1
OPTIMAL DIET PROFILE COMPOSITION FOR MAXIMUM SURVIVAL OF Octopus vulgaris PARALARVAE IN CULTURE CONDITIONS José A. Hormiga 1 , Antonio V. Sykes 3 , I. Frías 1 , Ali Skalli 2 , Eduardo Almansa 2 , Néstor V. Torres 1 1 Grupo de Tecnología Bioquímica. Departamento de Bioquímica y Biología Molecular. Facultad de Biología. Universidad de La Laguna. 38206, San Cristóbal de La Laguna. Tenerife. Islas Canarias. Spain. 2 Instituto Español de Oceanografía. Centro Oceanográfico de Canarias, Avd. Tres de Mayo, nº 73, Apdo. 1373. 38005, Sta. Cruz de Tenerife, Spain 3 CCMar - Universidade do Algarve. F.C.M.A. – Campus de Gambelas 8005, 139, Faro, PORTUGAL Parameter estimation using data fitting From the kinetic model representation, we estimate the parameter values from the experimental data time series (Vera et al, 2006, Hormiga et al. 2008). The fit problem is turned into an optimization problem using a objective a function to minimize the distances between the experimental data points and model results (D). To find the best fit is a global optimization problem and requires a special optimizer like the SGA or the modified GA. Simple and modified Genetic Algorithm Simple Genetic Algorithm (SGA) is an optimization method inspired in the natural selection process (Holland et al., 1975). The parameter space is explored by means crossover and mutation of the population elements, which are previously coded as binary strings. The initial population is generated by random exploration of the search space. The best individuals of the population are selected in the considered iteration using the value of the objective function (D). In the modified SGA, an additional fast climbing and stochastic algorithm is applied to the best solutions in each iteration. References: Work supported by research Grants from Spanish MICINN, Ref BIO2008-04500-C02-C2. JH was awarded with a research grant from IEO Octopus vulgaris represents a highly valued species of great commercial interest. However the industrial culture has proven unfeasible until now due to paralarvae, first stage growth phase, high mortality (Iglesias et al., 2007). One of the main causes of this problem is the diet since there is a lack of knowledge on the nutritional requirements of this species. Most likely, a nutritional imbalance in the protein and lipid profile of the artificial feeding protocol may be responsible for this high mortality (Villanueva and Norman, 2008). Therefore, it is necessary to establish an optimal nutritional regime based on the nutrient metabolism throughout the ontogenic process as well as the effects of diet composition. In order to deal with this evaluation we have considered the integration, in a mathematical model describing the species growth, of the available information on the nutritional requirements. The model is aiming to predict the time evolution of paralarve nutritional composition in terms of the protein and diet lipid fractions. Also it integrates paralarvae and adult nutrient composition data from closely related cephalopod species (i.e. cuttlefish, F) in order to dilucidate the best diet. By comparing the model predictions with the experimental results, we are able to present an optimal diet composition that should assure the maximal survival. TP, NL and PL contents have been obtained from: 1. O. vulgaris eggs and paralarvae: Quintana et al. (2005, 2006) 2. O. vulgaris juveniles: Navarro and Villanueva (2003) 3. Artemia (prey): Quintana et al. (2006) 4. Spider crab zoea (prey): Navarro and Villanueva (2000) 5. Cuttlefish eggs: Sykes et al. (2009) Center of Marine Sciences MATERIAL AND METHODS INTRODUCTION •AOAC (1990) Washington, USA •Folch et al. (1957) J. Biol. Chem. 226: 497-509. •Iglesias et al. (2007) Aquaculture 266: 1-15. •Navarro, J.C. and Villanueva, R. (2000) Aquaculture 183: 161–177. •Navarro, J.C. and Villanueva, R. (2003) Aquaculture 219: 613–631. •Olsen, R.E. et al. (1989) J. Exp. Mar. Biol. Ecol. 129: 189-197. •Quintana et al. (2006) VIII Simposium Internacional de Nutrición Acuícola (Sinaloa, México) •Quintana et al. (2005) X Congreso Nacional de Acuicultura (Valencia, Spain) •Sykes et al. (2009) Aquaculture Nutrition 15: 38-53 •Villanueva, R. and Norman, M.D. (2008) Oceanogr. Mar. Biol. Ann. Rev. 46: 105– 202 •Holland et al. (1975), University of Michigan Press, p. 211 •Vera et al (2006) , Understanding ane Exploiting Systems Biology,Eds. CM CajaMurcia •Voit E. O. (2000), . Computational analysis of biochemical systems. A practical guidefor biochemists and molecular biologists. Cambridge University Press, Cambridge. U. K. •Hormiga et al. (2008), Journal of Biotecnology, 137(1):50-58 (A) Diets for the broodstock and paralarvae, (B) Differents stages of Octopus Vulgaris growth, (C) Selected model variables (TP, NL & PL). (G) Model diagram: The dark arrows represent the variable transformations. Green arrows are the diet supply. Excrections are represented by the red arrows. (H) Data fitting for cuttlefish eggs variables Total Protein (TP), Neutral Lipids (NL), and Polar Lipids (PL) Model development The objective is to construct a dynamic phenomenologic model for the variables TP, PL and NL. These variables represents 90% of the body mass at the egg, paralarvae and juveniles stages (B). Accordingly, a GMA model (E & G) describing the transformation between these variables and the interchange with the culture media was constructed. The high mortality in Octopus Vulgaris paralarvae impairs data adquisistion of the selected variables, so we use a similar specie (cuttlefish, F) to calibrate the model. The fluxes from the culture media to the organism (G), are equal to zero when both species are in the egg stage, but in the paralarvae phase of Octopus vulgaris are given by the composition of the feed. RESULTS Predictions on Octopus Vulgaris After the model calibration it’s possible to introduce the data from the specimen of interest. The initial variables values correspond to the yolk composition. The uptake paralarvae stage fluxes are the composition of the diet respect the mean time of feed. The GMA P-L formalism is a good tool to build phenomenologic models and simulate the behaviour of complex organism using only macroscopic data measures. Our model predicts that the industrial diet with the nearest composition to the optimal one is spider crab zoea. This result has been validated by some experimental data (Navarro and Villanueva (2003). It is thus suggested that any culture feeding material matching the optimal composition would produced better paralarvae survival rates. ∑∑ = 2 ˆ ) ( . . j i j i j i j i j i i j y x t x F O σ = = j p k g k j ij i jk X c dt dX 1 γ Cuttlefish eggs Common octopus (Octopus vulgaris) is one of the main candidates to the aquaculture diversification, but the culture of this specimen present significant difficulties, mainly related with a inadequate first stages diet. With the aim of analyse and predict optimal diet composition to ensure the maximal survival we have developed a model which integrates data from the different growth phases of Octopus Vulgaris, the main body composition on the first stages of similar species and the nutritional composition of the diet supplied in captivity. ABSTRACT Fish Crustacean Cephalopods Broodstock diet Paralarval prey Artemia Spider crab zoea Juvenils Paralarvae Egg Female with eggs Diets Octopus Development Total protein (TP) Total lipid (TL) Neutral lipid (NL) Polar lipid (PL) Folch et al. (1957) Olsen y Henderson (1989). AOAC (1985) Biochemical composition Data adquisition Olsen y Henderson (1989). (A) (B) (C) (G) (D) (E) (F) (D) Objective Function for fata fitting. This funtion calculates de quadratic distance between the experimental (y) and simulated values (x) at each time point (i). By using normalized data (y) and error (σ ), results are the total distance for each time point (i) and curve (j). (E) GMA equations, Xi are the variables, cij the elements of the stochometric matrix, γj the flux (j) rate constants and gjk the kinetic orders with the variable Xk and flux γj. Cephalopod Crustacean Fish TP 8.30% -7.80% -5.60% PL -29.20% -22.10% -30.50% NL -23.90% -17.60% -24.70% Cephalopod Crustacean Fish TP 5.10% 0.29% 3.40% PL -13.20% -8.50% -12.40% NL -3.90% -4.10% -3.10% Paralarvae diet: Artemia Paralarvae diet: Spider crab zoea (I.1) (I.2) Broodstock diet Broodstock diet Artemia Spider crab zoea TP -7.60% -19% PL -42.30% -8% NL 23.90% -12.70% Optimal diet relative to the common diets when the Broodstock are feeding with Crustacean (I.3) (I.1) Predicted Relative Composition of juveniles when paralarvae are feed with artemia for differents broodstock diets. (I.2) Predicted Relative Composition of juveniles when paralarvae are feed with spider crab zoea for differents broodstock diets. (I.3) Predicted Optimal diet deviation from the artemia and spider crab zoea composition when crustacean is the broodstock diet. CONCLUSIONS (H)

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OPTIMAL DIET PROFILE COMPOSITION FOR MAXIMUM SURVIVAL OF Octopus vulgaris PARALARVAE IN CULTURE CONDITIONS

José A. Hormiga1, Antonio V. Sykes3, I. Frías1, Ali Skalli2, Eduardo Almansa2, Néstor V. Torres1

1Grupo de Tecnología Bioquímica. Departamento de Bioquímica y Biología Molecular. Facultad de Biología. Universidad de La Laguna. 38206, San Cristóbal de La Laguna. Tenerife. Islas Canarias. Spain.

2Instituto Español de Oceanografía. Centro Oceanográfico de Canarias, Avd. Tres de Mayo, nº 73, Apdo. 1373. 38005, Sta. Cruz de Tenerife, Spain3CCMar - Universidade do Algarve. F.C.M.A. – Campus de Gambelas 8005, 139, Faro, PORTUGAL

Parameter estimation using data fittingFrom the kinetic model representation, we estimate the parametervalues from the experimental data time series (Vera et al, 2006,Hormiga et al. 2008). The fit problem is turned into an optimizationproblem using a objective a function to minimize the distancesbetween the experimental data points and model results (D). Tofind the best fit is a global optimization problem and requires aspecial optimizer like the SGA or the modified GA.

Simple and modified Genetic AlgorithmSimple Genetic Algorithm (SGA) is an optimization method inspired in the natural selectionprocess (Holland et al., 1975). The parameter space is explored by means crossover andmutation of the population elements, which are previously coded as binary strings. The initialpopulation is generated by random exploration of the search space. The best individuals of thepopulation are selected in the considered iteration using the value of the objective function (D).In the modified SGA, an additional fast climbing and stochastic algorithm is applied to the bestsolutions in each iteration.

References:

Work supported by research Grants from Spanish MICINN, Ref BIO2008-04500-C02-C2. JH was awarded with a research grant from IEO

Octopus vulgaris represents a highly valued species of great commercial interest. However theindustrial culture has proven unfeasible until now due to paralarvae, first stage growth phase,high mortality (Iglesias et al., 2007). One of the main causes of this problem is the diet sincethere is a lack of knowledge on the nutritional requirements of this species. Most likely, anutritional imbalance in the protein and lipid profile of the artificial feeding protocol may beresponsible for this high mortality (Villanueva and Norman, 2008). Therefore, it is necessary toestablish an optimal nutritional regime based on the nutrient metabolism throughout theontogenic process as well as the effects of diet composition. In order to deal with thisevaluation we have considered the integration, in a mathematical model describing the speciesgrowth, of the available information on the nutritional requirements.The model is aiming to predict the time evolution of paralarve nutritional composition in termsof the protein and diet lipid fractions. Also it integrates paralarvae and adult nutrientcomposition data from closely related cephalopod species (i.e. cuttlefish, F) in order todilucidate the best diet. By comparing the model predictions with the experimental results, weare able to present an optimal diet composition that should assure the maximal survival.

TP, NL and PL contents have been obtained from:1. O. vulgaris eggs and paralarvae: Quintana et al. (2005, 2006)

2. O. vulgaris juveniles: Navarro and Villanueva (2003)

3. Artemia (prey): Quintana et al. (2006)

4. Spider crab zoea (prey): Navarro and Villanueva (2000)

5. Cuttlefish eggs: Sykes et al. (2009)

Center of Marine Sciences

MATERIAL AND METHODS

INTRODUCTION

•AOAC (1990) Washington, USA•Folch et al. (1957) J. Biol. Chem. 226: 497-509.•Iglesias et al. (2007) Aquaculture 266: 1-15. •Navarro, J.C. and Villanueva, R. (2000) Aquaculture 183: 161–177.•Navarro, J.C. and Villanueva, R. (2003) Aquaculture 219: 613–631.•Olsen, R.E. et al. (1989) J. Exp. Mar. Biol. Ecol. 129: 189-197.•Quintana et al. (2006) VIII Simposium Internacional de Nutrición Acuícola (Sinaloa, México)•Quintana et al. (2005) X Congreso Nacional de Acuicultura (Valencia, Spain)•Sykes et al. (2009) Aquaculture Nutrition 15: 38-53•Villanueva, R. and Norman, M.D. (2008) Oceanogr. Mar. Biol. Ann. Rev. 46: 105–202

•Holland et al. (1975), University of Michigan Press, p. 211•Vera et al (2006) , Understanding ane Exploiting Systems Biology,Eds. CM CajaMurcia•Voit E. O. (2000), . Computational analysis of biochemical systems. A practical guidefor biochemists and molecular biologists. Cambridge University Press, Cambridge. U. K.•Hormiga et al. (2008), Journal of Biotecnology, 137(1):50-58

(A) Diets for the broodstock and paralarvae, (B) Differents stages of Octopus Vulgaris growth, (C) Selected model variables (TP, NL & PL).

(G) Model diagram: The dark arrows represent the variabletransformations. Green arrows are the diet supply. Excrections arerepresented by the red arrows.

(H) Data fitting for cuttlefish eggs variables Total Protein (TP), Neutral Lipids(NL), and Polar Lipids (PL)

Model development

The objective is to construct a dynamic phenomenologic model for the variables TP, PL andNL. These variables represents 90% of the body mass at the egg, paralarvae and juvenilesstages (B). Accordingly, a GMA model (E & G) describing the transformation between thesevariables and the interchange with the culture media was constructed. The high mortality inOctopus Vulgaris paralarvae impairs data adquisistion of the selected variables, so we use asimilar specie (cuttlefish, F) to calibrate the model. The fluxes from the culture media to theorganism (G), are equal to zero when both species are in the egg stage, but in the paralarvaephase of Octopus vulgaris are given by the composition of the feed.

RESULTS

Predictions on Octopus VulgarisAfter the model calibration it’s possible tointroduce the data from the specimen ofinterest. The initial variables valuescorrespond to the yolk composition. Theuptake paralarvae stage fluxes are thecomposition of the diet respect the meantime of feed.

The GMA P-L formalism is a good tool to build phenomenologic models and simulate thebehaviour of complex organism using only macroscopic data measures.

Our model predicts that the industrial diet with the nearest composition to the optimal one isspider crab zoea. This result has been validated by some experimental data (Navarro andVillanueva (2003). It is thus suggested that any culture feeding material matching the optimalcomposition would produced better paralarvae survival rates.

∑ ∑

−=

2

ˆ)(.. j

ij

i

ji

ji

ji

ij yxtxFO

σ

∑ ∏=

⋅⋅=j

p

k

gkjij

i jkXcdt

dX1

γ

Cuttlefish eggs

Common octopus (Octopus vulgaris) is one of the main candidates to the aquaculturediversification, but the culture of this specimen present significant difficulties, mainly relatedwith a inadequate first stages diet. With the aim of analyse and predict optimal dietcomposition to ensure the maximal survival we have developed a model which integrates datafrom the different growth phases of Octopus Vulgaris, the main body composition on the firststages of similar species and the nutritional composition of the diet supplied in captivity.

ABSTRACT

• Fish

• Crustacean

• Cephalopods

Broodstock diet Paralarval prey

Artemia Spider crab zoea

JuvenilsParalarvae

Egg

Female with eggs

Diets

Octopus Development

Total protein (TP) Total lipid (TL)

Neutral lipid (NL)

Polar lipid (PL)Folch et al. (1957)

Olsen y Henderson (1989).AOAC (1985)

Biochemical compositionData adquisition

Olsen y Henderson (1989).

(A)

(B)

(C)

(G)

(D)

(E)

(F)

(D) Objective Function for fata fitting. This funtion calculates de quadratic distance between the experimental (y) and simulated values (x) at each time point (i). Byusing normalized data (y) and error (σ ), results are the total distance for each time point (i) and curve (j). (E) GMA equations, Xi are the variables, cij the elementsof the stochometric matrix, γj the flux (j) rate constants and gjk the kinetic orders with the variable Xk and flux γj.

Cephalopod Crustacean Fish

TP 8.30% -7.80% -5.60%

PL -29.20% -22.10% -30.50%

NL -23.90% -17.60% -24.70%

Cephalopod Crustacean Fish

TP 5.10% 0.29% 3.40%

PL -13.20% -8.50% -12.40%

NL -3.90% -4.10% -3.10%

Paralarvae diet: Artemia

Paralarvae diet: Spider crab zoea

(I.1)

(I.2)

Broodstock diet

Broodstock diet

Artemia Spider crab zoea

TP -7.60% -19%

PL -42.30% -8%

NL 23.90% -12.70%

Optimal diet relative to the common diets when the Broodstock are feeding with Crustacean

(I.3)(I.1) Predicted Relative Composition of juveniles when paralarvae arefeed with artemia for differents broodstock diets. (I.2) PredictedRelative Composition of juveniles when paralarvae are feed with spidercrab zoea for differents broodstock diets. (I.3) Predicted Optimal dietdeviation from the artemia and spider crab zoea composition whencrustacean is the broodstock diet.

CONCLUSIONS

(H)