the quantile regression with the 0.5 quantile of the RMR estimate. 87
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Table 1 Diploid and triploid juvenile brook charr (Salvelinus fontinalis) size at initial sorting and characterization of metabolic rate (MR) and specific dynamic action (SDA) following a single feeding. Values are mean ± standard error of the mean, with sample sizes of 9 for size measurements, and 8 and 7 (diploids and triploids, respectively) for MR and SDA. Bolded p-values indicate significant differences at an alpha level of 0.05. ANOVA Variable Body mass Fork length Condition factor SMR
RMR
Analysis
q
Quantile
0.1 0.15 0.2 0.25 0.5
SDA
Quantile ALLd6to10 ALLd8to10 Quantile
SDAduration
GAM Quantile
MRpeak
GAM Quantile
MRscope
GAM Quantile
MRfactscope
GAM Quantile
GAM
tau
0.15 0.15 0.25 0.25 0.5 0.5
0.1 0.25 0.1 0.25 0.4 0.5
0.15 0.15 0.25 0.25 0.5 0.5
0.1 0.25 0.1 0.25 0.4 0.5 0.1 0.15 0.2 0.25 0.4 0.5
0.15 0.15 0.25 0.25 0.5 0.5
0.1 0.25 0.1 0.25 0.4 0.5
0.15 0.15 0.25 0.25 0.5 0.5
0.1 0.25 0.1 0.25 0.4 0.5
Diploid 2.93 ± 0.07 6.3 ± 0.2 1.22 ± 0.12 175.1 ± 12.8 187.6 ± 12.7 197.5 ± 13.6 205.7 ± 14.2 240.7 ± 16.8 253.0 ± 18.1 239.3 ± 15.6 8049 ± 2024 13,998 ± 2047 5890 ± 1437 10,483 ± 1608 8912 ± 1170 11,407 ± 1356 13,671 ± 2572 121.0 ± 14.3 188.6 ± 9.3 95.8 ± 15.9 141.6 ± 19.5 127.7 ± 18.1 141.5 ± 17.9 147.7 ± 15.3 320.3 ± 33.4 350.0 ± 32.9 320.3 ± 33.4 398.1 ± 37.1 441.4 ± 41.7 456.7 ± 38.8 510.0 ± 54.3 132.7 ± 28.2 210.5 ± 27.6 114.7 ± 26.0 192.4 ± 24.3 200.7 ± 27.0 216.0 ± 23.8 270.7 ± 45.1 1.71 ± 0.14 2.11 ± 0.11 1.56 ± 0.12 1.92 ± 0.07 1.82 ± 0.08 1.89 ± 0.06 2.12 ± 0.17
Triploid 2.65 ± 0.13 6.4 ± 0.2 1.03 ± 0.08 206.9 ± 18.3 222.4 ± 20.3 234.6 ± 21.4 243.0 ± 21.4 281.5 ± 23.6 291.7 ± 24.7 279.8 ± 26.0 6802 ± 706 12,957 ± 1189 4191 ± 1652 9118 ± 999 7458 ± 1253 10,116 ± 1490 12,468 ± 1904 146.6 ± 18.4 194.2 ± 10.6 107.2 ± 16.3 170.4 ± 8.9 129.8 ± 16.3 160.6 ± 19.8 142.4 ± 16.1 328.4 ± 37.2 354.3 ± 34.6 328.4 ± 37.2 378.7 ± 32.1 430.6 ± 37.5 464.7 ± 42.3 513.9 ± 46.8 106.0 ± 21.0 156.2 ± 19.4 85.5 ± 20.1 135.7 ± 19.6 149.0 ± 27.2 183.1 ± 34.8 234.1 ± 40.1 1.47 ± 0.06 1.72 ± 0.13 1.34 ± 0.06 1.58 ± 0.09 1.55 ± 0.12 1.68 ± 0.16 1.88 ± 0.20
F-ratio 3.42 0.140 1.70 1.738 2.033 2.195 2.261 2.465 1.877 2.479 0.332 0.331 1.417 0.530 1.257 0.737 0.367 0.867 0.065 0.028 1.557 0.019 0.577 0.310 0.041 0.290 0.000 0.096 0.814 0.013 0.003 0.416 2.005 0.659 2.744 2.099 0.831 0.697 1.839 5.478 2.331 8.199 5.593 2.573 1.817
Mixed effect model p-Value 0.083 0.711 0.207 0.212 0.179 0.164 0.159 0.142 0.196 0.141 0.575 0.516 0.257 0.481 0.284 0.407 0.556 0.370 0.803 0.869 0.236 0.894 0.462 0.588 0.844 0.869 1.000 0.762 0.385 0.192 0.960 0.531 0.182 0.433 0.124 0.173 0.380 0.420 0.200 0.037 0.153 0.014 0.036 0.135 0.203
AIC (full/reduced)
χ2-Value
p-Value
159/159 160/161 161/162 161/162 164/165 167/168 165/167 300/298 134/133 291/290 295/294 290/290 295/294 311/309 162/162 304/305 161/159 162/161 164/162 160/159 161/159 184/182 182/180 183/181 179/178 194/193 181/180 189/187 176/174 174/172 174/172 170/173 174/176 177/177 188/187 14/14 12/16 8/9 3/9 7/10 13/13 26/26
2.292 2.726 2.986 3.187 3.461 2.402 2.237 0.344 0.399 1.188 0.736 1.779 0.951 0.268 1.367 0.264 0.134 1.782 0.008 0.897 0.111 0.006 0.0001 0.064 0.799 0.950 0.061 0.249 0.619 4.087 0.844 4.841 4.199 1.865 1.613 2.335 5.989 2.589 7.746 5.155 2.129 1.936
0.130 0.099 0.084 0.074 0.063 0.121 0.072 0.558 0.528 0.276 0.391 0.182 0.329 0.604 0.242 0.605 0.715 0.182 0.928 0.343 0.739 0.936 0.993 0.800 0.371 0.330 0.805 0.618 0.431 0.043 0.358 0.028 0.040 0.172 0.204 0.126 0.014 0.108 0.005 0.023 0.145 0.164
SMR: standard MR; RMR: routine MR; SDAduration: time elapsed since feeding until MR and SMR (or RMR) no longer differed; SDA: total post-prandial metabolic cost; MRpeak: peak postprandial MR; MRscope: increase in MR from SMR (or RMR) to MRpeak; MRfactscope: factorial increase in SMR (or RMR) at MRpeak; q: quantile of the day 8 to 10 MR data used to determine SMR or RMR; tau: quantile of SDA data used to perform the additive quantile regression analysis (i.e., the relationship between MR and time after feeding); ANOVA: one-way ANOVA test with ploidy as the factor and trial as an error term; Mixed effect model: top down χ2 comparisons including ploidy as a fixed effect and trial as a random effect with a nested model including only trial as a random effect; ALLd6to10 and ALLd8to10: RMR using all data for days 6 to 10 and days 8 to 10, respectively, after feeding; GAM: general additive model with a gamma distribution to determine the relationship between MR and time after the meal.
triploids required less energy to process their last meal than diploids, but they took longer to do so. The only other study to estimate SDA in triploid salmonids found no effect of ploidy (rainbow trout; Oliva-Teles and Kaushik, 1987). Conducted properly, SDA measurements are made by feeding previously food-deprived fish within the respirometer, thereby both minimizing the metabolic cost of the stress of transferring fish to the respirometer and also measuring the initial cost of ingesting and processing food (Chabot et al., 2016b). Thus, SDA measurements should include the integrated area under the curve bound by standard metabolism for both increasing and decreasing MO2 following the meal. There was no observable increase in metabolic rate at the start of the current study, likely due to the combination of initial handling stress and not starting measurements at the time of feeding. As a result, only the decreasing phase of SDA was measured. The SDA data in this study thus represent just a crude estimation of true SDA.
the frequent observation of lower condition factor in triploids (Piferrer et al., 2009), and supports the suggestion that triploids should have diets tailored to meet their specific nutritional requirements (Tibbetts et al., 2013; Benfey, 2016; Smedley et al., 2016). Higher standard metabolism would also imply trade-offs with respect to directing limited energy reserves towards specific functions, thus providing an explanation for lower titres of heat shock proteins in triploids (Saranyan et al., 2017). Under optimum conditions, a diminished capacity to mount an HSP-mediated stress response may not be of any significance, but coupling this with lower aerobic scope – itself an outcome of higher standard metabolism – provides a testable hypothesis for why triploids have a diminished ability to withstand high temperature and hypoxia. Although not a goal of this study, the experimental design also allowed for the estimation of SDA. Similar to SMR and RMR, the various analyses that were conducted showed a consistent effect of ploidy, i.e., 88
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Metabolic Rate (mg O2 kg -1 h -1)
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Time after Feeding (h) Fig. 1. Predicted metabolic rate of diploid (2N) and triploid (3N) juvenile brook charr (Salvelinus fontinalis) following a single feeding (solid lines) and estimated standard metabolic rate (SMR; dashed lines) with 95% confidence intervals (in A) or standard errors (in B) around the means (dotted lines). The metabolic response to feeding was predicted by analyzing the relationship between time after feeding and metabolic rate, with the two ploidies analyzed separately. In A, SDA was modelled as an additive quantile regression using the rqss function of the quantreg package and with time after feeding as an additive nonparametric component (Wood, 2011) in R. Arguments specified within the rqss function included a tau of 0.25, lambda value of 100, and SMR was estimated as the 0.15 quantile of metabolic rate data from days 6 to 10 after feeding. In B, SDA was modelled as a general additive model using the gam function of the mgcv R package (Wood, 2011). Arguments included a k value of 3 and a ‘tp’ bases, and SMR was estimated as the average of all metabolic rate measurements on days 8 through 10 after feeding.
undergraduate Honours thesis project in Biology at UNB (KMO), and was supported financially by the Natural Sciences and Engineering Research Council of Canada (46180-2011), through both a Discovery Grant (TJB) and an Undergraduate Student Research Award (KMO), and by the New Brunswick Innovation Fund, through the Research Assistantships Initiative (KLM).
In conclusion, triploid brook charr were shown by multiple analyses to have a higher standard metabolic rate than diploids at above optimum temperature, although not significantly so by any single analysis. This suggests that they (a) have lower aerobic scope and (b) divert proportionately more dietary energy to maintenance than to growth compared to diploids at this temperature. Optimizing triploid performance at elevated temperatures should therefore focus on minimizing aerobic stresses on the animals and providing them with diets that favour energy storage in forms that are readily mobilized. Followup experiments to assess aerobic scope at a range of temperatures around the optimum are warranted.
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Acknowledgements This study was designed to build upon concepts developed and results obtained in partial fulfillment of the requirements for an 89
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