Open Access

Amino acid composition in eyes from zebrafish (Danio rerio) and sardine (Sardina pilchardus) at the larval stage

  • Francesca Falco1, 2,
  • Marco Barra1,
  • Matteo Cammarata3,
  • Angela Cuttitta1,
  • Sichao Jia2,
  • Angelo Bonanno1Email author,
  • Salvatore Mazzola1 and
  • Guoyao Wu2
SpringerPlus20165:519

https://doi.org/10.1186/s40064-016-2137-1

Received: 4 February 2016

Accepted: 11 April 2016

Published: 26 April 2016

Abstract

A comparative study was performed to identify differences in the amino acid composition of the eyes from zebrafish (Danio rerio) and sardine (Sardina pilchardus) larvae and their link to the environmental adaption of the species. Amino acids in the acidic hydrolysates of eyes from 11 zebrafish and 12 sardine were determined with the use of high-performance liquid chromatography involving precolumn derivatization with ortho-phthalaldehyde. Differences in the content of most amino acids were detected between zebrafish and sardine. These amino acids were aspartate, glutamate, serine, glycine, threonine, arginine, methionine, valine, phenylalanine, isoleucine, leucine and lysine. Of particular note, the percentage of methionine in zebrafish eyes was much higher than that in sardine, whereas the opposite was observed for glutamate and glycine. These results indicate that zebrafish and sardine likely have experienced differences in adaptation to environmental changes. We suggest that the amino acid composition of eyes represents a powerful tool to discriminate between species characterized by different lifestyle and inhabiting different environments.

Keywords

Larval fishEyeAmino acid composition Danio rerio Sardina pilchardus

Background

Recent studies led to the discovery that the genes involved in the eye ontogeny are conserved and that all of the eyes are monophyletic, that is, they arose from a single eye origin (Gehring and Ikeo 1999; Russell et al. 2000; Fernald 2000). Likewise, the conservation of a specific transcription factor has a common evolutionary origin for all eyes (Treisman 2004), and regulatory effect of certain AA on gene expression may be mediated by transcription factors (Wu 2010, 2013a).

Salvini-Plawen and Mayr (1977) demonstrated that the eye evolved at least 40 times among the branches of the animal evolutionary tree. The evolutionary phenomenon that led to the development of complex eyes, as those of mammals from teleost fish, is due to different factors, such as the influence of specific environmental changes on the biochemical composition of the tissue structure of a living being (Brown and Taylor 1992; Nissling and Vallin 1996; Guisande et al. 1998; Riveiro et al. 2000, 2003).

According to the Darwinist idea that animals adapted to the environment where they live in order to survive to specific environmental pressures, changes in amino acid composition (AAC) and density patterns of pelagic and mesopelagic fish larvae were evidenced in relation to oceanographic phenomenon in different areas of the Central Mediterranean Sea (Cuttitta et al. 2004, 2006; Bonanno et al. 2013). Another factor that could affect the biochemical composition of the tissues is that their synthesis during the larval development happens at different times and rates (Osse et al. 1997).

Conceição et al. (1998) showed that in the larval catfish (Clarias gariepinus) changes in the amino acid profiles occur at different temperatures, due to the synthesis of additional proteins during larval growth. Such environmental influence on biochemical composition lead to of use of AAC in eggs and larvae of fish to discriminate among species and spawning areas within species (Riveiro et al. 2003), considering also that larval AAC in pelagic fishes may also be affected by the parental strategies (Baynes and Howell 1996; Riveiro et al. 2011).

According to the preliminary study of Riveiro et al. (2011), the eyes may be the best fish tissue to discriminate among species through the AAC analysis. Generally all cells have a basal requirement for amino acids in processes such as protein synthesis (Wu 2013a). Amino acids are building blocks of proteins and also regulate metabolic processes in the body (Hou et al. 2015; Wu 2013b).

Amino acids play a critical role also in healthy vision. Interestingly, the most abundant amino acids in vertebrate’s eyes are glutamate (for gamma amino-butyric acid synthesis; GABA) and GLY (Neal 1976; Massey and Redburn 1987; Massey and Miller 1988; Barnstable 1993; Pourcho 1996; Redburn 1998; Thoreson and Witkovsky 1999). In addition to peptide-bound amino acids, eyes also contain free amino acids, including aspartate, asparagine, glutamate, glutamine, glycine, serine, proline, homocysteine, and taurine. At present, little is known about the ocular content of total amino acids in eyes. In addition, reference values of AAC in the eyes of larval fish of different species are not available in literature.

In this study we focused our attention on two fish species at larval stage: the cyprinidae zebrafish (Danio rerio), a tropical freshwater species, and sardine (Sardina pilchardus), belonging to the Clupeidae family that is a typical pelagic species living in open sea waters. The two species differ markedly in biology, habitat, and growth rates. The results can be used to assess the adaptation of the species to different environmental conditions.

Results

We analyzed the total content of amino acids (both free and peptide-bound) in the eyes of two fish species: zebrafish (Danio rerio) and sardine (Sardina pilchardus) at the larval stage. The mean and median values on amino acid composition (g/100 g amino acids) in the eyes of the two fish species are reported in Table 1. Reported values show that both mean and median percentage compositions (Fig. 1) of amino acids in the eyes of S. pilchardus are generally higher (p < 0.05) than those ones in D. rerio, especially for ASP + ASN, GLU + GLN, GLY, THR, ARG, PHE, VAL, and LEU. On the contraty, mean and median percentage compositions of SER, MET and LYS in the eyes of D. rerio were higher than those in S. pilchardus. Furthermore, except for GLY and ASP + ASN, it was evident that AAC percentage values showed generally higher variability (as inferred by interquartile range—Fig. 1) in D. rerio than in S. pilchardus.
Table 1

Median and mean values of the composition of amino acids in the eyes of Danio rerio and Sardina pilchardus larvae

Amino acid (g/100 g amino acids; %)

Danio rerio (n = 11)

Median

Quartile range

Min–max

Mean

SE

ASP + ASN

7.9

1.4

5.5–9.7

7.80

0.32

GLU + GLN

11.3

2.4

8.9–13.5

11.16

0.46

SER

13.1

10.7

6.6–22.8

14.04

1.66

HIS

3.1

2.5

1.7–5.8

3.31

0.41

GLY

6.2

1.4

4.2–9.4

6.15

0.40

THR

4.1

1.4

3.1–5

4.02

0.21

ARG

6.3

3.6

3.9–8.5

6.39

0.51

ALA

5.8

2.0

4.8–8.1

6.19

0.35

TYR

5.0

1.5

4–6.3

5.03

0.24

MET

4.6

1.3

2.2–6.2

4.65

0.36

VAL

4.7

1.1

3.7–5.9

4.76

0.22

PHE

5.7

0.9

4.8–6.8

5.63

0.20

ILE

4.2

1.6

3.0–5.9

4.29

0.28

LEU

7.7

2.0

5.8–9.7

7.52

0.39

LYS

8.9

2.1

6.4–10.9

9.07

0.42

CYS

1.6

0.7

0.7–1.8

1.39

0.24

TRP

0.3

0.1

0.2–0.3

0.29

0.02

PRO

4.0

1.3

3.6–5.4

4.22

0.44

Amino acid (%)

Sardina pilchardus (n = 12)

Median

Quartile range

Min–max

Mean

SE

ASP + ASN

10

2.3

2.7–11.8

9.34

0.69

GLU + GLN

14.1

1.6

6.2–14.7

13.33

0.70

SER

4.4

0.4

4.1–4.9

4.46

0.08

HIS

3.2

0.3

1.1–3.7

3.02

0.19

GLY

7.4

1.3

6.6–11.6

7.95

0.39

THR

5.1

0.3

4.3–5.3

5.03

0.08

ARG

11.5

0.8

10.7–15.9

11.96

0.39

ALA

5.5

0.5

4.7–6.1

5.51

0.11

TYR

4.9

0.4

4.3–5.7

4.97

0.11

MET

0.5

0.7

0.1–2.3

0.80

0.21

VAL

5.8

0.1

5.6–6

5.76

0.03

PHE

6.5

0.4

5.9–8

6.59

0.15

ILE

5.0

0.2

5.0–5.3

5.08

0.03

LEU

8.4

0.6

7.5–9.8

8.49

0.18

LYS

7.5

1.1

6.2–11

7.72

0.37

CYS

0.7

0.4

0.5–1.4

0.83

0.16

TRP

0.1

0.1

0.0–0.2

0.08

0.02

PRO

3.0

2

2.1–5.4

3.33

0.64

Fig. 1

Box plot comparing amino acid composition (g/100 g amino acids; %) between zebrafish (Danio rerio) and sardine (Sardina pilchardus) larvae

Statistical tests were carried out in order to evaluate the significance of observed differences in terms of AAC (Table 2). In particular, the Mann–Whitney U test was used because not all the data met homoscedasticity assumptions, as required by parametric tests. Indeed, the Levene’s test (not shown) evidenced a significant difference in variance between the two groups of fish for some amino acids. Test results (Table 2) highlighted that median values of HIS, ALA and TYR were not significantly different (p > 0.05) between the two considered species. Conversely, significant differences were recorded for all the other AACs (p < 0.05). In particular, SER, ARG and MET showed the highest differences in median values with respect to the other AACs (Table 2).
Table 2

Mann Whitney U test results for differences in amino acid composition in eyes between Danio Rerio and Sardina pilchardus larvae

Amino acid

U

Z

Z adj.

p-value

Median differences

ASP + ASN

19

2.862

2.862

0.004

2.1

GLU + GLN

17

2.985

2.985

0.003

2.8

SER

0

4.031

4.031

0.000

8.7

HIS

61

−0.277

−0.277

0.782

0.1

GLY

12

3.293

3.293

0.001

1.3

THR

8

3.539

3.539

0.000

1.1

ARG

0

4.031

4.031

0.000

5.2

ALA

50

0.954

0.954

0.340

0.3

TYR

61

0.277

0.277

0.782

0.1

MET

2

3.908

3.908

0.000

4.1

VAL

20

2.800

2.800

0.005

1.1

PHE

19

2.862

2.862

0.004

0.8

ILE

31

2.123

2.123

0.034

0.9

LEU

28

2.308

2.308

0.021

0.7

LYS

29

2.246

2.246

0.025

1.4

CYS

2

1.837

1.837

0.066

0.9

PRO

6

0.857

0.857

0.391

1.0

TRP

0

2.327

2.327

0.02

0.2

Significant differences are marked in italic. The absolute differences in median values were also reported

The mean and standard deviation values for S. pilchardus were compared with those obtained on the amino acid content of the eyes of adult fish of the same species (Fig. 2) obtained from the Strait of Sicily (Riveiro et al. 2011). Our results showed higher standard deviations for ASP, GLY, GLU, ARG, LYS and PRO, compared to the values reported by Riveiro et al. (2011); the opposite was observed for the remaining AAs.
Fig. 2

Comparison of the average amino acid composition (top panel) and SD values (bottom panel) between adults (Riveiro et al. 2011) and larvae (this study) of the species Sardina pilchardus

Discussion

Results of the present study provide reference values of amino acid content in the eyes of zebrafish and sardine for the larval stage. As free amino acids represent <3 % of total amino acids in tissues (Wu 2013a), our values refer to primarily peptide-bound amino acids in the eyes of the fish. The amino acid composition found in this work could be compared with the amino acid composition in structural proteins of the retina (Harding and Dilley 1976; Wistow and Piatigorsky 1988; Zhao et al. 2011). Our results showed that it is possible to discriminate fish species based on the AAC of the eyes. Among the considered AA, the two species showed marked differences particularly in SER, ARG and MET. It is unknown whether the differences in AAC of the fish eyes result from differences in dietary protein intake and/or plasma concentrations of amino acids. It has been demonstrated that SER, ARG and MET have a greater insulinotropic effect compared with glucose in fish (Andoh 2007; Zinalla and Hall 2008). Further, MET has growth-promoting effects in the rainbow trout (Rodehutscord et al. 1995).

In the eyes of larval zebrafish, the amount of methionine was lower than in the sardine larvae but the opposite was observed for arginine. The difference between the species was smaller for lysine. Moreover, it was found that GLU + GLN and GLY were higher in sardine than in zebrafish. Whether these differences are unique to the eyes or common to other fish tissues remain to be determined.

The mean and standard deviation values for S. pilchardus were compared with those for the amino acid concentration of the eyes of adult fish of the same species obtained from the Sicilian Channel. The composition of most amino acids in the eyes of adult and larval specimens of S. pilchardus was similar (Fig. 2); only ASP, SER, GLY, ARG, LEU and LYS appeared to have quite different values. On the basis of this result, we surmise that ASP, SER and GLY are generally more abundant in adults, while ARG, LEU and LYS were higher in larvae than in adults. Such differences within the same species, during growth from the larval to adult stage, are in agreement with the findings of Conceição et al. (1997, 2010) and Aragão et al. (2004) who carried out the study of the AAC in the whole body of larval fish.

In particular, the observed higher glycine concentration in adults than in the sardine larvae is in agreement with Sivilotti (2010), which highlights the synaptic role of GLY. It is possible that the eyes of adult fish have higher content of collagen proteins than larvae, because glycine is a major amino acid in these proteins (Wang et al. 2013). The glicinergic synapses are important in restricted areas of the adult nervous system, such as the spinal cord, brain stem and retina. They are activated primarily by GLY, but can also be activated by common amino acids.

The ASP was classified by Wu (2013b) as a conditionally essential AA. Abundant AA in food proteins of plant and animal origins (Li et al. 2011) is a major metabolic fuel for mammalian enterocytes (Burrin and Stoll 2009; Rezaei et al. 2013a, b). Further, Wu (2010) and Wu (2013b) found that some Amino Acids are involved in regulating the metabolic key pathways improving health, survival, growth, development, lactation, and reproduction of organisms. At present, little is known about ASP metabolism in fish. According to Kim et al. (2011a, b), Wu et al. (2011a, b) and Wu (2013b), the GLY, together with other amino acids, was traditionally classified as non-essential amino acids, but these amino acids play an important role in regulating gene expression (Liu et al. 2012), cell signaling (Bazer et al. 2012; Jewell et al. 2013), nutrient transport and metabolism in animal cells (Suryawan et al. 2012; Wang et al. 2013). Regarding SER and LYS, their high concentration has been reported in the whole body of fish at the larval period (Zakeri et al. 2009). As building blocks of peptides, these amino acids have an important role in the synthesis of protein. Like many of the other amino acids (Li et al. 2007a), SER and LYS may be critical for immune response during the larval stage.

According to Kalloniatis et al. (2013), amino acids are also involved in metabolism, and in retina cell, glutamate is the major excitatory neurotransmitter in the retina (Fletcher and Kalloniatis 1996; Ehinger et al. 1988; Massey and Miller 1990). Glutamate is also the precursor of GABA (Erecinska and Silver 1990) and there is strong evidence that glutamate is used by photoreceptors (Massey and Miller 1990, 1998).

Riveiro et al. (2011) found that there were differences in the AAC of the eyes of adult sardine between samples from two different regions (the Atlantic Ocean and the Mediterranean Sea). With the available data, it is not possible to determine whether the different environmental conditions may affect AAC in the eyes of zebrafish and sardine reported from the present study. However, this is a very important issue to be addressed in future investigations. Such work could help to explain the link between environment and AAC in fish eyes.

It is noteworthy that differences in AAC of fish eyes found in this study are in agreement with those reported by Li et al. (2007b) and Li and Ortí (2007) who used the D. rerio specie belonging to the Ostariophysi superorder within Teleosts (Lê et al. 1993; Lecointre and Nelson 1996). The most abundant and major vehicle of amino acid delivery in all fish is high-density lipoprotein vitellogenin (Vtg) (Ziv et al. 2008), it’s coded by two major genes Vtga and Vtgb, as well as a minor one, Vtgc. Vtgc is expressed also in Ostariophysi, but at low levels (Wang et al. 2000, 2005). In this context it is important to emphasize that because the Vtg sub domains may be disparately involved in the binding or transporting of nonpolar ligands such as lipids and retinoic acid (Grogan and Taborsky 1987; Sawaguchi et al. 2006). Robust evidences showed that a positive selection of coding genes for proteins is provided by synonymous substitution (Yang and Bielawski 2000), and the change of AA offers a selective advantage.

An interesting concept emerging from the present work is that differences of AAC in fish eyes may provide insight into the different capacity of the animals to adapt to different environmental temperatures. In fact, several authors have defined zebrafish and sardine as eurythermics. Sardines are eurythermic and euryhaline clupeoids that generally inhabit waters with temperatures ranging from 8 to 24 °C and salinities from 30 to 38 psu (Haynes and Nichols 1994; Giannoulaki et al. 2005; Coombs et al. 2006; Petitgas et al. 2006; Stratoudakis et al. 2007; Bonanno et al. 2014). Zebrafish are freshwater fish; even if they are also tolerant to a wide range of salinities that technically extend to brackish conditions. Sawant et al. (2001) found that embryos, reared in salinities of up to 2 parts per thousand, displayed similar rates of survival and hatching in controlled environment at 0.3 ppt. They can tolerate a wide temperature range from 6 to 38 °C.

Costas et al. (2012) suggested that acclimation to different environmental temperatures induces several metabolic changes in Senegalese sole, suggesting that plasma amino acids (e.g., ASP, GLU and GLY) may be important for thermal acclimation; they showed that temperature affect more drastically concentrations of dispensable amino acids than those of indispensable amino acids and that different exposure temperatures induce different responses. Thus, as in mammals (Liu et al. 2016; Wu et al. 2014; Wu 2014), dietary requirements of all amino acids by fish to meet optimal needs for protein synthesis in tissues (including eyes) are affected by both genotypes and environmental factors. In support of this notion, environmental salinity plays an important role in affecting plasma AAC of fish species (Li et al. 2009). Our results are in agreement with Aragão et al. (2010) who showed that the levels of some indispensable amino acids (HIS, MET and PHE) do not change significantly with environmental salinity, and ILE, LEU and VAL tend to increase with salinity.

Conclusions

The amino acid composition of the eyes of two fish species (zebrafish and sardine) at the larval stage were determined. The results indicate that eye’s AAC could be used as a useful tool to discriminate the evolutionary origin and species of fish. Although further studies are needed to evaluate the power of such approach, our study showed that the AAC was different between Sardina pilchardus and Danio rerio species. This does not mean that this technique is sufficient to identify genetic differences between the species, but the data can be used as auxiliary information. Considering that this study stressed the importance of the use of AAC in eyes as a discriminating factor, more experiments are warranted to define the scientific degree of certainty in studies of fish evolution and metabolism.

Methods

Zebrafish (Danio rerio)

Larvae of zebrafish, which were raised under normal farming conditions, were obtained from Department of Biology, Texas A&M University, College Station, USA, and maintained according to the regulations of the Texas A&M University Animal Care and Use committee. The total number of samples used for the experiment was 11. The fish were used about 4 days of age after hatching, and they were picked up individually to make sure they were still alive. The fish were anesthetized with tricainemethanesulfonate (TMS), also known as MS-222, at the concentration of 200 mg/L in deionized water, with the pH of the solution being adjusted to 7.4 through the addition of sodium bicarbonate. The fish were then fixed in alcohol and the main morphological measurements were taken by means of an optical microscope. The total length of the fish 3.7 mm and the eye diameter was 0.3 mm. Finally, using a pair of needles, the eyes were extracted, dried in an oven at 50 °C to evaporate all the alcohol, and then subjected to acid hydrolysis for the determination of total amino acids.

Sardine (Sardina pilchardus)

Twelve samples of sardine were obtained along the Sicily coast in the Tyrrhenian Sea and used for the experiment, with the approval of the Institute for Coastal and Marine Environment (IAMC), Detached Units of Capo Granitola, Naples, Italy. Fish samples were obtained and preserved in the same manner as described for zebrafish. The total length of the fish (TL) was 33 mm and the eye diameter was 1.6 mm. The fish eyes were extracted and then processed for hydrolysis, as described previously.

General consideration

Amino acid analysis, although a classical technique, remains indispensable for quality control studies in biochemistry and biotechnology. Over the year, a large number of HPLC methods with fluorescence or UV/visible detection have been developed for the analysis of AAC in protein hydrolysates (Wu et al. 1999; Dai et al. 2014). A successful amino acid analysis depends on the proper performance of the hydrolysis. In fact, other studies have shown that the influence of the hydrolysis conditions represent a major source of error in the analysis (Yüksel et al. 1995). Using our HPLC method, we successfully identified 15 amino acids in fish eyes.

Method for hydrolysis of protein in fish

The acid hydrolysis method (Dai et al. 2014; Wu et al. 1999) has been used with some modifications. Briefly, two eyes were inserted in a 2-ml glass vial to which was added 1 ml of 6 M HCl. The glass vial was gassed with N2 for one min and then capped. All tubes were placed in an oven with 110 °C. Two hours later, the glass vials were gently shacked to ensure that the sample was completely dissolved in the solution. After 20 h of hydrolysis, the glass vials were gently shacked to ensure that the precipitate was suspended in solution. At the end of the 24-h hydrolysis, the whole solution was dried carefully under N2. Finally 1 ml of HPLC-grade water was added to each vial and the solution was stored at 4 °C until analyzed within 2 days.

Amino acid analysis

Amino acids in acid hydrolysates were analyzed with the use of the Waters HPLC apparatus, an analytical column (supelco 3 μm C18 column, 150 mm × 4.6 mm ID) protected by guard column (supelco 5 cm × 4.6 mm), a model 2475 Multi l fluorescence detector and a Millennium-32 workstation (Dai et al. 2014). Fluorescence is monitored at excitation wavelengths of 340 and 455 nm, respectively. The following amino acids were analyzed: aspartate (ASP) plus asparagine (ASN), serine (SER), glutamate (GLU) plus glutamine (GLN), glycine (GLY), histidine (HIS), arginine (ARG), threonine (THR), alanine (ALA), tyrosine (TYR), valine (VAL), lysine (LYS), isoleucine (ILE), leucine (LEU), Phenylalanine (PHE), methionine (MET), cystine (CYS), tryptophane (TRP) and proline (PRO).

Statistical methods

The unpaired t-test was used to evaluate the significance of observed differences between the two groups of fish. This kind of test belongs to the so-called parametric methods and it is subjected to some assumptions, such as the normality and homoscedasticity. Such properties were checked by means of the Lilliefors and Levene’s test. Even though the assumption of normality and homoscedasticity was met for most AA in both fish species, the same was not verified for several amino acids. As a consequence, we used the Mann–Whitney U test that is the non-parametric analogue of the t-test. The Mann–Whitney U test is conceptually similar to the t-test, except that it is based on the U statistic and does not require normality nor homoscedasticity. Probability values ≤0.05 were taken to indicate statistical significance.

Abbreviations

AAC: 

amino acid composition

ASN: 

aspartate

ASP: 

asparagine

GLN: 

glutamine

GLU: 

glutamate

SER: 

serine

HIS: 

histidine

THR: 

threonine

ARG: 

arginine

ALA: 

alanine

TYR: 

tyrosine

MET: 

metionine

VAL: 

valine

PHE: 

phenylalanine

ILE: 

isoleucine

LYS: 

lysine

CYS: 

cystine

TRP: 

tryptophane

PRO: 

proline

GABA: 

gamma amino butyric acid

Declarations

Authors’ contributions

WG, MS, FF, AB designed research. WG, FF and JS performed research. FF and BM designed of the study and performed the statistical analysis. FF, WG, MS, CM, AB and AC wrote the paper. All the authors read and approved the final manuscript.

Acknowledgements

The Authors would like to express their gratitude to the Department of Biology, Texas A&M University, College Station, USA, for the support of this work. We would like to thank Dr. Gayan Nawaratna in Prof. Guoyao Wu’s laboratory for technical assistance.

Competing interests

The authors declare that they have no competing interests.

Disclosures

Experiments on animals were performed in accordance with the guidelines and regulations set forth by committee of Animal Care and Use.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Detached Units of Capo Granitola (TP) and Naples, Institute for Coastal and Marine Environment (IAMC), Consiglio Nazionale delle Ricerche
(2)
Department of Animal Science, Texas A&M University
(3)
Marine Immunobiology Laboratory, Department of Biological, Chemical, Pharmaceutical Science and Technology, University of Palermo

References

  1. Andoh T (2007) Amino acids are more important insulinotropins than glucode in teleost fish, barfin flounder (Verasper moseri). Gen Comp Endocrinol 151:308–317View ArticleGoogle Scholar
  2. Aragão C, Luis E, Conceiao C, Hans-Jorgen F, Dinis MT (2004) Estimated amino acid requirements during early ontogeny in fish with different life styles: gilthead seabream (Sparus aurata) and Senegalese sole (Solea senegalensis). Aquaculture 242:589–605View ArticleGoogle Scholar
  3. Aragão C, Costas B, Vargas-Chacoff L, Ruiz-Jarabo I, Dinis MT, Mancera JM, Conceição LE (2010) Changes in plasma amino acid levels in a euryhaline fish exposed to different environmental salinities. Amino Acids 38:311–317View ArticleGoogle Scholar
  4. Barnstable CJ (1993) Glutamate and GABA in retinal circuitry. Curr Opin Neurobiol 3:520–525View ArticleGoogle Scholar
  5. Baynes SM, Howell BR (1996) The influence of egg size and incubation temperature on the condition of Solea solea (L.) larvae at hatching and first feeding. J Exp Mar Biol Ecol 199:59–77View ArticleGoogle Scholar
  6. Bazer FW, Song GH, Kim JY, Erikson DW, Johnson GA, Burghardt RC, Gao HJ, Satterfield MC, Spencer TE, Wu G (2012) Mechanistic mammalian target of rapamycin (MTOR) cell signaling: effects of select nutrients and secreted phosphoprotein 1 on development of mammalian conceptuses. Mol Cell Endocrinol 354:22–33View ArticleGoogle Scholar
  7. Bonanno A, Zgozi S, Cuttitta A, El Turki A, Di Nieri A, Ghmati H, Basilone G, Aronica S, Hamza M, Barra M, Genovese S, Falco F, Kinittweis L, Mifsud R, Patti B, Bahri T, Giacalone G, Fontana I, Tranchida G, Mazzola S (2013) Influence of environmental variability on anchovy early life stages (Engraulis encrasicolus) in two different areas of the Central Mediterranean Sea. Hydrobiologia 701:273–287View ArticleGoogle Scholar
  8. Bonanno A, Giannoulaki M, Barra M, Basilone G, Machias A, Genovese S, Goncharov S, Popov S, Rumolo P, Di Bitetto M, Aronica S, Patti B, Fontana I, Giacalone G, Ferreri R, Buscaino G, Somarakis S, Pyrounaki MM, Tsoukali S, Mazzola S (2014) Habitat selection response of small pelagic fish in different environments. Two examples from the Oligotrophic Mediterranean Sea. PLoS One 9(7):e101498. doi:10.1371/journal.pone.0101498 View ArticleGoogle Scholar
  9. Brown RW, Taylor WW (1992) Effects of egg composition and prey density on the larval and survival of lake whitefish (Coregonus clupeaformis Mitchill). J Fish Biol 40:381–394View ArticleGoogle Scholar
  10. Burrin DG, Stoll B (2009) Metabolic fate and function of dietary glutamate in the gut. Am J Clin Nutr 90:850S–856SView ArticleGoogle Scholar
  11. Conceição LEC, Van der Meeren T, Verreth JAJ et al (1997) Amino acid metabolism and protein turnover in larval turbot (Scophthalmus maximus) fed natural zooplankton or Artemia. Marine Biol 129:255–265View ArticleGoogle Scholar
  12. Conceição LE, Ozório R, Suurd EA, Verreth JJ (1998) Amino acid profiles and amino acid utilization in larval African catfish (Clarias gariepinus): effects of ontogeny and temperature. Fish Physiol Biochem 19:43–58View ArticleGoogle Scholar
  13. Conceição LE, Aragão C, Rønnestad I (2010) Protein metabolism and amino acid requirements in fish larvae. In: Cruz-Suarez LE, Ricque-Marie D, Tapia-Salazar M, Nieto-López MG, Villarreal-Cavazos DA, Gamboa-Delgado J (eds) Avances en Nutrición Acuícola X - Memorias del Décimo Simposio Internacional de Nutrición Acuícola, 8-10 de Noviembre, San Nicolás de los Garza, N. L., México. Universidad Autónoma de Nuevo León, Monterrey, México, pp 250–263. ISBN: 978-607-433-546-0Google Scholar
  14. Coombs S, Smyth T, Conway D, Halliday N, Bernal M, Stratoudakis Y, Alvarez P (2006) Spawning season and temperature relationships for sardine (Sardina pilchardus) in the eastern North Atlantic. J Mar Biol Assoc 86:1245–1252View ArticleGoogle Scholar
  15. Costas B, Aragao C, Ruiz-Jarabo I, Vargas-Chacoff L, Arjona FJ, Mancera JM, Dinis MT, Conceicao LEC (2012) Different environmental temperatures affect amino acid metabolism in the eurytherm teleost Senegalese sole (Solea senegalensis Kaup, 1858) as indicated by changes in plasma metabolites. Amino Acids 43(1):327–335View ArticleGoogle Scholar
  16. Cuttitta A, Arigo A, Basilone G, Bonanno A, Buscaino G, Rollandi L, Patti B (2004) Mesopelagic fish larvae species in the Strait of Sicily and their relationships to main oceanographic events. Hydrobiologia 527:177–182View ArticleGoogle Scholar
  17. Cuttitta A, Guisande C, Riveiro I, Maneiro I, Patti B, Vergara AR, Basilone G, Bonanno A, Mazzola S (2006) Factors structuring reproductive habitat suitability of Engraulis encrasicolus in the south coast of Sicily. J Fish Biol 68:264–275View ArticleGoogle Scholar
  18. Dai ZL, Wu ZL, Jia SC, Wu G (2014) Analysis of amino acid composition in proteins of animal tissues and foods as pre-column o-phthaldialdehyde derivatives by HPLC with fluorescence detection. J Chromatogr B 964:116–127View ArticleGoogle Scholar
  19. Ehinger B, Ottersen OP, Storm-Mathisen J, Dowling JE (1988) Bipolar cells in the turtle retina are strongly immunoreactive for glutamate. Proc Natl Acad Sci USA 85:8321–8325View ArticleGoogle Scholar
  20. Erecinska M, Silver IA (1990) Metabolism and role of glutamate in mammalian brain. Prog Neurobiol 35:245–296View ArticleGoogle Scholar
  21. Fernald RD (2000) Evolution of eyes. Curr Opin Neurobiol 10:444–450View ArticleGoogle Scholar
  22. Fletcher EL, Kalloniatis M (1996) Neurochemical architecture of the normal and degenerating rat retina. J Comp Neurol 376:343–360View ArticleGoogle Scholar
  23. Gehring WJ, Ikeo K (1999) Pax 6: mastering eye morphogenesis and eye evolution. Trends Genet 15:371–377View ArticleGoogle Scholar
  24. Giannoulaki M, Machias A, Somarakis S, Tsimenides N (2005) The spatial distribution of anchovy and sardine in the northern Aegean Sea in relation to hydrographic regimes. Belgian J Zool 135:151–156Google Scholar
  25. Grogan J, Taborsky G (1987) Iron binding by phosvitins: variable mechanism of iron release by phosvitins of diverse species characterized by different degrees of phosphorylation. J Inorg Biochem 29:33–47View ArticleGoogle Scholar
  26. Guisande C, Riveiro I, Solá A, Valdés L (1998) Effect of biotic and abiotic factors in the biochemical composition of wild eggs and larvae of several fish species. Mar Ecol Prog Ser 163:53–61View ArticleGoogle Scholar
  27. Harding JJ, Dilley KJ (1976) Structural proteins of the mammalian lens: a review with emphasis on changes in development, aging and cataract. Exp Eye Res 22:1–73View ArticleGoogle Scholar
  28. Haynes GM, Nichols JH (1994) Pilchard (Sardina pilchardus, Walbaum) egg distribution in the English Channel from plankton surveys in 1978, 1981, 1988 and 1991. J Plankton Res 16:771–782View ArticleGoogle Scholar
  29. Hou YQ, Yin YL, Wu G (2015) Dietary essentiality of “nutritionally nonessential amino acids” for animals and humans. Exp Biol Med 240:997–1007View ArticleGoogle Scholar
  30. Jewell JL, Russell RC, Guan KL (2013) Amino acid signalling upstream of mTOR. Nat Rev Mol Cell Biol 14:133–139View ArticleGoogle Scholar
  31. Kalloniatis M et al (2013) Retinal amino acid neurochemistry in health and disease. Clin Exp Optometry 96:310–332View ArticleGoogle Scholar
  32. Kim JY, Burghardt RC, Wu G, Johnson GA, Spencer TE, Bazer FW (2011a) Select nutrients in the ovine uterine lumen: VII. Effects of arginine, leucine, glutamine, and glucose on trophectodem cell signaling, proliferation, and migration. Biol Reprod 84:62–69View ArticleGoogle Scholar
  33. Kim JY, Burghardt RC, Wu G, Johnson GA, Spencer TE, Bazer FW (2011b) Select nutrients in the ovine uterine lumen: IX. Differential effects of arginine, leucine, glutamine and glucose on interferon tau, orinithine decarboxylase and nitric oxide synthase in the ovine conceptus. Biol Reprod 84:1139–1147View ArticleGoogle Scholar
  34. Lê HL, Lecointre G, Perasso R (1993) A 28S rRNA-based phylogeny of the gnathostomes: first steps in the analysis of conflict and congruence with morphologically based cladograms. Mol Phylogenet Evol 2:31–51View ArticleGoogle Scholar
  35. Lecointre G, Nelson G (1996) Clupeomorpha, sister group of Ostrariophysi. In: Stiassny MLJ, Parenti LR, Johnson GD (eds) Interrelationships of fishes. Academic Press, San Diego, pp 193–207View ArticleGoogle Scholar
  36. Li C, Ortí G (2007) Molecular phylogeny of Clupeiformes (Actinopterygii) inferred from nuclear and mitochondrial DNA sequences. Mol Phylogenet Evol 44:386–398View ArticleGoogle Scholar
  37. Li P, Yin YL, Li DF, Kim SW, Wu G (2007a) Amino acids and immune function. Br J Nutr 98:237–252View ArticleGoogle Scholar
  38. Li C, Ortí G, Zhang G, Lu G (2007b) A practical approach to phylogenomics: the phylogeny of ray-finned fish (Actinopterygii) as a case study. BMC Evol Biol 7:1View ArticleGoogle Scholar
  39. Li P, Mai KS, Trushenski J, Wu G (2009) New developments in fish amino acid nutrition: towards functional and environmentally oriented aquafeeds. Amino Acids 37:43–53View ArticleGoogle Scholar
  40. Li XL, Rezaei R, LiP WuG (2011) Composition of amino acid in feed ingredients for animal diets. Amino Acid 40:1159–1168View ArticleGoogle Scholar
  41. Liu XD, Wu X, Yin YL, Liu YQ, Geng MM, Yang HS, Blachier F, Wu G (2012) Effects of dietary l-arginine or N-carbamylglutamate supplementation during late gestation of sows on the miR-15b/16, miR-221/222, VEGFA and eNOS expression in umbilical vein. Amino Acids 42:2111–2119View ArticleGoogle Scholar
  42. Liu Y, Kong X, Li F, Tan B, Li Y, Duan Y, Yin Y, He J, Hu C, Blachier F, Wu G (2016) Co-dependence of genotype and dietary protein intake to affect expression of amino acid/peptide transporters in porcine skeletal muscle. Amino Acids 48:75–90View ArticleGoogle Scholar
  43. Massey SC, Miller RF (1988) Glutamate receptors of ganglion cells in the rabbit retina: evidence for glutamate as a bipolar cell transmitter. J Physiol 405:635–655View ArticleGoogle Scholar
  44. Massey SC, Miller RF (1990) N-methyl-d-aspartate receptors of ganglion cells in rabbit retina. J Neurophysiol 63:16–30Google Scholar
  45. Massey SC, Miller RF (1998) Glutamate receptors of ganglion cells in the rabbit retina: evidence for glutamate as a bipolar cell transmitter. J Physiol 405:635–655View ArticleGoogle Scholar
  46. Massey SC, Redburn DA (1987) Transmitter circuits in the vertebrate retina. Prog Neurobiol 28:55–96View ArticleGoogle Scholar
  47. Neal MJ (1976) Amino acid transmitter substances in the vertebrate retina. Gen Pharmacol Vasc Syst 7:321–332View ArticleGoogle Scholar
  48. Nissling A, Vallin L (1996) The ability of Baltic cod eggs to maintain neutral buoyancy and the opportunity for survival in fluctuating conditions in the Baltic Sea. J Fish Biol 48:217–227View ArticleGoogle Scholar
  49. Osse JWM, Van den Boogaart JGM, Van Snik GMJ, Van der Sluys L (1997) Priorities during early growth of fish larvae. Aquaculture 155:249–258View ArticleGoogle Scholar
  50. Petitgas P, Masse J, Bourriau P, Beillois P, Delmas D, Herbland A, Santos M (2006) Hydro-plankton characteristics and their relationship with sardine and anchovy distributions on the French shelf of the Bay of Biscay. Sci Mar 70:161–172View ArticleGoogle Scholar
  51. Pourcho RG (1996) Neurotransmitters in the retina. Curr Eye Res 15:797–803View ArticleGoogle Scholar
  52. Redburn DA (1998) Neurotransmitter systems in the outer plexiform layer of mammalian retina. Neurosci Res Suppl 8:S127–S136View ArticleGoogle Scholar
  53. Rezaei R, Wang WW, Wu ZL, Dai ZL, Wang JJ, Wu G (2013a) Biochemical and physiological bases for utilization of dietary amino acids by young pigs. J Anim Sci Biotech 4:7View ArticleGoogle Scholar
  54. Rezaei R, Knabe DA, Tekwe CD, Dahanayaka S, Ficken MD, Fielder SE, Eide SJ, Lovering SL, Wu G (2013b) Dietary supplementation with monosodium glutamate is safe and improves growth performance in postweaning pigs. Amino Acids 44:911–923View ArticleGoogle Scholar
  55. Riveiro I, Guisande C, Lloves M, Maneiro I, Cabanas JM (2000) Importance of parental effects on larval survival in Sardina pilchardus. Mar Ecol Prog Ser 205:249–258View ArticleGoogle Scholar
  56. Riveiro I, Guisande C, Franco C, Lago de Lanzos A, Maneiro I, Vergara AR (2003) Egg and larval amino acid composition as indicators of niche resource partitioning in pelagic fish species. Mar Ecol Prog Ser 260:255–262View ArticleGoogle Scholar
  57. Riveiro I, Guisande C, Iglesias P, Basilone G, Cuttitta A, Giráldez A, Maneiro I (2011) Identification of subpopulations in pelagic marine fish species using amino acid composition. Hydrobiologia 670:189–199View ArticleGoogle Scholar
  58. Rodehutscord M, Jacobs S, Pack M, Pfeffer E (1995) Response of rainbow trout (Oncorhynchus mykiss) growing from 50–170 g supplements either l-Arginine or l-Threonine in a semipurified diet. Jurnal of Nutrition 125:970–975Google Scholar
  59. Russell AP, Rittenhouse DR, Bauer AM (2000) Laryngotracheal morphology of Afro-Madagascan geckos: a comparative survey. J Morphol 245:241–268View ArticleGoogle Scholar
  60. Salvini-Plawen LV, Mayr E (1977) On the evolution of photoreceptors and eyes. Evol Biol 10:207–263Google Scholar
  61. Sawaguchi S, Kagawa H, Ohkubo N, Hiramatsu N, Sullivan CV, Matsubara T (2006) Molecular characterization of three forms of vitellogenin and their yolk protein products during oocyte growth and maturation in red seabream (Pagrus major), a marine teleost spawning pelagic eggs. Mol Reprod Dev 73:719–736View ArticleGoogle Scholar
  62. Sawant MS, Zhang S, Li L (2001) Effect of salinity on development of zebrafish, Brachydanio rerio. Curr Sci 81:1347–1349Google Scholar
  63. Sivilotti LG (2010) What single-channel analysis tells us of the activation mechanism of ligand-gated channels: the case of the glycine receptor. J Physiol 588:45–58View ArticleGoogle Scholar
  64. Stratoudakis Y, Coombs S, De Lanzós AL, Halliday N, Costas G, Caneco B, Bernal M (2007) Sardine (Sardina pilchardus) spawning seasonality in European waters of the northeast Atlantic. Mar Biol 152:201–212View ArticleGoogle Scholar
  65. Suryawan A, Nguyen HV, Almonaci RD, Davis TA (2012) Abundance of amino acid transporters involved in mTORC1 activation in skeletal muscle of neonatal pigs is developmentally regulated. Amino Acids 45:523–530View ArticleGoogle Scholar
  66. Thoreson WB, Witkovsky IP (1999) Glutamate receptors and circuits in the vertebrate retina. Progr Retin Eye Res 18:765–810View ArticleGoogle Scholar
  67. Treisman JE (2004) How to make an eye. Development 131:3823–3827View ArticleGoogle Scholar
  68. Wang H, Yan T, Tan JTT, Gong Z (2000) A zebrafish vitellogenin gene (vg3) encodes a novel vitellogenin without a phosvitin domain and may represent a primitive vertebrate vitellogenin gene. Gene 256:303–310View ArticleGoogle Scholar
  69. Wang H, Tan JT, Emelyanov A, Korzh V, Gong Z (2005) Hepatic and extrahepatic expression of vitellogenin genes in the zebrafish, Danio rerio. Gene 356:91–100View ArticleGoogle Scholar
  70. Wang WW, Wu ZL, Dai ZL, Yang Y, Wang JJ, Wu G (2013) Glycine metabolism in animals and humans: implications for nutrition and health. Amino Acids 45:463–477View ArticleGoogle Scholar
  71. Wistow GJ, Piatigorsky J (1988) Lens crystallins: the evolution and expression of proteins for a highly specialized tissue. Annu Rev Biochem 57:479–504View ArticleGoogle Scholar
  72. Wu G (2010) Functional amino acids in growth, reproduction, and health. Adv Nutr 1:31–37View ArticleGoogle Scholar
  73. Wu G (2013a) Amino acids: biochemistry and nutrition. CRC Press, Boca RatonView ArticleGoogle Scholar
  74. Wu G (2013b) Functional amino acids in nutrition and health. Amino Acids 45:407–411View ArticleGoogle Scholar
  75. Wu G (2014) Dietary requirements of synthesizable amino acids by animals: a paradigm shift in protein nutrition. J Anim Sci Biotechnol 5:34View ArticleGoogle Scholar
  76. Wu G, Bazer FW, Knabe DA, Ott T (1999) Amino acid composition of the fetal pig. J Nutr 129:1031–1038Google Scholar
  77. Wu G, Bazer FW, Johnson GA, Knabe DA, Burghardt RC, Spencer TE, Li XL, Wang JJ (2011a) Important roles for l-glutamine in swine nutrition and production. J Anim Sci 89:2017–2030View ArticleGoogle Scholar
  78. Wu G, Bazer FW, Burghardt RC, Johnson GA, Kim SW, Knabe DA, Li P, Li XL, McKnight JR, Satterfield MC, Spencer TE (2011b) Proline and hydroxyproline metabolism: implications for animal and human nutrition. Amino Acids 40:1053–1063View ArticleGoogle Scholar
  79. Wu G, Bazer FW, Dai ZL, Li DF, Wang JJ, Wu ZL (2014) Amino acid nutrition in animals: protein synthesis and beyond. Annu Rev Anim Biosci 2:387–417View ArticleGoogle Scholar
  80. Yang Z, Bielawski JP (2000) Statistical methods for detecting molecular adaptation. Trends Ecol Evol 15:496–503View ArticleGoogle Scholar
  81. Yüksel KÜ, Andersen TT, Apostol I, Fox JW, Paxton RJ, Strydom DJ (1995) The hydrolysis process and the quality of amino acid analysis: ABRF-94AAA collaborative trial. Techniques in Protein Chemistry 6:185View ArticleGoogle Scholar
  82. Zakeri M, Marammazi JG, Kochanian P, Savari A, Yavari V, Haghi M (2009) Effects of protein and lipid concentrations in broodstock diets on growth, spawning performance and egg quality of yellowfin sea bream (Acanthopagrus latus). Aquaculture 295:99–105View ArticleGoogle Scholar
  83. Zhao H, Magone MT, Schuck P (2011) The role of macromolecular crowding in the evolution of lens crystallins with high molecular refractive index. Physical Biol 8:046004View ArticleGoogle Scholar
  84. Zinalla V, Hall MN (2008) Linking nutrients to growth. Nature 454:287–288View ArticleGoogle Scholar
  85. Ziv T, Gattegno T, Chapovetsky V, Wolf H, Barnea E, Lubzens E, Admon A (2008) Comparative proteomics of the developing fish (zebrafish and gilthead seabream) oocytes. Comp Biochem Physiol D Genomics Proteomics 3:12–35View ArticleGoogle Scholar

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