Growth and IGF-I response of juvenile Nile tilapia (Oreochromis niloticus) to changes in water temperature and dietary protein level

Growth and IGF-I response of juvenile Nile tilapia (Oreochromis niloticus) to changes in water temperature and dietary protein level

Journal of Thermal Biology 37 (2012) 686–695 Contents lists available at SciVerse ScienceDirect Journal of Thermal Biology journal homepage: www.els...

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Journal of Thermal Biology 37 (2012) 686–695

Contents lists available at SciVerse ScienceDirect

Journal of Thermal Biology journal homepage: www.elsevier.com/locate/jtherbio

Growth and IGF-I response of juvenile Nile tilapia (Oreochromis niloticus) to changes in water temperature and dietary protein level J. Qiang a,b, H. Yang a,b, H. Wang c, M.D. Kpundeh a, P. Xu a,b,n a

Wuxi Fisheries College, Nanjing Agricultural University, Wuxi 214081, China Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization, Ministry of Agriculture, Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Wuxi 214081, Jiangsu, China c Fisheries College, Guangdong Ocean University, Zhanjiang 524025, China b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 16 June 2012 Accepted 31 July 2012 Available online 23 August 2012

Water temperature and dietary protein level play an important role in influencing the growth and insulinlike growth factor I (IGF-I) in Nile tilapia juveniles. The combined effect of temperature (20–34 1C) and dietary protein level (25–50%) on the specific growth rate (SGR), feed efficiency (FE), serum IGF-I level and hepatic IGF-I mRNA level was examined under laboratory conditions by employing central composite design and response surface method. Results showed that the linear effects of temperature and dietary protein level on the SGR, FE, serum IGF-I and hepatic IGF-I mRNA level were significant (Po0.05); the quadratic effects of temperature and dietary protein level on the FE and serum IGF-I were significant (Po0.05). The interaction of temperature and dietary protein level on the FE, serum IGF-I and hepatic IGF-I mRNA level all proved significant (Po0.05). The optimal temperature/dietary protein level combination was determined, i.e., 29.9 1C/40.3%, at which the greatest SGR (2.748%/d) and FE (0.775) were simultaneously arrived. Both SGR and FE were linearly correlated with serum IGF-I or hepatic IGF-I mRNA level. These results suggested that optimum combination of temperature and dietary protein level would enhance tilapia growth efficiency and IGF-I would regulate growth and FE. & 2012 Elsevier Ltd. All rights reserved.

Keywords: Nile tilapia (Oreochromis niloticus) Water temperature Dietary protein level Growth Insulin-like growth factor I Response surface

1. Introduction The quality and high yield of commercial fishes are intimately related to feed quality, feeding regime and the rearing environment. Typically, protein makes up a larger proportion of the feed, and at the same time is also one of the most important dietary nutrients (Singh et al., 2006). The intake of proteins is advantageous for tissue renewal/repair and metabolism in fish (Alvarez-Gonzalez et al., 2001). When the level of dietary proteins is greater than 40%, the growth of tilapia juveniles will be promoted (Al Hafedh, 1999); whereas deficiency of dietary proteins can affect tilapia growth and survival (Al Hafedh, 1999), gonadal vitelline development (Gunasekera and Lam, 1997), and fertilization (El-Sayed and Kawanna, 2008). Therefore, higher levels of protein is typically needed in fish feed. For instance, a dietary protein level of 50% is required by juvenile starry flounder, Platichthys stellatus (Lee, 2006); 38–45% by juvenile black sea bream, Sparus macrocephalus (Zhang et al., 2010); and 50% by juvenile silver pomfret, Pampus argenteus (Hossain et al., 2010).

n Corresponding author at: Wuxi Fisheries College, Nanjing Agricultural University, Wuxi 214081, China. Tel./fax: þ 86 510 85557959. E-mail address: [email protected] (P. Xu).

0306-4565/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jtherbio.2012.07.009

The requirement of dietary proteins for aquatic animals is closely associated with water temperature (Peres and Oliva-Teles, 1999; Singh et al., 2009), salinity (Perez-Velazquez et al., 2007), size (Abdel-Tawwab et al., 2010), rearing density (Omar et al., 1997), dietary lipid level (Carmona-Osalde et al., 2005), dietary energy (Pirozzi et al., 2010), sources of protein (Garcia and Villarroel, 2009; Zheng et al., 2011), and so forth. Temperature is a crucial factor in aquaculture; it has direct impacts on fish biochemical reactions (Streit Jr et al., 2010). Singh et al. (2008) found that when water temperature ranged between 28 1C and 32 1C, the dietary protein requirement for mrigal Cirrhinus mrigala fry was 36%, and the protein utilization rate was higher at dietary protein level of 28%. When water temperatures were 15 1C and 20 1C, optimal protein level of sea bass juveniles Dicentrarchus labrax was 50%, but the daily protein requirement and food intake were markedly higher at 20 1C than at 15 1C (Hidalgo and Alliot, 1988). Increasing water temperature quickens the fish energy metabolism within certain range (Likongwe et al., 1996). There have been many reports on the influence of water temperature or dietary protein level upon the growth and feed utilization in tilapia (Abdel-Tawwab et al., 2010; Al Hafedh, 1999; Azaza et al., 2008; Likongwe et al., 1996). Using factorial experimental design, Musuka et al. (2009), examined the effect of dietary protein requirement and water temperature on the growth performance of Tilapia rendalli; this is the only report in

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terms of the influence of dietary protein level at differing water temperatures in tilapia so far. Neuroendocrine factors play a role in regulating and controlling fish growth and energy metabolism (Beckman et al., 2004). Growth hormone (GH), insulin-like growth factor (IGF-I) and insulin, are three important neuroendocrine factors that can contribute greatly to growth and metabolism (Planas et al., ˜ os et al., 1999). GH level can directly affect the secretion 2000; Ban of IGF-I in liver. The production and secretion of these hormones are directly or indirectly related to some exogenous factors, such as nutritional status (Cameron et al., 2007; Riley et al., 2009; Enes et al., 2010; Jiang et al., 2010), feeding frequency (Petersona et al., 2009), water temperature (Imsland et al., 2007), salinity (Taylor et al., 2008), photoperiod (Cruz and Brown, 2009) and season (Davis and McEntire, 2006). For example, increased water temperature led to an increased plasma IGF-I levels in Chinook salmon Oncorhynchus tshawytscha (Beckman et al., 1998), turbot Scophthalmus maximus (Imsland et al., 2007), sunshine bass (Morone chrysops  Morone saxatilis) (Davis and McEntire, 2011); as well as increased hepatic IGF-I mRNA level in Nile tilapia, Oreochromis niloticus (Vera Cruz et al., 2006). Dietary protein level is also closely correlated with the level of GH and IGF-I (Pe´rez-Sa´nchez et al., 1995; Dyer et al., 2004). No reports have been found thus far, however, on the interactive effect between water temperature and dietary protein level on growth, feed efficiency, serum IGF-I and hepatic IGF-I mRNA level in Nile tilapia. In order to gain a better understanding of growth and IGF-I response in the Nile tilapia under different temperatures and dietary protein levels, this study was conducted and aimed at examining: (i) the combined effect of water temperature and dietary protein level on growth, feed efficiency, serum IGF-I and hepatic IGF-I mRNA level in Nile tilapia juveniles under laboratory conditions; (ii) the quadratic effect of the above two factors and predictive model equations of growth, feed efficiency, serum IGF-I and hepatic IGF-I mRNA level towards water temperature and dietary protein level; (iii) the relationship of growth and feed efficiency to serum IGF-I and hepatic IGF-I mRNA level. This study was conducted to provide scientific basis for growth regulation in Nile tilapia.

2. Materials and methods 2.1. Experimental fish Healthy Nile tilapia juveniles, of the 16th generation of the Genetically Improved Farm Tilapia (GIFT) strain, were obtained as

687

experimental fish from Yixing, the experimental base of Freshwater Fisheries Research Center of Chinese Academy of Fishery Sciences. Prior to the experiment, these fish were acclimatized for 10 days in an indoor cement pool with water temperature 27 1C70.3, under natural photoperiod and continuous aeration using recirculating water. The fish were trained to accept submerged feed (crude protein 37.5%, fat 8.0%). 2.2. Experimental design In order to examine the relationship between the responses, which were the specific growth rate (SGR), feed efficiency (FE), serum IGF-I level and hepatic IGF-I mRNA level, and the factors of interest, which were temperature and dietary protein level, central composite design was used in this experiment. Temperature ranged from 20 1C to 34 1C, and dietary protein level ranged from 25% to 50% (Proximate composition of the experimental diets was determined using AOAC (2000) procedures). Each factor has five coded levels with this central composite design:  a, 1, 0, 1, a, respectively, with a being the star arm. The numbers of factorial and axial points are four and four, respectively. The number of center points was set equal to five, thus the star arm a ¼ 71.41421 in this case. The total number of experimental runs was 13, and each run was replicated thrice. See Table 1 for coded and actual combinations of temperature and dietary protein levels. 2.3. Acclimatization of experimental fish The acclimatization of experimental fish to temperature was conducted in plastic buckets (1.2 m3) in a progressive fashion, with a temperature increase or decrease of about 2 1C each day. After acclimatized to the temperatures as set up in Table 1, experimental fish continued to be reared for 7 days under this regime. Temperatures were controlled using electronic thermostat rods (range 18–36 1C). 2.4. Experimental management A total of 39 plastic buckets (1.2 m3 each) were used in the experiment, with each experimental run having three buckets or replicates. Volume (1 m3) of tap water that had been aerated consecutively for 3 day was added to each of the 39 plastic buckets into which also a 300-W submersible pump was put for the purposes of water filtration and recirculation. The temperatures were adjusted to the corresponding ones as in Table 1.

Table 1 Experimental design of temperature-dietary protein level combinations and response observations (Mean 7SD) (n¼ 15). Run

1 2 3 4 5 6 7 8 9 10 11 12 13

Coded

Actual

T

P

T(1C)

P (%)

0 1 0 0 1 0 0 0

0 1 a 0 1 0

27.0 22.1 27.0 27.0 22.1 27.0 27.0 27.0 34.0 20.0 31.9 27.0 31.9

37.5 28.7 25.0 37.5 46.3 37.5 50.0 37.5 37.5 37.5 46.3 37.5 28.7

a a 1 0 1

a 0 0 0 1 0 1

SGR (%/d)

FE

Serum IGF-I (ng/mL)

Hepatic IGF-I mRNA/b-actin mRNA

2.454 70.147 1.501 70.102 1.989 70.151 2.503 70.217 1.764 70.146 2.378 70.152 2.484 70.163 2.526 70.231 2.330 70.205 1.408 70.107 2.991 70.271 2.597 70.219 2.570 70.248

0.757 7 0.068 0.436 7 0.032 0.576 7 0.042 0.782 7 0.071 0.6057 0.055 0.8037 0.063 0.7037 0.072 0.752 7 0.061 0.629 7 0.047 0.391 7 0.026 0.683 7 0.055 0.741 7 0.058 0.772 7 0.073

28.429 74.154 17.283 72.951 24.251 73.817 28.639 74.284 17.538 73.026 30.412 74.160 22.492 73.281 28.635 73.942 23.389 73.229 15.232 71.902 23.511 72.763 29.418 74.751 29.702 74.095

3.869 7 0.927 1.5037 0.414 2.851 7 0.832 3.927 7 0.963 1.0007 0.311 3.562 7 1.027 2.0527 0.615 3.693 7 1.094 2.916 7 1.135 1.0457 0.322 2.758 7 0.681 3.722 7 0.775 3.674 7 0.892

Note: a is star arm, and 9a9¼ 1.41421 for this experimental design.

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Forty-five fish were contained in each experimental run, with each replicate having fifteen individuals. The body weight and body length of the experimental fish used were 27.64 (71.09 g) and 9.43 ( 70.46 cm), respectively. Results of MANOVA showed that there was no significant difference between various experimental runs and between all replicates (P40.05). The feed that with differing levels of protein was given as prescribed in Table 2. Fish were offered experimental diets to apparent satiation three times daily (7:00 h, 11:30 h and 16:00 h), six days a week. Fish were considered satiated when two to three pellets feed were not consumed within 3 min after being offered. The amount of feed consumed by each group was subsequently calculated as summation of given diets during the experimental period. Fish in each bucket were fortnightly group-weighed. Continuous aeration was ensured during the entire experimental period. Fish feces were siphoned out every day. Water (1/3) was replaced after every 3 days, with a temperature difference of 70.3 1C. Dissolved oxygen was greater than 5 mg/L; pH was 7.470.2; ammonia-N and nitrite were both less than 0.01 mg/L. The whole experiment was carried out under natural photoperiod and lasted for 56 days; from 1 November 2011 to 26 December 2011. 2.5. Measurement of response Feeding stopped 24 h before the conclusion of experiment, and the data measurement of all the fish within each experimental run was done on the second day. SGR and FE were computed as follows: SGRð%=dÞ ¼ ½ðlnW 2 lnW 1 Þ=ðt 2 t 1 Þ  100 FE ¼ ðW 2 W 1 Þ=F where W1, W2 are body weights (g) at starting (t1) and ending time (t2) of the experiment, respectively; F is total feeding amount (g). To avoid changes in measurement index induced by stress, fish were killed with an overdose of tricaine methanesulfonate (2%; MS-222) within 1 min after being captured. Blood samples were collected from the caudal vein of five fish in each plastic Table 2 Ingredients and composition of experimental diets. Ingredients

Dietary protein level (%) (g/100 g dry diet) 25.0

28.7

37.5

46.3

50.0

Fish meal Casein Gelatin Corn starch Fish oilþ soybean oil (1:1) Soybean meal cottonseed meal Rapeseed meal Vitamin premix1 Mineral premix2 Choline chloride Vitamin C phosphate ester Ca(H2PO4)2 Total

5.00 4.00 1.00 36.80 7.00 12.00 15.00 15.00 1.00 1.00 0.50 0.20 1.50 100

5.00 7.60 1.90 32.30 7.00 12.00 15.00 15.00 1.00 1.00 0.50 0.20 1.50 100

5.00 16.20 4.05 21.55 7.00 12.00 15.00 15.00 1.00 1.00 0.50 0.20 1.50 100

5.00 23.80 5.95 12.05 7.00 12.00 15.00 15.00 1.00 1.00 0.50 0.20 1.50 100

5.00 27.50 6.88 7.42 7.00 12.00 15.00 15.00 1.00 1.00 0.50 0.20 1.50 100

Proximate composition (%) Dry matter Crude protein Crude lipid Ash Gross energy (kJ/g diet)

91.57 25.16 7.87 6.23 12.90

91.68 28.95 7.89 6.38 12.97

91.74 38.04 7.93 6.64 13.12

91.94 46.09 7.97 6.87 13.26

92.05 49.92 7.99 6.92 13.31

Note:(1) Vitamin premix (mg/kg dry diet):VA 10, VD 0.05,VE 400, VK 40, VB1 50, VB2 200,VB3 500, VB6 50, VB7 5, VB11 15, VB12 011,VC1000, inositol 2000, choline 5000; (2) Mineral premix (mg/kg dry diet): FeSO4  7H2O 372, CuSO4  5H2O 25, ZnSO4  7H2O 120, MnSO4  H2O 5, MgSO4 2475, NaCl 1875, KH2PO4 1000, Ca (H2 PO4)2 2500.

bucket. All blood samples were kept for 2 h in a refrigerator at 4 1C, were then centrifuged for 10 min at 4 1C and 3500 rpm to obtain the serum. The supernatant was transferred and held in refrigerator at  80 1C for further use. Another five fish samples were collected from each plastic bucket, and some 0.1 g liver were obtained and immediately frozen in liquid nitrogen, then stored at  80 1C until measurement of IGF-I mRNA levels. 2.6. Serum IGF-I level assay Serum IGF-I was measured using the fish insulin-like growth factor I radioimmunoassay (RIA) kit from Tianjin Nine Tripods Medical & Bioengineering Co., Ltd. (Tianjin, China). Fish RIA kits follow acid:ethanol extraction as described in Taylor et al. (2005). The resultant supernatant was collected and 50 mL assay collected for analysis, following the manufacturer’s protocol. The minimum detection limit was 0.15 ng/mL, with intra- and inter-assay coefficient of variation of 4.4% and 13.9%, respectively. 2.7. Real-time quantitative PCR (qPCR) Tissue mRNA expression levels were determined by qPCR. Primers for qPCR were designed with reference to the known sequences of tilapia as given in Table 3. All primers were synthesized by Shanghai Genecore, BioScience & Technology Company, China. The PCR products were 100–110 bp long. We extracted total RNA from the tissue using Trizol reagent (Dalian Takara Co. Ltd., China). RNA samples were treated with DEPC water (Dalian Takara Co. Limited, China). The quantity of the RNA was calculated using the absorbance at 260 nm. The integrity and relative quantity of RNA were checked by electrophoresis. We generated cDNA from 350 ng RNA using PrimeScript RT reagent Kit Perfect Real Time kit (Dalian Takara). PCR amplification was conducted using an ABI 7900HT Fast Real-Time PCR System (ABI, USA) and SYBR Green PCR Master Mix (ABI), according to the manufacturer’s instructions. The amplifications were performed in a 96-well plate in a 25 mL reaction volume containing 12.5 mL of 2  SYBR Green PCR Master Mix, 0.5 mL (each) of the forward and reverse primers (10 mM), 2 mL of template and 9.5 mL of DEPC water. qPCR was performed as follows: denaturizing at 95 1C for 5 min; 40 cycles for denaturizing at 95 1C for 15 s, annealing at 62 1C for 60 s. We calculated the relative quantification of the target gene transcript IGF-I with a chosen reference gene transcript (b-actin) using the 2-DDCT method. This mathematical algorithm computes an expression ratio based on real-time PCR efficiency and the crossing point deviation of the sample versus the control. We measured the PCR efficiency by constructing a standard curve using a serial dilution of cDNA. The PCR efficiency for all assay was 498%. A no template control (NTC) and no reverse transcriptase control (NRT) were used as control for template and genomic contamination, respectively. All samples were run in triplicate. Values of IGF-I mRNA were then expressed relative to the lowest sample level (control) measured within an experiment (assigned an arbitrary value of 1).

Table 3 Primer sequences. Target mRNA

Sequence

NCBI Genbank accession no.

IGF-I

F: 50 - TTGTCTGTGGAGAGCGAGGCTT-30 F: 50 - CAGCTTTGGAAGCAGCACTCGT-30 F: 50 -CCACACAGTGCCCATCTACGA-30 R: 50 -CCACGCTCTGTCAGGATCTTCA-30

XM003448059

b-actin

EU887951.1

J. Qiang et al. / Journal of Thermal Biology 37 (2012) 686–695

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2.8. Data processing Experimental data were recorded in terms of mean ( 7SD). The following form of the relationship between the responses and the factors of interest was assumed:

2.48

where Y^ is the prediction of response (SGR, FE, serum IGF-I or hepatic IGF-I mRNA level); b0 is regression constant; b1, b2, linear effects of temperature and dietary protein level, respectively; b3, interactive effect between temperature and dietary protein level; b4, b5, quadratic effects of temperature and dietary protein level, respectively. All these effects were estimated using the least squares method. STATISTICA (v 8.0) Software was used for plotting and analyzing the experimental data. Correlations between SGR, FE, serum IGF-I and hepatic IGF-I mRNA level were tested using Pearson’s product-moment correlations of the SPSS software (v15.0) and drawing were done using Microsoft excel. Significance level was set at Po0.05.

Specific growth rate (%d

)

Y^ ¼ b0 þ b1 T þb2 P þ b3 T  P þ b4 T 2 þ b5 P 2

3.00

1.95 1.43 0.90

50.0

34.0 43.8

Die

tar

yp

Fig. 1. Response surface plot of the effect of temperature and dietary protein level and their mutual interactions on SGR of Nile tilapia juveniles (n¼ 15).

The experimental results of SGR are listed in Table 1, and the least squares estimates of regression coefficients are displayed in Table 4. Using ANOVA, the P value for the model of SGR was 0.0031, showing that the model of SGR built was of high significance. The P value for the lack-of-fit test of the model was 0.0993, showing that the model was adequate. From Table 4, the linear and quadratic effect of water temperature on SGR was highly significant (P o0.01); the linear effect of dietary protein level on SGR was highly significant (Po0.01), but the quadratic effect was insignificant (P40.05); the interaction between the two factors of interest was also not significant (P40.05). According to the magnitude of coded coefficients, water temperature was more crucial than dietary protein level. The actual model equation derived was as follows: 2

SGR ¼ 8:8079 þ 0:583T þ 0:0927P þ 0:001TP0:0096T 0:0013P

2

The coefficient of determination of the model R2,0.958, demonstrating that this model equation was of high goodness of fit to experimental data. In order to visualize how SGR is simultaneously affected by water temperature and dietary protein level, response surface plot was drawn (Fig. 1). It could be seen clearly that under the conditions of the experiment, SGR varied with increased water temperature and dietary protein level in a curvilinear manner. The SGR was greater at higher protein levels than at lower protein Table 4 Significance, standard error and confidence interval of regression coefficients for SGR model. Term

Intercept T P TP T2 P2

Regression coefficient

Standard error

95%C.I. Low

95% C.I. High

P value

– o 0.0001 0.0060 0.5506 0.0017 0.0710

2.492 0.485

0.056 0.045

2.358 0.380

2.625 0.591

0.173 0.040  0.235  0.102

0.045 0.063 0.048 0.048

0.068  0.110  0.348  0.215

0.278 0.189  0.122 0.011

37.5 27.0 ) °C e( ein r 31.3 23.5 u t lev era el 25.0 20.0 (% mp e ) T

rot

3. Results 3.1. Effects of water temperature and dietary protein level on SGR of Nile tilapia juveniles

30.5

Note: coefficients were given in terms of coded factors. R2 ¼ 0.958, adjusted R2 ¼0.928.

Table 5 Significance, standard error and confidence interval of regression coefficients for FE model. Term

Regression coefficient

Standard error

95%C.I. Low

95%C.I. High

P value

Intercept 0.767 T 0.094 P 0.032 TP  0.065 T2  0.116

0.016 0.013 0.013 0.018 0.014

0.728 0.063 0.002  0.108  0.149

0.806 0.124 0.063  0.021  0.083

P2

0.014

 0.084

 0.019

– 0.0002 0.0404 0.0096 o 0.0001 0.0076

 0.051

Note: coefficients were given in terms of coded factors. R2 ¼ 0.955, adjusted R2 ¼ 0.923.

levels regardless of water temperature differences. For example, SGR was notably higher when protein level was 45% than when protein level was 25%, with water temperature held at 27 1C.

3.2. Effects of water temperature and dietary protein level on FE of Nile tilapia juveniles The observed data of FE are provided in Table 1, and the model coefficients estimated using least squares approach are presented in Table 5. It was found via ANOVA that the model of FE was highly significant (P ¼0.0001); the P value for the lack-of-fit test was 0.1231, showing that the model of FE was of great adequacy; the linear and quadratic effects of water temperature on FE were all highly significant (P o0.01); the linear effect of dietary protein level on FE was significant (Po0.05), and the quadratic effect was highly significant (Po0.01); the interaction between the two factors was also highly significant (P o0.01). Water temperature was more important than dietary protein level in influencing FE. The actual model equation of FE attained was as follows: FE ¼ 5:7582 þ 0:3303T þ 0:0929P0:0015TP0:0047T 2 0:0007P2

with the coefficient of determination as high as R2 ¼0.955.

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J. Qiang et al. / Journal of Thermal Biology 37 (2012) 686–695

From Fig. 2, it could be seen that FE varied curvilinear with both water temperature and dietary protein level. For instance, with water temperature ranging between 20 1C and 29 1C and protein level kept at 37.5%, FE increased as water temperature increases; when water temperature was higher than 29 1C, FE began to decrease. With water temperature held at 27 1C and protein level ranged between 25% and 40%, FE gradually increased as dietary protein level increases; as dietary protein levels were higher than 40%, FE began to decrease. When water temperature and protein level lay at the combination of 28.9 1C/38.2%, a larger FE, 0.786, was reached. 3.3. Effects of water temperature and dietary protein level on serum IGF-I level in Nile tilapia juveniles Estimates of regression coefficients and their significance (Table 6) were obtained through statistical analysis for the experimental results of serum IGF-I level, as shown in Table 1. Outputs of ANOVA showed that the model equation of serum IGF-I level was highly significant (Po0.01) and adequate (P¼0.1042 for the lack-of-fit test); the linear and quadratic effects of water temperature on serum IGF-I level were highly significant (Po0.01); the linear effect of dietary protein level on serum

IGF-I was significant (Po 0.05), and the quadratic effect proved highly significant (Po0.01); the interaction between the two factors was also significant (Po0.05); water temperature was more critical than dietary protein level in affecting serum IGF-I. The actual model equation secured was as follows: Serum IGF-I ¼ 213:5159þ 12:5650T þ 3:4680P 0:0368TP0:1931T 2 0:0346P2 the coefficient of determination arrived at was R2 ¼0.967 It could be seen from Fig. 3 that serum IGF-I level varied with both water temperature and dietary protein level in a curvilinear fashion. For example, with water temperature ranged between 20 1C and 29 1C and dietary protein level kept at 37.5%, serum IGF-I level increased as water temperature increases; but when water temperature was higher than 29 1C, serum IGF-I level began to decrease. At water temperature of 27 1C and dietary protein level between 25% and 36%, serum IGF-I level gradually increased as dietary protein level was increasing; while dietary protein level higher than 36%, resulted to a gradual decrease in serum IGF-I. When water temperature and dietary protein level lay at the combination, 29.2 1C/34.6%, a larger serum IGF-I level, 30.122 ng/mL, was observed. 3.4. Effects of water temperature and dietary protein level on the hepatic IGF-I mRNA level of Nile tilapia juveniles

79.00

The observed results of hepatic IGF-I mRNA levels are provided in Table 1, and the model coefficients estimated using least squares approach are presented in Table 7. It was found via ANOVA that the model of hepatic IGF-I mRNA levels was highly significant (P¼ 0.0001); the P value for the lack-of-fit test was 0.1334, showing that the model of hepatic IGF-I mRNA levels was of great adequacy. The linear effect of water temperature on IGF-I mRNA levels was highly significant (Po0.01), but the quadratic effect was insignificant (P 40.05); the linear and quadratic effect of dietary protein level on IGF-I mRNA levels was highly significant (Po0.01); and the interaction between the two factors of interest was also highly significant (Po0.01). Water temperature was more crucial than dietary protein level. The following actual

45.50 28.75 12.00

50.0

34.0

Fig. 2. Response surface plot of the effect of temperature and dietary protein level and their mutual interactions on FE of Nile tilapia juveniles (n¼ 15).

Table 6 Significance, standard error and confidence interval of regression coefficients for serum IGF-I model. Term

Intercept T P TP T2 P2

Regression coefficient 29.107 3.741  1.053  1.612  4.731  2.701

Standard error 0.559 0.442 0.442 0.625 0.474 0.474

95%C.I. Low 27.784 2.695  2.099  3.091  5.853  3.822

95%C.I. High 30.430 4.787  0.007  0.132  3.610  1.579

31.00

el (ng/ml)

30.5 Die 43.8 tar ) yp 37.5 27.0 °C rot e( ein r u 31.3 t 23.5 lev era el (% mp 25.0 20.0 e ) T

Serum IGF-I lev

Feed efficiency

62.25

25.00 19.00 13.00 7.00

P value

– o 0.0001 0.0488 0.0367 o 0.0001 0.0007

Note: coefficients were given in terms of coded factors. R2 ¼ 0.967, adjusted R2 ¼0.943.

50.0 Die 43.8 tar y p 37.5 rot ein lev 31.3 el (% )

34.0 30.5

)

27.0 23.5 25.0 20.0

re atu

(°C

er

mp

Te

Fig. 3. Response surface plot of the effect of temperature and dietary protein level and their mutual interactions on serum IGF-I level of Nile tilapia juveniles (n¼ 15).

J. Qiang et al. / Journal of Thermal Biology 37 (2012) 686–695

Table 7 Significance, standard error and confidence interval of regression coefficients for hepatic IGF-I mRNA model. Term

Regression coefficient

Standard error

95%C.I. Low

95%C.I. High

P value

Intercept T P TP T2 P2

4.755 0.822  0.319  0.103  0.883  0.647

0.093 0.073 0.073 0.104 0.079 0.079

4.535 0.648  0.492  0.349  1.069  0.833

4.974 0.995  0.145 0.142  0.697  0.461

– o 0.0001 o 0.0001 0.0034 0.3529 o 0.0001

Note: coefficients were given in terms of coded factors. R2 ¼ 0.978, adjusted R2 ¼0.963.

4.00

691

3.6. Relationship of serum IGF-I level and hepatic IGF-I mRNA level to SGR and FE Serum IGF-I level was found to be positively correlated with SGR (Fig. 5), with correlation coefficient r¼ 0.768 (Po0.01). The regression of serum IGF-I level towards SGR was serum IGFI¼ 8.6416 SGRþ 4.9267 Hepatic IGF-I mRNA level was found to be positively correlated with SGR (Fig. 6), with correlation coefficient r ¼0.751 (Po0.01). The regression of hepatic IGF-I mRNA level towards SGR was hepatic IGF-I mRNA level ¼1.7195SGR  1.1146. Serum IGF-I level was also found to be positively correlated with FE (Fig. 7), with correlation coefficient r ¼0.911 (Po0.01). The regression of serum IGF-I level towards FE was serum IGF-I ¼36.189 FE þ0.509. Hepatic IGF-I mRNA level was also found to be positively correlated with FE (Fig. 8), with correlation coefficient r ¼0.835 (P o0.01). The regression of hepatic IGF-I mRNA level towards FE was hepatic IGF-I mRNA level ¼ 6.8477 FE  1.7326.

4. Discussion 1.60

4.1. Effects of water temperature on SGR and FE in Nile tilapia juveniles

0.40

Water temperature plays a crucial role in food digestibility in fish. Higher temperature contributes to increased food intake and feed utilization, and in turn to intestinal digestion and absorption

-0.80

50.0

35

34.0

30.5 Die 43.8 tar ) yp 37.5 27.0 (°C rot e r ein tu 23.5 lev 31.3 era el mp 25.0 20.0 e (% T ) Fig. 4. Response surface plot of the effect of temperature and dietary protein level and their mutual interactions on hepatic IGF-I mRNA level of Nile tilapia juveniles (n¼ 15).

Serum IGF-I levels (ng/mL)

Hepatic IGF-I mRNA /-actin mRNA

2.80

28 21 14 Serum IGF-I = 8.6416SGR + 4.9267 r = 0.768

7

model equation was obtained: Hepatic IGFI mRNA levels ¼ 38:6765þ 2:1999T þ0:6489P

0 1.2

1.5

0:0024T  P0:0367T 2 0:0083P 2

3.5. Simultaneous optimization of responses To obtain the optimal level combination of the two factors, the model equations of the SGR and FE were simultaneously optimized, following the procedure of Montgomery (2005). It was found that the optimum level combination of water temperature and dietary protein level was 29.9 1C/40.3%, at which the greatest SGR and FE were simultaneously reached, i.e., 2.748%/d and 0.775, respectively, with a desirability value of 0.888.

3

3.3

Fig. 5. Relationship between serum IGF-I level and SGR of Nile tilapia juveniles. Data from three replicates are mean values (n¼ 15).

5 Hepatic IGF-I mRNA /-actin mRNA

with the coefficient of determination: R2 ¼0.978. From Fig. 4 it is observed that IGF-I mRNA levels of juveniles first increased with water temperature at 37.5% protein level, and then decreased when water temperature exceeded 29 1C. IGF-I mRNA levels of juveniles varied curvilinear as dietary protein level changed linearly. Hepatic IGF-I mRNA levels of tilapia juveniles was obviously subdued by low temperature, low and high dietary protein level.

1.8 2.1 2.4 2.7 Specific growth rate (%/d)

4 3 2 IGF-I mRNA = 1.7195 SGR - 1.1146 r = 0.751

1 0 1.2

1.5

1.8

2.1

2.4

2.7

3

3.3

Specific growth rate (%/d) Fig. 6. Relationship between hepatic IGF-I mRNA level and SGR of Nile tilapia juveniles. Data from three replicates are mean values (n¼ 15).

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J. Qiang et al. / Journal of Thermal Biology 37 (2012) 686–695

Serum IGF-I level (ng/mL)

35 28 21 14 Serum IGF-I = 36.189FE + 0.509 r = 0.911

7 0 0.3

0.4

0.5

0.6

0.7

0.8

0.9

Feed efficiency Fig. 7. Relationship between serum IGF-I level and FE of Nile tilapia juveniles. Data from three replicates are mean values (n¼ 15).

Hepatic IGF-I mRNA /-actin mRNA

5

IGF - I mRNA = 6.8477 FE - 1.7326 r = 0.835

4 3 2 1 0 0.3

0.4

0.5

0.6 0.7 Feed efficiency

0.8

0.9

Fig. 8. Relationship between hepatic IGF-I mRNA level and FE of Nile tilapia juveniles. Data from three replicates are mean values (n¼ 15).

(Reid et al., 1995; Musuka et al., 2009). In the present study, the effect of water temperature on SGR and FE in tilapia juveniles proved very significant. For example, when dietary protein level maintained at 37.5%, the SGR and FE were respectively 2.378– 2.597%/d and 0.741–0.803 at water temperature 27 1C, notably higher than 1.408%/d and 0.391 at water temperature 20 1C. This is analogous with the finding of Musuka et al. (2009). Response surface analysis showed that when dietary protein level was 37.5%, the greatest SGR and FE reached were 2.706%/d and 0.779 at 30.2 1C respectively. This water temperature falls within the suitable temperature range, 29–31 1C, reported by Popma and Lovshin (1995) for tilapia growth. It can be seen that less energy was used for maintaining fish’s internal requirements at optimal water temperature, growth was thus effectively promoted. High water temperature, above 30 1C for example, may pose physiological stress in fish, and the energy produced from the resulting metabolism is primarily used to sustain homeostasis. At the same time, high temperature could be attributed to the high rate of gastric evacuation leading to retard growth and poor feed utilization (Elliot, 1972). Azaza et al. (2008) further reported that growth rate of Nile tilapia was better at 30 1C than at 34 1C. 4.2. Effects of dietary protein level on SGR and FE in Nile tilapia juveniles As dietary protein level increased, tilapia juveniles were found to grow faster in the study. When water temperature held at 27 1C, SGR value was 2.565%/d at dietary protein level of 45%, noticeably higher than 1.989%/d at 25%; high dietary protein level

of 45% did not restrain growth in Nile tilapia. This is different from the result of Abdel-Tawwab et al. (2010), who found that at water temperature of 27 1C, SGR value was 1.107%/d at dietary protein level of 45%, slightly lower than 1.143%/d at 35%. The impact of dietary proteins on the growth of tilapia may be closely linked to other factors such as rearing density, strain, number of generation of selection and environment (Al Hafedh, 1999). In this experiment, the Nile tilapia juveniles used were of the 16th generation of GIFT strain, and furthermore four rounds of mass selection have been carried out on them in Yixing experimental Base, China. When dietary protein level reached 50%, growth can be inhibited in Nile tilapia. Juancey (1982) also found that, the Mozambique tilapia Oreochromis mossambicus fed diets of higher protein level (56%) showed poor growth rate than those fed with lower protein level of 48%. However, when dietary protein level was 25%, most of the proteins may have being utilized to maintain the organism’s energy requirements, and the quantity of essential amino acids to be used for fish growth dwindled. Alternatively, the higher level of dietary carbohydrates may play an inhibitive role in tilapia growth (Pe´rez-Sa´nchez et al., 1995). Dietary protein level also had significant impact on FE of tilapia juveniles. For instance, at a water temperature of 27 1C, FE increased as dietary protein level varied from 25% to 40% and is akin to the result reported by Al Hafedh (1999). When dietary protein level went beyond 40%, FE decreased with increased dietary protein level. This is similar to the finding reported by Abdel-Tawwab et al. (2010). Maybe the dietary protein level went out of the suitable range required; and excessive amino acids were unable to be normally absorbed. Therefore they are either transformed into fats accumulating in tissue such as muscle, or excreted as urine nitrogen and hence caused a waste of proteins (Alvarez-Gonzalez et al., 2001). 4.3. Change in IGF-I at varying levels of water temperature and its relationship with SGR and FE The IGF-I/GH axis of fish species, like that of vertebrates, plays an important role in sex differentiation, growth and reproduction (Cameron et al., 2007), whose activity can be affected by both biological functions of fish organs and external factors (Duan, 1997). IGF-I is mainly produced in liver, which is also the main source of IGF-I hormone (Debnath, 2010). This study found, water temperature to be closely related to tilapia serum IGF-I and hepatic IGF-I mRNA level, and higher water temperature helped increase serum IGF-I and hepatic IGF-I mRNA level. Vera Cruz et al. (2006) also found that hepatic IGF-I mRNA level was significantly correlated with temperature conditions in Nile tilapia. Similar results were found in other fish species such as coho salmon, Oncorhynchus kisutch (Duan et al., 1995), channel catfish (Silverstein et al., 2000), gilthead sea bream, Sparus aurata (Mingarro et al., 2002), rainbow trout, Oncorhynchus mykiss (Gabillard et al., 2003b; Imsland et al., 2007), and halibut Hippoglossus hippoglossus (Imsland et al., 2008). The serum IGF-I level was found to be closely correlated with SGR (Fig. 5), with the Pearson correlation r ¼0.768 (Po0.01). Analogous findings of this relationship have also been reported in barramundi, Lates calcarifer, by Matthews et al. (1997); in coho salmon by Pierce et al. (2001); in Mozambique tilapia, by Uchida et al. (2003) and in turbot, by Imsland et al. (2007). At the same time, hepatic IGF-I mRNA level was significantly related to SGR (Fig. 6), and this result was similar to Vera Cruz et al. (2006). However, when the water temperature was 34 1C, high temperature suppressed serum IGF-I and hepatic IGF-I mRNA level from our study. Improved SGR and FE at 30 1C inferred that, this temperature perhaps was approaching the thermal optima for Nile tilapia; with 34 1C possibly exceeding it, whereby high temperatures

J. Qiang et al. / Journal of Thermal Biology 37 (2012) 686–695

decrease biochemical activity or production rates, that may lead to reduction in circulating IGF-I. Gabillard et al. (2005) pointed out that optimal temperature could hasten growth and release of GH in rainbow trout, and serum IGF-I was positively correlated with GH, which in turn could increase hepatic IGF-I mRNA level and serum IGF-I. Mingarro et al. (2002) also found that serum IGF-I level increased in temperate fish during suitable season for their growth. IGF-I, as a cytokinin, can catalyze the ornithine dehydrogenase activity, expedite the intracellular biosynthesis of DNA, RNA and proteins, and finally cause the proliferation and differentiation of cells, thereby contributing to growth (Tsai et al., 1994). The FE was for the first time, found to be positively correlated with the serum IGF-I and hepatic IGF-I mRNA level of Nile tilapia juveniles, the Pearson correlation was r ¼0.911 and r ¼0.835 receptively (Po0.01). This is similar to the finding reported by Pierce et al. (2001) and Luckenbach et al. (2007). However, this correlation was not found in the study of Imsland et al. (2007). 4.4. Effect of dietary protein level on serum IGF-I and hepatic IGF-I mRNA level As an important hormone, IGF-I has many functional tendencies, such as regulating cellular metabolism, promoting cellular growth, division and differentiation, enhancing the development of oosperm, mediating growth and osmotic pressure adaptation (Me´ndez et al., 2000; Gabillard et al., 2003a). In this study, dietary protein level was found to have significant impact on the serum IGF-I and hepatic IGF-I mRNA level in tilapia juveniles. Dyer et al. (2004) found that plasma IGF-I level was positively correlated with growth rate and dietary protein level in barramundi (Lates calcarifer), with r2 ¼0.65 and 0.59, respectively. Pe´rez-Sa´nchez et al. (1995) reported that plasma IGF-I level increased with increasing dietary protein level in gilthead sea bream (Sparus aurata). IGF-I might provide a useful tool for monitoring fish growth and evaluating nutritional status (Ma et al., 1992; Wilkinson et al., 2006). Jiang et al. (2010) also found that dietary protein level could noticeably affect the hepatic IGF-I mRNA level in mud carp (Cirrhinus molitorella), and SGR was significantly correlated with the serum IGF-I level. Different sources of protein can significantly affect serum IGF-I and hepatic IGF-I mRNA level in fish. Go´mez-Requeni et al. (2004) reported that total or partial replacement of fish meal by a mixture of plant protein sources could lead to decreased growth, reduced plasma IGF-I and hepatic IGF-I mRNA level in juvenile gilthead sea bream.

693

the dietary proteins. Thus, the demand and utilization of dietary protein in tilapia diet changed at different water temperature. These changes may alter the GH/IGF-I axis, and in turn impact on growth and feed utilization. In this study, the quadratic effect of water temperature on SGR (Table 4), FE (Table 5) and serum IGF-I level (Table 6) and the quadratic effect of dietary protein level on FE, serum IGF-I level and hepatic IGF-I mRNA level (Table 7) were found to be significant for the first time. This may be of great value in tilapia production, because when water temperature and dietary protein level deviate from the optimal factor combination, the response(s) of interest would be declining rapidly. Therefore, if the rearing of tilapia juveniles could be arranged according to the optimal factor combination derived in this study, the production efficiency would be sharpened. 4.6. Model building and response optimization The factorial design was used mainly in previous studies that dealt with the relationship of SGR and FE with water temperature and/or dietary protein level, whereas in our study the central composite design was adopted. Using the central composite design, the effect of the factors of interest can be examined in concert rather than singly; the predictive model equations can be established, and the optimal factor combination also can be determined through simultaneous optimization of response models. In this study, the model equations of SGR, FE, serum IGF-I level and hepatic IGF-I mRNA level using least squares method were obtained, with the coefficients of determination R2 ¼0.958, 0.955, 0.967, 0.978, respectively. These models can be used for practical projection. Using the procedure of Montgomery (2005), the model equations of SGR and FE were simultaneously optimized, and the optimal factor combination of water temperature and dietary protein level, i.e., 29.9 1C/40.3%, was obtained, at which the largest SGR and FE were 2.748%/d and 0.775, respectively, with the desirability function value of 0.888. It should be seen, however, that in practical production, due to the increasing fish meal prices, a higher level of dietary protein may bring about an increasing cost of culture. Increasing dietary lipid level or determining optimal ratio of protein to carbohydrate may help improve the utilization of dietary nitrogen and diminish the waste of protein. Other factors such as salinity, pH, dissolved oxygen and photoperiod may play a combined role in the utilization of dietary proteins in tilapia. This should be further examined.

Acknowledgments 4.5. Interaction and quadratic effects of water temperature and dietary protein level on SGR, FE and serum IGF-I and hepatic IGF-I mRNA level The growth of fish is an intricate process which is affected by both biotic and abiotic factors such as nutrition, temperature, rearing density and salinity. The interaction among these factors may occur. In our study, the interaction between water temperature and dietary protein level on FE, serum IGF-I and hepatic IGF-I mRNA level was significant in Nile tilapia, but that on SGR was insignificant, such has not being found or reported by others. When water temperature is relatively lower, higher demand for dietary proteins or amino acids may be required by tilapia juveniles to maintain their energy requirement. At higher water temperature, say 27 1C, which may be more suitable for the growth of tilapia juveniles, more dietary proteins may be used for growth. Whereas in high water temperature environment, physiological stress usually occurs within fish and the activity of proteinase is prohibited (Han et al., 2011), thereby underutilizing

The study was financed by the following grants: Special Fund for Agro-scientific Research in the Public Interest (200903046-02); Special Fund for Modern Agricultural Industry Technology System Construction-Tilapia Industry Technology System (CARS-49); Postgraduate Scientific Research Innovation Program of Jiangsu Ordinary Higher Colleges and Universities (CXLX11-0708); Special Fund for Guangdong Marine Fisheries Science & Technology Extension Program (A201009C02, A2010002-010b); Guangdong Science & Technology Program (2010B090500032); National Science & Technology Program (2012BAD26B00). The authors are also grateful to the director, Mr. Zhu Zhixiang, of the Yixing Experimental Base of Chinese Academy of Fishery Sciences, for providing us with biological material, site and other technical assistance. References Abdel-Tawwab, M., Ahmad, M.H., Khattab, Y.A.E., Shalaby, A.M.E., 2010. Effect of dietary protein level, initial body weight, and their interaction on the growth,

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